Science, Faculty of
Oceans and Fisheries, Institute for the
DSpace
UBCV
Lye, Sadie L. R.
Master of Science - MSc
University of British Columbia
Urbanization has disrupted the movement of freshwater and the materials it transports, altering the primary biogeochemical link between land and sea. Coastal ecosystems are subsidized by terrestrial organic matter and nutrient inputs; however, inputs have increased or been altered due to land-use change. Urbanization has increased impervious surfaces, changed vegetation abundance and composition, and introduced novel inputs via wastewater and stormwater. To investigate freshwater and stormwater organic matter and macronutrients (silicate, phosphate, and nitrate), I compared these constituents in Metro Vancouver river water and stormwater to literature values. I estimated the flux of these biogeochemical parameters transported to Burrard Inlet via stormwater annually and identified tracers of stormwater using stable isotopes (carbon and nitrogen) and fatty acids. The concentrations of these biogeochemical parameters were high and generally significantly different between river and stormwater samples. There were higher concentrations of nitrate and silicate in river samples and higher concentrations of phosphate, dissolved organic carbon, particulate organic carbon, and particulate nitrogen in stormwater samples. To investigate the composition of particulate organic matter (POM) in the surface water of Burrard Inlet, I used a Bayesian mixing model approach (MixSIAR) to quantify the relative contributions of phytoplankton, macrophyte, freshwater, and wastewater across 5 basins and 3 seasons. POM is a basal resource for marine food webs and a key component of zooplankton diet, which transfers energy to higher trophic level organisms. Thus, understanding how urbanization changes the composition of POM is important for understanding the productivity and functioning of marine ecosystems. Across all basins and seasons, phytoplankton contributed the most (average = 80 %), followed by macrophytes (average = 7.9 %), wastewater (average = 6.1 %), and freshwater (average = 5.8 %). There were seasonal and spatial differences in POM composition. As cities expand, so will their impact on coastal marine environments, and therefore, there is a need to understand how urbanization changes freshwater and the materials it transports, disrupting marine productivity and ecosystem functioning.
URBAN DISRUPTION OF THE LAND-SEA CONNECTION: UNDERSTANDING STORMWATER AND RIVER INPUTS FROM METRO VANCOUVER AND PARTICULATE ORGANIC MATTER COMPOSITION IN BURRARD INLET BRITISH COLUMBIA by Sadie L. R. Lye B.Sc., University of British Columbia, 2022 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Oceans and Fisheries) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2025 © Sadie L. R. Lye, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Urban disruption of the land-sea connection: understanding stormwater and river inputs from Metro Vancouver and particulate organic matter composition in Burrard Inlet British Columbia submitted by Sadie Lye in partial fulfilment of the requirements for the degree of Master of Science in Oceans and Fisheries Examining Committee: Briant Hunt, Associate Professor, Oceans and Fisheries, UBC Supervisor Rachel Scholes, Assistant Professor, Civil Engineering, UBC Supervisory Committee Member Sophie Johannessen, Research Scientist, Institute of Ocean Sciences, DFO Supervisory Committee Member Ali Ameli, Assistant Professor, Department of Earth, Ocean and Atmospheric Sciences, UB Additional Examiner iii Abstract Urbanization has disrupted the movement of freshwater and the materials it transports, altering the primary biogeochemical link between land and sea. Coastal ecosystems are subsidized by terrestrial organic matter and nutrient inputs; however, inputs have increased or been altered due to land-use change. Urbanization has increased impervious surfaces, changed vegetation abundance and composition, and introduced novel inputs via wastewater and stormwater. To investigate freshwater and stormwater organic matter and macronutrients (silicate, phosphate, and nitrate), I compared these constituents in Metro Vancouver river water and stormwater to literature values. I estimated the flux of these biogeochemical parameters transported to Burrard Inlet via stormwater annually and identified tracers of stormwater using stable isotopes (carbon and nitrogen) and fatty acids. The concentrations of these biogeochemical parameters were high and generally significantly different between river and stormwater samples. There were higher concentrations of nitrate and silicate in river samples and higher concentrations of phosphate, dissolved organic carbon, particulate organic carbon, and particulate nitrogen in stormwater samples. To investigate the composition of particulate organic matter (POM) in the surface water of Burrard Inlet, I used a Bayesian mixing model approach (MixSIAR) to quantify the relative contributions of phytoplankton, macrophyte, freshwater, and wastewater across 5 basins and 3 seasons. POM is a basal resource for marine food webs and a key component of zooplankton diet, which transfers energy to higher trophic level organisms. Thus, understanding how urbanization changes the composition of POM is important for understanding the productivity and functioning of marine ecosystems. Across all basins and seasons, phytoplankton contributed the most (average = 80 %), followed by macrophytes (average = 7.9 %), wastewater (average = 6.1 %), and freshwater (average = 5.8 %). There were iv seasonal and spatial differences in POM composition. As cities expand, so will their impact on coastal marine environments, and therefore, there is a need to understand how urbanization changes freshwater and the materials it transports, disrupting marine productivity and ecosystem functioning. v Lay Summary Urbanization has altered freshwater movement and the materials it carries, disrupting the flow of nutrients and organic matter (OM) that subsidize coastal ecosystems. These changes occur because of landscape changes, such as increased impervious surfaces and associated stormwater discharge, changes in terrestrial vegetation, and wastewater input. In this study, I compared freshwater and stormwater OM and nutrients in Metro Vancouver’s rivers and stormwater, estimated their annual flux to Burrard Inlet, and identified tracers. Rivers had higher nitrate and silicate, while stormwater contained more phosphate, dissolved and particulate organic carbon, and particulate nitrogen. I found that particulate organic matter (POM), an important resource for marine food webs, composition in Burrard Inlet was dominated by phytoplankton (80%), followed by macrophytes (7.9%), wastewater (6.1%), and combined rivers/stormwater (5.8%). Given the contribution of anthropogenic materials to marine ecosystems, understanding urbanization’s impact on freshwater, transported materials, and marine productivity becomes increasingly important for ecosystem management. vi Preface This thesis comprises four chapters, a general introduction (Chapter 1), two data chapters (Chapters 2 and 3), and a general conclusion (Chapter 4). For Chapter 2, I am the lead author, having led the study design, fieldwork, lab work, analysis, and writing. Dilan Sunthareswaran collected, performed the analysis on, and contributed to the writing and interpreting of all fatty acid data. This Chapter is being prepared for submission for peer review. For Chapter 3, I am the lead author, having led portions of the study design and fieldwork. These field surveys were concerted efforts between many people while I performed all the lab work. I led the analysis, modeling, and writing for Chapter 3. This Chapter is being prepared for submission for peer review. Brian Hunt provided supervision, analytical support, and editing to each chapter. Generative AI was not used in the conception, execution, or drafting of this thesis. vii Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ............................................................................................................................... xii List of Figures ............................................................................................................................. xvi List of Symbols ........................................................................................................................... xix List of Abbreviations ...................................................................................................................xx Acknowledgements .................................................................................................................... xxi Chapter 1: Introduction ................................................................................................................1 1.1 Land-ocean connectivity and urbanization ..................................................................... 1 1.2 Urban disrupted freshwater and associated organic matter and nutrients ....................... 2 1.3 Knowledge gap of urbanization disruption of land-sea connections .............................. 4 1.4 Marine relevant biogeochemical parameters and stable isotopes ................................... 5 1.5 Impacts of urbanization on coastal ecosystems .............................................................. 6 1.6 Metro Vancouver and Burrard Inlet ................................................................................ 7 1.7 Thesis objectives ............................................................................................................. 8 Chapter 2: Stormwater and rivers from urban environments deliver high concentrations of traceable nutrients and organic matter to the coastal ocean ...................................................10 2.1 Introduction ................................................................................................................... 10 2.2 Methods......................................................................................................................... 14 viii 2.2.1 Study area .............................................................................................................. 14 2.2.2 Field sampling ....................................................................................................... 15 2.2.2.1 Stormwater sampling ........................................................................................ 15 2.2.2.2 River sampling .................................................................................................. 16 2.2.2.3 Wastewater treatment plant sampling ............................................................... 17 2.2.3 Laboratory processing ........................................................................................... 17 2.2.3.1 Dissolved organic carbon and total dissolved nitrogen .................................... 17 2.2.3.2 Macronutrients .................................................................................................. 18 2.2.3.3 POM stable isotopes ......................................................................................... 18 2.2.3.4 POM fatty acids ................................................................................................ 19 2.2.4 Statistical analysis ................................................................................................. 20 2.2.5 Additional datasets ................................................................................................ 21 2.3 Results ........................................................................................................................... 