Science, Faculty of
Zoology, Department of
DSpace
UBCV
Morris, Carolyn
Doctor of Philosophy - PhD
University of British Columbia
The ecological roles of dissolved organic carbon (DOC) in aquatic ecosystems are widespread although not yet fully understood, but DOC is likely to impact physiological processes in fish. Generally, DOC is supportive to ionoregulation in freshwater fish, especially in acidic or metal contaminated waters, although the exact protective mechanisms and the influence of water chemistry remain unknown. DOCs can be characterized by optical and chemical indices but the effect of pH and their inter-relationships are not well understood. I showed that the indices used to characterize DOC should consider pH and be interpreted carefully as some changes reflect alterations in conformation (i.e. spatial arrangement of the molecule) while others reflect changes in composition (i.e. chemical makeup of the molecule) resulting from proton binding. I also investigated the independent and interactive effects of DOC and pH, major ion concentrations (Na⁺, Ca²⁺) and/or a potential metal pollutant (copper, Cu) on fish. To explore the physiological effects of these environmentally relevant DOC-water quality interactions, fish native to specific habitats with different ionoregulatory strategies were utilized: rainbow trout, Pacific sanddab and rock sole, and the Amazonian dwarf cichlid. There were independent effects of major ions (Na⁺ and Ca²⁺), and Cu as well as interactive effects with DOCs which were altered by a change in pH. Generally, DOC was supportive to ionoregulation against physiological disturbances caused by ambient pH, major ions or copper. The pH-dependent physiological responses to DOC may be due to conformation changes in DOC such as condensation or the titration of the negative net charge on both DOC and the gill leading to more interaction. Natural DOC sources spanning a wide variety of characteristics, together with model compounds of known chemistry representing key chemical moieties of natural DOCs, were used. I demonstrated that specific chemical groups of the DOC molecules (e.g. carboxylic rings, aliphatic chains, and amino acids (i.e. peptides)) likely play a role in the physiological responses to natural DOCs. This thesis highlights that the variability in DOC structure and function is reflected in the physiochemistry of the DOC and in the physiological response of fishes, both of which are pH-dependent.
The independent and interactive effects of dissolved organic carbon (DOC), major salt ions (Na+, Ca2+) or Cu and pH on osmoregulatory processes of the fish gill by Carolyn Morris BSc, Memorial University of Newfoundland, 2012 MSc, McMaster University, 2020 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Zoology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2025 © Carolyn Morris, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: The independent and interactive effects of dissolved organic carbon (DOC), major salt ions (Na+, Ca2+) or Cu and pH on osmoregulatory processes of the fish gill Submitted by Carolyn Morris in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Zoology Examining Committee: Chris Wood, Adjunct Professor, Zoology, UBC Supervisor Colin Brauner, Professor, Zoology, UBC Co-supervisor Ora Johannsson, Adjunct Professor, Zoology, UBC Supervisory Committee Member Philip Matthews, Associate professor, Department of Zoology, UBC University Examiner Suzie Currie, Vice-Principal and Associate Vice-President, Research and Innovation, UBC University Examiner Claude Fortin, Professor, Centre eau terre environnement, Institut national de la recherche scientifique, External Examiner Additional Supervisory Committee Members: Patricia Schulte, Professor, Zoology, UBC Supervisory Committee Member iii Abstract The ecological roles of dissolved organic carbon (DOC) in aquatic ecosystems are widespread although not yet fully understood, but DOC is likely to impact physiological processes in fish. Generally, DOC is supportive to ionoregulation in freshwater fish, especially in acidic or metal contaminated waters, although the exact protective mechanisms and the influence of water chemistry remain unknown. DOCs can be characterized by optical and chemical indices but the effect of pH and their inter-relationships are not well understood. I showed that the indices used to characterize DOC should consider pH and be interpreted carefully as some changes reflect alterations in conformation (i.e. spatial arrangement of the molecule) while others reflect changes in composition (i.e. chemical makeup of the molecule) resulting from proton binding. I also investigated the independent and interactive effects of DOC and pH, major ion concentrations (Na+, Ca2+) and/or a potential metal pollutant (copper, Cu) on fish. To explore the physiological effects of these environmentally relevant DOC-water quality interactions, fish native to specific habitats with different ionoregulatory strategies were utilized: rainbow trout, Pacific sanddab and rock sole, and the Amazonian dwarf cichlid. There were independent effects of major ions (Na+ and Ca2+), and Cu as well as interactive effects with DOCs which were altered by a change in pH. Generally, DOC was supportive to ionoregulation against physiological disturbances caused by ambient pH, major ions or copper. The pH-dependent physiological responses to DOC may be due to conformation changes in DOC such as condensation or the titration of the negative net charge on both DOC and the gill leading to more interaction. Natural DOC sources spanning a wide variety of characteristics, together with model compounds of known chemistry representing key chemical moieties of natural DOCs, were used. I demonstrated that specific chemical groups of the DOC molecules (e.g. carboxylic rings, iv aliphatic chains, and amino acids (i.e. peptides)) likely play a role in the physiological responses to natural DOCs. This thesis highlights that the variability in DOC structure and function is reflected in the physiochemistry of the DOC and in the physiological response of fishes, both of which are pH-dependent. v Lay Summary Dissolved organic carbon (DOC) is a term describing naturally occurring, complex, highly variable compounds that are the products of the breakdown of organic matter in soil and water. DOCs play large roles in aquatic ecosystems as they influence light penetration and temperature in the water, metabolism in aquatic organisms, and bioavailability of harmful contaminants. DOCs have been shown to have beneficial effects on fish physiology including osmoregulation (salt and water balance) and they protect against metal toxicity, particularly when the water is acidic. However, how DOCs provide these beneficial and protective effects and the influence of other water chemistry parameters (e.g. pH, ion concentration, contaminants) is largely unknown. This thesis demonstrated that there are both independent and interactive effects of DOCs, salt ions (Na+, Ca2+), pH, and copper on osmoregulation in freshwater and marine fish and that these pH-dependent effects are likely due to specific chemical groups of the DOC molecules. vi Preface Chapter 1 is a General Introduction that provides an overview of background information, identifies objectives, provides an overall hypothesis of the thesis, and outlines brief summaries of research in the subsequent Chapters. With the exception of Chapter 5, Chapters 2-9 are mildly altered versions of manuscripts published in peer-reviewed journals. Throughout these research Chapters and Appendices please note that the pronoun “we” is used within the original manuscripts. Although I led these investigations, all authors contributed and take responsibility for the contents therein. However, the General Introduction (Chapter 1) and the General Discussion (Chapter 10) uses the pronoun “I” as I take sole responsibility for the points presented. Chapter 2 is a review paper that was written at the start of my doctoral studies when the covid pandemic prevented work in the lab. Its goal was to provide a background and framework for thesis research on DOC, much of which would be done in the Brazilian Amazon. However, covid forced me to pivot so as to work mainly in Canada on Canadian DOC, with only a modest amount of later research in Brazil. The paper was published as: Morris C, Val AL, Brauner CJ, and Wood CM (2021). The physiology of fish in acidic waters rich in dissolved organic carbon, with specific reference to the Amazon basin: Ionoregulation, acid–base regulation, ammonia excretion, and metal toxicity. Journal of Experimental Zoology Part A: Ecological and Integrative Physiology, 335(9-10), 843-863. DOI: 10.1002/jez.2468. I performed the literature search and wrote the first draft of the manuscript which was edited by Dr. Wood and revised by all authors. vii Chapter 3 has been published as: Morris C, Zulian S, Brauner CJ, Wood CM and Smith DS (2024b). A critical assessment of physicochemical indices used to characterize natural dissolved organic carbon (DOC), their interrelationships, and the effects of pH. Environmental Chemistry. 21, DOI:10.1071/EN24021. This project was jointly conceived by myself and Dr. Wood. I performed all experiments with the help of Samantha Zulian under the supervision of Dr. Wood and Dr. Smith respectively. Dr. Brauner provided advice. I wrote the first draft of the paper which was edited by Dr. Wood and revised by all authors. Chapter 4 has been published as: Morris C, Zulian S, Smith DS, Brauner CJ, and Wood CM (2024c). Using physicochemical properties to predict the impact of natural dissolved organic carbon on transepithelial potential in the freshwater rainbow trout (Oncorhynchus mykiss) at neutral and acidic pH. Fish Physiology and Biochemistry. 50(6):2619-2635. DOI:10.1007/s10695-024-01409-3. This project was jointly conceived by myself and Dr. Wood. I performed all experiments with the help of Samantha Zulian under the supervision of Dr. Wood and Dr. Smith respectively. Dr. Brauner provided advice. I wrote the first draft of the paper which was edited by Dr. Wood and revised by all authors. Chapter 5 is being prepared for submission: Morris C, Zulian S, Smith DS, Brauner CJ, and Wood CM (2025). The chemical characterization of model compounds (dissolved organic carbon analogues) and their effects on transepithelial potential in rainbow trout (Oncorhynchus mykiss) at circumneutral and low pH. This project was jointly conceived by myself and Dr. Wood. I performed all experiments with viii the help of Samantha Zulian under the supervision of Dr. Wood and Dr. Smith respectively. Dr. Brauner provided advice. I wrote the first draft of the paper which was edited by Dr. Wood and revised by Samantha Julian and Dr. Brauner. Dr. Smith’s input is currently delayed by illness. Chapter 6 has been published as: Morris C, Crémazy A, Brauner CJ and Wood CM (2025a). Interactions of major ions, pH, and dissolved organic carbon (DOC) on transepithelial potential (TEP) in rainbow trout: are there implications for the prediction of salt toxicity? Archives of Environmental Contamination and Toxicology 88, 303–323 DOI:0.1007/s00244-025-01125-w. This project was jointly conceived by myself and Dr. Wood. I performed all experiments, Dr. Crémazy did the speciation modeling and Dr. Brauner provided advice. I wrote the first draft of the manuscript, Dr. Wood edited it, and the text was revised by all authors. Chapter 7 has been published as: Morris C and Wood CM (2023): The effect of salinity and calcium on diffusive water flux, oxygen consumption, and nitrogenous waste excretion rates in Pacific sanddab (Citharichthys sordidus) and Rock sole (Lepidopsetta bilineata). Marine Biology, 170: 108. https://doi.org/10.1007/s00227-023-04245-w. This project was jointly conceived by Dr. Wood and myself. I performed all experiments under the supervision of Dr. Wood. I wrote the first draft of the manuscript and Dr. Wood edited it. Chapter 8 has been published as: Morris C, Martins C, Zulian S, Smith DS, Brauner CJ, and Wood CM (2024a). The effects of dissolved organic carbon and model compounds (DOC analogues) on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and gill transepithelial potential in Pacific sanddab (Citharichthys sordidus) at two salinities. Journal of Comparative Physiology B. ix 194. 805-825. DOI:10.1007/s00360-024-01580-2. This project was jointly conceived by Dr. Wood and myself. I performed all experiments under the supervision of Dr. Wood and with the help of Dr Martins and Samantha Zulian. Dr. Martins assisted with the physiological experiments and Samantha Zulian assisted with the analytical chemistry under the supervision of Dr. Smith. Dr. Brauner provided advice. I wrote the first draft of the manuscript which was edited by Dr. Wood, and the text was revised by all authors. Chapter 9 has been published as: Morris C, Crémazy A, Mota da Silva J, Johannsson OE, Brauner CJ, Wood CM, Val, AL. (2025b): The acute osmoregulatory effects of copper on the dwarf cichlid (Apistogramma agassizii) in Rio Negro blackwater and Rio Solimões whitewater: Flux rates of ions, nitrogenous wastes and water in Journal of Fish Biology. JFB-MS-25-0223. 1-17. https://doi.org/10.1111/jfb.70157. I and Dr. Wood jointly conceived the project. I performed all the experiments with the help of Dr. Crémazy. Dr. Crémazy did the copper speciation modeling. Jhonathan Mota da Silva assisted in the radioisotope counting of samples. Dr. Johannsson, Dr. Brauner and Dr. Val provided advice. I wrote the first draft of the manuscript, Dr. Wood edited it, and the text was revised by all authors. Chapter 10 is the General Discussion and Conclusions. This chapter summarizes the major findings of the work, addresses the original objectives and suggests future research questions. The Appendices contain Supporting Information for each of the chapters as published in the journal papers. All experiments performed for this thesis followed the guidelines of the Canada Council for Animal Care, under joint approval of the animal care committees of the University of British x Columbia (AUPs A18-0271 and A22-0195) and the Bamfield Marine Science Centre (AUP RS-21(19)-01, RS-22-08). Additionally, the experiments of Chapter 9 were approved by the Ethics Committee on Animal Experiments of the National Institute of Amazon Research (INPA) under registration number 004/2018, in conformity with the Brazilian Ethics Committee on Animal Care (CONCEA) guidelines (RN 61/2023). The research was also authorized by the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) (SISBio number: 29837-24). Generative artificial intelligence (GenAI) was not used for any aspects of the work presented in this thesis. xi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary……………………………………………………………………………………v Preface ........................................................................................................................................... vi Table of Contents ......................................................................................................................... xi List of Tables ............................................................................................................................ xxiv List of Figures ........................................................................................................................... xxvi List of Abbreviations ...............................................................................................................xxxv Acknowledgements ................................................................................................................ xxxix Chapter 1: General Introduction .................................................................................................1 1.1 Overview ......................................................................................................................... 1 1.2 Thesis objectives and chapter summaries ....................................................................... 7 1.2.1 Chapter 2: “The physiology of fish in acidic waters in fish dissolved organic carbon with specific reference to the Amazon basin: ionoregulation, acid-base regulation, ammonia excretion and metal toxicity”.. ................................................................................ 7 1.2.2 Chapter 3: “A critical assessment of physicochemical indices used to characterize natural dissolved organic carbon (DOC), and their inter-relationships and the effects of pH”…….. ................................................................................................................................ 8 1.2.3 Chapter 4: “Using physicochemical properties to predict the impact of natural dissolved organic carbon on transepithelial potential in freshwater rainbow trout (Oncorhynchus mykiss) at neutral and acidic pH” ................................................................. 8 xii 1.2.4 Chapter 5: “The chemical characterization of model compounds (dissolved organic carbon analogues) and their effects on transepithelial potential in rainbow trout (Oncorhynchus mykiss) at circumneutral and low pH.” ......................................................... 9 1.2.5 Chapter 6: “Interactions of major ions, pH, and dissolved organic carbon (DOC) on transepithelial potential (TEP) in rainbow trout: are there implications for the prediction of salt toxicity?” ................................................................................................................... 10 1.2.6 Chapter 7: “The effect of salinity and Ca2+ on the diffusive water flux, oxygen consumption, nitrogenous waste excretion rates of the gill in Pacific sanddab (Citharichthys sordidus) and rock sole (Lepidopsetta bilineata)”. .............................................................. 12 1.2.7 Chapter 8: “The effects of dissolved organic carbon and model compounds (DOC analogues) on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and gill transepithelial potential in Pacific sanddab (Citharichthys sordidus) at two salinities.”.............................................................................................................................. 12 1.2.8 Chapter 9: “The acute osmoregulatory effects of copper on the dwarf cichlid (Apistogramma agassizii) in Rio Negro blackwater and Rio Solimoes whitewater: Flux rates of ions, nitrogenous wastes and water”................................................................................. 13 Chapter 2: The physiology of fish in acidic waters rich in dissolved organic carbon with specific reference to the Amazon basin: Ionoregulation, acid-base regulation, ammonia excretion and metal toxicity. .......................................................................................................15 2.1 Summary ....................................................................................................................... 15 2.2 Introduction ................................................................................................................... 16 2.3 Physicochemical properties of DOC ............................................................................. 18 2.4 DOC as a general ecological driving factor in aquatic ecosystems .............................. 23 xiii 2.5 Chemistry of Rio Negro blackwater ............................................................................. 25 2.6 Active ion uptake and passive ion loss at circumneutral and acidic pHs ..................... 27 2.7 The protective and supportive effects of natural DOCs on ionoregulation .................. 33 2.8 Acid-base balance at circumneutral and acidic pHs ..................................................... 37 2.9 Electrical properties of the gill (TEP) at circumneutral and acidic pHs ....................... 40 2.10 Ammonia transport ....................................................................................................... 42 2.11 Amelioration of metal toxicity ...................................................................................... 46 2.12 Concluding remarks ...................................................................................................... 52 2.13 Chapter 2 – Tables ........................................................................................................ 55 2.14 Chapter 2 – Figures ....................................................................................................... 56 Chapter 3: A critical assessment of physicochemical indices used to characterize natural dissolved organic carbon (DOC), their inter-relationships, and the effects of pH. ...............61 3.1 Summary ....................................................................................................................... 61 3.2 Introduction ................................................................................................................... 62 3.3 Experimental methods .................................................................................................. 65 3.3.1 Experimental solutions.......................................................................................... 65 3.3.2 Optical characterization of DOCs ........................................................................ 68 3.3.3 Specific absorbance coefficient at 340 nm............................................................ 68 3.3.4 Fluorescence index ............................................................................................... 68 3.3.5 Molecular weight index......................................................................................... 69 3.3.6 Parallel factor analysis ......................................................................................... 69 3.3.7 Octanol-water partition coefficient....................................................................... 70 3.3.8 Size fractionation .................................................................................................. 70 xiv 3.3.9 Proton binding index and molecular charge ........................................................ 71 3.3.10 Statistical analysis ................................................................................................ 72 3.4 Results ........................................................................................................................... 73 3.4.1 Optical characterization ....................................................................................... 73 3.4.2 Proton binding index and molecular charge ........................................................ 75 3.4.3 Size fractionation .................................................................................................. 76 3.4.4 Correlations among the physicochemical characteristics of DOC related to pH………. .............................................................................................................................. 76 3.5 Discussion ..................................................................................................................... 78 3.5.1 Overview ............................................................................................................... 78 3.5.2 The physicochemical characteristics of DOC: ecological and physiological implications ........................................................................................................................... 81 3.6 Concluding remarks ...................................................................................................... 86 3.7 Chapter 3 – Tables ........................................................................................................ 88 3.8 Chapter 3 – Figures ....................................................................................................... 90 Chapter 4: Using physicochemical properties to predict the impact of natural dissolved organic carbon on transepithelial potential in the freshwater rainbow trout (Oncorhynchus mykiss) at neutral and acidic pH.................................................................................................95 4.1 Summary ....................................................................................................................... 95 4.2 Introduction ................................................................................................................... 96 4.3 Methods......................................................................................................................... 99 4.3.1 Experimental animals ........................................................................................... 99 4.3.2 Experimental solutions........................................................................................ 100 xv 4.3.3 Transepithelial potential measurements ............................................................. 101 4.3.4 Statistical analysis .............................................................................................. 103 4.4 Results ......................................................................................................................... 103 4.4.1 Characterization of the five natural DOCs at two pHs using physicochemical indices…… .......................................................................................................................... 103 4.4.2 The effects of DOC on transepithelial potential in trout .................................... 105 4.4.3 The relationships between TEP and the physicochemical characteristics of DOC……. ............................................................................................................................ 106 4.5 Discussion ................................................................................................................... 107 4.5.1 Overview ............................................................................................................. 107 4.5.2 DOCs sharing physicochemical characteristics show similar trends in TEP response…. .......................................................................................................................... 108 4.6 Concluding remarks .................................................................................................... 113 4.7 Chapter 4 – Figures ..................................................................................................... 116 Chapter 5: Model compounds as analogues for dissolved organic matter: physicochemical characterization and their effects on the electrical properties of the rainbow trout gill at circumneutral and low pH. .......................................................................................................126 5.1 Summary ..................................................................................................................... 126 5.2 Introduction ................................................................................................................. 127 5.3 Methods....................................................................................................................... 130 5.3.1 Experimental animals ......................................................................................... 130 5.3.2 Chemical moiety groups ..................................................................................... 130 5.3.3 Experimental solutions........................................................................................ 131 xvi 5.3.4 Optical characterization of the model compounds ............................................. 132 5.3.5 Octanol-water partition coefficient (log Kow) ................................................... 132 5.3.6 Molecular charge ................................................................................................ 134 5.3.7 Transepithelial potential measurements ............................................................. 134 5.3.8 Statistical analysis .............................................................................................. 136 5.4 Results ......................................................................................................................... 136 5.4.1 The effect of model compounds on transepithelial potential .............................. 136 5.4.2 The relationship between lipophilicity and charge of the model compounds and TEP response at pH 7 and pH 4. ........................................................................................ 138 5.5 Discussion ................................................................................................................... 139 5.5.1 Overview ............................................................................................................. 139 5.5.2 Possible key chemical moieties of natural DOCs influencing TEP, informed by model compounds................................................................................................................ 140 5.5.3 Are the chemical indices (based on titration properties) related to TEP responses?…. ...................................................................................................................... 144 5.5.4 Comparison of TEP responses to model compounds and natural DOCS and their shared chemical characteristics ......................................................................................... 146 5.6 Concluding remarks .................................................................................................... 147 5.7 Chapter 5 – Figures ..................................................................................................... 149 Chapter 6: Interactions of major ions, pH and dissolved organic carbon (DOC) on transepithelial potential (TEP) in rainbow trout: are there implications for prediction of salt toxicity? ................................................................................................................................155 6.1 Summary ..................................................................................................................... 155 xvii 6.2 Introduction ................................................................................................................. 156 6.3 Methods....................................................................................................................... 161 6.3.1 Experimental animals ......................................................................................... 161 6.3.2 Experimental solutions........................................................................................ 161 6.3.3 Transepithelial potential measurements ............................................................. 163 6.3.4 Speciation modeling ............................................................................................ 165 6.3.5 Statistical analyses .............................................................................................. 166 6.4 Results ......................................................................................................................... 168 6.4.1 The effect of pH and DOC with no added salt on TEP ....................................... 168 6.4.2 The effects of NaCl and CaCl2 on absolute TEP and ΔTEP at pH 7 and pH 4 .. 168 6.4.3 The effects of NaCl in the presence and absence of added DOC on absolute TEP and ΔTEP at pH 7 and pH 4 ............................................................................................... 170 6.4.4 The effects of CaCl2 in the presence and absence of added DOC on absolute TEP and ΔTEP at pH 7 and pH 4 ............................................................................................... 171 6.4.5 The effects of DOC on absolute TEP and ΔTEP at the LC50 salt value .............. 172 6.4.6 Cation speciation modeling ................................................................................ 173 6.5 Discussion ................................................................................................................... 174 6.5.1 Overview ............................................................................................................. 174 6.5.2 The independent effects of pH Na+, or Ca2+, or DOC on TEP ........................... 175 6.5.3 Interactive effects of pH Na+, or Ca2, and DOC................................................. 178 6.5.4 Predicating toxicity ............................................................................................. 179 6.6 Concluding remarks .................................................................................................... 182 6.7 Chapter 6 – Tables ...................................................................................................... 184 xviii 6.8 Chapter 6 – Figures ..................................................................................................... 186 Chapter 7: The effect of salinity and calcium on diffusive water flux, oxygen consumption and nitrogenous waste excretion rates in Pacific sanddab (Citharichthys sordidus) and Rock sole (Lepidopsetta bilineata). ......................................................................................................199 7.1 Summary ..................................................................................................................... 199 7.2 Introduction ................................................................................................................. 200 7.3 Methods....................................................................................................................... 205 7.3.1 Animals ............................................................................................................... 205 7.3.2 Experimental series ............................................................................................. 206 7.3.3 Experimental solutions........................................................................................ 206 7.3.4 Diffusive water flux ............................................................................................. 207 7.3.5 Oxygen consumption ........................................................................................... 207 7.3.6 Ammonia and urea-N excretion .......................................................................... 208 7.3.7 Analytical procedures and calculations.............................................................. 208 7.3.8 Statistical analyses .............................................................................................. 210 7.4 Results ......................................................................................................................... 211 7.4.1 Allometric scaling exponents .............................................................................. 211 7.4.2 The effect of salinity on diffusive water flux rates .............................................. 212 7.4.3 The effect of salinity on ṀO2 .............................................................................. 213 7.4.4 The effect of salinity on ammonia and urea-N excretion rates ........................... 213 7.4.5 The effect of salinity on the nitrogen quotient .................................................... 214 7.4.6 The effect of Ca2+ during a salinity challenge in Rock sole ................................ 214 7.5 Discussion ................................................................................................................... 216 xix 7.5.1 Overview ............................................................................................................. 216 7.5.2 Scaling exponents of diffusive water flux, ṀO2 and ammonia excretion rate .... 217 7.5.3 Diffusive water flux and oxygen consumption rates can be independently regulated in response to a salinity challenge ..................................................................... 218 7.5.4 Ammonia excretion rate is a function of salinity ................................................ 219 7.5.5 [Ca2+] plays a role in diffusive water flux and ammonia excretion rates in Rock sole………. .......................................................................................................................... 221 7.6 Concluding remarks .................................................................................................... 223 7.7 Chapter 7 – Tables ...................................................................................................... 225 7.8 Chapter 7 – Figures ..................................................................................................... 226 Chapter 8: The effects of dissolved organic carbon and model compounds (DOC analogues) on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and gill transepithelial potential in Pacific sanddab (Citharichthys sordidus) at two salinities. .......232 8.1 Summary ..................................................................................................................... 232 8.2 Introduction ................................................................................................................. 233 8.3 Methods....................................................................................................................... 237 8.3.1 Animals ............................................................................................................... 237 8.3.2 Experimental series ............................................................................................. 238 8.3.3 Experimental solutions........................................................................................ 239 8.3.4 Optical characterization of experimental solutions ............................................ 240 8.3.5 Diffusive water flux ............................................................................................. 243 8.3.6 Oxygen consumption rate measurements............................................................ 244 8.3.7 Ammonia and urea-N excretion rate measurements ........................................... 244 xx 8.3.8 Transepithelial potential measurements ............................................................. 245 8.3.9 Analytical procedures and calculations.............................................................. 246 8.3.10 Statistical analyses .............................................................................................. 248 8.4 Results ......................................................................................................................... 249 8.4.1 Measured DOC concentrations and the optical characterization of natural DOCs and model compounds at two salinities .............................................................................. 249 8.4.2 Allometric scaling coefficients ............................................................................ 251 8.4.3 Control values as a function of salinity .............................................................. 251 8.4.4 The effects of DOCs and model compounds on diffusive water flux rates at two salinities…........................................................................................................................... 252 8.4.5 The effects of DOCs and model compounds on ṀO2 at two salinities ............... 252 8.4.6 The effects of DOCs and model compounds on ammonia and urea-N excretion rates at two different salinities ............................................................................................ 252 8.4.7 The effects of DOCs and model compounds on nitrogen quotients at two different salinities…........................................................................................................................... 253 8.4.8 The effects of DOCs and model compounds on TEPs at two different salinities 254 8.5 Discussion ................................................................................................................... 254 8.5.1 Overview ............................................................................................................. 254 8.5.2 Optical indices of natural DOCs are a function of salinity ................................ 256 8.5.3 Diffusive water flux and ammonia excretion can be uncoupled from oxygen consumption, and independently regulated across salinities, in the presence and absence of DOC……. ............................................................................................................................ 257 xxi 8.5.4 The shared physiological responses between natural DOCs and model compounds as a function of salinity are likely due to key chemical moieties. .................... 259 8.6 Concluding Remarks ................................................................................................... 261 8.7 Chapter 8 – Tables ...................................................................................................... 262 8.8 Chapter 8 – Figures ..................................................................................................... 265 Chapter 9: The acute osmoregulatory effects of low pH and Cu, alone and in combination, on the dwarf cichlid (Apistogramma agassizii) in Rio Negro blackwater and Rio Solimões whitewater: flux rates of ions, nitrogenous wastes, and water ..............................................273 9.1 Summary ..................................................................................................................... 273 9.2 Introduction ................................................................................................................. 274 9.3 Methods....................................................................................................................... 278 9.3.1 Animals ............................................................................................................... 279 9.3.2 Exposure waters .................................................................................................. 279 9.4 Diffusive water flux measurements ............................................................................. 281 9.5 Net ion flux and ammonia and urea-N excretion measurements ................................ 282 9.6 Paracellular permeability and drinking rate .............................................................. 282 9.7 Calculations ................................................................................................................ 283 9.7.1 Cu speciation modeling....................................................................................... 286 9.7.2 Statistical analyses .............................................................................................. 286 9.8 Results ......................................................................................................................... 287 9.8.1 Water Chemistry ................................................................................................. 287 9.8.2 Cu speciation ...................................................................................................... 288 9.8.3 The effects of pH and Cu on net ion flux rates in the three water types ............. 289 xxii 9.8.4 The effects of pH and Cu on nitrogenous waste excretion rates in the three water types………. ......................................................................................................................... 291 9.8.5 The effects of pH and Cu on the water transport pathways and drinking rate in the three water types ................................................................................................................. 292 9.9 Discussion ................................................................................................................... 294 9.9.1 Overview ............................................................................................................. 294 9.9.2 Water chemistry greatly affects the speciation of Cu ......................................... 295 9.9.3 Rio Negro DOC provides protection against ionoregulatory disturbances caused by low pH or Cu. ................................................................................................................. 296 9.9.4 Cu decreases water transport through tight junctions and transcellularly as a function of water chemistry ................................................................................................. 297 9.9.5 Cu tends to inhibit nitrogenous waste excretion rates ........................................ 299 9.10 Concluding remarks .................................................................................................... 301 9.11 Chapter 9 – Tables ...................................................................................................... 303 9.12 Chapter 9 – Figures ..................................................................................................... 306 Chapter 10: General Discussion and Conclusions ..................................................................312 10.1 Physicochemical characterization indices of DOCs and acute physiological responses to DOCs are pH-dependent. .................................................................................................... 312 10.2 The interactive effects of water quality parameters (pH, major ions, or copper) and DOC on ionoregulatory function ............................................................................................ 315 10.3 Identifying specific physicochemical moieties of DOC that are responsible for the altered osmoregulatory function using natural DOCs and model compounds. ...................... 317 xxiii 10.4 DOCs influence osmoregulatory processes at the gills in fish with different ionoregulatory strategies. ........................................................................................................ 319 10.5 Environmental and regulatory considerations ............................................................ 321 10.6 Perspectives for future directions................................................................................ 323 10.7 Chapter 10 – Figures……………………………………………………………….. 326 Bibliography…………………………………………………………………………………...330 Appendices ..................................................................................................................................367 Appendix A Supplementary material – Chapter 3 .................................................................. 367 Appendix B Supplementary material – Chapter 4 .................................................................. 372 Appendix C Supplementary material – Chapter 5 .................................................................. 377 Appendix D Supplementary material – Chapter 6 .................................................................. 389 Appendix E Supplementary material – Chapter 7 .................................................................. 397 Appendix F Supplementary material – Chapter 8................................................................... 399 Appendix G Supplementary material – Chapter 9 .................................................................. 400 xxiv List of Tables Table 2.1. General water chemistry ranges for acidic, DOC‐rich black waters of the Rio Negro watershed, based on the experience of the authors and data of Duarte (2012) ............................. 55 Table 3.1. The specific absorbance coefficient at 340 nm (SAC340), fluorescence index (FI), molecular weight index (MWI) and octanol-water partition coefficient (log Kow) in Lake Ontario (LO), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at ~10 mg C L-1 at pH 7 and pH 4.. .................................................................................................. 88 Table 3.2. Proton binding index (PBI) and molecular charge (mol charge mg-1 C-1) at pH 7 and pH 4 for Lake Ontario (LO), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS). ................................................................................................................................. 88 Table 3.3. Percent change in DOC concentration between 0.45-m – 100-kDa, 0.45 m – 10-kDa and 0.45-m – 3-kDa of Lake Ontario, Luther Marsh, Preston Flats, Ancient Woods Pond, and Ancient Woods Swamp. ......................................................................................................... 89 Table 6.1. The Michaelis-Menten constants and R2 values for NaCl at pH 7 and pH 4 with and without added DOC. ................................................................................................................... 184 Table 6.2. The Michaelis-Menten constants and R2 values with modified substrate inhibition for CaCl2 at pH 7 and pH 4 with and without DOC ......................................................................... 185 Table 7.1. Allometric mass scaling for diffusive water flux, oxygen consumption, ammonia and urea-N excretion rates for Rock sole (Lepidopsetta bilineata) and Pacific sanddab (Citharichthys sordidus) ..................................................................................................................................... 225 xxv Table 8.1. Characterization of experimental water samples in terms of pH, DOC concentration, specific absorbance coefficient at 340 nm (SAC340), fluorescence index (FI) and molecular weight index (MWI) in exposures at two different salinities, 30 ppt and 7.5 ppt. ..................... 262 Table 8.2. Allometric mass scaling for diffusive water flux, oxygen consumption, ammonia and urea-N excretion rates for Pacific sanddab (Citharichthys sordidus) at 30 ppt and 7.5 ppt ....... 263 Table 8.3. The mean values ± SEM of the two control groups at each salinity combined (Series 1 and 3 at 30 ppt versus Series 2 and 4 at 7.5 ppt).. ....................................................................... 264 Table 9.1. Water characterization summary of INPA (control), Rio Negro (RN) and Rio Solimoes (RS) waters. ................................................................................................................. 303 Table 9.2. Relative percentages of the main chemical forms of Cu in the experimental waters, as calculated by WHAM VII. .......................................................................................................... 304 Table 9.3. %Urea-N Excretion (mean ± SEM) at pH 7 and 4 with and without the addition of nominally 200 µg L-1 of Cu in INPA (control), Rio Negro (RN) and Rio Solimões (RS) water....................................................................................................................................................... 305 xxvi List of Figures Figure 2.1. The typical structure of (a) humic and (b) fulvic acids which typically comprise a substantial proportion of allochthonous DOC molecules ............................................................. 56 Figure 2.2. Models of transport processes in ionocytes of the freshwater fish gill. (a) proposed model of ion uptake pathways in the freshwater fish gill epithelium noting the effects of DOC, Ca2+, and low pH on ion transporters (b) proposed model of ammonia transport through the freshwater gill epithelium, noting the effects of DOC at low pH ................................................. 57 Figure 2.3. The interactive effects of dissolved organic carbon (DOC), pH, and Ca2+ on gill transepithelial potential (TEP) in freshwater fish. ........................................................................ 58 Figure 2.4. A conceptual model of the interactive effects of DOC, low pH, and water Ca2+ and Na+ concentrations with respect to ionoregulation and metal toxicity at the gills of freshwater fish................................................................................................................................................. 59 Figure 2.5. The relationship between the affinity (Km values from Gonzalez et al. 2002) for Na+ uptake and the toxicity of Cu (96‐h LC50 values from Duarte et al. 2009) in five species of Rio Negro fish...................................................................................................................................... 60 Figure 3.1. Relative % fluorophores of (A) humic acid-like (B) fulvic acid-like and (C) protein-like components for Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM) Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) ............................................................................... 90 Figure 3.2. Pearson r correlation matrices demonstrating the correlations between optical characterization indices, specific absorbance coefficient 340 (SAC340), fluorescence index (FI), molecular weight index (MWI), log Kow, molecular charge, proton binding index (PBI), % humic acid-like, % fulvic acid-like, % protein like, % < 100-kDa, % < 10-kDa, % < 3-kDa at (A) pH 7 or (B) pH 4 separately and (C) pH 7 and pH 4 combined.. ........................................... 92 xxvii Figure 3.3. Simple linear regressions of relationships between indices at pH 7, and at pH 4 separately, as well as with the pH 7 and pH 4 data combined. ..................................................... 94 Figure 4.1. The effect of natural DOC sources on absolute transepithelial potential (TEP) (A) Lake Ontario (LO), (B) Preston Flats (PF), (C) Luther Marsh (LM), (D) Ancient Woods Pond (AP) and (E) Ancient Woods Swamp (AS) at pH 7 and pH 4 .................................................... 116 Figure 4.2. The effect of natural DOC sources on delta transepithelial potential (ΔTEP) (A) Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM) Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at pH 7 and (B) Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM) Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at pH 4. ..................................... 117 Figure 4.3. Absolute TEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Specific absorbance coefficient, (C, D) Fluorescence index, (E, F) Molecular weight index, (G, H) log Kow and (I, J) absolute charge. ....................................................................................... 119 Figure 4.4. Absolute TEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Proton binding index, (C, D) relative % humic acid-like concentration, (E, F) relative % fulvic acid-like concentration (G, H) relative % protein-like concentration ......................................... 121 Figure 4.5. ΔTEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Specific absorbance coefficient, (C, D) Fluorescence index, (E, F) Molecular weight index, (G, H) log Kow and (I, J) absolute charge. .................................................................................................. 123 Figure 4.6. ΔTEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Proton binding index, (C, D) relative % humic acid-like concentration, (E, F) relative % fulvic acid-like concentration (G, H) relative % protein-like concentration) ...................................................... 125 Figure 5.1. Absolute TEP at pH 7 and pH 4 of model compounds in the key chemical moiety groups: Tannic and humic acid (A) Tannic acid (TA), (B) AldrichTM humic acid (AHA), xxviii Phenolic acids (C) Salicylic acid (SA), (D) Naphthionic acid (NA) and Surfactants (E) Sodium dodecyl sulfate, (F) Linear alkylbenzene sulfonate (LAS). ........................................................ 150 Figure 5.2. Absolute TEP at pH 7 and pH 4 of model compounds in the key chemical moiety groups: Carboxylic acids (A) Formic acid (FA), (B) Acetic acid and Fatty acids (C) Palmitic acid (PA), (D) Steric acid (StA), (E) Methyl palmitate, (F) Methyl stearate (MS) ............................ 151 Figure 5.3. Absolute TEP at pH 7 and pH 4 of model compounds in the key chemical moiety groups: Amino acids (A) Tryptophan (Tryp), Tyrosine (Tyr), -Lactalbumin (LAC) and Bovine serum albumin (BSA). ................................................................................................................ 152 Figure 5.4. Absolute TEP of model compounds regressed against (A) log Kow at pH 7 (B) log Kow at pH 4 (C) Charge at pH 7 (D) Charge at pH 4 ................................................................ 153 Figure 5.5. ΔTEP of model compounds regressed against (A) log Kow at pH 7 (B) log Kow at pH 4 (C) Charge at pH 7 (D) Charge at pH 4.. ........................................................................... 154 Figure 6.1. The effects of natural dissolved organic carbon (DOC) or model DOC compounds on baseline TEPs with 0% added salt at pH 7 and pH 4: (A) Luther Marsh (LM) DOC; (B) Lake Ontario (LO) DOC; (C) Tannic acid (TA); (D) Sodium dodecyl sulfate (SDS); (E) Bovine serum albumin (BSA)… ........................................................................................................................ 186 Figure 6.2. The effect of added (A) NaCl at pH 7 and pH 4 on absolute TEP: (B) NaCl at pH 7 and pH 4 on TEP; (C) CaCl2 at pH 7 and pH 4 on absolute TEP; (D) CaCl2 at pH 7 and pH 4 on TEP ........................................................................................................................................... 187 Figure 6.3. The interactive effects of NaCl and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 7: (A) Luther Marsh (LM) DOC on absolute TEP; (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E)Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on xxix absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP. .......................................................................................................................................... 189 Figure 6.4. The interactive effects of NaCl and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 4: (A) Luther Marsh (LM) DOC on absolute TEP; (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E) Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP. .......................................................................................................................................... 191 Figure 6.5. The interactive effects of CaCl2 and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 7: (A) Luther Marsh (LM) DOC on absolute TEP; ( (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E) Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP ........................................................................................................................................... 193 Figure 6.6. The interactive effects of CaCl2 and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 4: (A) Luther Marsh (LM) DOC on absolute TEP; (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E) Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP. .......................................................................................................................................... 195 xxx Figure 6.7. The absolute TEP response with and without added natural DOC or model DOC compounds at LC50 concentration of (A) NaCl at pH 7 (B) CaCl2 at pH 7 (C) NaCl at pH 4 (D) CaCl2 at pH 4............................................................................................................................... 196 Figure 6.8. The TEP response with and without added natural DOC or model DOC compounds at LC50 concentration of (A) NaCl at pH 7 (B) CaCl2 at pH 7 (C) NaCl at pH 4 (D) CaCl2 at pH 4............................................................................................................................... 197 Figure 6.9. The predicted toxicities of the various experimental solutions [Luther Marsh (LO), Lake Ontario (LO), Tannic acid (TA), Sodium dodecyl sulfate (SDS) or Bovine serum albumin (BSA)] relative to their appropriate reference solutions [NaCl or CaCl2 ] as assessed by differences in absolute TEP, TEP and the M-M constants, TEPmax and Km at pH 7 and pH 4...................................................................................................................................................... 198 Figure 7.1. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on diffusive water flux rate (ml kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata) and (B) Pacific sanddab (Citharichthys sordidus), N=6-7 The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and diffusive water flux rate (ml kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), and (D) Pacific sanddab (Citharichthys sordidus). .............................................................................................. 226 Figure 7.2. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on oxygen consumption rate (ṀO2) (µmol kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), and (B) Pacific sanddab (Citharichthys sordidus). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and oxygen consumption rate (ṀO2) (µmol kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), and (D) Pacific sanddab (Citharichthys sordidus)............................................................................. 227 Figure 7.3. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on ammonia-N excretion rate (µmol kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), and (B) Pacific sanddab (Citharichthys xxxi sordidus), (B). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and ammonia-N excretion rate (µmol kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), and (D) Pacific sanddab (Citharichthys sordidus) ............................................................................................... 228 Figure 7.4. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on urea-N excretion rate (µmol kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), and (B) Pacific sanddab (Citharichthys sordidus). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and urea-N excretion rate (µmol kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata) and (D) Pacific sanddab (Citharichthys sordidus) ............................................................................................................. 229 Figure 7.5. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on nitrogen quotient (NQ= ṀN/ ṀO2) on (A) Rock sole (Lepidopsetta bilineata) (B) Pacific sanddab (Citharichthys sordidus). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and nitrogen quotient (C) Rock sole (Lepidopsetta bilineata) and (D) Pacific sanddab (Citharichthys sordidus)..................................................................................................................................................... 230 Figure 7.6. The effect of [Ca2+] and salinity (31 ppt and 7.5 ppt) in the salinity-Ca2+ series on Rock sole (Lepidopsetta bilineata) on (A) Diffusive water flux rate (B) ṀO2, (C) ammonia excretion rate (D) urea-N excretion rate and (E) nitrogen quotient (NQ) .................................. 231 Figure 8.1. Fluorescence excitation-emission matrices for natural DOCs at 30 ppt, (A) - Lake Ontario, (B) - Luther Marsh and at 7.5 ppt, (C) - Lake Ontario, (D) - Luther Marsh and (E) the relative % fluorophores of humic acid-like, fulvic acid-like and protein-like components for Lake Ontario (LO), and Luther Marsh (LM) at 30 ppt and 7.5 ppt. .................................................... 265 Figure 8.2. The interactive effects on diffusive water flux rate (ml kg-1 h-1) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin) (C) 7.5 ppt and natural DOCs (Luther Marsh xxxii and Lake Ontario) and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin) of Pacific sanddab (Citharichthys sordidus).. ................................ 266 Figure 8.3. The interactive effects on O2 consumption rate (ṀO2) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), of Pacific sanddab (Citharichthys sordidus).................................................... 267 Figure 8.4. The interactive effects on ammonia excretion rate of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), of Pacific sanddab (Citharichthys sordidus).................................................... 268 Figure 8.5. The interactive effects on urea-N excretion rate of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), of Pacific sanddab (Citharichthys sordidus).................................................... 269 Figure 8.6. The interactive effects on the nitrogen quotient (NQ) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), of Pacific sanddab (Citharichthys sordidus) ........................................ 270 xxxiii Figure 8.7. The interactive effects on transepithelial potential (TEP) of (A, B) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario)(C, D, E) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin) (F, G) 7.5 ppt and natural DOCs (Luther Marsh and Lake Ontario), (H, I, J) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), of Pacific sanddab (Citharichthys sordidus) ..................... 272 Figure 9.1. The effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on net Na+ flux rate (A) in control INPA water (B) in RN water and (C) in RS water on net K+ flux rate (D) in control water, (E) in RN water and (F) in RS water, and on net Cl- flux rate (G) in control water (H) in RN water and (I) in RS water. ....................................................... 307 Figure 9.2. The effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on ammonia-N excretion rate (A) in control INPA water, (B) in RN water and (C) in RS water), and on urea-N excretion rate (D) in control water, (E) in RN water and (F) in RS water...................................................................................................................................................... 308 Figure 9.3. The effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on diffusive water flux rate (A) in control INPA water, (B) in RN water and (C) in RS water, on gill PEG clearance rate (D) in control water, (E) in RN water) and (F) in RS water and on drinking rate (G) in control water (H) in RN water and (I) in RS water.. ............................. 310 Figure 9.4. The effect of %free copper ion (Cu2+) on net (A) Na+, (B) K+ and (C) Cl- flux rates. Data at nominal total Cu concentrations of 200 µg L-1 in control water, RN water, and RS water, at both pH 7 and pH 4 have been combined in these relationships ............................................ 311 Figure 10.1. (A) The physicochemical indices used to characterize DOC are pH dependent. (B) There are interactive effects of DOC, salt ions (Na+ and Ca2+) or Cu2+ and low pH on physiology. xxxiv (C) Three model compounds have been identified as useful and share key chemical characteristics with natural humic acid, a key component of DOC ............................................ 327 Figure 10.2. The interaction between DOC and the gill at (A) pH 7 where the net charge of the gill and DOC molecule is negative and (B) pH 4 where the net charge of the gills and DOC are titrated by H+ ........................................................................................................................................... 329 xxxv List of Abbreviations 3H2O Tritium AA Acetic acid AgNO3 Silver nitrate AHA AldrichTM humic acid Al Aluminum AP Ancient Pond AS Ancient Swamp BMSC Bamfield Marine Science Center BSA Bovine serum albumin Ca2+ Calcium ion CaCl2 Calcium chloride Cd Cadmium Cl- Chloride ion CO2 Cu Carbon dioxide Copper CONCEA Brazilian Ethics Committee on Animal Care Cu2+ Free copper ion Da Dalton DOC Dissolved organic carbon FA Formic acid Fe2+/3+ Divalent and trivalent iron FEEM Fluorescence excitation–-emission matrix FI Fluorescence index Fru Fructose Galac Galactose Glu Glucose H+ Proton HL oct Fraction of ligand in octanol xxxvi HNO3 Nitric acid HSP Heat shock protein IBAMA Brazilian Institute of Environment and Renewable Natural Resources INPA Instituto Nacional de Pesquisas da Amazônia Jmax Jnet K+ Maximum transport capacity Net flux rate Potassium ion Km Kow Affinity constant octanol water partition coefficient LAC -lactalbumin LAS linear alkylbenzene sulfonate LC50 Lethal concentration to 50% of organisms LEEM-INPA Laboratory of Ecophysiology and Molecular Evolution at Instituto Nacional de Pesquisas da Amazônia LM Luther Marsh LO Lake Ontario log Kow Logarithm of the octanol water partition coefficient LT Ligand total M-M equation Michaelis-Menten equation Mann Mannose Mg Magnesium MIT Multi-ion toxicity model ṀN Total nitrogen waste excretion Mn+ Metallic cation ṀO2 Oxygen consumption rate MP Methyl palmitate mRNA Messenger ribonucleic acid MS Methyl stearate MS222 Tricaine methanesulfonate xxxvii MW Molecular weight MWI Molecular weight index NA Naphthionic acid Na+ Sodium ion Na+/K+-ATPase Sodium potassium pump Na+/NH4+‐ATPase Sodium ammonia pump NaCl Sodium chloride NaOH Sodium hydroxide NBC Sodium bicarbonate co-transporter NEM N-ethylmaleimide NH3 Ammonia NH4+ Ammonium NHE Sodium-hydrogen exchanger Ni Nickel NQ Nitrogen quotient O2 Oxygen P Phosphorus PA Palmitic acid PARAFAC Parallel factor analysis PBI Proton binding index PEG [3H]-polyethylene glycol-4000 PF Preston Flats pO2 Partial pressure of oxygen ppt Parts per thousand Rb Rubidium Rh Rhesus proteins RN Rio Negro RS Rio Solimões SA Salicylic acid SAC340 Specific absorbance coefficient at 340 nm xxxviii SDS Sodium dodecyl sulphate Se Selenium SEM Standard error of the mean SGC São Gabriel da Cachoeira SID Strong ion difference Sn Tin StA Steric acid TA Tannic acid TEP Transepithelial potential Th Thorium Tryp Tryptophan Tyr Tyrosine UBC University of British Columbia UT Urea transporter UV Ultraviolet V Vanadium V‐ H+ ATPase Vacuolar type proton pump ΔTEP Delta transepithelial potential xxxix Acknowledgements I am extremely grateful to the many people who have contributed to my growth as both a researcher and an individual over the past five years. Chris Wood, what an incredible journey we have been on. I will forever be grateful for the profound impact you have had on both my life and my scientific education. Your unwavering support, guidance, and belief in me over the past five years have been a source of strength I can never fully put into words. You taught me resilience, flexibility, and the courage to pursue my own ideas, while always knowing when to offer your insight. This journey has spanned years, countries, and life phases, and your influence will stay with me. This has been an extraordinary opportunity, one that simply would not have been possible without you. Thank you. Colin Brauner, I am deeply thankful for your encouragement and support over the past five years. Your insightful feedback and expertise shaped the direction of my thesis and challenged me to think critically and approach challenges with confidence. I especially appreciate your patience during difficult stages of life and research, your willingness to discuss ideas at any time, and your belief in my abilities, which inspired both my personal and professional growth. Thank you for dedicating your time and effort to mentoring me and for creating an environment that fostered both academic and personal development. Scott Smith, your passion and enthusiasm for chemistry are contagious, and I am thankful for the opportunity to have learned from you. Your patience, dedication, and knowledge made navigating the steep chemistry learning curve both possible and enjoyable. To my chemistry partner, tutor, and friend, Sam Zulian- your generosity, willingness to learn new methods, and thoughtful approach are deeply appreciated. I sincerely thank Adalberto Val for hosting me at the Laboratory of Ecophysiology and Molecular Evolution (LEEM-INPA) at the Instituto Nacional de Pesquisas da Amazônia, and for your invaluable guidance in shaping my research approach in the Amazon. I very appreciative of my collaborators at LEEM; Susana Braz-Mota, Rafael Duarte, and Jhonathan Mota da Silva for helping me navigate the lab and fieldwork in the Amazon. My gratitude extends to my committee members, Ora Johannsson and Trish Shulte. The advice, suggestions, and expertise you both offered were instrumental in shaping this thesis. Trish, your dedication and thoughtful guidance are a testament to your generosity and xl commitment to mentoring aspiring academics. Ora, your kindness and insight, both within and beyond the lab, made navigating the complexity of DOC and graduate school far less intimidating. Tamzin Blewett, Anne Crémazy and Erin Lenoard: thank you to each of you for your mentorship and extremely valuable advice which inspired me to continue on this journey and provided balance and perspective along the way. Gudrun de Boeck, Camila Martins and Bernd Pelster, your guidance, support, and camaraderie during the Bamfield and Amazon field trips led to not only exceptional research experiences but also truly unforgettable adventures. I feel incredibly fortunate to have been a part of both the Wood Lab and Brauner Lab, thank you to the past and present lab members. A special thank you to the UBC friends I have met along the way and shared the highs and lows of graduate school with: Clare Kilgour, Ellen Jung, Rachel MacKinnon, Evan McKenzie, Carley Winter and Lauren Zink. I would like to thank my friends and family for their support and encouragement. To my friends who listened to my countless 'fish stories' and offered advice, laughter, and friendship throughout the years. To my dear friend Melissa, whom I lost during this degree, your light and strength continue to guide and inspire me even on the toughest days. To my favourite husky team: Rennie and River, thank you for the warm greetings after weeks apart and the late-night writing companionship. To my brother and best friend, Aaron, I am very thankful for your ever grounding presence in my life. To my sister-in-law, Lisa, thank you for always listening to my graduate school experiences and for your genuine interest in sharing both the challenges and successes along the way. To my parents, Paul and Debbie, I cannot begin to express my gratitude for the opportunities, encouragement and love that you continuously provide. To my husband, Damien, I am endlessly thankful for your unwavering love and support, which have been my greatest source of strength and inspiration. I am eternally grateful for you. Finally, thank you to my right leg, which, despite repeatedly rebelling, faithfully carried me through each of the four major fieldtrips - I owe more than a little of my perseverance to you. To all those mentioned above and beyond, your influence has shaped me personally, guided this incredible journey, and enriched the work itself - I am deeply grateful. 1 Chapter 1: General Introduction 1.1 Overview Freshwaters are browning globally with the increase in dissolved organic carbon (DOC) concentrations (Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025). Concurrently, water pH is decreasing, with temporal fluctuations. Short-term decreases in pH are driven by periodic inputs of DOC-rich waters and long-term trends have been associated with climate change–induced increases in atmospheric CO₂ (Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; Quijada-Rodriguez et al. 2021). DOCs are heterogenous, complex compounds and are sometimes the most abundant dissolved carbon-containing component of freshwater (Thurman 1985). They have widespread biological and ecological effects on aquatic ecosystems that are not yet fully understood. DOCs influence abiotic and biotic processes including UV light screening within the water column, metabolic processes in organisms, nutrient transfer across trophic levels and bioavailability of toxicants (see Section 2.4; Al-Reasi et al. 2011; Kullberg et al. 1993; Petersen 1991; Steinberg et al. 2006; Sucker and Krause 2010; Wood et al. 2011). By reducing the bioavailability of metal cations, DOCs protect against metal toxicity in freshwater fish (see Section 2.11; Crémazy et al. 2016; Hollis et al. 2001; Playle et al. 1993; Wood et al. 2011). It has been proposed that the important characteristics of DOC in protecting against metal toxicity are the same chemical properties that exert physiological effects in freshwater fish (Al-Reasi et al. 2011). These physiological effects at the gills are often beneficial, particularly at low environmental pH: active ion uptake is protected and passive loss of salt ions (e.g. Na+, Cl-) is attenuated (see Section 2.7; Al-Reasi et al. 2011, 2016; Duarte et al. 2016; Gonzalez et al. 2002, 2 2005; Matsuo et al. 2004; Wood et al. 2002, 2003), the inhibition of ammonia excretion is mitigated (see Section 2.10; Duarte et al. 2016; Sadauskas‐Henrique et al. 2019, 2021; Wood et al. 2003) and transepithelial potential (TEP, the diffusion potential between the blood plasma and the external water) becomes more negative (see Section 2.9, Galvez et al. 2008; Sadauskas‐Henrique et al. 2019), improving the electrochemical gradient for net Na+ uptake at the gills (Wood et al. 2011, 2025). The effects of other water quality parameters (e.g. pH, alkalinity, hardness, salinity) on the ion transport functions of the fish gill have been studied extensively by physiologists, yet comparatively, DOC effects have been largely overlooked. The few available studies suggest that DOC may exert comparable or greater physiological effects on freshwater fish than the other well-studied water quality parameters (Wood et al. 1998, 2003, 2011; Gonzalez et al. 2002; Duarte et al. 2016; Sadauskas‐Henrique et al. 2019). As such, DOC effects on important osmoregulatory parameters including the permeability of the gill epithelium to water have been relatively unexplored. Water moves across the gill through two separate transport pathways in freshwater fish (Wood et al. 2019). Water can move paracellularly through tight junctions via bulk flow. It can also move by diffusion across the entire gill surface but largely it moves transcellularly through aquaporins, channels that facilitate the diffusion of water (Preston et al. 1992; Wood et al. 2019). Although it has been suggested that DOC may affect water movement through these pathways (Galvez et al. 2008), prior to the investigations of this thesis (Chapters 8 and 9) there were no experimental data confirming this. The ability of DOCs to protect against metal toxicity and physiological disturbances caused by low pH in aquatic organisms has been correlated to their physicochemical characteristics, with some DOCs being more effective than others (see Section 2.3; Al-Reasi et 3 al. 2011, 2012; Al-Reasi, Wood, et al. 2013; Sadauskas‐Henrique et al. 2019). The molecular variability between DOCs can be described using optical properties (e.g. absorbance and fluorescence signatures) to assess aromaticity (specific absorbance coefficient at 340 nm, SAC340; Curtis and Schindler 1997), molecular weight (molecular weight index, MWI; Dahlén et al. 1996; Peuravuori and Pihlaja 1997), and allochthonous versus autochthonous origin (fluorescence index, FI; DePalma et al. 2011; McKnight et al. 2001) (see Section 2.3). Allochthonous DOCs are formed by the breakdown of terrestrial plant compounds such as lignins (Ertel et al. 1986) and autochthonous DOCs are formed in lakes and river by the metabolism of invertebrates, plankton and bacteria. Chemical indices based on titration properties can indicate lipophilicity (octanol-water partition coefficient, log Kow; Egeberg and Alberts 2002; Gjessing et al. 1999), chemical reactivity (proton binding index, PBI; Al-Reasi et al. 2013) and the ionizable fraction of the molecule (molecular charge) (see Section 2.3). The analyses within this thesis investigate the effect of a change in pH from 7 to 4 on physicochemical characterization indices including those described above, their interrelationships and their relationships with physiological endpoints (Chapters 3, 4, 5, 6 and 8). Indeed, DOCs have direct biological effects on the gills although the exact protective mechanisms remain unknown. The variability in DOC structure and function is reflected in both their physiochemistry and in the physiological response of fishes. This may be due to key chemical moieties which have not yet been previously determined. Due to the complexity and heterogeneity of fresh natural DOCs, identifying the chemical entities interacting with the gill in mechanistic physiological studies is challenging. To isolate these potentially important chemical groups, model compounds of known chemistry were tested (Chapters 5, 6, 7, 8 and 9). Throughout this thesis, these compounds were selected based on the criteria that they structurally 4 resemble, or functionally behave like, certain components of DOC. As DOC is an ecological driver in aquatic ecosystems (see Section 2.4), a mechanistic understanding of the interaction of DOC at the gill as well as the role of other environmental parameters is crucial for future monitoring of aquatic ecosystem health. The interactive effects of DOC and pH, major ion concentrations and/or potential pollutants on fish physiology have been investigated throughout this thesis. To explore the physiological effects of these environmentally relevant DOC-water quality interactions, fish native to specific habitats with different ionoregulatory strategies were utilized (Chapters, 6, 7, 8 and 9). Through anthropogenic activities including road de-icing (Findlay and Kelly 2011), changes in land usage (Boetler et al. 1992; Smedema and Shiati 2002; Pond et al. 2008; Blewett et al. 2017) and seawater intrusion (Chun et al. 2018; Baena-Ruiz et al. 2020), concentrations of major salt ions (e.g. Na+, Ca2+ and Cl-) are increasing, leading to freshwater salinization. This is now one of the most concerning stressors on freshwater ecosystems (Goodfellow et al. 2000; Findlay and Kelly 2011; Cañedo-Argüelles et al. 2013, 2016; Herbert et al. 2015) as it leads to hydromineral disturbance in freshwater organisms (Mount et al. 2016; Wood et al. 2020; Po and Wood 2021). Concurrently, within these environments DOC concentrations are increasing (Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025) and the water is becoming more acidic (Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; Quijada-Rodriguez et al. 2021) as described above. The non-acidophilic rainbow trout (Oncorhynchus mykiss) with a “standard” teleost ionoregulatory system (see Section 2.6) was used for the investigation on the interactive 5 effects of DOC, pH and major ions on TEP, an important osmoregulatory indicator (Chapters 4, 5 and 6). As concentrations of major ions in freshwater environments are changing with anthropogenic activities and climate change, so are the levels in marine environments. Coastal areas of the north-west Pacific Ocean are experiencing reductions in salinities with estuarine areas experiencing more extreme seasonal fluctuations (Rogers et al. 1984; Cao et al. 2020). In estuarine environments, local fish populations not only experience changes in salinity but they are also exposed to DOC of freshwater origin (McNicol et al. 2023). The studies to date involving DOCs in seawater have been limited entirely to marine invertebrates (Nadella et al. 2009, 2013; DePalma et al. 2011; Cooper et al. 2014; Tait et al. 2016; Blewett et al. 2016, 2018, 2021). Marine flatfish, including, Pacific sanddab (Citharichthys sordidus) and rock sole (Lepidopsetta bilineata) feed and spawn in highly dynamic estuaries (Schreiber 2001; Ruiz-Jarabo et al. 2015) and have a typical marine fish ionoregulatory system (i.e. passive ion uptake and active ion excretion). These fish were used in this thesis to explore the interactive effects of DOC and salinity in marine flatfish as experienced in natural estuarine environments (Chapters 7 and 8). Among continental aquatic environments, blackwater systems, found globally, have high concentrations of DOC, low pH and are dilute in major ions (Sabater et al. 1993; Robroek et al. 2017; Gandois et al. 2020). The Rio Negro (RN), a relatively well studied blackwater tributary of the Amazon basin, has water chemistry that is extremely harsh, yet the biodiversity within the river is remarkable (Furch 1984; Val and De Almeida-Val 1995; Walker and Henderson 1996; Duarte et al. 2013). The dwarf cichlid (Apistogramma agassizii), in the Order Cichliformes, is native to the RN and Rio Solimões (RS) waters and has a unique low affinity ion transport 6 system with very tight regulation of Na+ efflux at low pH (Gonzalez et al. 2002, 2005; Duarte et al. 2009, 2013, 2024; Val and Wood 2022; Crémazy et al. 2022). Prior to this thesis, measurements testing the roles of DOC and Cu both separately and in combination on water transport pathways in the gills had not been performed. The dwarf cichlid was used to investigate the effects of natural DOCs, pH and copper (Cu), a contaminant of great interest in the Amazon (Moulatlet et al. 2023; Braz-Mota et al. 2024; Duarte et al. 2024) (Chapter 9). Throughout this thesis the experimental solutions were adjusted to approximately pH 7 and pH 4. Many of the collected natural waters and rearing conditions of the fish were near neutral pH (pH 7). pH 4 was used as the representative acidic pH treatment as this allowed for marked separation between test pHs (3 orders of magnitude higher H+ concentration than at pH 7) so as to affect both the protonation of the gill and the protonation of the DOC molecules. This acidic pH is environmentally relevant to naturally acidic, DOC-rich peat bogs and blackwater rivers. The objectives of each chapter within the thesis are outlined below (see Section 1.2). The overall goals of this thesis were (i) to investigate how ambient acidic water influences DOC physicochemical characterization indices and DOCs ability to elicit changes in fish physiology (ii) to determine whether DOCs and major salt (Na+, Ca2+ ) or metal (Cu2+) cations have independent and/or interactive effects on physiological processes at the gills; (iii) to identify the specific physicochemical properties of DOCs that are responsible for the altered osmo- and iono-regulatory function; and (iv) to investigate how DOCs influence osmoregulatory processes at the gills in fish with different ionoregulatory strategies. The overarching hypothesis being tested throughout was that DOCs and major ions have independent and interactive effects on particular 7 physiological processes in the gills which are due to specific chemical composition or moieties of the DOC molecules that are pH-dependent. 1.2 Thesis objectives and chapter summaries The investigations of this thesis focused on the physicochemical characteristics of natural DOCs and the chemical moieties as DOC analogues (model compounds) and their interactive effects with pH, major ions or Cu on physiological processes at the gill in fish with diverse ionoregulatory strategies. The thesis contains one review paper, written during the covid pandemic at the start of my Ph.D. studies (Chapter 2) so as to outline possible areas for investigation, followed by 7 experimental chapters (Chapters 3-9) as outlined below. 1.2.1 Chapter 2: “The physiology of fish in acidic waters rich in dissolved organic carbon with specific reference to the Amazon basin: ionoregulation, acid-base regulation, ammonia excretion and metal toxicity”. Published as Morris et al. (2021). This review paper outlines the ecological role of DOC in aquatic ecosystems, their physicochemistry, and their often-protective or supportive effects on ionoregulation in freshwater fish especially at low pH. The focus of the review is one of the most well studied biodiverse, blackwater systems globally, the Rio Negro. I review how native fish species thrive in physiologically challenging water chemistry that would be fatal to most freshwater fish. The influence of DOC particularly at low pH on active and passive ion transport, acid base balance, the electrical properties of the gill (i.e. transepithelial potential), ammonia transport and metal toxicity, across species is discussed. Finally, future research needs are highlighted, including a 8 greater understanding of the mechanistic actions of DOC at the gill. 1.2.2 Chapter 3: “A critical assessment of physicochemical indices used to characterize natural dissolved organic carbon (DOC), and their inter-relationships and the effects of pH”. Published as Morris et al. (2024b). The objectives of this chapter were to determine the effect of water pH on physicochemical characterization indices used to determine the molecular variability of natural DOCs and to assess the relationships between these indices. I applied various analytical techniques to characterize five sources of natural DOCs spanning large differences in origin and composition. I analyzed how the various indices were altered by a change in pH from 7 to 4 and assessed their inter-relationships. The main findings of this chapter were that physicochemical indices used to characterize DOCs are pH-dependent and should be interpreted carefully as it is likely that most of the changes between pH 7 and pH 4 reflect alterations in the conformation of the DOC molecules rather than changes in the composition (i.e. chemical makeup of the molecule) of DOCs. Some of the indices were correlated to one another and understanding these relationships aided in the interpretation of the physiological effects of different DOCs in subsequent chapters. 1.2.3 Chapter 4: “Using physicochemical properties to predict the impact of natural dissolved organic carbon on transepithelial potential in freshwater rainbow trout (Oncorhynchus mykiss) at neutral and acidic pH” Published as Morris et al. (2024c). The primary objective of this chapter was to determine how different DOCs at neutral and acidic pH relate to the physiology of the gills. I tested the effects of the same five DOCs 9 from the previous chapter on transepithelial potential (TEP), a key indicator of ionoregulatory function in rainbow trout. I assessed the relationships between each of the characterization indices and TEP to determine if physicochemical characterization indices of DOC could predict the effects of different DOCs on TEP. Each of the DOCs significantly influenced TEP, although in a unique manner or magnitude which may be due to physicochemical differences among the DOCs. I concluded that there are three particularly important indices that are predictors of changes in TEP across pHs in rainbow trout: the specific absorbance coefficient at 340 nm (SAC340), the octanol-water partition coefficient (log Kow), and the proton binding index (PBI). The identification of these characteristics allowed for potentially important specific chemical moieties of natural DOCs influencing TEP to be determined. It also facilitated the choice of model compounds in order to test the specific moieties in Chapter 5. 1.2.4 Chapter 5: “The chemical characterization of model compounds (dissolved organic carbon analogues) and their effects on transepithelial potential in rainbow trout (Oncorhynchus mykiss) at circumneutral and low pH.” (to be submitted for publication after input by co-author Dr. Scott Smith) To determine the key chemical moieties that influence the physiological responses to DOC, twenty model compounds were chosen based on the criteria that they structurally resemble and/or functionally behave like certain components of typical humic and fulvic acids. Each model compound was characterized using the physicochemical indices that I had used to characterize DOC in Chapters 2 and 3. Their effects on TEP in rainbow trout were tested at pH 7 and pH 4. Most characterization techniques based on absorbance and fluorescence signatures used for natural DOCs proved to be inappropriate for synthetic model compounds. However, 10 indices based on titration properties including lipophilicity (i.e. log Kow), and charge were applicable and important. Some groups of model compounds representing key chemical moieties had significant effects on TEP responses while other whole groups did not, and these responses were pH-dependent. pH-specific calculations and regression analyses were performed between TEP and appropriate chemical characterization indices to determine their relationships. Three key model compounds were identified as useful and appropriate indicators of key chemical groups of natural DOCs: tannic acid (TA), sodium dodecyl sulfate (SDS) and bovine serum albumin (BSA). Phenolic groups and long aliphatic chains may be contributing to the TEP response in natural allochthonous DOCs making TA and SDS appropriate model compounds for this type of DOC. Amino acids and peptides may contribute to the effect of autochthonous DOCs on TEP, so BSA may be an appropriate model compound to represent this type of DOC. The results from this chapter demonstrate that selected model compounds (i.e. TA, SDS and BSA) and chemical characterization indices (i.e. log Kow and charge) may be used as predictors of effects on TEP, indicating ionoregulatory status. As such, the three identified model compounds (TA, SDS and BSA) were tested alongside natural DOCs throughout the remainder of the thesis in evaluating how other water quality parameters interact with DOCs in fish with different ionoregulatory strategies. 1.2.5 Chapter 6: “Interactions of major ions, pH, and dissolved organic carbon (DOC) on transepithelial potential (TEP) in rainbow trout: are there implications for the prediction of salt toxicity?” Published as Morris et al. (2025a). The Multi-Ion Toxicity (MIT) Model is a theoretical model originally developed by the Electric Power Research Institute to predict the toxicity of major ions to organisms in fresh 11 water. It assumes that major ions differentially disturb electrical gradients across biological membranes such as the gills and that this disturbance is ultimately associated with toxicity and mortality. Previous studies (Wood et al. 2020; Po and Wood 2021) experimentally testing the MIT model in fish had concluded that certain elements of the model are valid. Specifically, in accord with the model, the magnitude of ΔTEP (difference from baseline control) was predictive of toxicity. In the present study, I experimentally evaluated how DOC, which also causes changes in TEP, interacted with major ions, and therefore the predictions of the model for toxicity in rainbow trout. I tested 8 concentrations of NaCl or CaCl2 at pH 7 and pH 4 in the presence and absence of DOCs (two natural sources from Chapters 2 and 3 and three model compounds from Chapter 4). The effect of either salt alone (Na+ or Ca2+) on ΔTEP followed a hyperbolic relationship with concentration, one that could be characterized by the Michaelis-Menten equation, and baseline absolute TEP was shifted more positively in response to low pH. Each of the DOCs or model compounds affected baseline TEP such that the hyperbolic relationship was shifted based on ΔTEP. Therefore, based on these results, and according to the MIT model, specific DOCs should protect against major ion toxicity as reflected in reduced ΔTEP, while others should potentiate major ion toxicity as reflected in increased ΔTEP. Others shifted the Km values (affinity constants, which represented the salt concentration at 50% of TEPmax) of the Michaelis-Menten relationships to the left or right, thereby respectively potentiating or ameliorating the predicted toxicity. I used a weight-of-evidence approach to predict how DOC and pH will influence Na+ or Ca2+ toxicity. Additionally, I concluded that key chemical moieties of DOC will likely play pH-dependent roles in both Na+ and Ca2+ toxicity. 12 1.2.6 Chapter 7: “The effect of salinity and Ca2+ on the diffusive water flux, oxygen consumption, nitrogenous waste excretion rates of the gill in Pacific sanddab (Citharichthys sordidus) and rock sole (Lepidopsetta bilineata)” Published as Morris and Wood (2023). The overall goal of Chapters 7 and 8 was to determine the effects of DOC and salinity on ionoregulatory function and metabolism in seawater fish. This chapter contributed to the understanding of the effect of environmentally relevant changes in salinity and [Ca2+] alone on various physiological endpoints in marine flatfish. This understanding was required prior to testing the interactive effects of salinity and DOC in Chapter 8, an area that had not previously been investigated in marine fish. I measured the effect of 7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt salinities on diffusive water flux, oxygen consumption, and nitrogenous waste excretion rates at the gills in Pacific sanddab (Citharichthys sordidus) and rock sole (Lepidopsetta bilineata). The results demonstrated that both diffusive water flux and ammonia excretion rates are a function of salinity in both species, and that neither of these are coupled to the rate of oxygen consumption in either species. Additionally, at least in rock sole, [Ca2+] also plays a role in these rates. 1.2.7 Chapter 8: “The effects of dissolved organic carbon and model compounds (DOC analogues) on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and gill transepithelial potential in Pacific sanddab (Citharichthys sordidus) at two salinities.” Published as Morris et al. (2024a) Building on the findings of Chapter 7, I evaluated the effects of two natural freshwater DOCs (Chapters 3, 4) and three model compounds (Chapter 5), at two salinities on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and TEP in Pacific sanddab (Citharichthys sordidus). The major findings were that diffusive water flux and O2 consumption 13 rates can be uncoupled and independently regulated across salinities in the presence and absence of DOC and that the effect of DOC on osmoregulatory responses of the gill are salinity-dependent, which may be due to changes in the physicochemical properties of the DOC at different salinities. This is the first work to examine the physiological effects of DOC in seawater fish. 1.2.8 Chapter 9: “The acute osmoregulatory effects of copper on Apistogramma agassizii, in Rio Negro blackwater and Rio Solimões whitewater: Flux rates of ions, nitrogenous wastes and water.” (published as Morris et al. 2025b) The final experimental chapter of the thesis was performed in natural waters from two very different river systems of the Amazon basin the Rio Negro (RN) blackwater (low ions, high DOC) and Rio Solimões (RS) whitewater (higher ions, intermediate DOC), considering pH and an important local toxicant, copper (Cu). The chosen test species, the dwarf cichlid (Apistogramma agassizii) is native to both river systems and indeed migrates between the RN and RS. The primary objective of this study was to determine the effect of copper at pH 7 and pH 4 in RN and RS water on the water transport pathways of the gills. This chapter is the first study to test the effect of these waters and copper on both water transport pathways and urea-N excretion in Amazonian fish. Additionally model compounds were used to aid in the interpretation of the effects of the natural river waters. This work was done on a research boat expedition in Brazil to the two major tributaries of the Amazon River in November-December, 2023, organized by the National Institute for Amazon Research (INPA). I measured the effects of copper (nominally 200 µg L-1) in control water, RN blackwater and RS whitewater at pH 7 and pH 4 on diffusive water flux rate (transcellular water movement), paracellular permeability 14 ([3H]-polyethylene glycol-4000 clearance), ion balance (net Na+, K+ and Cl- fluxes) and nitrogenous waste (ammonia and urea) excretion in the dwarf cichlid. I found that copper increased net ion losses in control water, especially at low pH; RN water protected against these effects. My results showed that copper tends to inhibit urea-N excretion and ammonia excretion and also decreases branchial water transport both transcellularly and through tight junctions. In some cases, the physiological effects of Cu could be explained by the bioavailability of the free Cu2+ ion. However, there were also physiological effects of copper even when there was negligible free Cu2+ present. Overall, RN water, which has higher levels of DOC which is more allochthonous, but much lower ion concentrations, provided greater protection against disturbances caused by low pH and copper. This was possibly due to the difference in DOC concentration and water composition but also likely due to the physicochemical differences in the DOCs themselves (Crémazy et al. 2016; Holland et al. 2017). Therefore, further knowledge of the mechanism(s) by which copper disturbs osmoregulatory processes and the role of water chemistry, particularly DOC characteristics, may help inform guidelines for copper pollution levels in different areas across the Amazon basin. 15 Chapter 2: The physiology of fish in acidic waters rich in dissolved organic carbon with specific reference to the Amazon basin: Ionoregulation, acid-base regulation, ammonia excretion and metal toxicity. 2.1 Summary Although blackwaters, named for their rich content of dissolved organic carbon (DOC), are often very poor in ions and very acidic, they support great fish biodiversity. Indeed, about 8% of all freshwater fish species live in the blackwaters of the Rio Negro watershed in the Amazon basin. We review how native fish survive these harsh conditions that would kill most freshwater fish, with a particular focus on the role of DOC, a water quality parameter that has been relatively understudied. DOC, which is functionally defined by its ability to pass through a 0.45‐µm filter, comprises a diverse range of compounds formed by the breakdown of organic matter and is quantified by its carbon component that is approximately 50% by mass. Adaptations of fish to acidic blackwaters include minimal acid–base disturbances associated with a unique, largely unknown, high‐affinity Na+ uptake system that is resistant to inhibition by low pH in members of the Characiformes, and very tight regulation of Na+ efflux at low pH in the Cichliformes. Allochthonous (terrigenous) DOC, which predominates in blackwaters, consists of larger, more highly colored, reactive molecules than autochthonous DOC. The dissociation of protons from allochthonous components such as humic and fulvic acids is largely responsible for the acidity of these blackwaters, yet at the same time, these components may help protect organisms against the damaging effects of low water pH. DOC makes the transepithelial potential (TEP) more negative, mitigates the inhibition of Na+ uptake and ammonia excretion, and protects against the elevation of diffusive Na+ loss in fish exposed to acidic waters. It also 16 reduces the gill binding and toxicity of metals. At least in part, these actions reflect direct biological effects of DOC on the gills that are beneficial to ionoregulation. After chronic exposure to DOC, some of these protective effects persist even in the absence of DOC. Two characteristics of allochthonous DOC, the specific absorbance coefficient at 340 nm (SAC340 determined optically) and the proton binding index (PBI, determined by titration), are indicative of both the biological effectiveness of DOC and the ability to protect against metal toxicity. Future research needs are highlighted, including a greater mechanistic understanding of the actions of DOCs on gill ionoregulatory function, morphology, TEP, and metal toxicity. These should be investigated in a wider range of native fish Orders that inhabit one of the world's greatest biodiversity hotspots for freshwater fishes. 2.2 Introduction Dissolved organic matter, often loosely referred to as dissolved organic carbon (DOC), is central to the function, structure, and diversity of aquatic ecosystems (Lindeman and Lindeman 2007; Findlay and Parr 2017). It is defined by passage through a 0.45‐µm filter (therefore “dissolved”), and quantified by its carbon content (therefore “DOC”), which generally makes up about 50% of the molecules by mass (Wood et al. 2011). When molar units are used, these are based only on the moles of carbon content (molecular weight [MW] = 12.01 Da), because the exact structures of most DOC molecules are unknown. It should be recognized that there are many carbon atoms in each DOC molecule. These heterogeneous compounds are naturally occurring transformed products of the breakdown of organic matter by microbes, light, heat, and enzymes in soil and water (Zara et al. 2006). Allochthonous DOCs (also known as terrigenous) are formed largely on land from the breakdown of plant products such as lignins, whereas 17 autochthonous DOCs are formed largely in lakes and rivers by the metabolism of very small organisms (invertebrates, plankton, and bacteria). DOC is sometimes the most abundant dissolved carbon-containing component in freshwater. It provides essential nutrients to organisms and influences the productivity of trophic interactions within an ecosystem (Lindeman and Lindeman 2007; Findlay and Parr 2017). The effects of fluctuations in other water quality parameters (e.g. pH, alkalinity, Ca, Na, salinity) on gill function have been extensively studied by physiologists but the effects of DOC on the ion transporting properties of the gill remain relatively unexplored. DOC is a critically important water quality parameter to consider for ecological understanding and risk assessment as it may have comparable or greater effects on freshwater fish physiology (e.g. ionoregulation, acid–base balance, and acute metal toxicity) than the previously mentioned and well‐studied water quality parameters (Wood et al. 1998, 2003, 2011; Gonzalez et al. 2002; Duarte et al. 2016; Sadauskas‐Henrique et al. 2019). The dissociation of protons from allochthonous DOC is the major cause of acidity in peat bogs and many other natural blackwaters. However, there is now extensive evidence in freshwater fish that natural DOCs may actually mitigate the ionoregulatory disturbances of the ambient low pH which they help to create (Wood et al. 1998, 2003; Gonzalez et al. 2002; Duarte et al. 2016, 2018). It has even been suggested that DOCs may affect ventilation (Holland et al. 2014; Perry et al. 2021) and respiratory gas exchange (O2, CO2, and ammonia) at the gills (Matsuo et al. 2004), and at least for ammonia, there are data that support this (Wood et al. 2003; Duarte et al. 2016, 2018). Here, our major focus is on ionoregulatory physiology and associated functions (acid–base balance, ammonia excretion), where there remain significant gaps in our understanding of the effect(s) of DOC on ion transport in freshwater fish. DOC source, physicochemical properties, and the species of interest all influence the effects of DOC on 18 freshwater organisms under acidic conditions (Wood et al. 2011). We will first review the nature, origins, ecological roles, and chemistry of DOC, and then provide an overview of previous investigations on the effects of DOC in acidic water on ion transport including active ion uptake and passive ion loss, acid–base balance, electrical properties of the gill (transepithelial potential [TEP]), ammonia excretion, and the amelioration of metal toxicity. Blackwater systems are found globally from tropical peatlands in Southeast Asia, European peat bogs, swamps along the Atlantic coast of North America to South American tropical rainforests (Sabater et al. 1993; Robroek et al. 2017; Gandois et al. 2020). Blackwater systems have a characteristically high concentration of DOC, low pH, and often low ion concentration. Our focus will be on the best studied of these habitats, the Amazon basin, particularly the fish native to Rio Negro blackwaters. 2.3 Physicochemical properties of DOC Humification is a poorly understood biological process where DOC is formed by the microbial processing of lignin‐rich plant materials and the decay of organic remains of animals (Ertel et al. 1984; Hatcher and Spiker 1988). Humification yields complex chemical structures that are more stable than the original compounds from which they are derived (Boggs et al. 1985). DOC is often the largest component by mass of the dissolved components of natural waters. However, there is a wide variation in concentrations (5–35 mg L-1 in Rio Negro; Table 2.1) found within freshwater systems that may fluctuate seasonally and differ among regions (Thurman 1985; Boggs et al. 1985; Tipping 2002; Holland et al. 2017, 2018). DOC is a combination of humic substances which are generally larger molecules than non-humic substances such as amino acids, fatty acids, phenols, sterols, natural sugars, hydrocarbons, urea, 19 and porphyrins (Boggs et al. 1985; Gaffney et al. 1996). Humic substances are primarily composed of carbon, nitrogen, oxygen, and sulfur that make up organic acids that have highly oxygenated functional groups (Boggs et al. 1985; Zara et al. 2006). Operationally, humic substances are fractionated into “humic acids” which precipitate at low pH (1–2) and “fulvic” acids which do not (Figure 2.1). Humic acid DOC is often more aromatic and has a higher mean MW compared to fulvic acid DOC. The general structure of the humic substance macromolecule found in aquatic systems, a flexible polyelectrolyte, depends on the conditions of the system including electrolyte concentration and pH (Figure 2.1; Holland et al. 2018; Zara et al. 2006). Naturally acidic waters tend to have higher concentrations of humic substances and appear to be optically darker, indicating a different quality DOC than found in circumneutral water (Holland et al. 2018). DOC can be distinguished by origin, optical characteristics, or molecular properties. Allochthonous DOC, composed of∼50%–90% humic substances, is produced on land and washed into nearby natural waters (Thurman 1985; Tipping 2002). The transport of DOC from terrestrial to aquatic environments varies spatially and temporally, creating variation in DOC characteristics (Kullberg et al. 1993). Autochthonous DOC is generated within the water column by algae and bacteria and is much lighter in color compared to allochthonous DOC (Tipping 2002). Optical properties such as aromatic composition (quantified by specific absorbance coefficients), fluorescence signatures, and parallel factor analysis (PARAFAC) have been used to describe molecular variability of DOC (Al-Reasi et al. 2011). DOCs identified by these methods are often referred to as chromophoric DOCs because they absorb light (Nimptsch et al. 2014; Holland et al. 2018). Humic fractions can be distinguished from fulvic fractions as they produce longer wavelength emissions (Wu 2007). The specific absorption coefficient (SAC) is the absorbance of 20 DOC at 300–350 nm normalized to DOC concentration, and is used as an index of aromatic composition, with the higher the value, the greater the aromaticity (i.e. phenol ring content). The specific absorption coefficient at 340 nm (SAC340) appears to be a very useful indicator of the ability of DOC to both bind metals (Al-Reasi et al. 2011, 2012) and exert physiological effects on aquatic organisms (Al-Reasi et al. 2013a). Fluorescence index (FI) may indicate if organic matter originates from different sources. It is the ratio of fluorescence intensity450 nm/fluorescence intensity500 nm at an excitation wavelength of 370 nm, with high values indicating an autochthonous origin, and low numbers an allochthonous origin (McKnight et al. 2001). Overall, Al‐Reasi et al. (2011) concluded that FI was less successful than SAC in predicting the ability of different DOCs to protect against metal toxicity. This may reflect spatial and temporal variations during humification (Al-Reasi et al. 2011). Parallel factor analysis is a computational model based on the fluorescence excitation‐emission fingerprint of a DOC sample that uses a multivariate statistical approach (Kroonenberg and Heiser 1998; Stedmon and Bro 2008). It allows for greater molecular discrimination than other methods (e.g. FI and SAC) because of its advanced spectral resolution based on excitation‐emission fluorescence spectroscopy. This method yields relative percent fractionation into user‐defined components, and generally assumes 2–4 such components as representative fluorophores in each sample for (example, a humic‐like, a fulvic‐like, and two different protein/amino acid‐like components), and then produces summary numbers representing organic matter quality (Al-Reasi et al. 2011). The protective effect of DOC against metal toxicity and the molecular variability between samples from different environments can be tracked based on the wavelengths of light emitted and the resulting fluorescent composition. Samples that are high in humic‐ and fulvic-like content are generally allochthonous and highly protective, whereas autochthonous samples are high in 21 amino‐acid‐like fluorescence and are generally much less protective (Al-Reasi et al. 2011). Overall, SAC appears to be positively correlated with the humic‐like component and negatively correlated with the fulvic‐like component calculated by PARAFAC, whereas the opposite is true for FI (Al-Reasi et al. 2011). Lipophilicity and binding capacity of DOC have also been investigated to determine their role in affecting ionoregulatory physiology and metal toxicity in fish (Al-Reasi et al. 2011; Wood et al. 2011). Lipophilicity has been estimated by two methods, reverse‐phase high‐pressure liquid chromatography and the octanol–water partition coefficient (Kow) (Gjessing et al. 1999; Egeberg and Alberts 2002). When these two isolation procedures were performed on the same samples, different lipophilicity ranges were reported suggesting that the lipophilic nature of DOC is dependent on the isolation procedure (Namjesnik-Dejanovic and Cabaniss 2004). The lipophilic nature of DOC is likewise dependent on pH (Gjessing et al. 1999; Egeberg and Alberts 2002; Namjesnik-Dejanovic and Cabaniss 2004). The overall conclusion appears to be that there is no relationship between lipophilicity and the ability to bind metals (Al-Reasi et al. 2011). There has been a large matrix of methods employed to determine the binding capacity properties of DOC with debate over the importance of the specific binding ligands involved (Alberts et al. 1984). Ultrafiltration through a 1000 Da MW filter followed by a series of titrations as well as measurements with ion‐selective microelectrodes have been used (Alberts et al. 1984; Smith and Kramer 1999; Takács 1999). With respect to protection against metal toxicity, no clear association between H+‐ or metal‐binding site density was apparent in earlier analyses (Al-Reasi et al. 2011). However, Al-Reasi et al. (2013) developed a new metric, the proton binding index (PBI), as a general indicator of the chemical reactivity of DOC, based on acid–base titration over a wide range of pK values. There was a strong positive correlation 22 between PBI and SAC340, such that DOCs with high PBI values were both protective against metal toxicity and supportive of ionoregulation. Photo‐oxidation breaks down DOC into smaller, less aromatic molecules with generally lower binding capacities for metals (Patel-Sorrentino et al. 2002; Shiller et al. 2006) and therefore lower protective abilities against metal toxicity to fish, although some exceptions to this trend have also been observed (Brooks et al. 2007a, b, c). Finally, it is important to note that while commercially available humic acids, which are usually derived from coal or peat, can be characterized and classified by the above approaches, it is now clear that they are fundamentally different from humic substances occurring in natural waters (Malcolm and MacCarthy 1986; Chiou et al. 1987; Rodríguez et al. 2014). Typically, they have been treated with strong chelating agents to strip away metals, and they may have unusually high ash content, both of which may give them unusually high cation binding capacity and reactivity with biological membranes. There may also be structural differences. Results obtained with commercially available humic acids can be misleading and should be interpreted cautiously. For example, AldrichTM humic acid, at the same total DOC concentration as natural compounds in Rio Negro blackwater, exacerbated rather than protected against the effects of low pH on ion balance in Amazonian stingrays (Wood et al. 2003). Similarly, it disturbed the chemosensory control of ventilation, whereas natural DOC did not (Perry et al. 2021). AldrichTM humic acid was also much less protective against Ag toxicity to daphnia (Glover et al. 2005) and less effective on reducing urea excretion at low pH in daphnia (Al-Reasi et al. 2013b) than would have been predicted by its optical properties. Likewise, exposure to environmentally relevant concentrations of AldrichTM humic acid at low pH decreased the survival of the silver catfish (Rhamdia quelen) and altered gill morphology, suggesting ionic and respiratory disturbances (da Costa et al. 2015, 2017). 23 2.4 DOC as a general ecological driving factor in aquatic ecosystems DOC concentrations are presently increasing in freshwater systems on a worldwide basis (Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025), though with great temporal and spatial variability. Driving factors include changes in air temperature, increased precipitation, changes in land usage, increased atmospheric carbon dioxide, decreased atmospheric sulfur deposition, and accumulation of atmospherically deposited nitrogen (reviewed by Sucker and Krause 2010; Pagano et al. 2014). DOC is an environmental regulator of biotic and abiotic processes in freshwater ecosystems (Petersen 1991; Kullberg et al. 1993; Steinberg et al. 2006; Al-Reasi et al. 2011). The full extent of the ecological significance of DOC in freshwater systems is not yet understood. Aquatic ecosystems are very sensitive to changes in DOC concentrations as these molecules interact with complex biological processes including ultraviolet screening, the carbon cycle, CO2 generation and O2 consumption by photo‐oxidation, production of reactive oxygen species (ROS), acidification, nutrient transport, and metabolic processes (Kullberg et al. 1993; Sucker and Krause 2010; Wood et al. 2011; Johannsson et al. 2017, 2020; Holland et al. 2018). While autochthonous DOC is usually colorless, high concentrations of allochthonous DOC give water a brown hue which decreases UV penetration and influences water temperature, productivity, stratification, food web structure, and organism distribution within the water column (Hessen and Tranvik 1998; Keller et al. 2003; Sucker and Krause 2010). The photo‐mineralization of allochthonous DOC produces CO2 which has been estimated to be responsible for up to 10% of global greenhouse gas emissions (Koehler et al. 2016; Panneer Selvam et al. 24 2019). Acidification of water has been reported to increase DOC photodegradation (Anesio and Granéli 2003; Koehler et al. 2016). While DOC contributes to the acidity of the surface water, it may also buffer against acidification (Kullberg et al. 1993). While there is a general accord that most DOCs buffer effectively around circumneutral pH, and then again at very low pHs (<4.5) (Leenheer 1980; Wood et al. 2003), detailed titration studies have shown that a multiplicity of pK values exist within each type of DOC, reflecting different moieties within the molecules (variable amongst types). The overall buffer characteristics that are seen represent averages of these. Some DOCs can also have toxic effects to fish populations that are exacerbated at low pH (Kullberg et al. 1993), while others are protective (Wood et al. 2011). DOC delivers nutrients and energy to freshwater bacteria which are transferred to zooplankton that have a high reliance on allochthonous carbon, and in turn, these are subsequently transferred to fish (Jones 2005; Steinberg et al. 2006). Overall, the influence of DOC on these processes depends on the quality of DOC itself (Holland et al. 2018). While it has been argued that DOC molecules can be taken up across the gills of aquatic organisms (Steinberg et al. 2003, 2006), there appears to be no definitive evidence in fish on this point, though there is evidence that DOC molecules can bind to the external surfaces of gill cells (Campbell et al. 1997). Much of the focus has been placed on the binding capabilities of DOC with regard to chelating xenobiotics and metals, thereby reducing their bioavailability and toxicity (Hollis et al. 2001; Steinberg et al. 2003; Niyogi and Wood 2004; Glover et al. 2005; Duarte et al. 2009; Al-Reasi et al. 2011). The functional groups that interact with the toxicants appear to be the same groups that interact with biological systems (Al-Reasi et al. 2013a), thus DOCs can act as xenobiotics themselves (Steinberg et al. 2003). Specifically, DOC exposures have been shown to provoke chemical and oxidative stress 25 responses such as the induction of defense proteins (e.g. HSP70), and the creation of free radicals and ROS with subsequent lipid peroxidation (Steinberg et al. 2006). As discussed subsequently, there also appear to be significant beneficial effects of DOC on the physiology of aquatic organisms. 2.5 Chemistry of Rio Negro blackwater The blackwaters of the Rio Negro, a major tributary of the Amazon River, are characteristically dilute yet deeply colored (Val and De Almeida-Val 1995). The soil surrounding the river is largely composed of silicate sand and due to its binding properties, has been long since been stripped of its major cations, leaving the water in this region extremely ion‐poor (Benedetti et al. 2003; Seyler and Boaventura 2003). The unique geochemistry of the headwaters and breakdown of jungle vegetation are reflected in the water composition, making Rio Negro blackwaters some of the most naturally acidic, DOC‐rich, and ion‐poor waters anywhere in the world (Furch 1984; Val and De Almeida-Val 1995; Walker and Henderson 1996). The pH is typically 4–6 but can be as low as∼3 (Table 2.1) in nearby forest streams and riverside lakes, likely due to poor buffering capacity as well as the input of decaying tropical plant material (Furch 1984; Walker and Henderson 1996). It is this decaying vegetation that results in a high DOC concentration, typically 5–15 mg L-1 and occasionally as high as 35 mg L-1 (Table 2.1) in blackwaters. In contrast, the Rio Solimões (often called whitewater because of its silt burden from the Andes mountains) typically has only 2 - 5 mg L-1 DOC. Na+, Cl-, Mg2+, and Ca2+ levels in the Rio Negro are usually less than 30 µmol L-1 (Table 2.1) and water conductivity less than 10 µS cm-1 (Furch 1984; Küchler et al. 2000; Wood et al. 2003), whereas typical levels in the Rio Solimões are 10‐fold higher or more. On average, Na+, Cl-, Mg2+, and Ca2+ 26 concentrations within Rio Negro waters are only 6%, 22%, 3%, and 1% of the mean values in global rivers (Gonzalez et al. 2005). As outlined below, the exceptionally low Ca2+ concentration may be an especially important influence on the physiology of Rio Negro fish. There is considerable seasonal variability between the wet (May–July) and dry (October–November) seasons in DOC and major ion concentrations. Concentrations of DOC, Na+, Mg2+, and Cl- were higher in the wet season relative to the dry whereas trends in Ca2+ and K+ concentrations were variable (Duarte 2012; Holland et al. 2017). Fluctuations in O2 concentration occur between the day and night driving many species of fish to migrate laterally to the river from the flooded forest before nightfall. At night, the flooded forest O2 levels may reach as low as zero whereas the running river is generally normoxic (Val 2019). DOC‐rich waters that drain from the forest soils, rocks, and the plants growing there may have high concentrations of metals, reflecting the preferential binding of metals to humic substances (Benedetti et al. 2003; Seyler and Boaventura 2003). Rainfall is an additional source of metals to Amazonian river systems which may partially explain the relatively high concentrations of Al, Sn, Se, Th, Rb, and Cd in the Rio Negro (Konhauser et al. 1994). Konhauser et al. (1994) reported that Al, Cd, Sn, P, and V were precipitated at more than 10‐fold the concentration of the surface waters based on analysis of collected rainfall compared with the concentration of dissolved metals in the Rio Negro. In summary, the chemistry of these blackwaters is so severe that they would likely be toxic to most freshwater fish, yet the ichthyofauna of the Rio Negro watershed is one of the most biodiverse in the world and represents about 8% of the global freshwater fish species. Clearly, this biodiversity must be associated with a range of physiological adaptations to this otherwise very challenging environment, as discussed below. 27 2.6 Active ion uptake and passive ion loss at circumneutral and acidic pHs Animals living in hypo‐osmotic environments face the osmotic influx of water and diffusive loss of salts to the external environment (Aladin and Potts 1995; Harris and Aladin 1997; Kirschner 2004; Evans et al. 2005; Larsen et al. 2014). Freshwater fish maintain ionic balance by employing active ion uptake through specialized branchial transport mechanisms, having low permeability of the body surface to ions and tight gill epithelia to limit diffusive ion loss through paracellular tight junctions (Rudy 1967; Lockwood 1997; Evans et al. 2005; Duarte et al. 2013; Potts and Parry 2016). Dietary salt uptake may also be important (Wood and Bucking 2011), especially when branchial ion transport is reduced by low environmental pH (D’Cruz and Wood 1998). The physiological response of non-acidophilic fish to environmentally relevant acidity (e.g. pH 3.5–5) is generally inhibition of active Na+ and Cl- uptake and elevation of passive ion loss resulting in reduced plasma Na+ and Cl- levels, lowered blood volume, haemoconcentration, and elevated plasma protein concentrations (McDonald et al. 1980; Wood and McDonald 1982; McDonald 1983; Wood 1989). Mortality eventually occurs due to circulatory failure (Milligan and Wood 1982). At extremely low pH (2.5–3.5), suffocation and rapid death are due to the breakdown of the gill structure and branchial mucus production (Daye and Garside 1976; Ultsch and Gros 1979). Increased ambient Ca2+ concentrations generally mitigate the damaging effects of low pH because of the competitive binding between Ca2+ versus H+ at sites on the gills that normally maintain epithelial integrity of the tight junctions (McWilliams and Potts 1978; McWilliams 1982; McDonald 1983; Hunn 1985; McDonald and Rogano 1986). As discussed subsequently, elevated environmental Ca2+ also changes the nature of the physiological response away from ionoregulatory disturbance towards acid–base disturbance (Wood 1989). 28 In most “standard” freshwater teleosts (e.g. the non-acidophilic rainbow trout [Oncorhynchus mykiss], the acidophilic zebrafish [Danio rerio]), Na+ uptake through the gills occurs via an electroneutral ion exchanger (Na+/H+ antiporter, NHE) which exports H+ and/or an electrogenic apical V‐ H+ ATPase which also exports H+, the latter energizing Na+ entry via an apical channel (Randall and Lin 1993; Kirschner 2004) (Figure 2.2A). The Na+ channel may be an “acid‐sensing ion channel” (Dymowska et al. 2014, 2015). Over the past 15 years, it has become clear that these mechanisms are coupled to ammonia excretion through apical Rh glycoproteins (Nawata et al. 2007; Wright and Wood 2009, 2012), channels that facilitate NH3 movement across the gill membranes (Nawata et al. 2010). By this model (Figure 2.2B), NH4+, the dominant form at physiological pH, is deprotonated as it enters the Rh channel, the NH3 moves through the channel, and the H+ is transported outwards by the V‐H+ ATPase or NHE, acidifying the external boundary layer, and immediately re-protonating the NH3 back to NH4+, effectively trapping it in the exhalent water (Wright and Wood 2009, 2012). The various components (NHE, V‐ H+ ATPase, Rh glycoprotein, and carbonic anhydrase as a source of additional protons) may be organized into a functional metabolon (Ito et al. 2013). Based on assumed electrochemical gradients, it was originally thought that Na+ uptake in low pH environments would rely on the V‐ H+ ATPase/Na+ channel mechanism because NHE could not accomplish Na+ uptake (Avella and Bornancin 1989; Parks et al. 2008). However, NHE appears to be quite important in Na+ uptake at low pH (3.5–4) in several species (e.g. zebrafish - Kumai et al. 2011; Kumai and Perry 2011 Lake Osorezan dace - Hirata et al. 2003). It has been argued that upregulation of the Rh‐glycoprotein metabolon removes the assumed electrochemical constraints on NHE function, such that Na+ uptake via NHE can function at low pH, and also that “active” ammonia excretion against apparent ammonia gradients can occur (Wright and 29 Wood 2012; Kwong et al. 2014). The exact energetics powering these mechanisms remain to be determined. At the basolateral membrane of the gill cells, Na+ is exported into the blood via a Na+/K+‐ATPase contributing to the electro-chemical gradient driving the inward movement of Na+ across the apical membrane (Figure 2.2A; Evans 2011; Kirschner 2004). An electrogenic Na+‐HCO3 cotransporter (NBC) of uncertain stoichiometry may also contribute to the basolateral export of Na+ (Parks et al. 2007). In some fish, including at least one Rio Negro native, the characid cardinal tetra (Paracheirodon axelrodi; Wood et al. 2014), the Na+/K+‐ATPase can also act as a Na+/NH4+ ‐ATPase with NH4+ at equal potency to K+ at concentrations (1 mmol L-1) that are physiologically relevant to plasma NH4+ levels, providing an alternate route for ammonia entry at the basolateral membrane (Figure 2.2A, B). Uptake of Cl- through the gill is coupled to HCO3- (base) excretion via an apical Cl-/HCO3 exchanger (Figure 2.2A), but there is little knowledge of the details or on the basolateral pathways (Evans 2011). Many fish species native to ion‐poor, acidic waters show particular ion transport mechanisms that differ from nonnative species, allowing them to thrive in these harsh environments (Gonzalez et al. 2005; Nelson 2015; Yanagitsuru et al. 2019). This likely involves unique adaptations that contrast with the general teleost models described above (Gonzalez and Preest 1999; Gonzalez et al. 2002). The lack of these mechanisms may explain why non-acidophilic fish do not readily acclimate to low pH (Audet and Wood 1988, 1993; Audet et al. 1988). Amazonian blackwaters are rich in allochthonous DOC that is the very cause of the acidity. Many of the Rio Negro fish species have an exceptionally high acid tolerance, surviving at or below pH 4, by avoiding imbalances in net Na+ and Cl- flux rates. While the degree of 30 tolerance to extremely dilute, low pH waters in Rio Negro natives is species‐specific (Gonzalez et al. 1998, 2002; Wilson et al. 1999; Duarte et al. 2013), one common feature may be the maintenance of generally lower plasma Na+ levels, a strategy to minimize energy expenditure in the low Na+ waters of the Rio Negro (Mangum et al. 1977, 1978). Another may be a general resistance to the stimulation of gill diffusive ion loss caused by low pH. This stimulated efflux, associated with a leaching away of Ca2+ ions, critical to maintaining the “tightness” of paracellular junctions, is the major cause of net ion loss and subsequent death at low pH in most fish (Wood 1989). There appear to be two basic ionoregulatory strategies of Rio Negro fish native to ion‐poor, acidic blackwaters. A high‐affinity (= low Km) ion transport system that supports generally high rates of Na+ uptake is characteristic of the Order Characiformes and a low‐ affinity (= high Km) ion transport system that achieves generally low rates of Na+ uptake is characteristic of the Order Cichliformes, more specifically the Family Cichlidae (Gonzalez et al. 2002, 2005, 2018, 2021a). By examining representatives of these two groups that are not native to the Amazon, Gonzalez et al. (2017) concluded that the strategies were likely linked to phylogeny. While there have not been any correlations described between the two basic ionoregulatory strategies and ecophysiological traits (e.g. ion and DOC concentration, diet, or hypoxia tolerance) it is certainly an interesting area for future research. Teleosts in the Order Characiformes, the most abundant order in Rio Negro, are generally insensitive to low pH and have high maximum transport capacity (Jmax), high‐affinity (= low Km) ion transport systems which continue to provide high rates of unidirectional Na+ uptake (i.e. influx) at low pH; rates may even increase under very acidic conditions (Gonzalez et al. 1997, 2002, 2018, 2021b; Gonzalez and Preest 1999; Duarte et al. 2013; Wood et al. 2014). 31 Unidirectional Na+ efflux rates are also quite resistant to low water pH. Indeed, ionoregulation in neon tetras (Paracheirodon innesi) and tambaqui (Colossoma macropomum) appears to be unaffected down to a water pH of 3.5 (Gonzalez and Preest 1999; Gonzalez et al. 2021b). Notably, Na+ influx rates in characid species exhibiting this strategy are also generally insensitive to most drugs that inhibit Na+ transport, including those (e.g. 100 µmol L-1 each of amiloride, 5‐N, N dimethyl amiloride, 5‐N‐methyl‐N‐isopropyl amiloride, 5‐N, N-hexamethylene amiloride, benzamil, and vanadate [Na3VO4], 10–100 µmol L-1 of phenamil, and 50 µmol L-1 of 5‐N‐ethyl‐N‐isopropyl amiloride]), that are known to block the standard NHE and V‐ H+ ATPase/Na+‐channel systems described earlier (Figure 2.2; Gonzalez and Preest, 1999; Preest et al. 2005; Wood et al. 2014). On the one hand, this could indicate that H+ may not be necessary as the counter‐ion for Na+ uptake. On the other hand, the carbonic anhydrase inhibitor acetazolamide (100 µmol L-1) reduced Na+ uptake in some studies but not others (Gonzalez and Preest 1999; Preest et al. 2005; Wood et al. 2014), whereas 0.06–0.10 µmol L-1 AgNO3 (a less specific, but more potent, rapidly acting carbonic anhydrase blocker and a more slowly acting Na+/K+‐ATPase inhibitor; Morgan et al. 2004) quickly eliminated both Na+ and Cl- uptake in two studies (Preest et al. 2005; Wood et al. 2014). These results suggest that both processes are dependent on H+ and HCO3 provision by carbonic anhydrase. Therefore, whether H+ is required as a counter‐ion for Na+ uptake remains unclear (Wood et al. 2014). These authors also found that branchial Na+/K+‐ATPase could be activated by NH4+ just as effectively as by K+ (Figure 2.2A, B). Based on this and other evidence, Wood et al. (2014) proposed that Na+ uptake was dependent on ammonia excretion, but that ammonia excretion was not dependent on Na+ uptake, but Gonzalez et al. (2018) argued against this interpretation. Regardless, the studies described above suggest that the characid transport mechanism appears to be unique, and does not fit 32 current transport models. The other ionoregulatory strategy, employed by members of another abundant teleost Order in the Rio Negro, the Cichliformes, as well as the elasmobranch Rajiformes (freshwater stingrays) is to greatly limit but not eliminate net ion loss at low pH. The diet may be used to make up the deficit. These species employ a pH‐sensitive, low‐affinity (= high Km) ion transport system; transport capacity is variable but often low (Gonzalez et al. 2002, 2005, 2021a; Wood et al. 2002; Duarte et al. 2013). Recent reports indicate there may be some variability within the cichlid strategy. For example, responses to a Na+ channel blocker (phenamil) varied (Gonzalez et al. 2017), as did kinetic characteristics and the degree of resistance of Na+ uptake to inhibition by low pH (Gonzalez et al. 2017, 2018). While most Rio Negro species in the Order Cichliformes have a low‐affinity ion transport system (= high Km) as described above, Tapajos cichlids (Geophagus sp) and keyhole cichlids (Cleithracara maronii), both native to ion‐poor water similar to that of Rio Negro but endemic to neighboring regions, were found to have high‐affinity (= low Km) Na+ transporters (Gonzalez et al. 2021a). The Tapajos cichlid in particular was an outlier, in being similar to members of the Order Characiformes, (but unlike keyhole cichlids), in having both a high affinity (= low Km) and high maximum transport capacity (Jmax) Na+ transport system. The Tapojos cichlid is the first cichlid described to display this transport pattern (Gonzalez et al. 2021a). Overall a low‐affinity system is more energetically economical, compared to a high‐affinity, high‐capacity system so long as efflux remains low (Gonzalez and Dunson 1987). Indeed, in Amazonian species showing this strategy, efflux rates are extremely resistant to stimulation by low pH, which may be a unique adaptation (Gonzalez et al. 2002, 2005; Wood et 33 al. 2003; Duarte et al. 2013). As outlined below, DOC may play a role. The Na+ and Cl- uptake systems in this group have been pharmacologically characterized with a wide range of antagonists only in the freshwater stingrays (Potamotrygonidae sp.), where they appear to be similar to those of standard freshwater teleosts (Wood et al. 2002). At low pH, Na+ uptake in angelfish (Pterophyllum scalare) was inhibited both competitively and noncompetitively (Duarte et al. 2013). Non-competitive inhibition may be due to the observed acute reduction in N-ethylmaleimide (NEM)‐sensitive branchial ATPase activity, but not in Na+/K+‐ATPase activity (Duarte et al. 2013). The specificity of NEM has been challenged (Forgac 1989), but Nawata et al. (2007) directly tested the same NEM concentration against 10 μM bafilomycin on trout gill, and found the same results with the two inhibitors. This has been interpreted as evidence for the involvement of H+‐ATPase; however, NEM is not a specific inhibitor of this enzyme so other ATPases cannot be ruled out. 2.7 The protective and supportive effects of natural DOCs on ionoregulation DOC can alter or stabilize biological membranes such as the gills and appears to be particularly effective in this regard at low pH, thereby mitigating the negative impacts of ambient acidity (Karns 1983; Freda et al. 1990; Gonzalez et al. 1998; Wood et al. 2011; Nelson 2015). Given the complexity of the composition of DOC, it is extremely difficult to determine the mechanism(s) of these interactions. However as noted earlier, allochthonous, darkly colored DOCs with a high aromatic content of humic substances and high PBI and SAC340 values seem to exert the greatest protective effects on ionoregulation (Wood et al. 2011; Al-Reasi et al. 2013a). Studies to date have suggested that paracellular tight junctions, apical ion transporters, and basolateral Na+/K+‐ATPase may be the direct or indirect targets of these DOC effects 34 (Gonzalez et al. 2005). With respect to paracellular junctions, the presence of DOC (6–15.5 mg L-1) has been shown to reduce the efflux rates of Na+ and Cl- across the gills in a variety of species, both at circumneutral and acidic pHs, but often with more pronounced effects in the latter (Gonzalez et al. 2002, 2005; Wood et al. 2002; Al-Reasi et al. 2016; Duarte et al. 2016, 2018). In freshwater stingrays, the protective effects of the natural DOC of Rio Negro blackwater at pH 4 were mimicked by a 10‐fold increase in environmental Ca2+ concentration (in the absence of DOC), suggesting that DOC had the same “tightening” actions on the paracellular junctions as those of Ca2+ discussed earlier (Wood et al. 2003). Thus, the normal displacement of Ca2+ from tight junctions by high H+ concentration may be prevented by DOC, or DOC may somehow replace Ca2+. However, in some other native Rio Negro species, Ca2+ was not protective, suggesting that other mechanisms must occur in other species (Gonzalez et al. 1998; Gonzalez and Preest 1999). As discussed below, the hyperpolarizing effects of DOC on the TEP across the gills (Figure 2.3; Galvez et al. 2008) also suggest action on the paracellular pathway, but one that is different from the depolarizing effect of Ca2+ (McWilliams and Potts 1978; Wood et al. 1998). In addition to reducing ion loss, DOC may minimize or reverse the inhibitory effects of low pH on active ion uptake, possibly by acting on apical and basolateral membranes. A consistent theme appears to be an increase in maximum transport rate (Jmax) for Na+, as well as for Cl- and Ca2+, as revealed by concentration–kinetic analysis (Wood et al. 2003; Matsuo et al. 2004; Glover et al. 2005; Glover and Wood 2005; Al-Reasi et al. 2016). This stimulation of Jmax could be explained by the increased total gill Na+/K+‐ATPase activity, which could secondarily drive Cl- uptake. McGeer et al. (2002) reported that chronic exposure of trout to elevated DOC resulted in greater branchial Na+/K+‐ATPase activity, and a similar phenomenon was recently 35 reported in zebrafish (Sadauskas‐Henrique et al. 2021). It could also be explained by a higher abundance or more efficient functioning of apical transport sites. For example, if DOC actually binds to the gill surface, it might increase the local concentration of ions such as Na+, Ca2+, and Cl− available to apical transporters as has been proposed for gill and body mucus (Handy 1989; Handy et al. 1989). DOC may also act as a buffer in the external microenvironment of the gills so as to minimize the inhibitory effects of low pH on apical Na+ uptake transporters (Wood et al. 2003; Al-Reasi et al. 2016). Finally, in a related explanation to be discussed in a subsequent section, through its ability to facilitate ammonia excretion, DOC might improve the local electrochemical gradient for Na+ uptake, thereby promoting the coupling of Na+ influx to ammonia excretion. Most of the above explanations assume that DOC directly interacts and binds with gill membranes (Figure 2.4). Physiological evidence supporting this idea is that protective effects on ionoregulation appear to increase with prior acclimation to DOC (Matsuo et al. 2004). In zebrafish (Danio rerio), after 7 days of pre-exposure to natural allochthonous DOCs, the protective effects on Na+ influx and efflux during low pH exposure persisted even when the DOC was removed during the 3‐h period of low pH challenge (Duarte et al. 2016, 2018). Furthermore, the protective effects of high DOCs against copper (Cu) and cadmium (Cd) binding to the gills of tambaqui were consistent with the effects of high Ca2+ levels, and in both cases persisted even when DOC or Ca2+ was not present during the metal exposures (Matsuo et al. 2005). DOC molecules generally bear net negative charge at circumneutral pH, so a priori, it is not intuitive how they interact with the freshwater fish gill. The latter is usually considered to bear net negative charge, explaining its high binding affinity for metallic cations (Reid and 36 McDonald 1991). However, DOC molecules are also generally amphiphilic, with hydrophilic and hydrophobic components (Figure 2.1). Hydrophobic groups contribute to lipophilicity, and these parts of the molecule could conceivably bind to or dissolve in the lipoprotein gill cell membranes. Al-Reasi et al. (2011) found no relationship between DOC lipophilicity and the ability of DOC to bind to and detoxify cationic metals. This is perhaps not surprising, because metal binding would occur at anionic (hydrophilic) sites. However, at low pH, where DOC molecules are most effective in supporting ionoregulation, much of the negative charge on both the gills and the DOC molecules will be removed by H+ titration, resulting in ligands that on an overall basis would be more hydrophobic and lipophilic, thereby promoting interaction. Campbell et al. (1997) demonstrated by transmission electron microscopy that DOC molecules can bind directly to the surface of living membranes of algae, and proposed that the same would occur with fish gill cells. They presented electrophysical evidence that this phenomenon increased at ambient low pH (4 versus 7) in both fish gills and algal cells. These workers proposed that binding was either a hydrogen-bonding sorption mechanism, whereby electronegative functional groups of DOC form hydrogen bonds with the biological surfaces or due to the formation of hydrophobic bonds between the hydrophobic domain of DOC and the plasma membrane (Figure 2.4). The direct binding of DOC molecules may alter the total charge or stabilize tight junctions in the paracellular channels of the gills which in turn may alter the permeability ratio between Na+ and Cl−, thereby altering the TEP (Galvez et al. 2008). Alternately or additionally, the hydrophobic domain of DOC could indirectly alter the activity of Na+ transport sites by changing the fluidity of the lipoprotein bilayers in the transcellular pathway (Wood et al. 2011). Indeed, Vigneault et al. (2000) demonstrated that DOC could alter the permeability of algal cell membranes in a pH‐dependent fashion. 37 Finally, as noted earlier for commercial humic acid, not all highly allochthonous, highly aromatic DOCs are necessarily protective, and indeed even natural DOCs may lose their protectiveness during storage. In nonnative zebrafish, a highly colored DOC, freshly collected and isolated from the upper Rio Negro at São Gabriel da Cachoeira (SGC), with a very high SAC340, was extremely protective against ionoregulatory disturbance caused by acute low environmental pH exposure (Duarte et al. 2016). However, after 2 years of refrigerator storage, it had lost about half of its color as indicated by the decline in SAC340, and the mean MW had also declined, though the relative distribution (quantified by PARAFAC) of humic acid-, fulvic acid‐, and amino acid‐like components remained unchanged. When tested at this time, SGC DOC exacerbated rather than protected against ionoregulatory disturbance in a native species, the tambaqui, even though it still exerted hyperpolarizing effects on TEP (Sadauskas‐Henrique et al. 2019). Unfortunately, species differences and the potential degradation of the DOC confounded interpretation in that investigation. However, in a very recent study, Sadauskas‐Henrique et al. (2021), reported that this stored SGC DOC, now even older, did not protect against (and indeed exacerbated) ionoregulatory disturbance in zebrafish acutely exposed to pH 4. This result, now on the same species, strongly suggests that some or all of the protective effects of DOC on ionoregulation may be lost during long‐term storage, even if other effects (e.g. stimulation of Na+/K+‐ATPase activity, hyperpolarization of TEP, positive effects on ammonia excretion) persist. 2.8 Acid-base balance at circumneutral and acidic pHs In “standard” freshwater fish, ventilatory control of acid–base status is minimal, so acid–base homeostasis between the external environment and internal extracellular fluid is maintained 38 mainly by the branchial exchange of acid–base equivalents for Na+ or Cl- respectively, thus linking acid–base balance to ion transport (Goss and Wood 1990; Wood 1991). Acid–base exchange and ion uptake occur simultaneously through the gills where H+ (“acid”) is exported in exchange for Na+ and HCO3- (“base”) is exported in exchange for Cl-, as described above. In addition, differential rates of net Na+ versus net Cl- loss, or net Na+ versus net Cl- gain, will constrain net acid or base fluxes. This is because overall acid–base balance must conform to the constraints of electrical neutrality, as recognized by strong ion difference (SID) theory (Stewart 1983). In simple terms, if net fluxes of the major strong cation (i.e. Na+) and strong anion (i.e. Cl-) are equal, there can be no net acid–base flux. If net Na+ loss exceeds net Cl- loss, net acid uptake (= base loss) must occur. If net Cl- loss exceeds net Na+ loss, net acid excretion (= base gain) must occur. The diversity in ionoregulatory mechanisms described above may be reflective of acid–base demands due to the activity and habitat of a particular species. Increased activity as well as inhabiting anoxic or acidic waters disturbs internal acid–base balance and requires greater ion transport capacity to restore balance. Species that inhabit moderate environments (i.e. circumneutral pH) do not have as large an environmental threat to acid–base status and can afford to have lower rates of acid–base relevant ion flux (Gonzalez et al. 2002). As reviewed by Wood and McDonald (1982) and Wood (1989), during the acid‐rain crisis of the 1970s–1980s in the northern hemisphere, blood acidosis was initially thought to be an important part of the toxic response in fish. Studies on rainbow trout demonstrated that net acid uptake occurred at the gills due to differential inhibition of Na+ and Cl- uptake and stimulation of efflux processes, such that net Na+ loss exceeded net Cl- losses. Blood pH dropped during low pH exposure, and the trout were only able to partially compensate by increasing net acid excretion in the urine via the kidney (McDonald et al. 1980, 1983; McDonald and Wood 39 1981; Wood and McDonald 1982; McDonald 1983). However, it later became apparent that this clear acid–base response occurred only when the fish were acclimated to relatively hard water, high in Ca2+ concentration (mmol L-1 range). When experiments were performed in soft water with low Ca2+ levels (<250 µmol L-1 range), Na+ and Cl- losses were even greater, but there was little uptake of acid at the gills and blood acid–base disturbance was negligible, because Na+ and Cl- losses were approximately equal, in accord with SID theory (Stewart 1983). The low water Ca2+ situation seems to be the environmentally relevant one in nature, because these waters are generally also low in alkalinity and buffer capacity, and are therefore the ones that are easily acidified. Certainly, this is the situation in most Amazonian waters (Ca2+ < 250 µmol L-1), and particularly in the Rio Negro watershed (Table 2.1) where, as noted above, Ca2+ may be less than 10 µmol L-1 (Val and De Almeida-Val 1995). There appear to be few investigations of the acid–base responses of native fish to low pH exposure under natural soft water conditions. A study by Wilson et al. (1999) demonstrated that net acid fluxes were altered in only one of the three tested freshwater Rio Negro native fish species upon exposure to low pH (3.5–5). Net acid fluxes were positive (acid uptake or base excretion) in all three species under control conditions (pH 6); however, when exposed to low pH, net acid uptake decreased in matrinchã (Brycon erythropterus), and did not change in either tamoatá (Hoplosternum littorale) (which died) or tambaqui (which survived), though all three suffered ion losses to the water, which were greatest in tamoatá and least in tambaqui. In all three, the net acid fluxes were relatively small. A parallel study on tambaqui revealed only a small disturbance of internal acid–base status, plasma ions, and associated blood parameters down to a water pH of 4, with some changes at pH 3. The physiological pH limit of tambaqui appears to be 3–3.5 at which point permanent damage occurs to ionoregulatory mechanisms 40 (Wood et al. 1998; Gonzalez et al. 2021b). Therefore, this species is 10–100‐fold more H+-tolerant than the rainbow trout, but still appears to conform to the same pattern of negligible acid–base disturbance in low Ca2+ waters. Unfortunately, all of these studies were performed in soft ground waters almost devoid of DOC, and there is a need to repeat them in natural soft water high in natural allochthonous DOC. 2.9 Electrical properties of the gill (TEP) at circumneutral and acidic pHs TEP across freshwater fish gills is almost entirely a diffusion potential between the external medium and the blood plasma (Potts 1984). While some authors have suggested that an electrogenic component may also contribute to TEP in freshwater fish (e.g. Evans, 1980), there is little evidence supporting this (Kirschner 2004; Wood et al. 2020; Po and Wood 2021). At circumneutral pH this diffusion potential arises predominantly from the differential permeability of the gills to Na+ versus Cl-, with ion movements generally believed to occur via the paracellular pathway. The resulting TEP is inside negative as the Na+ permeability is higher than that of Cl- (Potts 1984). Transepithelial diffusion is dependent on the concentration gradient, TEP, branchial surface area, and epithelial permeabilities to the various ions (Gonzalez et al. 2002). Therefore, knowledge of fish gill electrophysiology is essential in the interpretation of ion movement across the gills, as has become apparent from recent studies on salt toxicity (Wood et al. 2020; Po and Wood 2021). DOC, much like other water quality parameters (e.g. hardness, pH and salinity; Potts, 1984) may have a large impact on the electrical properties of the gill (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019). Wood et al. (1998) demonstrated that TEP in tambaqui increased from negative values in pH 6.5 water to positive values in pH 4 water. This depolarization in response to relatively low 41 pH was similar to that observed earlier in brown trout and rainbow trout (McWilliams and Potts 1978; Ye et al. 1991). Elevated ambient Ca2+ concentration at circumneutral pH shifted TEP to become more positive in tambaqui and brown trout but slightly moderated the hyperpolarizing effect of low pH exposure (McWilliams and Potts 1978; Wood et al. 1998). Thus, as discussed earlier, while both DOC and Ca2+ may help to reduce the ion permeability of the gill, especially at low pH, they have opposite effects on TEP (Figure 2.3), suggesting dissimilar mechanisms of action. DOC appears to directly influence gill TEP in rainbow trout both in vitro and in vivo (Galvez et al. 2008). Exposure of cultured gill epithelia from rainbow trout in vitro at circumneutral pH to various DOCs collected in Ontario, Canada resulted in hyperpolarization (Galvez et al. 2008). Ca2+ activity measurements eliminated the removal of Ca2+ from solution by DOC‐complexation as a possible indirect cause of the hyperpolarization. The magnitude of this hyperpolarization was strongly correlated to the SAC340 values of the various DOCs, suggesting that the aromaticity of the molecules directly influences the electrophysiology of the fish gill (Galvez et al. 2008). Allochthonous isolates had large effects, while autochthonous isolates had only small effects. This study showed that similar, but slightly reduced hyperpolarization also occurred in response to DOC exposures in vivo (Galvez et al. 2008). These effects were reversible and likewise correlated to the aromaticity of the DOC molecules. Galvez et al. (2008) offered two explanations for the attenuated hyperpolarization reported in vivo. DOC may have affected the paracellular permeability of the cultured epithelia to a greater extent compared to the whole animal, or diffusive permeability was counteracted by the electrogenic uptake of ions initiated by DOC in vivo (Galvez et al. 2008). To date, there are no data to support the latter possibility. Nevertheless, the more negative internal TEP would 42 certainly favor the uptake of all cations, including Na+. Regardless, differentially altered membrane permeability to Na+ versus Cl- upon exposure to DOC may be due to the abundance of charged functional groups in DOC that may influence the electrical properties of the paracellular pathway, or the entire gill epithelium (Campbell et al. 1997; Galvez et al. 2008). While both low pH and DOC individually alter TEP, DOC may offer protection over changes in the electrical properties of the gill in response to low pH. Consistent with previously described TEP results in salmonids at low pH (McWilliams and Potts 1978; Ye et al. 1991), exposure of tambaqui to low pH caused depolarization (Wood et al. 1998; Sadauskas‐Henrique et al. 2019). However, exposure to DOC from SGC at circumneutral pH caused hyperpolarization, and the DOC completely mitigated the depolarization of TEP at low pH (Sadauskas‐Henrique et al. 2019). This occurred despite the inability of this DOC to protect against net ion loss at low pH, perhaps because it had degraded during storage, as discussed earlier. Mean measured losses of Na+ and Cl- were about equal, in accord with no net acid–base disturbance, as would be expected in the low [Ca2+] water in which the study was performed. It appears as though the discrepancy of relative permeabilities of Na+ and Cl- seen at circumneutral pH is diminished in low pH as indicated by depolarization in acidic water (Sadauskas‐Henrique et al. 2019) 2.10 Ammonia transport Ammonia, derived from the degradation of proteins, nucleic acids, purines, and pyrimidines, is the primary waste product of nitrogen metabolism in teleost fish (Wood 1993; Wilkie 1997). Ammonia production is less metabolically demanding than urea and is promptly excreted via the gills to prevent toxicity. Overall, Amazonian fish native to acidic waters are 43 more sensitive to ammonia toxicity than “standard” fish endemic to circumneutral waters in North America, when compared at a common pH 7 (Souza-Bastos et al. 2017). In other words, toxicity occurs at lower total ammonia and lower NH3 concentrations. This may be because Amazonian species both evolved and presently live at low pH, where the NH3 fraction is lower. Given that NH3 is the more toxic form of ammonia relative to NH4+ and is the form that diffuses into the fish across the gills, thereby setting the blood levels (Randall and Tsui 2002; Chew et al. 2005; Walsh et al. 2007), and Amazonian species have had less exposure to NH3, they are in turn less resistant to it. While ammonia transport across the gills has been extensively investigated, the specific mechanisms involved have been historically controversial (Wood 1993; Wilkie 1997; Wright and Wood 2009). Our understanding was revolutionized by the relatively recent discovery of Rh glycoproteins in the gills and their involvement in facilitating ammonia excretion (Nakada et al. 2007; Nawata et al. 2007, 2010). This “Rh‐mediated Na+/NH4+ exchange” model has been reviewed by Wright and Wood (2009, 2012), where apical transport has been described as a metabolon involving several membrane transporters (apical Rhcg, V‐type H+‐ ATPase, Na+/H+ exchanger NHE‐2 and/or NHE‐3, Na+ channel, carbonic anhydrase) creating a Na+/NH4+ exchange complex which accounts for the variable linkage of Na+ uptake and net ammonia efflux. The overall model (Figure 2.2B) suggests that Rhag moves NH3 out of the erythrocyte into the plasma, and Rhbg facilitates the transit of NH3 across the basolateral membrane of the branchial ionocyte. Then the multiple membrane transporters (including Rhcg) working as an apical Na+/NH4+ exchange complex provides an acid trapping mechanism for apical export, as described earlier. The already complex mechanism(s) of ammonia excretion in freshwater fish is certainly influenced by low ambient pH and elevated DOC concentrations. To our knowledge, 44 there have been no molecular investigations of the “Rh‐mediated Na+/NH4+” exchange complex in fish endemic to acidic, DOC‐rich tropical waters, but as outlined below, some physiological investigations cast light on this issue. In the oscar (Astronotus ocellatus), a member of the Cichliformes that would likely have the “standard” Na+ uptake systems, Na+ influx and ammonia excretion appeared to be coupled under normoxic conditions at circumneutral pH, but this coupling disappeared under acute hypoxia (Wood et al. 2007). The tambaqui, a member of the Characiformes that exhibits the unique H+‐resistant Na+ uptake system, was able to maintain ammonia excretion against a high external ammonia concentration (2.5 mmol L-1), but it remains unclear whether the observed ammonia excretion was active (Wood et al. 2017). These findings are compatible with the “Rh‐mediated Na+/NH4+” model. However, based on pharmacological tests on three endemic members (“tetras”) of the Characiformes, in which ammonia excretion appeared to be independent of Na+‐uptake and persisted in its absence (Wood et al. 2014), it was suggested that the model did not apply. High ambient NH4+ resulted in increased Na+ influx in the cardinal tetra (Wood et al. 2014) and the black neon tetra, as well as in an African characiform, the Congo tetra, Phenacogrammus interruptus (Gonzalez et al. 2017), in contrast to the general inhibition of Na+ uptake caused by this treatment in cichlids, including the oscar (Gonzalez et al. 2017, 2021a). However, not all species of Characiformes showed an increase in Na+ uptake in high environmental ammonia, in fact most tetras showed no stimulation, including the black neon tetra, Hyphessobrycon herbertaxelrodi, (Gonzalez et al. 2017, 2018). Based on an earlier model originally proposed by Randall et al. (1996), Wood et al. (2014) proposed that Na+ uptake was nevertheless dependent on ammonia excretion in the cardinal tetra, driven by active NH4+ entry via a competition on the K+ site of basolateral Na+/K+‐ATPase, where it was equally or more 45 effective than K+ in enzyme activation (Figure 2.2A, B). With respect to responses to low environmental pH, Wood et al. (1998) demonstrated that internal total ammonia levels in tambaqui remained constant upon exposure to pH values as low as 4 in very soft water, but doubled from control levels at pH 3. Recovery was incomplete when water pH was returned to 6.5. This trend was likewise described in a parallel study by Wilson et al. (1999) in tambaqui as well as two other Amazonian teleosts, matrinchã and tamoatá: only modest changes in branchial ammonia excretion occurred down to pH 4, but marked stimulation occurred at pH 3.5. The mirrored response of plasma cortisol in tambaqui was suggested to be an important contributor to elevated plasma ammonia in low pH due to the known effect of cortisol in promoting proteolysis (Wood et al. 1998). A later study confirmed unchanged ammonia excretion down to pH 4 in this species (Wood et al. 2018). However, all the above‐mentioned investigations (except Wood et al. 2014) were performed in ion‐poor water essentially lacking DOC. The presence of DOC influences the ammonia excretion response of fish to low pH exposure. Sadauskas‐Henrique et al. (2019) found increased ammonia excretion at pH 4 in tambaqui when SGC DOC was present, whereas there was no change in the absence of DOC. A similar response with SGC DOC was seen in zebrafish (Sadauskas‐Henrique et al. 2021), even though both studies used long‐term stored DOC. Ammonia excretion was similarly increased by 60% in stingrays exposed to pH 4 in fresh DOC‐rich natural Rio Negro water, but not in matching reference water lacking DOC (Wood et al. 2003). Amiloride and amiloride analogues inhibited both Na+ uptake and ammonia excretion in the stingrays in the DOC‐rich water at circumneutral pH (Wood et al. 2002). These stingray results, before the discovery of the “Rh‐ mediated Na+/NH4+ exchange” model (Wright and Wood 2009), were interpreted as inhibition of 46 “diffusion trapping” of NH3 in the gill boundary layer caused by the blockade of Na+‐coupled H+ efflux. In fact, they fit the model well. DOC would act by partially protecting Na+ influx in low ambient pH so it may also influence H+ extrusion and in turn lead to elevated ammonia excretion (Wood et al. 2003), though other explanations are possible. Freshly collected Rio Negro SGC DOC also appeared to maintain Na+ coupling to ammonia excretion in zebrafish exposed to low pH in ion‐poor water suggesting that DOC supports this coupling via the Rh metabolon (Duarte et al. 2016). Increased ammonia excretion can therefore drive elevated Na+ uptake in acidic water (Duarte et al. 2016). Another allochthonous DOC from Luther Marsh provided similar protection to zebrafish at low pH (Duarte et al. 2018), and in both studies this persisted after prior acclimation to DOC, even if the DOC was removed during the period of low pH challenge. This again suggests that the binding of the amphiphilic DOC molecules to the gill surfaces (Figure 2.4) influences ionocyte physiology, including the persistence of the coupling of Na+ uptake to ammonia excretion at low pH. Interestingly in daphnia, natural DOCs had exactly the opposite effect, reducing ammonia excretion at low pH without affecting Na+ flux rates (Al-Reasi et al. 2013b). 2.11 Amelioration of metal toxicity Increasing pollution by metals is one of the many anthropogenic pressures currently threatening the entire Amazon watershed (Duarte and Val 2020). In “non‐polluted” Rio Negro waters, the concentrations of major metals are low (e.g. 0–2 μg L-1; Holland et al. 2017; Wood et al. 2003), generally below the levels used in toxicity studies (10‐fold or more greater), but the situation is different where there are anthropogenic inputs. For example, Pinto et al. (2008) reported water-borne Cu and Cd concentrations of 10–50 and 8–90 μg L-1, respectively in several 47 tributaries in “natural areas” of the Rio Negro in the region of Manaus. In areas with heavy industrial inputs, the measured water Cu was up to 2100 μg L-1 and Cd was up to 590 μg L-1 (Geissler 1999; Pinto et al. 2008, 2009). All of these elevated concentrations are in the range of potential acute toxicity. DOC is a well‐recognized mitigating factor of metal toxicity, however, the mechanistic details of its protective nature remain poorly understood because of the structural irregularity, heterogeneity, and complexity of DOC (Al-Reasi et al. 2011). Nevertheless, as noted earlier, there is a general relationship whereby DOCs with high SAC340 values also generally have high PBI values, and both of these indices correlate with a high protective ability against metal toxicity, as well as a high capacity to exert direct biological effects on organisms (Al-Reasi et al. 2013a). The latter is important because it has been argued that only part of the protective actions of DOC against metal toxicity is explained by its ability to complex metal cations so as to reduce their bioavailability; the other part is due to the direct beneficial effects of DOC on ionoregulation due to its actions on gill membranes as discussed earlier (Crémazy et al. 2016; Wood et al. 2011; Figure 2.4). DOCs with high SAC340 and PBI values are typically darkly colored, highly aromatic, and allochthonous, with high humic acid content. Rio Negro DOCs, especially those from the upper part of the river such as SGC samples (Duarte et al. 2016) have these characteristics. Metal toxicity is alleviated by DOC in a concentration-dependent manner (e.g. Crémazy et al. 2017) as DOC decreases the bioavailability of metal cations by chelating and thereby altering their speciation (Figure 2.4; Al-Reasi et al. 2011; Hollis et al. 2001; Playle et al. 1993). In accord with their lower PBI and SAC340 values (Al-Reasi et al. 2013a; Duarte et al. 2016), autochthonous DOCs are less effective against metal toxicity than terrigenous (allochthonous) 48 DOCs (Richards et al. 2001; Luider et al. 2004; Schwartz et al. 2004). This is true for copper (Cu) and lead (Pb) toxicity and may influence the toxicity of silver (Ag), cadmium (Cd), and inorganic mercury (Hg), but there are insufficient data to draw definitive correlations between these latter metals and the effect of DOC with regard to quality and source (Al-Reasi et al. 2011). Most cationic metals act to disrupt ionoregulatory processes at the gills (Wood 2001; Niyogi and Wood 2004). Therefore, very soft, acidic ion‐poor waters such as Rio Negro blackwaters, are expected to exacerbate metal toxicity as there is a low concentration of ions for uptake, including a low concentration of protective cations (e.g. Ca2+) to compete with metals for important binding sites on fish gills such as those that regulate tight junction permeability. Additionally, the low pH ensures that dissolved metals will occur mainly as free cations and will tend to liberate metallic cations (Mn+) from DOC by H+ competition. These species (i.e. Mn+) can more readily interact with the fish gill, leading to increased toxic responses. In Amazonian fish, residing in extremely soft water, responses to only three metals have been studied in detail so far—copper (Cu), cadmium (Cd), and nickel (Ni). A fourth, Ag, has been used pharmacologically as a very effective inhibitor of Na+ and Cl- uptake in both characid and cichlid fishes (Preest et al. 2005; Wood et al. 2014; Gonzalez et al. 2021a), probably reflecting its ability to block both carbonic anhydrase quickly and Na+/K+‐ATPase more slowly (Morgan et al. 2004). In most fish, Cu increases diffusive permeability of the gills, thereby elevating ion efflux rates, inhibits active ion uptake, and decreases the density of mitochondrial‐rich cells within the gills causing ionoregulatory disruption leading to toxicity; Na+ regulation is particularly affected (Laurén and McDonald 1985). The eventual cause of death appears to be circulatory failure induced by high net losses of ions, similar to that caused by low pH (Wood 2001). Additionally, 49 at sublethal levels in soft water, Cu is a potent inducer of oxidative stress (Craig et al. 2007). In accord with expectation, Cu toxicity was found to be generally high (i.e. very low LC50 values) in 10 native ornamental species tested in a typically ion‐poor Amazonian softwater, and this was alleviated when Na+ and Ca2+ levels were raised (Duarte et al. 2009; Figure 2.4). Characiformes were the most sensitive to Cu, suggesting that the unique nature of their Na+ uptake mechanisms could be a contributory factor. In a recent study (R Duarte, personal communication, later published as Duarte et al. 2024), Characiformes were again the most sensitive Order to Cu, relative to Cichliformes and Siluriformes (catfish). Therefore, in Figure 2.5 we have plotted the affinity (Km) for Na+ uptake determined by Gonzalez et al. (2002) against the LC50 values reported by Duarte et al. (2009) for five of the same species. There appears to be at least a weak positive hyperbolic relationship (p < 0.10) in which the Characiformes with the unique Na+ uptake system with high affinity (low Km) tend to exhibit greater sensitivity to Cu. Perhaps greater affinity for Na+ translates to a greater affinity for Cu2+, when the ambient Cu2+ is at a toxic level, as the two cations may share an uptake mechanism under these conditions (Grosell and Wood 2002). There were no significant relationships with Jmax or efflux rates of Na+. Interestingly, when exposed to the same relatively low concentrations of Cu (∼20 µg L-1 = half of the LC50s), oxidative stress dominated in the dwarf cichlid (Apistogramma agassizii), a member of the Cichliformes (Braz-Mota et al. 2018), whereas ionoregulatory disruption dominated in the cardinal tetra (P. axelrodi), a member of the Characiformes (Crémazy et al. 2016; Braz-Mota et al. 2018). Interestingly, Na+ uptake in the oscar, another cichlid with a relatively high Km (Wood et al. 2007), was also very resistant to inhibition by Cu (Gonzalez et al. 2021a). However, it should be noted that another member of the Characiformes, the tambaqui, 50 appeared to be extremely tolerant of Cu with LC50s 10–100‐fold higher than those in Figure 2.5 (Oliveira 2003; Tavares-Dias et al. 2011). In accord with this high Cu tolerance, very high levels (up to 400 µg L-1) had only modest effects to either inhibit Na+ uptake or stimulate Na+ efflux in the tambaqui (Matsuo et al. 2005). In this same study, prior acclimation to either added Ca2+ or added “foreign” DOC before Cu exposure was effective at decreasing Cu accumulation at the gills, even when these agents were no longer present during the Cu exposure. Taylor et al. (2002) suggested that both the number of binding sites and binding affinity for Cu on the gills are regulated by Ca2+ acclimation. DOC may have similar effects on the binding properties of the gill. High levels of dietary Cu also had negligible effects on the physiology of the tambaqui (Giacomin et al. 2018), again indicating that this species is unusually tolerant to Cu. One complication with all the above-cited Cu tests is that they were performed in Amazonian groundwater with an ionic composition very similar to that of Rio Negro blackwaters, but essentially devoid of native DOC. More recent tests with some of these same species have demonstrated that the presence of Rio Negro DOC at natural levels greatly ameliorated toxicity, raising LC50 levels up to 20‐fold. Indeed, it was concluded (R Duarte, personal communication, later published as Duarte et al. 2024) that DOC concentration was by far the most important component of water chemistry protecting against Cu toxicity in multiple Rio Negro species. In the case of cardinal tetra, DOC greatly ameliorated ionoregulatory disruption (Crémazy et al. 2016). A detailed analysis in the cardinal tetra indicated that only part of the protective effect of Rio Negro DOC could be attributed to the complexation of Cu by DOC, with the other part attributed to the direct beneficial effects of DOC on the ionoregulatory physiology of the gills (Crémazy et al. 2016; Figure 2.4). In this same species, the presence of suspended particles, as would occur when whitewater flows into blackwater, also greatly 51 alleviated toxicity by complexation of Cu, though the particles themselves were mildly disruptive to ionoregulation, perhaps by physical damage to the gills (Crémazy et al. 2019). In most fish, Cd disrupts calcium homeostasis, by blocking the active uptake of Ca2+ at the gills (Wood 2001; Niyogi and Wood 2004) specifically by competition at apical channels and by inhibiting basolateral Ca2+‐ATPase in branchial ionocytes (Verbost et al. 1987, 1989). Additionally, it has been suggested that soft water causes ionocyte proliferation (reviewed by Perry, 1997) potentially contributing to increased susceptibility to Cd toxicity (Matsuo et al. 2005). Therefore, Cd contamination may present a particular threat to fish in the Amazon basin due to the low Ca2+ concentration available to outcompete its binding to key gill sites (Playle et al. 1993). Mechanistic studies with Cd have been performed only with tambaqui. In contrast to the high tolerance of this species to Cu, the tambaqui appears to be very sensitive to waterborne Cd. While LC50 data are not available, in DOC‐free soft water, moderate levels of Cd exposure (10–80 µg L-1) for 24 h caused 50%–90% inhibition of Ca2+ uptake (Matsuo et al. 2005). Acclimation to added Ca2+ or added foreign DOC before Cd exposure was effective in decreasing Cd accumulation at the gills, even when these agents were no longer present, suggesting persistent protective changes in gill properties, as similarly seen with Cu exposure (Matsuo et al. 2005). In contrast to dietary Cu, dietary Cd, at the same level as used for Cu (500 μg Cd g kg-1 food), resulted in much greater internal accumulation, and marked effects on the internal metabolic physiology of tambaqui, again indicating its greater potency in this species (Giacomin et al. 2018). The toxic mechanism of Ni to fish is not well understood, in contrast to Cu and Cd. There is evidence of respiratory disruption, oxidative stress, and disturbances in the regulation of Ca2+, Mg2+, and iron (Fe2+/3+) (Brix et al. 2016). In general Ni toxicity occurs at concentrations several 52 orders of magnitude greater than those for Cu and Cd (high µg L-1 to low mg L-1 levels). Ni toxicity is known to be influenced by pH, DOC concentration and water hardness, making Amazonian waters ideal study sites, but to date, only the cardinal tetra has been investigated. Ni toxicity in cardinal tetra differed seasonally in DOC‐rich water with greater toxicity at pH 7 relative to pH 4, except during the wet season (Holland et al. 2017). Surprisingly Ni was especially toxic in water at pH 4 with high concentrations of allochthonous Rio Negro DOC. At pH 4, Ni toxicity was negatively related to FI and positively related to DOC concentration and the amount of humic and fulvic‐like components. Clearly DOC quality and pH interact in a complex manner to influence Ni toxicity. These interactions differ from those for other metals, and much more work is needed to understand their nature in acidic, DOC‐rich softwaters. 2.12 Concluding remarks Although there has been an increasing number of studies over the past two decades on the specific effects of DOC, pH, and ionic composition on ionoregulation, acid–base regulation, TEP, ammonia excretion, and metal toxicity in native fish, there remain large knowledge gaps. DOC‐rich acidic softwaters comprise ecosystems that are hotspots of biodiversity, but they are critically threatened by climate change, industrial discharges, population growth, and deforestation, especially in the Amazon. Key areas for future research include the following: • The unusual ion uptake and ammonia excretion mechanisms in Characiformes that are so resistant to low pH defy current models and should be investigated with molecular techniques. Members of the other native Orders should also be surveyed to see if this is a widespread strategy, or whether additional strategies for ionoregulation at low pH exist. 