22 2.3.1 Environmental data ............................................................................................... 22 2.3.2 Metro Vancouver river and stormwater biogeochemistry .................................... 25 2.3.3 Metro Vancouver wastewater biogeochemistry .................................................... 32 2.3.4 Comparison among previous studies of freshwater biogeochemistry parameters 32 2.3.5 Comparison of freshwater to marine biogeochemistry ......................................... 33 2.3.6 Redfield ratios ....................................................................................................... 33 2.3.7 Estimate of annual stormwater flux ...................................................................... 34 2.3.8 Tracers of Metro Vancouver stormwater, river, and wastewater organic matter . 38 2.4 Discussion ..................................................................................................................... 40 2.4.1 Impacts of urbanization on freshwater biogeochemical parameters ..................... 41 ix 2.4.2 Impacts of urban inputs in the coastal marine ecosystem ..................................... 45 2.4.3 Evaluating Stormwater Flux Estimates ................................................................. 47 2.4.4 Identifying Tracers of Urban Derived Organic Material ...................................... 49 2.5 Conclusion .................................................................................................................... 51 Chapter 3: Wastewater, freshwater, phytoplankton, and marine macrophytes contribute to the particulate organic matter pool in the urban marine environment of Burrard Inlet, British Columbia. .........................................................................................................................53 3.1 Introduction ................................................................................................................... 53 3.2 Methods......................................................................................................................... 57 3.2.1 Study site: Burrard Inlet ........................................................................................ 57 3.2.2 Field surveys ......................................................................................................... 59 3.2.2.1 Pelagic survey ................................................................................................... 59 3.2.2.2 Intertidal survey ................................................................................................ 60 3.2.2.3 Macrophyte survey ............................................................................................ 61 3.2.2.4 Freshwater survey ............................................................................................. 61 3.2.2.5 Wastewater survey ............................................................................................ 61 3.2.3 Laboratory processing ........................................................................................... 62 3.2.3.1 Chlorophyll-a .................................................................................................... 62 3.2.3.2 Macronutrients .................................................................................................. 63 3.2.3.3 POM stable isotopes ......................................................................................... 63 3.2.3.4 Macrophyte stable isotopes ............................................................................... 64 3.2.4 Data analysis ......................................................................................................... 65 3.2.4.1 Mixing model .................................................................................................... 65 x 3.2.4.2 Model inputs ..................................................................................................... 66 3.2.4.3 Mix data ............................................................................................................ 67 3.2.4.4 Model run, fit, and interpretation ...................................................................... 67 3.2.4.5 POM biomass calculations ................................................................................ 67 3.3 Results ........................................................................................................................... 68 3.3.1 Average basin environment variables ................................................................... 68 3.3.2 Source isotope values ............................................................................................ 70 3.3.3 Mix data isotope values ........................................................................................ 73 3.3.4 Relative contributions of sources to POM ............................................................ 78 3.3.5 Composition of POM biomass .............................................................................. 79 3.4 Discussion ..................................................................................................................... 81 3.4.1 Temporal and spatial variability in the contribution of OM sources to POM ...... 82 3.4.2 Missing sources and model refinements ............................................................... 86 3.4.3 Fate of material in the marine environment .......................................................... 87 3.4.4 Future directions for research on urban impacts on marine OM .......................... 88 3.5 Conclusion .................................................................................................................... 89 Chapter 4: Conclusion .................................................................................................................91 4.1 The urban ocean ............................................................................................................ 91 4.2 Biogeochemical properties of river and stormwater in the urban environment ............ 92 4.3 Urban marine particulate organic matter composition .................................................. 92 4.4 Implications in a changing climate ............................................................................... 93 4.5 Implications for expanding cities .................................................................................. 94 4.6 Future directions ........................................................................................................... 94 xi References .....................................................................................................................................97 Appendices ..................................................................................................................................134 Appendix A ............................................................................................................................. 134 Appendix B ............................................................................................................................. 149 xii List of Tables Table 2.1 Mean concentration ± standard deviation of silicate (Si(OH)!), phosphate, (PO!"-), nitrate (NO"- ), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), particulate organic carbon (POC), and particulate nitrogen (PN) in stormwater, river water, wastewater, combined sewer overflows (CSOs), and the marine environment. Measurements were made for this study or collected from published literature. N/A = Not available. ....................................... 27 Table 2.2 Mean concentration ± standard deviation of total fatty acid (TFA), essential fatty acid (EFA), saturated fatty acid (SFA), monounsaturated fatty acid (SFA), polyunsaturated fatty acid (PUFA), and the DHA:EPA and carbon to nitrogen (C:N) ratios in stormwater, river water, wastewater, and the marine environment. Measurements were made for this study or collected from published literature. N/A = Not available. NR = Not reported. ........................................... 31 Table 2.3 Average (± standard deviation) ratio of nitrogen (N) to silica (Si), silica (Si) to phosphorous (P), and nitrogen (N) to phosphorous (P) in stormwater and rivers compared to the ideal marine ratio (Redfield Ratio) of N:Si:P of 16:16:1 (Redfield, 1958; Sterner & Elser, 2003)........................................................................................................................................................ 34 Table 2.4 Estimated annual flux of freshwater and materials from impervious surfaces of Metro Vancouver Burrard Inlet Catchment and literature estimates of freshwater flux and material flux from wastewater treatment plants (WWTPs), combined sewer overflows (CSOs), and the Fraser River. Freshwater flux is reported as km3 yr-1. Materials are reported in tonnes yr-1 and include silicate (Si(OH)!), phosphate, (PO!"-), nitrate (NO"- ), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), particulate organic carbon (POC), and particulate nitrogen (PN). N/A = Not Available. *first order LoadEst estimate see Voss et al. (2015). ........................................ 36 xiii Table 3.1 Mean and standard deviations (SD) for δ13C-POC (‰), δ15N-PN (‰), and C:N molar ratio for the source data used in the mixing model. The freshwater data were seasonally averaged, while the phytoplankton and macrophyte data were seasonally resolved for the wet, wet bloom, and dry seasons. Wastewater data were collected from one time point. .................... 72 Table 3.2 Median [interquartile range] for particulate organic carbon (POC; µmol.L-1), δ13C-POC (‰), particulate nitrogen (PN; µmol.L-1), δ15N-PN (‰), C:N (mol.mol-1), Chlorophyll-a (chl-a; mg.m-3), POC: chl-a (g.g-1) in each basin for each season. These data were the inputs in each model. ............................................................................................................................................ 76 Table A.1 The latitude (˚), longitude (˚), zoning, and traffic volume of stormwater collection sites. Zoning information retrieved from (City of Vancouver, 2023) and traffic volume qualitatively assessed from (City of Vancouver, 2024). (*) These sites are zoned by the Province of B.C. and were reclassified to match the City of Vancouver (Campus and Community Planning, 2023; University Endowment Lands Act, 1996). ....................................................... 134 Table A.2 Number samples taken per sample date of silicate (Si(OH)! ), phosphate, (PO!"-), nitrate (NO"- ), dissolved organic carbon (DOC), total nitrogen (TDN), particulate organic carbon (POC), particulate nitrogen (PN), carbon and nitrogen stable isotopes (δ13C & δ15N), carbon to nitrogen ratio (C:N), and Fatty Acids (FA). The total number of measurements made in river, stormwater, and wastewater shown. ........................................................................................... 136 Table A.3 Concentrations of materials measured in stormwater and river samples. Mean, median, minimum, maximum, standard deviation (SD) and sample number (n) are given for silicate (Si(OH)!), phosphate, (PO!"-) (µmol L-1), nitrate (NO"- ) (µmol L-1), dissolved organic carbon (DOC) (mg L-1), total nitrogen (TDN) (mg L-1), particulate organic carbo (POC) (mg L-1), particulate nitrogen (PN) (mg L-1). An independent two-sample t-test was performed between xiv river and stormwater on each measurement type. P-values reported as significant (*) if p-value <0.05. .......................................................................................................................................... 