53 • Virtually nothing is known about the possible structural changes in the gill morphology that may occur when fish residing in these waters are faced with ionoregulatory challenges. Comparison with the vast amount of morphological information on non-native fish will prove instructive. • The mechanistic basis of the apparent positive effects of DOC on ionoregulation and associated functions needs to be much better understood. Studies to date have been correlational rather than mechanistic, and many have used inappropriate DOCs. The use of native, freshly collected DOCs should be encouraged, as well as the use of well‐characterized “model” DOC compounds as experimental probes. It is quite possible that gill function in acidic DOC‐rich waters may be specific to the properties and quality of the native DOC. Given that DOC appears to interact with the gill boundary layer and/or surface, it may directly induce structural and molecular changes of the gills. • The effects of DOC on gill TEP, and its interactions with pH and Ca2+, remain particularly mysterious. A good starting point will be to determine whether these actions of DOC on gill TEP are concentration‐dependent, as they are for H+ and Ca2+. This should be investigated in several DOCs with different physicochemical properties, during exposure to different pH and Ca2+ levels. • With increased mining and industrial discharges (Duarte and Val 2020), as well as precipitation‐borne inputs of a variety of metals, there is an urgent need to better understand metal effects in tropical blackwaters. DOC is a valuable water quality parameter that clearly influences metal toxicity, and it has been incorporated into regulatory tools such as the biotic ligand model (BLM) (Niyogi and Wood, 2004). However, recent BLM analyses of Rio Negro Cu toxicity data have highlighted some uncertainties (Crémazy et al. 2016; Duarte et al. 2024). It 54 remains unclear whether the DOCs of tropical acidic blackwaters behave in the same ways as those of the northern hemisphere. It would be of special interest to understand whether the DOC functional groups that bind metals are the same as those that provide the beneficial ionoregulatory effects that have been described. Likewise, only three metals (Cu, Cd, and Ni) have been investigated in Amazonian fish from an environmental viewpoint. Of these only Cu has been studied in any detail, and results with Ni do not fit expected patterns. More extensive studies with a wider range of metals are needed. Exploring these mechanisms may aid in the creation of effective environmental regulations. 55 2.13 Chapter 2 – Tables Table 2.1. General water chemistry ranges for acidic, DOC‐rich black waters of the Rio Negro watershed, based on the experience of the authors and data of Duarte (2012) (in µmol L-1, except DOC which is in mg C L-1). Abbreviation: DOC, dissolved organic carbon. Parameter Range DOC 5-35 Na 5-50 K 0.2-30 Cl 8-70 Ca 0.1-20 Mg 0.3-10 pH 3.0-6.0 56 2.14 Chapter 2 – Figures Figure 2.1. The typical structure of (a) humic and (b) fulvic acids which typically comprise a substantial proportion of allochthonous DOC molecules Functional groups are circled (carboxylic groups, phenolic‐OH groups, aromatic units, quinone, sugar, aliphatic cha chains, and peptides). Functional groups responsible for characteristics of DOC (negative charge and lipophilicity) are noted (Stevenson 1994; Buffle 1997; Kinniburgh et al. 1998). DOC, dissolved organic carbon. 57 Figure 2.2. Models of transport processes in ionocytes of the freshwater fish gill. (a) proposed model of ion uptake pathways in the freshwater fish gill epithelium noting the effects of DOC, Ca2+, and low pH on ion transporters (b) proposed model of ammonia transport through the freshwater gill epithelium, noting the effects of DOC at low pH. DOC, dissolved organic carbon. 58 Figure 2.3. The interactive effects of dissolved organic carbon (DOC), pH, and Ca2+ on gill transepithelial potential (TEP) in freshwater fish. 59 Figure 2.4. A conceptual model of the interactive effects of DOC, low pH, and water Ca2+ and Na+ concentrations with respect to ionoregulation and metal toxicity at the gills of freshwater fish. Mn+ represents metallic cations. DOC, dissolved organic carbon. 60 Figure 2.5. The relationship between the affinity (Km values from Gonzalez et al. 2002) for Na+ uptake and the toxicity of Cu (96‐h LC50 values from Duarte et al. 2009) in five species of Rio Negro fish. The species to the left of the line are members of the Characiformes, whereas Corydoras is a catfish, and Apistogramma is a cichlid. 61 Chapter 3: A critical assessment of physicochemical indices used to characterize natural dissolved organic carbon (DOC), their inter-relationships, and the effects of pH. 3.1 Summary Dissolved organic carbon (DOC) is both ubiquitous and heterogeneous in freshwater. Freshwaters are browning universally, and pH values are decreasing with climate change. DOCs influence water pH, whereas changes in water pH potentially alter the conformation and function of DOCs. The physicochemical properties of DOCs can be characterized by optical and chemical indices, but the inter-relationships among them, and the effects of low pH, are not well understood. We characterized five naturally sourced DOCs, spanning large differences in origin and composition, at pH 7 and 4, using multiple indices: specific absorbance coefficient at 340 nm (SAC340), molecular weight index (MWI), fluorescence index (FI), octanol–water partition coefficient (log Kow), molecular charge (MC), proton binding index (PBI), size-fractionation, and percentage humic-acid-like, percentage fulvic-acid-like and percentage protein-like components by fluorescence-based parallel factor analysis. Many of the indices changed between pH 7 and 4 as reflected in the corresponding absorbance and fluorescence profiles. Generally, apparent aromaticity, apparent molecular weight and molecular charge all decreased with low pH, while lipophilicity increased. Key positive correlations occurred between aromaticity and apparent molecular weight, chemical reactivity and apparent molecular weight, and aromaticity and chemical reactivity, and a negative correlation between lipophilicity and molecular charge. These relationships were pH-dependent. Our results highlight that physicochemical indices used to characterize DOCs from distinct sources should consider pH and be interpreted carefully. The pH-dependent changes in many of the indices are likely alterations in the conformation, reflected 62 in the optical signatures, rather than changes in the composition of DOCs. In contrast, increased lipophilicity and reduced charge at lower pH are due to changes in the properties or composition of the DOC molecules, resulting from proton binding. The ecological functions of DOCs are dependent on source and will likely change with natural acidification events such as increasing atmospheric CO2. 3.2 Introduction Dissolved organic carbon (DOC) is a universal constituent of freshwater that is increasing worldwide with spatial and temporal variability ( Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025; Morris et al. 2021, see Chapter 2). Simultaneously, freshwater pH values are generally falling. This decrease in water pH can occur through sudden inputs of DOC-rich water, and over time through climate change ( Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; Quijada-Rodriguez et al. 2021). DOCs are primarily composed of humic substances (humic and fulvic acids) and various non-humic substances including amino acids, fatty acids, phenols, sterols, natural sugars, hydrocarbons, urea and porphyrins (Boggs et al. 1985; Gaffney et al. 1996). They are extremely heterogeneous, varying in quality and composition (i.e. chemical makeup of the molecule) based on origin and spatial, temporal, and seasonal factors. The dissociation of protons from humic substances acidifies water but DOCs also may indirectly alter pH by affecting other natural buffer systems that help to regulate pH (Erlandsson et al. 2010). Changes in water pH likewise potentially alter properties of DOCs, inducing changes in their fluorescence behaviour (Pullin and Cabaniss 1995; Patel-Sorrentino et al. 2002) and changes in 63 their conformation (i.e. spatial arrangement of the molecule) such as condensation or expansion of the molecules, probably associated with titration of negative charge by protons (Pace et al. 2012). As a result, the functional properties of DOC may change with pH (Wenk et al. 2021). In freshwater ecosystems, DOCs regulate both biotic and abiotic processes (Petersen 1991; Kullberg et al. 1993; Steinberg et al. 2006; Al-Reasi et al. 2011) and aquatic organisms are very sensitive to changes in DOC quality and concentration (Sucker and Krause 2010; Wood et al. 2011; Johannsson et al. 2017, 2020; Holland et al. 2018). Two well-established functional properties of DOC are their ability to bind cationic metals, thereby reducing toxicity, and their ability to exert generally beneficial physiological effects on osmoregulation in aquatic organisms. Both of these functions appear to vary with DOC type and are sensitive to pH (Morris et al. 2021, see Chapter 2; Wood et al. 2011). The ecological function of DOC is reflected in various optical and chemical indices. For example, there is evidence that DOCs that are more aromatic, more allochthonous, larger in molecular size, with greater humic acid content and with greater reactivity, are more effective at both detoxifying metals and exerting physiological effects (Wood et al. 2011; Al-Reasi et al. 2013a). These properties have been quantified by a variety of optical and chemical indices, as outlined below, but how they relate to one another and behave at different pH values is not well understood. Molecular variability of DOCs can be described by optical properties such as absorbance, fluorescence signatures and parallel factor analysis (PARAFAC) of fluorescence data (Al-Reasi et al. 2011; Wood et al. 2011). Indices have been developed to evaluate: aromaticity (specific absorbance coefficient at 340 nm, SAC340, Curtis and Schindler 1997), molecular weight (molecular weight index, MWI; Dahlén et al. 1996; Peuravuori and Pihlaja 1997), allochthonous 64 v. autochthonous origin (fluorescence index, FI, DePalma et al. 2011; McKnight et al. 2001; Namjesnik-Dejanovic and Cabaniss 2004), lipophilicity (log octanol–water partition coefficient, log Kow, Egeberg and Alberts 2002; Gjessing et al. 1999; Namjesnik-Dejanovic and Cabaniss 2004), (size fractionation by ultrafiltration (Wheeler 1976), and relative percentage composition by PARAFAC (Kroonenberg and Heiser 1998; Stedmon and Bro 2008). Non-optical indices of chemical reactivity include the proton binding index (PBI) (Al-Reasi et al. 2013a) and molecular charge (an indication of the ionizable fraction of the molecule). In the present study, we have applied all these techniques to characterize five sources of natural DOCs that were freshly isolated from diverse sites in Ontario, Canada. Two of the sources (Lake Ontario, LO; and Luther Marsh, LM) were selected because some of their physicochemical properties have been characterized in previous collections (Al-Reasi et al. 2012, 2013a; Duarte et al. 2018). These earlier studies established that these sources span extremes with regards to origin (autochthonous versus allochthonous) and structure (apparent molecular size, optical and physicochemical properties). The three other DOC collection sites (Preston Flats, PF; Ancient Woods Swamp, AS; and Ancient Woods Pond, AP) represent a gradient of aquatic environments within ‘The rare Charitable Research Reserve’, Ontario, that were predicted to ‘fill in the gaps’ between the extremes of LM (allochthonous) and LO (autochthonous). With a few exceptions, measurements were made at both pH 7 and 4. Additionally, size fractionation was performed, and the properties were evaluated for each fraction. Previous studies using the MWI have rarely done this. Size fractionation not only assessed the validity of the MWI, it allowed us to determine the importance of each size range considering DOC concentration, molecular weight, relative percentage fluorophore concentration (PARAFAC components) and aromaticity. The indices are related to DOC function; therefore, 65 we were interested in knowing if most of the protective capacity (related to metal toxicity and ionoregulatory function in aquatic organisms) of the DOC was in a specific fraction. Finally, results were analyzed to detect important relationships among the various optical and chemical indices and how they were affected by pH. Our goal was to critically assess these indices for use in a companion study (Morris et al. 2024c, see Chapter 4) probing the physiological effects of these same DOC solutions on freshwater rainbow trout (Oncorhynchus mykiss) at pH 7 and 4. As the indices are indicative of the quality and composition of DOCs, and thus potentially their functions, we predicted that DOCs that have higher aromaticity, larger molecular weight, more humic-acid-like content and a higher proton binding capacity, particularly at pH 4, would be more beneficial to ionoregulation in rainbow trout in our companion study (Morris et al. 2024c, see Chapter 4). 3.3 Experimental methods 3.3.1 Experimental solutions Natural DOC sources were collected from five sites in Ontario, Canada. The sites were Luther Marsh (LM) (43°57′42.8N, 80°24′04.0W), Lake Ontario (LO) (44°14′25.3″N 76°27′57.5″W) and three sites within ‘The rare Charitable Research Reserve’: Preston Flats (PF) (43°23′17.5″N 80°22′38.0″W), Ancient Woods Pond (AP) (43°22′30.4″N 80°21′55.5″W) and Ancient Woods Swamp (AS) (43°22′30.8″N 80°22′09.2″W). These are referred to throughout the manuscript by their site designations: LO, LM, PF, AP and AS. There were two types of samples collected, ‘grab samples’ and DOC concentrates. Single ‘grab samples’ of non-processed water were taken at the same time as the collection of the DOC concentrates (described below), for analysis of pH, DOC and cation and 66 metal concentrations (Appendix A Table SA 1). pH was measured using a sympHony pH electrode (C03243) and meter (SP70P) (VWR International, Radnor, PA, USA). DOC was measured using a Shimadzu total carbon analyzer (TOC-L Shimadzu, Mandel Scientific, Guelph, ON, Canada). All samples were well above the instrument detection limit (~0.1 mg C L-1). Metal concentrations were measured by inductively coupled plasma–optical emission spectroscopy (ICP-OES, Optima 8000, PerkinElmer Inc., Woodbridge, ON, Canada). Grab samples were taken from LO, PF, AP and AS; unfortunately, the grab sample from LM was lost. The DOC concentrates were collected as single stocks in reverse osmosis sessions, each lasting multiple hours from each location. We did not make multiple separate concentrates from each site. To concentrate the DOC, water was pumped from the source through a 1-µm wound string pre-filter to remove large debris, and then to a portable reverse osmosis unit fitted with a polyamide thin-film composite membrane (FilmTec BW30-4040, DuPont Water Solutions, Edina, MN, USA) which concentrated organic matter gradually (Sun et al. 1995). The concentrates were treated with a cation exchange resin (Amberlite IR-118 (H), Sigma-Aldrich, Saint Louis, MO, USA) to remove cations that may have accumulated during reverse osmosis. For the DOC concentrates, there were two processing procedures, one for optical and chemical characterization of ‘whole’ DOC (i.e. not fractionated), and the other for size fractionation. The concentrates for characterization of ‘whole’ DOC were filtered using 47-mm hydrophilic, polyethersulfone polymer membrane filters (0.45-µm pore size) (MS PES Membrane Solutions, Auburn, WA, USA), and stored in sealed bottles at 4°C. Experimental solutions were then prepared for further physicochemical characterization, including ICP-OES analysis, as well as for use in the fish physiology tests of the companion study (Morris et al. 2024c, see Chapter 4). These solutions were made by adding each of the natural DOC concentrates to dechlorinated 67 Vancouver tap water (Na+ = 0.09, Cl-= 0.10, Ca2+ = 0.10, Mg2+ = 0.011, K+ = 0.004 mmol L-1, hardness as CaCO3 = 3.3 mg L-1, pH = 7, [DOC] = ~1.07 mg C L-1) to nominally equal 10 mg C L-1 and the pH was adjusted to approximately pH 7 or pH 4 using HNO3 or NaOH and a sympHony pH electrode and meter (Appendix A Table SA 2). The pH range among the experimental solutions was typically less than 0.5 pH units. The solutions were made, and pH was adjusted at least 12 hours prior to the experiment to allow for equilibration. Directly prior to the experiment, the pH was measured again to ensure that the solution was still at the target pH. DOC concentrations in the experimental waters (Appendix A Table SA 2) were measured using a Shimadzu total carbon analyzer, as described above. Size fractionation was performed only at neutral pH, using the experimental solutions. All samples for size fractionation were first filtered using polyether sulfone membrane syringe filters (0.45 µm, 25 mm) (VWR syringe filters 76479-020, VWR International, Radnor, PA, USA) and were prepared at ~10 mg C L-1 at neutral pH. Molecular weight centrifugation filters of three sizes (100, 10 and 3 kDa) (MWCO, Vivaspin 20 mL, 100 kDa, GE28-9323-63; 10 kDa, GE28-9323-60; 3 kDa, GE28-9323-58; Sigma–Aldrich) were used in the next step. As these may contain glycerol, which would add carbon, they were preconditioned for 9 days following the soaking protocol outlined by Hourtané et al. (2022). The 0.45-µm filtrate was then used to conduct 3-,10- or 100-kDa ultrafiltration by centrifugation. Aliquots from each individual filtrate (i.e. 45 µm, 3, 10 or 100 kDa) were collected for analysis of DOC concentration, SAC340, FI, MWI and fluorescence excitation–-emission matrix (FEEM) as described below. 68 3.3.2 Optical characterization of DOCs An Aqualog optical spectrometer (HORIBA Scientific, Kyoto, KM, Japan) was used to measure the fluorescence and absorbance of each of the experimental solutions. This instrument measures the simultaneous excitation-emission matrices required for PARAFAC of fluorophores (Stedmon and Markager 2005; Stedmon and Bro 2008). All indices were measured at pH 7 and 4 with the exception of those associated with the size fractionation by ultrafiltration. 3.3.3 Specific absorbance coefficient at 340 nm The SAC340, an index of aromatic composition, was estimated by the method of Curtis and Schindler (1997) by examining the absorbance of samples at a wavelength of 340 nm using a 1-cm quartz cuvette (Helma Canada Ltd, Concord, ON, CA) in the Aqualog spectrometer. The instrument was ‘blanked’ using ultrapure water. Two replicates were performed for each source at pH 7 and 4. Briefly, SAC340 (cm2 mg-1 C) was calculated as: SAC340 =(2.303 × Abs340)/pathlength[DOC]/1000 (Equation 3.1) where DOC is in mg C L-1 and pathlength is in cm. 3.3.4 Fluorescence index The FI is an indicator of the DOC source with higher values indicating a more autochthonous origin, and lower values, a more allochthonous origin (McKnight et al. 2001). Other FI ratios have been proposed but the original ratio seems to work best for predicting the 69 protective effects of DOC (DePalma et al. 2011). FI was calculated by previously described methods (McKnight et al. 2001): FI = Em450Em500 (Equation 3.2) where Em450 and Em500 refer to emission intensities at 450 and 500 nm, both taken at an excitation wavelength of 370 nm. 3.3.5 Molecular weight index The ratio of absorbance measurements at 254 and 365 nm may be used as an indirect indicator of the relative molecular weight (MWI) of DOC (Peuravuori and Pihlaja 1997; Dahlén et al. 1999). Note that this is an inverse index, with high values indicating lower molecular weight, and low values indicating a higher molecular weight: MWI =Abs254Abs365 (Equation 3.3) 3.3.6 Parallel factor analysis PARAFAC modelling was conducted in MATLAB (ver. 9.12.0.1956245, MathWorks, Natick, MA, USA) using the PLS Toolbox (ver. 9.2, Eigenvector Research Incorporated, Manson, WA, USA). PARAFAC is a computational model that uses a multivariate statistical approach to define the components of a sample based on the fluorescence excitation–emission matrix (FEEM) and known predetermined number of fluorophores (Stedmon and Markager 2005; Stedmon and Bro 2008). Two replicates were performed for each source at pH 7 and 4. In 70 the present study, three fluorophore categories were selected: humic- acid-like, fulvic-acid-like and protein-like components. 3.3.7 Octanol-water partition coefficient The octanol–water partition coefficient, usually expressed as a logarithm (log Kow) is a measure of lipophilicity. The log Kow was measured following the procedure of Gjessing et al. (1999). Briefly, DOC solutions (~10 mg C L-1) from each source were made at pH 7 and 4. Octanol (5 mL) was added to a 15-mL aqueous DOC sample which was gently but thoroughly mixed using a three-dimensional nutating mixer (VWR International, Radnor, PA, USA) for 2.5 h. The distribution of the DOC in the water phase and octanol phase was determined by measuring the absorbance in each phase at 254 nm (Gjessing et al. 1999). The absorbance baseline zero was set by ‘blanking’ the machine with ultrapure water or octanol as appropriate. log Kow was calculated as per Gjessing et al. (1999): log Kow = 𝑙𝑜𝑔 (Abs254in octanol phaseAbs254in aqueous phase) (Equation 3.4) A higher log Kow value indicates a more lipophilic sample. 3.3.8 Size fractionation All samples were prepared as described above at ~10 mg C L-1 at neutral pH and were filtered through the 0.45-µm syringe filters. The 0.45-µm filtrate was then used to conduct 3, 10 or 100-kDa ultrafiltration by centrifugation. The swinging bucket rotor centrifuge ran at 4300g 71 for a duration of 8 min, at 4°C (Allegra X-14 Series Benchtop Centrifuges 120 V, Beckman Coulter, Brea, CA, USA). Aliquots from each individual filtrate were collected for analysis of DOC concentration, SAC340, FI, MWI and FEEM as described above. 3.3.9 Proton binding index and molecular charge The PBI shows the potential of DOC to exhibit strong tridentate binding of cations and has been used as a general indicator of chemical reactivity. The PBI is based on the protocol of Al-Reasi et al. (2013) using acid–base titrations over a wide range of pH values. Titrations were performed on DOC concentrates from each of the five sources (LM, LO, PF, AP and AS). Prior to the transfer to the titration vessel, the ionic strength of each DOC solution was adjusted to 0.01 M by the addition of 5 M NaNO3 (Sigma–Aldrich). The sample was acidified using HCl to pH ~2.0 then titrated by the gradual addition of 1 N NaOH at ~0.1 pH unit intervals until the pH reached 12 using an automated titrator (848 Titrino Plus with 801 magnetic stirrer with support rod, Metrohm Canada, Mississauga, ON, CA) with a pH electrode (Orion 8101BNWP ROSS Half-Cell Electrode, ThermoFisher Scientific, Waltham, MA, USA) and a double junction Ag/AgCl reference electrode (Orion 900200 Sure-Flow Reference Half Cell Electrode, ThermoFisher Scientific). All titrations were performed at room temperature under ultrapure N2 gas, to create a CO2-free environment. Three to five replicates were performed for each source. The experimental titration data were fitted to a fully optimised continuous (FOCUS) model using in-house MATLAB programs as described by Smith and Ferris (2001), to estimate proton binding constants (pKa) and their site densities (LT, μmol mg C-1). Binding site densities within a specified pKa range were determined by integration of the area under the curve in the pKa 72 spectrum. The PBI was calculated as in Al-Reasi et al. (2013): 𝐏𝐁𝐈 = 𝐢𝐧𝐭𝐞𝐫𝐦𝐞𝐝𝐢𝐚𝐭𝐞(𝐚𝐜𝐢𝐝 + 𝐛𝐚𝐬𝐢𝐜)/𝟐 (Equation 3.5) where, PBI is a function of the measured acidic (pKa ≤ 5), intermediate (5 > pKa ≤ 8.5) and basic (pKa > 8.5) proton binding site concentrations (determined by integration of the FOCUS pKa spectrum). Molecular charge of the DOC molecule, as moles of charge per milligram of carbon, is an indication of the ionisable fraction of the molecule and was determined directly from the experimental data, using interpolation to obtain the appropriate value at exactly pH 7 or pH 4. 3.3.10 Statistical analysis Error bars shown for indices represent ranges of replicate measurements. The relative percentage fluorophores (PARAFAC components) as individual sources of DOC at pH 7 and 4 were compared using one-way ANOVA with Tukey’s post hoc test. The overall effect of pH on the relative percentage fluorophores was assessed across all sites using unpaired Student’s t-test. To do this, we pooled all sites at pH 7 and 4 within their respective relative percentage fluorophore groups (e.g. relative percentage humic-acid-like concentration at pH 7 versus relative percentage humic-acid-like concentration at pH 4). Pearson r correlation matrices were used to analyze the relationships among the physicochemical characterization indices (SAC340, FI, MWI, log Kow, absolute charge, PBI, percentage humic-acid-like concentration, percentage 73 fulvic-acid-like concentration, percentage protein-like concentration, percentage <100 kDa, percentage <10 kDa and percentage <3 kDa) at pH 7 or pH 4 separately and at pH 7 and 4 combined. For each index, these analyses were conducted using single observations (or in the case of replicates, the mean values) from each of the five DOC sources. As the various indices were measured on five different DOCs, the degrees of freedom in the Pearson correlation matrices were only three, for pH 7 and 4 separately, so the threshold for statistical significance (p< 0.05) for a directional correlation value r was ±0.89; however, values that were ±0.70 or more were considered strongly correlated (Ratner 2009). For pH 7 and 4 data combined, the degrees of freedom in the Pearson correlation matrices was eight so the threshold for statistical significance (p < 0.05) for a directional correlation value r was ±0.63. Simple linear regressions (p < 0.05) were used to assess relationships between selected indices at pH 7 and at pH 4, and with the pH 7 and 4 data combined. All statistical analyses and data plots were done using GraphPad Prism 10 (ver. 10.2.3, GraphPad Software, San Diego, CA, USA). A significance level of p < 0.05 (two-tailed for all but the correlation analysis) was used throughout. 3.4 Results 3.4.1 Optical characterization At both pH 7 and 4, AP had the highest SAC340 value, indicating the highest aromaticity, followed by AS, LM and PF (Table 3.1). LO had the lowest SAC340 value (less than half the value of AP) indicating that it was the least aromatic DOC tested (Table 3.1). Adjusting the pH from pH 7 to 4 resulted in a lower SAC340 value for all but one source, although the changes were relatively small (less than 10%). The exception was LM where the SAC340 value increased 74 by 20%. At pH 7, LO had the highest FI, indicating a relatively more autochthonous origin, and LM had the lowest FI, indicating a more allochthonous origin than the other DOC sources (Table 3.1). This matched the initial assumption in the sampling design that LM and LO would represent extreme examples of allochthonous and autochthonous sources respectively. The three other DOCs had intermediate FI values. With a decrease in pH, all FI values decreased, except for LM which increased (Table 3.1); again, the changes were modest (~5%). LO exhibited the lowest apparent molecular weight as indicated by the MWI, an inverse ratio where higher values indicate a lower molecular weight (Table 3.1). The DOC with the highest apparent molecular weight was AP closely followed by AS and LM which were identical. The decrease of pH moderately increased (less than 20%) the MWI for all sources except for PF (decrease by 6%). In our PARAFAC analysis, the three resolved fluorophore components were labelled as humic-acid-like, fulvic-acid- like and protein-like moieties (Appendix A Figure SA 1), consistent with previous work (Al-Reasi et al. 2012), where the shortest UV peaks are typically assigned to protein-like components (e.g. peptides, amino acids), the next longest wavelength peaks to fulvic acids and the longest wavelength peaks to humic acids. The FEEM traces revealed a change in the fluorescence profile when the pH was lowered (Appendix A Figure SA 1 A–J). All sources were primarily composed of fulvic-acid-like components (Figure 3.1B), followed by humic-acid-like components (Figure 3.1A), with small protein-like components (Figure 3.1C). At pH 7, LM had the highest relative percentage humic-acid-like components, AP had the highest relative percentage protein-like components and LO had the highest relative percentage fulvic-acid-like component (Figure 3.1). For every source, the humic-acid-like 75 component increased with a decrease in pH, however, this was not statistically significant with LM DOC (Figure 3.1A). The overall increase at pH 4 considering all DOC sources was statistically significant (p < 0.0001). This was mirrored consistently by a significant decrease in the fulvic-acid-like component in all DOC sources (Figure 3.1B). Considering all sources together, the decrease was significant (p < 0.0001). The protein-like component also decreased at pH 4 in all sources but this was only significant with AP and AS (Figure 3.1C). The overall decrease in the protein-like component with a decrease in pH, considering all sources, was not significant (p= 0.0719). The most lipophilic DOC was LO followed by PF (Table 3.1), as determined by the octanol–water partition coefficient (log Kow). AP, AS and LM were less lipophilic and there were marked increases in log Kow values with the decrease in pH in all sources (Table 3.1). The total range in log Kow differed by 0.35 from highest to lowest; this corresponds to a factor of ~2 in the underlying linear quantity (Kow). 3.4.2 Proton binding index and molecular charge At almost 7× greater than the minimum measured value, LM had the highest PBI, a measure of general chemical reactivity, followed by AP, AS and PF, whereas LO had the lowest PBI (Table 3.2). The molecular charge (mol charge mg-1 C) was highest in AS (more than double the lowest value), followed by LM, AP, then LO, which was close to the lowest value, PF, at both pH values. As expected with proton binding sites being titrated, in each source, absolute charge decreased greatly with the lowering of pH (Table 3.2). 76 3.4.3 Size fractionation The DOC concentration of the filtrate generally decreased with decreasing pore size (Table 3.3). Both LM and PF had the largest percentage change in DOC concentration when looking at the difference between the 0.45-µm and 10-kDa filtrates rather than the 0.45-µm and 3-kDa filtrates (Table 3.3). However, when considering changes between 0.45 µm and 3 kDa, PF had the lowest percentage change in DOC concentration with filtration. Notably, in all cases, more than 62% of DOC passed through the 3-kDa filter. Generally, MWI increased with decreasing pore size, indicating a decrease in molecular weight, particularly at 3-kDa filtration. The absolute absorbance at 340 nm and SAC340 also decreased indicating that the filtrate was less aromatic (Appendix A Table SA 3). The FI increased, indicating that the filtrate was fluorescing more like autochthonous DOCs with decreasing pore size. The PARAFAC components also changed with filtration. In each source, when comparing the largest pore size (0.45 µm) and the smallest (3 kDa) there was a decrease in the percentage humic-acid-like component and an increase in the percentage fulvic-acid-like component with the protein-like component being more variable. 3.4.4 Correlations among the physicochemical characteristics of DOC related to pH At pH 7, there was a significant positive correlation between log Kow and MWI (Figure 3.2A). There were significant negative correlations between PBI and log Kow, between percentage fulvic-acid-like concentration and SAC340, between percentage protein-like concentration and percentage humic-acid- like concentration, as well as between percentage <10 kDa and percentage humic-acid-like concentration (Figure 3.2A). Although not significant, there were a number of strong positive correlations (i.e. a Pearson correlation value of +0.7 or more). 77 These occurred between log Kow and FI, between PBI and SAC340, between percentage fulvic-acid- like concentration and MWI, between percentage <100 kDa and percentage protein-like concentration, as well as between percentage <100 kDa and percentage <10 kDa (Figure 3.2A). In addition, there were many strong negative correlations. These were seen between MWI and SAC340, between log Kow and SAC340, between charge and MWI, between PBI and FI, between PBI and MWI, between percentage humic-acid-like concentration and FI, between percentage protein-like concentration and percentage fulvic- acid-like concentration, between percentage <100 kDa and percentage humic-acid-like concentration, and between percentage <3 kDa and percentage protein-like concentration (Figure 3.2A). At pH 4, the correlation relationships differed. PBI and SAC340 were significantly positively correlated with each other, as were percentage <10 kDa and FI. There were significant negative correlations between SAC340 and MWI, between PBI and MW, between percentage protein-like concentration and percentage fulvic-acid-like concentration, and between percentage <3 kDa and percentage humic-acid-like concentration (Figure 3.2B). Overall, there were less strong correlations at pH 4 compared to pH 7. The strong positive correlations were MWI with FI, PBI with charge and percentage <10 kDa with percentage <100 kDa. The strong negative correlations were charge with log Kow, PBI with FI and percentage <10 kDa with percentage fulvic-acid-like concentration (Figure 3.2B). When pH 7 and 4 data were grouped together, again the correlation relationships changed. The relationships that remained significantly positively correlated with each other were: SAC340 with PBI, percentage fulvic-acid-like concentration with charge, percentage <10 kDa with FI, and percentage <10 kDa with percentage <100 kDa (Figure 3.2C). 78 The significant negative correlations that remained were: between MWI and SAC340, between charge and log Kow, between PBI and MWI, between percentage fulvic-like concentration and log Kow, and between percentage fulvic-acid- like concentration and percentage humic-acid-like concentration ((Figure 3.2C).There were no other important correlations as the directional correlation value r for significance was ±0.63 for the combined pH values. Based on the Pearson r correlation matrices described above, important relationships were further assessed using simple linear regressions at pH 7 and at pH 4, and with pH 7 and 4 data combined (Figure 3.3). The regression of SAC340 against PBI was significant at pH 4 and when pH 7 and 4 data were combined, but not at pH 7 (Figure 3.3A). When SAC340 was regressed against MWI, again the relationship was significant at pH 4 and when pH 7 and 4 data were combined, but not at pH 7 alone (Figure 3.3C). The regression of log Kow against PBI was significant at pH 7 only (Figure 3.3C). The regression of PBI against MWI was significant when pH 7 and 4 data were combined and at pH 4, but not at pH 7 (Figure 3.3D). Finally, when log Kow was regressed against charge, the relationship was significant only when pH 7 and 4 data were combined (Figure 3.3E). 3.5 Discussion 3.5.1 Overview With respect to our original hypotheses, there were (i) substantial physicochemical differences among our five DOC sources. Indeed, at pH 7, LM DOC was among the most aromatic, and was the most allochthonous, with the largest apparent molecular weight and the largest relative humic-acid-like component, whereas LO was the least aromatic, most 79 autochthonous, with the smallest apparent molecular weight and lowest relative humic-acid-like component. As expected, the indices for the other three sources lay intermediate between these extremes. We (ii) confirmed that most of the physicochemical indices used to characterize the DOCs changed as pH was lowered from 7 to 4, and these changes were reasonably consistent in a qualitative manner. Thus, SAC340 and FI values decreased slightly at lower pH and MWI increased, although in each case there was one exception (Table 3.1). We attribute these shifts to pH-dependent changes (proton binding at lower pH) in the molecules that alter their optical properties, rather than changes in origin and molecular weight respectively. For example, there is evidence that DOC molecules tend to condense at low pH and expand at higher pH (Pace et al. 2012). This would fit with the higher MWI (i.e. lower apparent size) at pH 4 v. 7. It is unlikely that the pH changes alter the aromaticity as there are no associated oxidizing agents, only protonation–deprotonation reactions based on pH changes. Pace et al. (2012) speculated that condensation of the molecules at low pH would limit their exposure to light, thereby lowering their specific absorption, which would explain the small decreases in SAC340. By contrast, effects on fluorescence may be different. At the lower pH, by PARAFAC, samples consistently exhibited apparent increases in the percentage humic-acid-like component, and decreases in the percentage fulvic acid-like and percentage protein-like components, although the latter was not significant (Figure 3.1). Patel-Sorrentino et al. (2002) reported that pH affected the fluorescence of both humic-acid-like and fulvic-acid-like components in a qualitatively similar manner, but their ratio would be altered to favour the humic-acid-like components at low pH. This would also explain the shift to lower FI values (again an index based on fluorescence) at low pH, suggesting that the DOC manifests as though it is more allochthonous in origin. Again, conformational 80 changes, rather than compositional changes, were the likely explanation. Fluorescence spectra for protonated versus deprotonated fluorophores are different. Therefore, although the conformational and optical changes with pH are apparent, they do not reflect changes in the characteristics that the indices are generally thought to represent. Caution in interpretation is needed. On the other hand, the substantial and consistent decreases in charge (Table 3.2) and increases in log Kow (Table 3.1) at lower pH reflect changes in the properties or composition of the molecules, as proton binding to anionic sites on the DOCs reduces their negative charge, thereby making the molecules more lipophilic. We also confirmed (iii) that several of the indices used to characterize DOC correlated strongly with one another, with particularly positive correlations between aromaticity and apparent molecular weight, between chemical reactivity and apparent molecular weight, between aromaticity and chemical reactivity, and a negative correlation between lipophilicity and molecular charge. These and other relationships were pH-dependent and are explored below. We found that (iv) smaller DOC fractions did have lower DOC concentration, aromaticity, relative percentage humic-acid-like concentration and molecular weight, supporting our hypothesis. However, apart from the SAC340 values, the changes we saw in DOC concentration, relative percentage humic-acid-like concentration and molecular weight were more modest than we would have predicted. Our results indicate that the aromatic groups are within larger fractions of the DOC. However, although the overall DOC concentration, molecular weight and relative percentage humic-acid-like concentrations did decrease with decreasing pore size, they were somewhat retained even in the smallest fraction that we tested. 81 3.5.2 The physicochemical characteristics of DOC: ecological and physiological implications SAC340 values have been reported between 1 and 73 cm2 mg-1 with most natural waters being below 40 cm2 mg-1 (Al-Reasi et al. 2012; Johannsson et al. 2017; Sadauskas‐Henrique et al. 2021). We observed similar trends in SAC340 values in the two sources that have been previously characterised at pH 7, LO and LM (Al-Reasi et al. 2012), with LM being more aromatic compared to LO (Table 3.1). However, our absolute values differed. At pH 7, LM and LO were 26.55 and 16.45 respectively (Table 3.1) versus 39.03 and 4.85 reported by Al-Reasi et al. (2012). The SAC340 reported by Sadauskas‐Henrique et al. (2021) for LM DOC collected in 2010 was 39.70. These differences were perhaps due to spatial, temporal and seasonal variation in collections. In earlier studies, SAC340 has been positively correlated with relative percentage humic‐like concentration (PARAFAC component) and negatively correlated with the relative fulvic acid‐like concentration (Mann et al. 2012; Wickland et al. 2012). Our data only partially agreed: at pH 7 only, there was a significant negative correlation between SAC340 and percentage fulvic-acid-like concentration (Figure 3.2A) It is notable, however, that with size fractionation, for each DOC, there were consistent large increases in the percentage fulvic-acid-like component, large decreases in the percentage humic-acid-like component and substantial decreases in SAC340 in the smallest filtrate, <3 kDa (Appendix A Table SA 3). SAC340 appears to be an important index in predicting DOC effects on aquatic systems and organisms, and it exhibited a very strong negative correlation with MWI under all pH conditions in the present study (Figure 3.2, Figure 3.3B). Thus, larger DOC molecules appear to be more aromatic, which agrees with the substantially lower SAC340 values in the <3-kDa fraction (Appendix A Table SA 3 as noted above). The chemical composition of DOC greatly affects its biodegradation in aquatic ecosystems (Mann et al. 2012; Wickland et al. 2012). DOCs 82 with higher aromaticity and higher molecular weight are generally less biodegradable, and therefore are responsible for lower CO2 production, which is environmentally favourable in the current context of climate change (Palviainen et al. 2022). The aromaticity of DOC molecules is also often used as an indicator of their ability to protect against metal toxicity and to influence ionoregulation in aquatic organisms (Al-Reasi et al. 2011, 2012, 2013a; Duarte et al. 2016; Sadauskas‐Henrique et al. 2019). We noted a decrease in SAC340 with the decrease in pH in all DOC sources with the exception of one, however, it remains unknown if this optical change is mirrored in the physiological effects. Interestingly, DOCs seem to be more effective in providing beneficial physiological effects at low pH (Wood et al. 2011; Morris et al. 2021, see Chapter 2), yet are less effective in binding metals at low pH (Christensen and Christensen 2000; Tipping 2002). This suggests that different sites on the large aromatic molecules are involved in the two different protective processes. FI is a well-recognized indicator of DOC origin (McKnight et al. 2001). LM DOC was previously reported to be of allochthonous origin with relatively smaller FI values compared to LO (Al-Reasi et al. 2012; Sadauskas‐Henrique et al. 2021) and our results agree (Table 3.1) We observed that LO DOC had the smallest FI with high relative fulvic-acid-like concentrations and low relative humic-acid-like concentrations at both pH values (Table 3.1, Figure 3.1). FI was previously reported to be negatively correlated with the humic acid‐like component and positively correlated with the fulvic-acid-like component (Al-Reasi et al. 2012). However, only in our combined pH 7 and 4 data is this trend present, and the correlations are neither significant nor strong (Figure 3.2C). Notably, FI values were highest in the <3-kDa filtrates (Appendix A Table SA 3), indicating that the smaller molecules in each DOC sample were more autochthonous in nature. 83 As noted earlier, the change in FI values with the change in pH (Table 3.1) potentially reflected a change in the conformation of DOC towards a fluorescence profile that is normally associated with that origin (i.e. either of allochthonous or autochthonous origin) and the fulvic-acid-like component is more sensitive to a change in pH relative to the humic- acid-like component (Patel-Sorrentino et al. 2002). The change in fluorescence with pH is likely due to the molecular orbital of excitable electrons being altered by ionisation (Laane 1980; Patel-Sorrentino et al. 2002). Macromolecular configuration could also offer an explanation. More rigid structures give better fluorescent yields; humic substances have a more linear structure at high pH and coil as pH decreases which may mask some of the fluorescence (Ghosh and Schnitzer 1980). Generally, allochthonous DOCs have been described as highly protective against metal toxicity and physiological disturbances (Al-Reasi et al. 2011, 2013a; Wood et al. 2011). However, Al-Reasi et al. (2011) suggested that FI was a less successful predictor compared to SAC340 because FI was unable to explain the variability in protection offered by DOC against copper and silver toxicity in fish. Based on our results we agree that FI is not as strong a predictor of DOC quality because of the mechanistic explanation offered above, and the implication that a change in FI is not necessarily a direct change in origin of the DOC. Our log Kow values ranged from -1.48 to -1.13 for pH 7 and -1.09 to -0.66 for pH 4 (Table 3.1) which were similar to ranges for other DOC sources at pH 7, -1.92 to -0.97 (Al-Reasi et al. 2013a) and -1.05 to -0.48 (Gjessing et al. 1999). The lipophilic nature of DOC is dependent on pH (Gjessing et al. 1999; Namjesnik-Dejanovic and Cabaniss 2004). It is likely that this change in log Kow reflects compositional changes of the DOC molecules with proton binding to anionic sites making the molecules more lipophilic. The charges on weak acid sites are thereby neutralized, thus decreasing the molecule polarity. Less polar molecules will partition more 84 readily into the non-polar octanol phase. This conclusion was reinforced by the significant negative regression relationships between log Kow and charge for the combined pH 7 and 4 data (Figure 3.3e), and between log Kow and PBI at pH 7 (Figure 3.3C). More ionized DOC molecules (higher molecular charge) will more readily partition into the polar water phase (‘like dissolves like’) and result in a lower log Kow. At pH 7 the DOCs (AP and LM) that were the most aromatic, more allochthonous, and had generally higher relative humic-acid-like fluorophore concentrations, were also the least lipophilic, but at pH 4 the log Kow values of these DOCs lay intermediately within the range (Table 3.1). At both pH values, LO and PF were the most lipophilic and were the least aromatic, the most autochthonous and were among the lowest relative humic-acid-like fluorophore concentrations (Table 3.1, Figure 3.1) Al-Reasi et al. (2013) likewise described LO to be more lipophilic when compared to LM. At pH 7, log Kow and SAC340 were strongly negatively correlated in our Pearson correlation matrix, such that more aromatic DOCs were less lipophilic (Figure 3.2A), however, these indices were only moderately correlated at pH 4 (Figure 3.2B). Al-Reasi et al. (2011) concluded that there was no relationship between lipophilicity and the ability to bind metals; the present results suggest that at best, there is a weak negative relationship. At face value, greater lipophilicity might favour interaction with the cell membranes of the gills, and this might explain why the physiological effects of DOC, in contrast to the metal-binding actions of DOC, are more pronounced at low pH where DOC lipophilicity is greater. Further biological studies should assess how DOCs with varying lipophilicity affect physiological measurements at neutral and acidic pH. PBI, an indicator of the chemical reactivity of DOC, was developed for predicting the metal binding capacity of DOC by Al-Reasi et al. (2012) who proposed that it may also be useful 85 to predict physiological influences of DOC. The PBI range for our DOC sources (Table 3.2) was from 0.09 for LO (lower than the previously reported 0.20) to 0.60 for LM (higher than the previously reported 0.44) (Al-Reasi et al. 2013a). DOCs with high PBI have been described to also have high SAC340 values (Al-Reasi et al. 2013a). Our data show a similar trend: the two DOCs with the highest PBI also had the highest SAC340 values (AP and LM), likewise LO had the lowest PBI and SAC340 value (Table 3.1). PBI and SAC340 were strongly correlated at pH 7 and significantly correlated at pH 4, as well as in the combined data set (Figure 3.2). Note though that PBI is a pH-independent value because it is calculated from all pH values measured during acid-base titration. log Kow and PBI were significantly negatively correlated at pH 7 only. As molecules become more lipophilic (i.e. higher log Kow) the PBI (i.e. chemical reactivity) decreases (Figure 3.2A, Figure 3.3C) The MWI is considered an inverse index of the mean molecular weight of DOC molecules (Peuravuori and Pihlaja 1997; Dahlén et al. 1999). Our size fractionation data generally showed that as DOCs were filtered through decreasing pore size, MWI increased (i.e. molecular weight decreased) and FI increased indicating more autochthonous DOC (Appendix A ). The MWI for LM was slightly higher than previously reported and LO was slightly (Table 3.1) (Al-Reasi et al. 2012; Sadauskas‐Henrique et al. 2021). Relatively higher values of MWI have been noted for autochthonous DOC which are composed of a large proportion of low molecular weight macromolecules (Al-Reasi et al. 2012). A higher MWI indicates that LO has the lowest molecular weight followed by PF, with LM, AP and AS being very similar at both pH values (Table 3.1). This trend is generally supported by the percentage change in DOC concentration with size fractionation by ultrafiltration (Appendix A Table SA 3). At pH 4, FI and MWI were significantly correlated (Table 3.2B). Sadauskas‐Henrique et al. (2021) reported that SAC340 and 86 MWI were negatively correlated. We noted a strong negative correlation that was significant at pH 4 and when the pH values were combined (Table 3.1, Figure 3.3B). As MWI is an inverse index, this indicates that more aromatic DOCs also have larger molecular weights. The specific wavelength of 254 nm may represent the maximum absorbance for all aromatic structures present in humic samples whereas 280 nm is where electron transition occurs for some aromatic groups including phenolic arenes, polyenes and polycyclic aromatic hydrocarbons with two or more rings (Peuravuori and Pihlaja 1997). It has been suggested that the relative amount of aromatic moieties in the humic fraction increases with increasing molecular weight (Peuravuori and Pihlaja 1997). 3.6 Concluding remarks Mechanistic understanding of DOC effects is crucial for future monitoring of aquatic environments and interpreting how different systems with different DOCs interact with the organisms that reside there. Overall, our results highlight that the physicochemical indices used to characterize DOCs are pH-dependent, and as such should be interpreted carefully as it is likely that changes in the conformation rather than changes in the composition are altering the optical signatures. It should be noted that in previous works on optical indices they were all determined at a fixed pH (usually 7) because the pH dependence of absorbance and fluorescence spectra is well known. So in the application of those indices to characterize source waters the comparisons are valid only when compared at the same fixed pH. On the other hand, higher log Kow (indicative of greater lipophilicity) and reduced charge at lower pH undoubtedly reflect changes in the molecule, resulting from proton binding. Our major findings that apparent aromaticity, apparent molecular weight and molecular charge all generally decreased with low pH while 87 lipophilicity increased shows the importance of pH-specific characterization of DOC. Additionally, these results indicate that the ecological function of DOC likely changes with natural acidification events such as increases in atmospheric CO2 or anthropogenic influences such as acid mine drainage and acid rain. Further research is needed to determine if these changes are reflected in the physiological responses of aquatic organisms to DOC. Indeed, the present study has provided the background for a companion investigation on the rainbow trout (Morris et al. 2024c, see Chapter 4) evaluating the effects of these same DOC solutions on the transepithelial potential (TEP) across the gills, a sensitive indicator of biological effect (Galvez et al. 2008). In particular, we have established that the five chosen DOC sources differ widely in physicochemical indices and have critically evaluated the relationships among them. An important caveat is that our goal in this study was not to perform a comprehensive characterization of spatial and temporal variation within sites, but rather to collect discrete DOC stocks that had a range in characteristics in order to evaluate the relationships among indices, the effects of pH on these indices, and the relationships of these indices on fish physiology at two pH values in the companion study (Morris et al. 2024c, see Chapter 4). Some indices are strongly related to one another in a positive or negative fashion, whereas others are not, but these relationships vary with pH (Figure 3.2, Figure 3.3). DOC quality has major impacts spanning trophic levels, DOC concentrations are rising in freshwaters (Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025) and pH values are decreasing with climate change (Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; Quijada-Rodriguez et al. 2021). Indeed, pH should be considered when determining the ecological role of DOCs within aquatic ecosystems. 88 3.7 Chapter 3 – Tables Table 3.1. The specific absorbance coefficient at 340 nm (SAC340), fluorescence index (FI), molecular weight index (MWI) and octanol-water partition coefficient (log Kow) in Lake Ontario (LO), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at ~10 mg C L-1 at pH 7 and pH 4. SAC340 values are means ± range, N=2. Table 3.2. Proton binding index (PBI) and molecular charge (mol charge/ mg C) at pH 7 and pH 4 for Lake Ontario (LO), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS). Values are means ± range N= 3-5. Source pH 7 SAC340 pH 4 SAC340 pH 7 FI pH 4 FI pH 7 MWI pH 4 MWI pH 7 log Kow pH 4 log Kow LO 16.45 ± 0.28 14.95 ± 0.23 1.30 1.24 8.23 8.25 -1.13 -0.66 PF 21.52 ± 0.16 18.18 ± 0.29 1.24 1.18 7.52 7.04 -1.26 -0.68 LM 26.55 ± 0.32 31.92 ± 0.41 1.13 1.15 5.62 5.90 -1.48 -1.00 AP 36.94 ± 0.02 32.73 ± 0.12 1.24 1.19 5.53 6.11 -1.46 -0.68 AS 27.91 ± 0.03 27.87 ± 0.28 1.28 1.20 5.70 6.71 -1.34 -1.09 Source PBI charge at pH 7 charge at pH 4 LO 0.09 ± 0.007 3.95 ± 0.77 0.95 ± 0.56 PF 0.12 ± 0.02 3.65 ± 0.60 0.59 ± 0.25 LM 0.62 ± 0.17 6.10 ± 1.92 2.17 ± 1.60 AP 0.45 ± 0.10 4.71 ± 0.60 0.95 ± 0.42 AS 0.30 ± 0.04 7.58 ± 0.60 1.68 ± 0.36 89 Table 3.3. Percent change in DOC concentration between 0.45-m – 100-kDa, 0.45 m – 10-kDa, and 0.45-m – 3-kDa of Lake Ontario, Luther Marsh, Preston Flats, Ancient Woods Pond, and Ancient Woods Swamp. Source 0.45 m - 100 kDa 0.45 m - 10 kDa 0.45 m - 3 kDa Lake Ontario -9.25 -11.61 -24.62 Preston Flats -13.64 -24.13 -12.12 Luther Marsh -13.89 -31.64 -22.51 Ancient Woods Pond -6.38 -15.15 -37.99 Ancient Woods Swamp -13.13 -19.58 -37.78 90 3.8 Chapter 3 – Figures Figure 3.1. Relative % fluorophores of (A) humic acid-like (B) fulvic acid-like and (C) protein-like components for Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM) Ancient Woods Pond (AP) and Ancient Woods Swamp (AS). Values are mean ± range, N=2. Letters that differ indicate statistically significant differences (p<0.05 by one way ANOVA plus Tukey’s post hoc test). 91 92 Figure 3.2 Pearson r correlation matrices demonstrating the correlations between optical characterization indices, specific absorbance coefficient 340 (SAC340), fluorescence index (FI), molecular weight index (MWI), log Kow, molecular charge, proton binding index (PBI), % humic acid-like, % fulvic acid-like, % protein like, % < 100-kDa, % < 10-kDa, % < 3-kDa at (A) pH 7 or (B) pH 4 separately and (C) pH 7 and pH 4 combined. Asterisks (*) denote significance at p < 0.05. The threshold for significance for panels A and B is a directional correlation value r = ± 0.878 and for C is r = ± 0.632 based on the degrees of freedom. Values with r = ± 0.7 or more are considered highly correlated. See Methods for additional details. 93 94 Figure 3.3 Simple linear regressions of relationships between indices at pH 7 (blue circles and blue dashed lines), and at pH 4 (brown squares and brown dashed lines) separately, as well as with the pH 7 and pH 4 data combined (solid black line). Significance (p<0.05) is indicated by the presence of a line in the corresponding colour. The equations of the regression equations for pH 7 and pH 4 data combined are shown on each panel, together with the r2 and p values. Additionally, for the pH-specific regressions, the following were significant (p<0.05) (A) specific absorbance coefficient 340 regressed against proton binding index. (pH 4. Y = 34.87*X + 14.25, r2 = 0.8696, p= 0.0208). (B) specific absorbance coefficient 340 0 regressed against molecular weight index (pH 4. Y = -8.107*X + 80.29, r2 = 0.8638, p= 0.0223). (C) log Kow regressed against proton binding index (pH 7. Y = -0.6371*X - 1.133, r2 = 0.8902, p= 0.0160. (D) proton binding index regressed against molecular weight index (pH 4. Y = -0.2086*X + 1.731, r2= 0.7999, p= 0.0405). (E) log Kow regressed against molecular charge (Y = −0.1159x − 0.6986, r2 = 0.7663, p =0.0009). 95 Chapter 4: Using physicochemical properties to predict the impact of natural dissolved organic carbon on transepithelial potential in the freshwater rainbow trout (Oncorhynchus mykiss) at neutral and acidic pH. 4.1 Summary Dissolved organic carbon (DOC) is a complex mixture of molecules that varies in composition based on origin as well as spatial and temporal factors. DOC is an important water quality parameter as it regulates many biological processes in freshwater systems, including the physiological function of the gills in fish. These effects are often beneficial, especially at low pH where DOCs mitigate ion loss and protect active ion uptake. DOCs of different compositions and quality have varied ionoregulatory effects. The molecular variability of DOCs can be characterized using optical and chemical indices, but how these indices relate to the physiological effects exerted by DOCs is not well understood. We tested the effects of five naturally sourced DOCs, at both pH 7 and pH 4, on transepithelial potential (TEP) (a diffusion potential between the blood plasma and the external water) in rainbow trout. The five chosen DOCs have been well characterized and span large differences in physicochemical characteristics. Each of the DOCs significantly influenced TEP, although in a unique manner or magnitude which was likely due to their physicochemical characteristics. These TEP responses were also a function of pH. With the goal of determining which physicochemical indices are predictive of changes in TEP, we evaluated correlations between various indices and TEP at pH 7 and pH 4. The indices included: specific absorbance coefficient at 340 nm (SAC340), molecular weight index (MWI), fluorescence index (FI), octanol-water partition coefficient (log Kow), molecular charge (MC), proton binding index (PBI), % humic acid-like, % fulvic acid-like, and 96 % protein-like components by parallel factor analysis on fluorescence data (PARAFAC). Our results demonstrate the novel finding that there are three particularly important indices that are predictors of changes in TEP across pHs in rainbow trout: specific absorbance coefficient at 340 nm, octanol-water partition coefficient; and proton binding index. 4.2 Introduction In freshwater ecosystems, dissolved organic carbons (DOCs) regulate both biotic and abiotic processes (Petersen 1991; Kullberg et al. 1993; Steinberg et al. 2006; Al-Reasi et al. 2011). The biological processes with which DOC molecules interact include ultraviolet screening, the carbon cycle, CO2 generation and O2 consumption via photo‐oxidation, production of reactive oxygen species (ROS), acidification, nutrient transport, and metabolic processes (Kullberg et al. 1993; Sucker and Krause 2010; Wood et al. 2011; Johannsson et al. 2017, 2020; Holland et al. 2018). DOCs are also subject to seasonal and temporal changes in concentration and composition (i.e. chemical makeup of the molecule), further influencing aquatic ecosystems (Kullberg et al. 1993; Sucker and Krause 2010; Wood et al. 2011; Holland et al. 2018). The full extent of the ecological and biological significance of DOCs in freshwater systems is not yet understood. Nevertheless, there is now an abundance of evidence that DOCs affect gill function in freshwater organisms, particularly fish. It is well recognized that DOCs are a mitigating factor against metal toxicity as they have the ability to complex and thereby reduce the bioavailability of metal cations (Playle et al. 1993; Hollis et al. 2001; Matsuo et al. 2004; Wood et al. 2011; Crémazy et al. 2016). Al-Reasi et al. (2013) proposed that the physicochemical properties of DOCs that are important in the protection against metal toxicity may be similar to those that 97 exert physiological effects on the gills, though this has not been proven. These physiological effects are usually beneficial to the ionoregulation of the organism and are particularly important at low pH. These include protection of active ion uptake from inhibition and mitigation of the often-fatal increase in passive loss of major salt ions (Na+, Cl-) across the gills during low pH exposure (Gonzalez et al. 2002, 2005; Wood et al. 2003, 2011; Matsuo et al. 2004; Glover et al. 2005; Glover and Wood 2005; Al-Reasi et al. 2016; Duarte et al. 2016, 2018). At environmentally realistic low pH (i.e. pH 3.5–5), the general physiological response of non-acidophilic freshwater fish such as the rainbow trout is an elevation of passive ion loss and the inhibition of active Na+ and Cl- uptake. This results in reduced plasma Na+ and Cl-concentrations, low blood volume, and elevated plasma protein levels (McDonald et al. 1980, 1983; Wood and McDonald 1982; Wood 1989). Circulatory failure is the eventual cause of mortality (Milligan and Wood 1982). Low pH also affects the transepithelial potential (TEP) across the gills. In freshwater fish, the TEP largely represents a diffusion potential between the blood plasma and the ambient water, predominantly due to the differential permeabilities of Na+ versus Cl- across the gills (Potts 1984). An acidic environment alters this differential permeability of Na+ versus Cl- and increases the diffusion gradient for proton entry. The resulting less negative TEP (blood plasma relative to the external water) favors Na+ efflux and opposes active Na+ influx. Fresh, natural DOCs have been found to cause hyperpolarization of TEP in freshwater fish, thereby making the blood side more negative relative to the water side (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019). This improves the electrochemical gradient for net Na+ uptake at the gills and is likely an important contributor to the positive effects of DOCs on ionoregulation (Wood et al. 2011; Morris et al. 2021, see Chapter 2). 98 Some DOCs are more effective at protecting against metal toxicity and exerting physiological effects than others (Al-Reasi et al. 2011, 2013a; Sadauskas‐Henrique et al. 2019), and the extent of the effects appear to vary with DOC type and pH (Wood et al. 2011; Morris et al. 2021, see Chapter 2). Specific physicochemical indices have been developed to describe the molecular variability of DOCs based on their optical and chemical properties. The optical indices include aromaticity (specific absorbance coefficient at 340 nm, SAC340, Curtis and Schindler 1997), molecular weight (molecular weight index, MWI, Dahlén et al. 1996; Peuravuori and Pihlaja 1997), allochthonous versus autochthonous origin (fluorescence index, FI, McKnight et al. 2001; DePalma et al. 2011), lipophilicity (logarithm of the octanol-water partition coefficient, log Kow, Gjessing et al. 1999; Egeberg and Alberts 2002; Namjesnik-Dejanovic and Cabaniss 2004), and relative percent composition by parallel factor analysis (PARAFAC) (Kroonenberg and Heiser 1998; Stedmon and Bro 2008). Non-optical indices of chemical reactivity include the proton binding index (PBI) and molecular charge (an indication of the ionizable fraction of the molecule) (Al-Reasi et al. 2013a). Although these indices are well described, how they relate to one another, and behave at different pHs was not understood, until a recent companion study (Morris et al. 2024b, see Chapter 3), where we applied all of the techniques outlined above to characterize five sources of DOC that were freshly isolated from two very different sites in Ontario, Canada (Luther Marsh and Lake Ontario) and three intermediate sites within the ‘rare Charitable Research Reserve’ in Ontario, Canada (Preston Flats, Ancient Woods Swamp, and Ancient Woods Pond). Important relationships were detected among the various optical and chemical indices which were pH-dependent (Morris et al. 2024b, see Chapter 3). In the present study, we have used these same, now well characterized DOCs from the companion study, to systematically assess their effects on 99 a sensitive indicator of biological effect; the TEP of the freshwater fish gill. Specifically, we have described the relationships between TEP effects and the physicochemical characteristics of DOCs at pH 7 and pH 4. Our specific hypotheses were (i) DOCs that were more aromatic, more allochthonous, larger in molecular size, with greater % humic acid content, and with a greater proton binding index (PBI) would hyperpolarize TEP to a greater extent; (ii) the DOC effects on TEP would be greater at lower pH because ionoregulatory protection is more apparent at low pH; and (iii) one or more of the indices would strongly predict the effect of DOC on TEP at each pH. Our overall goals were to develop tools to predict the effects of DOCs with different physicochemical characteristics on TEP in fish, and in so doing better understand the nature of the interactions of DOC with fish gill function at circumneutral and acidic pH. 4.3 Methods 4.3.1 Experimental animals Juvenile rainbow trout (Oncorhynchus mykiss) (N=60, 124 ± 5 g) were obtained from the Freshwater Fisheries Society of BC (Abbotsford, BC, Canada) and transferred to the University of British Columbia (UBC). Fish were held for several months prior to commencing experiments at 12 ºC in flowing dechlorinated Vancouver tap water (Na+ =0.09, Cl- =0.10, Ca2+ =0.10, Mg2+ =0.011, K+ =0.004 mmol L-1, hardness as CaCO3 =3.3 mg L -1, pH =7, [DOC] = ~1.07 mg C L-1). Fish were fed to satiation every second day with commercial pellet food (BioTrout 2.0 mm, Bio-OregonTM, Long-view, WA, USA) and were fasted for at least 72 h prior to experiments. All experiments were approved by the UBC Animal Care Committee (A18-0271 and A22-0195) and conformed to national regulations of the Canada Council for Animal Care. 100 4.3.2 Experimental solutions The five natural sources of dissolved organic carbon (DOC) were collected in Ontario, Canada. These were Luther Marsh (LM) (43°57′42.8N, 80°24′04.0W), Lake Ontario (LO) (44°14'25.3"N 76°27'57.5"W) and three sites within the ‘rare Charitable Research Reserve’: Preston Flats (PF) (43°23'17.5"N 80°22'38.0"W), Ancient Woods Pond (AP) (43°22'30.4"N 80°21'55.5"W) and Ancient Woods Swamp (AS) (43°22'30.8"N 80°22'09.2"W). Throughout the paper, these are referred to by their site designations: LO, LM, PF, AP and AS. The collection and treatment of these DOCs was exactly as described by (Morris et al. 2024b, see Chapter 3). Briefly, water was pumped from the source and pre-filtered through a 1-m wound string filter. Then DOC was concentrated gradually (Sun et al. 1995) by a portable reverse osmosis unit fitted with a polyamide thin-film composite membrane (FilmTecTM BW30-4040, DuPont Water Solutions, Edina, MN, USA). The samples were then treated to remove cations that may have accumulated during reverse-osmosis with a cation exchange resin (Amberlite IR-118 (H), Sigma Aldrich, St. Louis, MO, USA). The concentrate was filtered using 0.45-m pore size (47 mm), hydrophilic, polyethersulfone polymer membrane filters (MS® PES Membrane Solutions, Auburn, WA, USA), and stored in sealed bottles at 4ºC until used. DOC concentrations and absorbance measurements were taken to ensure that significant degradation of DOC was not occurring during the storage time, which was consistent with previous studies (Peacock et al. 2015). Exposure solutions for physicochemical characterization (Morris et al. 2024b, see Chapter 3) and physiological testing were made by adding each of the natural DOC concentrates to dechlorinated Vancouver tap water to nominally equal 10 mg C L-1 and the pH was adjusted to approximately pH 7 or pH 4 using HNO3 or NaOH and a sympHonyTM pH electrode (C03243) 101 and meter (SP70P) (VWR International, Radnor, PA, USA) (Appendix B Table SB 1). Solutions were prepared and their pH adjusted at least 12 hours before the experiment to allow equilibration. Immediately before the experiment, the pH was remeasured to confirm that it remained at the target value. DOC concentrations of exposure waters were measured using a Shimadzu total carbon and nitrogen analyzer (TOC-L Shimadzu, Mandel Scientific, Guelph, ON, CA). This physicochemical characterization of exposure solutions was done in a companion study (Morris et al. 2024b, see Chapter 3) and is presented for reference in Table SB 1 of the present study. Morris et al. (2024a, see Chapter 8, 2024c, see Chapter 4) also analyzed the following indices for each of the DOC sources and quantified how they are altered by a change in pH from 7 to 4, as well as their inter-relationships: specific absorbance coefficient at 340 nm (SAC340), molecular weight index (MWI), fluorescence index (FI), the logarithm of the octanol-water partition coefficient (log Kow), molecular charge, PBI, and % humic acid-like, % fulvic acid-like, and % protein-like components by parallel factor analysis (PARAFAC) on fluorescence data. Values for these indices are tabulated in Table SB 2 of the present study. The methods and calculation equations for the physicochemical indices of Morris et al. (2024a, see Chapter 8) are briefly described here, in Appendix B 4.3.3 Transepithelial potential measurements Transepithelial potential measurements (TEP) were made following the procedure outlined by Wood et al. (2020). TEP was measured using intraperitoneal catheters which yield identical data to those generated using more invasive vascular catheters employed in earlier studies (Wood and Grosell 2008). Trout were anesthetized using 0.2 mg L-1 of tricaine methane sulfate (MS222), adjusted to neutral pH using NaOH (Sigma-Aldrich, St. Louis, MO, USA). 102 Gills were irrigated with a continuous flow of anaesthetic water to avoid hypoxic stress (Po and Wood 2021). A 5-cm section of polyethylene PE50 catheter (Clay Adams™, Becton Dickinson, Franklin Lakes, NJ, USA) filled with Cortland saline (Wolf 1963), was inserted into the peritoneal cavity as described by Wood and Grosell (2008). The catheter was anchored using a 2-cm PE160 sleeve secured with cyanoacrylate glue and silk sutures and sealed with a stainless-steel pin. Fish were allowed to recover overnight in separate aerated enclosures supplied with dechlorinated Vancouver tap water (no added DOC) before control TEP measurements were made. TEP determinations employed 3 M KCl agar bridges connected via Ag/AgCl electrodes (World Precision Instruments, Sarasota, FL, USA) to a high impedance voltmeter (Radiometer pHm 82, Radiometer-Copenhagen, Copenhagen, Denmark). The reference bridge was placed into the experimental solution of the measurement chamber and the measurement bridge was connected to the indwelling catheter. The individual measurement chambers were plastic containers filled with 2 L of solution held at 10 °C. Each individual fish was exposed to the appropriate solution for 2 min before the measurements commenced and then three measurements (with correction for junction potential) were completed within a further 2 min, and averaged. Fish were exposed to the control solution without added DOC either at pH 7 or pH 4 in one measurement chamber and then carefully transferred into another measurement chamber containing the experimental solution. The background TEP (baseline TEP measured in the control solution) served as a baseline TEP for comparison with the TEP measured in the experimental solution. The ΔTEP was calculated as the change from baseline TEP caused by the presence of DOC. A paired statistical design was used, where each fish was its own control. TEP was expressed in the traditional manner as the inside voltage relative to the outside water as 0 103 mV. Directly following the experiments fish were euthanized by an overdose of neutralized MS222 (0.5 mg L-1). 4.3.4 Statistical analysis The effect of each DOC source on absolute TEP, compared to the control value within the same pH, was assessed using Student’s paired t-test. The differences between the change in TEP (ΔTEP) amongst DOC sources within the same pH were assessed using one-way ANOVA with Tukey’s post hoc test. Simple linear regressions (p < 0.05) were used to assess relationships between selected indices and TEP, and between these same indices and ΔTEP, at pH 7 and at pH 4. All statistical analyses and data plots were done using GraphPadTM Prism 7 (GraphPad Software, San Diego, CA, USA). A significance level of p < 0.05 (two-tailed) was used throughout. 4.4 Results 4.4.1 Characterization of the five natural DOCs at two pHs using physicochemical indices As summarized in Appendix B Table SB 1 (data from Morris et al. 2024b, see Chapter 3), at pH 7, LO DOC exhibited the lowest aromaticity, as indicated by SAC340, and this coincided with the highest fluorescence index (FI), indicating the most autochthonous origin, which would be expected for a DOC collected from a large natural lake. LO also exhibited the lowest apparent molecular weight as indicated by the MWI value. Note that MWI is an inverse scale, with smaller DOC molecules displaying higher MWI values. In contrast, AP and AS, collected from small ponds, exhibited the highest aromaticities but intermediate positions with respect to FI, whereas their low MWI values indicated large molecular weights. LM DOC, 104 collected from a large swamp, exhibited intermediate aromaticity based on SAC340, but was the most allochthonous in origin as indicated by the lowest FI value, and had a high apparent molecular weight as indicated by the second lowest MWI value. LO DOC was again noteworthy for its greatest lipophilicity indicated by the highest log Kow value, and lowest chemical reactivity as indicated by the lowest PBI, and second lowest molecular charge at pH 7. In contrast, LM demonstrated the lowest lipophilicity (lowest log Kow value), greatest reactivity (highest PBI value), and a high molecular charge. AP DOC was similar to LM DOC in these characteristics, but AS DOC actually carried the greatest molecular charge at pH 7. PARAFAC analysis at pH 7 revealed that fulvic acid-like fluorophores were the dominant component (> 65%) in all 5 DOC sources, whereas the humic acid-like fluorophores accounted for < 30% and the protein-like fluorophores were the smallest component (0–20%). Notably, LM exhibited the highest humic acid-like component, and lowest protein-like component, whereas the opposite was true for AP DOC. PF DOC, collected from a small wetland pond, was generally more similar to LO than to the other three in most characteristics. When the pH was lowered from 7 to 4, some of the site-specific indices changed in order, but the general trends were for reductions in apparent aromaticity (except LM where SAC340 increased), and molecular charge, greater apparent allochthonous origin (again except for LM where FI increased), lower apparent molecular weight (except for PF where MWI decreased), and universal increases in lipophilicity (higher log Kow values), % humic-acid like fluorophores, and reciprocal decreases in % fulvic acid-like fluorophores. The % contribution of protein-like fluorophores also tended to decrease. It is well known that absorbance and fluorescence spectra are pH-dependent (Yan et al. 2013); proton binding sites with pKa values near 4 will become more protonated compared to pH 105 7. Thus, changes in these optical indices are expected and do not imply the sample actually changed in terms of aromaticity, molecular weight, or its origin; this is why the term “apparent” is used in the discussion of the trends (see above). Lipophilicity is a strongly pH-dependent variable where the more neutral (less ionized) form of the molecule will be more lipophilic. As negative sites become protonated, going from pH 7 to pH 4 the lipophilicity will increase. The PBI utilizes data from all titratable pH values and is thus a pH-independent parameter. 4.4.2 The effects of DOC on transepithelial potential in trout There was an overall significant difference between absolute transepithelial potential (TEP) at pH 7 and pH 4 in control, dechlorinated Vancouver tap water (p< 0.0001), with TEP becoming depolarized (i.e. less negative) at pH 4 (overall mean ± SEM = -18.1 ± 0.7 mV, N = 30 at pH 7 versus -4.8 ± 1.0 mV, N = 30 at pH 4). This trend was seen consistently in every control group (Figure 4.1). In response to LO DOC at pH 7, TEP became less negative and at pH 4 it became more negative (Figure 4.1A). Similarly, for PF DOC, TEP became less negative at pH 7 and more negative at pH 4 (Figure 4.1B). However, TEP became more negative at both pH 7 and pH 4 in response to LM DOC (Figure 4.1C), AP DOC (Figure 4.1D), and AS DOC (Figure 4.1E). Figure 4.1A). The ΔTEP values caused by LM, AP and AS DOCs were not significantly different from one another but were significantly different compared to the ΔTEP values caused by LO and PF DOCs at pH 7 (Figure 4.2A). At pH 4, ΔTEP in AP was significantly larger compared to all other DOC sources except LM (Figure 4.2B). The ΔTEP at pH 4 in LM was not significantly different from any of the other sources (Figure 4.2B). The ΔTEP at pH 7 versus pH 4 was only 106 significantly different for LO (p< 0.0001) and PF (p< 0.0001), as indicated by the asterisk symbol (Figure 4.2) 4.4.3 The relationships between TEP and the physicochemical characteristics of DOC Absolute TEP values were regressed separately against specific absorbance coefficient at 340 nm (SAC340), molecular weight index (MWI), fluorescence index (FI), the octanol–water partition coefficient (log Kow), molecular charge, proton binding index (PBI), relative % humic acid-like, relative % fulvic acid-like and relative %, protein-like components at pH 7 and pH 4 using simple linear regression; lines were fitted only for significant relationships (Figure 4.3, Figure 4.4). At pH 7, when absolute TEP was regressed against SAC340 (Figure 4.3A), absolute charge (Figure 4.3I), and PBI (Figure 4.4A), there were significant negative relationships. There were also significant positive relationships between absolute TEP and FI (Figure 4.3C) and absolute TEP and log Kow (Figure 4.3G) at pH 7. At pH 4, there were significant negative relationships when absolute TEP was regressed against FI (Figure 4.3D), log Kow (Figure 4.3H), and relative % protein-like concentration (Figure 4.4H) and with relative %fulvic acid-like concentration (Figure 4.4F). We reasoned that if the relationships were robust, they would persist when ΔTEP (Figure 4.5, Figure 4.6) rather than absolute TEP (Figure 4.3, Figure 4.4) was used in the same regressions because ΔTEP would compensate for inter-individual variations in baseline TEP that might unduly influence relationships. Again, lines were fitted only for significant relationships (Figure 4.5, Figure 4.6). Indeed, at pH 7, the significant negative relationships with SAC340 (Figure 4.5A), absolute charge (Figure 4.5I), and FI (Figure 4.5C) persisted, as did the significant positive relationships with PBI (Figure 4.6A) and log Kow (Figure 4.5G). There was also now a 107 significant positive correlation between relative % fulvic acid-like concentration and ΔTEP (Figure 4.6E). However, at pH 4, there was a loss of the formerly significant relationships with FI (Figure 4.5D), MWI (Figure 4.5F), and log Kow (Figure 4.5H). The significant negative relationship between ΔTEP and relative % protein-like concentration persisted (Figure 4.6H) and significant negative relationships between ΔTEP and SAC340 (Figure 4.5B), ΔTEP and PBI (Figure 4.6B) were now detected. 4.5 Discussion 4.5.1 Overview Each of the DOCs significantly influenced TEP, although in a unique manner or magnitude which may be due to physicochemical differences between the DOCs. In support of our original hypothesis (i) AP and LM had the highest SAC340 values (more aromatic), the lowest FI values (more allochthonous), and the lowest MWI values (larger in molecular size), and with greater PBI and did indeed hyperpolarize TEP to a greater extent, particularly at pH 7 (Appendix B Table SB 2, Figure 4.1, Figure 4.2). However, the predicted relationships with % humic acid content by PARAFAC were not apparent, as discussed subsequently. While LM did have a higher % humic acid-like concentration, AP had amongst the lowest at pH 7 (Appendix B Table SB 2). At pH 4 all DOCs caused TEP to become more negative (i.e. protective) (Figure 4.2). Therefore, our second hypothesis (ii) was only partially supported. The effects on TEP with two sources, LO and PF, went from positive (i.e. less protective) to negative (i.e. more protective); however, the magnitude of the hyperpolarization of the other three sources did not significantly change from pH 7 to pH 4 (LM: p= 0.2878, AP: p= 0.0932, AS: p= 0.960). At pH 7, 108 characteristics that appear to be predictive of a more negative TEP are SAC340 (more aromatic), log Kow (less lipophilic), FI (more allochthonous), molecular charge (higher charge), and PBI (higher value indicating more reactivity). However, not all these indices hold predictive power at pH 4 (Figure 4.3, Figure 4.4, Figure 4.5, Figure 4.6). Therefore, only SAC340, log Kow, and PBI appear to be predictive characteristics across pHs (Figure 4.3, Figure 4.4, Figure 4.5, Figure 4.6). Overall, this analysis supports our hypothesis (iii) that one or more of the indices would strongly predict the effect of DOC on TEP at each pH. 4.5.2 DOCs sharing physicochemical characteristics show similar trends in TEP response Our physicochemical data clearly show two groupings of DOCs based on the similarity of characteristics; LO and PF as one group, and LM, AP, and AS as the other group. LO and PF were less aromatic, more autochthonous, and more lipophilic (Morris et al. 2024b, see Chapter 3) (Appendix B Table SB 2). They also had smaller molecular weights, lower PBIs, and lower absolute charge. LM, AP, and AS had the opposite characteristics: they were more allochthonous, more aromatic, less lipophilic with higher molecular weights, and they had higher PBIs and absolute charges. The trends in TEP responses were likewise similar between LO and PF compared to LM, AP, and AS at pH 7 LO and PF caused depolarization (i.e. less negative/more positive TEP) and LM, AP, and AS caused hyperpolarization (i.e. more negative TEP) (Figure 4.1, Figure 4.2). At pH 4 all sources caused hyperpolarization (Figure 4.1, Figure 4.2) , thereby likely providing more protection to ionoregulation (Wood et al. 2011; Morris et al. 2021, see Chapter 2). Previously, it has been suggested that SAC340 may be an indicator of the ability of a DOC to influence ionoregulation in aquatic organisms (Al-Reasi et al. 2013a; Duarte et al. 2016; 109 Sadauskas‐Henrique et al. 2019) and that the aromaticity of the DOC molecules directly influences the electrophysiology of the fish gill (Galvez et al. 2008). Our results are in support of this: AP, AS, and LM had the highest SAC340 values and induced negative ΔTEP values at pH 7 (Appendix B Table SB 2, Figure 4.2). SAC340 is strongly correlated with molecular size, such that larger DOC molecules are more aromatic (Morris et al. 2024b, see Chapter 3) likely causing a more negative ΔTEP. We did observe that DOCs with larger molecular weights were likewise the DOCs that had the greater influence on TEP; however, the only significant relationship for MWI was with absolute TEP at pH 4 (Figure 4.3F). At pH 7, Galvez et al. (2008) reported a significant negative correlation between ΔTEP and SAC340. Our simple linear regressions showed the same relationship at pH 7 between SAC340 and absolute TEP, and between SAC340 and ΔTEP, and at pH 4 between SAC340 and ΔTEP (Figure 4.3A, B and Figure 4.5A, B). Galvez et al. (2008) suggested that the potency for hyperpolarization is a function of aromaticity. Our data agree with this at pH 7 but not entirely at pH 4. At low pH, SAC340 decreased for LO and PF but there was a coincident hyperpolarization of TEP (Appendix B Table SB 2, Figure 4.3). It is possible that SAC340 is a slightly better predictor of TEP responses at pH 7 than at pH 4. The more negative ΔTEPs at pH 7 for allochthonous DOCs were parallel to previous studies indicating that allochthonous DOCs are highly protective against metal toxicity (Al-Reasi et al. 2011, 2012; Wood et al. 2011), though this difference was no longer apparent at pH 4 (Appendix B Table SB 2, Figure 4.3). Overall, this supports the idea (Al-Reasi et al. 2013a) that DOCs that are important in the protection against metal toxicity may be similar to those that exert physiological effects on the gills. As allochthonous DOCs are generally larger in size, it is possible that molecular size may contribute to the physiological effect of DOC as mentioned above. There were significant positive correlations between FI and absolute TEP and ΔTEP at 110 pH 7 but a significant negative relationship between absolute TEP only at pH 4. The fluorescence profiles changed with pH such that at pH 4 the FI indicated the DOCs to be more autochthonous-like in origin (Morris et al. 2024b, see Chapter 3). This is, perhaps, not surprising as autochthonous DOCs are often less protective and the significant negative correlation by simple linear regression between FI and TEP did not hold true at low pH. The change in pH does not reflect a change in the DOC origin, of course, but rather in the fluorescence profile that we generally associate with a specific origin. The change in pH from 7 to 4 probably reduces the ionization of DOCs, altering the molecular orbital of excitable electrons (Laane 1980; Patel-Sorrentino et al. 2002), and causing the observed increases in log Kow values and reductions in molecular charge, or otherwise affecting the macromolecular composition (i.e. chemical makeup of the molecule) (Morris et al. 2024b, see Chapter 3). Although the overall conclusion appears to be that there is no relationship between lipophilicity and the ability to bind metals (Al-Reasi et al. 2012), it is certainly possible that the lipophilicity of a DOC may influence its ability to interact with the gill membrane and affect ionoregulatory processes. It is possible that the changes from TEP depolarization at pH 7 to TEP hyperpolarization at pH 4 with LO and PF were due to the changes in charge and lipophilicity (Figure 4.2, Figure 4.3). This greater lipophilicity might favor interaction with the cell membranes of the gills, and this may explain the differences in the physiological effects of these two DOCs at pH 7 versus pH 4. At low pH much of the negative charge on both the gills and the DOC molecules will be removed by H+ titration, resulting in ligands that on an overall basis would be more hydrophobic and lipophilic, thereby promoting interaction. Log Kow was significantly positively correlated to absolute TEP and ΔTEP at pH 7 but negatively correlated to absolute TEP only at pH 4 (Figure 4.3G, H and Figure 4.5G, H) whereas the relationships of 111 absolute TEP and ΔTEP to absolute charge were only significant at pH 7. These results indicate that at pH 7, log Kow is correlated to TEP responses that are not protective of Na+ transport but at pH 4, log Kow is correlated to TEP responses that are protective of Na+ transport. In the companion study by Morris et al. (2024b, see Chapter 3), log Kow was not correlated to charge at pH 7 (-0.57) but was very strongly correlated to charge at pH 4 (-0.85, threshold for significance, +/-0.87). It appears that, at pH 4, DOCs with lower charge and higher lipophilicity are beneficial to TEP and in turn Na+ transport. In contrast at pH 7, the reduced lipophilicity may decrease the ability of DOCs to interact with the gill compared to pH 4, and the higher charge could increase TEP in a manner similar to cations such as Na+ and Ca2+ (see Chapter 6). PBI is an indicator of the chemical reactivity of DOC and was developed by Al-Reasi et al. (2013a) for predicting its metal binding capacity; higher PBI was protective towards metal toxicity and is thought to represent the potential for “tridentate” metal binding sites in DOC molecules. These authors proposed that PBI may also be useful in predicting the effects of DOC on physiological processes, but did not test the idea experimentally. PBI, because it uses data from the entire titratable range, is a pH-independent parameter. Our study shows, for the first time, that PBI is a useful tool in predicting the TEP response to natural DOCs in freshwater fish. DOCs with higher PBIs generally had a larger effect on ΔTEP (Appendix B Table SB 2, Figure 4.2). PBI was significantly negatively correlated to absolute TEP at pH 7 (Figure 4.4A) and to ΔTEP at pH 7 and pH 4 (Figure 4.6A, B). With regards to the PARAFAC components, relative % humic acid-like concentration was not a useful predictor of TEP response. There were no significant relationships between relative % humic acid-like concentration and absolute TEP or ΔTEP at either of the tested pHs (Figure 4.4C, D and Figure 4.6C, D). These results were surprising because, in general, DOCs 112 that have a high humic acid concentration are also more aromatic and have higher molecular weights. As such, SAC340 has previously been positively correlated with relative % humic acid‐like concentration (PARAFAC component) and negatively correlated with the relative % fulvic acid‐like concentration (Al-Reasi et al. 2012). As described by Morris et al. (2024b, see Chapter 3) at pH 4, the sources that we used in the present study were consistent with this observation: AP had the highest SAC340 value, the highest humic-like concentration, and the lowest fulvic-like concentration (Appendix B Table SB 2). However, at pH 7 this was not the case. Morris et al. (2024b, see Chapter 3) reported a significant correlation between SAC340 and MWI and we did observe that DOCs with larger molecular weights were likewise the DOCs that had the greater influence on TEP. However, the only significant relationship between MWI was with absolute TEP at pH 7 (Figure 4.4E). For relative % fulvic acid-like concentration, absolute TEP was positively correlated at pH 4 (Figure 4.4F) and ΔTEP was positively correlated at pH 7 (Figure 4.6E), making it a better predictor of TEP effects. Again, it was surprising that the best PARAFAC component for predicting TEP response appeared to be relative % protein-like concentration but only at pH 4, where there was a significantly negative relationship with both absolute TEP and ΔTEP (Figure 4.4H and Figure 4.6H). However, it must be remembered that PARAFAC components are user-defined and the results depend on the quality and number of samples inputted, which is likely why our PARAFAC components show different relationships with SAC340 at pH 7 than previously reported, even though the quality and number of samples were acceptable in both Al-Reasi et al. (2012) and the present study. Overall, we conclude that the PARAFAC results must be interpreted with caution, as they are sample-dependent. It is possible that with a different set of natural DOC sources, PARAFAC components may provide more useful predictors of TEP responses than seen in the current study. 