138 Table A.4 Median, interquartile range [IQR], minimum, and maximum concentrations measured in river locations and stormwater are given for silicate (Si(OH)!) , phosphate, (PO!"-) (µmol L-1), nitrate (NO"- ) (µmol L-1), dissolved organic carbon (DOC) (mg L-1), total nitrogen (TDN) (mg L-1), particulate organic carbon (POC) (mg L-1), particulate nitrogen (PN) (mg L-1). ................... 139 Table A.5 Statistical test summary for fatty acid (FA) markers. Kruskal-Wallis p-value, z-value and Dunn’s Test p-value (Bonferroni-adjusted) for total fatty acid (TFA), essential fatty acid (EFA), saturated fatty acid (SFA), monounsaturated fatty acid (SFA), polyunsaturated fatty acid (PUFA), DHA:EPA for river, stormwater and wastewater particulate organic matter (POM) samples. _-values reported as significant (*) if p-value <0.05. .................................................. 141 Table A.6 Mean ± standard deviation of percentage contributions (% of total fatty acid) of individual fatty acids for particulate organic matter (POM) samples separated by POM type. Wastewater (Combined) includes both effluent and influent samples. Also indicated are mean ± standard deviation for total concentration (ug L-1) of all fatty acids (TFA), percentage contributions of total essential fatty acid (EFA), total saturated fatty acid (SFA), total monounsaturated fatty acid (MUFA), total polyunsaturated fatty acid (PUFA), mean ± standard deviation for DHA:EPA ratio and the number of samples per POM type (n). ........................... 143 Table A.7 Mean, Median, Min, Max, Standard Deviation (SD) and sample number (n) for particulate organic carbon (POC) (mg L-1), particulate nitrogen (PN) (mg L-1), δ13C (‰), δ15N (‰), and C:N molar ratio of wastewater POM samples including 4 influent and 2 effluent samples. An independent two-sample t-test was performed between wastewater and river or stormwater values. P-values reported as significant (*) if p-value <0.05. .................................. 146 xv Table A.8 Mean, median, min, max, standard deviation (SD) and sample number (n) for δ13C (‰), δ15N (‰), and C:N molar ratio of river and stormwater POM samples. An independent two-sample t-test was performed between river and stormwater values. P-values reported as significant (*) if p-value <0.05. .................................................................................................. 147 Table A.9 Statistical test summary for δ13C, δ15N, and C:N molar ratios for of river, stormwater, and wastewater particulate organic material (POM) samples. ANOVA P-Values and Tukey Test P-Values reported. P-values reported as significant (*) if p-value <0.05. .................................. 148 Table B.1 Mean and standard deviations (SD) for δ13C (‰), δ15N (‰), C:N molar ratio, and number of samples (n) for each macrophyte species. ................................................................. 151 Table B.2 The relative contributions of phytoplankton, macrophyte, freshwater (combined rivers and stormwater), and effluent to the surface (0-1 m) particulate organic matter (POM) pool in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek basins in Burrard Inlet during the wet, wet bloom, and dry seasons. Mean ± standard deviation (SD) and 95% Bayesian credible intervals are presented. .................................................................................. 152 Table B.3 Mean contribution of phytoplankton, macrophyte, freshwater and effluent contributions and standard deviations (SD) (mg.m-3) to measured mean total biomass (mg.m-3) for each basin and season. ........................................................................................................... 153 xvi List of Figures Figure 2.1 Map of stormwater (orange) and river (blue) collection sites around Metro Vancouver........................................................................................................................................................ 16 Figure 2.2 (A) Daily mean air temperature (˚C) and (B) total daily precipitation (mm) recorded at the weather station `Vancouver Harbor CS`; (C) river discharge (mm3 s-1) from Capilano, McKay, and Seymour Rivers during the sampling period. The vertical lines spanning the three panels represent stormwater (orange) and river (blue) sampling dates. Temperature and precipitation data were retrieved from Environment and Climate Change Canada (n.d.b) , and river discharge data were retrieved from (Environment and Climate Change Canada, n.d.c) from March 1st, 2023 to April 30th, 2024. Seymour River discharge measurements began in June. .... 25 Figure 2.3 Boxplots for (A) silicate (Si(OH)!) (µmol L-1), (B) phosphate, (PO!"- ) (µmol L-1), (C) nitrate (NO"- ) (µmol L-1), (D) dissolved carbon (DOC) (mg L-1), (E) dissolved total nitrogen (TDN) (mg L-1), (F) particulate organic carbon (POC) (mg L-1), (G) particulate organic Nitrogen (PN) (mg L-1), in Coquitlam Rivers (dark blue), North Vancouver Rivers (median blue), Port Moody Rivers (light blue), City of Vancouver rivers (turquoise), and stormwater (orange). High outliers are not shown (Table A.4). The median is represented by the line inside the box, the bottom of the box represents the first quartile, the top of the box represents the third quartile, and the length of the box represents the middle 50 % spread of the data. The whiskers show the range of the data, and the outliers are represented by points outside of the box and whisker. Values are reported in Table A.4. ................................................................................................................... 30 xvii Figure 2.4 Isotope biplots for stormwater (orange), river (blue), wastewater (red) influent (squares) and effluent (triangles) particulate organic matter (POM) samples: (A) δ13C (‰) vs δ15N (‰), (B) δ15N (‰) vs C:N, and (C) δ13C (‰) vs C:N. ......................................................... 39 Figure 2.5 NMDS ordination of arcsine-square root transformed fatty acid (FA) proportions for stormwater (orange), river (blue), wastewater (red) influent (squares) and effluent (triangles) particulate organic matter (POM) samples. The 18 FAs used in the NMDS were present in samples greater than 0.5 % across all samples on average. Red arrows indicate the strength and direction of correlation between isotopic values (δ13C and δ15N) and NMDS scores. ................. 40 Figure 3.1 Map of the intertidal survey (red), pelagic survey (yellow), and Indian Arm I pelagic survey led by Tsleil-Waututh (TWN) (orange) sites in Burrard Inlet. Basins are labeled. .......... 60 Figure 3.2 Salinity (ppt), temperature (˚C), phosphate (µmol.L-1), silicate (µmol.L-1) nitrate (µmol.L-1), chlorophyll mg.m-3 in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek for intertidal (light blue) and pelagic (dark blue) surveys. The points represent the mean value, and the bars show the standard deviation. In the bottom seasons are shown as shaded areas and defined as follows: the wet season from October 1st and February 29th (blue), the wet bloom from March 1st to May 30th (green), and the dry season from June 1 to September 30th (orange). ................................................................................................................................. 69 Figure 3.3 Seasonally and spatially averaged values for sources–wastewater (square cross), freshwater (square), phytoplankton (asterix), and macrophyte (diamond)–and POM data for δ13C vs. δ15N (A), δ15N vs. C:N (B), and δ13C vs. C:N (C). POM data are for the Outer Harbor (blue), Inner Harbor (yellow), Central Harbor (dark pink), Port Moody (light pink), and False Creek (orange) basins. POM data are seasonally separated by wet (cross), wet bloom (triangle), and dry (circle) seasons. ............................................................................................................................. 73 xviii Figure 3.4 Relative contributions of wastewater (red), freshwater (light blue), macrophyte (purple) and phytoplankton (green) to the surface (0-1 m) particulate organic matter (POM) pool in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek basins in Burrard Inlet during the wet, wet bloom, and dry seasons. Mean values for all contributions exceeding 7 % rounded to 2 decimal places. Mean Bayesian credible intervals are shown and 95 % credible intervals are presented in Table B.2. .......................................................................... 79 Figure 3.5 Mean contributions of wastewater (red), freshwater (light blue), macrophyte (purple) and phytoplankton (green) to the average surface (0-1 m) total particulate organic matter biomass (POM; mg.m-3) in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek in Burrard Inlet during the wet, wet bloom, and dry seasons. Mean values are presented on the bar for each component. Standard deviations are in Table B.2. ................................................... 81 Figure A.1 Map of Environmental weather station (`Vancouver Harbor CS`), river discharge sites (Seymour, McKay, and Capilano Rivers), and sampled Metro Vancouver wastewater treatment plants (WWTP). .......................................................................................................... 135 Figure A.2 Map of the percent (%) impervious surface within Metro Vancouver Administrative Boundary (red) and Burrard Inlet Catchment Area (yellow). Impervious surface data from Metro Vancouver (2024a) and Burrard Inlet Catchment area from Tsleil-Waututh Nation (2017). .... 137 Figure B.1 Map of macrophyte collection sites (purple) around Burrard Inlet. ......................... 149 Figure B.2 Map of Indian River and Fraser River at Hope sampling sites. ................................ 150 xix List of Symbols µ Micro δ Delta ˚ Degrees ˚ C Degrees Celsius ± Plus or Minus ‰ Per mill % Percent xx List of Abbreviations CSO: combined sewer overflow DOC: dissolved organic carbon DOM: dissolved organic matter FA: fatty acid GF/F: glass fiber filter N/A: Not Available NPCTR: Northeast Pacific Coastal Temperate Rainforest NO"$ : nitrate OM: organic matter PO!"