113 4.6 Concluding remarks The TEP response to natural DOCs appears to be directly related to their physicochemical characteristics. The most effective predictors of DOC effects on TEP were SAC340, log Kow, and PBI across pHs. Each of these indices had at least three significant relationships within the simple linear regression plots (Figure 4.3, Figure 4.4, Figure 4.5, Figure 4.6). The changes in these three indices with the change in pH from pH 7 to pH 4 likely reflect molecular or structural changes in the DOC as described above and by Morris et al. (2024b, see Chapter 3). This contrasts with other indices where there are changes in the optical signature that likely do not reflect changes in the DOC molecule. For example, the difference in the SAC340 value from pH 7 to pH 4 may reflect changes in the conformation, rather than in composition of the DOC molecule and this could be the cause of the altered TEP response for a given DOC source. FI also had three significant relationships within the simple linear regressions. However, as described by Morris et al. (2024b, see Chapter 3), and above, pH related changes in FI do not reflect changes in what the index is thought to represent (i.e. the origin of the DOC). Morris et al. (2024b, see Chapter 3) showed that the origin of the DOC does not change with a change in pH, rather, the fluorescence profile and in turn how we interpret that value changes. Therefore, we reject FI as being truly a good predictor of TEP effects across pHs. The natural water pHs of our sites were near circumneutral with a range of 6.83-7.35 (Morris et al. 2024b, see Chapter 3); however, these sites could be subjected to acidification through climate change events especially those situated in swamp or bog areas. The dissociation of protons from allochthonous DOC is a major cause of the acidity in natural blackwaters so as DOC concentrations increase, pH often decreases. 114 The hyperpolarization of TEP caused by DOC improves Na+ uptake and opposes Na+ efflux at the gills and is therefore supportive of ionoregulatory function. DOCs that are more aromatic, more chemically reactive, and less lipophilic may influence the paracellular permeability of the gills, mitigating diffusive ion loss. This, in turn, could alter the differential permeability of Na+ versus Cl- at the gill, directly influencing TEP where a more negative. TEP creates a favorable electrochemical gradient for net Na+ retention. This is even more important at low environmental pH where the diffusion gradient for proton entry is increased (see Section 4.2). Our short exposure times were designed to understand how changes in water chemistry impact TEP at a mechanistic level. Our experimental exposures were very acute; however, changes in TEP from acute exposures have been shown to persist and remain stable for 24 h (Wood et al. 2020) and even 96 h (Po and Wood 2022). Further investigation will be necessary to determine whether TEP responses are sustained beyond 96 h. Sustained changes in TEP from the baseline would likely have profound effects on overall ionoregulatory processes and homeostasis. While our data clearly show that some physicochemical properties of DOC are better predictors of TEP outcome than others, further work is required to explore which functional moieties of DOC are influencing TEP at the gills at circumneutral and acidic pH. For example, here, we show that aromaticity (SAC340), lipophilicity (log Kow), and chemical reactivity (PBI) are important characteristics of DOC in predicting the TEP responses, but future studies are needed to determine which particular chemical components associated with these properties are causing the TEP responses. In freshwater systems DOC concentrations are increasing (Morris et al. 2021, see Chapter 2; Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025), while pH levels are declining; as a result 115 of the rise in DOC concentrations and as a consequence of climate change (Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; Quijada-Rodriguez et al. 2021). The roles of DOCs within an ecosystem are widespread, spanning from UV light screening and changing microbial activity to influencing the bioavailability of contaminants, all of which may influence the health of freshwater fish. Therefore, a mechanistic understanding of not only the interaction between the physicochemical properties of DOC and ionoregulation in fish but also how these physicochemical characteristics influence other environmental parameters is crucial for the future monitoring of aquatic environmental health. Future studies should aim to integrate the effects of DOC on other physiological endpoints in freshwater organisms with the physicochemical properties of DOC while simultaneously considering other water quality parameters such as pH, hardness, alkalinity, major ion concentrations, and potential pollutants. 116 4.7 Chapter 4 – Figures Figure 4.1. The effect of natural DOC sources on absolute transepithelial potential (TEP) (A) Lake Ontario (LO), (B) Preston Flats (PF), (C) Luther Marsh (LM), (D) Ancient Woods Pond (AP) and (E) Ancient Woods Swamp (AS) at pH 7 and pH 4. Values are mean ± SEM, N=6. Asterisks indicate statistically significant differences (p<0.05 by Student’s paired t-test). 117 Figure 4.2. The effect of natural DOC sources on delta transepithelial potential (ΔTEP) (A) Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM) Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at pH 7 and (B) Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM) Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at pH 4. Values are mean ± SEM, N=6. Letters that differ indicate statistically significant differences (p<0.05 by one way ANOVA plus Tukey’s post hoc test). The asterisk symbol indicates the significant difference between the ΔTEP at pH 7 versus pH 4. 118 119 Figure 4.3. Absolute TEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Specific absorbance coefficient, (C, D) Fluorescence index, (E, F) Molecular weight index, (G, H) log Kow and (I, J) absolute charge. Values are mean ± SEM, N=6. A fitted line indicates statistical significance (p<0.05 by simple linear regression). 120 121 Figure 4.4. Absolute TEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Proton binding index, (C, D) relative % humic acid-like concentration, (E, F) relative % fulvic acid-like concentration (G, H) relative % protein-like concentration. Values are mean ± SEM, N=6. A fitted line indicates statistical significance (p<0.05 by simple linear regression). 122 123 Figure 4.5. ΔTEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Specific absorbance coefficient, (C, D) Fluorescence index, (E, F) Molecular weight index, (G, H) log Kow and (I, J) absolute charge. Values are mean ± SEM, N=6. A fitted line indicates statistical significance (p<0.05 by simple linear regression). 124 125 Figure 4.6. ΔTEP of natural DOC sources at pH 7 and pH 4 regressed against (A, B) Proton binding index, (C, D) relative % humic acid-like concentration, (E, F) relative % fulvic acid-like concentration (G, H) relative % protein-like concentration. Values are mean ± SEM, N =6. A fitted line indicates statistical significance (p<0.05 by simple linear regression). 126 Chapter 5: Model compounds as analogues for dissolved organic matter: physicochemical characterization and their effects on the electrical properties of the rainbow trout gill at circumneutral and low pH. 5.1 Summary Dissolved organic carbon (DOC) has an important, although not fully understood, ecological role in aquatic ecosystems. It influences both abiotic and biotic factors including ionoregulatory processes of the freshwater fish gill. A mechanistic understanding of the effects of DOC on these processes is crucial for monitoring aquatic health; however, this mechanistic understanding is challenging due to the complexity and heterogeneity of natural DOCs. To determine the key chemical moieties of DOC contributing to changes in ionoregulation, twenty model compounds were chosen based on the criteria that they structurally resemble and/or functionally behave like certain components of typical humic and fulvic acids found in natural waters. Each model compound was characterized using the physicochemical indices that are often used to characterize natural DOCs - e.g. specific absorbance coefficient (SAC340), octanol water partition coefficient (log Kow), molecular weight index (MWI), fluorescence index (FI), and molecular charge. Additionally, their effects on transepithelial potential (TEP), an indicator of osmoregulatory status, were tested at pH 7 and pH 4 in freshwater rainbow trout. Most characterization techniques based on absorbance and fluorescence signatures proved to be inappropriate for synthetic model compounds. However, indices based on titration properties including lipophilicity (i.e. log Kow), and charge may be used as predictors of TEP response, with careful consideration of pH. Our results demonstrate that some model compounds may be used as predictors of TEP. Specifically, phenolic groups and long aliphatic chains may be 127 contributing to the TEP response in natural allochthonous DOCs making tannic acid (TA) and sodium dodecyl sulphate (SDS) appropriate model compounds for this type of DOC. Amino acids and peptides may contribute to the effect of autochthonous DOCs on TEP, making bovine serum albumin (BSA) a possible model compound for DOC of this origin. 5.2 Introduction Dissolved organic carbon compounds (DOCs) are naturally occurring, critical components of freshwater that influence the structure, function, and diversity of aquatic ecosystems (Findlay and Parr 2017). They are often considered to be ecological drivers (Petersen 1991; Kullberg et al. 1993; Steinberg et al. 2006; Al-Reasi et al. 2011), affecting not only physical processes such as ultraviolet light screening and temperature gradients through the water column (Kullberg et al. 1993; Sucker and Krause 2010; Johannsson et al. 2017), but also physiological processes within individual organisms (reviewed by Wood et al. 2011; Morris et al. 2021, see Chapter 2), nutrient transfer across trophic levels (Findlay and Parr 2017) and bioavailability of metal contaminants (Playle et al. 1993; Hollis et al. 2001; Matsuo et al. 2004; Wood et al. 2011; Crémazy et al. 2016). Although the wide-spanning roles of DOC within aquatic ecosystems are not yet fully understood, it is clear that DOCs exert physiological effects on aquatic organisms particularly, fish. These effects are often beneficial to osmoregulatory processes especially in acidic fresh waters. DOCs protect against the inhibition of active ion uptake of major salt ions (Na+, Cl-) and against the passive ion loss that normally occurs at environmentally low pH (i.e. 3.5-5) (Gonzalez et al. 2002, 2005; Wood et al. 2003, 2011; Matsuo et al. 2004; Glover et al. 2005; Glover and Wood 2005; Al-Reasi et al. 2016; Duarte et al. 2016, 128 2018). Transepithelial potential (TEP), the diffusion potential between the blood plasma and the external water, is an important osmoregulatory indictor. It is predominantly due to the differential permeabilities of Na+ versus Cl- across the gills (Potts 1984). TEP is influenced by an acidic environment that alters this differential permeability of Na+ versus Cl- and increases the diffusion gradient for proton entry, thereby depolarizing the TEP to less negative/more positive values. This favours Na+ efflux, opposes active Na+ influx, and thereby increases net Na+ loss rates (McWilliams and Potts 1978; Wood et al. 1998; Sadauskas‐Henrique et al. 2019; Morris et al. 2024c, see Chapter 4). On the other hand, fresh, natural DOCs have been found to cause a hyperpolarization of TEP to more negative values in freshwater fish; this improves the electrochemical gradient for net Na+ uptake at the gills, and is likely an important contributor to the positive effects of DOCs on ionoregulation (Wood et al. 2011, 2025; Morris et al. 2021, see Chapter 2). Some DOCs are more effective at exerting physiological effects than others, reflecting their complexity and heterogeneity (Wood et al. 2011; Al-Reasi et al. 2013a; Sadauskas‐Henrique et al. 2019) and the extent of the effects appear to vary with DOC type, and pH (Wood et al. 2011; Morris et al. 2021, see Chapter 2). This is likely due to their functional chemical moieties. DOC molecules are formed through the breakdown of organic matter by light, heat, enzymes and microbes in the soil and water, with the exact structures remaining unknown (Zara et al. 2006). They are made up of two major components: (i) large humic substances (humic and fulvic acids) composed of carbon, nitrogen, oxygen and sulfur creating organic acids with oxygenated functional groups; (ii) non-humic substances such as amino acids, fatty acids, phenols, hydrocarbons and natural sugars (Thurman 1985; Boggs et al. 1985; Kullberg et al. 1993; Gaffney et al. 1996). 129 Recently, we have used indirect approaches based on physicochemical indices to understand which chemical moieties of natural DOCs may be contributing to their effects in freshwater rainbow at circumneutral and acidic pHs (Morris et al. 2024b, see Chapter 3, 2024c, see Chapter 4). The principal conclusions were that three particularly important indices were predictors of changes in TEP across pHs in rainbow trout: specific absorbance coefficient at 340 nm (SAC340), octanol-water partition coefficient (log Kow), and proton binding index (PBI) as reflected in molecular charge. Furthermore, the changes in these three indices between pH 7 to pH 4, and the changes in their effects on TEP, likely reflected either conformational changes (SAC340) or compositional changes (log Kow and PBI) in the DOC, as well as changes in the gill surface, with low pH. In the present study we have adopted a direct approach in order to refine these conclusions. Specifically, we have chosen 20 model compounds within 7 key chemical moiety groups (see Appendix C based on the criteria that they structurally resemble or functionally behave like key components of different DOCs. We tested each model compound on TEP in freshwater trout at pH 7 and pH 4. Our specific hypotheses were that: (i) as with natural DOCs, the effects of selected model compounds on TEP would be pH-dependent; (ii) model compounds sharing key chemical moieties with each other would have similar effects on TEP; (iii) the effects of the model compounds on TEP would be related to their lipophilicity or charge; (iv) some model compounds would show similar response patterns to natural DOCs. 130 5.3 Methods 5.3.1 Experimental animals Juvenile rainbow trout (Oncorhynchus mykiss) (N=240, 109.9 ± 10.0 g) were obtained from the Freshwater Fisheries Society of BC (Abbotsford, BC, Canada). Prior to commencing experiments, fish were held at the University of British Columbia (UBC) for several months at 12 ºC in flowing dechlorinated Vancouver tap water (Na+ = 0.09, Cl- = 0.10, Ca2+ = 0.10, Mg2+ = 0.011, K+ = 0.004 mmol L-1, hardness as CaCO3 = 3.3 mg L-1, pH = 7, [DOC] = ~1.07 mg C L-1). Fish were fed to satiation every second day with commercial pellet food (BioTrout 2.0 mm, Bio-OregonTM, Long-view, WA, USA) and were fasted for at least 72 h prior to experiments. All experiments were approved by the UBC Animal Care Committee (A18-0271 and A22-0195) and conformed to national regulations of the Canada Council for Animal Care. 5.3.2 Chemical moiety groups We tested 20 model compounds spanning 7 key chemical moieties in total, at pH 7 and pH 4. Details on the model compounds and the reasons for selecting them are provided in Appendix C and are briefly addressed in the Discussion. These model compounds, as organized within their chemical moiety groups, were: 1) Tannic and humic acids: tannic acid (TA) and AldrichTM humic acid (AHA) 2) Phenolic acids: salicyclic acid (SA) and naphthionic acid (NA) 3) Surfactants: sodium dodecyl sulfate (SDS) and linear alkylbenzene sulfonate (LAS) 4) Carboxylic acids: formic acid (FA) and acetic acid (AA). 5) Fatty acids: palmitic acid (PA), steric acid (StA), methyl palmitate (MP) and methyl stearate (MS). 131 6) Amino acids and amino acid-rich molecules: tryptophan (Tryp), tyrosine (Tyr) -lactalbumin (LAC), and bovine serum albumin (BSA). 7) Sugars: glucose (Glu), galactose (Galac), mannose (Mann) and fructose (Fru) 5.3.3 Experimental solutions Fresh model compound solutions were made by completely dissolving each compound (Sigma Aldrich, St. Louis, MO, USA) in dechlorinated Vancouver tap water to nominally equal 10 mg C L−1. The compounds in the fatty acid group, palmitic acid, steric acid, methyl palmitate and methyl stearate are not soluble in water and therefore were dissolved in 0.1% dimethylsulfoxide (DMSO). Control experiments with 0.1% alone were performed to ensure that the effect of DMSO alone was taken into account. The pH of each solution was adjusted to approximately pH 7 or pH 4 using HNO3 or NaOH and a sympHonyTM pH electrode (C03243) and meter (SP70P) (VWR International, Radnor, PA, USA). The solutions were made, and pH was adjusted at least 12 hours prior to the experiment to allow for equilibration. Directly prior to the experiment the pH, was measured again to ensure that the solution was still at the target pH. To ensure we were working with the dissolved compounds only, the solutions were filtered using 0.45-m pore size (47 mm), hydrophilic, polyethersulfone polymer membrane filters (MS® PES Membrane Solutions, Auburn, WA, USA). DOC concentrations of exposure waters were measured using a Shimadzu total carbon and nitrogen analyzer (TOC-L Shimadzu, Mandel Scientific, Guelph, ON, CA) (Appendix C We found that the 0.1% DMSO interfered with the functioning of the DOC analyser, so the carbon concentrations for the four compounds in the fatty acid group could not be confirmed by analysis. 132 5.3.4 Optical characterization of the model compounds The optical characterization techniques, based on absorbance and fluorescence measurements which we and others have used for natural DOCs (Curtis and Schindler 1997b; Peuravuori and Pihlaja 1997; McKnight et al. 2001; Stedmon and Bro 2008; DePalma et al. 2011; Al-Reasi et al. 2011; Morris et al. 2024b, see Chapter 3) include specific absorbance coefficient at 340 nm (SAC340), molecular weight index (MWI), fluorescence index (FI), and molecular charge. As we utilized model compounds as DOC analogues in this mechanistic study, we attempted to use these same techniques to characterize our exposure solutions. However, our results show that these techniques may not be appropriate comparison metrics, reflecting the, in many cases, synthetic nature of the model compounds. The methods and calculation equations for the physicochemical indices are briefly described in Appendix C with the techniques we believe acceptable outlined in further detail below. As many of the compounds yielded negative fluorescence and absorbance values which were reflected in some of the indices, we have rejected them. We have reported the full results of these indices in Appendix C Indices based on titration properties including lipophilicity and charge are applicable and important and are outlined below. 5.3.5 Octanol-water partition coefficient (log Kow) The octanol-water partition coefficient (log Kow) is a measure of lipophilicity. For many of the model compounds there were previously published data, however not at the pH of interest (i.e. pH 7 or pH 4). We used the following calculation to determine the log Kow. The proportion of protonated ligand was adjusted based on Equation 5.3 (below) as a correction for pH (Harris and Lucy 2020): 133 𝐾𝑜𝑤 =[𝐻𝐿 𝑜𝑐𝑡]𝐿𝑇 (Equation 5.1) Where: Kow = Octanol water partition coefficient HL oct= fraction of ligand in octanol LT= ligand total To use this calculation, and the below charge calculation, the previously published pK values and protonated structure must be incorporated. For compounds where log Kow was not reported in the literature, we performed measurements as per Gjessing et al. (1999). Octanol (5 ml) was added to a 15-mL aqueous model compound sample which was gently but thoroughly mixed using a 3-dimensonal nutating mixer for 2.5 h. The distribution of the DOC in the water phase and octanol phase was determined by measuring the absorbance in each phase at 254 nm (Gjessing et al. 1999). Log Kow was calculated as: log Kow = 𝑙𝑜𝑔 (Abs254in octanol phaseAbs254in aqueous phase) (Equation 5.2) Higher log Kow values indicate a more lipophilic sample. 134 5.3.6 Molecular charge Molecular charge of the model compound, as moles of charge per mg of carbon, is an indication of the ionizable fraction of the molecule. Charge was determined through the following calculation: ∝ 𝐻𝐿 =[𝐻+]𝐾𝑎 + [𝐻+] (Equation 5.3) Where: ∝ 𝐻𝐿 = fraction of total that is protonated [H+] = 10-(pH) concentration of protons Ka= 10-(pKa) proton dissociation constant 5.3.7 Transepithelial potential measurements Following the procedure outlined by Wood et al. (2020), transepithelial potential (TEP) measurements were made using intraperitoneal catheters which have been shown to yield identical data to those generated using more invasive vascular catheters employed in earlier studies (Wood and Grosell 2008). Tricaine methane sulfate (MS222), adjusted to neutral pH using NaOH (Sigma -Aldrich) at a concentration of 0.2 mg L-1 was used to anesthetize the fish. Gills were irrigated with a continuous flow of anaesthetic water to avoid hypoxic stress during surgery (Po and Wood 2021). As described by Wood and Grosell (2008), a polyethylene PE50 catheter (Clay Adams™, Becton Dickinson, Franklin Lakes, NJ, USA) (5-cm) filled with Cortland saline (Wolf 1963), was inserted into the peritoneal cavity. The catheter was anchored using a 2-cm PE160 sleeve secured with cyanoacrylate glue and silk sutures and sealed with a 135 stainless-steel pin. Prior to control TEP measurements, fish were allowed to recover overnight in separate aerated enclosures supplied with dechlorinated Vancouver tap water (no added DOC). TEP determinations employed 3 M KCl agar bridges connected via Ag/AgCl electrodes (World Precision Instruments, Sarasota, FL, USA) to a high impedance voltmeter (Radiometer pHm 82, Radiometer-Copenhagen, Copenhagen, DK). The reference bridge was placed into the experimental solution of the measurement chamber and the measurement bridge was connected to the indwelling catheter. The individual measurement chambers were plastic containers filled with 2 L of solution held at 10 °C. Individual fish were exposed to the control solution without added model compounds either at pH 7 or pH 4 in one chamber (for approximately 2 mins) for the measurement of the control TEP. The fish was then transferred carefully, to minimize air exposure, into another measurement chamber containing the experimental solution for the measurement of the experimental TEP. Each fish was exposed to the appropriate solution for 2 min before the measurements commenced and then three measurements (with correction for junction potential) were completed within a further 2 min, and averaged. The background TEP (TEP measured in the control solution) served as a baseline TEP for comparison with the TEP measured in the experimental solution. The ΔTEP was calculated as the change from baseline TEP caused by the presence of the experimental solution (i.e. model compound). Each fish served as its own control in this paired statistical design. TEP was expressed in the traditional manner as the inside voltage relative to the outside water as 0 mV. Fish were euthanized by an overdose of neutralized MS222 (0.5 mg L-1) directly following the experiment. 136 5.3.8 Statistical analysis The effect of each model compound on absolute TEP at pH 7 and pH 4, compared to the control value within the same pH, was assessed using Student’s paired t-test. Simple linear regressions (p < 0.05) were used to assess relationships between selected indices (log Kow and molecular charge) and TEP or ΔTEP at pH 7 and at pH 4. All statistical analyses and data plots were conducted using GraphPadTM Prism 7 (GraphPad Software, San Diego, CA, USA). Data are means ± SEMs. A significance level of p < 0.05 (two-tailed) was used throughout. 5.4 Results 5.4.1 The effect of model compounds on transepithelial potential The overall average TEP under control conditions at pH 7 for rainbow trout in dechlorinated Vancouver tap-water was -19.6 ± 0.6 (N = 114) mV, with the mean control values in individual groups ranging from -28.6 mV to -13.2 mV. In all test groups, exposure to pH 4 caused significant depolarization of the TEP to less negative/more positive values. The overall average TEP at pH 4 under control conditions was -3.7 ± 0.7 (N = 114) mV, with mean control values in individual groups ranging from -13.8 mV to 5.5 mV. Within the tannic and humic acids group, in response to tannic acid (TA), there was a significant decrease in TEP from control values at pH 7 but no significant change in TEP at pH 4 (Figure 5.1A). Exposure to AldrichTM humic acid (AHA) resulted in no change in TEP from the control at pH 7, but AHA caused a significant decrease in TEP to more negative values at pH 4 (Figure 5.1B). 137 Within the phenolic acids group, there was no effect of either salicyclic acid (SA) or naphthionic acid (NA) on TEP relative to control values at pH 7 (Figure 5.1C, D). However, at pH 4, both SA and NA caused significant increases in TEP relative to control values at pH 4. In response to both tested anionic surfactants, sodium dodecyl sulfate (SDS) (Figure 5.1E) and linear alkylbenzene sulfonate (LAS) (Figure 5.1F), TEP became more negative at both pH 7 and pH 4. The relative hyperpolarizations were of comparable magnitude at the two pHs. Within the carboxylic acid group, formic acid (FA) had no effect on TEP at pH 7, but caused a significant increase in TEP relative to the control group at pH 4 (Figure 5.2A). However, acetic acid (AA) had no effect on TEP at either pH 7 or pH 4 (Figure 5.2B). There was no effect of any of the fatty acids tested; palmitic acid (PA) (Figure 5.2C), steric acid (StA) (Figure 5.2D), methyl palmitate (MP) (Figure 5.2E) or methyl stearate (MS) (Figure 5.2F) on TEP at either pH 7 or pH 4. DMSO control water did not have a significant effect on TEP values compared to the VTW control water (p= 0.9721, paired Student’s t-test). Within the amino acids and amino-acid rich molecules group, tryptophan (Tryp) significantly increased TEP relative to the control at pH 7, but had no effect at pH 4 (Figure 5.3A). In contrast there was no effect of the other free amino acid tyrosine (Tyr) at either pH 7 or pH 4 (Figure 5.3B). -lactalbumin (LAC) had no effect on TEP at pH 7, but significantly increased TEP relative to the control at pH 4 (Figure 5.3C). Bovine serum albumin (BSA) resulted in a significant increase in TEP relative to the control at pH 7 and a significant decrease in TEP relative to the control at pH 4 (Figure 5.3D). Within the sugars group, there were no significant effects of either glucose (Glu) (Figure 5.3E) or galactose (Galac) (Figure 5.3F) at either pH 7 or pH 4. However, in marked contrast, exposure to both mannose (Mann) (Figure 5.3G) and fructose (Fru) (Figure 5.3H) had no effects 138 at pH 7, but caused marked decreases in TEP (i.e. hyperpolarization) relative to their respective control groups at pH 4. 5.4.2 The relationship between lipophilicity and charge of the model compounds and TEP response at pH 7 and pH 4. Absolute TEP values were regressed against corrected log Kow and charge values for individual model compounds (where possible; some values are unavailable) (Appendix C Table SC 3) separately at pH 7 and pH 4 using simple linear regressions (Figure 5.4, Figure 5.5). Regressions were also performed on the data when they were grouped by the 7 chemical moiety categories (see Section 5.3.2) and expressed as means and are reported in the supplementary material (Appendix C Figure SC 1). Lines were fitted only for significant relationships. At pH 7, when absolute TEP was regressed against log Kow, the relationship was not significant (Figure 5.4A), however, at pH 4 there was a significant positive correlation between absolute TEP and log Kow (Figure 5.4B). This same pattern was observed in the regressions where the data were grouped into the 7 chemical moiety categories (Appendix C When absolute TEP was regressed against charge there was a significant positive relationship (driven largely by TA) (Figure 5.4C) and a significantly negative relationship at pH 4 (Figure 5.4D). Once again these were the same trends noted when the data were represented as means of the 7 chemical moiety categories (Appendix C Figure SC 1, Figure SC 2). Given that ΔTEP compensates for the inter-individual variations in baseline TEP, robust relationships may also persist when regressions are performed with ΔTEP rather than absolute TEP against the same chemical indices, log Kow and charge. As with absolute TEP, when ΔTEP was regressed against log Kow, there was no significant relationship at pH 7 but there was a 139 significant positive relationship at pH 4 (Figure 5.5A, B). This was mirrored in the chemical moiety categories regressions (A, B). For charge, again the regression at pH 7 was significantly positive with ΔTEP and was significantly negative at pH 4 (Figure 5.5C, D). This trend was similar in the chemical moiety regressions but only at pH 4 (Appendix C Figure SC 2C, D). 5.5 Discussion 5.5.1 Overview While most DOC characterization techniques based on absorbance and fluorescence signatures were not appropriate for the synthetic model compounds tested, some of these compounds did cause TEP responses that were similar to those caused by natural DOCs. In support of our original hypothesis (i) many of the model compounds had pH-dependent effects on TEP. Most model compounds that resulted in a change in TEP showed a significant response at only one of the two tested pHs including tannic acid (TA), AldrichTM humic acid (AHA), salicylic acid (SA), naphthionic acid (NA), formic acid (FA), -lactalbumin (LAC), mannose (Mann) and fructose (Fruc) (Figure 5.1A, B, C, D, Figure 5.2A, C, G, H). (ii) Our second hypothesis, that model compounds sharing key chemical moieties would have similar effects on TEP was largely unsupported. We had predicted that the TEP results within each of the individual 7 key chemical moiety groups would be quite similar. The surfactant group (Figure 5.1E, F) was the only chemical moiety group where all the tested model compounds within the same category showed similar trends in TEP. (iii) In support of our third hypothesis, based on our regression results, the effects of the model compounds on TEP were indeed related to their lipophilicity and charge but only at pH 4 (Figure 5.4, Figure 5.5). When lipophilicity was regressed against absolute TEP or ΔTEP there was a significant positive relationship at pH 4 140 (Figure 5.4B, B) while the relationship between absolute TEP or ΔTEP and charge at pH 4 was significantly negative (Figure 5.4D, D). It has been previously observed that both the quality and origin of natural DOCs are reflected in the TEP response. Generally allochthonous, aromatic DOCs result in a decrease in TEP at circumneutral and acidic pHs, whereas autochthonous peptide-rich DOCs result in an increase in TEP at neutral pH and a decrease in TEP at low pH (Morris et al. 2024c, see Chapter 4). (iv) In accord with our final hypothesis, some model compounds did show similar response patterns to natural DOCs. For example, the two tested surfactants (SDS and LAC) resulted in a decrease in TEP at both pHs (Figure 5.1E, F) as is often seen with allochthonous DOCs (Morris et al. 2024c, see Chapter 4). Similar to autochthonous DOCs (Morris et al. 2024c, see Chapter 4), BSA resulted in an increase in TEP at pH 7 and a decrease in TEP at pH 4 (Figure 5.3D). 5.5.2 Possible key chemical moieties of natural DOCs influencing TEP, informed by model compounds Indeed, natural DOCs are extremely complex and cannot be represented by synthetic model compounds in a comprehensive manner. However, by individually testing several chemical moiety groups, with at least two representative model compounds within each group, we were able to identify components of natural DOCs that may be important in exerting physiological effects. Below we briefly discuss with further details in Appendix C the 7 key chemical moiety groups tested and highlight the potentially important moieties of natural DOCs that contribute to change in TEP. TA and AHA (group 1 - Tannic and humic acids) are commonly employed as analogues of natural DOCs. TA is often used as a model allochthonous carbon compound (Wershaw 1999; 141 Moreno-Castilla et al. 2004; Lin and Baoshan 2008; Campinas et al. 2013) as it is highly aromatic with polyphenolic biomolecules. Acute exposure to TA at pH 7 resulted in a decrease in TEP (Figure 5.1A), a response that has been observed with some allochthonous DOCs (Galvez et al. 2008; Morris et al. 2024c, see Chapter 4). Generally, the decrease in TEP caused by natural DOCs is supportive of ionoregulatory function, improving Na+ influx and opposing Na+ efflux at the gills. Notably, TA was the only model compound found to decrease TEP at pH 7. Based on the structure of TA and the TEP response we conclude that this model compound is likely a useful tool to assess the TEP effects of phenolic groups in allochthonous natural DOCs. Often used as a commercial source of humic acid, AldrichTM humic acid (AHA) is derived from natural sources such as soil and peats and contains large aromatic polysaccharides. However, it is known to have marked differences in its chemical properties compared to fresh natural DOC (Thurman 1985; Morris et al. 2021, see Chapter 2). AHA has been found to exacerbate physiological disturbances rather than protect against them in Amazonian stingrays (Wood et al. 2003), tambaqui (Perry et al. 2021), silver catfish (da Costa et al. 2015, 2017) and daphnia (Glover and Wood 2005; Al-Reasi et al. 2013a). Although we observed a significant decrease in TEP at low pH with AHA (Figure 5.1B), due to previously reported chemical differences and the maladaptive physiological effects mentioned above, we do not believe that it is a useful compound to represent a key component of natural DOCs. It is well recognized that DOC mitigates metal toxicity by reducing the bioavailability of metal cations through complexation (Playle et al. 1993; Hollis et al. 2001; Matsuo et al. 2004; Wood et al. 2011; Crémazy et al. 2016). Al-Reasi et al. (2013) proposed that the same physicochemical properties of DOCs that are important in protection against metal toxicity also protect ionoregulatory function at low pH. Therefore, we tested two phenolic acids, SA and NA 142 (category 2- phenolic acids) that are known for their metal complexing properties (Perrin 1958) and have been previously used as DOC proxies (Smith and Kramer 1999). The two phenolic acids have a similar structure, but NA has two aromatic rings rather than one and is twice as large. Both compounds resulted in a more positive TEP at low pH (Figure 5.1C, D). As both compounds show the same response at the same pH, it is possible that phenolic acids are valuable model compounds. However, we do not often observe increases in TEP at low pH with natural DOCs (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019; Morris et al. 2024c, see Chapter 4) , so it is uncertain if phenolic acids represent a chemical moiety contributing to TEP responses in natural DOCs. The ability to solubilize a wide range of hydrophobic materials, the surfactant property, is a notable characteristic of humic acids in natural DOCs (von Wandruszka 2000; Young and von Wandruszka 2001). As humic substances contain mostly negatively charged components, anionic surfactants: sodium dodecyl sulfate (SDS) and linear alkylbenzene sulfonate (LAS) (group 3 – surfactants) were tested in the present study. Both surfactants tested resulted in a decrease in TEP at pH 7 and pH 4 (Figure 5.1E, 1F), a similar response to natural, allochthonous DOCs (Galvez et al. 2008; Morris et al. 2024c, see Chapter 4). The importance of the surfactant property in natural DOCs and the shared TEP response led us to conclude that both of the tested surfactants are appropriate compounds to represent the surfactant property of DOC. Due to the magnitude of TEP response (Figure 5.1E) as well as the availability and relative costs of the two compounds, we would recommend SDS rather than LAC for future studies. Both of the major components of DOCs; humic and fulvic acids, contain carboxylic acid groups (Thurman 1985), the 4th key chemical moiety category. Of the two compounds that we tested, formic acid (FA) which is the simplest one with a single carbon atom, and acetic acid 143 (AA) is the second simplest with two carbon atoms. We predicted that the larger molecule (AA) would result in a TEP response. Our prediction was incorrect; there was a significant increase in TEP at pH 4 with FA and no significant change in TEP at either pH with AA. As mentioned above, it is not common to see an increase in TEP at low pH with natural DOC. This, coupled with the fact that this was the only significant response out of the four experimental solutions (AA and FA at pH 7 and pH 4) tested for carboxylic acids, it is likely that carboxylic acids are not a major contributor to the TEP response that we see in natural DOCs. Long chain fatty acids have been found in humic acids and much like surfactants, create micelles (Liao et al. 1982; Thurman 1985) making it possible for them to interact with physiological membranes, such as the gills. However, none of the compounds tested in the fatty acid category (category 5) (PA, SA, MP, MS) at either pH, resulted in a significant change in TEP (Figure 5.2C, D, E, F). Therefore, we do not consider fatty acids an important component of natural DOCs in eliciting physiological responses. The 6th category tested was amino acids and amino acid-rich molecules. Amino acids comprise ~3% of DOC in natural waters (Thurman 1985) and constittute a critical proton accepting (basic) group. Of the two aromatic amino acids tested, only Tryp at pH 7 resulted in a significant increase in TEP (Figure 5.3A). Free amino acids are very small and lack peptide bonds which are abundant in autochthonous DOCs, so a large tryptophan-rich molecule (LAC) and a large tyrosine rich molecule (BSA) were tested. LAC showed an increase in TEP at pH 4 (Figure 5.3C). Similar to the TEP response that has been observed with autochthonous DOCs (Morris et al. 2024c, see Chapter 4), BSA increased TEP at pH 7 and decreased TEP at pH 4 (Figure 5.3D). We conclude that BSA is an important model compound and may be used to assess the role of peptides in TEP responses in natural DOCs. 144 Sugars (category 7) are an important portion of DOCs (Thurman 1985) and although the tested compounds: glucose (Glu), galactose (Galac), mannose (Mann) and fructose share the same chemical formula, they are structurally and stereo-chemically different. Contradicting our prediction that due to the similarity between the compounds they would result in the same TEP response, only Mann and Fruc had a significant effect (decrease) on TEP and only at pH 4 (Figure 5.3G, H). It appears that, at low pH the specific structure of a sugar (rather than just the chemical formula) may be an important factor in its ability to affect TEP. Based on this we cannot classify sugars as being key contributors to TEP responses in natural DOCs, but this is an interesting area for future exploration considering the role of the chemical conformation (i.e. spatial arrangement of the molecule) rather than just formula. Overall, we have indicated three important model compounds, TA, SDS and BSA, that both represent key characteristics and elicit TEP responses that coincide with natural DOCs, further discussed below. 5.5.3 Are the chemical indices (based on titration properties) related to TEP responses? Based on the results from our recent studies (Morris et al. 2024b, see Chapter 3, 2024c, see Chapter 4), we have identified three physicochemical indices of natural DOCs as predictors of changes in TEP across pHs in rainbow trout: SAC340, log Kow, and PBI, as reflected in molecular charge. As mentioned in the Introduction, the pH-dependent changes in these indices likely indicate structural changes in the DOC which are mirrored in the TEP responses. In the present study, SAC340 values could not be used as valid characterization indices across all compounds as many of the model compounds produced negative absorbance signals (Appendix C Table SC 2). However, the pH-corrected log Kow and charge values appear to be quite 145 valuable. There was a positive correlation between TEP and log Kow at pH 4. This relationship was present when either absolute TEP (Figure 5.4B) or ΔTEP values (Figure 5.5B) were plotted and if the model compounds were plotted individually or in their respective key chemical moiety categories (Appendix C Figure SC 1 Figure SC 2) suggesting that this relationship is strong and important. This conclusion, that lower log Kow values (less lipophilic) are predictive of a more negative (i.e. more protective) TEP was also reported for natural DOCs at pH 7 with both absolute and ΔTEP (Morris et al. 2024c, see Chapter 4). However, with natural DOCs at pH 4, the relationship was significantly negative with absolute TEP only. In general DOCs may more readily interact with the cell membranes of the gills when lipophilicity is greater (at pH 4 compared to pH 7) which likely remains true with model compounds. Individual molecules with higher lipophilicity appear to be less beneficial (i.e. higher TEP) to ionoregulation at pH 7 for natural DOCs and at pH 4 for model compounds. The fact that these correlations (although directionally aligned) occur at different pHs, highlights that there are chemical and functional differences between the natural DOCs and the model compounds. Nevertheless, log Kow appears to be an appropriate predictor of TEP across natural DOCs and the tested model compounds, with the caveat that pH must be considered. Our results show a strong negative correlation between both absolute and ΔTEP and charge (Figure 5.4D, Figure 5.5D) at pH 4, such that as charge increases, TEP decreases. This same trend was reported for natural DOCs, although, again at pH 7 rather than pH 4 (Morris et al. 2024c, see Chapter 4). Charge represents the ionizable fraction of the molecule. At low pH, negatively charged sites on the DOC molecules and the gills would likely be protonated. The resulting ligand is more hydrophobic and lipophilic and could likely more readily interact with 146 the gill. With careful attention to pH, molecular charge may be an appropriate predictor of TEP for both natural DOCs and model compounds. Indeed, log Kow has been previously reported to be very strongly correlated to charge at pH 4 (Morris et al. 2024b, see Chapter 3) and both indices are correlated to TEP with natural DOC and DOC analogues (model compounds). 5.5.4 Comparison of TEP responses to model compounds and natural DOCS and their shared chemical characteristics The physiological effects in response to natural DOCs depends on the physicochemical characteristics of the DOC (Al-Reasi et al. 2011, 2013a; Sadauskas‐Henrique et al. 2019). DOC type and pH of the environment are particularly important (Wood et al. 2011; Morris et al. 2021, see Chapter 2). In our previous study (Morris et al. 2024c, see Chapter 4) we demonstrated that DOCs that share similar physicochemical characteristics also show similar TEP response trends. Out of the five natural DOCs tested there was a clear divide between two groups of DOCs in characteristics and in TEP responses. Allochthonous DOCs with higher aromaticity, molecular weight, charge and relative % humic acid and lower lipophilicity, decreased TEP at both pH 7 and pH 4 (Morris et al. 2024c, see Chapter 4). In contrast autochthonous DOCs with lower aromaticity, lower molecular weight, lower charge and a higher lipophilicity and higher relative % protein increased TEP at pH 7 but decreased TEP at pH 4. Some model compounds from the present study showed similar TEP responses to natural DOCs, as discussed above, which were likewise pH-dependent, possibly because they share key chemical moieties. TA was the only model compound to result in a more negative TEP at pH 7 (Figure 5.1A), a common response to natural allochthonous DOCs. This TEP response is likely, in part, due to the aromaticity and phenolic groups common to both allochthonous DOCs and TA. Natural allochthonous DOCs 147 result in a negative TEP at pH 4 as well as pH 7. We see this TEP response in both the surfactants tested, therefore it is possible that the surfactant property and long aliphatic chains play an important role in the protective effect (i.e. lower TEP) provided by allochthonous DOCs. The decrease in pH from 7 to 4 results in molecular and/or structural changes in DOC molecules as reflected in the properties of aromaticity, lipophilicity and charge (Morris et al. 2024b, see Chapter 3). A change in pH likely changes the conformation (e.g. condensation or expansion) of the DOC and in turn the function (Morris et al. 2024b, see Chapter 3). It can also alter the molecular orbital or excitable electrons and reduces the ionization (Laane 1980; Patel-Sorrentino et al. 2002). The pH-dependent changes in DOC, may be responsible for the directional shift in TEP response (i.e. positive TEP at pH 7, negative TEP at pH 4) observed with autochthonous DOCs. Autochthonous DOCs are often more enriched in amino acids and peptides (Thurman 1985; Morris et al. 2024b, see Chapter 3). It is possible that this TEP response is in part related to the amino acid and peptide content as this same TEP trend was observed in the tyrosine, peptide-rich molecule BSA. 5.6 Concluding remarks A mechanistic understanding of the key chemical moieties of DOC affecting ionoregulation in fish is crucial for monitoring aquatic health. However, this mechanistic understanding is challenging due to the complexity and heterogeneity of DOCs. Our results demonstrate that some model compounds and chemical characterization indices may be used as predictors of TEP, indicating osmoregulatory status. Specifically, phenolic groups and long aliphatic chains may be contributing to the TEP response in natural allochthonous DOCs making TA and SDS appropriate model compounds for this type of DOC. Amino acids and peptides may 148 contribute to the effect of autochthonous DOCs on TEP, for which BSA is a useful model compound. Log Kow and charge may be used as predictors of TEP response, with careful consideration of pH. Future studies could determine the effects of these model compounds in parallel with natural DOCs on different physiological endpoints (e.g. ion fluxes, water movement through paracellular and transcellular pathways and nitrogenous waste excretion rates) while considering water quality parameters such as pH, ion concentrations and potential pollutants. Integration of the physiological effects and physicochemical parameters of model compounds coinciding with natural DOCs could be used for future monitoring of freshwater ecosystems and determining the water quality impacts on fish health. 149 5.7 Chapter 5 – Figures 150 Figure 5.1. Absolute TEP at pH 7 and pH 4 of model compounds in the key chemical moiety groups: Tannic and humic acid (A) Tannic acid (TA), (B) AldrichTM humic acid (AHA), Phenolic acids (C) Salicylic acid (SA), (D) Naphthionic acid (NA) and Surfactants (E) Sodium dodecyl sulfate, (F) Linear alkylbenzene sulfonate (LAS). Values are mean ± SEM, N=6-8. Asterisks indicate statistically significant differences (p< 0.05 by Student’s paired t-test). 151 Figure 5.2. Absolute TEP at pH 7 and pH 4 of model compounds in the key chemical moiety groups: Carboxylic acids (A) Formic acid (FA), (B) Acetic acid and Fatty acids (C) Palmitic acid (PA), (D) Steric acid (StA), (E) Methyl palmitate, (F) Methyl stearate (MS). Values are mean ± SEM, N=6-8. Asterisks indicate statistically significant differences (p< 0.05 by Student’s paired t-test). 152 Figure 5.3. Absolute TEP at pH 7 and pH 4 of model compounds in the key chemical moiety groups: Amino acids (A) Tryptophan (Tryp), Tyrosine (Tyr), -Lactalbumin (LAC) and Bovine serum albumin (BSA). Values are mean ± SEM, N=6-8. Asterisks indicate statistically significant differences (p< 0.05 by Student’s paired t-test). 153 Figure 5.4. Absolute TEP of model compounds regressed against (A) log Kow at pH 7 (B) log Kow at pH 4 (C) Charge at pH 7 (D) Charge at pH 4. Values are mean ± SEM, N= 6-8. A fitted line indicates statistical significance (p < 0.05 by simple linear regression). 154 Figure 5.5. ΔTEP of model compounds regressed against (A) log Kow at pH 7 (B) log Kow at pH 4 (C) Charge at pH 7 (D) Charge at pH 4. Values are mean ± SEM, N=6.8. A fitted line indicates statistical significance (p < 0.05 by simple linear regression). 155 Chapter 6: Interactions of major ions, pH and dissolved organic carbon (DOC) on transepithelial potential (TEP) in rainbow trout: are there implications for prediction of salt toxicity? 6.1 Summary Freshwater salinization is increasing globally through seawater intrusion, road de-icing, and changes in anthropogenic land uses. Concurrently, freshwaters are browning with the rise in dissolved organic carbon (DOC) concentrations, while water pH is falling. Elevations in external major ion concentrations (Na+ or Ca2+) and low pH, independently, disturb osmoregulatory homeostasis in freshwater organisms. Several studies have demonstrated that DOC often mitigates osmoregulatory stress responses to acidic pH. However, the interactive effects of these three water quality parameters together have been relatively understudied. Transepithelial potential (TEP), the electrical gradient across the gills between the animal and the external water, can be used as an index of osmoregulatory stress. We investigated whether DOC and exposure to elevated major ions interact with TEP responses at circumneutral and low environmental pH in the freshwater rainbow trout. Two natural DOCs, one allochthonous and the other autochthonous, were used. To aid interpretation, three model compounds of known chemical structure were also employed (tannic acid, sodium dodecyl sulfate, bovine serum albumin), based on the criteria that they structurally resemble or functionally behave like certain chemical moieties of humic or fulvic acids, major components of DOC. The Multi-Ion Toxicity Model predicts that a disturbance in absolute TEP is indicative of salt toxicity; however, recent studies have shown that ΔTEP (the change in TEP relative to the baseline) may be more predictive. Our data followed a pattern that could be described by the Michaelis–Menten equation. Therefore, 156 considering Michaelis–Menten constants (Km and ΔTEPmax), absolute TEP and ΔTEP, we used a weight of evidence approach to predict how DOC and pH will influence Na+ or Ca2+ toxicity. We conclude that key chemical moieties of DOC will likely play pH-dependent roles in both Na+ and Ca2+ toxicity. 6.2 Introduction Freshwater salinization, the increase in major salt ions, including Na+, Ca2+ and Cl-, into freshwater environments is caused by seawater intrusion, accelerated by climate change (Chun et al. 2018; Baena-Ruiz et al. 2020) and anthropogenic activities such as road de-icing (Findlay and Kelly 2011) and changes in land usage (Boetler, et al. 1992; Smedema and Shiati 2002; Pond et al. 2008; Blewett et al. 2017). It is now one of the most detrimental stressors on freshwater ecosystems (Goodfellow et al. 2000; Findlay and Kelly 2011; Cañedo-Argüelles et al. 2013; Herbert et al. 2015; Cañedo-Argüelles 2020). The primary concern for freshwater animals is the disturbance to hydromineral homeostasis caused by increased major ions (Mount et al. 2016), resulting in osmoregulatory stress. Rising concentrations of dissolved organic carbon (DOC), a natural component of freshwater, is contributing to the browning of freshwater systems (Morris et al. 2021, see Chapter 2; Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025). While water pH is declining, both over short timescales following sudden inputs of DOC-rich water and over extended periods driven by climate change (Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; Quijada-Rodriguez et al. 2021). DOCs are composed of diverse molecules, primarily humic 157 substances (humic and fulvic acids) and various non-humic substances including amino acids, fatty acids, phenols, natural sugars, and hydrocarbons (Thurman 1985; Boggs et al. 1985; Gaffney et al. 1996), with a composition (i.e. chemical makeup of the molecule) that varies spatially and temporally. Aquatic organisms are very sensitive to changes in DOC concentration and composition as they regulate both biotic and abiotic processes within the ecosystem (Petersen 1991; Kullberg et al. 1993; Steinberg et al. 2006; Sucker and Krause 2010; Al-Reasi et al. 2011; Wood et al. 2011; Johannsson et al. 2017, 2020; Holland et al. 2018). DOCs reduce the osmoregulatory disturbance caused by low environmental pH through protection of active ion uptake and mitigation of the often-fatal increased passive loss of major salt ions (Na+, Cl-) across the gills, particularly in fish (Gonzalez et al. 2002, 2005; Wood et al. 2002, 2003, 2011; Matsuo et al. 2004; Glover et al. 2005; Glover and Wood 2005; Al-Reasi et al. 2016; Duarte et al. 2016, 2018) Recent studies have demonstrated that acute exposure to single-salt or salt mixtures has detrimental, often additive, effects on many freshwater organisms (Mount et al. 2016; Erickson et al. 2017). Background water chemistry (e.g. hardness, alkalinity, and ionic composition) has been shown to play a significant role in major ion toxicity (Mount et al. 1997, 2016) and in the physiological responses preceding toxicity (Wood et al. 2020; Morris et al. 2020; Po and Wood 2021, 2022). Although conductivity, osmolarity, total dissolved solids (TDS), salinity, and the concentrations of particular cations and anions have been proposed as regulatory endpoints (USEPA 2011; Cormier and Suter 2013; EPRI 2018), currently, there is no general agreement on criteria used for regulation of major ion pollution (Schuler et al. 2019). There is also no framework that considers the toxicity modifying effects of other water quality parameters such as DOC and water pH. 158 A potential approach for prediction of major ion toxicity is the Multi-Ion Toxicity Model (MIT) created by the Electric Power Research Institute (EPRI 2018). The MIT model is based on the knowledge that major ions disturb electrical gradients across biological membranes differentially and on the assumption that this disturbance in the transepithelial potential (TEP) at the gills of freshwater animals affects ionoregulation and ultimately leads to toxicity and death (EPRI 2018). Recent physiological studies have generally supported the validity of this model (Wood et al. 2020; Morris et al. 2020; Po and Wood 2021, 2022). The TEP in freshwater fish is usually negative (blood plasma relative to the external water) and is almost entirely a diffusion potential between the blood plasma and the external water, due to the higher permeability of Na+ (the major plasma cation) relative to Cl- (the major plasma anion) across the gills (Potts 1984; Wood et al. 1998). Increased ambient concentrations of Na+ or Ca2+, or low environmental pH, change this differential permeability of Na+ versus Cl- and increase the diffusion gradient for cation (e.g. Na+ or Ca2+or H+) entry. The resulting less negative TEP favors Na+ efflux and opposes Na+ influx (McWilliams and Potts 1978; Wood et al. 1998, 2020). In freshwater fish, natural DOCs have been found to result in a more negative TEP (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019). The resulting electrochemical gradient favors net Na+ uptake at the gills, which is one way that DOC supports ionoregulatory function (Wood et al. 2011; Morris et al. 2021, see Chapter 2). Although the individual effects of increased major ions, DOC, and low pH on TEP have been described, the interactive effects of these three water quality parameters on TEP are not yet well understood. At present, the MIT framework does not incorporate the influence of DOC in any way. The present study is an attempt to do so. While the MIT model (EPRI 2018) was based on absolute TEP, recent studies have shown that the change in TEP relative to the baseline (i.e. the ΔTEP) in response to acute 159 exposure to increasing salt concentration may be more relevant in the prediction of toxicity (Wood et al. 2020; Po and Wood 2021, 2022). These studies showed that the curve of ΔTEP versus salt concentration can be fitted with a Michaelis-Menten equation. The latter is often used to describe relationships between substrate concentration and velocity for enzyme or transport kinetics. In these studies, the equation was used to describe the relationship between salt concentration and ΔTEP, yielding ΔTEPmax and Km values. ΔTEPmax is the maximum change in TEP relative to the baseline, while Km indicates the salt concentration causing 50% of the ΔTEPmax. Although the LC50 values of the individual salts tested were highly variable, the acute ΔTEP response at each LC50 was extremely uniform. This demonstrated that the ΔTEP was strongly predictive of the LC50 across multiple salts (Wood et al. 2020; Po and Wood 2021, 2022). There were also strong relationships between the Michaelis-Menten Km values for different salts and the LC50 values (Wood et al. 2020; Po and Wood 2021, 2022), such that a lower Km value reflected higher toxicity. These patterns were demonstrated across multiple salts and species of fish. At present we do not know whether an increased TEP value (i.e. absolute TEP at the LC50, ΔTEP at the LC50, or ΔTEPmax) or a reduced Km values, effects which can occur either separately or concurrently, are the more important indicators of greater toxicity, which is why all were studied as possible metrics of toxicity in the present study. In the present study, we assessed the effects of two natural DOCs and three DOC model compounds at nine increasing concentrations of NaCl or CaCl2 at pH 7 or pH 4 on TEP in rainbow trout. We chose pH 4 as the acidic pH treatment because we wanted a marked separation (3 orders of magnitude higher H+ concentration than at pH 7) so as to affect both the protonation of the gill and the protonation of the DOC molecules This acidic pH 4 was used in both our previous chemical characterization study on natural DOCs (Morris et al. 2024b, see 160 Chapter 3) and in our previous physiological study of the effects of natural DOCs on TEP in trout (Morris et al. 2024c, see Chapter 4). This pH is environmentally relevant to naturally acidic, DOC-rich peat bogs and blackwater rivers, and to acidified DOC-rich lakes in North America and northern Europe polluted by acid rain and acid mine drainage (Wood 2022). Any or all of these may be additionally threatened by salinization (Goodfellow et al. 2000; Herbert et al. 2015; Cañedo-Argüelles et al. 2016; Schuler et al. 2019). The two natural sources of DOCs were freshly collected from two very different sites in Ontario, Canada (Luther Marsh and Lake Ontario), and span large differences in physicochemical characteristics which were reported by (Morris et al. 2024b, see Chapter 3). Luther Marsh (LM) DOC is allochthonous, optically dark, and highly aromatic, while Lake Ontario (LO) DOC is autochthonous, optically light, and much less aromatic. The complexity and diversity of DOCs make mechanistic interpretation difficult; therefore, based on the studies of Chapter 5, three model compounds were selected to help diagnose important chemical structures or functional behaviors of key chemical moieties of natural DOCs contributing to their effects on TEP. Tannic acid (TA) is highly aromatic with polyphenolic groups and has often been used as a model allochthonous DOC (Moreno-Castilla et al. 2004; Lin and Baoshan 2008; Campinas et al. 2013). Sodium dodecyl sulfate (SDS) is a common anionic surfactant and shares amphiphilic properties of DOCs with hydrophilic and hydrophobic moieties (von Wandruszka 2000). Bovine serum albumin (BSA) is a tyrosine-rich proteinaceous material (Heidari et al. 2018) that was used because many DOCs are rich in amino acids such as tyrosine, particularly autochthonous DOCs (Thurman 1985). Overall, our hypotheses were: (i) The interactive effect of increased Na+ or Ca2+ and DOCs would be pH-dependent; (ii) some model DOC compounds would have a similar interactive effect with the salts as the natural DOCs; (iii) based on the MIT model or the 161 Michaelis-Menten model, some DOCs would be protective (i.e. making TEP more negative), and others would exacerbate the harmful effects of Na+ or Ca2+ (i.e. making TEP less negative), and these responses would be pH-sensitive. 6.3 Methods 6.3.1 Experimental animals Juvenile rainbow trout (Oncorhynchus mykiss) (N=62, 125 ± 5 g) were obtained from the Freshwater Fisheries Society of BC (Abbotsford, BC, Canada) and transferred to the University of British Columbia (UBC). Prior to the start of experiments fish were held at 12 ºC in flowing dechlorinated Vancouver tap water (Na+ =0.09, Cl- =0.10, Ca2+ =0.10, Mg2+ =0.011, K+ =0.004 mmol L-1, hardness as CaCO3=3.3 mg L -1, pH=7, [DOC] = ~1.07 mg C L-1) for several months. Every second day, fish were fed a 2% of body mass ration with commercial pellet food (BioTrout 2.0 mm, Bio-OregonTM, Longview, WA, USA) and were fasted for at least 72 h prior to experiments. Experiments were approved by the UBC Animal Care Committee (A18-0271 and A22-0195) and conformed to national regulations of the Canada Council for Animal Care. 6.3.2 Experimental solutions Nine concentrations of NaCl or CaCl2 based on a geometric series as a percentage of the previously published 96-h median lethal concentration (LC50) value for rainbow trout (Durand-Hoffman 1995) were tested (Appendix D Table SD 1) (e.g. 3.12 %, 6.25 %, 12.5 %, 25 %, 50 %, 100 %, 200 %, and 400 % of the LC50 value). Analytical grade NaCl or CaCl2 salt powders (Sigma- Aldrich, Saint Louis, MO, USA) were freshly dissolved as concentrated stock solutions 162 in dechlorinated Vancouver tap water. The two geometric series was prepared by volumetrically diluting into dechlorinated Vancouver tap water and the conductivities of the solutions were measured with a WTW portable conductivity meter (ProfiLine Cond3310 (Xylem Analytics, Welheim, Germany) as in Po and Wood (2021) (Appendix D Table SD 1). Conductivity did not differ with the addition of DOC. The pH was adjusted to approximately pH 7 or pH 4 using HNO3 or NaOH and a sympHonyTM pH electrode (C03243) and meter (SP70P) (VWR International, Radnor, PA, USA). Solutions were prepared and adjusted to the desired pH at least 12 hours prior to the experiment to ensure equilibration. The pH was rechecked immediately before the experiment to verify that it remained at the target value. The various series were tested in the presence and absence of 5 sources of dissolved organic carbon (DOC). These comprised two natural sources, Luther Marsh (LM) and Lake Ontario (LO), and three model compounds, tannic acid (TA), sodium dodecyl sulfate (SDS) and bovine serum albumin (BSA). Thus, for each salt, there were 12 experimental series: [no added DOC at pH 7; no added DOC at pH 4; 5 different types of added DOC at pH 7 and 5 different types of added DOC at pH 4]. This totaled 5 series with DOC at pH 7, 5 series with DOC at pH 4 and one series at each pH without added DOC. The two natural sources of DOC were collected in Ontario, Canada, LM at 43°57′42.8N, 80°24′04.0W, and LO at 44°14'25.3"N 76°27'57.5"W. As described by Morris et al. (2024b, see Chapter 3), water was pumped from the source and pre-filtered through a 1-m wound string filter and gradually concentrated (Sun et al. 1995) by a portable reverse osmosis unit fitted with a polyamide thin-film composite membrane (FilmTecTM BW30-4040, DuPont Water Solutions, Edina, MN, USA). The concentrate was treated with a cation exchange resin (Amberlite IR-118 (H), Sigma Aldrich, St. Louis, MO, USA) to remove the accumulated cations from the reverse- 163 osmosis process. The concentrate was filtered using 0.45-m pore size (47 mm), hydrophilic, polyethersulfone polymer membrane filters (MS® PES Membrane Solutions, Auburn, WA, USA), and stored in sealed bottles at 4ºC until used. Detailed physicochemical characterization of DOCs was done in a previous study (Morris et al. 2024b, see Chapter 3). Model DOC compound powders (Sigma-Aldrich, St. Louis, MO, USA) were dissolved in dechlorinated Vancouver tap water (see above for water chemistry) to yield concentrated stock solutions. For both natural DOCs and model DOC compounds, experimental solutions were prepared for physiological testing by adding the concentrated stock solutions to the geometric series solutions so as to nominally equal 10 mg C L-1. DOC concentrations of exposure waters were verified using a Shimadzu total carbon and nitrogen analyzer (TOC-L Shimadzu, Mandel Scientific, Guelph, ON, CA) (Appendix D Table SD 2) 6.3.3 Transepithelial potential measurements Transepithelial potential measurements (TEP) were made following the procedure outlined by Wood et al. (2020). Intraperitoneal catheters yield identical data to those generated using more invasive vascular catheters employed in earlier studies (Wood and Grosell 2008), therefore, intraperitoneal catheters were used in the present study. Trout were anesthetized using 0.2 mg L-1 of tricaine methane sulfate (MS222) (Sigma-Aldrich), adjusted to neutral pH using NaOH . To avoid hypoxic stress, the gills were constantly irrigated with a continuous flow of anaesthetic (Po and Wood 2021). As described by Wood and Grosell (2008), a 5-cm section of polyethylene PE50 catheter (Clay Adams™, Becton Dickinson, Franklin Lakes, NJ, USA) filled with Cortland saline (Wolf 1963), was inserted into the peritoneal cavity. The catheter was anchored using a 2-cm PE160 sleeve secured with cyanoacrylate glue and silk sutures and sealed 164 with a stainless-steel pin. Before control TEP measurements were made, fish recovered overnight in separate aerated enclosures supplied with dechlorinated Vancouver tap water (no added salt or DOC). TEP measurements were made using 3 M KCl agar bridges connected to a high impedance voltmeter (Radiometer pHm 82, Radiometer-Copenhagen, Copenhagen, Denmark) through Ag/AgCl electrodes (World Precision Instruments, Sarasota, FL, USA). The measurement bridge was connected to the indwelling catheter and the reference bridge was placed into the experimental solution of the measurement vessel. Each individual fish was exposed to the experimental solution (e.g. 3.12 %, 6.25 %, 12.5 %, 25 %, 50 %, 100 %, 200 %, and 400 % of the LC50 value of either NaCl or CaCl2, with or without DOC) at the appropriate pH for 2 min before the measurements commenced and then three measurements (with correction for junction potential) were completed within a further 2 min, and averaged. The background TEP was similarly measured in the control solution (0 % added NaCl or CaCl2, with or without DOC) at pH 7 or pH 4 in each animal. For each solution series testing added DOC, an appropriate control series was performed. Each respective control series and added DOC series at 0% added salt served as a baseline TEP for comparison with the TEP measured in the experimental solutions. It was this baseline for each series that was then used for the ΔTEP calculations: ΔTEP = experimental TEP – baseline TEP (Equation 6.1) A paired statistical design was used, where each fish was its own control, meaning the baseline TEP and experimental TEP were measured in the same individual fish. TEP was expressed in the traditional manner as the inside voltage relative to the outside water as 0 mV. Directly following the experiments, fish were euthanized by an overdose of neutralized MS222 at 0.5 mg L-1. 165 6.3.4 Speciation modeling Complexation of major cations (Na+, Ca2+, Mg2+ and K+) with natural dissolved organic matter (DOM) was modelled (Appendix D Table SD 6) with the Windermere Humic Aqueous Model (WHAM, version VII) (Lofts and Tipping 2011) using test water physicochemical parameters (measured temperature, pH, DOC concentration and major cation concentrations and nominal alkalinity, and major anion concentrations). We made the most often used assumptions that the DOM:DOC ratio was 2 (Buffle 1988) and that 65% of the DOM was active in the complexation of metals (Bryan et al. 2002). For the experimental waters supplemented with DOM isolated from Luther Marsh (LM) or Lake Ontario (LO), we used the %humic acid-like and %fulvic acid-like values obtained from the PARAFAC analyses to calculate the final input humic acid (HA) and fulvic acid (FA) concentrations in WHAM (input FA concentration = %FA x 65% x 2 x DOC; input HA concentration = %HA x 65% x 2 x DOC). For waters with only background DOM (originating from Lake Capilano, the Vancouver city reservoir) for which no PARAFAC analysis was conducted, we made the DOM quality assumptions recommended by Bryan et al. (2002): DOM was represented entirely by (65% active) FA (input FA concentration= 65% x 2 x DOC; input HA concentration = 0). In order to mitigate any “drift” associated with time between experiments, different treatments were mixed within a run of experiments and at each time an experiment was run, a corresponding control was performed at the same time. 166 6.3.5 Statistical analyses The effect of each DOC source on absolute TEP at each of the tested salt concentrations, compared to the same concentration of that salt without DOC, within the same pH, was assessed using Student’s paired t-test. The effect of DOC with 0% added salt on TEP compared to control was assessed using Student’s paired t-test and differences among sources was compared using one-way analysis of variance (ANOVA) with Tukey’s post hoc test for multiple comparisons. Non-linear regressions were fitted to the ΔTEP versus salt concentration curves using the Michaelis-Menten (M-M) equation, often employed to describe enzyme or transport kinetics. Two versions of the M-M equation were used in the present study that were previously used to fit ΔTEP relationships to salt series (Wood et al. 2020; Po and Wood 2021, 2022). Equation 6.2 is the standard M-M equation used to fit all NaCl data in the current study: ΔTEP =𝛥𝑇𝐸𝑃𝑚𝑎𝑥 × [𝑆𝑎𝑙𝑡]o 𝐾𝑚 + [𝑆𝑎𝑙𝑡]o (Equation 6.2) Equation 6.3 is a modified M-M that considers substrate inhibition fitted with the analytical method described by Huitema and Horsman (2018). This was used in the present study to fit all CaCl2 data based on higher R2 values than for the standard M-M equation (see Results): ΔTEP =𝛥𝑇𝐸𝑃𝑚𝑎𝑥 × [𝑆𝑎𝑙𝑡]o 𝐾𝑚 × (1 + [𝑆𝑎𝑙𝑡]oKs) (Equation 6.3) 167 Where: ΔTEP = change in TEP (mV) relative to baseline TEP in background water ΔTEPmax = maximum change in TEP (mV) relative to baseline TEP [Salt]o = external salt concentration (mmol L-1) Km = affinity constant representing [Salt]o associated with 50% of ΔTEPmax (mmol L-1) Ks = constant (mmol L-1) accounting for the inhibition of the substrate. The CaCl2 data were also analyzed with the standard M-M equation for comparison of R2 values, however the R2 values were much lower (Appendix D Table SD 3) compared to the M-M equation with the substrate inhibition modification (Table 6.2). Therefore, we selected the M-M equation with the substrate inhibition modification as the preferred model for CaCl2 responses. The differences between ΔTEPmax values, as well as between Km values with NaCl at pH 7 versus NaCl at pH 4 or CaCl2 at pH 7 versus CaCl2 at pH 4 were evaluated using Student’s unpaired t-tests whereas the differences between these values with and without added DOC at the same pH (as the same series) were evaluated using Student’s paired t-tests (Table 6.1). The differences between the absolute TEP and the ΔTEP value at the LC50 with and without DOC were assessed using Student’s paired t-tests. All statistical analyses and data plots were done using GraphPadTM Prism 7 (GraphPad Software, San Diego, CA, USA). A significance level of p < 0.05 (two-tailed) was used throughout. 168 6.4 Results 6.4.1 The effect of pH and DOC with no added salt on TEP In response to the acute transfer from control water at pH 7 (TEP = -22.4 ± 0.7 mV, N=62) to control water at pH 4 (TEP = -18.8 ± 0.9 mV, N=53), TEP became significantly more positive (p=0.0013). Thus, the baseline was shifted. Each of the DOCs further influenced the baseline TEPs, although in a different manner and magnitude, which was pH-dependent. At pH 7, LM, TA and SDS caused a significant decrease in TEP whereas LO and BSA caused significant depolarization of TEP from their respective control values (Figure 6.1A). The baseline shifts caused by LM, TA and SDS were not significantly different from one another but were significantly different from those of LO and BSA (Figure 6.1A). At pH 4, the TEP in the presence of LM and SDS remained significantly more negative compared to the control values at pH 4 while TA had no significant effect (Figure 6.1B). LO and BSA also resulted in more negative TEPs (Figure 6.1B), in contrast to their opposite effects at pH 7 (Figure 6.1B). The only significant differences amongst these baseline shifts at pH 4 were between TA and SDS (Figure 6.1B). 6.4.2 The effects of NaCl and CaCl2 on absolute TEP and ΔTEP at pH 7 and pH 4 Increases in either NaCl or CaCl2 concentrations resulted in increases in the absolute TEP values (Figure 6.2A). The relationships between the absolute TEP response and the geometric concentration series were hyperbolic with the start of the plateau coinciding with the LC50 value, indicated by the dotted line, of the respective salt (Figure 6.2). Although pH had an effect on the baseline control value of TEP, the relationship between the salt concentration and the absolute TEP response was not greatly altered with the change from pH 7 to pH 4 when looking at 169 absolute TEP plots (Figure 6.2A, C). However, this upward shift in the baseline control value of TEP from pH 7 to pH 4 was reflected in the ΔTEP curves for both NaCl and CaCl2 (Figure 6.2B). This shift resulted in the ΔTEP values being lower at pH 4 compared to pH 7 for both salts. For NaCl, the M-M equation (Equation 6.2) was fitted to the pH 7 and pH 4 ΔTEP curves (Figure 6.2B) and the resulting ΔTEPmax and the Km values differed significantly between pHs (Table 6.1). Specifically, in the absence of added DOC, the ΔTEPmax value was reduced by low pH, whereas the Km value was increased by low pH. Thus, the M-M relationship was shifted downward and to the right (Figure 6.2B). For CaCl2, the M-M equation modified for substrate inhibition (Equation 6.3) was fitted to the ΔTEP curves (Figure 6.2D). The M-M modification for substrate inhibition model was used because the higher R2 values indicated that this model was a better fit compared to the M-M model without the modification (Appendix D Table SD 3). For example, the overall R2 value for CaCl2 at pH 7 with the M-M modification was R2 = 0.9 (Table 6.2) compared to R2 = 0.7 (Appendix D Table SD 3) for the standard M-M model; this was also the case at pH 4 (R2 = 0.8 versus R2 = 0.5). This trend was seen in almost every single-exposure solution. Therefore, we have selected the M-M equation with the substrate inhibition modification as the preferred model. As seen with NaCl, in the absence of added DOC, low pH significantly reduced the ΔTEPmax value and elevated the Km value (Table 6.2). Thus, the curve was again shifted downward and to the right. Notably, the ΔTEPmax values were very similar for NaCl and CaCl2, but the Km values were substantially lower for CaCl2 (Table 6.2 versus Table 6.1). 170 6.4.3 The effects of NaCl in the presence and absence of added DOC on absolute TEP and ΔTEP at pH 7 and pH 4 As described above, DOCs and model compounds influenced the baseline TEP (Figure 6.1). This was reflected in the starting position of the hyperbolic curve, for example LM DOC decreased TEP at pH 7 in 0 mM NaCl (Figure 6.3A), which resulted in a lower starting position of the curve. Although the baseline position was often shifted in response to a natural DOC or model compound, the trajectory of the curve for the salt with the added DOC/model compound remained the same and often superimposed on the curve representing the salt alone. To quantify this, we evaluated differences between the absolute TEP responses and between the ΔTEP with and without (control) added DOC at each of the test concentrations. Significant differences are indicated by asterisks above the symbol representing the salt concentration with the added DOC on the graph. Exact p-values for each concentration are provided in Appendix D, Table SD 4 The shift in baseline TEP with the addition of each DOC or model compound was reflected in the ΔTEP curves (Figure 6.3). Each curve was fitted with the M-M equation (Equation 6.1) and evaluated for significant differences in the ΔTEPmax and the Km values between the presence versus absence of added DOC/model compound. At pH 7, the addition of LM (Figure 6.3B) resulted in a significant increase in the ΔTEPmax value only (Table 6.1) and LO DOC (Figure 6.3D) resulted in a significant increase in the Km value only (Table 6.1). At pH 7, the addition of TA (Figure 6.3F) resulted in no significant changes in either the ΔTEPmax or Km values (Table 6.1). At this same pH, SDS (Figure 6.3H) caused a significant increase in the ΔTEPmax only, a similar effect to that of LM (Table 6.1). In contrast, BSA at pH 7 (Figure 6.3J) resulted in a significant decrease in the ΔTEPmax value only (Table 6.1). 171 As discussed above, the baseline shifts in TEP in both control solutions and with added DOC were pH-dependent (Figure 6.1). The absolute TEP plots for NaCl at pH 4 (Figure 6.4A, C, E, G, I) appeared similar to those at pH 7 (Figure 6.3 A,C, E, G, I), with and without DOC. However, the baseline shifts were apparent in the ΔTEP curves, and there were generally fewer effects on M-M parameters at pH 4 relative to those at pH 7. At pH 4, the addition of LM (Figure 6.4B) did not cause a significant increase in ΔTEPmax (p= 0.05) in contrast to the significant response at pH 7, and there was again no effect on Km (Table 6.1). The response to LO at pH 4 (Figure 6.4D), a significant decrease in the Km value, was opposite to that at pH 7, although again, there was no significant effect on the ΔTEPmax value (Table 6.1). At pH 4, as at pH 7, the addition of TA (Figure 6.4F) had no effects on either the Km or ΔTEPmax values (Table 6.1). At pH 4, SDS (Figure 6.4H) had a significant stimulatory effect on ΔTEPmax, only consistent with the response seen at pH 7 (Table 6.1). However, the addition of BSA (Figure 6.4J) at pH 4 did not have an influence on ΔTEPmax or Km values in contrast to the significant decrease in ΔTEPmax seen in the former at pH 7 (Table 6.1). 6.4.4 The effects of CaCl2 in the presence and absence of added DOC on absolute TEP and ΔTEP at pH 7 and pH 4 As in the NaCl experiments, the effects on absolute TEP and ΔTEP of added DOC/model compound compared to its absence at pH 7 (Figure 6.5) and pH 4 (Figure 6.6) were evaluated at each CaCl2 concentration. Significant differences are marked by an asterisk, and exact p-values for each concentration are reported in Appendix D (Table SD 4, Table SD 5). The shifts in baseline TEP for the CaCl2 series in response to both pH and DOC were likewise reflected in the ΔTEP curves which were evaluated by the M-M equation modified for substrate inhibition (Eq. 172 3, see Methods) as this was the best fit for our data, as indicated by the higher R2 values (demonstrated above). Notably, there were fewer significant changes in M-M parameters for the ΔTEP versus CaCl2 concentration curves caused by the various DOCs and model compounds, and none of them were the same as those seen in the NaCl trials (Table 6.2 versus Table 6.1). The response patterns were entirely different. Importantly, this conclusion would have been exactly the same if we had based it on a regular Michaelis–Menten analysis (Equation 6.2) (Appendix D Table SD 3) rather than on the M-M equation modified for substrate inhibition (Equation 6.3) (Table 6.2). Thus, it was not the result of using a different analysis. At pH 7 (Figure 6.5) the only significant changes were a reduction in the ΔTEPmax value with the addition of LO DOC and decrease in the respective Km values with the addition of LM and SDS (Table 6.2). At pH 4 (Figure 6.6) the only significant differences were a reduction in ΔTEPmax caused by the addition of LM DOC and decrease in the respective Km values with the addition of LM and TA (Table 6.2). 6.4.5 The effects of DOC on absolute TEP and ΔTEP at the LC50 salt value Based on the original Multi-ion Toxicity (MIT) model of EPRI (2018), the absolute TEP would be predictive of toxicity see Introduction). At pH 7, the absolute TEP at the LC50 for NaCl was significantly increased in the presence of LO DOC and BSA (Figure 6.7A). There were no changes in the absolute TEP values at the LC50 for CaCl2 at pH 7 in response to any of the natural DOCs or model compounds (Figure 6.7B). The same was true for absolute TEP responses for NaCl at pH 4 (Figure 6.7C). However, for CaCl2 at pH 4, the absolute TEP at the CaCl2 LC50 decreased in response to LM DOC and increased in response to BSA (Figure 6.7D). 173 Based on recent studies (Wood et al. 2020; Po and Wood 2021, 2022), the ΔTEP at the LC50, rather than the absolute TEP, may be more relevant in predicting toxicity (see Section 6.2), making it a value of specific interest in this study. For the NaCl series at pH 7, ΔTEP was significantly higher at the NaCl LC50 value with LM DOC and SDS and significantly lower with DOC and BSA (Figure 6.8A). For the CaCl2 series at pH 7, there were no significant differences among ΔTEP values at the CaCl2 LC50 value with the addition of any of the DOCs (Figure 6.8B). For the NaCl series at pH 4, the ΔTEP at the NaCl LC50 value was significantly higher with SDS (Figure 6.8C) and for the CaCl2 series at pH 4, the ΔTEP value at the CaCl2 LC50 was significantly higher with BSA (Figure 6.8D). 6.4.6 Cation speciation modeling Speciations of Na+ and Ca2+ in the experimental waters, as well as two other cations of potential interest (K+, Mg2+), were modeled in the presence and absence of LM or LO DOC at pH 7 and pH 4 at both the LC50 and the Km concentrations (Appendix D Table SD 6). Overall, there was very little Na+ (< 1%) or Ca2+ (< 5%) bound to DOC, with Ca2+ binding slightly more. The only exceptions were for Ca2+ binding to LO DOC at both pH 7 and 4, where the presence of NaCl at either its Km or LC50 concentrations reduced the relative concentrations of free Ca2+ by 11–15%. Considering all the experimental solutions, apart from these two exceptions, > 95% Ca2+ was free, and > 99.0% of Na+ was free (Appendix D Table SD 6). In all circumstances, > 99% of K+ and > 89% of Mg2+ remained free. 174 6.5 Discussion 6.5.1 Overview Independently, pH, NaCl or CaCl2, and DOCs/model compounds resulted in changes in absolute TEP relative to the control. The relationship between the salt concentration of NaCl or CaCl2 and absolute TEP was not greatly altered with the change in pH from 7 to 4 (Figure 6.2A, C). However, the change in baseline TEP was reflected in the ΔTEP curves (Figure 6.2B, D). The ΔTEPmax and the Km values also differed significantly between pHs (Table 6.1, Table 6.2). In general, the Km values were much lower for CaCl2 compared to NaCl. With respect to our original hypotheses, (i) the interactive effects between increased Na+ or Ca2+ and DOCs were indeed pH-dependent. In some cases, the directional response of ΔTEP at the LC50 compared to the control, changed at pH 4 with respect to pH 7. For example, at pH 7 at the LC50 of both NaCl and CaCl2, the addition of LO decreased ΔTEP, whereas at pH 4 LO increased ΔTEP (Figure 6.8). (ii) We confirmed that some model compounds would have a similar interactive effect with the salts as the natural DOCs. For example, at the LC50 of NaCl at pH 7, TA and SDS had a similar response of increased ΔTEP as LM, whereas BSA showed a similar response to LO of a decreased ΔTEP (Figure 6.8A). The similar trends between LM, TA, and SDS and between LO and BSA held true with CaCl2 and at pH 4 (Figure 6.8). Our final hypothesis, (iii) based on the MIT model or the Michaelis–Menten model, was that some DOCs would be protective (i.e. making TEP more negative), and others would exacerbate the harmful effects of Na+ or Ca2+ (i.e. making TEP less negative), and these responses would be pH-sensitive. Overall, this was supported. Predicting the toxicity with either model alone proved to be challenging as the models often did not agree with one another. In order to make meaningful predictions, we used a weight 175 of evidence approach, considering four metrics: absolute TEP, ΔTEP, ΔTEPmax, and Km. As noted in Introduction, it is currently unclear whether the various TEP metrics or Km values are the more important indicators of toxicity, so all were tabulated. This allowed us to determine the overall trends of agreement or disagreement among the metrics as well as to provide predictions on the toxicity of Na+ or Ca2+ at each pH, with respect to each of the tested DOCs. Indeed, this analysis showed that some DOCs are predicted to be protective against Na+ or Ca2+ toxicity, while others may exacerbate it, both in a pH-dependent manner. Each of these predictions is further discussed below. 