$ : phosphate POC: particulate organic carbon POM: particulate organic matter PN: particulate nitrogen Si(OH)! : silicate SD: standard deviation SOG: Strait of Georgia TDN: total dissolved nitrogen WWTP: wastewater treatment plant xxi Acknowledgements I would like to acknowledge that I am privileged to have worked, lived, and studied on the traditional, ancestral, and unceeded xʷməθkʷəy̓əm (Musqueam), Skwxwú7mesh (Squamish), Stó:lō and Səl̓ílwətaʔ/Selilwitulh (Tsleil-Waututh) Nations. These Nations have been stewards and caretakers of this land and water for time in memorial. This is truly a special place. First, I would like to thank the members of my supervisory committee, Dr. Rachel Scholes and Dr. Sophie Johanssen. Thank you for your guidance and advice; it has been instrumental to my success in this thesis. In addition, I would like to thank my funders at UBC for receiving both a David W. Strangeway fellowship and a Peter Wall Award to support my research. Thank you to NSERC, Metro Vancouver, and Tsleil-Waututh Nation who have helped to fund the wider Urban Oceans Project and given advice, resources, and time to me and this project. I truly hope that this research works towards ensuring healthy coastal oceans for everyone. On December 23rd, 2020, I had my first meeting with Brian Hunt in which he seemingly randomly offered me a job as a Co-op student rocketing me into many field, lab, and research projects even forever altering my academic and professional career. For that, I am forever grateful because I found an area of science that I am truly passionate about. Thank you, Brian, for championing opportunities, providing support and guidance, and challenging me to grow at every step along the way. Most importantly, thank you for all the excellent book recommendations over the years. In addition to an outstanding supervisor, I was lucky enough to land in a wonderful and supportive lab environment. So, to the members of the Pelagic Ecosystem, thank you for supporting and cheering me on during my degree. In particular, I would like to thank Jacob xxii Lerner and Anna McKlasky for always being excited to see new data and figures, to talk through the particulars of isotopes and mixing models, and to give advice when I was stuck. Thank you to everyone who came along on sampling trips and thank you for standing in the rain with me. To Julia Fast and Emily Brown, a special thank you for always waiting for me, giggling with me, and generally keeping me sane. Most importantly, thank you to Dilan Sunthareswaran. I physically could not have done this without you. Thank you for always getting your boots soaking wet and laughing when one of us fell over in the field. From late nights in the lab to hyping up each other’s graphs and finding solutions to every problem, I am lucky to have worked alongside someone who is so positive, kind, and smart. Truly, best friends doing best friend things! To my all friends near and far thank you for always being my biggest and loudest cheerleaders. I am lucky to have so many friends who always pick up the phone and immediately make me laugh. To my mum, Diane Lye, and my dad, David Rose, thank you for supporting my education, my passions, and my dreams. Thank you for being my first and oldest teachers and giving me unconditional love. To my brother, Max Rose, and sister, Zoe Lye, thank you for always giving sound advice. Finally, I would like to thank Taylor for your unwavering support during this degree. You have celebrated every victory, buoyed me at every low, and believed in me. This degree has brought me friendship and memories to last a lifetime and forever changed the way I look at rain and the ocean. Thank you. 1 Chapter 1: Introduction 1.1 Land-ocean connectivity and urbanization Coastal marine environments are some of the most productive and biodiverse regions of the global ocean, with high cultural and economic importance (Martínez et al., 2007). A key component for the functioning and structuring of coastal marine ecosystems is their location at the land-sea interface where they receive freshwater and associated terrestrially derived nutrients and organic matter (OM) (Xenopoulos et al., 2017). Freshwater transports the products of erosion, weathering, biological production, and decomposition to the marine environment (Bouwman et al., 2013); all sources of nutrients and OM potentially limiting to primary production. These inputs shape biogeochemical processes (Seitzinger et al., 2005; Ward et al., 2017) and create varied habitat types, often with steep environmental gradients that support diverse communities (Bidlack et al., 2021; Fredston-Hermann et al., 2016). Terrestrial nutrients can enhance autotrophic production, and OM can augment heterotrophic production through bacteria and suspension / deposit feeder consumption (Cloern, 2001; Ward et al., 2017) and be transferred through the food web to higher trophic levels (Arimitsu et al., 2018; Conway-Cranos et al., 2015; Vargas et al., 2018). Recognizing the importance of and studying land-sea connections in driving biogeochemical processes is essential for managing and conserving coastal ecosystems in the face of expanding urbanization. Urbanization and associated coastal development are one of the main disrupters of natural processes at the land-sea interface. One way in which urbanization alters land-sea connections is by modifying freshwater pathways. Urbanization causes large changes to the volumes and patterns of freshwater discharge due to factors including human water demand, impervious 2 surfaces, and wastewater production (Kaushal & Belt, 2012; Walsh et al., 2012) as well as increasing the concentrations of the materials they transport. In addition, urbanization also significantly modifies coastal habitat, through direct habitat loss, shoreline modification, ocean sprawl, increased boat traffic, novel species introduction, and pollution, among other impacts (Crain et al., 2009; Fang et al., 2018; Todd et al., 2019), which may all physically, biologically, or chemically change OM processing and composition. These urbanization driven changes to OM and nutrient processes may alter the biogeochemical processes that structure coastal ecosystems (Seitzinger et al., 2005; Ward et al., 2017). Though urbanization and human activity are routinely listed as disruptors of land-sea connection (Hunt et al., 2024; Xenopoulos et al., 2017), there are relatively few studies investigating urban altered biogeochemical cycles and the subsequent implications for the productivity and health of the marine ecosystem. Given that most of the world’s populations currently live in expanding coastal cities (Barragán & De Andrés, 2015), urban induced disruption of the land-sea interface and coastal marine environments is intensifying, underscoring the urgent need to better understand urban impacts on coastal oceans. 1.2 Urban disrupted freshwater and associated organic matter and nutrients Urbanization has disrupted the movement of water and the materials it transports, which are the primary biogeochemical links between terrestrial and marine systems. In non-urbanized environments, freshwater and the materials it transports pass through and transform in soils and freshwater systems before delivering important organic and nutrient subsidies to coastal oceans (Freeman et al., 2007; Hunt et al., 2024; Xenopoulos et al., 2017). In an urbanized environment, freshwater runoff is affected by the prevalence of impervious surfaces that decrease rainwater infiltration, increase surficial runoff volume and velocity, and reduce evapotranspiration (Paul & 3 Meyer, 2001). Stormwater, a novel input to the coastal ocean, is defined as rainwater that flows over impermeable surfaces such as sidewalks and roads into stormwater pipes, bypassing natural filtration mechanisms and wastewater management systems to enter the ocean or rivers at a higher velocity, a warmer temperature, and full of novel inputs (Walsh et al., 2012). In urban environments, rivers tend to be strongly impacted by stormwater, often exhibiting ‘urban stream syndrome,’ which is characterized by flashier hydrographs, reduced base flow, and changed channel morphology (Meyer et al., 2005; Paul & Meyer, 2001; Walsh et al., 2005). By altering the flow of freshwater from land to sea, urbanization impacts the quantity and quality of the materials transported by freshwater to the coastal ocean. As a consequence of urbanization, wastewater is another anthropogenically altered freshwater, OM, and nutrient input to the coastal ocean. Effluent from wastewater treatment plants (WWTPs) is discharged either directly into the ocean or indirectly via rivers. Globally, 349.4 km3 of wastewater is produced annually, with North America accounting for 20 % of this total (Jones et al., 2021). While some of this water is reused, the vast majority undergoes some level of treatment or is discharged without treatment to receiving environments with high OM and nutrient concentrations (Ehalt Macedo et al., 2022; Van Drecht et al., 2009). Urban impacted freshwater is thought to transport an increased load of OM and associated nutrients to the coastal environment. A study in developed coastal areas of the Northeast Pacific estimated a 1099 % increase in freshwater total suspended solids export to the ocean relative to pre-development conditions (Levin et al., 2020). Rivers in urban environments have higher OM and nutrient loads than those in forested watersheds (Kaushal & Belt, 2012; Kroeze et al., 2013; Walsh et al., 2005). In part, this is the result of stormwater that rapidly mobilizes and transports OM and nutrients to receiving waters (Jani et al., 2020; McCabe et al., 4 2021; Yang & Lusk, 2018). Land-use changes, primarily surface hardening, (McCabe et al., 2021; Yan et al., 2024) coupled with decreases in the abundance and changes in the composition of terrestrial vegetation, (Kaushal & Belt, 2012; Ruas et al., 2022) contribute to increases in freshwater material load. As a result, both stormwater and urban impacted rivers are characterized by increased suspended solids, OM, macronutrients (phosphate and nitrate), and contaminant loads (Meyer et al., 2005; Walsh et al., 2005; Wenger et al., 2009). Further, WWTPs discharge high volumes of material, delivering novel OM, and associated nutrients to the coastal ocean (Ehalt Macedo et al., 2022; Jones et al., 2021). The fate and composition of this increased material load originating from urban modified terrestrial environments in the marine environment is largely unknown. Thus, there is a need to study marine relevant biogeochemical parameters, including OM and nutrient constituents (phosphate, nitrate, and silicate), in urban altered freshwater with the purpose of understanding the implications in marine ecosystems. 1.3 Knowledge gap of urbanization disruption of land-sea connections Emerging concepts of urban ecology are generally focused on freshwater (Kaushal & Belt, 2012) and terrestrial systems (Alberti, 2008), neglecting how urbanization alters marine ecosystems. As a result, there remain many outstanding research questions and knowledge gaps in our understanding of how urbanization impacts the marine environment and the processes that connect land and sea (Airoldi et al., 2021; Todd et al., 2019). A concerted research agenda is needed to address the many ecological questions in this novel environment, however, first, it is critical to understand changes that alter OM as they have repercussions for the marine food web. Reviews commonly identify urbanization and human activity as disruptors of the land-sea connection (Hunt et al., 2024; Xenopoulos et al., 2017), as urbanization modifies freshwater 5 pathways (Walsh et al., 2012) and OM inputs (Kaushal & Belt, 2012). However, there have been few studies investigating these urban disrupted biogeochemical cycles in urban coastal environments. Stormwater, urban impacted rivers, and wastewater are all anthropogenically modified freshwater pathways discharging OM and nutrients into coastal oceans. Wastewater is relatively better studied (e.g. Berto et al., 2013; Khangaonkar et al., 2018; McCallum et al., 2019) than stormwater and urban impacted rivers, despite growing concern of stormwater impacts on coastal ecosystems (Levin et al., 2020). Furthermore, stormwater and urban impacted rivers have rarely been studied as sources of resources for marine food webs despite freshwater inputs being integral to coastal ocean’s functioning and global biogeochemical cycling (Seitzinger et al., 2005; Xenopoulos et al., 2017). Upon reaching the marine system, the fate of this material is poorly understood because of the need to identify tracers for stormwater in a complex urban marine matrix. In the marine system, to understand the uptake and sinking of freshwater material, it is necessary to understand the composition of POM. This work acts as a first step to understanding how urbanization alters land-sea connection and the surface POM pool to better understand the urban ocean: a growing global ecosystem. 1.4 Marine relevant biogeochemical parameters and stable isotopes Marine relevant biogeochemical parameters include OM (dissolved and particulate organic carbon and nitrogen) and inorganic nutrients (e.g., silicate, phosphate, and nitrate). Measurements of OM and nutrients are useful for understanding carbon, nitrogen, and phosphorous cycling (Seitzinger et al., 2005), oxygen demand (Khangaonkar et al., 2018), and heterotrophic versus autotrophic production (Andersson et al., 2018; Crump et al., 2017; 6 McNicol et al., 2023). These biogeochemical parameters are rarely measured in urban freshwater with the purpose of considering them as sources to marine environments. Answering the question of urban derived OM uptake in the coastal ocean requires material tracers. Stable isotopes (δ13C and δ15N) have been shown to be an effective tool to distinguish between terrestrial and marine organic matter sources and trace their uptake into food webs (Arimitsu et al., 2018; St. Pierre et al., 2022). δ13C isotope signatures reflect the primary producers of the system, which explains the different signatures in the marine (phytoplankton) and terrestrial (plants) systems (Fry, 2006). Baseline δ15N values reflect the environment, nitrification, and denitrification in a system or reflect anthropogenic enrichment, which helps to distinguish organic source material (Fry, 2006; Post, 2002). Previous studies have shown a clear separation in the isotope signatures of marine, freshwater, and wastewater sources (Berto et al., 2013; Liénart et al., 2016). However, no study that I am aware of has compared these sources to stormwater. 1.5 Impacts of urbanization on coastal ecosystems The disruption of land-sea connection resulting from urbanization could have significant implications for the functioning and productivity of the marine ecosystem. For example, increased nutrient loads from urban sources can lead to harmful algal blooms (Cloern, 2001) or hypoxia (Khangaonkar et al., 2018). Stormwater and wastewater discharge have been associated with changes in phytoplankton species composition and production (Corcoran et al., 2010; Reifel et al., 2013; Varkey et al., 2018). Additionally, terrestrial organic material is associated with higher heterotrophy and reduced phytoplankton growth (Andersson et al., 2018; Crump et al., 2017; McNicol et al., 2023) in marine systems. Phytoplankton are an important prey source for 7 zooplankton (Brett et al., 2009; McLaskey et al., 2022a) and transfer energy to higher trophic level organisms. Thus, anthropogenically induced changes in OM and nutrient inputs can directly or indirectly alter the composition and abundance of marine OM pools, which has implications for the productivity and health of the entire ecosystem. 1.6 Metro Vancouver and Burrard Inlet Metro Vancouver is located on Səl̓ilw̓ət (Burrard Inlet including Indian Arm), which is part of the unceded, ancestral, and traditional territory of the Coast Salish Peoples, including the territories of the xwməθkwəy̓əm (Musqueam), Skwxwú7mesh (Squamish), Stó:lō, and Səl̓ílwətaʔ/Selilwitulh (Tsleil-Waututh) Nations. Historically, Burrard Inlet has been a productive marine environment that is a habitat for many culturally and commercially important species such as herring, salmon, and shellfish (Tsleil-Waututh Nation, 2017). Processes of urbanization and colonization have dramatically transformed the physical environment and introduced novel inputs to the marine ecosystem. Today, Vancouver is Canada’s largest port (Vancouver Fraser Port Authory, 2023) and home to over 2.6 million people (Statistics Canada, 2023). Here, I use Metro Vancouver as a case study to investigate some of the effects of an urban environment on the marine coastal environment, with an emphasis on altered land-sea connection. Metro Vancouver and Burrard Inlet are an ideal case study because of their location within the Northwest Pacific Coastal Temperate Rainforest (NPCTR), an area of high land-to-sea connectivity and reliance on terrestrial inputs (Bidlack et al., 2021; Hunt et al., 2024). Metro Vancouver receives an average of 1537.4 mm of precipitation annually (Environment and Climate Change Canada, n.d.a), with climate change projected to increase precipitation by 10 % 8 in the next 20 to 50 years (Morrison et al., 2014). The population and urban sprawl of Metro Vancouver are expected to continue to grow (Metro Vancouver Growth Projections, 2024), mimicking the trend of growing coastal cities worldwide (Barragán & De Andrés, 2015) and increasing the stormwater volume. Finally, Metro Vancouver is an important place to do this work to meet the objectives laid by Tsleil-Waututh Nation in the “Burrard Inlet Action Plan” (Tsleil-Waututh Nation, 2017). Tsleil-Waututh Nation has the right to a safe and sustainable harvest, which is not possible with the current health of Burrard Inlet. I hope that this work can contribute to meeting the Burrard Inlet Water Quality Objectives and improve our understanding of stormwater from a marine perspective (British Columbia Ministry of Environment and Climate Change Strategy (ENV) & Tsleil-Waututh Nation (TWN), 2024). 1.7 Thesis objectives The overarching goal of this thesis is to improve the understanding of how urbanization modifies freshwater sources of OM and nutrients and modifies the POM pool in marine environments. Specifically, I address knowledge gaps in stormwater constituents and marine surface POM composition in the urban environment. In Chapter 2, I characterize marine-relevant biogeochemical parameters in stormwater and estimate the flux of this material to Burrard Inlet for the first time. I compare stormwater material concentrations and flux to rivers, wastewater treatment plans, and the marine environment to contextualize these measurements. Finally, I consider carbon and nitrogen stable isotopes and FAs as a tracer of stormwater. In Chapter 3, I use carbon and nitrogen stable isotopes and C:N ratios in a Bayesian mixing model to quantify 9 the contributions of freshwater, phytoplankton, wastewater, and macrophyte OM to surface POM in Burrard Inlet seasonally and spatially. 10 Chapter 2: Stormwater and rivers from urban environments deliver high concentrations of traceable nutrients and organic matter to the coastal ocean 2.1 Introduction Coastal marine environments are some of the most productive and biodiverse regions of the global ocean, with high cultural and economic importance (Martínez et al., 2007). A key component to the structure and functioning of coastal marine ecosystems is their location at the land-sea interface, where they receive freshwater and associated terrestrially derived nutrients and organic matter (OM) (Xenopoulos et al., 2017). These inputs shape key biogeochemical processes, including carbon cycling and sequestration (Seitzinger et al., 2005; Ward et al., 2017). Terrestrial nutrients and OM can also enhance autotrophic and heterotrophic production, respectively (Cloern, 2001; Ward et al., 2017; Xenopoulos et al., 2017), and can be transferred through the food web to higher trophic levels (Arimitsu et al., 2018; Conway-Cranos et al., 2015; Vargas et al., 2018). Urbanization is a form of land-use change that can alter the movement of freshwater and associated materials, thereby disrupting land-sea connection and associated ecosystem processes. Quantifying and characterizing urban derived material contributions to the ocean is an important step toward understanding the impact of urbanization on coastal ecosystems. Urbanization can modify freshwater and material inputs to the coastal ocean in several ways. Urbanization reduces terrestrial vegetation coverage and modifies species composition, which can change the quantity and composition of nutrients and OM available to be transported by freshwater (Kaushal & Belt, 2012; McCabe et al., 2021; Yang & Lusk, 2018). Urbanization 11 causes large changes to the volumes and patterns of freshwater discharge resulting from human water demand, wastewater, and the prevalence of impervious surfaces (Kaushal & Belt, 2012; Walsh et al., 2012). In particular, impervious surfaces have the effect of decreasing rainwater infiltration, increasing surficial runoff volume and velocity, and reducing evapotranspiration (Paul & Meyer, 2001). Stormwater, derived from rainfall moving over impervious surfaces, is managed by infrastructure designed to rapidly drain surfaces and transport water directly into receiving waters without filtration (Walsh et al., 2012) and can mobilize and transport high quantities of nutrient-rich OM (Jani et al., 2020; McCabe et al., 2021; Yang & Lusk, 2018). Levin et al. (2020) estimated a 1099 % increase in freshwater total suspended solids in developed coastal areas of the Northeast Pacific relative to pre-development conditions. Freshwater in urban areas is also channeled through rivers. These can be subject to ‘urban stream syndrome,’ where rivers are strongly influenced by stormwater flows and have flashier hydrographs, reduced base flow, and changed channel morphology (Meyer et al., 2005; Paul & Meyer, 2001; Walsh et al., 2005), while also having elevated nutrient and OM concentrations (Meyer et al., 2005; Walsh et al., 2005; Wenger et al., 2009). In addition to higher OM concentrations, urban derived OM in stormwater and rivers has been shown to be more labile than non-urban derived OM, which may be the result of increased microbial production (Parr et al., 2015; Smith et al., 2021), reduced soil processing and vegetation (Hosen et al., 2014; McCabe et al., 2021), and added anthropogenic OM sources such as oil, grease, and sewage (Badin et al., 2008). Thus, in urban environments, there is evidence that freshwater and associated material inputs to the coastal ocean are larger and more bioavailable in comparison to natural environments. These anthropogenic disruptions in material transport from the land to the ocean have significant implications for the functioning and productivity of coastal marine ecosystems. 12 Increased terrestrial nutrient (nitrate, phosphate, and silicate) inputs can increase primary production (Cloern, 2001) or cause changes in phytoplankton species composition (Redfield, 1958; Sterner & Elser, 2003). Indeed, stormwater discharge has been associated with changes in phytoplankton species composition (Varkey et al., 2018) and increased primary production (Corcoran et al., 2010), while wastewater discharge has been associated with changes in species composition (Reifel et al., 2013) but reduction in primary production (Gierach et al., 2017). Changes to phytoplankton community composition and productivity can affect the quantity and quality of prey for higher trophic levels (McLaskey et al., 2022a). Like phytoplankton, freshwater OM inputs, including dissolved organic carbon (DOC), total dissolved nitrogen (TDN), particulate organic carbon (POC), and particulate nitrogen (PN), contribute to marine pools of particulate and dissolved OM (St. Pierre et al., 2020, 2022; Vargas et al., 2018) and can ultimately be incorporated into marine food webs (Arimitsu et al., 2018; Conway-Cranos et al., 2015). However, increased terrestrial material is associated with higher heterotrophy and reduced phytoplankton growth in coastal ecosystems (Andersson et al., 2018; Crump et al., 2017; McNicol et al., 2023) , especially in response to anthropogenically modified headwaters (Fork et al., 2020). Changes to primary production and OM pool in marine systems can have cascading effects on higher trophic levels, altering entire ecosystem functioning and productivity. For example, a shift toward more bacteria-based food webs may reduce pelagic productivity at higher trophic levels, as observed in the Baltic Sea (Berglund et al., 2007). While it is apparent that urbanization has the potential to change the availability of nutrients and OM and, therefore, productivity in coastal environments, the contributions of urban sources to the marine environment and their effect on the marine food web remain poorly understood. 