6.5.2 The independent effects of pH Na+, or Ca2+, or DOC on TEP TEP became significantly more positive at pH 4 compared to pH 7 (p=0.0013). Our results agree with the acute TEP responses to low pH previously reported in the Amazonian tambaqui (Wood et al. 1998), brown trout (McWilliams and Potts 1978), and rainbow trout (Ye et al. 1991). As discussed above (see Section 6.2), TEP in freshwater fish is almost entirely a diffusion potential based on the differential permeability of Na+ (the major plasma cation) relative to Cl- (the major plasma anion) across the gills (Potts 1984; Wood et al. 1998). Ambient low pH changes this differential permeability of Na+ versus Cl- at the gill resulting in a more positive TEP. The external increased H+ concentration also increases the diffusion gradient for H+ entry. The result of the increased TEP is potentially fatal, favoring Na+ efflux and opposing Na+ influx, thereby inducing ionoregulatory failure (McWilliams and Potts 1978; Wood et al. 1998, 2020). Both NaCl and CaCl2 resulted in concentration-dependent increases in the absolute TEP values (Figure 6.2A, C). The relationships between the absolute TEP response and the geometric 176 concentration series were hyperbolic with the start of the plateau coinciding with the LC50 value. This response is in agreement with recent studies across species including fathead minnow, channel catfish, bluegill (Wood et al. 2020), goldfish, and rainbow trout (Po and Wood 2021). The trend in TEP response to the geometric series of NaCl or CaCl2 was not greatly different at pH 4; however, the shift in baseline TEP due to low pH is reflected in the ΔTEP curves (Figure 6.2B, D). Similarly to previously reported data (Wood et al. 2020; Po and Wood 2021), our data follow a pattern that can be described by the Michaelis-Menten equation. Km values define the position of the concentration-kinetic curve, and in general, across species, at circumneutral pH, the Km values were much lower (i.e. higher affinity) for CaCl2 compared to NaCl (Wood et al. 2020; Po and Wood 2021) which remained true in the present study (Table 6.1, Table 6.2). As with low environmental pH, increased ambient Na+ or Ca2+ changes the differential permeability at the gills and increases the diffusion gradient for ion entry. However, Ca2+ also likely reduces the ion permeability of the gill by acting on the tight junctions, titrating the negative charge on these pathways (Potts 1984; Evans et al. 2005). DOC has been shown to directly influence TEP in freshwater fish, generally resulting in a decrease in TEP (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019; Morris et al. 2021, see Chapter 2). Indeed, this was the case with LM DOC at both pHs (Figure 6.1). A decrease in TEP (i.e. more negative values) is beneficial to ionoregulation as it favors the uptake of cations including Na+. DOC has many charged chemical moieties that may alter the paracellular permeability of the gills or influence the differential permeability of Na+ versus Cl- at the gill (Campbell et al. 1997; Galvez et al. 2008; Morris et al. 2024b, see Chapter 3). However, DOCs are extremely diverse, and not all DOCs are equal in exerting physiological effects. TEP responses have been previously correlated to the quality and characteristics of the DOC (Galvez 177 et al. 2008; Morris et al. 2024b, see Chapter 3). Allochthonous DOCs often have a larger physiological effect, when compared to autochthonous DOCs which has been attributed to the higher aromaticity of allochthonous DOCs (Galvez et al. 2008; Morris et al. 2024c, see Chapter 4). Our data agree with this. For example, LM and LO did not have the same direction or magnitude in TEP response at pH 7. These DOCs have been previously characterized (Morris et al. 2024b, see Chapter 3), and indeed, the allochthonous LM DOC was much more aromatic compared to the autochthonous LO DOC. The model compounds shared similar TEP responses to the natural DOCs whereby at pH 7 LM, TA, and SDS decreased TEP, while LO and BSA increased TEP (Figure 6.1A). Based on these results, the decrease in TEP caused by LM at pH 7 could be due to the phenolic hydroxyl groups (shared with TA) and/or the long aliphatic chains (shared with SDS). In contrast, the increase in TEP caused by LO DOC may be due to the higher protein and amino acid content compared to LM such as tyrosine (shared by BSA). A higher amino acid content is predicted in autochthonous DOCs compared to allochthonous DOCs (Thurman 1985) which we confirmed in our DOCs in a previous study (Morris et al. 2024b, see Chapter 3). While low pH and DOC independently alter the TEP response, DOCs may offer protection against the changes in TEP caused by low pH (Sadauskas‐Henrique et al. 2019). Although low pH increased TEP, each of the tested natural DOCs and model compounds resulted in hyperpolarization (lower TEP) at pH 4 (Figure 6.1B). These could potentially be due to changes in the physicochemical properties of these natural DOCs at low pH, allowing them to interact with the gill more effectively. Many of these pH-dependent changes could be attributed to altered conformation (i.e. spatial arrangement of the molecule) of the DOCs rather than the composition (i.e. chemical makeup of the molecule); however, changes in proton binding at low pH likely result in compositional changes to the DOC molecules including greater lipophilicity 178 (Morris et al. 2024b, see Chapter 3). 6.5.3 Interactive effects of pH Na+, or Ca2, and DOC The independent effects of pH (McWilliams and Potts 1978; Ye et al. 1991; Wood et al. 1998; Sadauskas‐Henrique et al. 2019), major salt ions (Wood et al. 2020; Po and Wood 2021, 2022), and DOC (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019; Morris et al. 2021, see Chapter 2) have been previously described; however, our data are the first to analyze the interactive effects of these water quality parameters. While the TEP response curves to NaCl or CaCl2 follow the same trend, they were dependent on the pH and the DOC present (Figure 6.3, Figure 6.4, Figure 6.5, Figure 6.6). At pH 7, for both NaCl and CaCl2, there were no significant changes in the absolute TEP in response to a DOC or model DOC compound compared to the control that was maintained at pH 4 (Figure 6.7). With the exception of SDS in NaCl, as there was a significant increase at both pH 7 and pH 4, this was also true when looking at the ΔTEP responses at the LC50. For the M-M analysis, there were fewer significant changes for the ΔTEP versus CaCl2 concentration curves caused by the various DOCs and model compounds, and none of them were the same as those seen in the NaCl trials (Table 6.1, Table 6.2). The Km values were lower for the CaCl2 curves when compared to the NaCl curves, suggesting that CaCl2 is more potent and that the DOCs have a less mitigating effect against changes in TEP. This is likely because both DOCs and Ca2+ have effects on paracellular permeability as discussed above. Additionally, for some experimental solutions, the significant change when compared to the reference or control was in ΔTEPmax and others in Km, suggesting a different physiological mechanism depending on the water chemistry. 179 Although the presence of DOC may influence how the gills respond to increased ambient Na+ or Ca2+, it is likely not due to changes in the available free versus bound cations. There is only a very small percentage of Na+ or Ca2+ bound to the DOC at either pH, as shown in (Appendix D ). As described above, pH influences the physicochemical properties of the DOC and this may influence how Na+ or Ca2+ interacts with the gill; however, the increased ambient salt concentration may likewise influence the properties of the DOC. Previous studies have demonstrated that pH as well as ionic strength alters the molecular conformation of DOCs (Chin and Gschwend 1991; Gennings et al. 2001; Morris et al. 2024b, see Chapter 3). Therefore, it is likely that our results are due to changes in the DOCs themselves, resulting in changes in the differential permeability of Na+ or Cl- at the gill as well as in the paracellular permeability, especially in the CaCl2 series. 6.5.4 Predicting toxicity In order to predict a shift in Na+ or Ca2+ toxicity considering the DOCs/ model compounds and pH, we compared the changes in four metrics: absolute TEP, ΔTEP, ΔTEPmax, and Km. As per the EPRI MIT model, an increase in absolute TEP from baseline is thought to be predictive of increased salt toxicity (see Section 6.2). It has also been demonstrated that ΔTEP corresponds well with reference LC50 values (Wood et al. 2020; Po and Wood 2021, 2022) and could be useful in predicting toxicity whereby an increase in ΔTEP at the reference LC50 would represent an increase in toxicity. Finally using the M-M analyses, an increase in ΔTEPmax would similarly predict an increase in toxicity, whereas a decrease in Km would represent an increase in toxicity. We have indicated the predicted increase or decrease in salt toxicity with respect to the reference solution (i.e. control) for each of our experimental tests using each metric (Figure 6.9, 180 see Appendix D Table SD 7 for a full table of results). Overall, there was not consistent agreement between the four metrics; therefore, using a weight of evidence approach increased the support for our predictions. Absolute TEP and ΔTEP did not exhibit great agreement: Only 9 out of 22 cases or predictions were in agreement with one another (Figure 6.9, Appendix D Table SD 7). Absolute TEP and ΔTEPmax likewise only had only 9 out of 22 predictions in agreement. Absolute TEP and Km had the least agreement out of any pair of metrics with only 2 out of 22 predictions in agreement, whereas ΔTEP and ΔTEPmax had almost perfect agreement, supported by 21 out of 22 predictions. ΔTEP and Km had 10 out of 22 predictions in agreement, and ΔTEPmax and Km had exactly half of the total predictions in agreement at 11 out of 22 (Figure 6.9, Appendix D Table SD 7). In general, NaCl exhibited more significant changes in the four metrics (14) when compared to CaCl2 (9). There is a predicted increase in both NaCl and CaCl2 toxicity at pH 4, compared to pH 7, by absolute TEP, and predicted decreases by the 3 other criteria (Appendix D Table SD 7). The majority of the predictions about the effects of DOC changed between pH 7 and pH 4 for absolute TEP. This statement was supported by 6 out of 10 comparisons. There are more significant comparisons at pH 7 compared to pH 4. This is supported by 11 significant comparisons at pH 4 versus 5 significant comparisons at pH 4 (Appendix D Table SD 7). Using the same weight of evidence approach, we were also able to predict the effects of the DOC on Na+ or Ca2+ toxicity at each pH. At pH 7, LM was predicted to increase Na+ toxicity (supported by 4/4 comparisons, of which 2/4 were significant) and Ca2+ toxicity (supported by 3/4 comparisons, with 1/4 significant) (Figure 6.9), whereas at pH 4 it predicted that Na+ toxicity in the presence of LM would also increase (3/4 comparisons but 0/4 significant), but Ca2+ toxicity would decrease (supported by 3/4 comparisons with 2/4 significant). We predicted that at pH 7, 181 LO would decrease Na+ toxicity (3/4 comparisons, 2/4 significant) and may slightly decrease Ca2+ toxicity (2/4 comparisons, although only 1/4 significant). At pH 4 LO may increase Na toxicity (3/4 comparisons, 1/4 significant) and may increase Ca2+ toxicity (4/4, but 0/4 significant). We would also predict that TA may increase toxicity of both Na+ and Ca2+ at pH 7 (3/4 comparisons, 0/4 significant), but at pH 4 TA may decrease Na+ toxicity (3/4 comparisons, 0/4 significant) and decrease Ca2+ toxicity (3/4 comparisons, 0/4 significant). At pH 7 we predict that BSA may decrease Na+ toxicity (2/4 comparisons, 2/4 significant) and decrease Ca2+ toxicity (3/4 comparisons, 0/4 significant). However, at pH 4, BSA may increase both Na+ toxicity (3/4 comparisons, 0/4 significant) and Ca2+ toxicity (3/4 comparisons, 3/4 significant). At both pHs, SDS may increase Na+ toxicity (at pH 7, 2/4 comparisons, 2/4 significant; at pH 4, 3/4 comparisons, 2/4 significant) and Ca2+ toxicity (pH 7, 2/4 comparisons, 1/4 significant; at pH 4, 3/4 comparisons and 0/4 significant) (Figure 6.9). As outlined above, the TEP responses for LM, TA, and SDS follow a similar trend and the TEP responses for LO and BSA follow a similar trend which may be due to key chemical moieties. This is reflected in the toxicity predictions, particularly at pH 7. It is possible that the predicted increase in salt toxicity seen at pH 7 is due to the shared key chemical moiety between LM, TA, and SDS of phenolic hydroxyl groups and long aliphatic chains and the predicted decrease in salt toxicity may be due to the shared proteins and amino acids (e.g. tyrosine) in LO and BSA. At pH 4 the relationship is slightly more complicated. At pH 4 Na+ and Ca2+ toxicity may be increased due to proteins/amino acids as indicated by the predicted toxicity in the presence of LO and BSA. Na+ toxicity may also be increased in the presence of long aliphatic chains as Na+ toxicity is predicted to also increase in the presence of LM and SDS. At pH 4, a decrease in Ca2+ toxicity may be due to the presence of phenolic hydroxyl groups as reflected in 182 the predicted toxicity with LM and TA. Based on these results and the corresponding predictions, it is likely that key chemical moieties of DOC play a pH-dependent role in both Na+ and Ca2+ toxicity. 6.6 Concluding remarks In general, environmental decisions and policies (e.g. USEPA 2011) are guided by modeling which enhances the understanding of the response of environmental systems exposed to hazardous substances. While modeling is an extremely valuable tool, models must be both based on and confirmed by experimental testing. The predictions we have provided are not based on toxicity testing, but rather on physiological endpoints associated with reference LC50 values. Therefore, follow-up studies should validate these predictions with standardized toxicity testing. The reference LC50 values used in our analysis come from older studies (Durand-Hoffman 1995) with juvenile fish at a size where the gills are fully functional in ionoregulation. In most jurisdictions, including the one in which we work, it is no longer possible to carry out LC50 testing with fish once they have reached the yolk sac absorption stage, due to ethical and/or legal restrictions. Tests with such early life stages where the gills are not yet fully functional in ionoregulation would be problematic for validating the present models. Therefore, future testing of the preceding predictions will need to employ LC50 tests on invertebrates such as daphnids. There are certainly notable differences in the physiological response patterns to increases in ambient major ions between daphnids (Morris et al. 2020) and freshwater fish (Wood et al. 2020; Po and Wood 2021). However, there may unifying principles between TEP responses (i.e. the endpoint used here to predict toxicity) in daphnids and fish (fathead minnows) based on correlations in toxicity and a potency relationship between different individual salts and the 183 changes in TEP in the two very different species (C. Morris, B. Po, M. J. O’Donnell, C.M. Wood, unpublished results). This suggests that electrochemical modelling could be used to predict the short-term ΔTEP value at the gills and in turn the associated toxicity. However, more physiological data will be required to determine the modeling required for extrapolation across species and taxa, especially when dealing with the interactive effects of pH and different types of DOC. 184 6.7 Chapter 6 – Tables Table 6.1. The Michaelis-Menten constants and R2 values for NaCl at pH 7 and pH 4 with and without added DOC (means ± SEM, N =6). Significance for t-test comparisons p<0.05, with bold font used for significant differences. Exposure solution pH ∆TEPmax (mV) p-value ∆TEPmax Km (mmol L-1) p-value Km R2 NaCl 7 24.27 ± 0.911 - 7.35 ± 0.59 - 0.918 NaCl 4 18.72 ± 1.22 0.0006 12.01 ± 1.22 0.021 0.810 NaCl 7 23.39 ±1.83 - 8.19 ± 1.12 - 0.938 NaCl + LM 7 28.52 ± 0.92 0.049 5.24 ± 0.23 0.093 0.945 NaCl 7 23.89 ± 1.77 - 6.80 ± 0.79 - 0.889 NaCl + LO 7 19.43 ± 0.88 0.0531 12.06 ± 1.02 0.007 0.976 NaCl 7 23.90 ± 2.23 - 7.02 ± 1.74 - 0.911 NaCl + TA 7 29.96 ± 3.59 0.0567 8.58 ± 3.55 0.79 0.904 NaCl 7 23.75 ± 1.96 - 7.49 ± 1.13 - 0.882 NaCl + SDS 7 34.73 ± 1.70 0.006 7.59 ± 1.91 0.981 0.962 NaCl 7 26.53 ± 1.76 - 7.32 ± 1.15 - 0.973 NaCl + BSA 7 18.38 ± 1.04 0.011 7.30 ± 0.96 0.997 0.950 NaCl 4 17.44 ± 1.78 - 7.79 ± 1.24 - 0.902 NaCl + LM 4 22.16 ± 0.83 0.054 7.04 ± 2.19 0.604 0.860 NaCl 4 22.32 ± 2.08 - 10.57 ± 2.62 - 0.893 NaCl + LO 4 27.12 ± 2.13 0.133 3.59 ± 0.67 0.044 0.861 NaCl 4 20.94 ± 3.24 - 14.16 ± 3.44 - 0.870 NaCl + TA 4 18.80 ± 2.18 0.959 4.89 ± 1.67 0.364 0.649 NaCl 4 15.98 ± 2.26 - 17.45 ± 5.28 - 0.843 NaCl + SDS 4 24.89 ± 2.25 0.003 18.36 ± 4.00 0.608 0.900 NaCl 4 16.93 ± 3.04 - 7.71 ± 4.31 - 0.504 NaCl + BSA 4 22.10 ± 2.86 0.303 4.36 ± 1.01 0.475 0.626 185 Table 6.2. The Michaelis-Menten constants and R2 values with modified substrate inhibition for CaCl2 at pH 7 and pH 4 with and without DOC (means ± SEM, N = 6). Significance for t-test comparisons p<0.05, with bold font used for significant differences. Exposure solution pH ∆TEPmax (mV) p-value ∆TEPmax Km (mmol L-1) p-value Km R2 CaCl2 7 28.30 ± 0.92 - 2.51 ± 0.41 0.856 CaCl2 4 24.49 ± 1.15 0.024 4.69 ± 0.76 0.018 0.818 CaCl2 7 30.84 ± 1.26 - 2.59 ± 0.52 - 0.892 CaCl2 + LM 7 33.02 ± 2.31 0.522 0.62 ± 0.09 0.030 0.729 CaCl2 7 28.22 ± 1.68 - 3.55 ± 1.03 - 0.658 CaCl2 + LO 7 19.16 ± 1.94 0.021 3.29 ± 0.32 0.658 0.942 CaCl2 7 24.25 ± 2.18 - 0.15 ± 0.06 - 0.640 CaCl2 + TA 7 27.50 ± 1.71 0.332 0.484 ± 0.20 0.118 0.800 CaCl2 7 30.03 ± 1.44 - 4.97 ± 0.57 - 0.870 CaCl2 + SDS 7 27.43 ± 4.35 0.633 2.50 ± 0.21 0.011 0.938 CaCl2 7 30.25 ± 2.39 - 1.69 ± 0.45 - 0.906 CaCl2 + BSA 7 27.67 ± 2.23 0.491 3.43 ± 0.43 0.067 0.951 CaCl2 4 27.80 ± 3.38 - 8.25 ± 2.25 - 0.938 CaCl2 + LM 4 17.45 ± 2.11 0.009 0.62 ± 0.23 0.032 0.546 CaCl2 4 21.16 ± 3.49 - 4.31 ± 1.73 - 0.751 CaCl2 + LO 4 23.58 ± 3.26 0.597 1.67 ± 0.56 0.183 0.667 CaCl2 4 28.69 ± 2.66 - 5.09 ± 1.06 - 0.918 CaCl2 + TA 4 21.36 ± 1.76 0.153 1.57 ± 0.41 0.039 0.600 CaCl2 4 27.26 ± 2.01 - 3.45 ± 0.78 - 0.776 CaCl2 + SDS 4 31.73 ± 4.66 0.419 1.82 ± 0.28 0.287 0.746 CaCl2 4 16.19 ± 1.25 - 1.91 ± 0.71 - 0.635 CaCl2 + BSA 4 29.35 ± 0.84 0.0002 2.16 ± 0.70 0.717 0.832 186 6.8 Chapter 6 – Figures Figure 6.1. The effects of natural dissolved organic carbon (DOC) or model DOC compounds on baseline TEPs with 0% added salt at (A) pH 7 and (B) pH 4:Luther Marsh (LM) DOC, Lake Ontario (LO) DOC, Tannic acid (TA), Sodium dodecyl sulfate (SDS); Bovine serum albumin (BSA). Data are means + SEM, N=11-14. Asterisks represent significant difference from control with the addition of DOC (Student’s paired t-test, p<0.05). Bars not sharing the same letters are significantly different) (analysis of variance with Tukey’s test, p<0.05). 187 Figure 6.2. The effect of added (A) NaCl at pH 7 and pH 4 on absolute TEP: (B) NaCl at pH 7 and pH 4 on TEP; (C) CaCl2 at pH 7 and pH 4 on absolute TEP; (D) CaCl2 at pH 7 and pH 4 on TEP. Data are means + SEM, N=30-32. In each case, a Michaelis-Menten Model was fitted to the TEP data for NaCl, and a Michaelis-Menten Model with substrate inhibition was fitted to the TEP data for CaCl2. Lines represent connected data points rather than regression lines. 188 189 Figure 6.3. The interactive effects of NaCl and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 7: (A) Luther Marsh (LM) DOC on absolute TEP; (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E)Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP ; (J) BSA on TEP. Data are means ± SEM, N=6-8. In each case, a Michaelis-Menten Model was fitted to the TEP data for NaCl. Asterisks represent significant difference by Student’s paired t-test (p <0.05 is considered significant). 190 191 Figure 6.4. The interactive effects of NaCl and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 4: (A) Luther Marsh (LM) DOC on absolute TEP; (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E) Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP. Data are means ± SEM, N=6-8. In each case, a Michaelis-Menten Model was fitted to the TEP data for NaCl. Asterisks represent significant differences by Student’s paired t-test (p <0.05 is considered significant). 192 193 Figure 6.5. The interactive effects of CaCl2 and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 7: (A) Luther Marsh (LM) DOC on absolute TEP; ( (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E) Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP. Data are means ± SEM, N=6-8. In each case, a Michaelis-Menten Model with substrate inhibition was fitted to the TEP data for CaCl2. Asterisks represent significant differences by Student’s paired t-test (p <0.05 is considered significant). 194 195 Figure 6.6. The interactive effects of CaCl2 and natural dissolved organic carbon (DOC) or model DOC compounds on TEP at pH 4: (A) Luther Marsh (LM) DOC on absolute TEP; (B) LM DOC on TEP; (C) Lake Ontario (LO) DOC on absolute TEP; (D) LO DOC on TEP; (E) Tannic acid (TA) on absolute TEP; (F) TA on TEP; (G) Sodium dodecyl sulfate (SDS) on absolute TEP; (H) SDS on TEP; (I) Bovine serum albumin (BSA) on absolute TEP; (J) BSA on TEP. Data are means ± SEM, N=6-8. In each case, a Michaelis-Menten Model with substrate inhibition was fitted to the TEP data for CaCl2. Asterisks represent significant differences by Student’s paired t-test (p <0.05 is considered significant). 196 Figure 6.7. The absolute TEP response with and without added natural DOC or model DOC compounds at LC50 concentration of (A) NaCl at pH 7; (B) CaCl2 at pH 7; (C) NaCl at pH 4; (D) CaCl2 at pH 4. Data are means + SEM, N=6-8. Asterisks represent significant differences from control with the addition of DOC (Student’s paired t-test, p<0.05). 197 Figure 6.8. The TEP response with and without added natural DOC or model DOC compounds at LC50 concentration of (A) NaCl at pH 7; (B) CaCl2 at pH 7; (C) NaCl at pH 4; (D) CaCl2 at pH 4. Data are means + SEM, N=6-8. Asterisks represent significant differences from control with the addition of DOC (Student’s paired t-test, p<0.05). 198 Figure 6.9. The predicted toxicities of the various experimental solutions [Luther Marsh (LO), Lake Ontario (LO), Tannic acid (TA), Sodium dodecyl sulfate (SDS) or Bovine serum albumin (BSA)] relative to their appropriate reference solutions [NaCl or CaCl2 ] as assessed by differences in absolute TEP, TEP and the M-M constants, DTEPmax and Km at pH 7 and pH 4. Colours have been used to visualize trends: red indicates a statistically significant predicted increase in toxicity of the experimental solution (compared to the reference solution) , orange indicates a predicted increase in toxicity of the experimental solution (not statistically significant), green indicates a predicted decrease in toxicity of the experimental solution (not statistically significant) and blue represents a statistically significant predicted decrease in toxicity of the experimental solution. 199 Chapter 7: The effect of salinity and calcium on diffusive water flux, oxygen consumption and nitrogenous waste excretion rates in Pacific sanddab (Citharichthys sordidus) and Rock sole (Lepidopsetta bilineata). 7.1 Summary Marine flatfishes have a low metabolic rate and routinely encounter large fluctuations in salinity, and are therefore of interest in the study of diffusive water flux (a proxy for transcellular water permeability), oxygen consumption (ṀO2), ammonia excretion and urea-N excretion as a function of salinity and seawater [Ca2+]. These parameters were measured in two coastal marine flatfishes, Pacific sanddab and Rock sole acclimated to 31 ppt and exposed acutely (for up to 3h), to environmentally relevant salinities of 45, 15.5, or 7.5 ppt. In both species, diffusive water flux and ammonia excretion rates increased as salinity decreased. ṀO2 and urea-N excretion rates remained relatively unchanged. Nitrogen quotient analysis indicated increased oxidation of protein at lower salinity. A second experimental series was performed on Rock sole to separate the effects of salinity from those of ambient [Ca2+]. In direct contrast to the significant increase seen at 7.5 ppt, reducing salinity from 31 ppt to 7.5 ppt while maintaining [Ca2+] at 10 mM or increasing it to 20 mM resulted in no change in diffusive water flux rate, demonstrating that reduced [Ca2+], rather than reduced salinity itself, is the primary cause for the increases in diffusive water flux. However, ammonia excretion rate increased when salinity was decreased and [Ca2+] was increased compared to 31 ppt with added [Ca2+]. Our results demonstrate that both diffusive water flux and ammonia excretion rates are a function of salinity, that neither are coupled to ṀO2, and that ambient [Ca2+] also plays a role in these rates. 200 7.2 Introduction As the world’s climate gets warmer, ocean salinities are changing. Recent analyses show that in the past 50 years, the global water cycle has amplified by 2~4 % per degree Celsius since 1960, resulting in greater salinity extremes, with the largest effects in surface waters (Stagl et al. 2014; Cheng et al. 2020). Coastal waters of the north-west Pacific are becoming less saline, and greater reductions will likely occur in estuarine areas as winter and spring runoff events become more extreme (Rogers et al. 1984; Cao et al. 2020). On the other hand, sea level rise drives the formations of coastal lagoons, which can quickly develop hypersalinity due to evaporation (1994). Estuaries are prime habitats for many inshore fish species such as flatfishes (Order Pleuronectiformes), which in general have considerable capacity for euryhalinity (reviewed by Schreiber 2001; Ruiz-Jarabo et al. 2015). Both of these syntheses emphasize that there has been considerable research on salinity effects in flatfish early life stages, but very little on adults. Nevertheless, it is clear that salinity fluctuations exert considerable allostatic costs throughout the life cycle (Ruiz-Jarabo et al. 2015), and acute salinity challenges may elicit increases in oxygen consumption rates (e.g. Herrera et al. 2012; Onukwufor and Wood 2022). In the present study, we address the effects of acute decreases and increases in salinity on adults of two Pacific flatfish species that are known to move in and out of estuaries, thereby routinely encountering salinity challenges. Our experiments focused on water exchange, ammonia and urea-N excretion (indicative of protein metabolism), and aerobic metabolic rate as reflected in oxygen consumption (ṀO2). We also performed experiments to separate the effect of environmental calcium concentration, which usually, but not always, co-varies with salinity (Connors and Kester 1974), from those of salinity itself. 201 Water exchange in teleost fish is a complex and as yet relatively poorly understood process. As reviewed by Wood et al. (2019), it is presently believed that water moves across the gills through two distinct pathways, paracellularly through tight junctions where it is thought to move by bulk flow, and by diffusion across the entire gill surface, the latter largely by the transcellular pathway through aquaporins. Aquaporins are channels in cell membranes that greatly facilitate the diffusion of water. They were first identified by Preston et al. (1992), and several different types are now known to be abundant in fish gills (Cerdà and Finn 2010; Tingaud-Sequeira et al. 2010; Madsen et al. 2015). Diffusive water flux is measured by the unidirectional movement of tritiated water (3H2O) and is at least two orders of magnitude greater than net flux rate through the paracellular pathway, which can be measured only by indirect means. Therefore, measurement of diffusive water flux rate with 3H2O is considered a proxy for transcellular water permeability. Diffusive water flux rate is lower in seawater fishes compared to freshwater fishes which may represent an adaptation to combat the higher osmotic gradient between the external seawater environment and internal plasma (Evans 1969; Motais et al. 1969; Potts and Fleming 1970; Isaia 1984; Wood et al. 2019). This may also be due to the differences in specific ion concentrations such as Ca2+ (Isaia and Masoni 1976; Isaia 1984; Hunn 1985) which are higher in seawater than in freshwater. In both the Pacific sanddab, and the English sole, a decrease in salinity resulted in an increase in diffusive water flux rate (Onukwufor and Wood 2022). In accord with this general pattern, many studies have reported lower expression of aquaporins in the gills in seawater fishes compared to freshwater fishes (e.g. Lignot et al. 2002; Cutler et al. 2007; Tipsmark et al. 2010; Madsen et al. 2015; Breves et al. 2016). However, some exceptions occur. For example, in the euryhaline killifish, Jung et al. (2012) and Ruhr et al. (2020) demonstrated that protein abundance and mRNA expression of aquaporin AQP3 respond 202 in a complex fashion to differences in acclimation salinity, in the presence and absence of hypoxia. It is well-established that water calcium concentration affects several aspects of gill permeability. For example, elevated environmental [Ca2+] reduces the diffusive water permeability of the gills in both fish (Oduleye 1975; Isaia and Masoni 1976) and crustaceans (Rasmussen and Bjerregaard 1995). In mammals, both intracellular and extracellular [Ca2+] regulate aquaporin function (Németh-Cahalan and Hall 2000; Valenti et al. 2005), but it is not known whether the [Ca2+] in the external medium produces similar effects on branchial aquaporins in fish, thereby influencing the diffusive water flux rate. While we are aware of no evidence for the presence of aquaporins in tight junctions, it is also well established that elevated environmental [Ca2+] helps to maintain the integrity of paracellular tight junctions (McWilliams and Potts 1978; McWilliams 1982). Both these effects may contribute to reductions in permeability to water when osmotic gradients are present (McWilliams and Potts 1978; Wendelaar Bonga and Van Der Meij 1981; McWilliams 1982; McDonald 1983; Hunn 1985; McDonald and Rogano 1986). However, an additional complication is that paracellular permeability of the branchial tight junctions appears to increase at higher salinity (Marshall 2012), despite the higher water [Ca2+] and lower water permeability in seawater fish. In freshwater fish, ammonia excretion occurs predominantly by a transcellular route through Rh proteins, with contributions from a basolateral Na+/NH4+‐ATPase and an apical Na+/ H+ antiporter coupled with NH3 diffusion (Nawata et al. 2007; Wright and Wood 2009, 2012; Wood et al. 2014). In seawater fish, the Rh proteins and Na+/ H+ antiporter are present (Nawata et al. 2010), but the leakier paracellular tight junctions may also play an important role (Wilkie 1997, 2002; Weihrauch et al. 2009; Wright and Wood 2009). When three euryhaline species 203 (rainbow trout - Wood and Nawata 2011; guppies - Zimmer et al. 2012; killifish - Giacomin et al. 2020), were acclimated to seawater, ammonia excretion rates were higher than in freshwater. Urea produced by uricolysis and/or arginolysis circulates in adult ammoniotelic fish and is excreted continuously (McDonald et al. 2000; Walsh et al. 2001; McDonald and Wood 2003). A large proportion of these fish have urea transporter (UT) expression in their gills (Walsh et al. 2001; McDonald et al. 2006) and while this may not always translate into functional gill UT, there is clear evidence that many ammoniotelic fish do have UTs that effectively excrete urea through the gills (reviewed by McDonald et al. 2006, 2012). Some freshwater and seawater teleosts may also have the ability to transport ammonia and/or urea through aquaporin subtypes found in the gill (Cutler et al. 2007; Tipsmark et al. 2010; Chen et al. 2010; Tingaud-Sequeira et al. 2010; Kolarevic et al. 2012; Ip et al. 2013). The extent of transport through these transcellular pathways in fish remains uncertain. An additional complication is that ammonia and urea-N excretion rates may also change in response to changes in the rate at which protein is being burned in oxidative metabolism. However, this can be detected by measuring the nitrogen quotient (NQ), the ratio of nitrogen excretion to ṀO2 (Van Den Thillart and Kesbeke 1978; Van Waarde 1983; Lauff and Wood 1996). In general, flatfishes have a low metabolic rate, a high tolerance for hypoxia and are able to withstand large fluctuations in salinity (Wood et al. 1979; Steffensen et al. 1982; Dalla Via et al. 1998; Maxime et al. 2000; Schreiber 2001; Ruiz-Jarabo et al. 2015). Salinity influences flatfish distribution, with many species migrating to the lower salinity waters of estuaries for feeding, and during larval development and metamorphosis (Evans 1984; Burke et al. 1991; Minami and Tanaka 1992; Gibson 1994). Many also thrive in hypersaline lagoons (e.g. McNeil et al. 2013; Cruz et al. 2018); indeed the greenback flounder (Rhombosolea tapirine) has been 204 caught in salinities above 81 ppt (McNeil et al. 2013). In the current study we investigated two north-west Pacific flatfishes that reside in benthic coastal environments. Both the Pacific sanddab (Thornburgh 1980; Durkin et al. 1981; Bottom et al. 1984; Armor and Herrgesell 1985; Rackowski and Pikitch 1989; Rooper et al. 2006; Sobocinski et al. 2018) and the Rock sole (Abookire et al. 2000; Essington et al. 2013; Beaudreau et al. 2022) are well documented to move in and out of estuaries. Diffusive water flux, ṀO2, ammonia excretion and urea-N excretion rates were measured as a function of acute changes in water salinity and calcium concentration. With the preceding background in mind, we hypothesized that; i) diffusive water flux rates would increase in low salinity and decrease in high salinity; ii) oxygen consumption rates would become elevated during both of these challenges; iii) ammonia excretion would decrease at low salinity and increase in high salinity while urea excretion would remain stable through the experimental treatments; iv) changes in water [Ca2+] would play an important role in these responses to salinity challenge; and v) overall response patterns would be similar in these two benthic species. In the course of answering these hypotheses, we report several novel findings. Notably, ammonia excretion increases as salinity decreases, similar to the pattern of diffusive water flux, and both are uncoupled from changes in ṀO2. Reliance on protein as an oxidative fuel increases as salinity decreases. Furthermore, reduced [Ca2+], rather than reduced salinity itself, is the primary cause for the increases in diffusive water flux rates seen at low salinity. These make important contributions to our understanding of the ecophysiology of adult flatfishes when coping with fluctuations in salinity. 205 7.3 Methods 7.3.1 Animals Flatfishes were caught by angling off Brady’s beach in August and September near the Bamfield Marine Sciences Center (BMSC), Bamfield, BC, Canada, under Fisheries and Oceans Canada collection permit XR 136 2021. Pacific sanddab (Citharichthys sordidus) (N=20, 0.185 ± 0.006 kg) and Rock sole (Lepidopsetta bilineata) (N=45, 0.358 ± 0.018 kg) were transported to BMSC where they were held in aerated tanks supplied with flowing seawater (31 ppt, 12 ºC). Fishes were fed with small chunks of salmon every second day and were fasted for at least 72 h before experiments commenced. Experimental fishes were transferred to individual aerated vessels supplied with seawater (31 ppt) that rested in a water bath to maintain a control temperature of 12 °C. The night before the experiment, fishes were allowed to settle in the experimental vessels which were slightly longer and wider than each individual fish (35 cm X 25 cm). Seawater was pumped from the nearby ocean to both BMSC holding tanks and the experimental set-up. Sand was present in the holding tanks for flatfishes to bury in during the day but was absent in the experimental vessels, as a previous study showed no significant differences in diffusive water flux or oxygen consumption rates in the presence and absence of sand (Onukwufor and Wood 2022). All procedures used in this investigation were in accordance with the Canadian Council on Animal Care guidelines and were approved by the University of British Columbia Animal Care Committee (AUP A18-0271) and the BMSC Animal Care Committee (AUP RS-21(19)-01). 206 7.3.2 Experimental series Two experimental series were performed, a salinity series and a salinity-Ca2+ series. In both series, diffusive water flux rates, oxygen consumption rates, and ammonia-N and urea-N excretion rates were measured. The salinity series tested the effect of 45 ppt, 31 ppt, 15.5 ppt, and 7.5 ppt in both Rock sole and Pacific sanddab. The salinity-Ca2+ series tested the effect of 31 ppt at 10 mM Ca2+, 31 ppt at 20 mM Ca2+, 7.5 ppt at 10 mM Ca2+, and 7.5 ppt at 20 mM Ca2+ in Rock sole only. 7.3.3 Experimental solutions All experimental solutions were maintained at 12 °C. Solutions of 45 ppt were made by adding an appropriate amount of Instant Ocean® Sea Salt (Blacksburg, VA, USA) to natural seawater (31 ppt). Solutions of 15.5 ppt and 7.5 ppt were made by diluting seawater with BMSC freshwater (Na+ 0.3, Cl- 0.2, K+ 0.005, Ca2+ 0.1, Mg2+ 0.05 mM) until the desired salinity was reached. Salinity was measured using a WTW Portable Conductivity Meter (ProfiLine Cond3310; Xylem Analytics, Welheim, Germany). At control salinity of 31 ppt, the background Ca2+ concentration was 10 mM Ca2+, and at 7.5 ppt, the background Ca2+ concentration was 2.5 mM. Analytical grade CaCl2 was added to the appropriate test salinity solution (i.e. 31 ppt or 7.5 ppt) to create four test solutions: 31 ppt at 10 mM Ca2+ (no CaCl2 addition, so the same composition as in 31 ppt in the salinity series), 31 ppt at 20 mM Ca2+, 7.5 ppt at 10 mM Ca2+, and 7.5 ppt at 20 mM Ca2+. The pH range among the various experimental solutions was less than 1.0 pH unit (Appendix E Figure SE 1) 207 7.3.4 Diffusive water flux The experimental protocol used for measuring diffusive water flux rates follows the procedure outlined by Onukwufor and Wood (2020). Briefly, the loading period began 12 h before the experiment started whereby 6-8 fish per experiment were loaded with 3H2O by exposure to 30 µCi of 3H2O (PerkinElmer, Woodbridge, ON, Canada) per litre of seawater (salinity 31) in individual aerated vessels, maintained at 12 oC. After the loading period, each individual fish and vessel was quickly rinsed with clean seawater. The fish was immediately placed back into the aerated, temperature-controlled vessel containing 2-4 L (exact volume recorded) of the experimental water without 3H2O. These were 7.5 ppt, 15 ppt, 31 ppt, or 45 ppt in the salinity series, and 7.5 ppt at 10 mM Ca2+, 7.5 ppt at 20 mM Ca2+, 31 ppt at 10 mM Ca2+or 31 ppt at 20 mM Ca2+ in the salinity-Ca2+ series. Each fish was provided with enough experimental water such that they were covered to a depth of several cm. A 4 ml aliquot of the experimental solution was taken at time 0, marking the start of the washout period, and every 5 min thereafter for 60 min. A final sample was taken at 12 h when the external and internal 3H2O pools were once again in equilibrium. The 12 h sample was used to calculate the original amount of radioactivity in the fish and the 0-60 min samples were used to determine the diffusive water flux rates. 7.3.5 Oxygen consumption Oxygen consumption rates (ṀO2) were measured as per Onukwufor and Wood (2022), directly following the end of the 60 min diffusive water flux experiment on the same fish. At the start of the measurements, PO2 was >80%. Aeration was removed, and the vessels were sealed 208 with Styrofoam covers cut to the exact size of the chambers with a hole only big enough to fit the oxygen probe (DO 6 + galvanic oxygen electrode and meter, Oakton Instruments, Vernon Hills, IL, USA). The decrease in PO2 was measured every 5 min until it reached 50% saturation, a PO2 that is well above the critical PO2 where ṀO2 becomes dependent on PO2 in these species (O.E. Johannsson and C.M. Wood, unpubl data, (Appendix E Figure SE 1). This period ranged from 10-65 min within the various treatments. Preliminary experiments demonstrated that the Styrofoam covers adequately blocked the entry of O2. 7.3.6 Ammonia and urea-N excretion Water samples (5 ml) were taken from each vessel directly following the end of the ṀO2 measurements once aeration was re-established, representing time 0, and samples were taken every 30 min for 2 h thereafter. Preliminary experiments demonstrated that this time interval was adequate. Concentrations of total ammonia (salicylate hypochlorite assay, Verdouw et al. 1978) and total urea-N (diacetyl monoxime assay, Rahmatullah and Boyde 1980) in water samples were measured colorimetrically, with standards made up in the appropriate salinities. 7.3.7 Analytical procedures and calculations As described by Onukwufor and Wood (2018), the concentration of 3H2O was determined by adding 8 ml of Optiphase 3 fluor (Perkin-Elmer, Wellesley, MA, USA) to the 4 ml water sample, shaking vigorously and loading it into a scintillation counter (LS6500, Beckman Coulter, Fullerton, CA, USA). Preliminary tests showed that quenching and chemiluminescence were negligible. The rate constant of 3H2O efflux (k) was calculated using the protocol outlined by Onukwufor and Wood (2020). Briefly, using the final 12-h wash-out 209 sample, the initial amount of 3H2O in the fish was determined. It was then possible to calculate the amount of 3H2O left in the fish at each sampling time from 0-60 min based on the measured amounts that appeared in the external solution at each time. Next, the natural logarithm of the total 3H2O in the fish at each sample time was regressed against time in minutes on a linear scale. The fractional rate constant k for water turnover was the slope of this line. Multiplying the rate constant k by 60 yielded the fraction of the body water pool turned over per hour. Generally, the total exchangeable water pool of a fish is 800 ml kg-1 (Isaia 1984; Olson 1992; Holmes and Donaldson 1996). To calculate the diffusive water flux rate in ml fish-1 h-1, the weight of the fish in kg was multiplied by 800 ml kg-1 and then by the fraction of the body water pool turned over per hour. PO2 was measured using the oxygen probe described above (see Section 7.3.5). ṀO2 calculations followed the procedure of Onukwufor and Wood (2020). Briefly, using salinity and temperature-dependent solubility coefficients (Boutilier et al. 1984), PO2 values were converted to O2 concentrations (µmol L-1). The rate of decline of O2 concentration was then multiplied by the known volume of the experimental vessel, and divided by time (h), to give ṀO2 in µmol fish-1 h-1. Ammonia-N and urea-N excretion rates (note: 1N per ammonia molecule, 2N per urea molecule) were calculated as per Wood (1992) whereby the change in concentration in the water (µmol-N L-1) was divided by the time of the flux period (h), and multiplied by the volume of the experimental container (L) to give the excretion rate as µmol-N fish-1 h-1. The four 30-min rates were averaged to yield a single value for each fish. 210 To account for the differences in body mass, the logarithms of each experimental measurement (diffusive water flux, ṀO2, ammonia-N and urea-N excretion rates, expressed as units fish-1 h-1) were regressed against the logarithm of fish weight (Table 7.1). For each statistically significant result (Table 7.1), an allometric mass scaling exponent was obtained by using the power equation Y=aMb where Y is the rate of interest (units fish-1 h-1), M is the body weight (kg) and b is the scaling exponent. When the power equation is transformed into a linear function, a, representing the proportionality constant, a is the y-intercept and b, representing the scaling exponent, is the slope (Huang and Riviere 2014). The allometric mass scaling exponents were used to adjust the diffusive water flux rates, ṀO2, ammonia or urea excretion rates of each individual fish to that of a standard 0.25 kg of flatfish, and then divided by 0.25 kg so as to yield rates expressed per kg per h. In cases where no scaling was applied (see Section 7.4), each individual rate expressed per fish per h was divided by weight in kg, to yield rates expressed per kg per h. The nitrogen quotient (NQ) is the ratio of the total measured nitrogenous waste excretion (ṀN), the sum of the ammonia-N excretion and the urea-N excretion, to the ṀO2. Therefore, the NQ was calculated as NQ = (ṀN/ṀO2) for each individual fish at the control salinity and in the experimental solutions. The unscaled rates were used for each measurement in the calculations. 7.3.8 Statistical analyses Data have been expressed as means ± standard error (SEM; N) where n represents the number of animals sampled. All data passed normality tests. Data that also passed the homogeneity of variance tests were analyzed using one-way analysis of variance (ANOVA) with Tukey’s post hoc test (multiple comparisons). If data did not pass the Brown-Forsythe test for 211 homogeneity of variances, data were analyzed using the Brown-Forsythe and Welch ANOVA test with Dunnett’s T3 multiple comparison test. The effects of water salinity on each measurement (diffusive water flux, ṀO2, ammonia and urea-N excretion) were analyzed by linear regression of the appropriate measurement versus the salinity of the water, and the significance of the regressions were assessed. Differences in mean control rates at salinity 31 between species, and also within the Rock sole in the salinity series versus the salinity-Ca2+ series were assessed by unpaired Student’s t-tests. All statistical analyses and data plots were done using GraphPad™ Prism 7 (GraphPad Software, San Diego, CA, USA). A significance level of p<0.05 (i.e. two-tailed) was used throughout, except in the case of allometric regressions where p<0.10 (i.e. one-tailed) was used, because for these, we predicted a priori that positive relationships should occur for all parameters. 7.4 Results 7.4.1 Allometric scaling exponents To calculate each of the scaling exponents for diffusive water flux rates, ṀO2, ammonia excretion and urea-N excretion rates, the control data at salinity 31 (i.e. the acclimation salinity) were used. The logarithms of individual diffusive water flux rates, ṀO2, ammonia-N excretion or urea-N excretion rates (expressed as units per fish per h) for each species, were plotted against the logarithms of individual fish weights. The relationships were significant at p < 0.10 for all parameters in both species, except for ṀO2 in Rock sole, and urea-N excretion rates in both species, as indicated in Table 7.1. Therefore, allometric scaling, based on the power equation 212 Y=aMb (see Section 7.3.8), was applied in subsequent analyses for all species-specific parameters except the three non-significant ones. The scaling exponents (Table 7.1) were used to adjust the individual experimental rates to that of a 0.25 kg flatfish. Only parameters that yielded significant relationships in the regressions were scaled and scaling exponents were in general agreement with those previously published across species and salinities (See Section 7.5.2). The appropriately scaled or unscaled rates were finally expressed as ml-1 kg-1 h-1 for diffusive water flux rates, µmol O2 kg-1 h-1 for ṀO2, µmol ammonia-N kg-1 h-1 for ammonia excretion rates and µmol urea-N kg-1 h-1 for urea excretion rates. The scaling exponents were consistently lower for Rock sole than for Pacific sanddab and were highest for ammonia excretion rate (0.747, 1.401), intermediate for diffusive water flux rate (0.673, 1.069) and lowest for ṀO2, (0.441, 0.862) (Table 7.1). 7.4.2 The effect of salinity on diffusive water flux rates At control salinity, 31 ppt, the mean diffusive water flux rates in Pacific sanddab were 168 ml kg-1 h-1, significantly higher than in Rock sole which were 136 ml kg-1 h-1 (p= 0.0248) (Appendix E Table SE 2). In Rock sole, the acute transfer from control salinity, 31 ppt, to 7.5 ppt, resulted in a significant 37% increase in diffusive water flux rates within the first hour (Figure 7.1A). In Pacific sanddab, rates were likewise significantly higher by 36% at 7.5 ppt when compared to the control salinity (Figure 7.1B). When diffusive water flux rates were regressed against salinity, there were significant negative relationships for both Rock sole (p= 0.0100) and Pacific sanddab (p= 0.0005) (Figure 7.1C, D). 213 7.4.3 The effect of salinity on ṀO2 The ṀO2 values were not significantly different between species at 31 ppt (Appendix E Table SE 2). Mean ṀO2 values in Rock sole were 1549 µmol O2 kg-1 h-1 and 1437 µmol O2 kg-1 h-1 in Pacific sanddab. There were no significant differences in ṀO2 values among salinity treatments in either species (Figure 7.2A, B). When ṀO2 was plotted against salinity, there was a significant positive relationship for Rock sole (p= 0.0108) but not in Pacific sanddab (Figure 7.2C, D). 7.4.4 The effect of salinity on ammonia and urea-N excretion rates The average ammonia excretion rates for both Rock sole and Pacific sanddab were about 305 µmol ammonia kg-1 h-1 and were not significantly different between species (Appendix E Table SE 2). The acute transfer of Rock sole from 31 ppt to 45 ppt resulted in a significant 47% decrease in ammonia excretion rates, and no significant changes were observed compared to control salinity in response to transfers to 15.5 ppt or 7.5 ppt (Figure 7.3A). In Pacific sanddab, the acute transfer from 31 ppt to 7.5 ppt resulted in a significant increase of 92% in ammonia excretion rates, but there were no significant changes in response to transfers to other salinities (Figure 7.3B). When the ammonia excretion rates were regressed against salinity there were significant negative relationships in both Rock sole (p= < 0.0001) and Pacific sanddab (p= 0.0014) (Figure 7.3C, D). At 31 ppt, mean urea-N excretion rates were not significantly different between Rock sole (44.9 urea-N kg-1 h-1) and Pacific sanddab (69.1 urea-N kg-1 h-1) (Appendix E Table SE 2). In Rock sole, there were no significant differences in urea-N excretion rates in response to any of the salinity treatments tested (Figure 7.4A). In Pacific sanddab, the acute transfer from 31 ppt to 214 15.5 ppt yielded a significant increase of 115%, but there was no significant effect of transfer to 7.5 ppt or 45 ppt (Figure 7.4B). There were no significant relationships between urea-N excretion rates and salinity in either species when urea-N excretion rates were regressed against salinity (Figure 7.4C, D). 7.4.5 The effect of salinity on the nitrogen quotient The nitrogen quotient, the ratio between total nitrogenous waste excretion rate and ṀO2, was about 0.23 at control salinity, 31 ppt, and not significantly different between Rock sole and Pacific sanddab (Appendix E Table SE 2). In Rock sole, there were no significant differences compared to the control salinity in response to exposure to the three other test solutions (Figure 7.5A). However, compared to 45 ppt, NQ was significantly greater by 128% in 15.5 ppt (Figure 7.5A). In Pacific sanddab, there was a significant 124% increase in NQ in 7.5 ppt compared to the control ratio (Figure 7.5B). When the NQ values were regressed against salinity there were significant negative relationships in both Rock sole (p= 0.0004) and Pacific sanddab (p= 0.0007) (Figure 7.5C, D). 7.4.6 The effect of Ca2+ during a salinity challenge in Rock sole In Rock sole, there were no significant differences (Appendix E ) between the salinity series control rates presented above (diffusive water flux, ṀO2, ammonia excretion and urea-N excretion) and the salinity-Ca2+ series control rates presented below. Note that in both, the seawater composition was identical (31 ppt at 10 mM Ca2+). The goal of this series was to separate the effects of salinity from those of external [Ca2+]. Doubling [Ca2+] from 10 mM to 20 mM at control salinity, 31 ppt, appeared to decrease the 215 mean diffusive water flux rate by 38%, though this difference was not significant (p=0.1213) (Figure 7.6A). Reducing salinity from 31 ppt to 7.5 ppt while maintaining [Ca2+] at 10 mM (p=0.5980) or increasing it to 20 mM (p= 0.1060) resulted in no change in diffusive water flux (Figure 7.6A), in direct contrast to the significant increase (p=0.0205) in diffusive water flux rate seen earlier at 7.5 ppt when [Ca2+] was not adjusted (Figure 7.6A). There were no significant differences in ṀO2 in response to any of the experimental solutions tested (31 ppt at 10 mM Ca2+, 31 ppt at 20 mM Ca2+, 7.5 ppt at 10 mM Ca2+ or 7.5 ppt at 20 mM Ca2+) (Figure 7.6B). This was similar to the constancy of ṀO2 observed earlier when this same salinity challenge was performed without adjustments of [Ca2+] (Figure 7.2A). Doubling [Ca2+] from 10 mM to 20 mM at control salinity 31 ppt appeared to decrease the mean ammonia excretion rate by 28%, though this difference was not significant (p= 0.0967). There were also no significant differences from control rates at 31 ppt with 10 mM Ca2+ in response to any of the other test solutions (Figure 7.6C). Ammonia excretion rates increased significantly by 70% in response to 7.5 ppt at 10 mM Ca2+ compared to 31 ppt at 20 mM Ca2+. Again, in comparison to 31 ppt at 20 mM Ca2+, ammonia excretion rates increased by 67% in response to 7.5 ppt at 20 mM Ca2+ (Figure 7.6C). Earlier, we observed no significant change in ammonia excretion rate when this same salinity challenge was performed without adjustments of [Ca2+] (Figure 7.3A). There were no significant differences in urea-N excretion rates in response to any of the solutions tested (Figure 7.4D), similar to the pattern observed earlier when this same salinity challenge was performed without adjustments of [Ca2+] (Figure 7.4A). There were no significant differences in NQ at control 31 ppt between Rock sole in the salinity series and Rock sole in the salinity-Ca2+ series (Appendix E Figure SE 1). There were 216 also no significant changes to NQ in the salinity-Ca2+ series (Figure 7.6E), similar to the result when the same salinity challenge was performed without adjustments of [Ca2+] (Figure 7.5A). 7.5 Discussion 7.5.1 Overview Our results demonstrate that both diffusive water flux and ammonia excretion rates are a function of salinity in Rock sole and Pacific sanddab and that in Rock sole, [Ca2+] also plays a role in these rates. With regard to our original hypotheses (see Section 7.2), we predicted that diffusive water flux rates would increase in low salinity and decrease in high salinity which was only partially confirmed. Diffusive water flux rates did increase in response to low salinity, but did not decrease in response to high salinity (Figure 7.1A, B). Nevertheless, the overall relationships between diffusive water flux and salinity were significant (Figure 7.1C, D). In contrast to our prediction, ṀO2 was not significantly altered by acute increases or decreases in salinity (Figure 7.2). However, as postulated, urea-N excretion rates also remained relatively unchanged during the salinity challenges (Figure 7.4). Our hypothesis that ammonia excretion rates would decrease in low salinity and increase in high salinity was falsified (Figure 7.3). The opposite occurred, and the NQ analysis (Figure 7.5) suggested a greater contribution of protein oxidation to constant ṀO2 as salinity decreased. Our prediction that changes in water [Ca2+] would play an important role in the responses to a salinity challenge in Rock sole was confirmed (Figure 7.6). Thus, maintaining or elevating water [Ca2+] prevented the increase in diffusive water flux associated with low salinity exposure. However, effects of water [Ca2+] versus salinity on ammonia excretion were less clear. Our final hypothesis that overall response patterns would 217 be similar in these two benthic species was confirmed. 7.5.2 Scaling exponents of diffusive water flux, ṀO2 and ammonia excretion rate The scaling exponents were lower for Rock sole than for Pacific sanddab for diffusive water flux, ṀO2 and ammonia excretion rate, though the reason for these consistent differences is unknown. For diffusive water flux rate, the scaling exponent for Rock sole (0.673) was slightly lower than previously published values, however, high scaling exponents, similar to that of Pacific sanddab (1.069), have been reported for several other species across salinities (Potts et al. 1967; Evans 1969, 1984; Onukwufor and Wood 2020a, b). This suggests that this trait may be shared across multiple species and salinities. The scaling exponents for ṀO2 (0.441, 0.862) were in reasonable agreement with previously reported values for other flatfish species (0.50-0.85) (Duthie 1982; Fonds et al. 1992; Onukwufor and Wood 2022) which are generally typical for teleost fish (Clarke and Johnston 1999). The scaling exponents were highest for ammonia excretion rate. For Rock sole, the exponent (0.747), was within range of those previously reported for other teleost fish (0.724-0.99) including, pirarucu (Pelster et al. 2020), yellowtail kingfish (Moran and Wells 2007) and Atlantic cod larvae (Finn et al. 2002) whereas for Pacific sanddab (1.401), the exponent was higher. The high scaling exponents for ammonia excretion could indicate that with increasing body mass there are different principles that govern ammonia excretion relative to those determining diffusive water flux and ṀO2. Overall, the scaling exponents presented in this study are in general accord with those previously reported in the literature. 218 7.5.3 Diffusive water flux and oxygen consumption rates can be independently regulated in response to a salinity challenge Several studies have demonstrated that acute exposure of seawater fish to low salinity increases diffusive water flux rate (Evans 1969; Motais et al. 1969; Onukwufor and Wood 2022) while other reports indicate that ṀO2 may also be elevated for several days after exposure to lower salinity before returning to original rates (Barton and Barton 1987; Dalla Via et al. 1998; Herrera et al. 2012). Recently, Onukwufor and Wood (2022) investigated the simultaneous changes in diffusive water flux rate and ṀO2 in two species of marine flatfish, Pacific sanddab and English sole. In agreement with our results in Pacific sanddab and Rock sole (Figure 7.1A, B), they found that diffusive water flux rates increased in response to low salinity. The ṀO2 in Pacific sanddab did not change with altered salinity in both the current study (Figure 7.2B) and Onukwufor and Wood (2022). We observed that ṀO2 was also unchanged in Rock sole (Figure 7.2A) while in English sole ṀO2 was elevated at low salinity (Onukwufor and Wood 2022). The difference in ṀO2 response among the three species may indicate that some species (i.e. Pacific sanddab and Rock sole) are better able to cope with lower, inshore salinities, possibly due to life history traits (see Section 7.2). It should be noted that our study explored a larger range of salinities (45 ppt, 31 ppt, 15.5 ppt and 7.5 ppt) compared to Onukwufor and Wood (2022) (31 ppt and 16 ppt). Therefore, acute changes in diffusive water flux rate can be uncoupled from acute changes in ṀO2. Our findings also suggest that diffusive water flux rate is uncoupled from the decreasing paracellular permeability in the tight junctions bordering ionocytes that occurs at low salinity (Marshall 2012), which may be the case for many euryhaline species including Pacific sanddab and Rock sole. The decrease in salinity from 31 ppt to 7.5 ppt reflects a large decrease 219 or even slight reversal in the trans-gill osmotic gradient which also appears to be independent from the observed increase in diffusive water flux rate (Figure 7.1A, B). Low salinity could rapidly elicit changes in exposure of gill ionocytes (Marshall and Nishioka 1980; Wood and Marshall 1994), possibly either through ionocyte proliferation or through changes in the morphological relationships between ionocytes and adjacent pavement cells (reviewed by Wood and Eom 2021). Lower expression of aquaporins in the gill has been correlated with lower diffusive water flux rate in seawater fish compared to freshwater fish and the protein abundance and mRNA expression of aquaporins increases upon transfer or acclimation to dilute waters (Lignot et al. 2002; Cutler et al. 2007; Tipsmark et al. 2010; Jung et al. 2012; Madsen et al. 2015; Breves et al. 2016; Ruhr et al. 2020). This upregulation of the aquaporin-mediated transcellular pathway may be independent of the osmorespiratory compromise associated with altered ṀO2 (Wood and Eom 2021). Our study investigated acute changes (within 1 h) in diffusive water flux rate so changes in the function of existing protein in the channels rather than changes in mRNA expression associated with new protein synthesis seems a more probable explanation. Nevertheless, Ruhr et al. (2020) reported that changes in AQP3 mRNA expression and cellular protein distribution were apparent within 3 h of an experimental treatment (acute hypoxia), so this topic should be investigated further in the future. Another possible explanation is the reduction in water [Ca2+] associated with a decrease in salinity, which is known to affect many aspects of gill permeability and will be discussed in Section 7.5.5. 7.5.4 Ammonia excretion rate is a function of salinity Our ammonia and urea excretion rate values at 31 ppt are in agreement with previously published values in English sole and related species (Walsh et al. 2001). In both Pacific sanddab 220 and Rock sole, the general trends in ammonia excretion (Figure 7.3C, D) were similar to those in diffusive water flux (Figure 7.1C, D), with rates increasing as salinity decreased. These trends were opposite to the greater ammonia excretion rates seen in seawater-acclimated rainbow trout (Wood and Nawata 2011), guppies (Zimmer et al. 2012) and killifish (Giacomin et al. 2020) all of which are euryhaline species. This disagreement may reflect species-specific differences, but a fundamental difference is that in the present study, the animals were acutely exposed to the salinity challenges, whereas in the cited studies, they were long-term acclimated to freshwater and seawater. Bucking (2017) suggested that the greater ammonia excretion at higher salinities in the latter studies was a reflection of greater ammonia production by protein catabolism. In our study, this explanation appears to explain the opposite trend because the NQ, which is an indicator of reliance on amino acids to fuel oxidative metabolism, as discussed subsequently, increased significantly in both species as salinity decreased (Figure 7.5), whereas ṀO2 did not change (Figure 7.2). Additionally, the lower pH at lower salinities (Appendix E Table SE 1) would favour ammonia excretion, but the lower ionic strength would also decrease both NH3 solubility and the pK of the ammonia equilibrium reaction, which would oppose ammonia excretion (Cameron and Heisler 1983, 2001; Bucking 2017). As predicted, urea-N excretion rates generally did not change in response to acute exposure to altered salinities with the exception of an increase at 15.5 ppt in Pacific sanddab (Figure 7.4B). The reason for this is unknown. In general urea-N excretion rates tend to make a larger contribution to total N-excretion rates in seawater fish than in freshwater fish (Wood 1993), though many exceptions exist (Altinok and Grizzle 2004). Branchial UT expression also tends to be higher in seawater-acclimated fish (Mistry et al. 2001; Wood and Nawata 2011), but this would be unlikely to change in the short time frame of our exposures. 221 The nitrogen quotient (NQ), the ratio of the total measured nitrogenous waste excretion (i.e. the sum of the ammonia-N excretion and the urea-N excretion) to the ṀO2, is used to estimate metabolic fuel use. Historically it has been believed that protein was the dominant fuel source for fish (Driedzic and Hochachka 1978; Van Waarde 1983; Jobling 1994), however, it is now generally accepted that the dominant fuel in most species is lipid (Brett and Zala 1975; Lauff and Wood 1996; Alsop and Wood 1997; Kieffer et al. 1998; Alsop et al. 1999), followed by carbohydrate (Lauff and Wood 1996). From the knowledge of the metabolism of fish protein, an NQ= 0.27 represents aerobic respiration being 100% fueled by protein (Van Den Thillart and Kesbeke 1978). In control salinity, 31 ppt, the NQ in Rock sole was 0.23 (Figure 7.6A) and 0.22 in Pacific sanddab (Figure 7.6B) indicating that 83-86% of aerobic respiration is fueled by protein. Although we did not measure the respiratory quotient, this appears to be contrary to the notion that lipids are the primary source of fuel but to our knowledge these are the first presented NQ values for wild-caught marine flatfish. In low salinity there was a significant increase in NQ in both species (Figure 7.6A, B), which suggests a shift to even greater protein oxidation. Fat snook showed an increase in reliance on lipids over amino acids when acclimated to saltwater (Rocha et al. 2005, 2007), which fits with this scenario. Notably, at 7.5 ppt, the NQ became significantly greater than 0.27 (one sample t-test) in Pacific sanddab (Figure 7.5B), which could indicate that protein metabolism had increased so much that non-steady state conditions prevailed. 7.5.5 [Ca2+] plays a role in diffusive water flux and ammonia excretion rates in Rock sole This series was performed to separate the effects of salinity from those of water [Ca2+]. There were marked differences in the trends of diffusive water flux and ammonia excretion rates 222 between the salinity series and the salinity-Ca2+ series. Note that in contrast to these effects of water [Ca2+] on diffusive water flux and ammonia excretion, there were no confounding effects on ṀO2 or urea excretion. There was no change in diffusive water flux rate in response to a decrease in salinity when [Ca2+] was maintained at the concentration of control salinity (i.e. 31 ppt with 10 mM Ca2+) or elevated to 20 mM (Figure 7.6A). This demonstrates that reduced [Ca2+] is the primary cause for the increases in diffusive water flux rates seen at low salinity (Figure 7.1). To our knowledge, this has never been shown before. The effects of water [Ca2+] versus salinity on ammonia excretion are less clear. In the salinity series there were no significant changes in ammonia excretion rate in Rock sole between 31 ppt and 7.5 ppt (Figure 7.3A), however in the salinity-Ca2+ series when Ca2+ was adjusted there were significant increases between 31 ppt at 20 mM Ca2+ and 7.5 ppt at both 10 mM Ca2+ and 20 mM Ca2+ (Figure 7.5C). The modulation of aquaporins between low permeability and high permeability in mammals, specifically in kidney and brain tissue, is dependent on both external [Ca2+] and pH. The effects of [Ca2+] and pH are separable and arise from processes on opposite sides of the cell membrane (Németh-Cahalan and Hall 2000; Németh-Cahalan et al. 2004; Valenti et al. 2005). Low external [Ca2+] increases permeability of aquaporins, a process which is dependent on functioning calmodulin that binds to the aquaporin (Németh-Cahalan and Hall 2000; Németh-Cahalan et al. 2004). As the calmodulin binding site is on the cytoplasmic side of the membrane, it has been suggested that both Ca2+ and calmodulin may alter the interactions of water with the cytoplasmic vestibule (Németh-Cahalan et al. 2004). It is not yet clear if Ca2+ similarly regulates branchial aquaporin pathways in fish. Our results are in accord with previous studies that measured the effect of water [Ca2+] on diffusive water flux, where an increase in ambient [Ca2+] 223 reduced the diffusive water permeability of the gills in fish (Oduleye 1975; Isaia and Masoni 1976) and crustaceans (Rasmussen and Bjerregaard 1995), though in contrast to the present study, these reports did not separate the effects of water [Ca2+] from those of salinity. Some aquaporin subtypes found in the gill (e.g. AQP3) may have the ability to transport ammonia and/or urea (Cutler et al. 2007; Tipsmark et al. 2010; Chen et al. 2010; Tingaud-Sequeira et al. 2010; Kolarevic et al. 2012; Ip et al. 2013) and could likewise be affected by ambient calcium concentrations. Overall, the relationship between salinity and [Ca2+] on diffusive water flux and ammonia excretion rates and the role of aquaporins should be further investigated at the levels of transcription, protein function and distribution, and whole animal physiology. 7.6 Concluding remarks As noted in the Introduction, these two flatfish species, as well as many others, exploit estuarine areas for feeding, reproduction, and nurseries, where they are routinely exposed to a range of reduced salinities near those tested here. As the ocean of the north-west Pacific coast becomes more dilute and “atmospheric river” run-off events become more extreme, they will likely encounter even more extreme variations. Sea-level rise will also cause the formation of more lagoons, where flatfish can be temporarily or permanently trapped, and where hypersaline conditions can develop rapidly though evaporation. Such dilution and concentration events may also change the ratio of [Ca2+] to total salinity (Connors and Kester 1974). To our knowledge the salinities we evaluated (45-7.5 ppt) represent the largest range tested for these physiological endpoints in marine flatfishes, and our study is one of the very few to examine these effects in adult flatfishes. Understanding how these fish alter gill function and metabolic fuel use in response to acute, environmentally relevant, salinity challenges can inform the mechanisms used 224 to thrive within their life cycle that requires them to enter waters of these salinities. It can also give an indication of their physiological ability to endure the extreme salinity changes that climate change will inevitably bring. 225 7.7 Chapter 7 – Tables Table 7.1 Allometric mass scaling for diffusive water flux, oxygen consumption, ammonia and urea-N excretion rates for Rock sole (Lepidopsetta bilineata) and Pacific sanddab (Citharichthys sordidus) Measurement Species Regression equation R2 p-values Proportionality constant Scaling coefficient Diffusive water flux rate* Rock sole Y= 0.673*X - 0.06229 0.3380 0.0182 - 0.06229 0.673 Diffusive water flux rate* Pacific sanddab Y= 1.069*X - 0.9391 0.9786 0.0002 - 0.9391 1.069 Oxygen consumption rate Rock sole Y= 0.441*X + 1.500 0.08543 0.2720 + 1.500 0.441 Oxygen consumption rate* Pacific sanddab Y= 0.862*X + 0.6207 0.7064 0.00361 + 0.6207 0.862 Ammonia excretion rate* Rock sole Y= 0.747*X + 0.8316 0.4446 0.0906 + 0.8316 0.747 Ammonia excretion rate* Pacific sanddab Y= 1.401*X – 1.485 0.6121 0.066 – 1.485 1.401 Urea-N excretion rate Rock sole Y= 0.718*X – 0.9624 0.112 0.4631 – 0.9624 0.718 Urea-N excretion rate Pacific sanddab Y= 0.470*X – 0.3002 0.0404 0.7457 – 0.3002 0.470 Y = log rate and X = log body mass p<0.10 (i.e. one-tailed) was used for statistical significance *indicates parameters for which allometric scaling was applied 226 7.8 Chapter 7 – Figures Figure 7.1. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on diffusive water flux rate (ml kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), N=7-8 and (B) Pacific sanddab (Citharichthys sordidus), N=6-7. Data (means ± SEM) not sharing the same letters within a species are significantly different (p<0.05) (analysis of variance with Tukey’s test). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and diffusive water flux rate (ml kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), N=7-8 and (D) Pacific sanddab (Citharichthys sordidus), N=6-7. 227 Figure 7.2 The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on oxygen consumption rate (ṀO2) (µmol kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), N=7-8 and (B) Pacific sanddab (Citharichthys sordidus), N=6-7. Data (means ± SEM) are not significantly different (p<0.05) (analysis of variance with Tukey’s test). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and oxygen consumption rate (ṀO2) (µmol kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), N=7-8 and (D) Pacific sanddab (Citharichthys sordidus), N=6-7. 228 Figure 7.3. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on ammonia-N excretion rate (µmol kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), N=6-8 and (B) Pacific sanddab (Citharichthys sordidus), N=6. Data (means ± SEM), not sharing the same letters within a species are significantly different (p<0.05) (analysis of variance with Tukey’s test (A) or Brown-Forsythe and Welch analysis of variance with Dunnett’s t-test (B)). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and ammonia-N excretion rate (µmol kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), N=6-8 and (D) Pacific sanddab (Citharichthys sordidus), N=6. 229 Figure 7.4. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on urea-N excretion rate (µmol kg-1 h-1) in (A) Rock sole (Lepidopsetta bilineata), N=6-7 and (B) Pacific sanddab (Citharichthys sordidus), N=5-7. Data (means ± SEM), not sharing the same letters within a species are significantly different (p<0.05) (analysis of variance with Tukey’s test). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and urea-N excretion rate (µmol kg-1 h-1) in (C) Rock sole (Lepidopsetta bilineata), N=6-7 and (D) Pacific sanddab (Citharichthys sordidus), N=5-7. 230 Figure 7.5. The effect of salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) on nitrogen quotient (NQ= ṀN/ ṀO2) on (A) Rock sole (Lepidopsetta bilineata) N=6-7, (B) Pacific sanddab (Citharichthys sordidus), N=5-6. Data (means ± SEM), not sharing the same letters within a species are significantly different (p<0.05) (analysis of variance with Tukey’s test). The relationship between salinity (7.5 ppt, 15.5 ppt, 31 ppt, 45 ppt) and nitrogen quotient (C) Rock sole (Lepidopsetta bilineata), N=6-7 and (D) Pacific sanddab (Citharichthys sordidus), N=5-7. 231 Figure 7.6. The effect of [Ca2+] and salinity (31 ppt and 7.5 ppt) in the salinity-Ca2+ series on Rock sole (Lepidopsetta bilineata) on (A) Diffusive water flux rate (ml kg-1 h-1), N= 7-8, (B) ṀO2 (µmol kg-1 h-1), N=7-9, (C) ammonia excretion rate (µmol kg-1 h-1), N=6-8, (D) urea-N excretion rate (µmol kg-1 h-1), N=6-8, and (E) nitrogen quotient (NQ), N= 6-8. Data (means ± SEM), not sharing the same letters are significantly different (p<0.05) (analysis of variance with Tukey’s test). 232 Chapter 8: The effects of dissolved organic carbon and model compounds (DOC analogues) on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and gill transepithelial potential in Pacific sanddab (Citharichthys sordidus) at two salinities. 8.1 Summary Many flatfish species are partially euryhaline, such as the Pacific sanddab which spawn and feed in highly dynamic estuaries ranging from seawater to near freshwater. With the rapid increase in saltwater invasion of freshwater habitats, it is very likely that in these estuaries, flatfish will be exposed to increasing levels of dissolved organic carbon (DOC) of freshwater origin at a range of salinities. As salinity fluctuations often coincide with changes in DOC concentration, two natural freshwater DOCs [Luther Marsh (LM, allochthonous) and Lake Ontario (LO, autochthonous)] were investigated at salinities of 30 and 7.5 ppt. Optical characterization of the two natural DOC sources indicated salinity-dependent differences in their physicochemistry. LO and LM DOCs, as well as three model compounds [tannic acid (TA), sodium dodecyl sulfate (SDS) and bovine serum albumin (BSA)] representing key chemical moieties of DOC, were used to evaluate physiological effects on sanddabs. In the absence of added DOC, an acute decrease in salinity resulted in an increase in diffusive water flux (a proxy for transcellular water permeability), ammonia excretion and a change in TEP from positive (inside) to negative (inside). The effects of DOC (10 mg C L-1) were salinity-dependent and source-dependent, with generally more pronounced effects at 30 than 7.5 ppt, and greater potency of LM relative to LO. Both LM DOC and SDS increased diffusive water flux at 30 ppt but only SDS had an effect at 7.5 ppt. TA decreased ammonia excretion at 7.5 ppt. LO DOC 233 decreased urea-N excretion at both salinities whereas the stimulatory effect of BSA occurred only at 30 ppt. Likewise, the effects of LM DOC and BSA to reduce TEP were present at 30 ppt but not 7.5 ppt. None of the treatments affected oxygen consumption rates. Our results demonstrate that DOCs and salinity interact to alter key physiological processes in marine flatfish, reflecting changes in both gill function and the physicochemistry of DOCs between 30 and 7.5 ppt. 8.2 Introduction There is now abundant evidence that dissolved organic carbon (DOC) affects gill function in freshwater organisms, particularly fish. The effects are usually beneficial to the osmoregulation of the organism (Gonzalez et al. 2002; Wood et al. 2003, 2011; Matsuo et al. 2004; Al-Reasi et al. 2016), although exceptions exist (Steinberg et al. 2003, 2006). The mechanisms remain largely unknown, but it is clear that DOC affects unidirectional and net ion flux rates, ammonia and urea-N excretion rates, and transepithelial potential (TEP) (Gonzalez et al. 2002; Wood et al. 2003; Matsuo et al. 2004; Galvez et al. 2008; Al-Reasi et al. 2013b, 2016; Duarte et al. 2016). DOCs may also influence the electrical properties of the gills, hyperpolarizing the inside-negative TEP (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019). The TEP is a diffusion potential in freshwater fish (Potts 1984). However, as yet, there appears to be no information on whether DOC can affect diffusive water flux across the gills, the “water aspect” of osmoregulation. Some DOCs are more effective at exerting physiological effects than others (Al-Reasi et al. 2011, 2013a; Sadauskas‐Henrique et al. 2019). It has been proposed, but not yet proven, that the chemical properties or functional moieties of DOC that are important in the protection 234 against metal toxicity are similar to those that exert physiological effects on the gills (Al-Reasi et al. 2011, 2013a). Optical indices based on absorbance, fluorescence, and parallel factor analysis (PARAFAC) have been used to describe molecular variability of DOC (Al-Reasi et al. 2011; Wood et al. 2011). Indices that have shown promise in predicting protection by DOCs against metals are: (i) the specific absorbance coefficient 340 (SAC340) (Curtis and Schindler 1997a) with higher values representing greater aromaticity; (ii) the absorbance ratios at 254 nm to 365 nm (molecular weight index, MWI), with lower values indicating a greater molecular weight (Dahlén et al. 1999), (iii) the fluorescence index (FI) which is the ratio of fluorescence intensity450nm/fluorescence intensity500 nm at an excitation wavelength of 370 nm, with higher values indicating an autochthonous origin, and lower values, an allochthonous origin (McKnight et al. 2001); and (iv) PARAFAC, a computational model based on the fluorescence excitation‐emission fingerprint of a DOC sample that uses a multivariate statistical approach to yield a relative fractionation into user‐defined components such as % humic acid-like, % fulvic-acid-like, and %protein-like composition (Kroonenberg and Heiser 1998; Stedmon and Bro 2008). Generally, aromatic rich, high molecular weight allochthonous DOCs with high % humic acid‐ like fluorescence are highly protective against metal toxicity (Al-Reasi et al. 2011). Based on studies to date, limited entirely to marine invertebrates, it is unclear whether the same optical indices predict the protective abilities of DOCs in seawater (Nadella et al. 2009, 2013; DePalma et al. 2011; Cooper et al. 2014; Tait et al. 2016; Blewett et al. 2016, 2018, 2021; Nogueira et al. 2017, 2018). Nevertheless, these studies confirm that DOCs can protect against metal toxicity in seawater although the degree of protection varies among DOC sources, salinity, and aquatic species. It remains to be seen whether DOCs that protect best against metal toxicity 235 also have the greatest physiological effects on marine organisms, and specifically whether such effects occur in marine fish. With this background in mind, we evaluated the effects of two natural freshwater DOCs and three model compounds (reflective of specific properties of DOC) on gill function in the Pacific sanddab (Citharichthys sordidus). The sanddab is euryhaline, like many other flatfish (Evans 1984; Rogers et al. 1984; Minami and Tanaka 1992; Gibson 1994; Burke et al. 1995). They spawn, metamorphose, and feed in highly dynamic estuaries with salinity ranging from full seawater (30 ppt) to freshwater (0 ppt), depending on the seasonal river discharge (Thornburgh 1980; Durkin et al. 1981; Bottom et al. 1984; Armor and Herrgesell 1985; Rackowski and Pikitch 1989; Rooper et al. 2006; Sobocinski et al. 2018). Previous studies have established that gill function in Citharichthys sordidus is indeed very sensitive to changes in salinity, with marked effects on both ammonia excretion and diffusive water flux, a proxy for gill transcellular water permeability (Onukwufor and Wood 2022; Morris and Wood 2023, see Chapter 7). In these estuaries on the Pacific coast of North America, sanddab will also be exposed to freshwater DOCs of allochthonous and/or autochthonous origin (McNicol et al. 2023), such that interactive effects with salinity may occur. The two natural DOCs chosen for investigation were freshly isolated from two sources. These sources have been well studied in freshwater fish, and their physicochemical properties have been well characterized (Al-Reasi et al. 2012, 2013a, b, 2016; Duarte et al. 2018; Morris et al. 2024b, see Chapter 3), but they differ greatly. Lake Ontario (LO) DOC is an autochthonous DOC that is less aromatic, and smaller in molecular size, with lower % humic acid-like content when compared to Luther Marsh (LM) DOC which is allochthonous, highly aromatic, with a larger molecular weight and higher % humic content. As such, LM DOC appears to have greater 236 supportive effects on ionoregulation in freshwater fish than does LO DOC (Galvez et al. 2008; Wood et al. 2011; Al-Reasi et al. 2013; Morris et al. 2024c, see Chapter 4) The choice of model compounds used in the present study was based on the criteria that they structurally resemble and functionally behave like certain components of natural DOCs. Tannic acid (TA) has been a widely used as a model allochthonous carbon compound because of its high aromatic content and similarity to humic substances (Moreno-Castilla et al. 2004; Lin and Baoshan 2008; Campinas et al. 2013). Sodium dodecyl sulfate (SDS), often called sodium lauryl sulfate, is a commonly used anionic surfactant (Holmberg et al. 2007), and was chosen to mimic the amphiphilic properties of DOCs with hydrophilic and hydrophobic moieties (von Wandruszka 2000; Young and von Wandruszka 2001). Autochthonous DOCs may be richer in amino acids such as tyrosine (Thurman 1985). Therefore, bovine serum albumin (BSA) was chosen to represent tyrosine-rich proteinaceous material (Heidari et al. 2018). We chose several endpoints known to be affected by DOCs in freshwater organisms, including ammonia and urea-N excretion, and TEP. Notably, TEP has a rather different origin in marine fish, with both diffusive and electrogenic components of ion fluxes, whereas in freshwater fish, there is no electrogenic component (Potts 1984). We did not study ion flux rates themselves, because these are extremely challenging to measure due to the high background ion levels in seawater which would necessitate use of very large amounts of expensive radioisotopes, and the available techniques lack precision to detect small differences (Giacomin et al. 2020). Instead, we evaluated diffusive water flux rate, where the technology is well established. Previous studies have shown it to be sensitive to salinity, hypoxia, and temperature in marine flatfish (Onukwufor and Wood 2022; Morris and Wood 2023, see Chapter 7). We chose to study two different salinities because rapidly reduced salinity is an environmentally realistic osmotic 237 challenge when flatfish first enter dilute estuaries, where effects of DOC may become more apparent. Additionally, the effects of acute low salinity exposure in the absence of added DOC have previously been documented in this species (Onukwufor and Wood 2020a; Morris and Wood 2023, see Chapter 7) for comparison. As in these previous studies, routine oxygen consumption rate (ṀO2) was also monitored to check whether observed responses were secondary effects of changes in aerobic metabolism. Our specific hypotheses were: (i) as ionic strength and pH changes the molecular conformation (i.e. spatial arrangement of the molecule) of the DOC, the effects of DOC would be greater at lower salinity; (ii) as LM DOC is more aromatic and larger in size than LO DOC, the effects of LM DOC would be greater than those of LO DOC; (iii) as the origin of TEP is different at the two tested salinities, the TEP responses to DOC would differ between salinities; and (iv) as the model compounds shared specific key chemical structures with the natural DOCs, the effects of the model compounds would help illuminate which specific properties of the natural DOCs were contributing to the observed responses. 8.3 Methods 8.3.1 Animals Pacific sanddabs (Citharichthys sordidus) (N= 90, 0.389 ± 0.0129 kg) were caught in July, 2022, by angling off Brady’s beach, near the Bamfield Marine Sciences Center (BMSC), Bamfield, BC, Canada, under Fisheries and Oceans Canada collection permit XR 119-2022. At BMSC, flatfish were held in aerated fiber glass tanks supplied with flowing seawater (30 ppt, 12 ºC) and a layer of sand at the bottom into which the fish buried during the day. Fish were allowed to rest for at least 72 h after capture. The fish were fed small chunks of salmon every 238 second day and were fasted for at least 72 h before experiments commenced. Seawater was pumped from the nearby ocean to both BMSC holding tanks and the experimental set-up. Experimental fish were transferred to individual aerated chambers slightly longer and wider (35 cm X 25 cm) than each individual fish. The chambers were supplied with running seawater (30 ppt), and rested in a water bath to maintain a control temperature of 12 °C when seawater flow was stopped during experiments. Sand was absent in the experimental vessels, as a previous study showed no significant differences in diffusive water flux or oxygen consumption rates in the presence and absence of sand (Onukwufor and Wood 2022). All procedures used in this investigation were in accordance with the Canadian Council on Animal Care guidelines and were approved by the University of British Columbia Animal Care Committee (AUP A18-0271) and the BMSC Animal Care Committee (RS-22-08). 8.3.2 Experimental series Six experimental series were carried out. • Series 1 measured diffusive water flux rates, oxygen consumption rates, ammonia-N and urea-N excretion rates and the nitrogen quotient in response to two sources of natural DOC (LM and LO) at 30 ppt, together with their own control group at 30 ppt. • Series 2 evaluated the effect of these same natural DOCs on the same endpoints at 7.5 ppt, together with their own control group at 7.5 ppt. • Series 3 tested three model compounds (TA, BSA and SDS) at 30 ppt on diffusive water flux rates, oxygen consumption rates, ammonia-N and urea-N excretion rates and the nitrogen quotient, together with their own control group at 30 ppt. 239 • Series 4 tested these same three model compounds at 7.5 ppt on the same endpoints, together with their own control group at 7.5 ppt. • Series 5 measured transepithelial potential (TEP) in response to both natural DOCs and model compounds at 30 ppt, using each fish as its own control. • Series 6 measured TEP in response to both natural DOCs and model compounds at 7.5 ppt, again using each fish as its own control. 