13 To better understand the broader marine implications of urban disrupted freshwater material transport to the coastal ocean, it is first necessary to characterize, quantify, and identify tracers of the material inputs in stormwater, rivers, and wastewater. Stable carbon (δ13C) and nitrogen (δ15N) isotopes have been shown to be an effective tool to distinguish between river, wastewater, and marine OM sources and trace their uptake into food webs (Arimitsu et al., 2018; Berto et al., 2013; St. Pierre et al., 2022), but the comparisons of these sources to stormwater remain unexplored. Fatty acid (FA) profiles provide a complementary approach for delineating OM sources (Brett et al., 2016; Jaschinski et al., 2008; Liénart et al., 2020a; Mathieu-Resuge et al., 2019) while also providing insights into nutritional quality (McInerney et al., 2020; Schoo et al., 2018). Together, stable isotopes and fatty acids offer an effective approach to characterize and trace organic material passage through the marine environment, including food web uptake. Metro Vancouver, British Columbia, is a rapidly growing metropolitan area with an increasing footprint of impervious surfaces contributing to modified freshwater flux (Metro Vancouver, 2024a,b). Situated on səl̓ilw̓ət (Burrard Inlet including Indian Arm), Metro Vancouver is a part of the Northwest Coastal Temperate Rainforest, experiencing an average of 1154.7 mm of precipitation annually (Bidlack et al., 2021; Environment and Climate Change Canada, n.d.a; Tsleil-Waututh Nation, 2017). As a coastal region with high land to sea connectivity disrupted by urbanization, these features make Metro Vancouver an ideal case study for characterizing urban-related freshwater. Marine biogeochemical parameters, including nutrients and OM, have not been comprehensively measured in stormwater or rivers, nor have they been analyzed in comparison to baseline values in rivers, wastewater, and stormwater. In this study, we characterize and quantify marine relevant biogeochemical properties in stormwater and urban rivers of Vancouver and estimate material flux from stormwater to the coastal ocean. 14 We compare these measurements and fluxes to those made in previous studies of rivers, stormwater, and wastewater treatment plants (WWTPs). Finally, we evaluate the utility of OM tracers for understanding the fate of river and stormwater OM in the coastal environment. 2.2 Methods 2.2.1 Study area Vancouver was incorporated into a city in 1885 on the unceded, ancestral, and traditional territory of the Coast Salish Peoples, including the territories of the xʷməθkʷəy̓əm (Musqueam), Skwxwú7mesh (Squamish), Stó:lō and Səl̓ílwətaʔ/Selilwitulh (Tsleil-Waututh) Nations. Today, Vancouver has a population of over 2.6 million people (Statistics Canada, 2021 Census of Population). The terrestrial environment surrounding Burrard Inlet, the oceanographic feature on which Metro Vancouver is located, has been dramatically transformed by processes of urbanization and colonization. Land-use changes have resulted in an estimated 66,180 Ha of impervious surfaces within Metro Vancouver (Metro Vancouver, 2024a) and the loss of 120km of streams and 40 streams within the City of Vancouver and North Vancouver, respectively (Lesack & Proctor, 2019; Tsleil-Waututh Nation, n.d.). Some of the lost streams have been filled in, while others have been incorporated into the storm and sewer network. Burrard Inlet receives discharges from approximately 407 active and historic stormwater outfalls, as well as, 24 active and 11 historic combined stormwater sewer overflow outfalls (Rao, 2022). The Burrard Inlet Action Plan, authored by Tsleil-Waututh Nation, identified stormwater as a priority area for research and point source pollution reduction to improve water quality (Tsleil-Waututh Nation, 2017). This is important for restoring the health of Burrard Inlet such that Tsleil-Waututh Nation can exert their right to harvest many culturally important species, including herring, salmon, 15 shellfish, and sea birds affected by an urbanized land-sea connection (Tsleil-Waututh Nation, 2017). The historical, physical, social, biological, and environmental context of Burrard Inlet underpins the importance of resolving the effect of stormwater organic material on the marine environment. 2.2.2 Field sampling 2.2.2.1 Stormwater sampling Between September 2023 and February 2024, stormwater was collected at 16 different sites around Metro Vancouver (Figure 2.1). Sites were selected to represent different zoning categories (e.g., residential, commercial) and traffic volumes (Table A.1) while being located on a safe intersection at the base of a hill. A total of 34 samples were collected opportunistically during 7 rain events with a predicted rainfall > 20 mm over 24 hrs. All samples were collected directly from the road, above a storm grate at the bottom of a hill, using a plastic dustpan. I did not control for the preceding dry period or timing during the rainfall event, both of which are known to influence contaminant loads (Hathaway et al., 2012; Peter et al., 2020; Taebi & Droste, 2004). Fourteen liters of water were collected into triple-rinsed cubitainers to filter for fatty acid (FA) and stable isotope analysis of particulate organic matter (POM). A sample for dissolved organic carbon (DOC) and total dissolved nitrogen (TDN) was collected in the field by filtering 30 mL of water through a 0.7 µm filter using an acid washed syringe into an acid washed glass vesicle. An additional 13 mL was filtered through a 0.7 µm filter using a syringe into a 15 mL falcon tube for macronutrient analysis. All samples were transported back to the lab in a cooler on -80 ˚C Techni-ice. A Pro30 YSI was used to measure temperature, conductivity, and salinity directly from the water collected in the cubitainer. 16 Figure 2.1 Map of stormwater (orange) and river (blue) collection sites around Metro Vancouver. 2.2.2.2 River sampling Twelve rivers in Metro Vancouver were sampled in April, June, September, and December (Figure 2.1). One river, Stanley Park Culvert, recorded no flow in September. Rivers were selected based on size, accessibility, and geographical distribution across Vancouver. I classified rivers by location: Coquitlam rivers included the Brunette River and Coquitlam River; North Vancouver rivers included Capilano River, Dundarave Pipe, Lawson’s Creek, Lynn River, and Seymour River, Port Moody Rivers included Mossom Creek and Noon’s Creek; and the Vancouver rivers included Spanish Creek and the Stanley Park Culvert. At each sampling event, river water was collected using a triple-rinsed bucket and then sampled as described above for 17 stormwater, for FA and stable isotope analysis of POM, DOC and TDN, and temperature, conductivity, and salinity. 2.2.2.3 Wastewater treatment plant sampling One composite influent and one composite effluent sample were collected from each of Vancouver’s five WWTPs (Iona, Lulu Island, Lions Gate, Annacis Island, and Northwest Langley; Figure A.1). A standard amount of material (~80 mL) was collected each hour from 7:00 AM on September 18th, 2024, to 7:00 AM on September 19th, 2024, into an acid washed sampling vessel to a maximum volume of two liters. Samples were kept cool between collection. After, the final collection samples were transported on -80˚C techni-ice in coolers back to UBC for processing on September 19th, 2024. Samples were collected for FA and stable isotope analysis of POM. 2.2.3 Laboratory processing 2.2.3.1 Dissolved organic carbon and total dissolved nitrogen Dissolved Organic Carbon (DOC) and Total Dissolved Nitrogen (TDN) samples were acidified to a pH of less than 3 using 12 M HCl and stored in the fridge until analysis. Samples were analyzed within 28 days of collection (BC Environment. Laboratory Services, British Columbia Quality Assurance Users Committee, 2023) on a Shimadzu TOC-L. The TOC-L measured non-Purgeable Organic Carbon via combustion catalytic oxidation at 680 ˚C. The carbon dioxide generated by the oxidation process is detected by a high-sensitivity infrared gas analyzer (NDIR). Already acidified samples were purged with purified air to remove any inorganic carbon that may have been present. Samples were bracketed by quality control 18 standards every 14 samples. Each sample was measured 3 times, and the 2 most similar measurements were used to calculate the mean. TDN was measured simultaneously via the combination of thermal decomposition at 720 ˚C and chemiluminescence. 2.2.3.2 Macronutrients Macronutrient samples were frozen upright at -20˚C until analysis. Phosphate (PO!"$), nitrite+nitrate, and silicate (Si(OH)!) were analyzed on a Lachat QuikChem 8500 Series 2 Flow Injection Analysis System. The nitrite+nitrate, orthophosphate, and silicate principles were derived from (Grasshoff, 1976) and methods for each analysis were from Smith and Bogren (2003), Knepel and Bogren (2008), and Tucker (2010), respectively. In this study, I will refer only to nitrate (NO"$) when reporting the results of nitrite+nitrate. 2.2.3.3 POM stable isotopes At each sampling event, no more than 2 L of water was filtered through separate pre-weighed and pre-combusted (at 475 ˚C for 4 hrs.) ~ 0.7 µm 25 mm Sterlitech GF/Ff filters. One filter was acidified with 2 mL of 1 M HCl to remove particulate inorganic carbon (Lorrain et al., 2003). After 30 seconds, samples were rinsed with milli-Q water. The second filter was untreated. Each filter was folded and stored in a tin foil packet at -20 ˚C. Filters were dried in an oven for 24 hrs. at 50 ˚C and weighed to the nearest 0.01mg on a Cubis Sartorius Semi-Micro Balance. Filters were then encapsulated in a crimped tin capsule using a fulcrum press. Samples were placed in 96 well trays and sent to the University of Windsor for carbon and nitrogen stable isotope analysis. Samples were analyzed on a Delta V Advantage Mass spectrometer (Thermo) coupled to Costech 4010 Elemental Combustion system 19 and a ConFlo IV gas interface. Precision, assessed by the standard deviation of replicate analyses of four standards (NIST1577c, internal lab standard (tilapia muscle), USGS 40 and Urea (n = 250 for all), measured ≤ 0.16 ‰ for δ15N and ≤ 0.16 ‰ for δ13C for all the standards. Final δ13C-POC and δ15N-PN isotopic values are expressed relative to the international standards Vienna PeeDee Belemnite (VPDB) and atmospheric nitrogen (AIR), respectively. Wastewater POM precision, assessed by the standard deviation of replicate analyses of four standards (NIST1577c, internal lab standard (tilapia muscle), USGS 40 and Urea (n = 12 for all), measured ≤ 0.17 ‰ for δ15N and ≤ 0.13 ‰ for δ13C for all the standards. The acidified filter was used to quantify particulate organic carbon (POC) and δ13C-POC, and the unacidified filters were used to quantify particulate nitrogen (PN) concentration, δ15N-PN, and C:N molar ratio. 