8.3.3 Experimental solutions Two natural sources of DOCs were collected, from Luther Marsh (LM, 43°57′N, 80°26′W) and Lake Ontario (LO, 44°14'N, 76°28'W) in Ontario, Canada. For both locations, DOC concentrates were obtained by a portable reverse osmosis unit which concentrated organic matter gradually (Sun et al. 1995). Following reverse osmosis, samples were treated with a cation exchange resin (Amberlite IR-118 (H), Sigma Aldrich, St. Louis, MO, USA) to remove cations that may have accumulated during reverse-osmosis. The concentrate was then filtered using hydrophilic, polyethersulfone polymer membrane filters with a 0.45-m pore size (MS® PES Membrane Solutions, Auburn, WA, USA), and were stored and transported in sealed 1-L bottles at 4ºC until use. Salinity was measured using a WTW Portable Conductivity Meter (ProfiLine Cond3310; Xylem Analytics, Welheim, Germany). Solutions with a salinity of 7.5 ppt were made by diluting seawater with BMSC freshwater (Na+ 0.3, Cl- 0.2, K+ 0.005, Ca2+ 0.1, Mg2+ 0.05 mM) until the desired salinity was reached. All experimental solutions were maintained at 12 °C. Natural DOCs (LO and LM) and model compounds (TA, BSA, and SDS, Sigma-Aldrich, St. Louis, Missouri, USA) were added to and dissolved in the appropriate salinity to equal nominally 240 10 mg C L-1. Approximately, 10 mg C L-1 has been recorded as a global average DOC concentration within freshwater streams, river tributaries and main stems (Liu and Wang 2022) and is within range (3.7-12.0 mg C L-1) of coastal waters with DOC input via rivers (Maxey et al. 2020). DOC concentrations in the exposure waters were measured using a Shimadzu total carbon and nitrogen analyzer (TOC-L, Shimadzu, Mandel Scientific, Guelph, Canada) (Table 8.1). All DOC levels in samples were well above the instrument detection limit of approximately 0.1 mg C L-1. The measured concentrations of the model compounds differ somewhat from the nominal concentrations, likely because of the formation of aggregates caused by interaction with the natural seawater. We believe that the presence and concentration of the model compounds is sufficient for our mechanistic comparison with the natural DOCs. Importantly, the nominal and measured concentrations of the natural DOCs are quite close. The pH range among the control and experimental solutions was typically less than 1.0 pH unit (Table 8.1). The recorded pHs were those that resulted naturally from mixing DOCs from the different sources with the two salinities, making the pH values environmentally relevant. Adjusting the pHs could have introduced another confounding factor. Solutions were allowed to equilibrate overnight, and exposures occurred the following morning. Water samples were collected directly after concluding the experiment and were stored for a short time in the dark at 4°C prior to characterization. 8.3.4 Optical characterization of experimental solutions An Aqualog (HORIBA Scientific, Kyoto, Japan) was used to measure the fluorescence and absorbance of each of the experimental solutions. This instrument measures excitation and 241 emission simultaneously, and provides the required excitation emission matrices such that parallel factor analysis (PARAFAC) of fluorophores (Stedmon and Markager 2005; Stedmon and Bro 2008) can be conducted. All characterizations were done in the actual exposure solutions at the appropriate salinity (i.e. 30 ppt or 7.5 ppt). Specific absorbance coefficient at 340nm (SAC340), an index of aromatic composition of DOCs, was estimated based on the method described by Curtis and Schindler (1997) by examining the absorbance of samples at a wavelength of 340 nm using a 1-cm quartz cuvette (Helma Canada Ltd., Concord, ON, Canada) in the Aqualog instrument. The instrument was “blanked” using ultrapure water. Briefly, SAC340 (cm2 mg-1) was calculated as: SAC340 =(2.303 × Abs340)/pathlength [DOC]/1000 (Equation 8.1) Fluorescence index (FI) is an indicator of the DOC source with high values indicating an autochthonous origin, and low values, an allochthonous origin (McKnight et al. 2001). FI was calculated by previously described methods (McKnight et al. 2001): FI = Em450Em500 (Equation 8.2) 242 The excitation intensity at 370 nm, and Em450 and 500 refer to emission intensities at 450 nm and 500 nm. Absorbance measurements at 254 and 365 nm may be used as indirect indicators of relative molecular weight of DOC (Dahlén et al. 1999). Note that this molecular weight index (MWI) is an inverse ratio, with high values indicating lower molecular weight, and low values indicating a higher molecular weight: MWI =Abs254Abs365 (Equation 8.3) PARAFAC modelling was conducted in MATLAB (MathWorks, Natick, MA, USA). PARAFAC is a computational model that uses a multivariate statistical approach to define the components and quality of a sample based on the fluorescence excitation-emission matrix and known predetermined fluorophores (Stedmon and Markager 2005; Stedmon and Bro 2008). In the present study, our categories were humic acid-like, fulvic acid-like, and protein-like fluorophores. As some of the model compounds do not have these key functional moieties (therefore lack fluorescence in the appropriate range), they were excluded from the PARAFAC analysis. 243 8.3.5 Diffusive water flux In Series 1, 2, 3, and 4, the procedure outlined by Onukwufor and Wood (2020) was used for measuring diffusive water flux rates. Briefly, the loading period began 12 h before the experiment started. Fish (6 per experiment) were set in individual aerated vessels maintained at 12 oC and each were loaded with 3H2O radioactivity by exposure to 30 µCi of 3H2O (PerkinElmer, Woodbridge, ON, Canada) in the control solution (2-4 L), which was either 30 ppt (Series 1 and 3) or 7.5 ppt (Series 2 and 4) with no added DOC. Therefore. fish exposed to 7.5 ppt were not acclimated to this salinity, but rather had been acclimated to 30 ppt. Their exposure to 7.5 ppt started immediately at the onset of the 12-h loading period with 3H2O and continued during the approximately 4-h experimental period. This approach was adopted as our goal was to evaluate how fish would respond acutely when entering lower salinity water, rather than when resident in low salinity water. After the 12-h loading period, each individual fish and chamber were quickly rinsed with clean seawater with care to minimize disturbance to the fish. The fish was immediately placed back into the aerated, temperature-controlled chamber containing 2-4 L (exact volume recorded) of the appropriate control or experimental solution without 3H2O. Each fish was provided with enough solution so that they were covered by several cm. The experimental solutions were either 30 ppt or 7.5 ppt supplemented with natural DOCs (LO or LM) or model compounds (TA, BSA, or SDS) at nominally 10 mg C L-1. A 4-ml aliquot of the control or experimental solution was taken at time 0, marking the start of the washout period, and every 5 min thereafter for 60 min. A final sample was taken at 12 h when the external and internal 3H2O pools were once again in equilibrium. The 12-h sample 244 was used to calculate the original amount of radioactivity in the fish and the 0-60 min samples were used to determine the diffusive water flux rates. 8.3.6 Oxygen consumption rate measurements Directly following the end of the 60 min diffusive water flux experiment, oxygen consumption rates (ṀO2) were measured as per Onukwufor and Wood (2022), on the same fish. At the start of the measurements PO2 was >80%. Aeration was suspended, and the vessels were sealed with Styrofoam covers cut to the exact size of the chambers with a sealable hole specifically designed to fit the diameter of the oxygen probe (YSI 55 Handheld polarographic O2 meter, Yellow Springs, OH, USA). Preliminary experiments demonstrated that the Styrofoam covers adequately blocked the entry of O2. The decrease in PO2 was measured every 5 min until it reached 50% saturation, a PO2 that is well above the critical PO2 where ṀO2 becomes dependent on PO2 in this species (O.E. Johannsson and C.M. Wood, unpublished results). This period ranged from 10-60 min within the various treatments. 8.3.7 Ammonia and urea-N excretion rate measurements Immediately following the end of the ṀO2 measurements, aeration was re-established and 4-ml water samples were taken from each vessel representing time 0, and additional samples were drawn every 30 min for 2 h thereafter. Preliminary experiments demonstrated that this time interval was adequate to detect reliable changes in ammonia and urea-N levels in the water. Concentrations of total ammonia (salicylate hypochlorite assay, Verdouw et al. 1978) and total urea-N (diacetyl monoxime assay, Rahmatullah and Boyde 1980) in water samples were measured colorimetrically using a SpectraMax 190 microplate reader (Molecular Devices, San 245 Jose, CA, USA), with standards made up in the appropriate salinities. Based on a preliminary test, none of the experimental solutions with added DOC imparted significant colour to the water. Note that while we did not directly measure whether any ammonia was added to the experimental waters by the addition of DOC extracts, our assays of ammonia concentrations in the start water samples of our ammonia excretion trials indicated that it was negligible. It would not have contributed to our ammonia excretion measurements. 8.3.8 Transepithelial potential measurements In Series 5 and 6, transepithelial potential measurements (TEP) were conducted according to the procedure outlined by Wood et al. (2020). TEP was measured using intraperitoneal catheters which earlier studies have shown to yield identical data to those generated using more invasive vascular catheters (Wood and Grosell 2008). Fish were fasted for at least 72 h prior to surgery and anesthetized using 0.5 mg L-1 of tricaine methane sulfate (MS222) neutralized with NaOH. To avoid hypoxic stress, gills were irrigated with a continuous flow of anaesthetic water (Po and Wood 2021). A 10-cm section of polyethylene PE50 catheter (Clay Adams™, Becton Dickinson, Franklin Lakes, NJ, USA) filled with Cortland saline (Wolf 1963), set to pH ~7.7 and adjusted with an additional 20 mM NaCl to mimic the composition of the marine fish plasma, was inserted into the peritoneal cavity as described by Wood and Grosell (2008). The catheter was anchored using a 3-cm PE160 sleeve secured with cyanoacrylate glue and silk suture. The catheter was sealed with a stainless-steel pin until experiments were conducted. After overnight recovery in separate aerated enclosures supplied with DOC-free water (12ºC) at either 30 ppt (Series 5) or 7.5 ppt (Series 6) as appropriate, control TEP measurements were made. TEP determinations employed 3 M KCl agar bridges connected via 246 Ag/AgCl electrodes (World Precision Instruments, Sarasota, FL, USA) to a high impedance voltmeter (Radiometer pHm 82, Copenhagen, Denmark). The reference bridge was placed into the experimental solution of the measurement chamber and the measurement bridge was connected to the indwelling catheter. For every solution, three measurements were made over a 2-min period (with correction for the junction potential) and averaged. The background TEP was similarly measured in control solution (30 ppt or 7.5 ppt) in each animal and served as a baseline TEP for comparison with the TEP measured in the experimental solution. A paired statistical design was used, where each fish was its own control. Each individual fish was exposed to the experimental solution (DOC or model compounds) at the appropriate salinity for 2 min before the measurements commenced and the three measurements described above were completed in about 2 min. The total time during which each fish was exposed to the experimental solution (including the time to take the measurements) was less than 5 min. TEP was expressed in the traditional manner as the inside voltage relative to the outside water as 0 mV. Directly following the experiments fish were euthanized by an overdose of MS222. 8.3.9 Analytical procedures and calculations As described by Onukwufor and Wood (2018), the concentration of 3H2O was measured by adding 8 ml of Optiphase 3 fluor (Perkin-Elmer, Wellesley, MA, USA) to the 4-ml water sample, shaking vigorously and loading it into a scintillation counter (LS6500, Beckman Coulter, Fullerton, CA, USA). Preliminary tests showed that quenching and chemiluminescence were negligible. The rate constant of 3H2O efflux (k) was calculated employing the protocol outlined by Onukwufor and Wood (2020). Briefly, using the final 12-h wash-out sample, the initial amount of 3H2O in the fish was determined. It was then possible to calculate the amount of 3H2O 247 left in the fish at each sampling time from 0 to 60 min based on the measured amounts that appeared in the external solution at each time point and the known volume of the system. Next, the natural logarithm of the total 3H2O in the fish at each sample time was regressed against time in minutes on a linear scale. The fractional rate constant k for water turnover was the slope of this line. Multiplying the rate constant k by 60 yielded the fraction of the body water pool turned over per hour. Generally, the total exchangeable water pool of a fish is 800 ml kg-1 (Isaia 1984; Olson 1992; Holmes and Donaldson 1996). To calculate the diffusive water flux rate in ml fish-1 h-1, the weight of the fish in kg was multiplied by 800 ml kg-1 and then by the fraction of the body water pool turned over per hour. ṀO2 calculations followed the procedure of Onukwufor and Wood (2020). Briefly, using salinity-dependent and temperature-dependent solubility coefficients (Boutilier et al. 1984), PO2 values were converted to O2 concentrations (µmol L-1). The rate of decline of O2 concentration was then multiplied by the known volume of the experimental vessel, and divided by time (h), to give ṀO2 in µmol fish-1 h-1. Ammonia-N and urea-N excretion rates (note: 1N per ammonia molecule, 2N per urea molecule) were calculated as per Wood (1992) whereby the change in concentration in the water (µmol-N L-1) was divided by the time of the flux period (h), and multiplied by the volume of the experimental container (L) to give the excretion rate as µmol-N fish-1 h-1. The four 30-min rates were averaged to yield a single value for each fish. Scaling coefficients for diffusive water flux, ṀO2, ammonia excretion and urea-N excretion rates, were calculated using the control data for fish within each salinity group (i.e. 30 ppt or 7.5 ppt) in parallel to the approach used by Onukwufor and Wood (2020) and Morris and Wood (2023, see Chapter 7) in Pacific sanddab. The size ranges for each experimental group 248 were: 30 ppt natural DOCs 0.135 - 0.495 kg, 30 ppt model compounds 0.130 - 0.610 kg, 7.5 ppt natural DOCs 0.135 - 0.525 kg and 7.5 ppt model compounds 0.130 - 0.605 kg. The logarithms of the individual rates (expressed as units per fish per h) were plotted against the logarithms of the individual fish weights (Table 8.2, Table 8.3). For each statistically significant result (Table 8.2, Table 8.3), an allometric mass scaling coefficient was obtained by using the equation Y=aMb where Y is the rate of interest (units fish-1 h-1), M is the body weight (kg), and b is the scaling coefficient. When the power equation is transformed into a linear function, a, representing the proportionality constant, a is the y-intercept. The allometric mass scaling coefficient was used to adjust the measured rates of each individual fish to that of a standard 0.25 kg of flatfish, and then divided by 0.25 kg to yield rates expressed per kg per h. In cases where no scaling coefficient was applied because the regressions were not significant (see Results), each individual rate expressed per fish per h was divided by weight in kg, to yield rates expressed per kg per h. The nitrogen quotient (NQ) is the ratio of the total measured nitrogenous waste excretion (ṀN) (the sum of the ammonia-N excretion and the urea-N excretion) to the ṀO2. Therefore, the NQ was calculated as NQ= (ṀN/ṀO2) for each individual fish at the control salinity and in the experimental solutions. The unscaled rates were used for each measurement in the calculations. By metabolic theory (Van Den Thillart and Kesbeke 1978), an NQ of 0.27 means that 100% of aerobic metabolism is fueled by protein. 8.3.10 Statistical analyses Data have been expressed as mean ± standard error (SEM; n) where n represents the number of animals sampled. All data passed normality tests (Shapiro-Wilk). In Series 1, 2, 3, and 4, data that also passed the homogeneity of variance tests were analysed using one-way analysis 249 of variance (ANOVA) with Tukey’s post hoc test (multiple comparisons). If data did not pass the Brown-Forsythe test for homogeneity of variances, data were analysed using the Brown-Forsythe and Welch ANOVA test with Dunnett’s T3 multiple comparison test. Differences in mean control rates at 30 ppt and 7.5 ppt for diffusive water flux, ṀO2, ammonia and urea-N excretion were assessed by unpaired Student’s t-tests. For TEP measurements, each fish was used as its own control, so experimental effects relative to the control measurements were evaluated by paired Student’s t-tests. Differences in mean control TEPs at 30 ppt and 7.5 ppt were assessed by unpaired Student’s t-tests. All statistical analyses and data plots were done using GraphPad™ Prism 7 (GraphPad Software, San Diego, CA, USA). A significance level of p<0.05 (i.e. two-tailed) was used throughout except for allometric scaling coefficients where p < 0.10 was employed to avoid a Type 2 error. We adopted this approach based on our prior prediction that positive allometric scaling effects would occur for the parameters of interest, based on earlier findings with this and other species, and therefore a one-tailed rather than a two-tailed approach was used. In contrast, for physiological effects of the various experimental treatments, we made no prior prediction of the directionality of the effects, and therefore a two-tailed approach (i.e. lower alpha value) was employed. 8.4 Results 8.4.1 Measured DOC concentrations and the optical characterization of natural DOCs and model compounds at two salinities Measured DOC concentrations approximated the nominal value of 10 mg C L-1, ranging from about 8.3 to 12 mg C L-1, relative to natural background levels of ~2 mg C L-1 in the 30 ppt and 250 7.5 ppt seawater solutions (Table 8.1). However, the measured concentrations of model compounds ranged from about 4.4 to 15.8 mg C L-1 (Table 8.1). The three optical characterization methods used here were designed to characterize natural dissolved organic matter consisting of humic acid-like, fulvic acid-like, and protein-like components. At both salinities the general trends were for higher FI (i.e more autochthonous, less allochthonous origin), lower SAC340 (i.e. lower aromaticity), and higher MWI (i.e. lower mean molecular weight) in LO than in LM samples, though the effects of salinity were not consistent between the two sources. Consistent with our earlier study (Morris et al. 2024b, see Chapter 3) where PARAFAC was performed on these same DOC sources in freshwater, when they were tested in 30 ppt seawater (Figure 8.1), fulvic acid-like components dominated in both (69.8% for LM DOC and 75.3 % for LO DOC), humic-acid like components were intermediate (30.1% for LM DOC and 17.9 % for LO DOC), and protein -like components were low (0% for LM DOC and 6.8 % for LO DOC) (Figure 8.1E). LM DOC exhibited a moderately higher humic acid-like, lower fulvic acid-like, and lower protein-like composition than LO DOC. For both sources, the effects of lower salinity (7.5 ppt) were minor decreases in the % humic-like and the % fulvic-like components, and corresponding increases in the % protein-like components. Most notably, for LM DOC, the protein-like component increased from 0% at 30 ppt to 5.6% at 7.5 ppt. Although the model compounds were also examined using SAC340, FI and MWI (Table 8.1), interpreting them using these methods alone may not be appropriate in some cases (e.g. negative absorbances). These tools appear to be better suited to natural DOCs. 251 8.4.2 Allometric scaling coefficients The allometric regressions in the control fish were significant at p < 0.10 for diffusive water flux and ammonia excretion rates at both salinities in Series 1, 2, 3, and 4, and for urea-N excretion at 7.5 ppt only in Series 2 and 4, as indicated in Table 8.2. Therefore, allometric scaling was applied in subsequent analyses for those groups. Allometric scaling was not applied for ṀO2 excretion in any series, or for urea-N excretion rate in Series 1 and 3. 8.4.3 Control values as a function of salinity At 30 ppt, the control values were not significantly different between Series 1 (DOC studies) and Series 3 (model compound studies) (Appendix F Similarly, at 7.5 ppt, there were no significant differences between the control values between Series 2 (DOC studies) and Series 4 (model compound studies). When the flux data for the two control groups at each salinity were combined and compared, (Series 1 and 3 at 30 ppt versus Series 2 and 4 at 7.5 ppt), it was clear that exposure to the lower salinity had a marked effect on the control rates (Figure 8.2) Control rates for diffusive water flux and ammonia excretion were 23% and 33% higher respectively at the lower salinity, and the nitrogen quotient was 36% higher at the lower salinity. However, there were no significant differences in control ṀO2 or control urea-N excretion rates between the two salinities. The negative TEP in 7.5 ppt was significantly different from the positive value in 30 ppt (Figure 8.2). 252 8.4.4 The effects of DOCs and model compounds on diffusive water flux rates at two salinities At 30 ppt, exposure to LM DOC resulted in a significant increase of 38% in diffusive water flux rate (Figure 8.2A). The 29% increase associated with exposure to LO DOC was not significantly different from either the control or the response to LM DOC. However, compared to the control condition, there was a large significant increase (133%) in diffusive water flux rate in response to SDS, whereas small elevations with TA and BSA were not significant (Figure 8.2B). At 7.5 ppt, there were no significant changes in diffusive water flux rates in response to the natural DOCs (Figure 8.2C). However, as with 30 ppt, the acute transfer from the control solution to SDS at 7.5 ppt caused a large significant increase (162%) in diffusive water flux rate, whereas the other compounds were without effect (Figure 8.2D). 8.4.5 The effects of DOCs and model compounds on ṀO2 at two salinities There were no significant changes in ṀO2 in response to any of the natural DOCs or model compounds tested at 30 ppt or 7.5 ppt (Figure 8.3A, B, C, D). 8.4.6 The effects of DOCs and model compounds on ammonia and urea-N excretion rates at two different salinities At 30 ppt, although not significantly different (p=0.076) from the control, there was a 40% increase in ammonia excretion rate in response to LO DOC (Figure 8.4A), whereas exposure to LM DOC resulted in a slight but non-significant fall (23%, p= 0.4415) in ammonia excretion rate. Therefore, there was a significant 85% difference between the rates in LM and LO DOC at 253 30ppt (Figure 8.4A). There were no significant differences in ammonia excretion rate in response to the model compounds compared to the control rate (Figure 8.4B). At 7.5 ppt, there were no significant differences in ammonia excretion rates in response to the natural DOCs (Figure 8.4C). However, compared to the 7.5 ppt control, there was a significant 32% decrease in response to acute exposure to TA, similar to the non-significant fall seen at 30 ppt with TA, although the other model compounds were without effect at 7.5 ppt (Figure 8.4D). At 30 ppt, there were significant decreases in urea-N excretion rates in response to both LM DOC (47%) and LO DOC (39%) (Figure 8.5A). Exposure to BSA resulted in a significant increase in urea-N excretion rate by 119%, whereas the other model compounds were without effect (Figure 8.5B). At 7.5 ppt, there was a significant 61% decrease in urea-N excretion rate in response to LO DOC, whereas the smaller decrease (22%) associated with exposure to LM DOC was not significant relative to either the control or LO values (Figure 8.5C). There were no significant changes in urea-N excretion rates in response to any of the model compounds tested (Figure 8.5D). 8.4.7 The effects of DOCs and model compounds on nitrogen quotients at two different salinities At 30 ppt, there were no significant differences in NQ relative the control values in response to either of the natural DOCs. However, the NQ tended to fall slightly for LM and rise slightly for LO, such that the NQ in the latter was significantly greater by 109% than for LM (Figure 8.6A). However, there was a significant fall (48%) with TA and a non-significant 254 increase with BSA resulting in a significant difference (109%) between the lower value in TA and the 109% higher value in BSA (Figure 8.6B). SDS had no effect. At 7.5 ppt, the nitrogen quotient (NQ) was unaffected by exposure to either of the natural DOCs (Figure 8.6C). However, it decreased by 48% in response to TA when compared to the 30 ppt control (Figure 8.6B). At 7.5 ppt there were no significant changes in the NQ relative to the control value, although again there was a significant difference between the lower value in TA and the 87% higher value in BSA (Figure 8.6D). 8.4.8 The effects of DOCs and model compounds on TEPs at two different salinities At 30 ppt, where TEP was positive, there were significant decreases in TEP in response to acute exposure to LM DOC and to BSA (Figure 8.7A, D), whereas LO DOC (Figure 8.7B), TA (Figure 8.7C) and SDS (Figure 8.7E) had no effects. At 7.5 ppt, where the TEP was negative, there were no significant changes in TEP in response to any of the experimental solutions (Figure 8.7, G, H, I, J). 8.5 Discussion 8.5.1 Overview In accord with previous studies on this species (Onukwufor and Wood 2022; Morris and Wood 2023, see Chapter 7), an acute decrease in salinity resulted in increases in diffusive water flux rate, ammonia excretion rate, and NQ in the Pacific sanddab, responses that were not associated with changes in ṀO2 (Table 8.3). Furthermore, the TEP changed from a positive value in seawater to a negative value at low salinity, in accord with observations on many other teleost species reflecting the transition from a predominantly electrogenic potential in seawater to 255 a diffusion potential in freshwater (Potts 1984; Wood and Grosell 2008). As explained in the Introduction. Our goal was to examine the rapid physiological response that might occur when fish first enter dilute estuaries; in future studies it will be of interest to see whether these responses persist when sanddabs are resident for long periods in low salinity waters. The fundamental physicochemical differences between LO and LM DOCs, as established in earlier freshwater studies (i.e. greater aromaticity, molecular weight, humic acid-like composition, and allochthonous character in the latter; Al-Reasi et al. 2012, 2013a, b, 2016; Duarte et al. 2018; Morris et al. 2024b, see Chapter 3) were still seen when these sources were investigated in seawater. Our present results demonstrate that these DOCs, as well as model compounds, interact with the gill transport responses in a complex manner as a function of both salinity and source. Originally, we hypothesized that i) the effects of DOC would be greater at lower salinity; however, our data often showed greater effects at higher salinity, therefore, our first hypothesis was not supported. For example, there was a significant change in diffusive water flux rate in response to LM DOC at 30 ppt that was not present at 7.5 ppt (Figure 8.2A, C). This was also the case for urea-N excretion rate for LM DOC and BSA (Figure 8.5). Additionally, there were DOC effects on TEP at 30 ppt but not at 7.5 ppt (Figure 8.7). ii) The effects of LM DOC were indeed greater than those of LO DOC, supporting our second hypothesis. LM significantly affected diffusive water flux rate, urea-N excretion rate and TEP at 30 ppt (Figure 8.2A, Figure 8.5A, Figure 8.7A). There were no significant effects of LM at 7.5 ppt, whereas LO only significantly affected urea-N excretion rate which was observed at both salinities (Figure 8.5A, C). iii). In accord with our third hypothesis, the TEP responses to LM and BSA were different at 30 ppt compared to 7.5 ppt with significant decreases at 30 ppt only (Figure 8.7A, C, F, I), iv) In 256 support of our final hypothesis, the effects of the model compounds did help illuminate which specific properties of the natural DOCs were contributing to the observed responses, as outlined subsequently. 8.5.2 Optical indices of natural DOCs are a function of salinity Although the DOC concentration for the control solutions and concentrations within the same DOC source were quite similar between salinities, there were differences in SAC340 and MWI (Table 8.1). Previous studies have shown that ionic strength and pH play important roles in the molecular conformation of DOCs (Chin and Gschwend 1991; Gennings et al. 2001; Morris et al. 2024b, see Chapter 3) where for example, protonation results in condensation that limits light exposure, lowering absorption (Pace et al. 2012). It is likely that the change in absorption with salinity, reflected in the SAC340 and MWI values (Table 8.1), is due to the effects of ionic strength and pH combined, on the molecular conformation of the DOCs. Additionally, high ionic strength could potentially alter the solubility of the DOC, thereby precipitating certain fractions (Tipping and Hurley 1988; Kalbitz et al. 2000) in turn, altering the physicochemical characterization parameters. The characteristics of LO DOC and LM DOC are quite different, with the former being less aromatic, more autochthonous, and smaller in molecular size (Table 8.1). Therefore, it is perhaps not surprising that their optical responses to changes in salinity differ. This suggests that key chemical moieties of LO DOC or LM DOC that may interact at the gill at 30 ppt may no longer be accessible for interaction at 7.5 ppt due to changes in molecular conformation (e.g. condensation) which may result in an altered physiological response. 257 8.5.3 Diffusive water flux and ammonia excretion can be uncoupled from oxygen consumption, and independently regulated across salinities, in the presence and absence of DOC. Diffusive water flux is dominated by the transcellular pathway and aquaporin mediated flux and occurs through the entire gill surface area (Wood et al. 2019). The significant increase in diffusive water rate with a decrease in salinity (Table 8.3) is in accord with previous studies on this (Onukwufor and Wood 2022; Morris and Wood 2023, see Chapter 7) and other species (Evans 1969; Motais et al. 1969). As with the earlier investigations on the Pacific sanddab, ṀO2 did not change with salinity, confirming that diffusive water flux can be uncoupled from O2 uptake. To our knowledge, no previous studies have considered how this uncoupling may be influenced by DOC in marine fish. Given that there were significant effects of DOCs on diffusive water flux rate that differed with salinity (Figure 8.2) but there were no DOC effects on ṀO2 (Figure 8.3), we can conclude that DOCs are acting only on diffusive water flux, and therefore the uncoupling is not influenced by DOC. Seawater fish have lower expression of aquaporins in the gill compared to freshwater fish which has been correlated with lower diffusive water flux rate, lower mRNA abundance, and lower protein abundance (Lignot et al. 2002; Cutler et al. 2007; Tipsmark et al. 2010; Jung et al. 2012; Madsen et al. 2015; Breves et al. 2016; Ruhr et al. 2020). Perhaps DOC increases diffusive water flux rate, particularly LM DOC at 30 ppt (Figure 8.2), by direct effects on the function of aquaporin proteins. Altered mRNA expression associated with new protein synthesis seems less likely as we investigated acute (within 1 h) effects of DOC on diffusive water flux rate. Detectable changes in AQP3 mRNA expression and cellular protein distribution have been seen within 3 h of an experimental treatment (acute hypoxia), but were evaluated at a higher 258 temperature (Ruhr et al. 2020). Decreasing the salinity from 30 ppt to 7.5 ppt results in a large decrease or even slight reversal of the trans-gill osmotic gradient. Another feasible explanation is remodeling mechanisms of the gill. For example, rapid changes in the morphological relationships between ionocytes and adjacent pavement cells (reviewed by Wood and Eom 2021) may cause immediate changes in exposure of gill ionocytes (Marshall and Nishioka 1980; Wood and Marshall 1994) which could be a response to low salinity. Further investigation is required. Similarly, ammonia excretion can likewise be uncoupled from ṀO2, as ammonia excretion rates become greater at low salinity without a corresponding change in ṀO2 (Table 8.3). By metabolic theory (Van Den Thillart and Kesbeke 1978), an NQ = 0.27 represents aerobic respiration being 100% fueled by protein. The first presented NQ values for wild-caught marine flatfish indicated that 83–86% of aerobic respiration is fueled by protein at 30 ppt under steady-state conditions (Morris and Wood 2023, see Chapter 7). In agreement, our combined controls at 30 ppt exhibited an NQ of 0.241, suggesting that 89% of aerobic respiration is fueled by protein (Figure 8.6; Table 8.3). However, the increase in ammonia excretion at unchanged ṀO2 in fish acutely transferred to 7.5 ppt resulted in a significant rise in NQ to 0.327 (Table 8.3) This was not quite significantly above the theoretical maximum of 0.27 (p= 0.067, by 1-sample-t-test). While classically this would be representative of an increase in aerobic protein metabolism (Van Den Thillart and Kesbeke 1978), in our acute exposure study this was more likely explained by an improved gradient for ammonia excretion due to the lower water pH at lower salinity (Table 8.1), creating a non-steady state condition to transiently increase ammonia efflux across the gills. 259 8.5.4 The shared physiological responses between natural DOCs and model compounds as a function of salinity are likely due to key chemical moieties. Natural DOCs are heterogenous, complex molecules that have several key chemical groups or moieties. Therefore, we used three model compounds that are rich in particular moieties and/or have the DOC characteristic of interest to illuminate the mechanisms of DOC effects. At 30 ppt, exposure to both LM DOC and SDS resulted in an increase in diffusive water flux rate (Figure 8.2A, B). This may be due to the shared aliphatic chains, contributing to the surfactant property of both molecules, and possibly altering aquaporin function. Salinity may alter the surfactant property of natural DOC as the elevated diffusive water flux rate was not present with LM DOC at 7.5 ppt yet persisted with SDS. At 7.5 ppt, LM DOC may have undergone a change in molecular conformation. For example, molecular condensation with the change in ionic strength may have rendered the aliphatic chain no longer accessible to interact with the gill surface thereby altering the physiological response. The consistent, though not always significant reductions in ammonia excretion in response to both LM DOC and TA (Figure 8.4) could be physiologically important. LM DOC, compared to LO DOC is more aromatic (higher SAC340 value, Table 8.1) and thereby similar to the poly phenolic, aromatic model compound, TA. The ammonia-transporting function of the Rhesus (Rh) glycoproteins organized into a metabolon has been described in both freshwater and marine fish (Nakada et al. 2007; Nawata et al. 2007, 2010; Wright and Wood 2009). The already complex mechanism(s) of ammonia excretion in freshwater fish is certainly influenced by low ambient pH and elevated DOC concentrations (Morris et al. 2021, see Chapter 2). It is possible that here, the phenolic groups of both LM DOC and TA are influencing Rh proteins, so as to 260 reduce ammonia excretion rates. LO is a mostly autochthonous DOC with generally higher amino acid and peptide content when compared to allochthonous DOCs such as LM (Thurman 1985). This is reflected in the higher relative % protein concentration in LO DOC than in LM DOC as seen in our PARAFAC data (Figure 8.1E). BSA is a relatively large tyrosine-rich and peptide-rich molecule, so it is more similar to LO DOC. At 30 ppt, there were significant decreases in urea-N excretion rate in response to both natural sources of DOCs, but at 7.5 ppt the effect remained significant for LO only (Figure 8.5A, C). At 30 ppt, there was a significant increase in urea-N excretion rate in response to BSA (Figure 8.5B). Possibly, amino acid-rich DOCs interact with UT, the facilitated diffusion transport responsible for branchial urea excretion in fish (McDonald et al. 2006). The reductions in TEP in response to both LM DOC and BSA at 30 ppt were the only significant DOC effects; none occurred at 7.5 ppt (Figure 8.7). The origin and polarity of TEP are different at the two tested salinities, as discussed earlier. Therefore, the significant responses could be an influence on the inwardly directed Na+ diffusion potential and/or the electrogenic extrusion of Cl-, both of which contribute to the positive (inside) TEP that is present in marine fish at 30 ppt (Potts 1984; Wood and Grosell 2008). Given that there were only observed effects at 30 ppt and not at 7.5 ppt where the Cl- extrusion pump would be inactive, it was likely an effect on the latter. The chemistry of BSA is more similar to LO DOC than LM DOC with the shared key chemical moiety being peptides, however, LM DOC is more aromatic than LO DOC and BSA does have many cyclic amino acid groups (i.e. tyrosine). Perhaps it is the common aromatic rings between BSA and LM DOC that are influencing TEP. Additionally, DOC could indirectly affect the physicochemical environment leading to global changes in physiology. For example, DOC may act as a pH buffer in the external 261 microenvironment of the gills (Wood et al. 2003; Al-Reasi et al. 2012; Morris et al. 2021, see Chapter 2), and possibly a change in salinity likewise influences the gill microenvironment. Given the charged chemical moieties on DOC molecules, DOC could also possibly influence the stability of the tight junctions or even the electrical properties of the entire gill epithelium (Campbell et al. 1997; Galvez et al. 2008), as seen with the changes of TEP discussed above. 8.6 Concluding Remarks Overall, our results show that the effect of natural DOCs on the osmoregulatory responses of the gill of marine flatfish are salinity-dependent. These may be due to changes in both the physicochemical properties of the DOC, and changes in the gill physiology, as a function of salinity. Rapidly reduced salinity with increased DOC concentrations is an environmentally realistic challenge for Pacific sanddab, as outlined in the Introduction. Indeed, the experimental exposures used in this study can certainly occur in the natural environment (McNicol et al. 2023). Estuaries that receive inflow from a DOC-rich forested catchment or river would have a reduced salinity in the presence of elevated DOC concentrations (Maxey et al. 2020). To complete our mechanistic study, exposures of DOC in the presence of full-strength seawater were integral, although perhaps less common in the natural environment. Therefore, it is important to determine not only the effects of DOC as a function of salinity but also to identify which key chemical moieties of DOC could be playing a role to extrapolate our findings to the great diversities of DOCs that exist in different systems. We have described shared physiological responses between natural DOCs and model compounds and can conclude that key chemical groups of DOCs, including aliphatic chains, phenolic groups and peptides likely play a role in gill function in response to DOCs across salinities in the Pacific sanddab 262 8.7 Chapter 8 – Tables Table 8.1. Characterization of experimental water samples in terms of pH, DOC concentration, specific absorbance coefficient at 340 nm (SAC340), fluorescence index (FI) and molecular weight index (MWI) in exposures at two different salinities, 30 ppt and 7.5 ppt. Source Salinity pH [DOC] SAC340 FI MWI Control 30 ppt 7.96 1.71 NA NA NA Control 7.5 ppt 7.06 2.20 NA NA NA Lake Ontario 30 ppt 6.84 9.74 15.6 1.34 4.61 Lake Ontario 7.5 ppt 6.53 9.44 9.65 1.37 6.61 Luther Marsh 30 ppt 7.23 8.34 21.61 1.21 4.48 Luther Marsh 7.5 ppt 7.71 11.97 22.72 1.21 4.39 Tannic acid 30 ppt 7.47 4.44 NA NA 2.02 Tannic acid 7.5 ppt 7.36 5.53 NA NA 1.84 Bovine serum albumin 30 ppt 7.73 12.3 NA NA NA Bovine serum albumin 7.5 ppt 7.32 9.36 NA NA NA Sodium dodecyl sulphate 30 ppt 7.75 15.8 NA NA NA Sodium dodecyl sulphate 7.5 ppt 7.73 14.3 NA NA NA 263 Table 8.2. Allometric mass scaling for diffusive water flux, oxygen consumption, ammonia and urea-N excretion rates for Pacific sanddab (Citharichthys sordidus) at 30 ppt and 7.5 ppt. Y = log rate and X = log body mass p<0.10 was used for statistical significance *indicates parameters for which allometric scaling was applied Measurement Salinity Regression equation R2 p-values Diffusive water flux rate* 30 ppt Y = 0.8388*X - 0.4993 0.6326 0.0020 Diffusive water flux rate* 7.5 ppt Y = 0.7704*X - 0.2453 0.7569 0.0002 Oxygen consumption rate 30 ppt Y = 0.5554*X + 1.350 0.1262 0.2571 Oxygen consumption rate 7.5 ppt Y = -0.08703*X + 2.777 0.02585 0.6176 Ammonia excretion rate* 30 ppt Y = 0.7844*X - 0.05554 0.4643 0.0147 Ammonia excretion rate* 7.5 ppt Y = 0.6871*X + 0.2709 0.2481 0.0993 Urea-N excretion rate 30 ppt Y = 0.3910*X + 0.05888 0.03803 0.5436 Urea-N excretion rate* 7.5 ppt Y = 0.8806*X - 0.9213 0.3357 0.0484 264 Table 8.3. The mean values ± SEM of the two control groups at each salinity combined (Series 1 and 3 at 30 ppt versus Series 2 and 4 at 7.5 ppt) and the Student’s t-test unpaired comparison (p value, p<0.05 is significant) for diffusive water flux rate, oxygen consumption rate, ammonia excretion rate, urea-N excretion rate, nitrogen quotient and transepithelial potential. Physiological endpoint 30 ppt 7.5 ppt p-value Diffusive water flux rate (ml kg-1 h-1) 131.8 ± 6.3 162.5 ± 8.5 0.0084 Oxygen consumption rate (µmol kg-1 h-1) 1375 ± 115 1654 ± 171 0.1917 Ammonia excretion rate (µmol kg-1 h-1) 278 ± 22 369 ± 57 0.0219 Urea-N excretion rate (µmol kg-1 h-1) 94.4 ± 10.9 68.9 ± 9.1 0.0862 Nitrogen quotient 0.241 ± 0.027 0.327 ±0.028 0.0367 Transepithelial potential (mV) +11.9 ± 0.7 -9.2 ± 1.3 <0.0001 265 8.8 Chapter 8 – Figures Figure 8.1. Fluorescence excitation-emission matrices for natural DOCs at 30 ppt, (A) - Lake Ontario, (B) - Luther Marsh and at 7.5 ppt, (C) - Lake Ontario, (D) - Luther Marsh and (E) the relative % fluorophores of humic acid-like, fulvic acid-like and protein-like components for Lake Ontario (LO), and Luther Marsh (LM) at 30 ppt and 7.5 ppt. 266 Figure 8.2. The interactive effects on diffusive water flux rate (ml kg-1 h-1) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 1), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=6 (Series 3), (C) 7.5 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 2), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=5-6, (Series 4) of Pacific sanddab (Citharichthys sordidus). Data are means ± SEM. Bars not sharing the same letters are significantly different (p<0.05) (analysis of variance with Tukey’s test). 267 Figure 8.3. The interactive effects on O2 consumption rate (ṀO2, μmol kg-1 h-1) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 1), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=6 (Series 3), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 2), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=5-6, (Series 4), of Pacific sanddab (Citharichthys sordidus). Data are means ± SEM. Bars not sharing the same letters are significantly different (p<0.05) (analysis of variance with Tukey’s test). 268 Figure 8.4. The interactive effects on ammonia excretion rate (μmol kg-1 h-1) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 1) (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=6 (Series 3) (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 2) (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=5-6, (Series 4) of Pacific sanddab (Citharichthys sordidus). Data are means ± SEM. Bars not sharing the same letters are significantly different (p< 0.05) (analysis of variance with Tukey’s test or Brown-Forsythe and Welch ANOVA test with Dunnett’s T3 multiple comparison test). 269 Figure 8.5. The interactive effects on urea-N excretion rate (μmol kg-1 h-1) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 1), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=6 (Series 3), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 2), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=5-6, (Series 4) of Pacific sanddab (Citharichthys sordidus). Data are means ± SEM. Bars not sharing the same letters are significantly different (p<0.05) (analysis of variance with Tukey’s test). 270 Figure 8.6. The interactive effects on the nitrogen quotient (NQ) of (A) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 1), (B) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=6 (Series 3), (C) 7.5 ppt natural DOCs (Luther Marsh and Lake Ontario), N=6 (Series 2), and (D) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=5-6, (Series 4) of Pacific sanddab (Citharichthys sordidus). Data are means ± SEM. Bars not sharing the same letters are significantly different (p<0.05) (analysis of variance with Tukey’s test). 271 272 Figure 8.7. The interactive effects on transepithelial potential (TEP) of (A,B) 30 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=9 (C,D,E) 30 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=9 (Series 5) (F,G) 7.5 ppt and natural DOCs (Luther Marsh and Lake Ontario), N=5, and (H,I,J) 7.5 ppt and model compounds (tannic acid, sodium dodecyl sulfate and bovine serum albumin), N=5, (Series 6) of Pacific sanddab (Citharichthys sordidus). Data are means ± SEM. Bars not sharing the same letters are significantly different (p<0.05) (Student’s paired t-test). 273 Chapter 9: The acute osmoregulatory effects of low pH and Cu, alone and in combination, on the dwarf cichlid (Apistogramma agassizii) in Rio Negro blackwater and Rio Solimões whitewater: flux rates of ions, nitrogenous wastes, and water. 9.1 Summary Increases in anthropogenic activities in the Amazon have led to pollution from trace metals, including copper. Dissolved organic carbon (DOC) is known to protect against metal toxicity and ionoregulatory disturbances in Amazonian fish, particularly at low pH. However, little is known about the effects of DOC and trace metals such as copper, on the branchial water transport pathways. Water moves across the gills of fish through two distinct pathways: paracellularly through tight junctions and transcellularly by diffusion through aquaporins. In the present study, we evaluated the effects of copper (nominally 200 µg L-1) on diffusive water flux rate (transcellular water movement), paracellular permeability ([3H]-polyethylene glycol-4000 clearance), ion balance (net sodium, potassium and chloride fluxes) and nitrogenous waste (ammonia and urea) excretion in the dwarf cichlid, Apistogramma agassizii. Exposures were conducted in control water (low ions, very low DOC), in filtered Rio Negro (RN) blackwater (low ions, high DOC) and in filtered Rio Solimões (RS) whitewater (higher ions, intermediate DOC) at pH 7 and pH 4. Copper increased ion losses in control water, especially at low pH; RN water protected against these effects whereas RS water did not, reflecting greater complexation of free Cu2+ ion by RN DOC. Our results also show, for the first time, that copper tends to inhibit urea-N excretion as well as ammonia excretion, and also decreases branchial water transport both transcellularly and through tight junctions. The protective effects of DOC against the disturbances caused by copper were dependent on the source of the DOC and the water pH. 274 9.2 Introduction Blackwater systems are found globally (Sabater et al. 1993; Robroek et al. 2017; Gandois et al. 2020) and have characteristically high concentrations of dissolved organic carbon (DOC), low pH and are often very ion-poor. The Rio Negro (RN) is an example of these habitats, one that has been relatively well studied. RN water chemistry is influenced by the decomposition of jungle vegetation, resulting in one of the most naturally DOC-rich (~7-35 mg C L-1 ), acidic (pH 3-6) and ion-poor (<30 μmol L-1 of Na+, Cl-, Mg2+ and Ca2+) (Duarte et al. 2013) watersheds globally (Furch 1984; Val and De Almeida-Val 1995; Walker and Henderson 1996). This water chemistry is so extreme that it would likely be toxic to most other freshwater fish (Val and De Almeida-Val 1995). Yet, it is one of the most biodiverse watersheds in the world, home to about 8% of the global freshwater fish species (Val and De Almeida-Val 1995; Morris et al. 2021, see Chapter 2; Val and Wood 2022). This biodiversity may be associated with the quality and quantity of DOC as well as physiological adaptations of the organisms to this very challenging environment. Indeed, DOCs are able to exert ionoregulatory effects on freshwater fish that are often beneficial, and particularly important in low-pH blackwater. Notably, beneficial DOC effects have been observed against acidity. DOC has been shown to protect against the inhibition of active ion uptake and the often-fatal increase in passive loss of major salt ions (Na+, Cl-) across the gills at acidic pH (Gonzalez et al. 2002, 2005; Wood et al. 2003, 2011; Matsuo et al. 2004; Glover et al. 2005; Glover and Wood 2005; Al-Reasi et al. 2016; Duarte et al. 2016, 2018). The presence of DOC also protects against disturbances in ammonia excretion in response to low pH exposure in fish. Generally, an increase in ammonia excretion rate is observed in the presence of RN DOC at low pH (Wood et al. 2003; Sadauskas‐Henrique et al. 2019, 2021) which appears to 275 help maintain Na+ coupling to ammonia excretion. Duarte et al. (2016) suggested that DOC supports this coupling via the Rh metabolon (Wright and Wood 2009, 2012). However, overall, there has been very little work done on the interactive effects of low pH and DOC (and metals) on ammonia excretion rate and none, to our knowledge, on urea-N excretion rates. DOC is also known to protect fish against toxic trace metals, such as copper (Cu), a contaminant of interest in the Amazon (Duarte et al. 2013). Similar to acidity, Cu impairs Na+ homeostasis in freshwater fish, leading to often-fatal plasma Na+ loss. This occurs through inhibition of branchial Na+ influx via direct competition with Na+ at the Na+ channels on the apical membranes of the branchial ionocytes, and promotion of diffusive Na+ loss, via an increase of the branchial epithelium permeability (Laurén and McDonald 1985; Grosell et al. 2002). Using the Biotic Ligand Model, the severity of these effects is usually attributed to the concentration of the free Cu2+ ion in solution, which is greatly affected by the ambient water chemistry (Di Toro et al. 2001; Niyogi and Wood 2004). Notably, it is well-established that DOCs have the ability to complex with metals, and thereby, to reduce the bioavailability of metal cations, leading to the mitigation of metal toxicity (Playle et al. 1993; Hollis et al. 2001; Matsuo et al. 2004; Wood et al. 2011; Crémazy et al. 2016). Another osmoregulatory area in which DOC may be important is in altering the permeability of the gill epithelium to water. In freshwater fish, water moves across the gill barrier through two distinct pathways. Firstly, it can move paracellularly through tight junctions where it is thought to move by bulk flow (Wood et al. 2019). Secondly, it can move by diffusion across the entire gill surface, but largely by the transcellular pathway through aquaporins (Wood et al. 2019). These diffusive water channels were first discovered by Preston et al. (1992) using in vitro expression in frog oocytes. It has been suggested that DOC may affect paracellular or 276 diffusive permeability (Galvez et al. 2008), but there are no experimental data confirming this, to our knowledge. Increases in paracellular permeability at low environmental pH have been reported in zebrafish (Kwong and Perry 2013; Al-Reasi et al. 2016), a species which is acidophilic but does not occur in the Amazon. We are aware of only two previous studies, both on the oscar (Astronotus ocellatus), that have measured either of the two water transport pathways in any Amazonian fish (Wood et al. 2009; Robertson et al. 2015), and neither of them addressed the effects of low pH, DOC, or Cu. The ability of DOCs to protect against metal toxicity and exert physiological effects is linked to their physicochemistry, therefore, some DOCs exhibit more effective protection than others (Al-Reasi et al. 2011, 2013a; Sadauskas‐Henrique et al. 2019; Morris et al. 2024c, see Chapter 4). Notably, DOC from the RN blackwater (pH 3- 6, DOC > 7 mg C L-1) may offer more protection than DOC from Rio Solimões (RS) white waters, another major tributary of the Amazon basin. This latter water has a higher silt burden, lower DOC concentration (~2-6 mg C L-1), a higher natural pH (6-7), and ion concentrations that are at least 3-fold higher when compared to RN water (Morris et al. 2021, see Chapter 2). Many of the physicochemical properties of DOC can be determined using optical techniques (Al-Reasi et al. 2011; Wood et al. 2011). Generally, allochthonous, aromatic, DOCs that are optically dark and rich in humic acid, are more protective against metal toxicity and physiological disturbances (Wood et al. 2011; Al-Reasi et al. 2013a; Morris et al. 2024c, see Chapter 4). Indeed, based on absorbance and fluorescence measurements, RN water has been reported to be more allochthonous, highly aromatic and to have a higher % humic acid-like content in comparison to RS water (Duarte et al. 2016; Holland et al. 2017; Johannsson and Holland 2025; Sadauskas‐Henrique et al. 2025). In the present study we investigated the effects of low pH (4 versus 7) and Cu (0 versus 277 200 µg L-1) on the dwarf cichlid (Apistogramma agassizi) exposed in two freshly collected waters from the Amazon basin, “black water” from Anavilhanas Archipelago region of the Rio Negro (RN) and “white water” from Janauacá region of the Rio Solimões (RS). The dwarf cichlid was chosen as it is one of a number of species that lives naturally in both the RN and RS., and its basic ionoregulatory physiology has been well characterized, as well as some of its responses to low pH and to Cu (Gonzalez et al. 2002, 2005; Duarte et al. 2009, 2013, 2024; Val and Wood 2022; Crémazy et al. 2022). As an ornamental fish favoured by aquarists, it has regional socio-economic importance. To simplify the experiments, the natural waters were filtered to remove particles, so that only the dissolved water chemistry could influence the physiological responses of the fish. We used Instituto Nacional de Pesquisas da Amazônia groundwater (INPA), an ion-poor, DOC-poor groundwater to which the fish had been acclimated as a reference control. We measured net Na+, K+ and Cl- flux rates, ammonia and urea-N excretion rates, diffusive water flux rate (a proxy for transcellular permeability), [3H]PEG-4000 clearance rates (a proxy for paracellular permeability) and drinking rate (which is a byproduct of the [3H]PEG-4000 clearance rate measurements). This experimental design allowed us to determine which of the two field-collected waters was more protective against the disturbing effects of low pH and of Cu, and whether there were interactive effects between pH and Cu in each water type. Our specific hypotheses were: (i) Low pH would increase the net loss rate of major ions (Na+, K+, Cl-), and RN waters would offer the greatest protection against these effects due to the beneficial physiological effects of its highly allochthonous DOC on ionic homeostasis noted above. (ii) Cu would also increase the net loss rate of major ions, and the extent of these disturbances would be a function of the concentration of the free Cu2+ ion in the various test 278 waters, as estimated by chemical speciation modeling. (iii). RN would also provide a greater protection than RS against these ionoregulatory disturbances of low pH and Cu, due to the higher concentration of very allochthonous DOC in the RN. The RS response patterns would look more like the control response pattern. (iv) Other osmoregulatory parameters (diffusive water flux, paracellular permeability, drinking rate - i.e. ones which have never been looked at before with respect to low pH and Cu) would exhibit the same response patterns as the net ion flux rates. (v) Because of the likely linkage between Na+ uptake and ammonia excretion, treatments that disturbed Na+ balance would inhibit ammonia excretion. (vi) This would not be the case for urea-N excretion, for which there is no evidence of linkage to Na+ uptake. 9.3 Methods This study was a semi-field project where the fish were taken from the lab to the natural water sites. The work was performed in November-December 2023 on board the research vessel, the Ana Clara near Manaus, Brazil. Two field locations within the Amazon river basin were visited and fresh river water was collected from each. The first field location was visited between November 22nd and 29th of 2023 and was located in the Anavilhanas archipelago of the Rio Negro [approximately 110 km upstream of Manaus; S 02°43′10.3′′, W 060°45′19.6′′]. The second location was visited between November 30th and December 5th of 2023 and was near the village of Janauacá on the Rio Solimões [approximately 40 km upstream of the mixing zone between the Rio Negro and the Rio Solimões; S 03°21'19.7'' W 060°12'40.1'']. 279 9.3.1 Animals Dwarf cichlids (Apistogramma agassizi) (N= 175, 268.0 ± 1.3 mg) were obtained from a commercial dealer in Manaus, Brazil. These fish were wild-caught before being sold through the dealer so it is most likely that these fish were of mixed sex. Fish were held at the Laboratory of Ecophysiology and Molecular Evolution at Instituto Nacional de Pesquisas da Amazônia (LEEM-INPA) in aerated control water (INPA groundwater, Table 9.1) at 29 ± 1◦C. After 7 days they were transferred to the research vessel Ana Clara in the same water. Experiments commenced on board the vessel several days later. Fish were fed to satiation every day with commercial dry food (TetraMin®, Tropical Flakes Fish Food, Spectrum Brands, Blacksburg, VA, USA) and fasted for at least 24 h before testing. All experimental procedures were approved by the Ethics Committee on Animal Experiments of INPA under registration number 004/2018, in conformity with the Brazilian Ethics Committee on Animal Care (CONCEA) guidelines (RN 61/2023). The research was also authorized by the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) (SISBio number: 29837-24). 9.3.2 Exposure waters A total of 12 exposure solutions were tested: control (INPA), RN and RS water at pH 7 and pH 4, each in the presence and absence of nominally 200 µg L-1 of Cu. Fresh RN water from near Anavilhanas Archipelago (2o 43' 00" S, 60o 45' 29" W) and fresh RS water from near Janauacá (3o 21'26" S, 60o 12' 26" W) were collected upstream of Manaus. Control INPA water had been collected directly from the tap at LEEM-INPA and thoroughly aerated to remove CO2. Its particulate concentration was extremely low, so it was used without filtration. RN and RS waters were filtered using 0.45-m pore size (47 mm), hydrophilic, polyethersulfone polymer 280 membrane filters (MS® PES Membrane Solutions, Auburn, WA, USA), which were pre-rinsed with 500 ml of distilled water to remove any contaminants. All waters were stored in the dark in sealed bottles at 4ºC until use. The pH was adjusted to ~pH 7 or ~pH 4 using HNO3 or NaOH and measured using a sympHonyTM pH electrode (C03243) and meter (SP70P) (VWR International, Radnor, PA, USA). A copper (Cu) stock solution was prepared from CuSO4·5H2O (99% pure, Sigma Aldrich, St. Louis, MO, USA) and was added to the exposure waters 24 h before each test, to allow for equilibration. Prior to experiments, waters were warmed to the experimental temperature (29 ± 1◦C) and thoroughly aerated. Additionally, at this time, the pH was checked and adjusted appropriately if it deviated by more than ±0.1 pH units for the intended value. The DOC concentrations in the test waters were measured with a total organic carbon (TOC) analyzer (Shimadzu TOC-VCSH, Canby, OR, USA) and aqueous Cl− concentration was measured with the colorimetric assay of Zall et al. (1956) (Table 9.1). Certified commercial standards were used (ThermoFisher Scientific, Waltham, MA, USA). Cu and major cation concentrations were measured in the test waters by inductively coupled plasma atomic emission spectroscopy (5110 dual-view ICP-AES, Agilent, Santa Clara, CA, USA) using certified standards (SCP Science, Baie-D’Urfé, QC, Canada). For this ICP-AES analysis, samples were in a matrix of 0.5 % HNO3 (v/v) (trace metal grade, Fisher Scientific) with Internal Standard Yttrium 5 mg L-1 (yttrium oxide 99.99% pure from Sigma -Aldrich) with cesium chloride 0.2 % (99% pure from Fisher). Calibration was checked with certified reference water AQ0-213-985, COO-061-401 and 900-Q30-101 (SCP Science, Baie-D’Urfé, QC, Canada) (percent recovery was >90 % for Cu). A blank, quality control and calibration standard were reanalyzed every 20 281 samples to check and correct for potential instrument drift. 9.4 Diffusive water flux measurements The procedure outlined by Onukwufor and Wood (2020) was followed for measuring diffusive water flux rates. Briefly, the loading period began 2 h before the experiment started. Fish (6-8 per treatment) were pooled and exposed to 100 µCi L-1 of 3H2O (Eckert and Ziegler, Valencia, CA, USA) in 100 ml of INPA control water for 2 h. After the loading period, each individual fish was quickly rinsed in clean control water with care to minimize disturbance. Each fish was immediately placed in an individual enclosed, aerated temperature-controlled chamber containing 45 ml of the appropriate control or experimental solution without 3H2O. These containers were purposefully narrow, allowing sequential removal of water samples without emersing these very small fish. A sample of the 3H2O water was taken at the end of the loading period. For each treatment/replicate, a series of water samples were collected for analysis: a 5-ml water sample was taken at time 0 min and every 5 min for 30 min thereafter, and a final sample was taken at 4 h, at the end of the wash-out period, when the external and internal 3H2O pools were once again in equilibrium. The 4-h sample was used to calculate the original amount of radioactivity in the fish and the 0-30 min samples were used to determine the diffusive water flux rates. The concentration of 3H2O was measured by adding 10 ml of Optiphase 3 fluor (PerkinElmer, Waltham, MA, USA) to the 5-ml water sample, shaking vigorously and loading it into a scintillation counter (Hidex 300SL automatic, Turku, Finland). Preliminary tests showed that quenching and chemiluminescence were negligible. 282 9.5 Net ion flux and ammonia and urea-N excretion measurements Following the wash-out period for the diffusive water flux measurements, the experiments to determine the net ion flux and ammonia and urea-N excretion rates were started. Thus, by this time, the fish had been exposed to the experimental waters in the same chambers for 4 h. These experiments were run using this order of operations to minimize handling stress. A 5-ml water sample was taken from each individual experimental chamber marking the start of the ion flux and nitrogenous waste excretion period, and a final 5-ml sample was taken at 2 h which marked the end of the measurement period. Preliminary experiments demonstrated that this 2-h interval was adequate to detect reliable changes in ion concentrations and ammonia and urea-N levels in the water. Na+ and K+ ion concentrations were measured using atomic absorption spectrometry (AAS) (Varian AA240FS, Santa Clara, CA, USA). Water concentrations of Cl- (Zall et al. 1956), total ammonia (salicylate hypochlorite assay, Verdouw et al. 1978) and total urea-N (diacetyl monoxime assay, Rahmatullah and Boyde 1980) were measured colorimetrically. For each colorimetric assay, the three water types (i.e. control, RN and RS) were analysed against standard curves made with that water type, to account for any colour DOC may impart to the water. 9.6 Paracellular permeability and drinking rate Methodology developed by Robertson and Wood (2014) and modified by Al-Reasi et al. (2016) and Wood et al. (2019) was followed. A different batch of fish from those used in Sections 2.3 and 2.4 were transferred to individual aerated, temperature-controlled experimental chambers containing 35 ml of either control or experimental waters and were allowed to rest for 15 min. Similar studies on trout by Robertson and Wood (2014) and zebrafish by Al-Reasi et al. 283 (2016) used a 30-min resting period, but in preliminary experiments with dwarf cichlids we found no differences between 15 and 30 min. Then 50 µCi L-1 [3H]PEG-4000 (PerkinElmer, Shelton, CT, USA) was added to the water, followed by a 15-min mixing period. Water samples (5 ml) were taken for [3H]PEG-4000 radioactivity at 0.25 h and at 2 h, to mark the end of the experiment. Fish were euthanized with an overdose of tricaine methane sulfate (MS222) at a concentration of 0.5 g L-1 neutralized with NaOH. The gastrointestinal tract was carefully removed by dissection. Carcasses and gastrointestinal tracts were then weighed and individually digested in 2 volumes of 1 M nitric acid for 48 h at 65 °C, using sealed vials. [3H]PEG-4000 radioactivity was measured by liquid scintillation counting. Ultima Gold AB (PerkinElmer) scintillation fluid was used at a 2:1 ratio with sample digest. Quench curves were constructed to correct digest radioactivity to the same counting efficiency as water samples. 9.7 Calculations The rate constant of 3H2O efflux (k) was calculated employing the protocol outlined by Onukwufor and Wood (2020). Briefly, using the radioactivity of the final 2-h wash-out sample, the initial amount of 3H2O in the fish at time 0 min was determined. It was then possible to calculate the amount of 3H2O left in the fish at each sampling time from 0 to 30 min based on the measured amounts that appeared in the external solution at each time point and the known volume of the system. Next, the natural logarithm of the total 3H2O in the fish at each sample time was regressed against time in minutes on a linear scale. The fractional rate constant k for water turnover was the slope of this line. Multiplying the rate constant k by 60 yielded the fraction of the body water pool turned over per hour. Generally, the total exchangeable water pool of a fish is 800 ml kg-1 (Isaia 1984; Olson 1992; Holmes and Donaldson 1996). To calculate 284 the diffusive water flux rate in ml kg-1 h-1, the mass of the fish in kg was multiplied by 800 ml kg-1 and then by the fraction of the body water pool turned over per hour. Net ion flux rates and ammonia-N and urea-N excretion rates (Jnet, µmol kg-1 h-1) were calculated as per Wood (1992) using the following equation: 𝐽net =([X1] − [X2 ] × 𝑉)𝑚 × ∆𝑡 (Equation 9.1) where [X1] and [X2] represent the concentrations of X (X = Na+, K+, Cl-, ammonia-N or urea-N) at the beginning (1) and end (2) of the flux periods (µmol L-1). V is the volume of the exposure solution (L), m is the wet mass of the fish (kg) and Δt represents the total duration of the flux period (h). Note, there is 1 nitrogen atom per ammonia molecule, and 2 nitrogen atoms per urea molecule. The % urea-N excretion was calculated out of the total nitrogenous waste excretion (i.e. ammonia excretion + urea-N excretion) per fish in each water type. % urea N excretion = Urea N excretionurea N excretion + ammonia N excretion X 100 (Equation 9.2) As a proxy of paracellular permeability, gill [3H]PEG-4000 influx rates (expressed as water clearance rates, ml kg-1 h-1) were calculated as per Robertson and Wood (2014), modified by Al-Reasi et al. (2016) and Wood et al. (2019): 285 Gill influx clearance rate = PEG cpm gain from water at the final sampling pointMean watercpmml over sampling time ×1𝑚 ×1∆𝑡 (Equation 9.3) where PEG cpm gain from the water at final sampling point is the measured [3H]PEG-4000 radioactivity in the total carcass digest. The mean water cpm ml-1 is the average measured [3H]PEG-4000 radioactivity of the water samples over the sampling time. m is the mass of the whole fish (kg) and Δt represents the total duration of the flux period (h). Drinking rate was calculated based on the total gut [3H]PEG-4000 cpm measured in the removed gastrointestinal tract: Drinking rate = Gut PEG cpm gain from water at the final sampling pointMean watercpmml over sampling time ×1𝑚 ×1∆𝑡 (Equation 9.4) where gut PEG cpm gain from the water at the final sampling point is the measured [3H]PEG-4000 radioactivity in the whole gut digest. The mean water cpm ml-1 is the average measured [3H]PEG-4000 radioactivity of the water samples over the sampling time. m is mass of the whole fish (kg) including the gut, and Δt represents the total duration of the flux period (h). 286 9.7.1 Cu speciation modeling Cu speciation was modelled in the three waters as detailed in Crémazy et al. (2016), where the authors found good agreement between measured free Cu2+ ion concentrations, measured with a cupric ion-selective electrode, and modeled Cu2+ concentrations in Rio Negro water. Briefly, we used the Windermere Humic Aqueous Model (WHAM, version VII) (Lofts and Tipping 2011) and measured temperature, pH, concentrations of Cu, DOC, major cations and chloride. Alkalinity for the three waters was nominal and taken from Crémazy et al. (2016). We assumed that DOM was 50 % carbon in weight (Buffle 1988), only 65% active in complexing Cu, and composed of only fulvic acid (Bryan et al. 2002). Due to the relative proportion of protein-like DOC in the test waters: control (67%), RN (2.7%) and RS (4.3%) (Holland et al. 2017) and the limitations of WHAM in modeling metal binding to protein-like DOC, each of the three test waters were treated as containing fulvic acid only. A sensitivity analysis of the WHAM free ion estimates to the fulvic acid:humic acid ratio was tested assuming the opposite scenario (100% humic acid): the differences in %Cu2+ estimates proved to be negligible. The default log KCuHCO3 of 14.62 (Mattigod and Sposito 1979) was replaced by 12.13 in the thermodynamic database, as recommended by the International Union of Pure and Applied Chemistry (Powell et al. 2007). 9.7.2 Statistical analyses Data have been expressed as mean ± standard error (SEM; n) where n represents the number of animals sampled. Percentage data were analyzed both with and without arc-sin transformation. All data passed normality and homogeneity of variance tests and were analyzed using two-way analysis of variance (ANOVA) (factors, pH and Cu) with Tukey’s post hoc test 287 (multiple comparisons). A summary of two-way analysis of variance (ANOVA) p values and F (DFn, DFd) for pH, total Cu, and the interaction effect are summarized in (Appendix F Table SF 1). Simple linear regressions (p < 0.05) were used to assess relationships between each of the physiological parameters and the %free copper ion (Cu2+) for each water type. All statistical analyses and data plots were done using GraphPad™ Prism 10 (GraphPad Software, San Diego, CA, USA). A significance level of p<0.05 (i.e. two-tailed) was used throughout. 9.8 Results 9.8.1 Water Chemistry In general, the control (INPA) and RN waters exhibited similar, very low ion concentrations, but differed greatly in DOC concentration which was about 15-fold greater in RN (9.3 mg L-1) than in INPA water (0.6 mg L-1) (Table 9.1). In contrast to both, RS water exhibited ion concentrations that were at least 3-fold higher (Na+, K+, Cl-) and up to 30- to 50-fold higher (Ca2+, Mg2+) than in the other two waters. DOC concentration in RS water (5.6 mg L-1) was intermediate between control and RN waters. In all three waters, measured Cu concentrations after addition of nominally 200 µg L-1 were actually about 75% of the intended values. Note that as part of our experimental design, suspended particles had been removed from RN and RS water by 0.45-µm filtration, as they would otherwise bind and remove significant amounts of Cu out of solution (Crémazy et al. 2019, 2025). There were no suspended particles in control water. Our goal was to achieve the same concentrations of dissolved Cu in the three waters. 288 9.8.2 Cu speciation The relative proportions of the chemical forms of dissolved Cu in the experimental waters were modeled at pH 7 and pH 4 (Table 9.2). Cu bound to DOC accounted for the largest percentage in most, but not all of the experimental solutions, generally followed by Cu2+ (i.e. free Cu2+ ion). Notably for RN at pH 7 and RS at pH 7, %Cu2+ values were negligible because almost all (> 95%) of the Cu was bound to the DOC. The two exceptions to the dominance of Cu-DOC were control water at pH 4 and RS water at pH 4 where the free Cu2+ ion predominated. This reflected the general trend that for all waters the 1000-fold higher H+ ion concentration at pH 4 versus 7 displaced much of the Cu from the DOC into the free ion form. Thus, in each experimental water there was a higher %Cu2+ and a lower %Cu-DOC at pH 4 compared to pH 7 (Table 9.2). At pH 7, control + Cu had the highest %Cu2+ (27%), whereas RS + Cu and RN + Cu exhibited only very small %Cu2+ and the highest %Cu-DOC values (Table 9.2). At pH 4, control + Cu exhibited very high %Cu2+ (91%) whereas this dropped to 58% in RS + Cu and 33% in RN + Cu. Other copper species were generally of minor importance. For all solutions there was 0% CuCl+ and 0% Cu(CO3)2[2-]. Speciation analyses were also performed for the low background levels of Cu (4-6 µg L-1) in the waters without added Cu (data not shown). In these waters, the vast majority of background Cu was bound up by DOC - with > 94% Cu-DOC in all waters except control at pH 4 where it was 68 % Cu-DOC and 32 % Cu2+. 289 9.8.3 The effects of pH and Cu on net ion flux rates in the three water types In general, low pH, Cu, and their combination tended to increase net loss rates of major physiological ions in both control and RS water, whereas these effects were not seen in RN water (Figure 9.1). In control water at pH 7, the fish were in approximately zero net Na+ balance (Figure 9.1A). There was a significant overall effect of pH (p=0.0078) on net Na+ flux rate, such that net Na+ loss rate tended to become greater at low pH. There was no overall effect of Cu (p=0.1586) on net Na+ flux rate nor was there an interactive effect (p=0.7849). The only significant difference was between pH 7 and pH 4 + Cu treatments, where the highly negative net Na+ flux rate was 12-fold greater than the positive Na+ flux rate in the former (Figure 9.1A). In RN water, the fish exhibited negative Na+ balance at pH 7 (Figure 9.1B). There was no overall effect of pH (p= 0.5532) or Cu (p= 0.2634) and no interactive effect (p= 0.0984). There were also no significant differences in net Na+ flux rate among any of the exposures (Figure 9.1B) in RN water. In RS water, the fish exhibited net zero Na+ balance at pH 7 (Figure 9.1C). There were no overall effects of pH (p= 0.0652) or Cu (p= 0.2552) and no interactive effect (p= 0.4765). Similar to the pattern in control water, there was an observed trend of greater net Na+ loss with the decrease in pH and addition of Cu, however the only significant difference (101-fold more negative net Na+ flux rate) was at pH 4 + Cu relative to pH 7 (Figure 9.1C). In control water at pH 7, the fish were in negative K+ balance (Figure 9.1D); the same was true in RN water (Figure 9.1E) and RS water (Figure 9.1F). In each of the 3 water types, there were no overall effects of pH on net K+ flux rate (control p= 0.0513, RN p=0.4747, RS p=0.0766), though there were tendencies for greater loss rates with decreasing pH in control and RS waters. There were also no overall effects of Cu (control p= 0.9686, RN p=0.0990, RS 290 p=0.1836) and no interactive pH and Cu effects (control p= 0.7194, RN p=0.1388, RS p=0.6463). There were no significant differences among mean net K+ flux rates with the change in pH from 7 to 4 or with the addition of Cu (Figure 9.1D, E, F). The response patterns of net Cl- flux rates (Figure 9.1G, H, I) in the three water types were similar to those of net Na+ flux rates (Figure 9.1A, B, C). At pH 7, net Cl- balance was close to zero or slightly positive in control water and RS water, but negative in RN water. The general trend was for increased Cl- loss with decreased pH and the addition of Cu in control water (Figure 9.1G) and in RS water (Figure 9.1I) but not in RN water (Figure 9.1H). There were significant overall effects of both pH (p=0.0399) and Cu (p=0.0027) on net Cl- flux rate in control water, but there was no interactive effect of pH and Cu (p=0.3488). In control water there was a significant 8-fold more negative net Cl- flux rate at pH 4 + Cu relative to pH 7 (Figure 9.1G). In RN water, there was no overall effect of pH (p= 0.5230) or Cu (p= 0.8311) but there was a significant interactive effect between these two factors (p=0.0399) on net Cl- flux rate. There were no significant differences in net Cl- flux rate in RN among any of the experimental treatments (Figure 9.1H). In RS water, there was an overall effect of pH (p=0.0004) on net Cl- flux rate, such that there was an increase in Cl- loss with the decrease in pH (Figure 9.1I). There was no overall effect of Cu (p= 0.3945) and no interactive effect (p= 0.9519) between pH and Cu in RS water. There was a significant 7-fold increase in net Cl- loss rate between pH 7 and pH 4 + Cu (Figure 9.1I). 291 9.8.4 The effects of pH and Cu on nitrogenous waste excretion rates in the three water types The overall trend was for both ammonia and urea-N excretion rates to decrease in the presence of Cu, with negligible effects of pH (Figure 9.2). For ammonia excretion, in control water there was no overall effect of pH (p=0.5773) but a significant overall inhibitory effect of Cu (p<0.0001), with no interactive effect (p=0.1602). Ammonia excretion rate decreased significantly in control water with the addition of Cu at both pH 7 and pH 4 by 30-40% (Figure 9.2A). In RN water there was no overall effect of pH (p= 0.1693) but there was again a significant inhibitory effect of Cu (p=0.0034) as well as a significant interaction effect (p=0.0215). Copper addition significantly reduced ammonia excretion rate at pH 4 by about 70% (Figure 9.2B). In RS water, there was no overall effect of pH (p= 0.9253), but there was an overall inhibitory effect of Cu (p= 0.0012), and again no interactive effect (p= 0.2303) of pH and Cu on ammonia excretion rate. There was a significant 50% decrease in ammonia excretion rate between pH 7 and pH 7 + Cu (Figure 9.2C). For urea-N excretion, in control water there was no overall pH effect (p= 0.2823), but a strong inhibitory effect of Cu (p= 0.0006) without significant interaction (p= 0.9801). In control water, urea-N excretion rate decreased significantly by 70-80% upon the addition of Cu at both pH 7 and pH 4 (Figure 9.2D). In RN water, there was an overall inhibitory effect of Cu (p= 0.0002) on urea-N excretion rate, but no overall effect of pH (p= 0.2970) and the interactive effect was not significant (p= 0.0585) There was a significant 80% decrease in urea-N excretion rate between pH 4 and pH 4 + Cu in RN water (Figure 9.2E). In RS water, there was no overall effect of pH (p= 0.4385), but a significant overall effect of Cu (p= 0.0311), with no interactive effect (p= 0.6906). There were no statistically significant differences in urea-N excretion rates in RS water among any of the tested experimental solutions (Figure 9.2F). 292 The mean %urea-N excretion rate (i.e. as a % of total ammonia-N + urea-N excretion rate, see Equation 2) was around 25% in control water, and somewhat lower in RN and RS water (Table 9.3). The data were analysed both with and without the generally recommended arc-sin transformation for percentage data. Both analyses yielded the same conclusion of no significant effects of pH and Cu within each of the experimental waters (Table 9.3). 9.8.5 The effects of pH and Cu on the water transport pathways and drinking rate in the three water types Diffusive water flux rates (a proxy for transcellular permeability) were very high in these small fish, generally greater than 1000 ml kg -1 h-1 (Figure 9.3A, B, C), meaning that the water turnover by diffusion was more than the entire water volume in the body each hour. In control water, there was no overall effect of pH (p= 0.2315) or Cu (p= 0.4845), however, there was a significant interactive effect (p= 0.0011). In the absence of added Cu, there was a significant 2-fold greater diffusive water flux rate at pH 4 relative to pH 7 (p= 0.0052). There was also a significant 40% decrease in the rate at pH 4 with the addition of Cu (p= 0.0275) (Figure 9.3A). In RN water, again there was no overall effect of pH (p= 0.1436) or Cu (p= 0.2950) but there was an interactive effect (p= 0.0039). In RN water at pH 7, diffusive water flux rate was very high and decreased significantly by 55% with the addition of Cu (Figure 9.3B). In contrast, at pH 4 there was an increase in the rate with added Cu, although not statistically significant. In RS water, there were no overall effects of pH (p= 0.1812), Cu (p= 0.7535) or their interaction (p= 0.9251), and also no significant differences among any of the treatments (Figure 9.3C). Gill [3H]PEG-4000 clearance rates (a proxy for paracellular permeability) were generally less than 100 ml kg-1 h-1 (Figure 9.3D, E, F) – i.e. more than one order of magnitude lower than 293 diffusive water flux rates. The general trend was a decrease with the addition of Cu in all three waters at both pHs. In control water there were no overall effects of pH (p= 0.1161) or Cu (p= 0.0873), and no interactive effects (p= 0.6411) between pH and Cu. There were no significant differences between any of the experimental treatments in control water (Figure 9.3D). In RN water there was no overall effect of pH (p= 0.2167), but a very strong overall effect of Cu (p<0.0001) to reduce [3H]PEG-4000 clearance rate, with no interactive effect (p= 0.2888). There was no significant change in gill PEG clearance rate between pH 7 and pH 4. However, the addition of Cu resulted in significant 40 - 50% reductions in the rates at both pH 7 and pH 4 (Figure 9.3E). In RS water, there was no overall effect of pH (p= 0.3303), but a significant overall inhibitory effect of Cu (p=0.0134), and no interactive effect (p= 0.0883). There was a significant 70% reduction in gill PEG clearance rate at pH 4 with the addition of Cu in RS water (Figure 9.3F). Drinking rates were in the general range of 5-15 ml kg-1 h-1 (Figure 9.3G, H, I). In control water, there was a strong overall effect of pH (p<0.0001), no overall effect of Cu (p= 0.5984) and a significant interactive effect (p=0.001). Drinking rate was decreased significantly by almost 90% between pH 7 and pH 4 and also by 50% between pH 7 and pH 7 + Cu. In contrast, drinking rate significantly increased by 4.5-fold between pH 4 and pH 4 + Cu (Figure 9.3E). In RN water there was no overall effect of pH (p= 0.2483) or Cu (p= 0.9593), but there was a significant interaction effect (0.0233) on drinking rate. There were no significant differences among the treatment means (Figure 9.3F). In RS water, there was no overall effect of pH (p=0.2825) but there was an effect of Cu (p=0.022) such that drinking rate decreased in the presence of Cu. There was no interactive effect (p= 0.9448). There were no significant differences in drinking rate among the treatments (Figure 9.3G). 294 9.9 Discussion 9.9.1 Overview Both low pH and elevated copper caused osmoregulatory disturbances. The protective effects of DOC against the disturbances caused by copper were dependent on the source of the DOC and the water pH. In support of our first three original hypotheses: (i) low pH increased net loss rates of Na+ and Cl- in all water types, except RN where ion loss rates were actually lower at pH 4 than at pH 7 (Figure 9.1). (ii) Cu also increased the net loss rates of two of the major ions (Na+ and Cl-), effects which were associated with the concentration of free Cu2+ ions in solution, as estimated by speciation modeling (Figure 9.1, Table 9.1). This was further confirmed by the regression analyses where there were significant, negative correlations between all net ion flux rates (Na+, K+, Cl-) and %free copper ion (Cu2+) such that as %free Cu2+ increased, net flux rate became more negative (Figure 9.4). There were no other significant relationships between %free Cu2+ ion and any of the other physiological parameters (Appendix G, Table SG1). The highest ion loss rates were all at pH 4, with the greatest loss rates in control water (91% Cu2+) intermediate loss rates in RS (58 %Cu2+) and smallest loss rates in RN water (33 %Cu2+). (iii) RN water did provide much better protection than RS water against these ionoregulatory disturbances of low pH and Cu, reflecting the high concentration of very allochthonous DOC in the RN. The RS response pattern generally resembled the control response pattern (Figure 9.1). We had hypothesized (iv) that other osmoregulatory parameters that have not been previously evaluated with respect to low pH and elevated Cu (diffusive water flux, paracellular permeability, drinking rate) would exhibit the same response patterns as the net ion flux rates. Our data did not support this. With low pH and with the addition of Cu, we observed an increase in net ion loss rates (Figure 9.1). In contrast, in many cases there was an inhibition of water 295 transport and drinking rates (Figure 9.3), suggesting that different mechanisms were involved. (v) Given the previously described coupling between Na+ uptake and ammonia excretion via Rh-mediated Na+/NH4+ exchange, we had hypothesized that experimental solutions that disturbed Na+ balance and exacerbated net loss would likely inhibit ammonia excretion. Our results were generally supportive of this idea: at low pH and with the addition of Cu, net Na+ loss rate increased in most experimental waters (Figure 9.1A), while ammonia excretion rate decreased in all water types (Figure 9.2A). Our final hypothesis (vi) was not confirmed. In contrast to prediction, urea-N excretion rate followed the response pattern of ammonia excretion, also decreasing in experimental conditions that disturbed Na+ balance (Figure 3), suggesting some commonality in the mechanism(s) involved. 9.9.2 Water chemistry greatly affects the speciation of Cu Speciation modeling showed that, in most of the experimental waters, the most abundant Cu form was Cu bound to DOC, which was most often followed by %Cu2+ as the second largest component. There was a higher %Cu2+ and a lower %Cu-DOC at pH 4 compared to pH 7 (Table 9.2). Control + Cu had the highest %Cu2+, followed by RS + Cu. RN + Cu had the lowest %Cu2+ and the highest %Cu-DOC at both pHs, reflecting differences in absolute DOC concentrations (Table 9.2). As mentioned in the Methods, an important caveat with the speciation modeling is that it treats all DOCs as the same. While we did run two scenarios, considering all DOC as 100% fulvic acid or as 100% humic acid, it had only minor effects on the outcome. From previous optical data (Holland et al. 2017; Sadauskas‐Henrique et al. 2025), it is clear that the compositions (i.e. chemical makeup of the molecule) of RN and RS DOCs are quite different. As the composition varies, so does the protective nature and metal-binding capacity of the DOC (Al- 296 Reasi et al. 2011, 2013; Sadauskas‐Henrique et al. 2019; Morris et al. 2024c, see Chapter 4). This is mirrored in the differences in the physiological responses to RN and RS DOCs in the presence and absence of Cu at neutral and acidic pH, in this study and in previous work (Crémazy et al. 2016, 2019). While the speciation modeling is valuable in predicting metal toxicity, it is important to recall that the differences in DOCs, which certainly influence the physiological response and metal binding capacity, are not reflected in the model. 9.9.3 RN DOC provides protection against ionoregulatory disturbances caused by low pH or Cu. Fish species in the Order Cichliformes, including dwarf cichlids, have a unique, pH-sensitive low affinity ion transport system and a relatively pH-insensitive diffusive impermeability to major ions. This system allows for generally low rates of Na+ uptake and greatly limits but not eliminates a net ion loss at low pH (Gonzalez et al. 2002, 2005; Wood et al. 2003; Duarte et al. 2013; Val and Wood 2022). This results in an energetically economical ionoregulatory strategy (Gonzalez and Dunson 1987). Our results (Figure 9.1) agreed with the response pattern shown in discus angelfish (Duarte et al. 2013) and other RN cichlids (Gonzalez et al. 2002, 2005). In control water, we observed an increase in net Na+ and Cl- loss rates with the addition of Cu however, this response was much less in RN water (Figure 9.1). A similar trend was reported by Crémazy et al. (2022) in the dwarf cichlid. Generally, for each measured ion, there was a predictable response trend for control water and RS water whereby both low pH and the addition of Cu increased net ion loss (Figure 9.1). However, with RN water the response trend differed from that of control and RS waters, and there were no significant changes in net ion flux rate for 297 any of the ions measured. It is possible that RN DOC mitigated the negative effect of both low pH (by physiological actions) and of added Cu (by complexation of Cu2+). 9.9.4 Cu decreases water transport through tight junctions and transcellularly as a function of water chemistry Diffusive water flux was used as a proxy for transcellular water movement (Figure 9.3A) and gill PEG clearance rate (Figure 9.3B) as a proxy for water movement through tight junctions. These data provide only the second measurements of both water transport pathways in the same Amazonian fish. As in that study on the Amazonian oscar (Astronotus ocellatus) (Wood et al. 2009) where severe hypoxia greatly decreased diffusive water permeability while PEG permeability remained unchanged, the current data show inconsistencies in pH and Cu responses between the two metrics of water flux. Nevertheless, in both studies, the diffusive permeability was more than an order of magnitude greater than PEG permeability, and the patterns did not coincide with those observed for ion fluxes (Figure 9.1). It would appear that water fluxes are uncoupled from ion fluxes in response to the environmental challenges of the present experiments. One caveat in the interpretation of our results is that to our knowledge, there is no information on whether Cu and/or low pH can differentially affect gill 3[H]PEG-4000 permeability relative to true gill paracellular water permeability Generally, DOCs that are rich in humic-acids have long aliphatic chains, which contribute to the surfactant properties of the molecule (Thurman 1985). As mentioned above (see Introduction) previous optical data have shown that RN DOC has more relative %humic-acid-like fluorescent signatures compared to RS (Holland et al. 2017). In a prior study on marine flatfish, DOCs that were more humic-acid rich increased diffusive water flux rate (Morris et al. 298 2024a, see Chapter 8). Likewise, in the present study we observed a significant increase in diffusive water flux rate between pH 7 control and RN pH 7 (Figure 9.3A), likely due to the humic acid content. In both control water at pH 4 and in RN water at pH 7, there were significant decreases in diffusive water flux rate with the addition of Cu (Figure 9.3A). The same also occurred with PEG permeability in RN water at both pH 7 and 4 with the addition of Cu. This suggests that Cu may reduce both transcellular and paracellular permeability to water. This conclusion fits with the well-known ability of copper to block aquaporins (i.e. diffusive water permeability) (Zelenina et al. 2004), but is inconsistent with the equally well-known ability of Cu to disrupt tight junctions (Ferruzza et al. 1999), thereby increasing paracellular permeability. On the other hand, Cu has been shown to decrease the relative expression of important mRNA tight junction markers in the gill, including occludin, claudin b, claudin 3 and claudin 12 (Wang et al. 2015). Given that our data are the first showing the effect of Cu on both water transport pathways in any fish species, further investigation is required. The drinking rates of dwarf cichlids were relatively high (5-15 ml kg-1 h-1, Figure 3G, H, I). While it is often thought that freshwater fish do not drink, this is not true, especially in small fish, as reviewed by Al-Reasi et al. (2016) who reported drinking rates of 2-4 ml kg-1 h-1 in zebrafish of similar size at slightly lower temperature than the present study. High drinking rates in the present dwarf cichlids were likely due to both the high temperature (29°C) and very small size (mean = 268 mg). Using a standard allometric scaling coefficient of 0.75, a drinking rate of 15 ml kg-1 h-1 in a typical 268 mg dwarf cichlid would scale to a rate of only 1.9 ml kg-1 h-1 in a 1-kg fish. Notably, in partial agreement with the present study, Al-Reasi et al. (2016) reported no 299 effects of different DOC types in combination with low pH on drinking rate in zebrafish, though they did not see an inhibitory effect of pH alone in control water. 9.9.5 Cu tends to inhibit nitrogenous waste excretion rates An increase in ammonia excretion rate at low pH in the presence of RN DOC has been previously reported in stingrays (Wood et al. 2003), tambaqui (Sadauskas‐Henrique et al. 2019) and zebrafish (Sadauskas‐Henrique et al. 2021). Our data show a slight increase in mean ammonia excretion rate between RN at pH 7 and RN at pH 4 although not statistically significant (Figure 9.2B). It has been suggested that DOC helps maintain Na+ coupling to ammonia excretion (Duarte et al. 2016) via the Rh metabolon (Wright and Wood 2009, 2012). Our data support this as we observed no statistically significant changes in net Na+ flux rate between RN pH 7 and RN pH 4 but noted a trend of decreased net Na+ loss at pH 4 (Figure 9.1B). Indeed, between pH 7 and pH 4 in both control water and RS water there was a trend of increased net Na+ loss that corresponded to a slight decrease in ammonia excretion rate (Figure 9.1A, C, Figure 9.2A, C). It has been suggested that the composition of the DOCs will influence both the ammonia and urea-N excretion rates, at least in sea water (Morris et al. 2024a, see Chapter 8). DOCs with a higher amino acid content resulted in a higher ammonia excretion rate (Morris et al. 2024a, see Chapter 8). Indeed, RS DOC has previously been reported to have a higher %amino acid-like content (tyrosine and tryptophan) compared to RN DOC (Sadauskas‐Henrique et al. 2025). Coincidently we observed a slight increase in the mean ammonia excretion rates between control water and RS water. In both freshwater and seawater fish, a common response to Cu exposure is inhibition of ammonia excretion. Indeed, Lim et al. (2015) reported that Cu inhibits both ammonia uptake and 300 excretion in juvenile rainbow trout, at the same Cu concentration used in the present study. This implicated bi-directional Rh glycoproteins as a target for Cu toxicity (Lim et al. 2015). In agreement, our study showed that the addition of Cu to each water type at both pHs resulted in a trend of inhibition of ammonia excretion (Figure 9.2A, B, C). Although the extent of urea movement through the transcellular pathway in freshwater fish remains unclear, there is evidence that many species have urea transporters (UT) that facilitate diffusive transport of urea through the gills (McDonald et al. 2006, 2012). It has been suggested that amino-acid rich DOCs not only increase ammonia excretion rates as described above but decrease urea-N excretion rates (Morris et al. 2024a, see Chapter 8). There was a statistically significant (p<0.0001) reduction in urea-N excretion rate between control pH 7 and RS pH 7 and a notable trend between control pH 4 and RS pH 4 (Figure 9.2D, F). With regard to the effect of Cu, the urea-N excretion rate response pattern (Figure 9.2D,E,F) mirrored that of ammonia exertion rate (Figure 9.2A, B, C). Cu consistently, although not always significantly, inhibited urea-N excretion. This was contrary to what we had predicted. This inhibitory effect of Cu on both ammonia and urea-N excretion does not seem to relate to the %Cu2+ (free ion), as the inhibitions of excretion rates do not become greater when there was a higher %Cu2+, at low pH (Table 9.2, Figure 9.2). It is possible that Cu is acting directly to inhibit the UTs as well as the Rh proteins, as suggested above. Alternately, or additionally, Cu inhibition of aquaporins may be involved, as argued above for the inhibitory effects of Cu on diffusive water fluxes. It has been reported that some aquaporin subtypes found in teleost gills have the ability to transport both ammonia and urea-N in vitro (Cutler et al. 2007; Tipsmark et al. 2010; Chen et al. 2010; Kolarevic et al. 2012; Ip et al. 2013). However, these measurements 301 showing the effect of Cu on urea-N excretion in vivo are the first to our knowledge, so further studies will be necessary. 9.10 Concluding remarks The present work shows that the detrimental effects of Cu on osmoregulatory processes in dwarf cichlids depends on the water composition and pH. The present study focused on the effects of pH, Cu and DOCs within natural waters. It is important to recognize that, in an effort to truly represent the response differences induced by the natural waters, we used intact waters and did not experimentally manipulate individual aspects of their composition such as the concentrations of DOC and individual ions. These could also be important in the physiological responses observed, and should be evaluated in future studies. Increases in anthropogenic activities including, mining, agriculture and industrial practices have led to elevation in metal pollutants in Amazonian water, including Cu (Moulatlet et al. 2023; Braz-Mota et al. 2024; Echevarría et al. 2024). Based on our findings, increases in Cu in the RN, at the natural low pH of this river, would not be too problematic for the fish species used in this study. However, the same concentration of dissolved Cu in the RS, particularly at low pH, would be a greater threat to this fish and possibly other local species. In that respect, the particles that are normally abundant in RS water (but removed in our experiments) would likely provide protection by greatly reducing the dissolved Cu concentration (Crémazy et al. 2016, 2019, 2025). The greater protection provided by RN against dissolved Cu is likely due to its higher concentration of DOC (Table 9.1) as well as the different DOC compositions (Holland et al. 2017). The Cu speciation results can, in some cases, explain the physiological effects of Cu, simply on the basis of bioavailability of the free Cu2+ ion. However, there were also physiological functions for which 302 the addition of Cu had pronounced inhibitory effects even when there was negligible free Cu2+ present. Indeed, the regression analyses showed significant negative correlation between net Na+, K+ and Cl- flux rates against % free Cu2+ ion (Figure 9.4) but no significant relationships between any of the other physiological parameters measured and % free Cu2+ ion (Appendix G, Figure SG1). Given that our study provides the first data on these negative actions of Cu on urea-N excretion rates and on both water transport pathways through the gills, additional mechanistic studies are necessary. Further knowledge of the mechanism(s) by which Cu disturbs osmoregulatory processes, as well as the role of water chemistry, may help inform guidelines for Cu pollution levels in different areas across the Amazon basin. 303 9.11 Chapter 9 – Tables Table 9.1 Water characterization summary of INPA (control), Rio Negro (RN) and Rio Solimões (RS) waters. Means ± standard error (SEM; N) Parameter Control RN RS [DOC] (mg L-1) 0.60 ± 0.08 (N=5) 9.3 ± 0.09 (N=12) 5.6 ± 0.3 (N=7) [Na] (µmol L-1) 101.8 ± 12.8 (N=4) 69.9 ± 18.6 (N=4) 325.6 ± 14.5 (N=4) [K] (µmol L-1) 25.2 ± 3.9 (N=4) 18.8 ± 1.5 (N=4) 61.5 ± 11.7 (N=4) [Ca] (µmol L-1) 12.0 ± 3.9 (N=4) 13.2 ± 2.4 (N=4) 355.0 ± 3.9 (N=4) [Mg] (µmol L-1) 2.2 ± 0.8 (N=4) 4.9 ± 0.6 (N=4) 52.7 ± 3.4 (N=4) [Cl] (µmol L-1) 10.6 ± 1.9 (N=4) 6.6 ± 2.5 (N=4) 37.1 ± 4.8 (N=4) Background [Cu] (µg L-1) 4.0 ± 0.5 (N=2) 5.0 ± 0.5 (N=2) 6.0 ± 1.5 (N=2) Total [Cu] (µg L-1) 150 ± 26.6 (N=2) 153 ± 15.3 (N=2) 166 ± 39.4 (N=2) 304 Table 9.2. Relative percentages of the main chemical forms of Cu in the experimental waters, as calculated by WHAM VII. %Cu2+ %CuHCO3+ %CuOH+ %Cu(OH)2 %CuCO3 %Cu-DOC Control 7 + Cu 27.35 0.26 10.88 0.29 9.84 51.38 Control 4 + Cu 90.70 1.31 0.005 0.00 0.07 7.88 RN 7 + Cu 0.05 0.00 0.02 0.00 0.02 99.91 RN 4 + Cu 33.07 0.46 0.02 0.00 0.02 66.43 RS 7 + Cu 1.57 0.06 0.68 0.02 2.70 94.96 RS 4 + Cu 58.54 2.60 0.03 0.00 0.12 38.70 305 Table 9.3. Urea-N excretion as a percentage of total waste-N excretion (mean ± SEM) at pH 7 and 4 with and without the addition of nominally 200 µg L-1 of Cu in INPA (control), Rio Negro (RN) and Rio Solimões (RS) water. Control RN RS pH 7 29.7 ± 2.8 (N=6) 16.0 ± 4.8 (N=6) 7.9 ± 2.1 (N=8) pH 7 + Cu 33.2 ± 9.6 (N=7) 9.4 ± 1.76 (N=7) 8.7 ± 2.0 (N=8) pH 4 26.6 ± 8.2 (N=7) 17.9 ± 2.3 (N=7) 11.1 ± 1.7 (N=7) pH 4 + Cu 20.0 ± 7.2 (N=6) 31.9 ± 9.9 (N=8) 13.2 ± 6.9 (N=7) 306 9.12 Chapter 9 – Figures 307 Figure 9.1. The effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on net Na+ flux rate (A) in control INPA water (overall effect of pH: p=0.0078, Cu: p=0.1586, interaction: p=0.7849), (B) in RN water (overall effect of pH: p=0.5532, Cu: p=0.2634, interaction: p=0.0984) and (C) in RS water (overall effect of pH: p=0.0652, Cu: p=0.2552, interaction: p=0.4765), on net K+ flux rate (D) in control water (overall effect of pH: p=0.0513, Cu: p= 0.9686, interaction: p= 0.7194), (E) in RN water (overall effect of pH: p=0.4747, Cu: p=0.0990, interaction: p=0.1836) and (F) in RS water (overall effect of pH: p=0.0766, Cu: p=0.1836, interaction: p=0.6463), and on net Cl- flux rate (G) in control water (overall effect of pH: p=0.0399, Cu: p=0.0027, interaction: p=0.3488), (H) in RN water (overall effect of pH: p= 0.5230, Cu: p= 0.8311, interaction: p=0.0399) and (I) in RS water (overall effect of pH p=0.0004, Cu: p= 0.3945, interaction: p= 0.9519). Data are means ± SEM, N=6-8. Bars not sharing the same letters are significantly different (p < 0.05) (Two-way analysis of variance with Tukey’s test). 308 Figure 9.2. The effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on ammonia-N excretion rate (A) in control INPA water (overall effect of pH: p=0.5773, Cu: p<0.0001, interaction: p=0.1602), (B) in RN water (overall effect of pH: p=0.1693, Cu: p=0.0034, interaction: p=0.0215) and (C) in RS water (overall effect of pH: p=0.9253, Cu: p=0.0012, interaction: p=0.2303), and on urea-N excretion rate (D) in control water (overall effect of pH: p=0.2823, Cu: p=0.0006, interaction: p=0.9801), (E) in RN water (overall effect of pH p=0.2970, Cu: p=0.0002, interaction: p=0.0585) and (F) in RS water (overall effect of pH: p=0.4385, Cu: p=0.0311, interaction: p=0.6906). Data are means ± SEM, N=6-8. Bars not sharing the same letters are significantly different (p < 0.05) (Two-way analysis of variance with Tukey’s test). 309 310 Figure 9.3. The effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on diffusive water flux rate (A) in control INPA water (overall effect of pH: p=0.2315, Cu: p=0.4845, interaction: p=0.0011), (B) in RN water (overall effect of pH: p=0.1436, Cu: p=0.2950, interaction: p=0.0039) and (C) in RS water (overall effect of pH: p=0.1812, Cu: p=0.7535, interaction: p=0.9251), on gill PEG clearance rate (D) in control water (overall effect of pH: p=0.1161, Cu: p=0.0873, interaction: p=0.6411), (E) in RN water (overall effect of pH: p=0.2167, Cu: p=<0.0001, interaction: p=0.2888) and (F) in RS water (overall effect of pH: p=0.3303, Cu: p=0.0134, interaction: p=0.0883) and on drinking rate (G) in control water (overall effect of pH: p<0.0001, Cu: p=0.5984, interaction: p=0.001), (H) in RN water (overall effect of pH: p=0.2483, Cu: p=0.9593, interaction: p=0.0233) and (I) in RS water (overall effect of pH: p=0.2825, Cu: p=0.022, interaction: p=0.9448). Data are means ± SEM, N=6-8. Bars not sharing the same letters are significantly different (p < 0.05) (Two-way analysis of variance with Tukey’s test). 311 Figure 9.4. The effect of %free copper ion (Cu2+) on net (A) Na+, (B) K+ and (C) Cl- flux rates. Data at nominal total Cu concentrations of 200 µg L-1 in control water, RN water, and RS water, at both pH 7 and pH 4 have been combined in these relationships. Values are means ± SEM, N=6-8. Relationships were assessed with simple linear regression (p < 0.05 is considered significant). 312 Chapter 10: General Discussion and Conclusions. This section of the thesis integrates the major findings of the work and addresses the original goals of the thesis, discusses the potential environmental and regulatory implications of the results and offers suggestions for future research. Methodological and analytical caveats have been described in each individual chapter. The overall hypothesis of the thesis, that DOCs and major ions have independent and interactive effects on physiological processes at the gills which are due to specific chemical composition or moieties of the DOC molecules that are pH-dependent, was supported. My results indicated that natural DOCs alone alter physiological processes at the gill (Chapters 4, 8 and 9). There are both independent effects of major ions (Na+ and Ca2+) (Chapter 6, 7, 8) and copper (Chapter 9) as well as interactive effects with DOCs (Chapters 6, 8, and 9). I demonstrated, using natural DOCs from different sources (characterized and tested in Chapters 3 and 4) and model compounds (characterized and tested in Chapter 5), that the specific chemical composition and chemical moieties of DOC molecules likely play a role in their physiological effects (Chapters 4, 5, 6, 8, and 9). Additionally, both the physicochemical properties of DOCs (Chapter 3) and the physiological responses to DOCs (Chapters 4, 6, and 9) are pH-dependent. 10.1 Physicochemical characterization indices of DOCs and acute physiological responses to DOCs are pH-dependent. The first goal of the thesis was (i) to investigate how ambient acidic water influences DOC physicochemical characterization indices and the ability of DOCs to elicit changes in fish physiology. DOCs themselves influence water pH, and in turn, changes in water pH potentially alter the physiochemistry and function of DOCs. Prior to the present studies, the effects of pH on 313 optical and chemical indices often used to characterize DOC and their inter-relationships were not well understood. In most previous works, optical indices were determined at a fixed pH (often pH 7) meaning that the application of those indices to characterize source waters were only valid when comparisons were made at the same fixed pH, although this was often not realized by water chemists. Chapter 3 demonstrates that the physicochemical indices used to characterize DOCs that have varied properties are pH-dependent and therefore should be carefully interpreted (Figure 10.1A). Apparent aromaticity (SAC340), apparent molecular weight (MWI) and molecular charge all generally decreased with low pH while lipophilicity (log Kow) increased (Figure 10.1A). However, many of the changes in the indices observed at pH 4 compared to pH 7 are likely not changes in composition (i.e. chemical makeup of the molecule) of the DOCs but rather alterations in conformation (i.e. spatial arrangement of the molecule) of the DOC structure that are reflected in the optical signatures (e.g. SAC340, MWI). In contrast, chemical indices based on titration properties and octanol-water partitioning, including lipophilicity, molecular charge, and Proton Binding Index (PBI) change with pH due to alterations in the DOC molecules that result from proton binding. These changes in DOCs at acidic pH are mirrored in the physiological responses of rainbow trout (Chapters 4, 6) and dwarf cichlids (Chapter 9). TEP, a biological indicator of osmoregulatory function (Galvez et al. 2008) generally becomes more positive in response to low pH alone and more negative in response to fresh natural DOCs (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019). DOCs spanning different origins and characteristics were tested in this thesis. DOCs that were more allochthonous, more aromatic, less lipophilic and with higher molecular charge (Luther Marsh (LM), Ancient Pond (AP) and Ancient Swamp (AS)) resulted in a more negative TEP at both pH 7 and pH 4 in rainbow trout. In contrast, DOCs with 314 the opposite properties (Lake Ontario (LO) and Preston Flats (PF)) resulted in a more positive TEP at pH 7 and a more negative TEP at pH 4 (Chapter 4). The opposite effects of LM and LO were re-confirmed in Chapter 6. These changes in TEP could be due to changes in DOC conformation and proton binding. Two particularly important indices were identified as predictors of changes in TEP across pHs in rainbow trout: SAC340 and log Kow. The decrease in SAC340 at low pH may reflect changes in the conformation of aromatic groups of the DOC molecule, through condensation of the molecules and protonation/deprotonation reactions (Pace et al. 2012) which in turn may have contributed to the change in TEP. DOCs ability to interact with the gill membrane and affect TEP may be influenced by lipophilicity where greater lipophilicity may favour interaction with the cell membranes of the gills (Figure 10.2). As negative binding sites on DOC become protonated (at pH 4 compared to pH 7) lipophilicity will increase. Likewise, the negative charge on the gills may be titrated at low pH, potentially increasing the interaction between the gill and DOC via hydrogen sorption or hydrophobic bonding (Campbell et al. 1997) (Figure 10.2). Studies on the pH-dependency of DOC effects on metal uptake by green algae have suggested comparable interactions (Boullemant et al. 2009; Boullemant et al. 2011). The pH-dependent physiological effects of DOC extended to other physiological measurements in waters containing different types of DOCs (Chapter 9). Rio Negro (RN) blackwater (low ions, high DOC) and Rio Solimões (RS) whitewater (higher ions, intermediate DOC) had different physiological effects on dwarf cichlids from one another and at pH 7 and pH 4. Low pH increased net loss rates of Na+ and Cl- in control water (intermediate ions, very low DOC) and RS water, whereas ion loss rates were actually lower at pH 4 than at pH 7 in RN water. A trend of increased ammonia excretion rate between RN at pH 7 and RN at pH 4 was also 315 observed. Not only does the concentration of DOC differ between RN and RS water, so does the composition of the DOC. Previous optical measurements reported RN DOC to be more allochthonous, more aromatic and with a higher % humic acid-like content in comparison to RS DOC (Holland et al. 2017; Sadauskas‐Henrique et al. 2025). RN water provided much better protection than RS water against ionoregulatory disturbances caused by low pH in dwarf cichlids. This may be due to the physicochemical characteristics of RN versus RS DOC and the pH-related changes. 10.2 The interactive effects of water quality parameters (pH, major ions, or copper) and DOC on ionoregulatory function The second goal of this thesis was (ii) to determine whether DOCs and major salt ions (Na+, Ca2+) or copper have independent and/or interactive effects on physiological processes at the gills. The results confirmed that there are independent effects of DOC and major ions (Na+ and Ca2+) in freshwater rainbow trout, of DOC and salinity in seawater flatfish (Chapter 6, 7, 8), and of DOC and copper in Amazonian freshwater dwarf cichlids (Chapter 9). Interactive effects with DOCs (Chapters 6, 8, and 9) were also observed (Figure 10.1B). While the effects of low pH (McWilliams and Potts 1978; Wood et al. 1998, 2020, 2025), DOC (Galvez et al. 2008; Sadauskas‐Henrique et al. 2019) and increased major ions (Wood et al. 2020, 2025; Po and Wood 2021) on TEP have been described, the interactive effects of all three parameters were not previously well understood. Elevated ambient concentrations of NaCl or CaCl2 resulted in increases in absolute TEP values in rainbow trout (Chapter 6). The baseline TEP control value was rendered less negative by a change in pH from 7 to 4, however, the relationship between the salt concentration and the absolute TEP response was not greatly 316 altered. Upon the addition of DOC, at pH 7 the baseline TEP values were shifted in a negative direction by allocthochonous DOCs (LM) but a positive direction by autochthonous (LO) DOC, while at pH 4.0, both LM and LO caused hyperpolarization. The TEP response curves to NaCl or CaCl2 were qualitatively similar to those observed previously, but they were dependent on the pH and the DOC present. As pH influences the physiochemistry of DOC (as described above) it may likewise influence how Na+ or Ca2+ interacts with the gill. Coincidentally, the increase in salt concentration may also influence DOC properties. Both ambient pH and ionic strength are thought to alter the molecular conformation of DOC (Tipping and Hurley, 1988). It is possible that the differential responses observed in Chapter 6 are due to conformational or molecular changes in the DOCs which result in changes in the differential permeability of Na+ and Cl- at the gill as well as in the paracellular permeability, thereby altering TEP. Marine flatfish, including Pacific sanddab and rock sole, routinely encounter large fluctuations in salinity (Schreiber 2001; Ruiz-Jarabo et al. 2015). Acute exposure to reduced salinities in both species resulted in increases in diffusive water flux rates, ammonia excretion rates, and the apparent greater reliance on protein as a metabolic fuel, none of which were coupled to changes in ṀO2 (Chapters 7 and 8). In Pacific sanddab, reduced [Ca2+], rather than reduced salinity itself, was the primary cause for the increases in diffusive water flux at low salinity (Chapter 7). The effects of DOC in Pacific sanddab were dependent upon both salinity and source. The allochthonous DOC (LM) tested increased diffusive water flux rate at 30 ppt while urea-N excretion rate decreased in response to the autochthonous DOC (LO) at 30 and 7.5 ppt, reflecting changes in both gill function and the physicochemistry of DOCs between 30 and 7.5 ppt (Chapter 8). The optical characteristics of the two DOCs were salinity-dependent, suggesting that there may be conformational changes such as condensation of the DOCs. As a 317 result, chemical moieties that may interact with the gill may no longer be accessible for interaction leading to altered physiological responses (Chapter 8). Returning to fresh water, my examination of natural RN and RS waters that were filtered to remove particles but otherwise intact again indicated interactive effects among DOC, ion concentration, and copper (Chapter 9) (Figure 10.1B). Acute copper exposure tended to increase ion losses, inhibit urea-N excretion as well as ammonia excretion, and decrease branchial water transport both transcellularly and through tight junctions in dwarf cichlids. Most of these effects were exacerbated at low pH (Chapter 9). RN water provided more protection against these disturbances, possibly due to the difference in DOC concentration and water composition but also likely due to the physicochemical differences in the DOCs themselves (Holland et al. 2017). 10.3 Identifying specific physicochemical moieties of DOC that are responsible for the altered osmoregulatory function using natural DOCs and model compounds. The third goal of the thesis was (iii) to identify the specific physicochemical properties of DOCs that are responsible for the altered osmo- and iono-regulatory function. Using natural DOC sources spanning a wide variety of characteristics and model compounds representing key chemical moieties of natural DOCs, I found that specific chemical groups of the DOC molecules likely play a role in the physiological responses (Chapters 4, 5, 6, 8, and 9) (Figure 10.1C). Based on similarity of physicochemical characteristics, two distinct groups of natural DOCs were tested. The first group was LO and PF which were less aromatic, more autochthonous, and more lipophilic, with smaller apparent molecular weights, lower PBIs, and lower absolute charges. In contrast the second group, LM, AP, and AS, were more allochthonous, more aromatic, less lipophilic with larger apparent molecular weights, and they 318 had higher PBIs and absolute charges (Chapter 3). Interestingly the trends in TEP responses were similar between the DOCs that shared characteristics. At pH 7, LO and PF resulted in a more positive TEP whereas LM, AP, and AS resulted in a more negative TEP (Chapter 4). At pH 4, all 5 DOCs caused a more negative TEP, which would support Na+ uptake and oppose Na+ efflux at the gills, effects which are beneficial to ionoregulatory function. This pH-dependent change may be due to changes in DOC conformation and/or changes in net charge on the DOC due to proton binding as described above and shown in Figure 10.2. Guided by the correlations between physicochemical characteristics and TEP responses, out of 20 tested model compounds, 3 were identified as appropriate for further physiological studies (tannic acid (TA), sodium dodecyl sulphate (SDS), bovine serum albumin (BSA) (Chapter 5) (Figure 10.1C). TEP responses to TA and SDS were similar to those of the second group of natural DOCs (LM, AP, and AS), likely due to the shared aliphatic chains (SDS) and phenolic hydroxyl (TA) groups (Chapters 4, 5). The model compound BSA showed a similar TEP response to the first group of natural DOCs (LO and PF), possibly due to the shared peptide and amino acid groups (Chapters 4, 5). Based on the weight of evidence approach presented in Chapter 6, hydroxyl groups and long aliphatic chains may increase both Na+ and Ca2+ toxicity at pH 7, whereas peptides and amino acids may decrease both Na+ and Ca2+ toxicity. Natural humic-acid rich DOCs (LM - Chapter 3, RN - Holland et al. 2017) were found to increase diffusive water flux rates in both seawater and freshwater which likely can be attributed to the presence of long aliphatic chains (Chapters 8, 9). In seawater, this trend was also observed with the model compound SDS, again suggesting the role of aliphatic chains (Chapter 8). The composition of DOCs also influenced ammonia excretion rates in both seawater and freshwater. Exposure to DOCs with higher amino 319 acid and peptide content (LO - Chapter 3, RS - Sadauskas‐Henrique et al. 2025) resulted in an increase in ammonia excretion rates (Chapter 8, 9). In seawater this was also the case when peptide- and tyrosine-rich BSA was tested (Chapter 9). 10.4 DOCs influence osmoregulatory processes at the gills in fish with different ionoregulatory strategies. The fourth and final objective of this thesis was (iv) to investigate how DOCs influence osmoregulatory processes at the gills in fish with different ionoregulatory strategies. To carry out this goal, three species with unique ion transport systems were used. (1) The rainbow trout has a “standard” freshwater teleost transport system where active ion uptake is employed to combat passive ion loss. Na+ uptake occurs through a Na+/H+ antiporter (NHE) which exports H+ and/or an electrogenic apical V‐ H+ ATPase that also exports H+, energizing Na+ entry via an apical channel (Randall and Lin 1993; Kirschner 2004). (2) Marine flatfish have a typical marine ion transport system whereby ions are actively excreted and passively taken up. This occurs through paracellular efflux of Na+ in equal amounts to the active Cl- efflux through the transcellular pathway (Silva et al. 1977; Wood and Marshall 1994; Evans et al. 2005; Edwards and Marshall 2012). (3) The freshwater dwarf cichlid of the Brazilian Amazon has a unique low affinity ion transport system with very tight regulation of Na+ efflux at low pH (Gonzalez et al. 2002, 2005; Duarte et al. 2009, 2013, 2024; Val and Wood 2022; Crémazy et al. 2022). Generally, this system supports low rates of Na+ uptake and greatly limits net ion loss at low pH (Gonzalez et al. 2002, 2005; Wood et al. 2003; Duarte et al. 2013; Val and Wood 2022). The TEP in freshwater fish is an outwardly directed diffusion potential between the blood plasma and the external water, which is predominately due to the differential permeabilities of 320 Na+ versus Cl- at the gill (Potts 1984). In marine fish, the origin of the TEP is quite different as, in addition to the diffusive component (now inwardly directed), electrogenic aspects of active Cl- excretion also contribute to the TEP (Potts 1984). When freshwater fish, such as the rainbow trout are in control freshwater (i.e. 0 ppt) the baseline TEP is negative (blood relative to the water), whereas in marine fish including Pacific sanddab, at 30 ppt the TEP value is positive and in 7.5 ppt it is negative. This reflects the transition from a predominately electrogenic potential in seawater towards a diffusion potential in less saline water (Potts 1984; Wood and Grosell 2008). Given that the origin of TEP differs between the model freshwater (Chapter 4) and seawater fish (Chapter 8) studied in this thesis, it is perhaps not surprising that the TEP responses to the DOC and model compounds tested in their respective control waters were different. At pH 7 in freshwater, there was an increase in TEP (i.e. more positive) in response to both LO and BSA and a decrease in TEP (i.e. more negative) in response to LM, TA and SDS in rainbow trout (Chapters 4, 5). In Pacific sanddab, at full strength seawater (30 ppt) there was no significant effect of LO, TA or SDS on TEP. Similar to its actions in freshwater rainbow trout, LM caused a decrease in TEP, but in contrast, BSA likewise resulted in a decrease in TEP (Chapter 8). This may be a result of a conformational change in the DOCs and model compounds associated with ionic strength as described above, as well as the difference in the origin of TEP between the species. LM and RN DOCs share similar physicochemical characteristics in that they are both allochthonous, humic-acid rich DOCs, while LO and RS DOCs are autochthonous, more peptide-rich DOCs. It is important to note again that whole RN and RS waters were tested rather than isolated DOCs in Chapter 9. Nevertheless, despite the differences in ionoregulatory strategies between the marine flatfish and dwarf cichlids, similar DOCs elicited similar 321 physiological responses in these two species. In the Pacific sanddab at 30 ppt, diffusive water flux rates increased in response to LM, and ammonia excretion rates increased in response to LO, compared to control water at 30 ppt (Chapter 8). However, the dwarf cichlid exposed to Amazonian freshwaters, RN water resulted in increased diffusive water flux rates, but RS water resulted in decreased ammonia excretion rates (Chapter 9). It is therefore important to consider not only the physicochemical characteristics of the DOC and the water quality (e.g. pH, salinity, contaminants) but also the ionoregulatory strategy employed by the local fish species. 10.5 Environmental and regulatory considerations The ecological roles of DOC are not yet fully understood. The known influences of DOC, however, are widespread, influencing light and temperature fluctuations within the water column, microbial activity, nutrient transfer between trophic levels, and the bioavailability of contaminants. The results of the present study demonstrate that the ionoregulatory and osmoregulatory homeostasis of fish should be added to this list. All of these are likely to affect overall ecosystem health. To effectively monitor aquatic environments, a mechanistic understanding of the effects of DOC on ionoregulation in fish, considering the physicochemical characteristics and key chemical moieties of DOCs, water quality parameters (i.e. pH, ionic strength and potential contaminants) and the resident fish species is crucial. This is especially important as DOC concentrations are rising (Morris et al. 2021, see Chapter 2; Monteith et al. 2007, 2023; Sucker and Krause 2010; Erlandsson et al. 2010; Pagano et al. 2014; N’kaya et al. 2020; Drake et al. 2021; Sanwlani et al. 2022; Ramanathan et al. 2024; Wang et al. 2025) in fresh and estuarine waters coincidentally as pH values are falling (Clair et al. 2007; Krzyzanowski and Innes 2010; Phillips et al. 2015; Driscoll et al. 2016; Weiss et al. 2018; 322 Quijada-Rodriguez et al. 2021), freshwater salinization is increasing, and seawater is becoming more dilute. All of these are consequences of anthropogenic activities and climate change (Rogers et al. 1984; Sucker and Krause 2010; Pagano et al. 2014; Chun et al. 2018; Baena-Ruiz et al. 2020; Cao et al. 2020). Generally, environmental decisions and associated policy are guided by modeling which has the potential to increase our understanding of the environmental response to climate change and anthropogenic contaminants. A good example is the Biotic Ligand Model for predicting the toxicity of metals on the basis of water chemistry (DiToro et al. 2001; Niyogi and Wood 2004). This widely used regulatory model was founded on more than two decades of research directed at understanding the mechanistic nature of metal interactions with the gill and with other water chemistry components, including DOC, as well as the physiological responses underlying metal toxicity in aquatic organisms (reviewed by Mebane et al. 2020). The MIT model (EPRI 2018) that was evaluated in Chapter 6 for predicting major ion toxicity is another example, though it remains in a very early stage of development; much more mechanistic information is required. Further mechanistic research on the interactions of different types of DOC with pH, major ions, metals, and the gill surface itself will be required to develop models to predict how different DOCs affect the normal ionoregulatory functions of the gills in both freshwater and seawater fish. This understanding may result in further refinement of BLM and MIT models to protect aquatic environments. Therefore, while much more laboratory-based work is certainly required, some of the findings of this thesis could be first steps in informing water quality guidelines and improved regulatory frameworks for DOC. Some physicochemical characteristics (i.e. aromaticity, lipophilicity and molecular charge) and chemical moieties (i.e. phenolic hydroxyl groups, 323 aliphatic chains and peptides) of DOCs may be used to predict TEP effects in fish as an important biological indicator of osmoregulatory homeostasis or disturbance (Chapters 3, 4, 5). Key chemical moieties of DOC will likely play pH-dependent roles in both Na+ and Ca2+ toxicity, which may be predicted using a weight of evidence approach (Chapter 6). Overall, pH should receive greater consideration when determining the ecological role of DOCs within aquatic ecosystems and should be integrated into predictive models (Chapters 4, 5, 6, 9). The ratio of Ca2+ to salinity as well as the presence and specific components of DOC may influence the physiological ability of some marine fish to endure salinity extremes (Chapters 7 and 8). More physiological data will be required to fuel the modeling for the species used in this thesis, as well as for extrapolation across species and taxa and to explore the great diversities of DOCs that exist in different systems. This is an expansive area for future research. 10.6 Perspectives for future directions The results of each chapter of this thesis highlight the additional work that could be conducted particularly with respect to delineating the mechanisms by which DOC influences physiological processes. Considering the physicochemical characterization of DOC and the effect of pH (Chapter 3), a comprehensive characterization of spatial and temporal variation within sites across a wide range of pHs (rather than just fixed pHs of 7 and 4) should be performed. This would help illuminate variation of DOCs within and across sites and determine the sensitivities of the indices and DOCs to changes in pH. The experimental exposure times in this thesis were acute by design in an effort to gain more information on the mechanistic effects of DOC. For example, the TEP exposures throughout this study were generally less than 5 min (Chapters 4, 5, 6, 8). Changes in TEP 324 caused by acute exposures to major ions have been shown to persist and remain stable for 24 h (Wood et al. 2020) up to 96 h (Po and Wood 2022). It remains to be verified that this is also true of changes in TEP caused by exposure to different DOCs and pHs. Sustained changes in TEP would likely have profound osmoregulatory effects over time, so further investigation should be done to determine if changes in TEP are sustained beyond 96 h. Additionally, acute exposures do not allow for changes in different levels of biological organization such as changes in mRNA expression and cellular protein distribution. These could be very important for aquaporins and diffusive water fluxes (Chapters 7, 8, 9). Longer exposures and measurements of additional physiological endpoints would determine if cellular processes are also influenced by exposure to DOC and other water quality parameters. Ion and water fluxes as well as nitrogenous waste excretion rates were measured in flatfish and dwarf cichlids, but not rainbow trout. Integrating the effects of natural DOCs and model compounds on these additional physiological endpoints on a non-acidophilic teleost such as the rainbow trout could be the focus of future follow-up studies. Such studies should simultaneously consider other water quality parameters such as pH, hardness, alkalinity, major ion concentrations, and potential pollutants. The toxicity predictions presented in Chapter 6 were not based on actual toxicity testing, but rather on physiological endpoints associated with previously published LC50 values (Durand-Hoffman 1995). Further studies should use standardized testing in association with electrochemical modelling of DOC, pH, and major ion interactions on TEP to validate these predictions. Our understanding of the effects of DOC on marine fish is limited, reflecting the few studies completed to date. The present study employed only DOCs of freshwater origin, and examined only benthic species with low metabolic rates in Chapter 8. Future work should 325 explore the importance of the origin of the DOCs (marine versus freshwater), and should examine pelagic fish with higher metabolic rates. It should also further explore the mechanisms of action of DOC at the gill. Chapter 7 suggested but did not confirm that environmental calcium concentrations may also influence ammonia excretion rates in seawater fish, another topic for additional studies. The negative effects of copper on water transport pathways and ammonia and urea excretion through the gills, as seen in the dwarf cichlid in Chapter 9 constitute another area of particular interest, because they did not appear to be attributable to the free Cu2+ ion, in contrast to the well documented effects of Cu2+ on Na+ and Cl- flux rates. These effects would be evaluated in other Amazonian fish with a different ionoregulatory strategies such as the tambaqui (Gonzalez et al. 2006; Val and Wood 2022). Additionally, RN and RS water along with model compounds could be tested in other acidophilic Amazonian fish to determine the key chemical moieties of DOC acting on the gill for comparison with the species tested in this thesis. The areas for future studies outlined above could be some steps towards determining the exact protective mechanisms of DOC at the gill in diverse water chemistries. 326 10.7 Chapter 10 – Figures 327 Figure 10.1. (A) The physicochemical indices used to characterize DOC are pH dependent whereby a change in pH from 4 to 7 increases apparent aromaticity and molecular charge whereas a change in pH from 7 to 4 results in increased lipophilicity. (B) There are interactive effects of DOC, salt ions (Na+ and Ca2+) or Cu2+ and low pH on physiology and often times DOC protects or is beneficial against these physiological disturbances. (C) Three model compounds have been identified as useful and share key chemical characteristics with natural humic acid, a key component of DOC. Bovine serum albumin (BSA) is a peptide rich compound, tannic acid (TA) is highly aromatic and sodium dodecyl sulphate (SDS) is a surfactant with a long aliphatic chain. 328 329 Figure 10.2. The interaction between DOC and the gill at (A) pH 7 where the net charge of the gill and DOC molecule is negative (represented by “-”) and (B) pH 4 where the net charge of the gills and DOC are titrated by H+, so as to move toward neutral charge (represented by “H+”) and there is a conformational change in DOC and the interaction between the gill and DOC is likely increased due to hydrogen-bonding sorption or hydrophobic bonding, i.e. increased lipophilicity) 330 Bibliography Abookire AA, Piatt JF, Robards MD (2000) Nearshore fish distributions in an Alaskan estuary in relation to stratification, temperature and salinity. Estuar Coast Shelf Sci 51:45–59. https://doi.org/10.1006/ecss.1999.0615 Aladin NV, Potts WTW (1995) Osmoregulatory capacity of the Cladocera. J Comp Physiol B 164:671–683. https://doi.org/10.1007/BF00389810 Alberts JJ, Giesy JP, Evans DW (1984) Distribution of dissolved organic carbon and metal-binding capacity among ultrafilterable fractions isolated from selected surface waters of the southeastern United States. Environ Geol Water Sci 6:91–101. https://doi.org/10.1007/BF02509915 Al-Reasi HA, Scott Smith D, Wood CM (2012) Evaluating the ameliorative effect of natural dissolved organic matter (DOM) quality on copper toxicity to Daphnia magna: improving the BLM. Ecotoxicology 21:524–537. https://doi.org/10.1007/s10646-011-0813-z Al-Reasi HA, Smith DS, Wood CM (2016) The influence of dissolved organic matter (DOM) on sodium regulation and nitrogenous waste excretion in the zebrafish (Danio rerio). J Exp Biol jeb.139444. https://doi.org/10.1242/jeb.139444 Al-Reasi HA, Wood CM, Smith DS (2011) Physicochemical and spectroscopic properties of natural organic matter (NOM) from various sources and implications for ameliorative effects on metal toxicity to aquatic biota. Aquat Toxicol 103:179–190. https://doi.org/10.1016/j.aquatox.2011.02.015 Al-Reasi HA, Wood CM, Smith DS (2013a) Characterization of freshwater natural dissolved organic matter (DOM): Mechanistic explanations for protective effects against metal toxicity and direct effects on organisms. Environ Int 59:201–207. https://doi.org/10.1016/j.envint.2013.06.005 Al-Reasi HA, Yusuf U, Smith DS, Wood CM (2013b) The effect of dissolved organic matter (DOM) on sodium transport and nitrogenous waste excretion of the freshwater cladoceran (Daphnia magna) at circumneutral and low pH. Comp Biochem Physiol Part C Toxicol Pharmacol 158:207–215. https://doi.org/10.1016/j.cbpc.2013.08.004 Alsop DH, McGeer JC, McDonald DG, Wood CM (1999) Costs of chronic waterborne zinc exposure and the consequences of zinc acclimation on gill/zinc interactions of rainbow trout in hard and soft water. Environ Toxicol Chem 224:1014–1025 Alsop DH, Wood CM (1997) The interactive effects of feeding and exercise on oxygen consumption, swimming performance and protein usage in juvenile rainbow trout (Oncorhynchus mykiss). J Exp Biol 200:2337–2346. https://doi.org/10.1242/jeb.200.17.2337 331 Altinok I, Grizzle JM (2004) Excretion of ammonia and urea by phylogenetically diverse fish species in low salinities. Aquaculture 238:499–507. https://doi.org/10.1016/j.aquaculture.2004.06.020 Anesio AM, Granéli W (2003) Increased photoreactivity of DOC by acidification: Implications for the carbon cycle in humic lakes. Limnol Oceanogr 48:735–744. https://doi.org/10.4319/lo.2003.48.2.0735 Armor C, Herrgesell PL (1985) Distribution and abundance of fishes in the San Francisco Bay estuary between 1980 and 1982. Hydrobiologia 129:211–227. https://doi.org/10.1007/bf00048696 Audet C, Munger RS, Wood CM (1988) Long-term sublethal acid exposure in rainbow trout (Salmo gairdneri) in soft water: effects on ion exchanges and blood chemistry. Can J Fish Aquat Sci 45:1387–1398. https://doi.org/10.1139/f88-162 Audet C, Wood CM (1988) Do rainbow trout (Salmo gairdneri) acclimate to low pH? Can J Fish Aquat Sci 45:1399–1405. https://doi.org/10.1139/f88-163 Audet C, Wood CM (1993) Branchial morphological and endocrine responses of rainbow trout (Oncorhynchus mykiss) to a long-term sublethal acid exposure In which acclimation did not occur. Can J Fish Aquat Sci 50:198–209. https://doi.org/10.1139/f93-022 Avella M, Bornancin M (1989) A new analysis of ammonia and aodium transport through the gills of the freshwater rainbow trout (Salmo gairdneri). J Exp Biol 142:155–175. https://doi.org/10.1242/jeb.142.1.155 Baena-Ruiz L, Pulido-Velazquez D, Collados-Lara A., et al (2020) Summarizing the impacts of future potential global change scenarios on seawater intrusion at the aquifer scale. Environ Earth Sci 79:1–13 Barton M, Barton A (1987) Effects of salinity on oxygen consumption of Cyprinodon variegatus. Copeia 1:230–232 Beaudreau AH, Bergstrom CA, Whitney EJ, et al (2022) Seasonal and interannual variation in high-latitude estuarine fish community structure along a glacial to non-glacial watershed gradient in Southeast Alaska. Environ Biol Fishes 105:431–452. https://doi.org/10.1007/s10641-022-01241-9 Benedetti MF, Mounier S, Filizola N, et al (2003) Carbon and metal concentrations, size distributions and fluxes in major rivers of the Amazon basin. Hydrol Process 17:1363–1377. https://doi.org/10.1002/hyp.1289 Blanchard J, Grosell M (2006) Copper toxicity across salinities from freshwater to seawater in the euryhaline fish Fundulus heteroclitus: Is copper an ionoregulatory toxicant in high salinities? Aquat Toxicol 80:131–139. https://doi.org/10.1016/j.aquatox.2006.08.001 332 Blewett TA, Dow EM, Wood CM, et al (2018) The role of dissolved organic carbon concentration and composition on nickel toxicity to early life-stages of the blue mussel Mytilus edulis and purple sea urchin Strongylocentrotus purpuratus. Ecotoxicol Environ Saf 160:162–170. https://doi.org/10.1016/j.ecoenv.2018.05.029 Blewett TA, Leonard EM, Glover CN, et al (2021) The effect of marine dissolved organic carbon on nickel accumulation in early life-stages of the sea urchin, Strongylocentrotus purpuratus. Comp Biochem Physiol Part C Toxicol Pharmacol 250:109-150. https://doi.org/10.1016/j.cbpc.2021.109150 Blewett TA, Smith DS, Wood CM, Glover CN (2016) Mechanisms of nickel toxicity in the highly sensitive embryos of the sea urchin Evechinus chloroticus, and the modifying effects of natural organic matter. Environ Sci Technol 50:1595–1603. https://doi.org/10.1021/acs.est.5b05626 Blewett TA, Weinrauch AM, Delompré PLM, Goss GG (2017) The effect of hydraulic flowback and produced water on gill morphology, oxidative stress and antioxidant response in rainbow trout (Oncorhynchus mykiss). Sci Rep 7: https://doi.org/10.1038/srep46582 Boetler, AM, Lamming F.N., Farag, A.M., Bergman, H.L. (1992) Environmental effects of saline oil-field discharges on surface waters. Environ Toxicol Chem 11:1187–1195 Boggs SJr, Livermore D, Seitz MG (1985) Humic substances in natural waters and their complexation with trace metals and radionuclides: a review. Argonne National Lab., IL USA Bottom D, Jones K, Herring M (1984) Fishes of the Columbia River estuary. Oregon Department of Fish and Wildlife, Columbia river estuary data development program. Corvallis, Oregon, USA Boullemant A, Lavoie M, Fortin C, Campbell PGC (2009) Uptake of Hydrophobic Metal Complexes by Three Freshwater Algae: Unexpected Influence of pH. Environ Sci Technol 43:3308–3314. https://doi.org/10.1021/es802832u Boullemant A, Le Faucheur S, Fortin C, Campbell PGC (2011) Uptake of lipophilic cadmium complexes by three green algae: Influence of humic acid and its pH dependence. J Phycol 47:784–791. https://doi.org/10.1111/j.1529-8817.2011.01013.x Boutilier R, Heming T, Iwama G (1984) Appendix: Physico-chemical parameters for use in fish respiratory physiology. Hoar WS, Randall DJ, (eds.) Fish Physiology: Gills-Anatomy Gas Transfer and Acid-Base Regulation. Volume 10A, Academic Press, London, England pp. 403-430 Braz-Mota S, Campos DF, MacCormack TJ, et al (2018) Mechanisms of toxic action of copper and copper nanoparticles in two Amazon fish species: Dwarf cichlid (Apistogramma 333 agassizii) and cardinal tetra (Paracheirodon axelrodi). Sci Total Environ 630:1168–1180. https://doi.org/10.1016/j.scitotenv.2018.02.216 Braz-Mota S, Duarte RM, Val AL (2024) Toxicological impacts of pesticides and heavy metals on amazon fish: trends and future perspectives. In: de Souza, SS, Braz-Mota S, Val, AL (eds.) The Future of Amazonian Aquatic Biota. Springer, Cham Brett JR, Zala CA (1975) Daily pattern of nitrogen excretion and oxygen consumption of sockeye salmon (Oncorhynchus nerka) under controlled conditions. J Fish Res Board Can 32:2479–2486. https://doi.org/10.1139/f75-285 Breves JP, Inokuchi M, Yamaguchi Y, et al (2016) Hormonal regulation of aquaporin 3: opposing actions of prolactin and cortisol in tilapia gill. J Endocrinol 230:325–337. https://doi.org/10.1530/joe-16-0162 Brix KV, Schlekat CE, Garman ER (2016) The mechanisms of nickel toxicity in aquatic environments: An adverse outcome pathway analysis. Environ Toxicol Chem 36:1128–1137. https://doi.org/10.1002/etc.3706 Brooks ML, McKnight DM, Clements WH (2007a) Photochemical control of copper complexation by dissolved organic matter in Rocky Mountain streams, Colorado. Limnol Oceanogr 52:766–779. https://doi.org/10.4319/lo.2007.52.2.0766 Brooks ML, Meyer JS, Boese CJ (2007b) Toxicity of copper to larval Pimephales promelas in the presence of photodegraded natural dissolved organic matter. Can J Fish Aquat Sci 64:391–401. https://doi.org/10.1139/f07-012 Brooks ML, Meyer JS, McKnight DM (2007c) Photooxidation of wetland and riverine dissolved organic matter: altered copper complexation and organic composition. Hydrobiologia 579:95–113. https://doi.org/10.1007/s10750-006-0387-6 Bryan SE, Tipping E, Hamilton-Taylor J (2002) Comparison of measured and modelled copper binding by natural organic matter in freshwaters. Comp Biochem Physiol Part C Toxicol Pharmacol 133:37–49. https://doi.org/10.1016/s1532-0456(02)00083-2 Bucking C (2017) A broader look at ammonia production, excretion, and transport in fish: a review of impacts of feeding and the environment. J Comp Physiol B 187:1–18. https://doi.org/10.1007/s00360-016-1026-9 Buffle J (1988) Complexation reactions in aquatic systems: An analytical approach. Ellis Horwood., Chichester, UK Buffle J (1997) Les substances humiques et leurs interactions avec les minéraux. Conference Proceedings de la Comission d’Hydologie Appliquée de AGHTM l’Université de Orsay 3–10 334 Burke J, Miller JM, Hoss DE (1991) Immigration and settlement pattern of Paralichthys dentatus and P. lethostigma in an estuarine nursery ground, North Carolina, USA Neth J Sea Res 27:393–405. https://doi.org/10.1016/0077-7579(91)90041-x Burke J, Tanaka M, Seikai T (1995) Influence of light and salinity on behaviour of larval Japanese flounder Paralichthys oliaceus and implications for inshore migration. Neth J Sea Re 34:0–10 Cameron JN, Heisler N (1983) Studies of ammonia in the rainbow trout physico-chemical parameters, acid-base behaviour and respiratory clearance. J Exp Biol 105:107–125. https://doi.org/10.1242/jeb.105.1.107 Campbell PG, Twiss MR, Wilkinson KJ (1997) Accumulation of natural organic matter on the surfaces of living cells: implications for the interaction of toxic solutes with aquatic biota. Can J Fish Aquat Sci 54:2543–2554. https://doi.org/10.1139/f97-161 Campinas M, Viegas RMC, Rosa MJ (2013) Modelling and understanding the competitive adsorption of microcystins and tannic acid. Water Res 47:5690–5699. https://doi.org/10.1016/j.watres.2013.06.048 Cañedo-Argüelles M (2020) A review of recent advances and future challenges in freshwater salinization. Limnetica 39:185–211. https://doi.org/10.23818/limn.39.13 Cañedo-Argüelles M, Hawkins CP, Kefford BJ, et al (2016) Saving freshwater from salts. Science 351:914–916. https://doi.org/10.1126/science.aad3488 Cañedo-Argüelles M, Kefford BJ, Piscart C, et al (2013) Salinisation of rivers: An urgent ecological issue. Environ Pollut 173:157–167. https://doi.org/10.1016/j.envpol.2012.10.011 Cao Q, Gershunov A, Shulgina T, et al (2020) Floods due to atmospheric rivers along the U.S. West Coast: the Role of antecedent soil moisture in a warming climate. J Hydrometeorol 21:1827–1845. https://doi.org/10.1175/jhm-d-19-0242.1 Cerdà J, Finn RN (2010) Piscine aquaporins: an overview of recent advances. J Exp Zool Part A Ecol Genet Physiol 313A:623–650. https://doi.org/10.1002/jez.634 Chen L-M, Zhao J, Musa-Aziz R, et al (2010) Cloning and characterization of a zebrafish homologue of human AQP1: a bifunctional water and gas channel. Am J Physiol-Regul Integr Comp Physiol 299:R1163–R1174. https://doi.org/10.1152/ajpregu.00319.2010 Cheng L, Trenberth KE, Gruber N, et al (2020) Improved estimates of changes in upper ocean salinity and the hydrological cycle. J Clim 33:10357–10381. https://doi.org/10.1175/jcli-d-20-0366.1 335 Chew SF, Wilson JM, Ip YK, Randall DJ (2005) Nitrogen excretion and defense against ammonia toxicity. In: Val, Almedia-Val V, Randall DJ (eds.) Fish Physiology. Volume 21, Elsevier, New York, USA pp 307–395 Chin Y, Gschwend PM (1991) The abundance, distribution, and configuration of porewater organic colloids in recent sediments. Geochim Cosmochim Acta 55:1309–1317. https://doi.org/10.1016/0016-7037(91)90309-s Chiou CT, Kile DE, Brinton TI, et al (1987) A comparison of water solubility enhancements of organic solutes by aquatic humic materials and commercial humic acids. Environ Sci Technol 21:1231–1234. https://doi.org/10.1021/es00165a012 Christensen JB, Christensen TH (2000) The effect of pH on the complexation of Cd, Ni and Zn by dissolved organic carbon from leachate-polluted groundwater. Water Res 34:3743–3754. https://doi.org/10.1016/s0043-1354(00)00127-5 Chun J, Lim C, Kim D, Kim J (2018) Assessing impacts of climate change and sea-level rise on seawater intrusion in a coastal aquifer. Water 10:357. https://doi.org/10.3390/w10040357 Clair TA, Dennis IF, Scruton DA, Gilliss M (2007) Freshwater acidification research in Atlantic Canada: a review of results and predictions for the future. Environ Rev 15:153–167. https://doi.org/10.1139/A07-004 Clarke A, Johnston NM (1999) Scaling of metabolic rate with body mass and temperature in teleost fish. J Anim Ecol 68:893–905. https://doi.org/10.1046/j.1365-2656.1999.00337.x Connors D, Kester D (1974) Effect of major ion variations in the marine environment on the specific gravity-conductivity-chlorinity-salinity relationship. Mar Chem 2:301–314 Cooper CA, Tait T, Gray H, et al (2014) Influence of salinity and dissolved organic carbon on acute Cu toxicity to the rotifer Brachionus plicatilis. Environ Sci Technol 48:1213–1221. https://doi.org/10.1021/es402186w Cormier SM, Suter GW (2013) A method for deriving water-quality benchmarks using field data. Environ Toxicol Chem 32:255–262. https://doi.org/10.1002/etc.2057 Craig PM, Wood CM, McClelland GB (2007) Oxidative stress response and gene expression with acute copper exposure in zebrafish (Danio rerio). Am J Physiol-Regul Integr Comp Physiol 293:R1882–R1892. https://doi.org/10.1152/ajpregu.00383.2007 Crémazy A, Braz-Mota S, Brix KV, et al (2022) Investigating the mechanisms of dissolved organic matter protection against copper toxicity in fish of Amazon’s black waters. Sci Total Environ 843:157032. https://doi.org/10.1016/j.scitotenv.2022.157032 Crémazy A, Morris C, Braz-Mota S, et al (2025) Joint effects of elevated copper and temperature in juvenile Tamabqui exposed in black and white waters of the Amazon. Journal of Fish Biology. 1–14. https://doi.org/10.1111/jfb.70238 336 Crémazy A, Wood CM, Ng TY-T, et al (2017) Experimentally derived acute and chronic copper Biotic Ligand Models for rainbow trout. Aquat Toxicol 192:224–240. https://doi.org/10.1016/j.aquatox.2017.07.013 Crémazy A, Wood CM, Smith DS, et al (2016) Investigating copper toxicity in the tropical fish cardinal tetra (Paracheirodon axelrodi) in natural Amazonian waters: Measurements, modeling, and reality. Aquat Toxicol 180:353–363. https://doi.org/10.1016/j.aquatox.2016.10.011 Crémazy A, Wood CM, Smith DS, Val AL (2019) The effects of natural suspended solids on copper toxicity to the cardinal tetra in Amazonian river waters. Environ Toxicol Chem 38:2708–2718. https://doi.org/10.1002/etc.4586 Cruz LR, Santos LN, Santos AFGN (2018) Changes of fish trophic guilds in Araruama Lagoon, Brazil: What can be inferred about functioning and structure of hypersaline lagoons? Estuar Coast Shelf Sci 211:90–99. https://doi.org/10.1016/j.ecss.2017.11.024 Curtis PJ, Schindler DW (1997a) Hydrologic control of dissolved organic matter in low-order precambrian shield lakes. Biogeochemistry 36:125–138 Cutler CP, Martinez A-S, Cramb G (2007) The role of aquaporin 3 in teleost fish. Comp Biochem Physiol A Mol Integr Physiol 148:82–91. https://doi.org/10.1016/j.cbpa.2006.09.022 da Costa STD, Gressler LT, Sutili FJ, et al (2015) Effect of humic acid on survival, ionoregulation and hematology of the silver catfish, Rhamdia quelen (Siluriformes: Heptapteridae), exposed to different pHs. Zool Curitiba 32:215–224. https://doi.org/10.1590/S1984-46702015000300006 da Costa STD, Gressler LT, Sutili FJ, et al (2017) Humic acid of commercial origin causes changes in gill morphology of silver catfish Rhamdia quelen exposed to acidic water: Response of silver catfish gills to low pH and humic acid. J Exp Zool Part A Ecol Integr Physiol 327:504–512. https://doi.org/10.1002/jez.2136 Dahlén J, Bertilsson S, Pettersson C (1999) Effects of UV-A irradiation on dissolved organic matter in humic surface waters. Environ Int 22:501–506. https://doi.org/10.1016/0160-4120(96)00038-4 Dalla Via J, Villani P, Gasteiger E, Niederstätter H (1998) Oxygen consumption in sea bass fingerling Dicentrarchus labrax exposed to acute salinity and temperature changes: metabolic basis for maximum stocking density estimations. Aquaculture 169:303–313 Daye PG, Garside ET (1976) Histopathologic changes in surficial tissues of brook trout, Salvelinus fontinalis (Mitchill), exposed to acute and chronic levels of pH. Can J Zool 54:2140–2155. https://doi.org/10.1139/z76-248 337 D’Cruz LM, Wood CM (1998) The influence of dietary salt and energy on the response to low pH in juvenile rainbow trout. Physiol Zool 71:642–657. https://doi.org/10.1086/515987 DePalma SGS, Arnold WR, McGeer JC, et al (2011) Variability in dissolved organic matter fluorescence and reduced sulfur concentration in coastal marine and estuarine environments. Appl Geochem 26:394–404. https://doi.org/10.1016/j.apgeochem.2011.01.022 Di Toro DM, Allen HE, Bergman HL, et al (2001) Biotic ligand model of the acute toxicity of metals. 1. Technical Basis. Environ Toxicol Chem 20:2383–2396. https://doi.org/10.1002/etc.5620201034 Drake TW, Hemingway JD, Kurek MR, et al (2021) The pulse of the Amazon: Fluxes of dissolved organic carbon, nutrients, and ions from the world’s largest river. Glob Biogeochem Cycles 35:e2020GB006895. https://doi.org/10.1029/2020GB006895 Driscoll CT, Driscoll KM, Fakhraei H, Civerolo K (2016) Long-term temporal trends and spatial patterns in the acid-base chemistry of lakes in the Adirondack region of New York in response to decreases in acidic deposition. Atmos Environ 146:5–14. https://doi.org/10.1016/j.atmosenv.2016.08.034 Driedzic WR, Hochachka P (1978) Metabolism in fish during exercise. In: Hoar WS, Randall DJ (eds.) Fish Physiology. Volume 7 Academic Press, New York, USA. pp 503-543 Duarte RM (2012) Mecanismos de regulação de Na nas brânquias de peixes da Amazônia: modulação por fatores ambientais e ajustes espécie-específicos. PhD Thesis, INPA, Manaus, Brazil. Duarte RM, Crémazy A, Wood CM, et al (2024) The biotic ligand model as a promising tool to predict Cu toxicity in amazon blackwaters. Environ Pollut 341:122988. https://doi.org/10.1016/j.envpol.2023.122988 Duarte RM, Ferreira MS, Wood CM, Val AL (2013) Effect of low pH exposure on Na+ regulation in two cichlid fish species of the Amazon. Comp Biochem Physiol A Mol Integr Physiol 166:441–448. https://doi.org/10.1016/j.cbpa.2013.07.022 Duarte RM, Menezes ACL, Da Silveira Rodrigues L, et al (2009) Copper sensitivity of wild ornamental fish of the Amazon. Ecotoxicol Environ Saf 72:693–698. https://doi.org/10.1016/j.ecoenv.2008.10.003 Duarte RM, Smith DS, Val AL, Wood CM (2016) Dissolved organic carbon from the upper Rio Negro protects zebrafish (Danio rerio) against ionoregulatory disturbances caused by low pH exposure. Sci Rep 6:20377. https://doi.org/10.1038/srep20377 Duarte RM, Val AL (2020) Water‐related problem with special reference to global climate change in Brazil. In: In Singh P, Milshina Y, Tian K, Gusain D & Bassin JP (eds.), Water 338 conservation and wastewater treatment in BRICS Nations: Technologies, challenges, strategies, and policies. Elsevier, New York, USA. pp 3–21 Duarte RM, Wood CM, Val AL, Smith DS (2018) Physiological protective action of dissolved organic carbon on ion regulation and nitrogenous waste excretion of zebrafish (Danio rerio) exposed to low pH in ion-poor water. J Comp Physiol B 188:793–807. https://doi.org/10.1007/s00360-018-1169-y Durand-Hoffman M (1995) Analysis of physiological and toxicological effects of potassium on Dreissena polymorpha and toxicological effects on fish. Doctoral Thesis, The Ohio State University. Durkin J, Coley T, Verner K, Emmett R (1981) An evaluation of aquatic life found at four hydraulic scour sites in the Colombia River estuary selected for potential sediment deposition. Final Report of Research Financed by U.S. Army Corps of Engineers (Contract No. DACW57-79-F-0145), Coastal Zone and Estuarine Studies Division Northwest and Alaska Fisheries Center National Marine Fisheries Service National Oceanic and Atmospheric Administration 2725 Montlake Boulevard East Seattle, Washington 98112. Duthie GG (1982) The respiratory metabolism of temperature-adapted flatfish at rest and during swimming activity and the use of anaerobic metabolism at moderate swimming speeds. J Exp Biol 97:359–373. https://doi.org/10.1242/jeb.97.1.359 Dymowska AK, Boyle D, Schultz AG, Goss GG (2015) The role of acid-sensing ion channels (ASICs) in epithelial Na+ uptake in adult zebrafish (Danio rerio). J Exp Biol jeb.113118. https://doi.org/10.1242/jeb.113118 Dymowska AK, Schultz AG, Blair SD, et al (2014) Acid-sensing ion channels are involved in epithelial Na+ uptake in the rainbow trout Oncorhynchus mykiss. Am J Physiol-Cell Physiol 307:C255–C265. https://doi.org/10.1152/ajpcell.00398.2013 Echevarría G, Lujan NK, Montoya J, et al (2024) Abiotic and biotic factors influencing heavy metals pollution in fisheries of the Western Amazon. Sci Total Environ 908:168506. https://doi.org/10.1016/j.scitotenv.2023.168506 Edwards SL, Marshall WS (2012) Principles and patterns of osmoregulation and euryhalinity in fishes. In: McCormick SD, Farrell AP, Brauner CJ, Fish Physiology: Euryhaline Fishes. Volume 32, Elsevier, New York, USA, pp 2–45 Egeberg P, Alberts J (2002) Determination of hydrophobicity of NOM by RP-HPLC, and the effect of pH and ionic strength. Water Res 36:4997–5004. https://doi.org/10.1016/S0043-1354(02)00228-2 EPRI (2018) Multi-ion Toxicity review: data analysis and ongoing model framework development. EPRI, Palo Alto, CA, USA 339 Erickson RJ, Mount DR, Highland TL, et al (2017) The acute toxicity of major ion salts to Ceriodaphnia dubia. II. Empirical relationships in binary salt mixtures. Environ Toxicol Chem 36:1525–1537. https://doi.org/10.1002/etc.3669 Erlandsson M, Cory N, Köhler S, Bishop K (2010) Direct and indirect effects of increasing dissolved organic carbon levels on pH in lakes recovering from acidification. J Geophys Res Biogeosciences 115: G03004, https://doi.org/10.1029/2009jg001082 Ertel JR, Hedges JI, Perdue EM (1984) Lignin signature of aquatic humic substances. Science 223:485–487. https://doi.org/10.1126/science.223.4635.485 Ertel JR, Hedges JI, Devol AH, Richey JE, de Nazaré Góes Ribero M (1986) Dissolved humic substances of the Amazon River system. Limnol and Oceanogr 31: 739-754. Essington TE, Dodd K, Quinn TP (2013) Shifts in the estuarine demersal fish community after a fishery closure in Puget Sound, Washington. Fish Bull 111:205–217. https://doi.org/10.7755/fb.111.3.1 Evans DH (2011) Freshwater fish gill ion transport: August Krogh to morpholinos and microprobes. Acta Physiol 202:349–359. https://doi.org/10.1111/j.1748-1716.2010.02186.x Evans DH (1980) Kinetic studies of ion transport by fish gill epithelium. Am J Physiol-Regul Integr Comp Physiol 238:R224–R230. https://doi.org/10.1152/ajpregu.1980.238.3.R224 Evans DH (1969) Studies on the permeability to water of selected marine, freshwater and euryhaline teleosts. J Exp Biol 50:689–703. https://doi.org/10.1242/jeb.50.3.689 Evans DH (1984) The roles of gill permeability and transport mechanisms in euryhalinity. In: Hoar WS, Randall DJ (eds.) Fish Physiology, Volume 10B. Academic Press, Orlando, USA pp 239–328 Evans DH, Piermarini PM, Choe KP (2005) The multifunctional fish gill: dominant site of gas exchange, osmoregulation, acid-base regulation, and excretion of nitrogenous waste. Physiol Rev 85:97–177. https://doi.org/10.1152/physrev.00050.2003 Ferruzza S, Scarino M-L, Rotilio G, et al (1999) Copper treatment alters the permeability of tight junctions in cultured human intestinal Caco-2 cells. Am J Physiol-Gastrointest Liver Physiol 277:G1138–G1148. https://doi.org/10.1152/ajpgi.1999.277.6.g1138 Findlay SEG, Kelly VR (2011) Emerging indirect and long‐term road salt effects on ecosystems. Ann N Y Acad Sci 1223:58–68. https://doi.org/10.1111/j.1749-6632.2010.05942.x Findlay SEG, Parr TB (2017) Dissolved Organic Matter. In: Hauer G, Lamberti A (eds.) Methods in Stream Ecology. Elsevier, New York, USA pp 21–36 340 Finn R, Rønnestad I, Van Der Meeren T, Fyhn H (2002) Fuel and metabolic scaling during the early life stages of Atlantic cod Gadus morhua. Mar Ecol Prog Ser 243:217–234. https://doi.org/10.3354/meps243217 Fonds M, Cronie R, Vethaak AD, Van Der Puyl P (1992) Metabolism, food consumption and growth of plaice (Pleuronectes platessa) and flounder (Platichthys flesus) in relation to fish size and temperature. Neth J Sea Res 29:127–143. https://doi.org/10.1016/0077-7579(92)90014-6 Forgac M (1989) Structure and function of vacuolar class of ATP-driven proton pumps. Physiol Rev 69:765–796. https://doi.org/10.1152/physrev.1989.69.3.765 Freda J, Cavdek V, McDonald DG (1990) Role of organic complexation in the toxicity of aluminum to Rana pipiens embryos and Bufo americanus tadpoles. Can J Fish Aquat Sci 47:217–224. https://doi.org/10.1139/f90-024 Furch K (1984) Water chemistry of the Amazon basin: The distribution of chemical elements among freshwaters. In: Sioli H (eds) The Amazon. Springer Netherlands, Dordrecht, pp 167–199 Gaffney JS, Marley NA, Clark SB (eds.) (1996) Humic and fulvic acids and organic colloidal materials in the environment. American Chemical Society symposium book series, Washington, DC, USA Galvez F, Donini A, Playle RC, et al (2008) A matter of potential concern: natural organic matter alters the electrical properties of fish gills. Environ Sci Technol 42:9385–9390. https://doi.org/10.1021/es8005332 Gandois L, Hoyt AM, Mounier S, et al (2020) From canals to the coast: dissolved organic matter and trace metal composition in rivers draining degraded tropical peatlands in Indonesia. Biogeosciences 17:1897–1909. https://doi.org/10.5194/bg-17-1897-2020 Geissler RMO (1999) Geoquímica ambiental aplicada a bacia do Igarapé do Quarenta, município de Manaus (AM). MSc, Universidade Federal do Amazonas, Manaus, Amazonas, Brazil. Gennings C, Molot LA, Dillon PJ (2001) Enhanced photochemical loss of organic carbon in acidic waters. Biogeochemistry 52:339–354. https://doi.org/10.1023/a:1006499713835 Ghosh K, Schnitzer M (1980) Effects of pH and neutral electrolyte concentration on free radicals in humic substances. Soil Sci Soc Am J 44:975–978. https://doi.org/10.2136/sssaj1980.03615995004400050020x Giacomin M, Onukwufor JO, Schulte PM, Wood CM (2020) Ionoregulatory aspects of the hypoxia-induced osmorespiratory compromise in the euryhaline Atlantic killifish (Fundulus heteroclitus): the effects of salinity. J Exp Biol. https://doi.org/10.1242/jeb.216309 341 Giacomin M, Vilarinho GC, Castro KF, et al (2018) Physiological impacts and bioaccumulation of dietary Cu and Cd in a model teleost: The Amazonian tambaqui (Colossoma macropomum). Aquat Toxicol 199:30–45. https://doi.org/10.1016/j.aquatox.2018.03.021 Gibson RN (1994) Impact of habitat quality and quantity on the recruitment of juvenile flatfishes. Neth J Sea Res 32:191–206. https://doi.org/10.1016/0077-7579(94)90040-x Gjessing E, Egeberg PK, Håkedal J (1999) Natural organic matter in drinking water-The NOM-typing project, background and basic characteristics of original water samples and NOM isolates. Environ Int 25:145–159. https://doi.org/10.1016/S0160-4120(98)00119-6 Glover CN, Pane EF, Wood CM (2005) Humic substances influence sodium metabolism in the freshwater crustacean Daphnia magna. Physiol Biochem Zool 78:405–416. https://doi.org/10.1086/430036 Glover CN, Wood CM (2005) Accumulation and elimination of silver in Daphnia magna and the effect of natural organic matter. Aquat Toxicol 73:406–417. https://doi.org/10.1016/j.aquatox.2005.05.002 Gonzalez RJ, Cradeur A, Guinnip M, et al (2018) South American characids share very similar ionoregulatory characteristics. Comp Biochem Physiol A Mol Integr Physiol 226:17–21. https://doi.org/10.1016/j.cbpa.2018.06.025 Gonzalez RJ, Dalton VM, Patrick ML (1997) Ion regulation in ion‐poor acidic water by the blackskirt tetra (Gymnocorymbus ternetzi), a fish native to the Amazon river. Physiol Zool 70:428–435. https://doi.org/10.1086/515855 Gonzalez RJ, Dunson WA (1987) Adaptations of sodium balance to low pH in a sunfish (Enneacanthus obesus) from naturally acidic waters. J Comp Physiol B 157:555–566. https://doi.org/10.1007/BF00700975 Gonzalez RJ, Hsu R, Mahaffey L, et al (2021a) Examination of ionoregulatory characteristics of South American cichlids. Comp Biochem Physiol A Mol Integr Physiol 253:110854. https://doi.org/10.1016/j.cbpa.2020.110854 Gonzalez RJ, Jones SL, Nguyen TV (2017) Ionoregulatory characteristics of non–Rio Negro characiforms and cichlids. Physiol Biochem Zool 90:407–414. https://doi.org/10.1086/690306 Gonzalez RJ, Patrick ML, Duarte RM, et al (2021b) Exposure to pH 3.5 water has no effect on the gills of the Amazonian tambaqui (Colossoma macropomum). J Comp Physiol B 191:493–502. https://doi.org/10.1007/s00360-021-01349-x Gonzalez RJ, Preest MR (1999) Ionoregulatory specializations for exceptional tolerance of ion‐poor, acidic waters in the neon tetra (Paracheirodon innesi). Physiol Biochem Zool 72:156–163. https://doi.org/10.1086/316651 342 Gonzalez RJ, Wilson RW, Patrick ML, et al (1998) Effects of water pH and calcium concentration on ion balance in fish of the Rio Negro, Amazon. Physiol Zool 71:15–22. https://doi.org/10.1086/515893 Gonzalez RJ, Wilson RW, Wood CM, et al (2002) Diverse strategies for ion regulation in fish collected from the ion‐poor, acidic Rio Negro. Physiol Biochem Zool 75:37–47. https://doi.org/10.1086/339216 Gonzalez RJ, Wilson RW, Wood CM (2005) Ionoregulation in tropical fishes from ion‐poor, acidic blackwaters. In: Val AL, Almeida-Val, Randal DJ (eds) Fish Physiology. Volume 21 Elsevier, New York, USA pp 397–442 Goodfellow WL, Ausley LW, Burton DT, et al (2000) Major ion toxicity in effluents: a review with permitting recommendations. Environ Toxicol Chem 19:175. https://doi.org/10.1897/1551-5028(2000)019<0175:mitiea>2.3.co;2 Goss GG, Wood CM (1990) Na+ and Cl− uptake kinetics, diffusive effluxes and acidic equivalent fluxes across the gills of rainbow trout II. responses to bicarbonate infusion. J Exp Biol 152:549–571. https://doi.org/10.1242/jeb.152.1.549 Grosell M, Nielsen C, Bianchini A (2002) Sodium turnover rate determines sensitivity to acute copper and silver exposure in freshwater animals. Comp Biochem Physiol Part C Toxicol Pharmacol 133:287–303. https://doi.org/10.1016/s1532-0456(02)00085-6 Grosell M, Wood CM (2002) Copper uptake across rainbow trout gills: mechanisms of apical entry. J Exp Biol 205:1179–1188. https://doi.org/10.1242/jeb.205.8.1179 Handy RD (1989) The ionic composition of rainbow trout body mucus. Comp Biochem Physiol A Physiol 93:571–575. https://doi.org/10.1016/0300-9629(89)90012-1 Handy RD, Eddy FB, Romain G (1989) In vitro evidence for the ionoregulatory role of rainbow trout mucus in acid, acid/aluminium and zinc toxicity. J Fish Biol 35:737–747. https://doi.org/10.1111/j.1095-8649.1989.tb03024.x Harris DC, Lucy CA (2020) In: Harris DS, Charles LA. Quantitative chemical analysis. Macmillan Learning Volume 11, London, England. Harris RR, Aladin NV (1997) The ecophysiology of osmoregulation in crustacea. In: Hazon N, Eddy FB, Flik G (eds.) Ionic Regulation in Animals: A Tribute to Professor W.T.W.Potts. Springer Berlin Heidelberg, Berlin, Heidelberg, Germany, pp 1–25 Hatcher PG, Spiker EC (1988) Selective degradation of plant biomolecules. In: F. H. Frimmel FH, Christman RF(eds.), Humic substances and their role in the environment. John Wiley & Sons Ltd. New Jersey, USA. pp 59–74 Heidari S, Hemmateenejad B, Yousefinejad S, Moosavi-Movahedi AA (2018) Excitation- emission matrix fluorescence spectroscopy combined with three-way chemometrics 343 analysis to follow denatured states of secondary structure of bovine serum albumin. J Lumin 203:90–99. https://doi.org/10.1016/j.jlumin.2018.06.029 Herbert ER, Boon P, Burgin AJ, et al (2015) A global perspective on wetland salinization: ecological consequences of a growing threat to freshwater wetlands. Ecosphere 6:1–43. https://doi.org/10.1890/es14-00534.1 Herrera M, Aragão C, Hachero I, et al (2012) Physiological short-term response to sudden salinity change in the Senegalese sole (Solea senegalensis). Fish Physiol Biochem 38:1741–1751. https://doi.org/10.1007/s10695-012-9671-8 Hessen DO, Tranvik LJ (eds.) (1998) Aquatic Humic Substances: ecology and biogeochemistry. Springer Berlin Heidelberg, Berlin, Heidelberg, Germany Hirata T, Kaneko T, Ono T, et al (2003) Mechanism of acid adaptation of a fish living in a pH 3.5 lake. Am J Physiol-Regul Integr Comp Physiol 284:R1199–R1212. https://doi.org/10.1152/ajpregu.00267.2002 Holland A, Duivenvoorden LJ, Kinnear SHW (2014) The double-edged sword of humic substances: contrasting their effect on respiratory stress in eastern rainbow fish exposed to low pH. Environ Sci Pollut Res 21:1701–1707. https://doi.org/10.1007/s11356-013-2031-0 Holland A, Stauber J, Wood CM, et al (2018) Dissolved organic matter signatures vary between naturally acidic, circumneutral and groundwater-fed freshwaters in Australia. Water Res 137:184–192. https://doi.org/10.1016/j.watres.2018.02.043 Holland A, Wood CM, Smith DS, et al (2017) Nickel toxicity to cardinal tetra (Paracheirodon axelrodi) differs seasonally and among the black, white and clear river waters of the Amazon basin. Water Res 123:21–29. https://doi.org/10.1016/j.watres.2017.06.044 Hollis L, Hogstrand C, Wood CM (2001) Tissue-specific cadmium accumulation, metallothionein induction, and tissue zinc and copper levels during chronic sublethal cadmium exposure in juvenile rainbow trout. Arch Environ Contam Toxicol 41:468–474. https://doi.org/10.1007/s002440010273 Holmberg K, Jönsson B, Kronberg BI, Lindman B (2007) Surfactants and polymers in aqueous solution. John Wiley Sons Ltd Chichester West Sussex, UK. Holmes W, Donaldson E Body compartments and distribution of electrolytes. In: Hoar WS, Randall DJ (eds.) Fish Physiology, Volume 1, Academic Press, New York, USA, pp 1–89 Hourtané O, Rioux G, Campbell PGC, Fortin C (2022) Algal bioaccumulation and toxicity of platinum are increased in the presence of humic acids. Environ Chem 19:144–155. https://doi.org/10.1071/en22037 344 Huang Q, Riviere JE (2014) The application of allometric scaling principles to predict pharmacokinetic parameters across species. Expert Opin Drug Metab Toxicol 10:1241–1253. https://doi.org/10.1517/17425255.2014.934671 Hunn JB (1985) Role of calcium in gill function in freshwater fishes. Comp Biochem Physiol A Physiol 82:543–547. https://doi.org/10.1016/0300-9629(85)90430-X Ip YK, Soh MML, Chen XL, et al (2013) Molecular characterization of branchial aquaporin 1aa and effects of seawater acclimation emersion or ammonia exposure on its mRNA expression in the gills, gut, kidney and skin of freshwater climbing perch. Anabas testudineus. PLoS ONE 8:e61163. https://doi.org/10.1371/journal.pone.0061163 Isaia J (1984) Water and nonelectrolyte permeability. In: Hoar WS, Randall DJ (eds.) Fish Physiology. Volume 10B, Academic Press, San Diego, California, USA, pp 1–38 Isaia J, Masoni A (1976) The effects of calcium and magnesium on water and ionic permeabilities in the sea water adapted eel Anguilla anguilla. J Comp Physiol 109:221–233 Ito Y, Kobayashi S, Nakamura N, et al (2013) Close Association of carbonic anhydrase (CA2a and CA15a), Na+/H+ exchanger (Nhe3b), and ammonia transporter Rhcg1 in zebrafish ionocytes responsible for Na+ uptake. Front Physiol 4: https://doi.org/10.3389/fphys.2013.00059 Jobling M (1994) Biotic factors and growth performances. In: Jobling M (ed) Fish Bioenergetics, Fish and Fisheries series. Chapman and Hall, New York, USA Johannsson OE, Ferreira MS, Smith DS, et al (2020) Effects of natural light and depth on rates of photo-oxidation of dissolved organic carbon in a major black-water river, the Rio Negro, Brazil. Sci Total Environ 733:139193. https://doi.org/10.1016/j.scitotenv.2020.139193 Johannsson OE, Holland A (2025) Dissolved Organic Carbon (DOC) of the Rio Negro, Amazonia: importance, processes and potential anthropogenic impacts. In: Va AL, de Souza SS, Braz-Mota S (eds.) The Future of Amazonian Aquatic Biota. Springer, Gewerbestrasse, Switzerland. pp 49–75 Johannsson OE, Smith DS, Sadauskas-Henrique H, et al (2017) Photo-oxidation processes, properties of DOC, reactive oxygen species (ROS), and their potential impacts on native biota and carbon cycling in the Rio Negro (Amazonia, Brazil). Hydrobiologia 789:7–29. https://doi.org/10.1007/s10750-016-2687-9 Jones R (2005) Limnology of humic waters: Special theme or universal framework? Verh Intern Verein Limnol. 29:51–60 doi 10.1080/03680770.2005.11901974. Jung D, Sato JD, Shaw JR, Stanton BA (2012) Expression of aquaporin 3 in gills of the Atlantic killifish (Fundulus heteroclitus): Effects of seawater acclimation. Comp Biochem Physiol A Mol Integr Physiol 161:320–326. https://doi.org/10.1016/j.cbpa.2011.11.014 345 Kalbitz K, Solinger S, Park J-H, et al (2000) Controls on the dynamics of dissolved organic matter in soils: a review. Soil Sci 165:277 Karns DR (1983) The role of low pH in the toxicity of bog water to amphibian embryos. Bull Ecol Socof Am, (Abs). 