2.2.3.4 POM fatty acids At each sampling event, up to 5 L of water was filtered through separate pre-weighed and pre-combusted (at 475 ˚C for 4 hrs.) 47 mm Sterlitech GF/F filters. Two filters were combined to represent a single POM FA sample (10 L maximum per sample). Each filter was folded and stored in a tinfoil packet at -80 ˚C. FAs were measured as fatty acid methyl esters (FAMEs) which followed a one-step transesterification method described in McLaskey et al. (2022a) and quantified by gas chromatography with flame ionization detection (Scion 436). Briefly, samples were freeze dried in Pyrex screw cap tubes followed by the addition of HCl in methanol (catalyst) and nonadecanoic acid (19:0; internal standard). FAMEs were separated with an Agilent DB-23 column (30 m, 0.25 mm, 0.15 μm) with hydrogen carrier gas (1.2 mL min-1). Samples were injected at 250 ˚C; the column temperature started at 50 ˚C, held for 1 minute, then increased at a rate of 5 ˚C min-1 until 170 ˚C, then 2 ˚C min-1 until 176 ˚C, and then 8 ˚C 20 min-1 until 220 ˚C for a total run time of 33.5 minutes. Peaks were identified by comparing to commercially available standards (Nu-Chek Prep GLC-37; Matreya PUFA Mix No. 3). I excluded samples affected by equipment failure or contamination for a total of 9 stormwater, 15 river, and 10 wastewater samples. A summary of all samples collected and analyzed in this study is provided in Table A.2. 2.2.4 Statistical analysis All statistical analyses and visualizations were completed in R 4.4.1 (R Core Team, 2024). I used independent two-sample t-test and ANOVA to determine if there were statistical differences in measured biogeochemical parameters among stormwater, river, and wastewater samples. Non-metric multidimensional scaling (NMDS) was used to compare 17 FAs that were present at > 0.5 % of FA with a sample across all POM FA samples. The NMDS visualized Bray-Curtis dissimilarities that were calculated from FA proportions following an arcsine-square root transformation. To test for the influence of isotopic composition on FA profiles, NMDS scores were correlated with δ13C and δ15N using the envfit function from the ‘vegan’ package in R (Oksanen et al., 2020). A permutational multivariate analysis of variance (PERMANOVA) was performed on the Bray-Curtis dissimilarities to test for differences in FA profiles among POM types. To test for nutritional differences in POM among sources, I compared total (TFA), essential (EFA), saturated (SFA), monounsaturated (MUFA), and polyunsaturated (PUFA) fatty acid content (in µg L-1), along with the ratio between docosahexaenoic acid and eicosapentaenoic acid (DHA:EPA); the C:N ratio obtained from the stable isotope data was used as an additional nutritional metric. EFAs included all 18-carbon and longer PUFAs (McLaskey et al., 2022b): 21 18:2n-6, 18:3n-3 (ALA), 18:3n-6, 18:4n-3 (SDA), 20:4n-6 (ARA), 20:5n-3 (EPA), 22:6n-3 (DHA). Total stormwater flux was calculated as precipitation runoff from the impervious surface area of Metro Vancouver and the Burrard Inlet Catchment (Figure A2). Metro Vancouver impervious surface area was based on a previous estimate (Metro Vancouver, 2024a). Burrard Inlet Catchment impervious surface area was calculated in QGIS by clipping the impervious surface area dataset to the area of Burrard Inlet Catchment Area (Tsleil-Waututh Nation, 2017) and summing the total area. Using these two estimates of impervious surface, I calculated the total volume of annual precipitation using an estimate of annual precipitation for the `Vancouver Harbor CS` Weather Station from the period between 1991 - 2020 (1537.4 mm) (Environment and Climate Change Canada, n.d.a). Then, I estimated the maximum and minimum annual flux of each measured parameter in tonnes. Finally, I calculated the mean and standard deviation for annual flux and the total volume. 2.2.5 Additional datasets Data for total daily precipitation and mean air temperature for the period March 1st, 2023 to April 30th, 2024 from the weather station `Vancouver Harbor CS` (49°17'43.270" N, 123°07'18.730" W; Figure A.1), were obtained from Environment and Climate Change Canada (n.d.b). River discharge data for MacKay Creek, Seymour River, and Capilano River (sites 08GA031, 08GA030, and 08GA061; Figure A.1) for the period March 1st, 2023 to April 30th, 2024 were obtained from Environment and Climate Change Canada (n.d.c). Surface Si(OH)!, PO!"$, and NO"$data for the Strait of Georgia in 2023 were retrieved from the Strait of Georgia Data Centre data portal (Pacific Salmon Foundation, n.d.). 22 Representative marine POC and DOC data for the Strait of Georgia were obtained from Johannessen et al. (2008). Si(OH)!, PO!"$, NO"$, DOC, TDN, and POC concentration and flux data were gathered from the literature for stormwater (MacDonald et al., 1997), previous studies of Metro Vancouver rivers (MacDonald et al., 1997; Sakamaki & Richardson, 2008), seven coastal watersheds on Calvert and Hectate Island on the Central Coast of B.C. (St Pierre et al., 2021), the Fraser River (Voss et al., 2014, 2015), and wastewater and CSOs (Metro Vancouver Liquid Waste Services Environmental Management and Quality Control, 2024). These data were used to compare average concentrations and flux estimates. The units were standardized before averaging, combining standard deviations, and comparison. FA data were gathered from the literature for stormwater in Los Angeles, USA (Eganhouse et al., 1981a) and Tauranga, New Zealand (Culliford, 2015), the Baker River in the Chilean Patagonia (Vargas et al., 2011), and marine water from the Strait of Georgia (McLaskey et al., 2022b). In Vargas et al. (2011), total EFA was calculated by summing the concentrations of EFAs (see above for classification). In Eganhouse et al. (1981a), SFA and MUFA were calculated by summing the concentration of FAs belonging to their respective FA group. FA data from the literature was standardized to µg L-1 before comparison. 2.3 Results 2.3.1 Environmental data Daily mean air temperature, total precipitation, and river discharge followed the expected seasonal pattern (Figure 2.2). Daily mean air temperatures were highest in the summer months and cooler in the winter months. Higher precipitation occurred in the fall, winter, and spring months. Higher river discharge was generally correlated with higher precipitation. There was 23 higher river discharge in the fall, winter, and spring months, while low discharge was recorded in the summer months. All stormwater sampling events occurred on days with recorded precipitation accumulation. River sampling events occurred throughout the seasonal discharge cycle. 24 25 Figure 2.2 (A) Daily mean air temperature (˚C) and (B) total daily precipitation (mm) recorded at the weather station `Vancouver Harbor CS`; (C) river discharge (mm3 s-1) from Capilano, McKay, and Seymour Rivers during the sampling period. The vertical lines spanning the three panels represent stormwater (orange) and river (blue) sampling dates. Temperature and precipitation data were retrieved from Environment and Climate Change Canada (n.d.b) , and river discharge data were retrieved from (Environment and Climate Change Canada, n.d.c) from March 1st, 2023 to April 30th, 2024. Seymour River discharge measurements began in June. 2.3.2 Metro Vancouver river and stormwater biogeochemistry Si(OH)! and NO"$, concentrations were significantly higher in river than stormwater, while the opposite was true for PO!"$, DOC, POC, and PN (T-test: p < 0.05) (Table 2.1; Table A.3). There was no significant difference in TDN between river and stormwater samples. Macronutrient concentrations were highly variable among the rivers sampled, though the pattern was inconsistent (Figure 2.3; Table A.4). For example, Spanish Creek and Mossom Creek both had elevated levels of Si(OH)!, NO"$, and PO!"$ while Lawson’s Creek and Stanley Park Culvert were primarily elevated in NO"$. DOC concentrations were relatively consistent among rivers, with the exception of elevated and variable levels in Spanish Creek and Stanley Park culvert. TDN had relatively high levels in Brunette River and Stanley Park Culvert, while POC and PN were at consistently at low levels relative to stormwater. Stormwater showed the greatest variability among samples in PO!"$, DOC, POC, and PN values. The FA metrics of TFA, EFA, SFA, MUFA, and PUFA were significantly higher in Metro Vancouver stormwater than rivers (Dunn's test: p < 0.05) (Table 2.2; Table A.5). Stormwater had a lower DHA:EPA (Dunn's test, p = 0.0512) and significantly higher C:N ratio (T-test: p < 0.001) than rivers. In both stormwater 26 and rivers, 16:0 was the most abundant FA, followed by 18:1n-9 in stormwater and 18:0 in rivers (Table A.6). 27 Table 2.1 Mean concentration ± standard deviation of silicate (𝐒𝐢(𝐎𝐇)𝟒), phosphate, (𝐏𝐎𝟒𝟑#), nitrate (𝐍𝐎𝟑#), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), particulate organic carbon (POC), and particulate nitrogen (PN) in stormwater, river water, wastewater, combined sewer overflows (CSOs), and the marine environment. Measurements were made for this study or collected from published literature. N/A = Not available. Data source Location 𝐒𝐢(𝐎𝐇)𝟒 (µmol L-1) 𝐏𝐎𝟒𝟑$ (µmol L-1) 𝐍𝐎𝟑$ (µmol L-1) DOC (mg L-1) TDN (mg L-1) POC (mg L-1) PN (mg L-1) Stormwater 1 Metro Vancouver 8.88 ± 12.29 1.36 ± 2.53 8.81 ± 6.46 10.26 ± 13.55 2.41 ± 1.71 15.92 ± 21.46 0.81 ± 0.84 2 Metro Vancouver N/A N/A 29.71 ± 20.93 7.38 ± 5.55 N/A N/A N/A River 1 Metro Vancouver 114.98 ±168.91 0.40 ± 0.70 38.52 ± 31.95 4.57 ± 4.37 3.43 ± 2.94 0.97 ± 3.37 0.06 ± 0.08 2 Metro Vancouver N/A N/A 65.6 10.4 N/A N/A N/A 3 Metro Vancouver N/A 0.16 ± 0.09 29.35 ± 13.37 11.28 ± 7.61 N/A 1.10 ± 1.1 NA 4 Central Coast of B.C. 0.047 ± 0.063 0.003 ± 0.003 0.007 ± 0.01 11.46 ± 4.66 0.198 ± 0.063 N/A N/A Wastewater 1 5 WWTPs in Metro Vancouver (effluent and influent) N/A N/A N/A N/A N/A 0.07 ± 0.06 0.01 ± 0.01 5 5 WWTPs in Metro Vancouver (effluent) N/A N/A 7.68 ± 19.53 N/A N/A N/A N/A 28 CSOs 5 4 CSO locations in Metro Vancouver N/A N/A 11.73 ± 10.95 N/A N/A N/A N/A Fraser River 6 B.C. 81.23 ± 0.12 0.125 ± 0.016 4.76 ± 0.28 3.24 ± 0.85 N/A 0.54 ± 0.11 N/A Marine 7 Strait of Georgia B.C. 31.35 ± 15.18 0.81 ± 0.65 7.58 ± 9.25 N/A N/A N/A N/A 8 Strait of Georgia B.C. N/A N/A N/A 0.74 ± 0.11 N/A 0.14 ± 0.098 N/A 1. This Study; 2. (MacDonald et al., 1997); 3. (Sakamaki & Richardson, 2008); 4. (St Pierre et al., 2021); 5. (Metro Vancouver Liquid Waste Services Environmental Management and Quality Control, 2024); 6. (Voss et al., 2014, 2015); 7. (Pacific Salmon Foundation, n.d.); 8. (Johannessen et al., 2008) 29 30 Figure 2.3 Boxplots for (A) silicate (𝐒𝐢(𝐎𝐇)𝟒) (µmol L-1), (B) phosphate, (𝐏𝐎𝟒𝟑#) (µmol L-1), (C) nitrate (𝐍𝐎𝟑#) (µmol L-1), (D) dissolved carbon (DOC) (mg L-1), (E) dissolved total nitrogen (TDN) (mg L-1), (F) particulate organic carbon (POC) (mg L-1), (G) particulate organic Nitrogen (PN) (mg L-1), in Coquitlam Rivers (dark blue), North Vancouver Rivers (median blue), Port Moody Rivers (light blue), City of Vancouver rivers (turquoise), and stormwater (orange). High outliers are not shown (Table A.4). The median is represented by the line inside the box, the bottom of the box represents the first quartile, the top of the box represents the third quartile, and the length of the box represents the middle 50 % spread of the data. The whiskers show the range of the data, and the outliers are represented by points outside of the box and whisker. Values are reported in Table A.4. 