64:188. Keller W (Bill), Heneberry JH, Dixit SS (2003) Decreased acid deposition and the chemical kecovery of Killarney, Ontario lakes. Ambio J Hum Environ 32:183–189. https://doi.org/10.1579/0044-7447-32.3.183 Kieffer JD, Alsop D, Wood CM (1998) A respirometric analysis of fuel use during aerobic swimming at different temperatures in rainbow trout (Oncorhynchus Mykiss). J Exp Biol 201:3123–3133. https://doi.org/10.1242/jeb.201.22.3123 Kinniburgh DG, Van Riemsdijk WH, Koopal LK, Benedetti MF (1998) Ion binding to humic substances: measurements, models, and mechanisms. In: Jenne EA (eds.) Adsorption of Metals by Geomedia. Academic Press, New York, USA. pp 483–520 Kirschner LB (2004) The mechanism of sodium chloride uptake in hyperregulating aquatic animals. J Exp Biol 207:1439–1452. https://doi.org/10.1242/jeb.00907 Koehler B, Broman E, Tranvik LJ (2016) Apparent quantum yield of photochemical dissolved organic carbon mineralization in lakes: Photochemical DOM mineralization. Limnol Oceanogr 61:2207–2221. https://doi.org/10.1002/lno.10366 Kolarevic J, Takle H, Felip O, et al (2012) Molecular and physiological responses to long-term sublethal ammonia exposure in Atlantic salmon (Salmo salar). Aquat Toxicol 124–125:48–57. https://doi.org/10.1016/j.aquatox.2012.07.003 Konhauser KO, Fyfe WS, Kronberg BI (1994) Multi-element chemistry of some Amazonian waters and soils. Chem Geol 111:155–175. https://doi.org/10.1016/0009-2541(94)90088-4 Kroonenberg PM, Heiser WJ (1998) Parallel factor analysis with constraints on the configurations: an overview. In: Hayashi C, Yajima K, Bock H-H, et al. (eds.) Data Science, Classification, and Related Methods. Springer Japan, Tokyo, pp 587–597 Krzyzanowski J, Innes JL (2010) Back to the basics – Estimating the sensitivity of freshwater to acidification using traditional approaches. J Environ Manage 91:1227–1236. https://doi.org/10.1016/j.jenvman.2010.01.013 Küchler IL, Miekeley N, Forsberg BR (2000) A contribution to the chemical characterization of rivers in the Rio Negro Basin, Brazil. J Braz Chem Soc 11:286–292. https://doi.org/10.1590/S0103-50532000000300015 Kullberg A, Bishop KH, Hargeby A, et al (1993) The ecological significance of dissolved organic carbon in acidified waters. Ambio 22:331–337 346 Kumai Y, Bahubeshi A, Steele S, Perry SF (2011) Strategies for maintaining Na+ balance in zebrafish (Danio rerio) during prolonged exposure to acidic water. Comp Biochem Physiol A Mol Integr Physiol 160:52–62. https://doi.org/10.1016/j.cbpa.2011.05.001 Kumai Y, Perry SF (2011) Ammonia excretion via Rhcg1 facilitates Na+ uptake in larval zebrafish, Danio rerio, in acidic water. Am J Physiol-Regul Integr Comp Physiol 301:R1517–R1528. https://doi.org/10.1152/ajpregu.00282.2011 Kwong RWM, Kumai Y, Perry SF (2014) The physiology of fish at low pH: the zebrafish as a model system. J Exp Biol 217:651–662. https://doi.org/10.1242/jeb.091603 Kwong RWM, Perry SF (2013) The tight junction protein claudin-b regulates epithelial permeability and sodium handling in larval zebrafish, Danio rerio. Am J Physiol-Regul Integr Comp Physiol 304:R504–R513. https://doi.org/10.1152/ajpregu.00385.2012 Laane RWPM (1980) Conservative behaviour of dissolved organic carbon in the EMS-Dollart estuary and the Western Wadden Sea. Neth J Sea Res 14:192–199. https://doi.org/10.1016/0077-7579(80)90021-6 Larsen EH, Deaton LE, Onken H, et al (2014) Osmoregulation and excretion. Comprehensive. Physiology 4:405-473 Lauff RF, Wood CM (1996) Respiratory gas exchange, nitrogenous waste excretion, and fuel usage during starvation in juvenile rainbow trout, Oncorhynchus mykiss. J Comp Physiol B 165:542–551. https://doi.org/10.1007/bf00387515 Laurén DJ, McDonald DG (1985) Effects of copper on branchial ionoregulation in the rainbow trout, Salmo gairdneri Richardson. J Comp Physiol B 155:635–644. https://doi.org/10.1007/BF00694455 Leenheer JA (1980) Origin and nature of humic substances in the waters of the Amazon River Basin. Acta Amaz 10:513–526. https://doi.org/10.1590/1809-43921980103513 Liao Wenta, Christman RF, Johnson JD, et al (1982) Structural characterization of aquatic humic material. Environ Sci Technol 16:403–410. https://doi.org/10.1021/es00101a007 Lignot J-H, Cutler CP, Hazon N, Cramb G (2002) Immunolocalisation of aquaporin 3 in the gill and the gastrointestinal tract of the European eel Anguilla anguilla (L.). J Exp Biol 205:2653–2663. https://doi.org/10.1242/jeb.205.17.2653 Lim MY-T, Zimmer AM, Wood CM (2015) Acute exposure to waterborne copper inhibits both the excretion and uptake of ammonia in freshwater rainbow trout (Oncorhynchus mykiss). Comp Biochem Physiol Part C Toxicol Pharmacol 168:48–54. https://doi.org/10.1016/j.cbpc.2014.12.002 Lin D, Baoshan B (2008) Tannic acid absorption and its role for stabilizing carbon nanotube suspensions. Environ Sci Technol 42:5917–5923. https://doi.org/10.1021/es800329c 347 Lindeman RL, Lindeman L (2007) The trophic dynamic of ecology. Ecology 23:399–417 Liu F, Wang D (2022) Dissolved organic carbon concentration and biodegradability across the global rivers: A meta-analysis. Sci Total Environ 818:151828. https://doi.org/10.1016/j.scitotenv.2021.151828 Lockwood APM (1997) Transport of ions and water in animals. Academic Press Lofts S, Tipping E (2011) Assessing WHAM/Model VII against field measurements of free metal ion concentrations: model performance and the role of uncertainty in parameters and inputs. Environ Chem 8:501. https://doi.org/10.1071/en11049 Luider CD, Crusius J, Playle RC, Curtis PJ (2004) Influence of natural organic matter source on copper speciation as demonstrated by Cu binding to fish gills, by ion selective electrode, and by DGT gel sampler. Environ Sci Technol 38:2865–2872. https://doi.org/10.1021/es030566y Madsen SS, Engelund MB, Cutler CP (2015) Water transport and functional dynamics of aquaporins in osmoregulatory organs of fishes. Biol Bull 229:70–92. https://doi.org/10.1086/bblv229n1p70 Malcolm RL, Ronald L, MacCarthy P (1986) Limitations in the use of commercial humic acids in water and soil research. Environ Sci Technol 20:904–911. https://doi.org/10.1021/es00151a009 Mangum CP, Haswell MS, Johansen K (1977) Low salt and high pH in the blood of Amazon fishes. J Exp Zool 200:163–168. https://doi.org/10.1002/jez.1402000120 Mangum CP, Haswell MS, Johansen K, Towle DW (1978) Inorganic ions and pH in the body fluids of Amazon animals. Can J Zool 56:907–916. https://doi.org/10.1139/z78-126 Marshall W (2012) Osmoregulation in estuarine and intertidal fishes. In: McCormick SD (ed.) Fish Physiology, Euryhaline Fishes. Volume 32, Elsevier, New York, USA pp 395-434 Marshall WS, Nishioka RS (1980) Relation of mitochondria‐rich chloride cells to active chloride transport in the skin of a marine teleost. J Exp Zool 214:147–156. https://doi.org/10.1002/jez.1402140204 Matsuo AYO, Playle RC, Val AL, Wood CM (2004) Physiological action of dissolved organic matter in rainbow trout in the presence and absence of copper: sodium uptake kinetics and unidirectional flux rates in hard and softwater. Aquat Toxicol 70:63–81. https://doi.org/10.1016/j.aquatox.2004.07.005 Matsuo AYO, Wood CM, Val AL (2005) Effects of copper and cadmium on ion transport and gill metal binding in the Amazonian teleost tambaqui (Colossoma macropomum) in extremely soft water. Aquat Toxicol 74:351–364. https://doi.org/10.1016/j.aquatox.2005.06.008 348 Mattigod S, Sposito G (1979) Chemical modeling of trace metal equilibria in contaminated soil solutions using the computer program GEOCHEM, In: Jenne EA (ed.) Chemical Modeling in Aqueous Systems, Volume 93. American Chemical Society, New York, USA pp 837-856. Maxey JD, Hartstein ND, Then AYH, Barrenger M (2020) Dissolved oxygen consumption in a fjord-like estuary, Macquarie Harbour, Tasmania. Estuar Coast Shelf Sci 246:107016. https://doi.org/10.1016/j.ecss.2020.107016 Maxime V, Pichavant K, Boeuf G, Nonnotte G (2000) Effects of hypoxia on respiratory physiology of turbot Scophthalmus macimus. Fish Physiol Biochem 22:51–59. https://doi.org/10.1023/a:1007829214826 McDonald DG (1983) The effects of H+ upon the gills of freshwater fish. Can J Zool 61:691–703. https://doi.org/10.1139/z83-093 McDonald DG, Hobe H, Wood CM (1980) The influence of calcium on the physiological responses of the rainbow trout, Salmo gairdneri, to low environmental pH. J Exp Biol 88:109–132. https://doi.org/10.1242/jeb.88.1.109 McDonald DG, Rogano MS (1986) Ion regulation by the rainbow trout,Salmo gairdneri, in ion-poor water. Physiol Zool 59:318–331. https://doi.org/10.1086/physzool.59.3.30156103 McDonald DG, Walker RL, Wilkes PRH (1983) The interaction of environmental calcium and low pH on the physiology of the rainbow trout, Salmo gairdneri. J Exp Biol 102:141–155. https://doi.org/10.1242/jeb.102.1.141 McDonald DG, Wood CM (1981) Branchial and renal acid and ion fluxes in the rainbow trout, Salmo gairdneri, at low environmental pH. J Exp Biol 93:101–118. https://doi.org/10.1242/jeb.93.1.101 McDonald MD, Gilmour KM, Walsh PJ (2012) New insights into the mechanisms controlling urea excretion in fish gills. Respir Physiol Neurobiol 184:241–248. https://doi.org/10.1016/j.resp.2012.06.002 McDonald MD, Smith CP, Walsh PJ (2006) The physiology and evolution of urea transport in fishes. J Membr Biol 212:93–107. https://doi.org/10.1007/s00232-006-0869-5 McDonald MD, Wood CM (2003) Differential handling of urea and its analogues suggests carrier‐mediated urea excretion in freshwater rainbow trout. Physiol Biochem Zool 76:791–802. https://doi.org/10.1086/378919 McDonald MD, Wood CM, Wang Y, Walsh PJ (2000) Differential branchial and renal handling of urea, acetamide and thiourea in the gulf toadfish Opsanus beta. J Exp Biol 203:1027–1037. https://doi.org/10.1242/jeb.203.6.1027 349 McGeer JC, Szebedinszky C, McDonald DG, Wood CM (2002) The role of dissolved organic carbon in moderating the bioavailability and toxicity of Cu to rainbow trout during chronic waterborne exposure. Comp Biochem Physiol Part C Toxicol Pharmacol 133:147–160. https://doi.org/10.1016/S1532-0456(02)00084-4 McKnight DM, Boyer EW, Westerhoff PK, et al (2001) Spectrofluorometric characterization of dissolved organic matter for indication of precursor organic material and aromaticity. Limnol Oceanogr 46:38–48. https://doi.org/10.4319/lo.2001.46.1.0038 McNeil DG, Westergaard S, Cheshire KJM, et al (2013) Effects of hyper-saline conditions upon six estuarine fish species from the Coorong and Murray Mouth. Inland waters & catchment ecology, SARDI South Australian Research and Development Institute, SARDI Aquatics Sciences Publication No F2009/000014-4, Research report series no. 700, Henley Beach, SA. McNicol G, Hood E, Butman DE, et al (2023) Small, coastal temperate rainforest watersheds dominate dissolved organic carbon transport to the northeast Pacific ocean. Geophys Res Lett 50:. https://doi.org/10.1029/2023gl103024 McWilliams PG (1982) The effects of calcium on sodium fluxes in the rainbow trout Salmo trutta, in neutral and acid media. Journal of Biological Chemistry 126:277–286 McWilliams PG, Potts WTW (1978) The effects of pH and calcium concentrations on gill potentials in the brown trout, Salmo trutta. Journal of Biological Chemistry 126:277–286 Milligan CL, Wood CM (1982) Disturbances in haematology, fluid volume distribution and circulatory function associated with low nvironmental pH in the rainbow trout, Salmo gairdneri. J Exp Biol 99:397–415. https://doi.org/10.1242/jeb.99.1.397 Minami T, Tanaka M (1992) Life history cycles in flatfish from the northwestern Pacific, with particular reference to their early life histories. Neth J Sea Res 29:35–48. https://doi.org/10.1016/0077-7579(92)90006-z Mistry AC, Honda S, Hirata T, et al (2001) Eel urea transporter is localized to chloride cells and is salinity dependent. Am J Physiol-Regul Integr Comp Physiol 281:R1594–R1604. https://doi.org/10.1152/ajpregu.2001.281.5.r1594 Monteith DT, Henrys PA, Hruška J, et al (2023) Long-term rise in riverine dissolved organic carbon concentration is predicted by electrolyte solubility theory. Sci Adv 9: https://doi.org/10.1126/sciadv.ade3491 Monteith DT, Stoddard JL, Evans CD, et al (2007) Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry. Nature 450:537–540. https://doi.org/10.1038/nature06316 350 Moran D, Wells R (2007) Ontogenetic scaling of fish metabolism in the mouse-to-elephant mass magnitude range. Comp Biochem Physiol A Mol Integr Physiol 148: https://doi.org/10.1016/j.cbpa.2007.08.006 Moreno-Castilla C, Álvarez-Merino MA, López-Ramón MV, Rivera-Utrilla J (2004) Cadmium ion adsorption on different carbon adsorbents from aqueous solutions. effect of surface chemistry, pore texture, ionic strength, and dissolved natural organic matter. Langmuir 20:8142–8148. https://doi.org/10.1021/la049253m Morgan TP, Grosell M, Gilmour KM, et al (2004) Time course analysis of the mechanism by which silver inhibits active Na+ and Cl− uptake in gills of rainbow trout. Am J Physiol-Regul Integr Comp Physiol 287:R234–R242. https://doi.org/10.1152/ajpregu.00448.2003 Morris C, Crémazy A, Brauner CJ, Wood CM (2025a) Interactions of major ions, pH, and dissolved organic carbon (DOC) on transepithelial potential (TEP) in rainbow trout: are there implications for the prediction of salt toxicity? Arch Environ Contam Toxicol 88:303–323. https://doi.org/10.1007/s00244-025-01125-w Morris C, Crémazy A, Mota da Silva, Johannsson O, Brauner CJ, Wood CM, Val AL (2025b) The acute osmoregulatory effects of low pH and Cu, alone and in combination, on the dwarf cichlid (Apistogramma agassizii) in Rio Negro blackwater and Rio Solimões whitewater: Flux rates of ions, nitrogenous wastes and water. J of Fish Biol 1- 17. https://doi.org/10.1111/jfb.70157 Morris C, Martins C, Zulian S, et al (2024a) The effects of dissolved organic carbon and model compounds (DOC analogues) on diffusive water flux, oxygen consumption, nitrogenous waste excretion rates and gill transepithelial potential in Pacific sanddab (Citharichthys sordidus) at two salinities. J Comp Physiol B 194:805–825. https://doi.org/10.1007/s00360-024-01580-2 Morris C, Sakarya M, Koh O, O’Donnell M (2020) Alterations in hemolymph ion concentrations and pH in adult Daphnia magna in response to elevations in major ion concentrations in freshwater. Environ Toxicol Chem 40:366–379. https://doi.org/10.1002/etc.4919 Morris C, Val AL, Brauner CJ, Wood CM (2021) The physiology of fish in acidic waters rich in dissolved organic carbon, with specific reference to the Amazon basin: Ionoregulation, acid-base regulation, ammonia excretion, and metal toxicity. J Exp Zool Part A Ecol Integr Physiol 335:843–863. https://doi.org/10.1002/jez.2468 Morris C, Wood CM (2023) The effect of salinity and calcium on diffusive water flux, oxygen consumption, and nitrogenous waste excretion rates in Pacific sanddab (Citharichthys sordidus) and Rock sole (Lepidopsetta bilineata). Mar Biol 170:https://doi.org/10.1007/s00227-023-04245-w 351 Morris C, Zulian S, Brauner CJ, et al (2024b) A critical assessment of physicochemical indices used to characterise natural dissolved organic carbon (DOC), their inter-relationships, and the effects of pH. Environ Chem 21 https://doi.org/10.1071/EN24021 Morris C, Zulian S, Smith DS, et al (2024c) Using physicochemical properties to predict the impact of natural dissolved organic carbon on transepithelial potential in the freshwater rainbow trout (Oncorhynchus mykiss) at neutral and acidic pH. Fish Physiol Biochem 50:2619–2635. https://doi.org/10.1007/s10695-024-01409-3 Motais R, Isaia J, Rankin JC, Maetz J (1969) Adaptive changes of the water permeability of the teleostean gill epithelium in relation to external salinity. J Exp Biol 51:529–546. https://doi.org/10.1242/jeb.51.2.529 Moulatlet GM, Yacelga N, Rico A, et al (2023) A systematic review on metal contamination due to mining activities in the Amazon basin and associated environmental hazards. Chemosphere 339:139700. https://doi.org/10.1016/j.chemosphere.2023.139700 Mount DR, Erickson RJ, Highland TL, et al (2016) The acute toxicity of major ion salts to Ceriodaphnia dubia: I. influence of background water chemistry. Environ Toxicol Chem 35:3039–3057. https://doi.org/10.1002/etc.3487 Mount DR, Gulley DD, Hockett JR, et al (1997) Statistical models to predict the toxicity of major ions to Ceriodaphnia dubia, Daphnia magna and Pimephales promelas (fathead minnows). Environ Toxicol Chem 16:2009–2019. https://doi.org/10.1002/etc.5620161005 Nadella SR, Fitzpatrick JL, Franklin N, et al (2009) Toxicity of dissolved Cu, Zn, Ni and Cd to developing embryos of the blue mussel (Mytilus trossolus) and the protective effect of dissolved organic carbon. Comp Biochem Physiol Part C Toxicol Pharmacol 149:340–348. https://doi.org/10.1016/j.cbpc.2008.09.001 Nadella SR, Tellis M, Diamond R, et al (2013) Toxicity of lead and zinc to developing mussel and sea urchin embryos: Critical tissue residues and effects of dissolved organic matter and salinity. Comp Biochem Physiol Part C Toxicol Pharmacol 158:72–83. https://doi.org/10.1016/j.cbpc.2013.04.004 Nakada T, Westhoff CM, Kato A, Hirose S (2007) Ammonia secretion from fish gill depends on a set of Rh glycoproteins. FASEB J 21:1067–1074. https://doi.org/10.1096/fj.06-6834com Namjesnik-Dejanovic K, Cabaniss SE (2004) Reverse-phase HPLC method for measuring polarity distributions of natural organic matter. Environ Sci Technol 38:1108–1114. https://doi.org/10.1021/es0344157 352 Nawata CM, Hung CCY, Tsui TKN, et al (2007) Ammonia excretion in rainbow trout (Oncorhynchus mykiss): evidence for Rh glycoprotein and H+-ATPase involvement. Physiol Genomics 31:463–474. https://doi.org/10.1152/physiolgenomics.00061.2007 Nawata CM, Wood CM, O’Donnell MJ (2010) Functional characterization of Rhesus glycoproteins from an ammoniotelic teleost, the rainbow trout, using oocyte expression and SIET analysis. J Exp Biol 213:1049–1059. https://doi.org/10.1242/jeb.038752 Nelson JA (2015) Pickled fish anyone? In: Riesch R, Tobler M, Plath M (eds.) Extremophile Fishes: Ecology, evolution, and physiology of teleosts in extreme environments. Springer International Publishing, Cham, Switzerland, pp 193–215 Németh-Cahalan KL, Hall JE (2000) pH and calcium regulate the water permeability of aquaporin. J Biol Chem 275:6777–6782. https://doi.org/10.1074/jbc.275.10.6777 Németh-Cahalan KL, Kalman K, Hall JE (2004) Molecular basis of pH and Ca2+ regulation of aquaporin water permeability. J Gen Physiol 123:573–580. https://doi.org/10.1085/jgp.200308990 Nimptsch J, Woelfl S, Kronvang B, et al (2014) Does filter type and pore size influence spectroscopic analysis of freshwater chromophoric DOM composition? Limnologica 48:57–64. https://doi.org/10.1016/j.limno.2014.06.003 Niyogi S, Wood CM (2004) Biotic Ligand Model, a flexible tool for developing site-specific water quality guidelines for metals. Environ Sci Technol 38:6177–6192. https://doi.org/10.1021/es0496524 N’kaya GDM, Orange D, Bayonne Padou SM, et al (2020) Temporal variability of sediments, dissolved solids and dissolved organic matter fluxes in the Congo River at Brazzaville/Kinshasa. Geosciences 10:341. https://doi.org/10.3390/geosciences10090341 Nogueira LS, Bianchini A, Smith S, et al (2017) Physiological effects of five different marine natural organic matters (NOMs) and three different metals (Cu, Pb, Zn) on early life stages of the blue mussel (Mytilus galloprovincialis). PeerJ 5:e3141. https://doi.org/10.7717/peerj.3141 Nogueira LS, Bianchini A, Smith S, et al (2018) Physiological effects of marine natural organic matter and metals in early life stages of the North Pacific native marine mussel Mytilus trossulus; a comparison with the invasive Mytilus galloprovincialis. Mar Environ Res 135:136–144. https://doi.org/10.1016/j.marenvres.2017.12.009 Oduleye S (1975) The effects of calcium on water balance of the brown trout Salmo trutta. J Exp Biol, 63(2):343–356. Oliveira CPF (2003) Efeito de dois metais pesados presentes na água de formação derivada da extração do petróleo da província petroleira do Urucu‐Am sobre o tambaqui, Colossoma macropomum (Cuvier, 1818). MSc Thesis, Manaus, Brazil. 353 Olson K (1992) Blood and extracellular fluid volume regulation. In: Hoar WS, Randall DJ, Farrell AP (eds.) Fish Physiology Volume 12B. Academic Press, San Diego, California, USA pp 135-254. Onukwufor JO, Wood CM (2022) The osmorespiratory compromise in marine flatfish: differential effects of temperature, salinity, and hypoxia on diffusive water flux and oxygen consumption of English sole (Parophrys vetulus) and Pacific sanddab (Citharichthys sordidus). Mar Biol 169: https://doi.org/10.1007/s00227-022-04040-z Onukwufor JO, Wood CM (2020a) Reverse translation: effects of acclimation temperature and acute temperature challenges on oxygen consumption, diffusive water flux, net sodium loss rates, Q10 values and mass scaling coefficients in the rainbow trout (Oncorhynchus mykiss). J Comp Physiol B 190:205–217. https://doi.org/10.1007/s00360-020-01259-4 Onukwufor JO, Wood CM (2018) The osmorespiratory compromise in rainbow trout (Oncorhynchus mykiss): The effects of fish size, hypoxia, temperature and strenuous exercise on gill diffusive water fluxes and sodium net loss rates. Comp Biochem Physiol A Mol Integr Physiol 219–220:10–18. https://doi.org/10.1016/j.cbpa.2018.02.002 Onukwufor JO, Wood CM (2020b) Osmorespiratory compromise in zebrafish (Danio rerio): effects of hypoxia and acute thermal stress on oxygen consumption, diffusive water flux, and sodium net loss rates. Zebrafish 17:400–411. https://doi.org/10.1089/zeb.2020.1947 Pace ML, Reche I, Cole JJ, et al (2012) pH change induces shifts in the size and light absorption of dissolved organic matter. Biogeochemistry 108:109–118. https://doi.org/10.1007/s10533-011-9576-0 Pagano T, Bida M, Kenny J (2014) Trends in levels of allochthonous dissolved organic carbon in natural water: A review of potential mechanisms under a changing climate. Water 6:2862–2897. https://doi.org/10.3390/w6102862 Palviainen M, Peltomaa E, Laurén A, et al (2022) Water quality and the biodegradability of dissolved organic carbon in drained boreal peatland under different forest harvesting intensities. Sci Total Environ 806:150919. https://doi.org/10.1016/j.scitotenv.2021.150919 Panneer Selvam B, Lapierre J-F, Soares ARA, et al (2019) Photo-reactivity of dissolved organic carbon in the freshwater continuum. Aquat Sci 81:57. https://doi.org/10.1007/s00027-019-0653-0 Parks SK, Tresguerres M, Goss GG (2008) Theoretical considerations underlying Na+ uptake mechanisms in freshwater fishes. Comp Biochem Physiol Part C Toxicol Pharmacol 148:411–418. https://doi.org/10.1016/j.cbpc.2008.03.002 354 Parks SK, Tresguerres M, Goss GG (2007) Interactions between Na+ channels and Na+ -HCO3− cotransporters in the freshwater fish gill MR cell: a model for transepithelial Na+ uptake. Am J Physiol-Cell Physiol 292:C935–C944. https://doi.org/10.1152/ajpcell.00604.2005 Patel-Sorrentino N, Mounier S, Benaim JY (2002) Excitation–emission fluorescence matrix to study pH influence on organic matter fluorescence in the Amazon basin rivers. Water Res 36:2571–2581. https://doi.org/10.1016/S0043-1354(01)00469-9 Peacock M, Freeman C, Gauci V, et al (2015) Investigations of freezing and cold storage for the analysis of peatland dissolved organic carbon (DOC) and absorbance properties. Environ Sci Process Impacts 17:1290–1301. https://doi.org/10.1039/C5EM00126A Pelster B, Wood CM, Braz-Mota S, Val AL (2020) Gills and air-breathing organ in O2 uptake, CO2 excretion, N-waste excretion, and ionoregulation in small and large pirarucu (Arapaima gigas). J Comp Physiol B 190:569–583. https://doi.org/10.1007/s00360-020-01286-1 Perrin DD (1958) Stability of metal complexes with salicylic acid and related substances. Nature 182:741–742. https://doi.org/10.1038/182741a0 Perry SF (1997) The chloride cell: structure and function in the gills of freshwater fishes. Annu Rev Physiol 59:325–347. https://doi.org/10.1146/annurev.physiol.59.1.325 Perry SF, Gilmour KM, Duarte RM, et al (2021) The effects of dissolved organic carbon on the reflex ventilatory responses of the neotropical teleost (Colossoma macropomum) to hypoxia or hypercapnia. Chemosphere 277:130314. https://doi.org/10.1016/j.chemosphere.2021.130314 Petersen RC (1991) The contradictory biological behavior of humic substances in the aquatic environment. In: Allard B, Borén H, Grimvall A (eds.) Humic Substances in the Aquatic and Terrestrial Environment. Springer Berlin Heidelberg, Berlin, Heidelberg, Germany pp 367–390 Peuravuori J, Pihlaja K (1997) Molecular size distribution and spectroscopic properties of aquatic humic substances. Anal Chim Acta 337:133–149. https://doi.org/10.1016/S0003-2670(96)00412-6 Phillips JC, McKinley GA, Bennington V, et al (2015) The potential for CO2-induced acidification in freshwater: A Great Lakes Case Study. Oceanography 25:136-145. https://doi.org/10.5670/oceanog.2015.37 Pinto AGN, Horbe AMC, Silva MSR, et al (2009) The human action effects on the hydrogeochemistry of Negro river at the Manaus shoreline. Acta Amazonica 30:627–638 Pinto AGN, Silva MSR, Pascoaloto D, Santos HMC (2008) Effects of the anthropic contribution on the Negro river water, in Manaus, Amazonas State. Caminhos de Geografia 10:26–32 355 Playle RC, Dixon, DG, Burnison BK (1993) Copper and cadmium binding to fish gills: Modification by dissolved organic carbon and synthetic ligands. Can J Fish Aquat Sci 50:2667–2677 Po BHK, Wood CM (2021) Transepithelial potential (TEP) response as an indicator of major ion toxicity in rainbow trout and goldfish exposed to 10 different salts in ion-poor water. Environ Pollut 276:116699. https://doi.org/10.1016/j.envpol.2021.116699 Po BHK, Wood CM (2022) Transepithelial potential remains indicative of major ion toxicity in rainbow trout (Oncorhynchus mykiss) after 4-day pre-exposure to major salts. Aquat Toxicol 246:106132. https://doi.org/10.1016/j.aquatox.2022.106132 Pond GJ, Passmore ME, Borsuk FA, et al (2008) Downstream effects of mountaintop coal mining: comparing biological conditions using family- and genus-level macroinvertebrate bioassessment tools. J North Am Benthol Soc 27:717–737. https://doi.org/10.1899/08-015.1 Potts WTW (1984) Transepithelial potentials in fish gills. In: Hoar WS, Randall DJ (eds.) Fish Physiology. Volume 10B, Academic Press, New York, USA. pp 105–128 Potts WTW, Fleming WR (1970) The effects of prolactin and divalent ions on the permeability to water of Fundulus kansae. J Exp Biol 53:317–327. https://doi.org/10.1242/jeb.53.2.317 Potts WTW, Foster MA, Rudy PP, Howells GP (1967) Sodium and water balance in the cichlid teleost, Tilapia mossambica. J Exp Biol 47:461–470. https://doi.org/10.1242/jeb.47.3.461 Potts WTW, Parry G (2016) Osmotic and ionic regulation in animals: international series of monographs on pure and applied biology. Volume 19, Elsevier, New York, US 438 pp Powell KJ, Brown PL, Byrne RH, et al (2007) Chemical speciation of environmentally significant metals with inorganic ligands Part 2: The Cu2+-OH-, Cl-, CO32-, SO42-, and PO43- systems (IUPAC Technical Report). Pure Appl Chem 81:2425–2476. https://doi.org/10.1351/pac-rep-09-03-05 Preest MR, Gonzalez RJ, Wilson RW (2005) A pharmacological examination of Na+ and Cl− transport in two species of freshwater fish. Physiol Biochem Zool 78:259–272. https://doi.org/10.1086/427058 Preston GM, Carroll TP, Guggino WB, Agre P (1992) Appearance of water channels in Xenopus oocytes expressing red cell CHIP28 protein. Science 256:385–387. https://doi.org/10.1126/science.256.5055.385 Pullin MJ, Cabaniss SE (1995) Rank analysis of the pH-dependent synchronous fluorescence spectra of six standard humic substances. Environ Sci Technol 29:1460–1467. https://doi.org/10.1021/es00006a006 356 Quijada-Rodriguez AR, Kuan P-L, Sung P-H, et al (2021) Anthropogenic CO2-mediated freshwater acidification limits survival, calcification, metabolism, and behaviour in stress-tolerant freshwater crustaceans. Biogeosciences 18:6287–6300. https://doi.org/10.5194/bg-18-6287-2021 Rackowski J, Pikitch E (1989) Species profiles: Life histories and environmental requirements of coastal fishes and invertebrates (Pacific Southwest), Pacific and speckled sanddabs. U.S. Fish and Wildlife Service Biological Report, Vol 82. Rahmatullah M, Boyde TRC (1980) Improvements in the determination of urea using diacetyl monoxime; methods with and without deproteinisation. Clin Chim Acta 107:3–9. https://doi.org/10.1016/0009-8981(80)90407-6 Ramanathan T, Ollivier Q, Rahman A, et al (2024) Long-term dissolved organic carbon changes in Woronora drinking water system in Australia. Chemosphere 364:143047. https://doi.org/10.1016/j.chemosphere.2024.143047 Randall DJ, Brauner CJ, Wilson JM (1996). Physiology and Biochemistry of the Fishes of the Amazon. In: Val AL, Almeida-Val, VMF, Randall DJ (eds.) Acid excretion in Amazonian fish, INPA, Manaus, Brazil. pp 91–100 Randall DJ, Lin H (1993) Effects of water pH on gas and ion transfer across fish gills. In: Rankin JC, Jensen FB (eds.) Fish Ecophysiology. Springer Netherlands, Dordrecht, pp 265–275 Randall DJ, Tsui TKN (2002) Ammonia toxicity in fish. Mar Pollut Bull 45:17–23. https://doi.org/10.1016/S0025-326X(02)00227-8 Rasmussen AD, Bjerregaard P (1995) The effect of salinity and calcium concentration on the apparent water permeability of Cherax destructor, Astacus astacus and Carcinus maenas (Decapoda, Crustacea). Comp Biochem Physiol A Physiol 111:171–175. https://doi.org/10.1016/0300-9629(95)98534-n Ratner B (2009) The correlation coefficient: Its values range between +1/−1, or do they? J Target Meas Anal Mark 17:139–142. https://doi.org/10.1057/jt.2009.5 Reid SD, McDonald DG (1991) Metal binding activity of the gills of rainbow trout (Oncorhynchus mykiss). Can J Fish Aquat Sci 48:1061–1068. https://doi.org/10.1139/f91-125 Richards JG, Curtis PJ, Burnison BK, Playle RC (2001) Effects of natural organic matter source on reducing metal toxicity to rainbow trout (Oncorhynchus mykiss) and on metal binding to their gills. Environ Toxicol Chem 20:1159–1166. https://doi.org/10.1002/etc.5620200604 Robertson LM, Kochhann D, Bianchini A, et al (2015) Gill paracellular permeability and the osmorespiratory compromise during exercise in the hypoxia-tolerant Amazonian oscar 357 (Astronotus ocellatus). J Comp Physiol B 185:741–754. https://doi.org/10.1007/s00360-015-0918-4 Robertson LM, Wood CM (2014) Measuring gill paracellular permeability with polyethelene glycol-4000 in freely swimming trout: proof of principle. J Exp Biol. https://doi.org/10.1242/jeb.099879 Robroek BJM, Jassey VEJ, Payne RJ, et al (2017) Taxonomic and functional turnover are decoupled in European peat bogs. Nat Commun 8:1161. https://doi.org/10.1038/s41467-017-01350-5 Rocha AJ, Gomes V, Van Ngan P, et al (2005) Metabolic demand and growth of juveniles of Centropomus parallelus as function of salinity. J Exp Mar Biol Ecol 316:157–165. https://doi.org/10.1016/j.jembe.2004.11.006 Rocha AJS, Gomes V, Ngan PV, et al (2007) Effects of anionic surfactant and salinity on the bioenergetics of juveniles of Centropomus parallelus (Poey). Ecotoxicol Environ Saf 68:397–404. https://doi.org/10.1016/j.ecoenv.2006.10.007 Rodríguez FJ, Schlenger P, García-Valverde M (2014) A comprehensive structural evaluation of humic substances using several fluorescence techniques before and after ozonation. Part I: Structural characterization of humic substances. Sci Total Environ 476–477:718–730. https://doi.org/10.1016/j.scitotenv.2013.11.150 Rogers SG, Targett TE, Van Sant SB (1984) Fish-nursery use in Georgia salt-marsh estuaries: the influence of springtime freshwater conditions. Trans Am Fish Soc 113:595–606. https://doi.org/10.1577/1548-8659(1984)113 Rooper CN, Gunderson DR, Armstrong DA (2006) Evidence for resource partitioning and competition in nursery estuaries by juvenile flatfish in Oregon and Washington. Fish Bull 104:616–622 Rudy PP (1967) Water permeability in selected decapod crustacea. Comp Biochem Physiol 22:581–589. https://doi.org/10.1016/0010-406X(67)90620-2 Ruhr IM, Wood CM, Schauer KL, et al (2020) Is aquaporin‐3 involved in water‐permeability changes in the killifish during hypoxia and normoxic recovery, in freshwater or seawater? J Exp Zool Part A Ecol Integr Physiol 333:511–525. https://doi.org/10.1002/jez.2393 Ruiz-Jarabo I, Herrera M, Hachero-Cruzado I, et al (2015) Environmental salinity and osmoregulatory processes in cultured flatfish. Aquac Res 46:10–29. https://doi.org/10.1111/are.12424 Sabater F, Meyer JL, Edwards RT (1993) Longitudinal patterns of dissolved organic carbon concentration and suspended bacterial density along a blackwater river. Biogeochemistry 21:73–93. https://doi.org/10.1007/BF00000872 358 Sadauskas‐Henrique H, De Souza‐Bastos LR, Smith DS, et al (2025) Dissolved organic carbon from “white” waters in Amazon basin (Brazil) and the osmoregulatory responses of tambaqui (Colossoma macropomum) in neutral and acidic environments. J Fish Biol. https://doi.org/10.1111/jfb.16054 Sadauskas‐Henrique H, Smith DS, Val AL, Wood CM (2021) Physicochemical properties of the dissolved organic carbon can lead to different physiological responses of zebrafish (Danio rerio) under neutral and acidic conditions. J Exp Zool Part A Ecol Integr Physiol 335:864–878. https://doi.org/10.1002/jez.2537 Sadauskas‐Henrique H, Wood CM, Souza‐Bastos LR, et al (2019) Does dissolved organic carbon from Amazon black water (Brazil) help a native species, the tambaqui Colossoma macropomum to maintain ionic homeostasis in acidic water? J Fish Biol 94:595–605. https://doi.org/10.1111/jfb.13943 Sanwlani N, Evans CD, Müller M, et al (2022) Rising dissolved organic carbon concentrations in coastal waters of northwestern Borneo related to tropical peatland conversion. Sci Adv 8:eabi5688. https://doi.org/10.1126/sciadv.abi5688 Schreiber AM (2001) Metamorphosis and early larval development of the flatfishes (Pleuronectiformes): an osmoregulatory perspective. Comp Biochem Physiol B Biochem Mol Biol 129:587–595. https://doi.org/10.1016/s1096-4959(01)00346-3 Schuler MS, Cañedo-Argüelles M, Hintz WD, et al (2019) Regulations are needed to protect freshwater ecosystems from salinization. Philos Trans R Soc B Biol Sci 374:20180019. https://doi.org/10.1098/rstb.2018.0019 Schwartz ML, Curtis PJ, Playle RC (2004) Influence of natural organic matter source on acute copper, lead, and cadmium toxicity to rainbow trout (Oncorhynchus mykiss). Environ Toxicol Chem 23:2889–2899. https://doi.org/10.1897/03-561.1 Seyler PT, Boaventura GR (2003) Distribution and partition of trace metals in the Amazon basin. Hydrol Process 17:1345–1361. https://doi.org/10.1002/hyp.1288 Shiller AM, Duan S, Van Erp P, Bianchi TS (2006) Photo‐oxidation of dissolved organic matter in river water and its effect on trace element speciation. Limnol Oceanogr 51:1716–1728. https://doi.org/10.4319/lo.2006.51.4.1716 Silva P, Solomon R, Spokes K, Epstein FH (1977) Ouabain inhibition of gill Na‐K‐ATPase: Relationship to active chloride transport. J Exp Zool 199:419–426. https://doi.org/10.1002/jez.1401990316 Smedema LK, Shiati K (2002) Irrigation and salinity: a perspective review of the salinity hazards of irrigation development in the arid zone. Irrig Drain Syst 16:161–174. https://doi.org/10.1023/A:1016008417327 359 Smith D, Kramer J (1999) Multi-site proton interactions with natural organic matter. Environ Int 25:307–314. https://doi.org/10.1016/S0160-4120(98)00108-1 Smith DS, Ferris FG (2001) Proton binding by hydrous ferric oxide and aluminum oxide surfaces interpreted using fully optimized continuous pKa Spectra. Environ Sci Technol 35:4637–4642. https://doi.org/10.1021/es0018668 Sobocinski K, Ciannelli L, Wakefield W, et al (2018) Distribution and abundance of juvenile demersal fishes in relation to summer hypoxia and other environmental variables in coastal Oregon, USA. Estuar Coast Shelf Sci 205:75–90 Souza-Bastos LR, Val AL, Wood CM (2017) Are Amazonian fish more sensitive to ammonia? Toxicity of ammonia to eleven native species. Hydrobiologia 789:143–155. https://doi.org/10.1007/s10750-015-2623-4 Stagl J, Mayr E, Koch H, et al (2014) Effects of climate change on the hydrological cycle in central and eastern europe. In: Rannow S, Neubert M (eds.) Managing Protected Areas in Central and Eastern Europe Under Climate Change: Advances in Global Change Research. Springer, Dordrecht, USA Stedmon CA, Bro R (2008) Characterizing dissolved organic matter fluorescence with parallel factor analysis: a tutorial. Limnol Oceanogr Methods 6:572–579. https://doi.org/10.4319/lom.2008.6.572 Stedmon CA, Markager S (2005) Resolving the variability in dissolved organic matter fluorescence in a temperate estuary and its catchment using PARAFAC analysis. Limnol Oceanogr 50:686–697. https://doi.org/10.4319/lo.2005.50.2.0686 Steffensen JF, Lomholt JP, Johansen K (1982) Gill ventilation and O2 extraction during graded hypoxia in two ecologically distinct species of flatfish, the flounder (Platichthys flesus) and the plaice (Pleuronectes platessa). Environ Biol Fishes 7:157–163. https://doi.org/10.1007/bf00001786 Steinberg CEW, Kamara S, Prokhotskaya VYu, et al (2006) Dissolved humic substances – ecological driving forces from the individual to the ecosystem level? Freshw Biol 51:1189–1210. https://doi.org/10.1111/j.1365-2427.2006.01571.x Steinberg CEW, Paul A, Pflugmacher S, et al (2003) Pure humic substances have the potential to act as xenobiotic chemicals - A review. ResearchGate 12:391–401 Stevenson FJ (1994) Humus chemistry: genesis, composition, reactions. Volume 2, John Wiley & Sons, New York, USA. Stewart PA (1983) Modern quantitative acid–base chemistry. Can J Physiol Pharmacol 61:1444–1461. https://doi.org/10.1139/y83-207 360 Sucker C, Krause K (2010) Increasing dissolved organic carbon concentrations in freshwaters: what is the actual driver? IForest - Biogeosciences For 3:106–108. https://doi.org/10.3832/ifor0546-003 Sun L, Perdue EM, McCarthy JF (1995) Using reverse osmosis to obtain organic matter from surface and ground waters. Water Res 29:1471–1477. https://doi.org/10.1016/0043-1354(94)00295-i Tait TN, Cooper CA, McGeer JC, et al (2016) Influence of dissolved organic matter (DOM) source on copper speciation and toxicity to Brachionus plicatilis. Environ Chem 13:496. https://doi.org/10.1071/en15123 Takács M (1999) Characterization of natural organic matter from eight Norwegian surface waters: Proton and copper binding. Environ Int 25:315–323. https://doi.org/10.1016/S0160-4120(98)00109-3 Tavares-Dias M, Ferreira JS, Affonso EG, et al (2011) Toxicity and effects of copper sulfate on parasitic control and hematological response of tambaqui Colossoma macropomum. Bol Inst Pesca, 37:4. Taylor LN, Baker DW, Wood CM, Gordon McDonald D (2002) An in vitro approach for modelling branchial copper binding in rainbow trout. Comp Biochem Physiol Part C Toxicol Pharmacol 133:111–124. https://doi.org/10.1016/s1532-0456(02)00101-1 Thornburgh K (1980) Patterns of resource utilization in flatfish communities. Doctoral Thesis, University of Washington, Seattle, Washington, USA. Thurman EM (1985) Organic geochemistry of natural waters. Springer Netherlands, Dordrecht Tingaud-Sequeira A, Calusinska M, Finn RN, et al (2010) The zebrafish genome encodes the largest vertebrate repertoire of functional aquaporins with dual paralogy and substrate specificities similar to mammals. BMC Evol Biol 10: https://doi.org/10.1186/1471-2148-10-38 Tipping E (2002) Cation binding by humic substances, 1st edn. Cambridge University Press, Cambridge, UK. Tipping E, Hurley MA (1988) A model of solid-solution interactions in acid organic soils, based on the complexation properties of humic substances. J Soil Sci 39:505–519. https://doi.org/10.1111/j.1365-2389.1988.tb01235.x Tipsmark CK, Sørensen KJ, Madsen SS (2010) Aquaporin expression dynamics in osmoregulatory tissues of Atlantic salmon during smoltification and seawater acclimation. J Exp Biol 213:368–379. https://doi.org/10.1242/jeb.034785 361 Ultsch GR, Gros G (1979) Mucus as a diffusion barrier to oxygen: Possible role in O2 uptake at low pH in carp (Cyprinus carpio) gills. Comp Biochem Physiol A Physiol 62:685–689. https://doi.org/10.1016/0300-9629(79)90125-7 USEPA (2011) A field-based aquatic life benchmark for conductivity in central Appalachian streams (final report). Cincinnati, Ohio, USA Val AL (2019) Fishes of the Amazon: diversity and beyond. An Acad Bras Ciênc 91:e20190260. https://doi.org/10.1590/0001-3765201920190260 Val AL, De Almeida-Val VMF (1995) Fishes of the Amazon and their environment. Springer Berlin Heidelberg, Berlin, Heidelberg, Germany Val AL, Wood CM (2022) Global change and physiological challenges for fish of the Amazon today and in the near future. J Exp Biol 225: https://doi.org/10.1242/jeb.216440 Valenti G, Procino G, Tamma G, et al (2005) Minireview: Aquaporin 2 trafficking. Endocrinology 146:5063–5070. https://doi.org/10.1210/en.2005-0868 Van Den Thillart G, Kesbeke F (1978) Anaerobic production of carbon dioxide and ammonia by goldfish Carassius auratus (L.). Comp Biochem Physiol A Physiol 59:393–400. https://doi.org/10.1016/0300-9629(78)90185-8 Van Waarde A (1983) Aerobic and anaerobic ammonia production by fish. Comp Biochem Physiol Part B Comp Biochem 74:675–684. https://doi.org/10.1016/0305-0491(83)90127-x Verbost PM, Flik G, Lock RA, Wendelaar Bonga SE (1987) Cadmium inhibition of Ca2+ uptake in rainbow trout gills. Am J Physiol-Regul Integr Comp Physiol 253:R216–R221. https://doi.org/10.1152/ajpregu.1987.253.2.r216 Verbost PM, Van Rooij J, Flik G, et al (1989) The movement of cadmium through freshwater trout branchial epithelium and its interference with calcium transport. J Exp Biol 145:185–197. https://doi.org/10.1242/jeb.145.1.185 Verdouw H, Van Echteld CJA, Dekkers EMJ (1978) Ammonia determination based on indophenol formation with sodium salicylate. Water Res 12:399–402. https://doi.org/10.1016/0043-1354(78)90107-0 Vigneault B, Percot A, Lafleur M, Campbell PGC (2000) Permeability changes in model and phytoplankton membranes in the presence of aquatic humic substances. Environ Sci Technol 34:3907–3913. https://doi.org/10.1021/es001087r von Wandruszka R (2000) Humic acids: Their detergent qualities and potential uses in pollution remediation. Geochem Trans 1:10. https://doi.org/10.1186/1467-4866-1-10 362 Walker I, Henderson PA (1996) Ecophysiological aspects of Amazonian blackwater litterbank fish communities. In: AVL. Val, VMF Almeida‐Val, DJ Randall (eds.), Physiology and Biochemistry of Fishes of the Amazon. Instituto Nacional de Pesquisas da Amazonia (INPA), Manaus, Brazil, pp 7–22 Walsh P, Wang, Campbell C., et al (2001) Patterns of nitrogenous waste excretion and gill urea transporter mRNA expression in several species of marine fish. Mar Biol 139:839–844. https://doi.org/10.1007/s002270100639 Walsh PJ, Veauvy CM, McDonald MD, et al (2007) Piscine insights into comparisons of anoxia tolerance, ammonia toxicity, stroke and hepatic encephalopathy. Comp Biochem Physiol A Mol Integr Physiol 147:332–343. https://doi.org/10.1016/j.cbpa.2006.09.001 Wang B, Feng L, Jiang W-D, et al (2015) Copper-induced tight junction mRNA expression changes, apoptosis and antioxidant responses via NF-κB, TOR and Nrf2 signaling molecules in the gills of fish: preventive role of arginine. Aquat Toxicol Amst Neth 158:125–137. https://doi.org/10.1016/j.aquatox.2014.10.025 Weihrauch D, Wilkie MP, Walsh PJ (2009) Ammonia and urea transporters in gills of fish and aquatic crustaceans. J Exp Biol 212:1716–1730. https://doi.org/10.1242/jeb.024851 Weiss LC, Pötter L, Steiger A, et al (2018) Rising pCO2 in freshwater ecosystems has the potential to negatively affect predator-induced defenses in Daphnia. Curr Biol 28:327-332.e3. https://doi.org/10.1016/j.cub.2017.12.022 Wendelaar Bonga SE, Van Der Meij JCA (1981) Effect of ambient osmolarity and calcium on prolactin cell activity and osmotic water permeability of the gills in the teleost Sarotherodon mossambicus. Gen Comp Endocrinol 43:432–442. https://doi.org/10.1016/0016-6480(81)90227-6 Wenk J, Graf C, Aeschbacher M, et al (2021) Effect of solution pH on the dual role of dissolved organic matter in sensitized pollutant photooxidation. Environ Sci Technol 55:15110–15122. https://doi.org/10.1021/acs.est.1c03301 Wershaw RL (1999) Molecular aggregation of humic substances. Soil Sci 164:803–813. https://doi.org/10.1097/00010694-199911000-00004 Wheeler JR (1976) Fractionation by molecular weight of organic substances in Georgia coastal water. Limnol Oceanogr 21:846–852. https://doi.org/10.4319/lo.1976.21.6.0846 Wilkie MP (1997) Mechanisms of ammonia excretion across fish gills. Comp Biochem Physiol A Physiol 118:39–50. https://doi.org/10.1016/S0300-9629(96)00407-0 Wilkie MP (2002) Ammonia excretion and urea handling by fish gills: present understanding and future research challenges. J Exp Zool 293:284–301. https://doi.org/10.1002/jez.10123 363 Wilson RW, Wood CM, Gonzalez RJ, et al (1999) Ion and acid‐base balance in three species of Amazonian fish during gradual acidification of extremely soft water. Physiol Biochem Zool 72:277–285. https://doi.org/10.1086/316672 Wolf K (1963) Physiological salines for fresh-water teleosts. Progress Fish-Cult 25:135–140. https://doi.org/10.1577/1548-8659(1963)25[135:psfft]2.0.co;2 Wood CM (1993) Ammonia and urea metabolism and excretion. In: Evans D (Ed.), The physiology of fishes. CRC Press, Boca Raton, FL, USA. pp 379–425 Wood CM (2001) Toxic responses of the gill. In: Schlenk, DW Benson, WH (eds.), Target organ toxicity in marine and freshwater teleosts: Organs. Taylor and Francis. CRC Press, London, England, pp 1–89 Wood CM (2022) Conservation aspects of osmotic, acid-base, and nitrogenous waste homeostasis in fish. In: Cooke S, Fangue N, Brauner CJ, Farrell AP, Eliason, (eds). Fish Physiology. Volume 39A, Academic Press, New York, USA, pp 321–338 Wood CM (1991) Branchial ion and acid-base transfer in freshwater teleost fish: environmental hyperoxia as a probe. Physiol Zool 64:68–102 Wood CM (1992) Flux measurements as indices of H+ and metal effects on freshwater fish. Aquat Toxicol 22:239–263. https://doi.org/10.1016/0166-445x(92)90043-m Wood CM (1989) The physiological problems of fish in acid waters. In: Morris R, Brown DJA, Taylor EW, Brown JA (eds.), Acid toxicity and aquatic animals, society for experimental biology seminar series. Cambridge University Press, Cambridge, UK, pp 125–148, Wood CM, Al-Reasi HA, Smith DS (2011) The two faces of DOC. Aquat Toxicol 105:3–8. https://doi.org/10.1016/j.aquatox.2011.03.007 Wood CM, Bucking C (2011) The role of feeding in salt and water balance. In: Grosell, M, Farrell AP, Brauner CJ (eds.) Fish Physiology. Volume 30, Academica Press, New York, USA, pp 165–212 Wood CM, Crémazy A, Morris C, et al (2025) The effect of environmental factors on transepithelial potential in a model Amazonian teleost, the tambaqui (Colossoma macropomum): Implications for sodium balance in harsh environments. J Fish Biol jfb.16050. https://doi.org/10.1111/jfb.16050 Wood CM, De Souza Netto JG, Wilson JM, et al (2017) Nitrogen metabolism in tambaqui (Colossoma macropomum), a neotropical model teleost: hypoxia, temperature, exercise, feeding, fasting, and high environmental ammonia. J Comp Physiol B 187:135–151. https://doi.org/10.1007/s00360-016-1027-8 Wood CM, Eom J (2021) The osmorespiratory compromise in the fish gill. Comp Biochem Physiol A Mol Integr Physiol 254:110895. https://doi.org/10.1016/j.cbpa.2021.110895 364 Wood CM, Gonzalez RJ, Ferreira MS, et al (2018) The physiology of the Tambaqui (Colossoma macropomum) at pH 8.0. J Comp Physiol B 188:393–408. https://doi.org/10.1007/s00360-017-1137-y Wood CM, Grosell M (2008) A critical analysis of transepithelial potential in intact killifish (Fundulus heteroclitus) subjected to acute and chronic changes in salinity. J Comp Physiol B 178:713–727. https://doi.org/10.1007/s00360-008-0260-1 Wood CM, Iftikar FI, Scott GR, et al (2009) Regulation of gill transcellular permeability and renal function during acute hypoxia in the Amazonian oscar (Astronotus ocellatus): new angles to the osmorespiratory compromise. J Exp Biol 212:1949–1964. https://doi.org/10.1242/jeb.028464 Wood CM, Kajimura M, Sloman KA, et al (2007) Rapid regulation of Na+ fluxes and ammonia excretion in response to acute environmental hypoxia in the Amazonian oscar, Astronotus ocellatus. Am J Physiol-Regul Integr Comp Physiol 292:R2048–R2058. https://doi.org/10.1152/ajpregu.00640.2006 Wood CM, Marshall WS (1994) Ion balance, acid-base regulation, and chloride cell function in the common killifish,Fundulus heteroclitus: A euryhaline estuarine teleost. Estuaries 17:34–52. https://doi.org/10.2307/1352333 Wood CM, Matsuo AYO, Gonzalez RJ, et al (2002) Mechanisms of ion transport in Potamotrygon, a stenohaline freshwater elasmobranch native to the ion-poor blackwaters of the Rio Negro. J Exp Biol 205:3039–3054. https://doi.org/10.1242/jeb.205.19.3039 Wood CM, Matsuo AYO, Wilson RW, et al (2003) Protection by natural blackwater against disturbances in ion fluxes caused by low pH exposure in freshwater stingrays endemic to the Rio Negro. Physiol Biochem Zool 76:12–27. https://doi.org/10.1086/367946 Wood CM, McDonald DG (1982) Physiological mechanisms of acid toxicity in fish. In: Johnson RE (eds.), Acid rain/fisheries, Proceedings of an International Symposium on Acidic Precipitation and Fishery Impacts in North‐eastern North America. American Fisheries Society. Bethesda, MD, USA, pp 197–226 Wood CM, McDonald MD, Grosell M, et al (2020) The potential for salt toxicity: Can the trans-epithelial potential (TEP) across the gills serve as a metric for major ion toxicity in fish? Aquat Toxicol 226:105568. https://doi.org/10.1016/j.aquatox.2020.105568 Wood CM, McMahon BR, McDonald DG (1979) Respiratory gas exchange in the resting starry glounder, Platichthys stellatus: A comparison with other teleosts. J Exp Biol 78:167–179. https://doi.org/10.1242/jeb.78.1.167 Wood CM, Nawata CM (2011) A nose-to-nose comparison of the physiological and molecular responses of rainbow trout to high environmental ammonia in seawater versus freshwater. J Exp Biol 214:3557–3569. https://doi.org/10.1242/jeb.057802 365 Wood CM, Robertson LM, Johannsson OE, Val AL (2014) Mechanisms of Na+ uptake, ammonia excretion, and their potential linkage in native Rio Negro tetras (Paracheirodon axelrodi, Hemigrammus rhodostomus, and Moenkhausia diktyota). J Comp Physiol [B] 184:877–890. https://doi.org/10.1007/s00360-014-0847-7 Wood CM, Ruhr IM, Schauer KL, et al (2019) The osmorespiratory compromise in the euryhaline killifish: water regulation during hypoxia. J Exp Biol 222:jeb204818. https://doi.org/10.1242/jeb.204818 Wood CM, Wilson RW, Gonzalez RJ, et al (1998) Responses of an Amazonian teleost, the tambaqui (Colossoma macropomum), to low pH in extremely soft water. Physiol Zool 71:658–670. https://doi.org/10.1086/515977 Wright PA, Wood CM (2009) A new paradigm for ammonia excretion in aquatic animals: role of Rhesus (Rh) glycoproteins. J Exp Biol 212:2303–2312. https://doi.org/10.1242/jeb.023085 Wright PA, Wood CM (2012) Seven things fish know about ammonia and we don’t. Respir Physiol Neurobiol 184:231–240. https://doi.org/10.1016/j.resp.2012.07.003 Yan M, Fu Q, Li D, et al (2013) Study of the pH influence on the optical properties of dissolved organic matter using fluorescence excitation–emission matrix and parallel factor analysis. J Lumin 142:103–109. https://doi.org/10.1016/j.jlumin.2013.02.052 Yanagitsuru YR, Hewitt CR, Gam LTH, et al (2019) Effect of water pH and calcium on ion balance in five fish species of the Mekong Delta. Comp Biochem Physiol A Mol Integr Physiol 232:34–39. https://doi.org/10.1016/j.cbpa.2019.02.026 Ye X, Randall DJ, He X (1991) The effect of acid water on oxygen consumption, circulating catecholamines and blood ionic and acid-base status in rainbow trout (Salmo gairdneri, Richardson). Fish Physiol Biochem 9:23–30. https://doi.org/10.1007/BF01987608 Young C, von Wandruszka R (2001) A comparison of aggregation behavior in aqueous humic acids. Geochem Trans 2:16. https://doi.org/10.1186/1467-4866-2-16 Zall DM, Fisher Donald, Garner MQ (1956) Photometric determination of chlorides in water. Anal Chem 28:1665–1668. https://doi.org/10.1021/ac60119a009 Zara LF, Rosa AH, Toscano IAS, Rocha JC (2006) A structural conformation study of aquatic humic acid. J Braz Chem Soc 17:1014–1019. https://doi.org/10.1590/S0103-50532006000500028 Zelenina M, Tritto S, Bondar AA, et al (2004) Copper inhibits the water and glycerol permeability of aquaporin-3. J Biol Chem 279:51939–51943. https://doi.org/10.1074/jbc.M407645200 366 Zimmer AM, Barcarolli IF, Wood CM, Bianchini A (2012) Waterborne copper exposure inhibits ammonia excretion and branchial carbonic anhydrase activity in euryhaline guppies acclimated to both fresh water and sea water. Aquat Toxicol 122–123:172–180. https://doi.org/10.1016/j.aquatox.2012.06.010 367 Appendices Appendix A Supplementary material - Chapter 3 Table SA 1. Characterization of grab samples from Lake Ontario (LO), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) Ions are expressed as mg L-1 and DOC as mg C L-1 Pb, Cu and Ni were below the detection limit of 0.02 (Pb), 0.01 (Cu and Ni) Sample pH [DOC] Na Ca K Mg Al LO 6.83 1.52 28.10 80.46 0.36 11.73 0.12 PF 7.35 4.15 106.76 147.33 2.27 22.57 0.08 AP 7.07 22.18 1.31 57.51 0.82 11.12 0.10 AS 6.89 37.96 10.98 171.17 0.75 37.83 0.14 368 Table SA 2. Characterization of experimental solutions from Lake Ontario (LO), Luther Marsh (LM), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS). DOC and pH values are mean ± range, N=2. Ions are expressed as mg L-1 and DOC as mg C L-1 *ND indicates not detectable due to the detection limit of 0.01 for K. Pb, Cu and Ni were below the detection limits of 0.02 (Pb) and 0.01 (Cu and Ni) Source Na Ca K Mg Al [DOC] pH 7 [DOC] pH 4 pH ~7 pH ~4 LO 25.76 18.67 0.38 12.24 0.100 10.20 ± 0.18 10.50 ± 0.16 6.76 ± 0.08 3.94 ± 0.07 PF 24.05 14.93 0.33 7.92 0.09 9.17 ± 0.06 10.66 ± 0.17 6.73 ± 0.03 3.95 ± 0.04 LM 0.13 2.48 *ND 0.29 0.08 10.06 ± 0.12 10.03 ± 0.13 6.77 ± 0.27 4.02 ± 0.05 AP 0.18 0.40 0.10 0.22 0.08 9.42 ± 0.005 9.19 ± 0.04 7.01 ± 0.16 3.98 ± 0.01 AS 0.91 0.74 0.17 0.49 0.085 8.82 ± 0.01 8.62 ± 0.09 6.88 ± 0.06 3.99 ± 0.03 369 Table SA 3. Size fractionation of DOCs from Lake Ontario, Luther Marsh, Preston Flats, Ancient Woods Pond, and Ancient Woods Swamp at neutral pH, achieved by via ultrafiltration using 0.45-m, 100-kDa, 10-kDa and 3-kDa filters Lake Ontario 0.45-m 100-kDa 10-kDa 3-kDa [DOC] 9.30 mg C L-1 8.44 mg C L-1 8.22 mg C L-1 7.01 mg C L-1 Absorbance at 340 nm 0.0488 0.0290 0.0270 0.0128 Molecular weight index 9.00 13.95 13.48 35.55 SAC340 12.07 7.90 7.57 4.21 Relative percent fluorophore (PARAFAC Components) 22.50 % Pro 46.90% FA 30.60 % HA 18.26% Pro 41.45% FA 40.29% HA 19.47% Pro 42.09% FA 38.44% HA 22.88% Pro 58.37% FA 18.75% HA Fluorescence Index 1.25 1.22 1.23 1.35 Preston Flats 0.45-m 100-kDa 10-kDa 3-kDa [DOC] 9.24 mg C L-1 7.98 mg C L-1 7.01 mg C L-1 8.12 mg C L-1 Absorbance at 340 nm 0.0721 0.0417 0.0328 0.0186 Molecular weight index 6.89 9.69 11.31 9.30 SAC340 17.98 12.02 10.78 6.24 Relative percent fluorophore (PARAFAC Components) 19.42% Pro 40.72% FA 39.86% HA 15.28% Pro 34.47% FA 50.25% HA 15.14% Pro 33.20% FA 51.66% HA 18.56% Pro 53.64% FA 27.79% HA Fluorescence Index 1.22 1.18 1.19 1.23 Luther Marsh 0.45-m 100-kDa 10-kDa 3-kDa [DOC] 9.86 mg C L-1 8.49 mg C L-1 6.74 mg C L-1 7.64 mg C L-1 Absorbance at 340nm 0.112 0.0750 0.0609 0.0103 Molecular weight index 5.16 6.14 6.46 18.74 SAC340 26.16 20.33 20.79 3.11 Relative percent fluorophore (PARAFAC Components) 13.44% Pro 66.55% FA 20.01% HA 13.21% Pro 66.69% FA 20.10% HA 12.39% Pro 67.79% FA 19.81% HA 16.18% Pro 73.23% FA 10.59% HA Fluorescence Index 1.18 1.20 1.23 1.40 370 %pro represents %protein %FA represents %fulvic acid %HA represents %humic acid. Ancient Woods Pond 0.45-m 100-kDa 10-kDa 3-kDa [DOC] 9.24 mg C L-1 8.65 mg C L-1 7.84 mg C L-1 5.73 mg C L-1 Absorbance at 340nm 0.0982 0.0684 0.0582 0.0135 Molecular weight index 6.00 7.35 7.62 25.09 SAC340 24.48 18.21 17.09 5.42 Relative percent fluorophore (PARAFAC Components) 21.57% Pro 30.64% FA 47.80% HA 19.24% Pro 26.68% FA 54.08% HA 18.07% Pro 26.28% FA 55.65% HA 18.48% Pro 56.08% FA 25.44% HA Fluorescence Index 1.20 1.17 1.17 1.30 Ancient Woods Swamp 0.45-m 100-kDa 10-kDa 3-kDa [DOC] 8.68 mg C L-1 7.54 mg C L-1 6.98 mg C L-1 5.40 mg C L-1 Absorbance at 340nm 0.0765 0.0505 0.0466 0.0147 Molecular weight index 5.91 7.41 7.32 14.70 SAC340 20.34 15.42 15.37 6.25 Relative percent fluorophore (PARAFAC Components) 20.07% Pro 38.56% FA 41.38% HA 16.85% Pro 33.53% FA 49.62% HA 17.04% Pro 32.45% FA 50.51% HA 18.86% Pro 60.20% FA 20.94% HA Fluorescence Index 1.20 1.18 1.19 1.32 371 Figure SA 1. Preselected parallel factor analysis (PARAFAC) excitation and emission fluorophore components and parallel factor analysis (PARAFAC) fluorescence excitation-emission matrices for natural DOCs at pH 7 for (A) Lake Ontario, (B) Preston Flats, (C) Luther Marsh, (D) Ancient Woods Pond, and (E) Ancient Woods Swamp, and at pH 4 for (F) Lake Ontario, (G) Luther Marsh, (H) Preston Flats, (I) Ancient Pond, and (J) Ancient Swamp. 372 Appendix B Supplementary material – Chapter 4 Brief description of methods and equations for physicochemical indices. Specific absorbance coefficient at 340 nm (SAC340) The specific absorbance coefficient at 340 nm (SAC340), an index of aromatic composition, was estimated by the method of Curtis and Schindler (1997) by examining the absorbance of samples at a wavelength of 340 nm using a 1-cm quartz cuvette in an Aqualog spectrophotometer. SAC340 (cm2/mg C) was calculated as: SAC340 =(2.303 × Abs340)/pathlength[DOC]/1000 where DOC is in mg C L-1 and pathlength is in cm. Molecular weight index (MWI) The ratio of absorbance measurements at 254 nm and 365 nm was used as an indirect indicator of the relative molecular weight (MWI) of DOC, with high values indicating lower molecular weight, and low values indicating a higher molecular weight (Dahlén et al. 1997, Peuravuori and Pihlaja 1997): Molecular weight index =Abs254Abs365 Fluorescence index (FI) The fluorescence index (FI) is an indicator of the DOC source with higher values indicating a more autochthonous origin, and lower values, a more allochthonous origin (McKnight et al. 2001). FI was calculated as: 373 FI = Em450Em500 where Em 450 and 500 refer to emission intensities at 450 nm and 500 nm, both taken at an excitation wavelength of 370 nm. Logarithm of octanol-water partition coefficient (log Kow) The octanol-water partition coefficient (log Kow), a measure of lipophilicity was measured as per Gjessing et al. (1999). Octanol (5 ml) was added to a 15-mL aqueous DOC sample which was gently but thoroughly mixed using a 3-dimensonal nutating mixer for 2.5 h. The distribution of the DOC in the water phase and octanol phase was determined by measuring the absorbance in each phase at 254 nm (Gjessing et al. 1999). Log Kow was calculated as: log Kow = 𝑙𝑜𝑔 (Abs254in octanol phaseAbs254in aqueous phase) Higher log Kow values indicate a more lipophilic sample. Proton binding index (PBI) and molecular charge The proton binding index (PBI) shows the potential of DOC to exhibit strong tridentate binding of cations and has been used as a general indicator of the chemical reactivity. The PBI is based on the protocol of Al-Reasi et al. (2013a) using acid–base titrations over a wide range of pH values. The experimental titration data were fitted to a fully optimized continuous (FOCUS) model using in-house Matlab™ programs as described by Smith and Ferris (2001), to estimate proton binding constants (pKa) and their site densities (LT, μmol/mg C). Molecular charge of the 374 DOC molecule, as moles of charge per mg of carbon, is an indication of the ionizable fraction of the molecule and was determined directly from the experimental data, using interpolation to obtain the appropriate value at exactly pH 7 or pH 4. The PBI was calculated as in Al-Reasi et al. (2013a): PBI = intermediate(acid+basic)/2 where PBI is a function of the measured acidic (pKa ≤ 5), intermediate (5 > pKa ≤ 8.5) and basic (pKa > 8.5) proton binding site concentrations (determined by integration of the FOCUS pKa spectrum). Parallel factor analysis (PARAFAC) Parallel factor analysis (PARAFAC) is a computational model (conducted in MATLAB using the PLS Toolbox (version 9.2) that uses a multivariate statistical approach to define the components of a sample based on the fluorescence excitation-emission matrix (FEEM) and known predetermined number of fluorophores (Stedmon and Markager 2005; Stedmon and Bro 2008). Three fluorophore categories were selected in this study: humic-like, fulvic-like, and protein-like components. 375 Table SB 1. Characterization of experimental solutions from Lake Ontario (LO), Luther Marsh (LM), Preston Flats (PF), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS). DOC and pH values are mean ± range, N=2. Ions are expressed as mg L-1 and DOC as mg C L-1 *ND indicates not detectable due to the detection limit of 0.01 for K. Pb, Cu and Ni were below the detection limit of 0.02 (Pb), 0.01 (Cu and Ni) Morris et al. (2024b, see Chapter 3) Source Na Ca K Mg Al [DOC] pH 7 [DOC] pH 4 pH ~7 pH ~4 LO 25.76 18.67 0.38 12.24 0.100 10.20 ± 0.18 10.50 ± 0.16 6.76 ± 0.08 3.94 ± 0.07 PF 24.05 14.93 0.33 7.92 0.09 9.17 ± 0.06 10.66 ± 0.17 6.73 ± 0.03 3.95 ± 0.04 LM 0.13 2.48 *ND 0.29 0.08 10.06 ± 0.12 10.03 ± 0.13 6.77 ± 0.27 4.02 ± 0.05 AP 0.18 0.40 0.10 0.22 0.08 9.42 ± 0.005 9.19 ± 0.04 7.01 ± 0.16 3.98 ± 0.01 AS 0.91 0.74 0.17 0.49 0.085 8.82 ± 0.01 8.62 ± 0.09 6.88 ± 0.06 3.99 ± 0.03 376 Table SB 2. The specific absorbance coefficient at 340 nm (SAC340), fluorescence index (FI), molecular weight index (MWI) and octanol-water partition coefficient (log Kow) Proton binding index (PBI), molecular charge (mol charge/ mg C), and relative % humic acid-like, relative % fulvic acid-like and relative % protein-like fluorophores by PARAFAC, in Lake Ontario (LO), Preston Flats (PF), Luther Marsh (LM), Ancient Woods Pond (AP) and Ancient Woods Swamp (AS) at ~10 mg C L-1 at pH 7 and pH 4. Morris et al. (2024b, see Chapter 3) Index LO PF LM AP AS SAC340 pH 7 16.45 21.52 26.55 36.94 27.91 SAC340 pH 4 14.95 18.18 31.92 32.73 27.87 FI pH 7 1.30 1.24 1.13 1.24 1.28 FI pH 4 1.24 1.18 1.15 1.19 1.20 MWI pH 7 8.23 7.52 5.62 5.53 5.70 MWI pH 4 8.25 7.04 5.90 6.11 6.71 log Kow pH 7 -1.13 -1.26 -1.48 -1.46 -1.34 log Kow pH 4 -0.66 -0.68 -1.00 -0.68 -1.09 PBI 0.09 0.12 0.62 0.45 0.30 Charge pH 7 3.95 3.65 6.10 4.71 7.58 Charge pH 4 0.95 0.59 2.17 0.95 1.68 Relative % humic acid, pH 7 17.89 21.28 26.81 13.73 19.54 Relative % humic acid, pH 4 46.37 48.63 34.74 54.28 51.63 Relative % fulvic acid, pH 7 75.93 72.30 73.19 68.15 69.22 Relative % fulvic acid, pH 4 50.44 47.85 65.26 37.20 43.35 Relative % protein acid, pH 7 6.18 6.42 0 18.11 11.23 Relative % protein acid, pH 4 3.19 3.52 0 8.51 5.01 377 Appendix C Supplementary material – Chapter 5 The Chemistry of Model Compounds (i) Tannic acid and AldrichTM humic acid Tannic acid (TA) and AldrichTM humic acid (AHA) were tested because they are commonly employed as analogues of natural DOCs. TA has been a widely used as a model allochthonous carbon compound (Moreno-Castilla et al. 2004; Lin and Baoshan 2008; Campinas et al. 2013; Wershaw 2004). Tannins are complex molecules found in a wide variety of plants and can be soluble in water forming uncrystallizable colloidal dispersions (Chung et al. 1998). They share properties with humic substances including complex formation, and color. Hydrolyzable tannins are highly aromatic, polyphenolic biomolecules with carbohydrate backbones and contain s polyhydric alcohol central core such as glucose. In gallotannins, this central core is esterified by gallic acid. TA is an important example of a hydrolyzable gallotannin which contains approximately 10 gallic acid molecules linked to a glucose center through ester bonds. While tannic acid contains no carboxyl groups, it is weakly acidic (pKa 6) because of the high phenolic hydroxyl content. Although AldrichTM humic acid (AHA) is derived from natural sources such as soil and peats, it has marked differences in its chemical properties compared to fresh natural DOC (Thurman 1985; Morris et al. 2021) but is often used as a commercial source of humic acid. AHA is composed of large aromatic polysaccharides, proteins, phenols and chelated metal ions. 378 (ii) Phenolic acids: Salicylic acid (SA) and naphthoic acid (NA) were tested because of their known ability to complex metals. Salicylic acid is a phenolic derivative found in a wide variety of plants (Hayat et al. 2007). It contains a hydroxyl group and a carboxylic acid functional group attached to a benzene ring (phenolic group). In circumneutral conditions salicylic acid is able to complex metal ions because the carboxyl group is almost completely ionized and a simple complex with a metal ion would not lead to a significant release of protons. Naphthoic acid has a similar structure to salicylic acid but it has two aromatic rings and is twice as large. Along with salicylic acid, it has been used as a DOC proxy (Smith and Kramer 1997). To test if complexation is a mechanism of ionoregulatory protection, salicylic acid and naphthoic acid were used as model compounds due to their known metal complexing properties (Perrin 1958). (iii) Surfactants: Sodium dodecyl sulfate (SDS) and linear alkylbenzene sulfonate (LAS) were tested because of their surfactant properties. A notable characteristic of humic acids are their surfactant properties, the ability to solubilize a wide range of hydrophobic materials (von Wandruszka 2000, Young and von Wandruszka, 2001). Humic acids are able to form pseudomicelles, operationally similar to the conventional micelles found in synthetic surfactants although more structurally constrained (von Wandruszka, 2000). Humic acids aggregate intramolecularly, folding and coiling in a manner that keeps hydrophobic moieties (i.e. hydrocarbons) in the center and directs hydrophilic groups (i.e. carboxyls and hydroxyls) towards the outside of the molecule (von Wandruszka 2000). Much like natural humic substances, synthetic surfactants are 379 amphiphilic, with hydrophilic and hydrophobic moieties (Vergütz et al. 2015). Surfactants can be broadly classified as ionic (anionic or cationic), non-ionic and zwitterionic based on the net charge of the headgroup. Anionic surfactants were tested because humic substances contain mostly negatively charged components. Sodium dodecyl sulfate, often called sodium lauryl sulfate is a widely used anionic surfactant that has a long-chain aliphatic group with a negatively charged sulfate attached. It is an organic sodium salt of dodecyl hydrogen. Linear alkylbenzene sulfonate, like sodium dodecyl sulfate, is one of the oldest, most commonly used surfactants. It consists of a hydrophilic sulfonate head-group and a hydrophobic alkylbenzene tail and is prepared by the sulfonation of linear alkylbenzenes. (iv) Carboxylic acids: Carboxylic acid groups are found in both humic and fulvic acids. We tested formic (FA) and acetic acid (AA). Formic acid is the simplest carboxylic acid, containing only a single carbon atom and acetic acid is the second simplest carboxylic acid with two carbon atoms. (v) Fatty acids: Four fatty acids were tested because they have a similar structure to the lipid in membranes, with a hydrophilic head and a hydrophobic tail, and they are able to form micelles like surfactants so it is possible for them to interact with physiological membranes. A fatty acid is a carboxylic acid with a long aliphatic chain. As such, they are amphiphilic molecules that are hydrophilic at the carboxyl end and hydrophobic at the methyl end. Long chain fatty acids (LCFAs) are abundant in plant material and contain 12 or more carbon atoms that contribute to the straight fatty acid chain. Longer chain fatty acids have been found in humic acids and have 380 been suggested to increase their hydrophobicity when compared to fulvic acids (Liao et al. 1982, Thurman 1985). Lipids extracted from DOC collected from a natural brown water lake were found to be predominately even-numbered methyl esters of saturated n-alkyl fatty acids from C14 to C28, with the greatest concentration being C16, palmitic acid (PA) (hexadecanoic acid) and C18, steric acid (StA) (octadecanoic acid) n-alkyl fatty acids. Two methyl esters of unsaturated n-alkyl fatty acids, methyl palmitate (MP) (hexadecenoic acid methyl ester) and methyl stearate (MS) (octadecenoic acid methyl ester) were found in moderate amounts (Jandl et al. 2002). Fatty acid methyl esters are a type of fatty acid ester (the result of a reaction with a fatty acid and an alcohol) which have undergone transesterification of fats and methanol (Katritzky and Taylor 2004). Palmitic acid is the most common saturated fatty acid found in plants, animals and microorganisms. It has a 16-carbon backbone and no double bonds (C16:0) (Carta et al. 2017). Steric acid is found in various plants and animals and has an 18-carbon backbone with no double bonds (C18:0). The important functional group of palmitic acid and steric acid is a carboxylic acid. Methyl palmitate is a naturally occurring fatty acid methyl ester with a 17-carbon backbone. The important functional group of both methyl palmitate and methyl stearate is an ester. As such, we tested saturated (palmitic acid and steric acid) and unsaturated fatty acid methyl esters (methyl palmitate and methyl stearate). (vi) Amino acids and amino acid-rich molecules Tyrosine (Tyr) and tryptophan (Tryp), as free amino acids, and α-lactalbumin (LAC) and bovine serum albumin (BSA), representing amino acid-rich molecules, were tested. Amino acids are a critical basic group (i.e. accepts protons) that make up approximately 3% of dissolved organic matter in natural waters (Thurman 1985). Using fluorescent spectroscopy and 381 parallel factor analysis (PARAFAC), previous researchers have identified trytophan-like and tyrosine-like DOCs based on the comparison of tryptophan and tyrosine flurophores (Cory and McKnight 2005; Johannsson et al. 2016; Barker et al. 2013). Although these findings do not mean that tyrosine and tryptophan are the cause of the fluoresence in the DOC, the presence of tyrosine- and tryptophan-like fluorophores has been correlated with total hydrolyzable amino acid abundance (Barker et al. 2013). Tyrosine and tryphophan are aromatic amino acids. Tyrosine has a phenol side chain and a hydroxyl group making it polar (Wetlaufer et al. 1958). Tryptophan contains an α-amino group, an α-carboxylic group and an indole (aromatic heterocyclic compound) making it non-polar. At physiological pH tryptophan is a zwitterion. Free amino acids are very small molecules that lack peptide bonds. As such, tyrosine and tryptophan residues in complex DOC molecules will likely behave in a different manner than free amino acids. To determine the contribution of these residues to the ionoregulatory protection of DOC, macromolecules rich in tyrosine or tryptophan were selected. Bovine serum albumin (BSA) has been used to represent tyrosine-rich proteinaceous material (Heidari et al. 2018). It consists of 607 amino acids and has a molecular weight of 66 kDa (Majorek et al. 2012). It has 21 tyrosine residues and only 2 tryptophan residues (Majorek et al. 2012). α-lactalbumin is a smaller molecule with a molecular weight of 15 kDa (Permyakov 2013). It is composed of 123-140 amino acids and is rich is tryptophan (Permyakov 2013). BSA and α-lactalbumin may be valuable proxies for testing the effect of tyrosine and tryptophan when they are components of the structures of natural DOCs. 382 (vii) Sugars: Four isomers of glucose were tested. Natural carbohydrates are polyhydroxy aldehydes, polyhydroxy ketones or compounds that can be hydrolyzed into ketones and are an important portion of DOC (Thurman 1985). Monosaccharides, oligosaccharides, polysaccharides and saccharides bound to humic substances are the major classes of carbohydrates found in DOC (Thurman 1985). Monosaccharides are simple and contain only one sugar unit. They make take two forms, an open chain form and ring form including 6-membered rings for hexose and 5-membered rings for pentoses (Thurman 1985). Glucose (Glu), mannose (Mann), fructose (Fru) and galactose (Galac) were identified in a humic substance rich lake (Tranvik and Jorgensen, 1995). Although glucose, mannose, fructose and galactose share the same chemical formula, they are structurally and stereochemically different). Glucose contains 6-carbon atoms and an aldehyde group. Mannose is the C-2 epimer of glucose and fructose is the structural isomer of glucose. Galactose is the stereoisomer of glucose, where the orientation of a hydroxyl group bonded to a carbon is in a different orientation than seen in glucose. Brief description of methods and equations for physicochemical indices. Specific absorbance coefficient at 340 nm (SAC340) Using the method described by Curtis and Schindler (1997), the specific absorbance coefficient at 340 nm (SAC340), an index of aromatic composition, was estimated by examining the absorbance of samples at a wavelength of 340 nm using a 1-cm quartz cuvette in an Aqualog spectrophotometer. SAC340 (cm2/mg C) was calculated as: 383 SAC340 =(2.303 × Abs340)/pathlength[DOC]/1000 where DOC is in mg C L-1 and pathlength is in cm. Molecular weight index (MWI) To estimate an indirect indicator of the relative molecular weight (MWI) of DOC, the ratio of absorbance measurements at 254 nm and 365 nm was used, with high values indicating lower molecular weight, and low values indicating a higher molecular weight (Dahlén et al. 1997, Peuravuori and Pihlaja 1997): Molecular weight index =Abs254Abs365 Fluorescence index (FI) The fluorescence index (FI) is an indicator of the DOC source, with higher values indicating a more autochthonous origin, and lower values, a more allochthonous origin (McKnight et al. 2001). FI was calculated as: FI = Em450Em500 Em 450 and 500= emission intensities at 450 nm and 500 nm, both taken at an excitation wavelength of 370 nm. 384 Table SC 1. pH values of control and experiment solutions and dissolved organic carbon concentration (mg C L-1) at pH 7 and pH 4. * Rejected based on solutions interfering with the equipment, therefore the measurement could not be made Source pH ~7 pH ~4 [DOC] pH 7 [DOC] pH 4 Control 7.06 4.02 1.05 1.07 Tannic acid 6.90 4.07 10.46 9.98 AldrichTM humic acid 7.09 4.02 10.02 10.47 Salicylic acid 6.85 3.98 10.69 10.42 Naphthoic acid 6.70 3.96 10.38 9.37 Sodium dodecyl sulfate 7.01 4.19 13.58 13.52 Linear alkylbenzene sulfonate 6.90 3.96 10.37 10.77 Palmitic acid 6.67 4.14 -* -* Steric acid 6.87 4.06 -* -* Methyl palmitate 6.86 4.13 -* -* Methyl stearate 6.99 4.09 -* -* Formic acid 7.09 4.06 11.13 11.01 Acetic acid 6.78 4.02 10.71 17.70 Tryptophan 6.90 4.07 11.59 11.96 α-Lactalbumin 6.60 4.04 10.69 13.40 Tyrosine 6.93 4.11 11.37 11.68 Bovine serum albumin 6.94 4.09 9.11 9.04 Glucose 6.75 4.03 10.61 10.71 Galactose 6.89 4.09 11.08 11.97 Mannose 6.92 4.03 11.05 13.44 Fructose 7.06 4.06 10.02 10.20 385 Table SC 2. Optical characterization of model compounds * Rejected based on values not being applicable Model Compound SAC340 pH 7 SAC340 pH 4 FI pH 7 FI pH 4 MWI pH 7 MWI pH 4 Tannic acid 9.03 -* 0.17 -* -* 17.66 AldrichTM humic acid 69.96 59.10 0.78 0.80 0.99 0.81 Salicylic acid 1.04 -* 0.24 0.40 0.60 0.67 Naphthoic acid -* -* 2.50 1.95 1.28 1.52 Sodium dodecyl sulfate -* -* -* -* 0.39 -* Linear alkylbenzene sulfonate -* -* 1.40 1.13 1.24 0.91 Palmitic acid 0.45 0.18 0.015 -* -* 12.43 Steric acid 0.16 0.25 1.24 0.23 5.35 0.04 Methyl palmitate 0.10 -* -* 0.31 -* -* Methyl stearate 0.11 -* 0.75 6.43 0.12 55.44 Formic acid 0.20 -* -* -* 0.21 -* Acetic acid 0.57 -* 0.56 0.11 5.14 0.02 Tryptophan -* -* -* -* 0.64 -* α-Lactalbumin -* -* 1.39 1.62 0.85 1.90 Tyrosine -* -* -* -* 1.59 -* Bovine serum albumin -* -* -* 0.13 -* -* Glucose -* -* -* -* 15.40 -* Galactose -* 1.65 1.64 -* -* 0.03 Mannose -* 0.09 0.52 0.39 1.32 0.30 Fructose 2.27 -* 0.91 0.13 6.95 0.02 386 Table SC 3. Log Kow and charge values corrected to pH 7 and pH 4 -indicates that value was unable to be calculated Model Compound log Kow pH 7 log Kow pH 4 Charge pH 7 Charge pH 4 Tannic acid -1.23 -0.19 0.0909 0.990 AldrichTM humic acid 0.09 0.26 - - Salicylic acid -1.77 1.19 0.999 0.915 Naphthoic acid -0.23 2.83 0.998 0.602 Sodium dodecyl sulfate -4.09 -1.09 0.999 0.998 Linear alkylbenzene sulfonate -0.21 -0.54 1 0.999 Palmitic acid 5.12 7.12 0.991 0.101 Steric acid 5.98 8.16 0.994 0.151 Methyl palmitate -6.62 -3.62 1 1 Methyl stearate -5.65 -2.65 1 1 Formic acid -3.84 -1.02 0.999 0.666 Acetic acid -2.41 -0.240 0.994 0.148 Tryptophan -1.06 -1.07 0.996 0.996 α-Lactalbumin -0.36 -0.63 - - Tyrosine 5.04 5.04 0.979 0.975 Bovine serum albumin 0.21 0.12 - - Glucose -12.9 -4.74 0.999 0.999 Galactose -13.60 -10.6 0.999 0.999 Mannose -13.60 -10.6 0.999 0.999 Fructose -12.80 -9.80 0.999 - 387 Figure SC 1. Absolute TEP of model compounds grouped within the 7 key chemical moiety groups regressed against (A) log Kow at pH 7 (B) log Kow at pH 4 (C) Charge at pH 7 (D) Charge at pH 4. Values are mean ± SEM. A fitted line indicates statistical significance (p < 0.05 by simple linear regression). 388 Figure SC 2. ΔTEP of model compounds grouped within the 7 key chemical moiety groups regressed against (A) log Kow at pH 7 (B) log Kow at pH 4 (C) Charge at pH 7 (D) Charge at pH 4. Values are mean ± SEM. A fitted line indicates statistical significance (p < 0.05 by simple linear regression). 389 Appendix D Supplementary material – Chapter 6 Table SD 1. Water conductivity (μS cm-1) at each concentration (mM) and adjusted pH of the NaCl or CaCl2 salt solutions which were made in Vancouver de-chlorinated tap water. The 24-h LC50 concentration for rainbow trout (Durand-Hoffman, 1995) is bolded. 1concentration in mM 2 conductivity in µS cm-1 Percentage of LC50 NaCl concentration1 NaCl conductivity2 NaCl pH ~7 NaCl pH ~4 CaCl2 concentration1 CaCl2 conductivity2 CaCl2 pH ~7 CaCl2 pH ~4 0 0 220 7.30 4.01 0 267 7.09 4.09 3.12 3.41 482 7.27 3.96 1.87 559 7.13 4.01 6.25 6.83 864 7.28 4.06 3.75 1088 6.88 3.97 12.5 13.66 1684 7.30 4.12 7.5 1962 6.75 3.98 25 27.32 3310 7.31 4.05 15 3690 6.66 4.03 50 54.65 6230 7.30 3.99 30 6910 6.68 3.98 100 109.3 11880 7.26 4.06 60 12910 6.72 4.04 200 218.6 22300 7.17 4.01 120 23700 6.83 4.05 400 437.2 41300 6.98 4.04 240 43300 6.92 4.07 390 Table SD 2. Dissolved organic carbon (DOC) concentration (mg C L-l) in test solutions for natural DOCs and model compounds at pH 7 and pH 4. Source [DOC] in mg C L-1 at pH 7 [DOC] in mg C L-1 at pH 4 Luther Marsh 10.2 10.5 Lake Ontario 10.6 10.0 Tannic acid 9.2 10.1 Sodium dodecyl sulphate 9.4 9.2 Bovine serum albumin 8.8 8.6 391 Table SD 3. The Michaelis-Menten constants, derived using the standard Michaelis-Menten equation 2 (see Methods), for CaCl2 at pH 7 and pH 4 with and without DOC (means ± SEM, N =6) and R2 values. Compare with Table 2, where the equation modified for substrate inhibition (equation 3) was fitted to the same data so as to derive the Michaelis-Menten constants. Exposure solutions sharing the same number or letter are in the same series and constants were compared within each series. Significance for t-test comparisons is shown, with bold font used for significant differences (p<0.05). Exposure solution pH ∆TEPmax (mV) p-value ∆TEPmax Km (mmol L-1) p-value Km R2 CaCl2 7 26.57 ± 0.92 - 2.05 ± 0.34 - 0.647 CaCl2 4 18.47 ± 1.37 <0.0001 2.27 ± 0.38 0.666 0.517 CaCl2 7 27.7 ± 0.61 - 1.62 ± 0.34 - 0.760 CaCl2 + LM 7 30.58 ± 2.34 0.302 0.36 ± 0.11 0.009 0.402 CaCl2 7 26.52 ± 2.41 - 3.35 ± 0.92 - 0.822 CaCl2 + LO 7 18.28 ± 1.98 0.036 2.92 ± 0.41 0.702 0.915 CaCl2 7 22.81 ± 2.16 - 0.03 ± 0.02 - -0.01 CaCl2 + TA 7 26.23 ± 1.39 0.171 0.29 ± 0.08 0.0035 0.413 CaCl2 7 27.60 ± 1.27 - 4.01 ± 0.37 - 0.850 CaCl2 + SDS 7 25.56 ± 4.29 0.688 1.94 ± 0.23 0.002 0.853 CaCl2 7 28.23 ± 2.39 - 1.24 ± 0.20 - 0.820 CaCl2 + BSA 7 25.35 ± 2.33 0.450 2.51 ± 0.25 0.0047 0.904 CaCl2 4 18.52 ± 1.34 - 3.46 ± 1.01 - 0.603 CaCl2 + LM 4 14.77 ± 1.91 0.173 0.32 ± 0.17 0.017 0.097 CaCl2 4 14.75 ± 3.82 - 1.34 ± 0.69 - 0.371 CaCl2 + LO 4 22.19 ± 2.99 0.192 1.39 ± 0.51 0.954 0.536 CaCl2 4 26.16 ± 2.07 - 3.96 ± 0.67 - 0.899 CaCl2 + TA 4 19.65 ± 2.39 0.185 1.06 ± 0.29 0.003 0.361 CaCl2 4 21.12 ± 1.53 - 1.78 ± 0.54 - 0.463 CaCl2 + SDS 4 26.54 ± 5.18 0.380 5.15 ± 3.19 0.645 0.363 CaCl2 4 11.83 ± 1.83 - 0.82 ± 0.38 - 0.249 CaCl2 + BSA 4 27.33 ± 1.25 <0.0001 1.64 ± 0.48 0.251 0.733 392 Table SD 4. Significance values (p) for the effects of DOC and model compounds on absolute transepithelial potential (TEP) compared to control at a geometric series of added Na+ or Ca2+ (as a percentage of the LC50) at pH 7 and pH 4; p values <0.05 are considered significant and are bolded. Source pH 0% 3.12 % 6.25% 12.5% 25% 50% 100% 200% 400% NaCl + LM 7 0.0436 0.972 0.4237 0.0902 0.0399 0.0036 0.3352 0.6383 0.2581 NaCl + LO 7 0.0027 0.0082 0.0267 0.0062 0.0128 0.0062 0.0028 0.0652 0.0320 NaCl + TA 7 0.0262 0.1366 0.0411 0.1414 0.0516 0.5230 0.8453 0.6342 0.1550 NaCl + SDS 7 0.0012 0.0017 0.0052 0.0020 0.0005 0.0293 0.0408 0.0256 0.1396 NaCl + BSA 7 0.0228 0.0039 0.0147 0.0069 0.0271 0.0445 0.1178 0.4475 0.5460 CaCl2 + LM 7 0.0299 0.0482 0.4342 0.1982 0.4656 0.0643 0.2022 0.2755 0.2798 CaCl2 + LO 7 0.0338 0.0910 0.0302 0.1614 0.3497 0.1680 0.1850 0.3366 0.5332 CaCl2 + TA 7 0.0075 0.2540 0.0389 0.3427 0.9540 0.6742 0.2902 0.2347 0.2685 CaCl2 + SDS 7 0.0270 0.2643 0.0023 0.2155 0.0276 0.4388 0.2428 0.1080 0.0772 CaCl2 + BSA 7 0.0105 0.2102 0.1839 0.4594 0.1589 0.9160 0.0830 0.0293 0.5367 NaCl + LM 4 0.0424 0.7456 0.8566 0.5102 0.7461 0.7155 0.6902 0.5327 0.4865 NaCl + LO 4 0.0115 0.4270 0.2726 0.6416 0.7956 0.0216 0.1036 0.5805 0.2666 NaCl + TA 4 0.8574 0.5973 0.1791 0.2904 0.0194 0.400 0.2722 0.8662 0.2016 NaCl + SDS 4 0.0010 0.0321 0.0610 0.06047 0.00995 0.4665 0.9525 0.8996 0.9770 NaCl + BSA 4 0.3660 0.5274 0.5549 0.0214 0.0155 0.2666 0.9208 0.5475 0.7002 CaCl2 + LM 4 0.5122 0.0126 0.0389 0.5122 0.4213 0.0037 0.0125 0.0967 0.0221 CaCl2 + LO 4 0.0122 0.9416 0.7543 0.8820 0.7387 0.6709 0.4475 0.2053 0.2374 CaCl2 + TA 4 0.5215 0.0992 0.1879 >0.9999 0.5144 0.0565 0.1032 0.0009 0.0063 CaCl2 + SDS 4 0.0158 0.0519 0.0248 0.0015 0.0438 0.0840 0.8354 0.4256 0.3727 CaCl2 + BSA 4 0.0072 0.2528 0.5791 0.2547 0.1078 0.0772 0.0460 0.0002 0.0048 393 Table SD 5. Significance values (p) for the effects of DOC and model compounds on delta transepithelial potential (TEP) compared to control at a geometric series of added Na+ or Ca2+ (as a percentage of the LC50) at pH 7 and pH 4; p values <0.05 are considered significant and are bolded. Source pH 3.12 % 6.25% 12.5% 25% 50% 100% 200% 400% NaCl + LM 7 0.0149 0.0079 0.0042 0.0051 0.0086 0.0429 0.0956 0.0640 NaCl + LO 7 0.1075 0.0160 0.0081 0.0116 0.0229 0.0243 0.0788 0.0549 NaCl + TA 7 0.0491 0.2543 0.0746 0.0680 0.0526 0.0656 0.0686 0.0465 NaCl + SDS 7 0.1971 0.3896 0.0915 0.1165 0.1367 0.0574 0.0242 0.0469 NaCl + BSA 7 0.2215 0.0551 0.0487 0.0317 0.0242 0.0351 0.0109 0.0122 CaCl2 + LM 7 0.0023 0.0293 0.0206 0.0548 0.3380 0.3336 0.2997 0.5657 CaCl2 + LO 7 0.1131 0.2054 0.2113 0.1423 0.0273 0.0670 0.0862 0.1217 CaCl2 + TA 7 0.5223 0.6514 0.4417 0.4089 0.3078 0.2607 0.2752 0.2047 CaCl2 + SDS 7 0.0347 0.9077 0.8978 0.8928 0.8464 0.9918 0.7353 0.6833 CaCl2 + BSA 7 0.0400 0.1017 0.1301 0.1397 0.3754 0.5598 0.5240 0.4826 NaCl + LM 4 0.4895 0.1747 0.1317 0.4004 0.1307 0.1164 0.0563 0.0576 NaCl + LO 4 0.0002 0.0262 0.0014 0.0014 0.0209 0.1081 0.0773 0.0256 NaCl + TA 4 0.8107 0.2246 0.4732 0.3074 0.7114 0.9904 0.9314 0.7888 NaCl + SDS 4 0.5596 0.2870 0.0734 0.3243 0.0013 0.0051 0.0004 0.0039 NaCl + BSA 4 0.8103 0.2386 0.0176 0.0489 0.1240 0.4385 0.3025 0.5066 CaCl2 + LM 4 0.0770 0.2071 0.4059 0.7026 0.0389 0.0914 0.0659 0.0618 CaCl2 + LO 4 0.1449 0.0243 0.0406 0.1152 0.2767 0.1746 0.1496 0.1865 CaCl2 + TA 4 0.1059 0.1658 0.4370 0.4280 0.6998 0.3831 0.0372 0.1025 CaCl2 + SDS 4 0.4490 0.7074 0.8870 0.7038 0.4920 0.2721 0.3983 0.1910 CaCl2 + BSA 4 0.0882 0.0217 0.0022 0.0002 0.0007 0.0009 0.0004 0.0002 394 Table SD 6. Relative proportions of the chemical forms of Na, Mg, K and Ca in the experimental waters, as calculated by WHAM VII. Only the proportions of free cations and cation complexes with HA and FA are given. Relative proportions of inorganic complexes (CaHCO3, CaCO3, MgHCO3 and MgCO3) were always < 0.5%. 395 Experimental water Sodium Magnesium Potassium Calcium % free % bound to HA % bound to FA % free % bound to HA % bound to FA % free % bound to HA % bound to FA % free % bound to HA % bound to FA NaCl at the LC 50 value without added DOC at pH 7 99.99 0.000 0.006 99.65 0.000 0.163 99.99 0.000 0.006 99.47 0.000 0.349 NaCl at the LC 50 value with added LM DOC at pH 7 99.95 0.010 0.045 97.77 0.719 1.328 99.94 0.010 0.045 95.60 1.315 2.915 NaCl at the LC 50 value with added LO DOC at pH 7 99.95 0.007 0.048 97.98 0.482 1.349 99.95 0.007 0.048 96.02 0.877 2.928 NaCl at the LC 50 value without added DOC at pH 4 100.00 0.000 0.003 99.74 0.000 0.021 100.00 0.000 0.003 99.76 0.000 0.025 NaCl at the LC 50 value with added LM DOC at pH 4 99.97 0.006 0.023 99.55 0.077 0.147 99.97 0.006 0.023 99.52 0.088 0.177 NaCl at the LC 50 value with added LO DOC at pH 4 99.97 0.007 0.019 99.55 0.088 0.114 99.97 0.007 0.019 99.54 0.100 0.138 CaCl2 at the LC 50 value without added DOC at pH 7 100.00 0.000 0.001 99.83 0.000 0.005 100.00 0.000 0.001 99.83 0.000 0.007 CaCl2 at the LC 50 value with added LM DOC at pH 7 99.99 0.001 0.006 99.80 0.008 0.034 99.99 0.001 0.006 99.78 0.013 0.053 CaCl2 at the LC 50 value with added LO DOC at pH 7 99.99 0.000 0.006 99.79 0.006 0.036 99.99 0.000 0.006 99.78 0.009 0.056 CaCl2 at the LC 50 value without added DOC at pH 4 100.00 0.000 0.001 99.80 0.000 0.003 100.00 0.000 0.001 99.82 0.000 0.004 CaCl2 at the LC 50 value with added LM DOC at pH 4 99.99 0.001 0.006 99.77 0.006 0.020 99.99 0.001 0.006 99.78 0.007 0.025 CaCl2 at the LC 50 value with added LO DOC at pH 4 99.99 0.001 0.005 99.77 0.007 0.017 99.99 0.001 0.005 99.78 0.009 0.021 NaCl at the Km value without added DOC at pH 7 99.93 0.000 0.067 98.95 0.000 0.721 99.93 0.000 0.067 98.57 0.000 1.128 NaCl at the Km value without added DOC at pH 4 100.00 0.000 0.027 99.52 0.000 0.125 99.97 0.000 0.027 99.53 0.000 0.143 NaCl at the Km value without added LM DOC at pH 7 99.94 0.000 0.061 98.92 0.000 0.752 99.94 0.000 0.061 98.44 0.000 1.249 NaCl at the Km value with added LM DOC at pH 7 99.24 0.103 0.654 90.36 2.773 6.546 99.24 0.103 0.654 85.53 3.888 10.295 NaCl at the Km value without added LO DOC at pH 7 99.93 0.000 0.071 98.91 0.000 0.764 99.93 0.000 0.071 98.48 0.000 1.209 NaCl at the Km value with added LO DOC at pH 7 99.59 0.040 0.344 93.23 1.484 4.995 99.62 0.040 0.344 89.14 2.191 8.404 NaCl at the Km value without added LM DOC at pH 4 99.96 0.000 0.038 99.46 0.000 0.156 99.96 0.000 0.038 99.47 0.000 0.175 NaCl at the Km value with added LM DOC at pH 4 99.66 0.061 0.279 97.84 0.679 1.095 99.66 0.061 0.279 97.70 0.713 1.226 NaCl at the Km value without added LO DOC at pH 4 100.00 0.000 0.030 99.50 0.000 0.136 99.97 0.000 0.030 99.51 0.000 0.154 NaCl at the Km value with added LO DOC at pH 4 99.47 0.121 0.407 97.19 1.112 1.264 99.47 0.121 0.407 97.06 1.155 1.388 CaCl2 at the Km value without added DOC at pH 7 99.97 0.000 0.028 99.55 0.000 0.117 99.97 0.000 0.028 99.51 0.000 0.166 CaCl2 at the Km value without added DOC at pH 4 99.99 0.000 0.012 99.61 0.000 0.036 99.99 0.000 0.012 99.63 0.000 0.041 CaCl2 at the Km value without added LM DOC at pH 7 99.97 0.000 0.027 99.54 0.000 0.114 99.97 0.000 0.027 99.50 0.000 0.164 CaCl2 at the Km value with added LM DOC at pH 7 98.85 0.095 1.052 95.34 0.835 3.448 98.85 0.095 1.052 93.96 1.136 4.555 CaCl2 at the Km value without added LO DOC at pH 7 99.98 0.000 0.019 99.60 0.000 0.083 99.98 0.000 0.019 99.58 0.000 0.118 CaCl2 at the Km value with added LO DOC at pH 7 99.83 0.010 0.163 98.88 0.109 0.689 99.83 0.010 0.163 98.58 0.157 0.967 CaCl2 at the Km value without added LM DOC at pH 4 99.99 0.000 0.006 99.65 0.000 0.020 99.99 0.000 0.006 99.67 0.000 0.023 CaCl2 at the Km value with added LM DOC at pH 4 99.16 0.092 0.746 97.50 0.447 1.610 99.16 0.092 0.746 97.38 0.482 1.737 CaCl2 at the Km value without added LO DOC at pH 4 99.99 0.000 0.013 99.59 0.000 0.038 99.99 0.000 0.013 99.61 0.000 0.043 CaCl2 at the Km value with added LO DOC at pH 4 99.75 0.041 0.212 98.84 0.213 0.520 99.75 0.041 0.212 98.80 0.235 0.573 396 Table SD 7. The predicted toxicities of the various experimental solutions [Luther Marsh (LO), Lake Ontario (LO), Tannic acid (TA), Sodium dodecyl sulfate (SDS) or Bovine serum albumin (BSA)] relative to their appropriate reference solutions [NaCl, CaCl2 or Vancouver tap water (VTW)] as assessed by differences in absolute TEP, ΔTEP and the M-M constants, ΔTEPmax and Km at pH 7 and pH 4. Here “+” indicates an increase in toxicity of the experimental solution (compared to the reference solution) and “-” indicates a decrease in toxicity of the experimental solution, and “*” indicates significance for t-test comparisons (p<0.05). Reference solution Variable solution pH Predicted toxicity by absolute TEP Predicted toxicity by TEP Predicted toxicity by TEPmax from M-M Predicted toxicity from Km from M-M VTW LM 7 -* NA NA NA VTW LO 7 +* NA NA NA VTW TA 7 -* NA NA NA VTW SDS 7 -* NA NA NA VTW BSA 7 +* NA NA NA NaCl 7 NaCl 4 7 versus 4 + -* -* -* NaCl LM 7 + +* +* + NaCl LO 7 +* -* - -* NaCl TA 7 + + + - NaCl SDS 7 - +* +* - NaCl BSA 7 +* -* -* + CaCl2 7 CaCl2 4 7 versus 4 + -* -* -* CaCl2 LM 7 - + + +* CaCl2 LO 7 + - -* + CaCl2 TA 7 + + + - CaCl2 SDS 7 - + - +* CaCl2 BSA 7 + - - - VTW LM 4 -* NA NA NA VTW LO 4 -* NA NA NA VTW TA 4 - NA NA NA VTW SDS 4 -* NA NA NA VTW BSA 4 -* NA NA NA NaCl LM 4 - + + + NaCl LO 4 - + + +* NaCl TA 4 - - - + NaCl SDS 4 + +* +* - NaCl BSA 4 - + + + CaCl2 LM 4 -* - -* +* CaCl2 LO 4 + + + + CaCl2 TA 4 - - - + CaCl2 SDS 4 - + + + CaCl2 BSA 4 +* +* +* - 397 Appendix E Supplementary material – Chapter 7 Table SE 1. pH of test solutions Table SE 2. Unpaired t-test results between Rock sole (Lepidopsetta bilineata) and Pacific sanddab (Citharichthys sordidus) for diffusive water flux, oxygen consumption, ammonia, urea-N excretion rates and nitrogen quotient at control salinity (salinity 31) p<0.05 denotes statistical significance Salinity pH 7.5 7.08 15.5 7.70 31 7.91 45 31 with 10mM Ca2+ 8.00 7.91 7.5 with 10mM Ca2+ 7.60 7.5 with 20mM Ca2+ 8.06 31 with 20mM Ca2+ 8.03 Measurement p-values Diffusive water flux 0.0248 Oxygen consumption 0.6914 Ammonia excretion 0.9574 Urea-N excretion 0.1117 Nitrogen quotient 0.8611 398 Table SE 3. Unpaired t-test results between values at control salinity 31 in Rock sole (Lepidopsetta bilineata) in the salinity series versus the salinity-Ca2+ series for diffusive water flux, oxygen consumption, ammonia, urea-N excretion rates and nitrogen quotient. p<0.05 denotes statistical significance Figure SE 1. The effect of % saturation in the water on oxygen consumption rate. Measurement p-values Diffusive water flux 0.2710 Oxygen consumption 0.1524 Ammonia excretion 0.9569 Urea-N excretion 0.3590 Nitrogen quotient 0.0846 399 Appendix F Supplementary material – Chapter 8 Table SF 1. Unpaired t-test results within salinities 30 ppt or 7.5 ppt between the control group means for natural DOC source experiments versus those for model compound experiments in Pacific sanddab (Citharichthys sordidus) for diffusive water flux, oxygen consumption (MO2) ammonia and urea-N excretion rates, and nitrogen quotient. p<0.05 denotes statistical significance. Measurement p-values Diffusive water flux 30 ppt 0.1530 Oxygen consumption 30 ppt Ammonia excretion 30 ppt 0.1611 0.4103 Urea-N excretion 30 ppt 0.1469 Nitrogen Quotient 30 ppt 0.0745 Diffusive water flux 7.5 ppt 0.1239 Oxygen consumption 7.5 ppt Ammonia excretion 7.5 ppt 0.9222 0.9960 Urea-N excretion 7.5 ppt 0.7209 Nitrogen Quotient 7.5 ppt 0.6474 400 Appendix G Supplementary material – Chapter 9 Table SG1. Statistical significance of the effects of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) on physiological parameters in control water, Rio Negro (RN) blackwater and Rio Solimões (RS), assessed with a two-way analysis of variance with Tukey’s test, (p < 0.05 is considered significant). 401 Parameter p-value pH effect p-value Cu effect p-value Interaction effect F (DFn, DFd) pH F (DFn, DFd) Cu F (DFn, DFd) Interaction Na+ flux rate control water 0.008 0.159 0.785 F (1, 28) = 0.076 F (1, 28) = 2.098 F (1, 28) = 8.212 Na+ flux rate RN water 0.553 0.264 0.099 F (1, 25) = 0.362 F (1, 25) = 1.309 F (1, 25) = 2.948 Na+ flux rate RS water 0.065 0.256 0.477 F (1, 24) = 3.735 F (1, 24) = 1.359 F (1, 24) = 0.523 K+ flux rate control water 0.052 0.969 0.720 F (1, 25) = 4.191 F (1, 25) = 0.002 F (1, 25) = 0.132 K+ flux rate RN water 0.475 0.099 0.139 F (1, 26) = 0.526 F (1, 26) = 2.927 F (1, 26) = 2.332 K+ flux rate RS water 0.077 0.184 0.647 F (1, 25) = 3.412 F (1, 25) = 1.870 F (1, 25) = 0.216 Cl- flux rate control water 0.040 0.003 0.349 F (1, 28) = 4.642 F (1, 28) = 10.86 F (1, 28) = 0.908 Cl- flux rate RN water 0.523 0.831 0.040 F (1, 26) = 0.419 F (1, 26) = 0.047 F (1, 26) = 4.678 Cl- flux rate RS water 0.0004 0.395 0.952 F (1, 26) = 16.550 F (1, 26) = 0.750 F (1, 26) = 0.004 Ammonia excretion control water 0.578 <0.0001 0.160 F (1, 26) = 0.319 F (1, 26) = 21.39 F (1, 26) = 2.090 Ammonia excretion RN water 0.170 0.004 0.022 F (1, 25) = 2.004 F (1, 25) = 10.44 F (1, 25) = 6.014 Ammonia excretion RS water 0.926 0.001 0.231 F (1, 26) = 0.009 F (1, 26) = 13.19 F (1, 26) = 1.509 Urea excretion control water 0.283 0.0006 0.980 F (1, 22) = 1.215 F (1, 22) = 15.91 F (1, 22) = 0.0007 Urea excretion RN water 0.297 0.0002 0.059 F (1, 25) = 1.134 F (1, 25) = 19.43 F (1, 25) = 3.930 Urea excretion RS water 0.439 0.031 0.691 F (1, 23) = 0.622 F (1, 23) = 5.271 F (1, 23) = 0.163 DWF control water 0.232 0.485 0.0011 F (1, 24) = 1.507 F (1, 24) = 0.505 F (1, 24) = 13.640 DWF RN water 0.144 0.295 0.004 F (1, 20) = 2.317 F (1, 20) = 1.156 F (1, 20) = 10.620 DWF RS water 0.181 0.754 0.925 F (1, 22) = 1.907 F (1, 22) = 0.101 F (1, 22) = 0.009 PEG clearance control water 0.116 0.088 0.641 F (1, 27) = 2.636 F (1, 27) = 3.148 F (1, 27) = 0.223 PEG clearance RN water 0.217 <0.0001 0.289 F (1, 25) = 1.606 F (1, 25) = 29.03 F (1, 25) = 1.175 PEG clearance RS water 0.331 0.014 0.089 F (1, 22) = 0.991 F (1, 22) = 7.224 F (1, 22) = 3.181 Drinking rate control water <0.0001 0.599 0.0001 F (1, 27) = 27.840 F (1, 27) = 0.284 F (1, 27) = 19.530 Drinking rate RN water 0.249 0.960 0.024 F (1, 25) = 1.397 F (1, 25) = 0.003 F (1, 25) = 5.836 Drinking rate RS water 0.283 0.0222 0.9448 F (1, 24) = 1.209 F (1, 24) = 5.978 F (1, 24) = 0.0048 402 Figure SG1. The effect of copper (nominally 0 versus 200 µg L-1 of Cu) and pH (pH 7 versus pH 4) in control water, in RN water and in RS water on net (A) Ammonia excretion rate (B) Urea-N excretion rate (C) Diffusive water flux rate (D) Drinking rate (E) Gill PEG-4000 clearance rate regressed against %free copper. Data are means ± SEM, N=6-8. Assessed with simple linear regression (p < 0.05 is considered significant).
Thesis/Dissertation
eng
Zoology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Wood, Chris M.
Brauner, Colin J.
The independent and interactive effects of dissolved organic carbon (DOC), major salt ions (Na⁺, Ca²⁺) or Cu and pH on osmoregulatory processes of the fish gill
Text