31 Table 2.2 Mean concentration ± standard deviation of total fatty acid (TFA), essential fatty acid (EFA), saturated fatty acid (SFA), monounsaturated fatty acid ( SFA), polyunsaturated fatty acid (PUFA), and the DHA:EPA and carbon to nitrogen (C:N) ratios in stormwater, river water, wastewater, and the marine environment. Measurements were made for this study or collected from published literature. N/A = Not available. NR = Not reported. Data source Location TFA (µg L-1) EFA (µg L-1) SFA (µg L-1) MUFA (µg L-1) PUFA (µg L-1) DHA:EPA C:N Stormwater 1 Metro Vancouver 464.81 ± 463.74 68.64 ± 44.93 237.23 ± 218.93 144.22 ± 201.39 70.11 ± 45.2 0.05 ± 0.16 23.58 ± 6.52 2 Los Angeles, USA 752.24 ± 593.44 NR 442.08 ± 450.12 301.26 ± 180.41 NR NR N/A 3 Tauranga, New Zealand 554.0 ± 85.56 N/A N/A N/A N/A N/A N/A River 1 Metro Vancouver 17.92 ± 14.53 1.48 ± 1.27 12.26 ± 11.1 3.44 ± 3.15 1.61 ± 1.38 0.4 ± 0.4 13.18 ± 2.98 4 Metro Vancouver N/A N/A N/A N/A N/A N/A 8.10 ± 0.38 5 Chilean Patagonia 9.8 0.82 7.2 1.8 0.8 NR N/A Wastewater 1 5 WWTPs in Metro Vancouver (effluent and influent) 16341.72 ± 13017.81 1842.24 ± 1498.04 6909.51 ± 6335.19 7270.90 ± 5898.83 1872.30 ± 1513.69 0.64 ± 0.37 7.49 ± 2.38 6 Melbourne, Australia 535 N/A N/A N/A N/A N/A N/A Marine 7 Strait of Georgia B.C. 21.6 ± 1.4 4.8 ± 0.4 10.48 ± 6.88 3.99 ± 3.33 6.37 ± 6.03 0.95 ± 0.03 4.88 ± 0.89 1. This Study; 2. (Eganhouse et al., 1981a); 3. (Culliford, 2015) 4. (Sakamaki & Richardson, 2008); 5. (Vargas et al., 2011) 6. (Volkman et al., 1999); 7. (McLaskey et al., 2022b) 32 2.3.3 Metro Vancouver wastewater biogeochemistry Stormwater and river samples both had higher POC (T-test: P < 0.001) and PN (T-test: P < 0.001 only for stormwater) than wastewater samples (Table 2.1; Table A.6). All FA metrics in wastewater were substantially higher than stormwater with DHA:EPA being significantly greater (Dunn's test: p < 0.05) (Table 2.2; Table A.5). DHA:EPA was higher in wastewater than river samples and all other FA metrics were significantly higher in wastewaters (Dunn's test: p < 0.05). C:N was significantly lower in wastewater than in stormwater and river samples (T-test P < 0.001) (Table 2.2; Table A.7). 18:1n-9 was the most dominant FA in wastewater, followed by 16:0 (Table A.6). 2.3.4 Comparison among previous studies of freshwater biogeochemistry parameters Mean silicate concentrations in Metro Vancouver rivers and stormwater were ≥ three orders of magnitude higher than those measured in non-urbanized coastal watersheds on the Central Coast of BC, while river data were similar to the Fraser River (Table 2.1). Mean phosphate concentrations in Metro Vancouver rivers and stormwater were higher than those measured previously in Metro Vancouver and ≥ two orders of magnitude higher than in non-urbanized coastal watersheds and the Fraser River. Mean nitrate concentrations in stormwater were lower than those measured previously for Metro Vancouver and CSOs but greater than those measured for WWTP effluent. Similarly, mean nitrate concentrations in Metro Vancouver rivers were higher than in CSOs, WWTP effluent, previous studies of Metro Vancouver rivers, the Fraser River, and in non-urbanized coastal watersheds. Mean DOC concentrations were higher in stormwater but lower in rivers than previously measured for Metro Vancouver. Both stormwater and rivers had higher mean DOC and POC concentrations than the Fraser River but 33 lower than mean DOC concentrations in non-urbanized coastal watersheds. Mean TDN concentrations in stormwater and rivers were higher than in non-urbanized coastal watersheds. Rivers in our study had a higher C:N than previously measured in Metro Vancouver (Table 2.2). TFA, SFA, and MUFA concentrations in Metro Vancouver SW were lower than in previous stormwater studies (Table 2.2). All FA parameters (excluding DHA:EPA) were higher in Metro Vancouver rivers compared to non-urbanized Chilean Patagonia rivers. 2.3.5 Comparison of freshwater to marine biogeochemistry Mean Si(OH)! concentrations were higher in river water samples and lower in stormwater than in the marine environment (Table 2.1). In contrast, mean PO!"$ concentrations were lower in river samples while higher in stormwater samples than the marine samples. Mean NO"$, DOC, and POC concentrations were higher in river and stormwater than the marine samples. Marine POM had lower values than stormwater for all FA metrics, apart from DHA:EPA (Table 2.2). Marine water had similar TFA, SFA, and MUFA concentrations to and higher EFA and PUFA concentrations than rivers. Marine POM had higher DHA:EPA but lower C:N than stormwater and rivers. 2.3.6 Redfield ratios The Redfield ratios for ideal phytoplankton growth in the marine environment are 106:16:16:1 for C:N:Si:P (Redfield, 1958; Sterner & Elser, 2003). For Si:N ratios, river and stormwater samples were generally above the Redfield ratios (Table 2. 3). Most river samples had an average Si:P and N:P ratios above the Redfield ratio. Stormwater samples had an average Si:P ratio below and N:P ratio above the Redfield ratio. 34 Table 2.3 Average (± standard deviation) ratio of nitrogen (N) to silica (Si), silica (Si) to phosphorous (P), and nitrogen (N) to phosphorous (P) in stormwater and rivers compared to the ideal marine ratio (Redfield Ratio) of N:Si:P of 16:16:1 (Redfield, 1958; Sterner & Elser, 2003). Si:N Si:P N:P Redfield Ratio (Redfield, 1958) 16:16 16:1 16:1 Stormwater 4.88 ± 19.09 13.52 ± 12.85 25.76 ± 23.51 Rivers 3.08 ± 2.89 441.64 ± 393.71 212.03 ± 200.63 2.3.7 Estimate of annual stormwater flux I estimated the annual discharge of stormwater from impervious surfaces within the Burrard Inlet Catchment (14680 Ha) and Metro Vancouver (66,180 Ha) (Figure A.2) to be 0.226 km3 yr-1 and 1.07 km3 yr-1, respectively (Table 2.4). For reference, the Fraser River discharges 96 ± 14.87 km3 yr-1, while it was estimated that in 2023 all five Metro Vancouver WWTPs discharged 0.428 km3 and CSOs discharged 0.018 km3 for 15 outfalls. Estimates of annual stormwater silicate flux were higher than that of small non-urbanized coastal watersheds. The annual stormwater silicate flux estimates from Metro Vancouver were 140x larger than those of small non-urbanized coastal watersheds and 10.7 % of the flux from the Fraser River. The nitrate flux from Metro Vancouver stormwater was 2.7x greater than from WWTPs but only 1.88 % of the flux from the Fraser River. The flux of DOC from Metro Vancouver stormwater was 3.1 % of flux from the Fraser River and 5.6x greater than that of small non-urbanized coastal watersheds. Estimated TDN flux was higher than that of small non-urbanized coastal watersheds. 35 The estimated flux of POC from Metro Vancouver was higher than estimates of all sewage to the Strait of Georgia and 13.4 % of that estimated from the Fraser River. The estimated flux of PN from Metro Vancouver stormwater was 1.5x higher than estimated from WWTPs and 3 % of the flux from the Fraser River. 36 Table 2.4 Estimated annual flux of freshwater and materials from impervious surfaces of Metro Vancouver Burrard Inlet Catchment and literature estimates of freshwater flux and material flux from wastewater treatment plants (WWTPs), combined sewer overflows (CSOs), and the Fraser River. Freshwater flux is reported as km3 yr-1. Materials are reported in tonnes yr-1 and include silicate (𝐒𝐢(𝐎𝐇)𝟒), phosphate, (𝐏𝐎𝟒𝟑#), nitrate (𝐍𝐎𝟑#), dissolved organic carbon (DOC), total dissolved nitrogen (TDN), particulate organic carbon (POC), and particulate nitrogen (PN). N/A = Not Available. *first order LoadEst estimate see Voss et al. (2015). Flux Data source Freshwater Volume (km3 yr-1) 𝐒𝐢(𝐎𝐇)𝟒 (tonnes yr-1) 𝐏𝐎𝟒𝟑$ (tonnes yr-1) 𝐍𝐎𝟑$ (tonnes yr-1) DOC (tonnes yr-1) TDN (tonnes yr-1) POC (tonnes yr-1) PN (tonnes yr-1) Stormwater from Burrard Inlet Catchment 1 0.226 120.41 ± 166.65 29.46 ± 54.80 123.30 ± 90.41 2315.58 ± 3058.10 543.91 ± 385.95 3592.99 ± 4843.31 182.81 ± 189.57 Stormwater from Metro Vancouver 1 1.07 542.81 ± 751.27 132.80 ± 247.04 555.84 ± 407.58 10439.05 ± 13786.47 2452.06 ± 1739.84 16197.83 ± 21834.51 824.14 ± 854.66 Metro Vancouver’s 5 WWTPs 2 0.428 N/A N/A 203.55 ± 517.42 N/A N/A N/A N/A 7 WWTPs discharging into the Strait of Georgia 3 0.38 N/A N/A N/A 7400 N/A 12000 N/A 4 N/A N/A N/A N/A N/A N/A N/A 532.76 Metro Vancouver CSOs 2 0.0182 N/A N/A 13.21 ± 12.33 N/A N/A N/A N/A Fraser River 5 96 ± 14.87 755138 ± 184180 1234.61 ± 474.85 29764.8 ± 5580.9 336280 ± 132110 N/A ~ 120100* N/A 4 N/A N/A N/A N/A N/A N/A N/A 27395.08 37 7 watersheds (4690 Ha) on Calvert and Hecate Islands in Central B.C. 6 0.186 22.10 ± 1.32 0.95 ± 0.12 4.34 ± 3.00 1873.56 ± 528.44 28.86 ± 6.00 N/A N/A 1. This Study; 2. (Metro Vancouver Liquid Waste Services Environmental Management and Quality Control, 2024); 3. (Johannessen et al., 2003) 4. (Sutton et al., 2013); 5. (Voss et al., 2014, 2015); 6. (St Pierre et al., 2021) 38 2.3.8 Tracers of Metro Vancouver stormwater, river, and wastewater organic matter Metro Vancouver river and stormwater POM were not distinct with respect to δ13C and δ15N values, however, the range of river δ13C values (-32.61 to -24.15 ‰) was much wider than that of stormwater (-29.05 to -27.61 ‰) (Figure 2.4; Table A.8). River and stormwater POM did differ with respect to C:N ratios. Wastewater POM δ13C, δ15N, and C:N ratio values differed significantly from stormwater and river samples (Table A.6). There was no apparent difference between wastewater influent and effluent values. An ANOVA found significant differences between stormwater, river, and wastewater in δ13C, δ15N, and C:N ratio values (P < 0.05), but Tukey post-hoc tests did not show significance between stormwater and river values (Table A.9). With respect to FAs, POM samples were generally clustered by source in the NMDS, indicating distinct and consistent FA profiles for source inputs (Figure 2.5): river POM all had negative NMDS1 scores, stormwater POM all had negative NMDS2 scores, and wastewater POM all had positive NMDS1 scores. However, wastewater and river samples demonstrated more dispersion along the NMDS1 and NMDS2 axes, respectively, indicating greater variability in FA profiles than stormwater. Influent and effluent POM showed some overlap, indicating similar FA profiles between wastewater types. PERMANOVA indicated that the FA profiles were significantly different between POM types (p < 0.001), explaining nearly half of the FA variability (R2 = 0.48). The NMDS scores were significantly correlated with δ13C (R2 = 0.669, p = 0.001) and δ15N (R2 = 0.372, p = 0.003). Higher δ13C was most strongly correlated with 18:1n-9, and δ15N is most strongly correlated with 20:5n-3. 39 Figure 2.4 Isotope biplots for stormwater (orange), river (blue), wastewater (red) influent (squares) and effluent (triangles) particulate organic matter (POM) samples: (A) δ13C (‰) vs δ15N (‰), (B) δ15N (‰) vs C:N, and (C) δ13C (‰) vs C:N. 40 Figure 2.5 NMDS ordination of arcsine-square root transformed fatty acid (FA) proportions for stormwater (orange), river (blue), wastewater (red) influent (squares) and effluent (triangles) particulate organic matter (POM) samples. The 18 FAs used in the NMDS were present in samples greater than 0.5 % across all samples on average. Red arrows indicate the strength and direction of correlation between isotopic values (δ13C and δ15N) and NMDS scores. 2.4 Discussion This study characterized the biogeochemical properties of stormwater and urban rivers in Metro Vancouver on the Northeast Pacific coast of Canada to better understand the potential impacts of urbanization on receiving environments in the marine ecosystem. I found that Metro Vancouver urban rivers and stormwater had concentrations of OM (DOC, TDN, POC, PN, and FAs) and nutrients (NO"$, PO!"$, and Si(OH)!) that often exceeded those made previously for the 41 city or for the marine environment. Using these measurements, I calculated the flux of materials transported by stormwater annually and found that these estimates exceeded those from WWTP discharge. Finally, we found that a multi-tracer approach using carbon and nitrogen stable isotopes and FAs effectively distinguished stormwater, river, and wastewater POM, providing a means to trace these materials into the marine food web. Below, I discuss the sources, drivers, and potential implications of urban derived material inputs to the marine ecosystem and consider the limitations of the data in this study. Finally, I suggest future research directions to enhance our understanding of urban impacts on the coastal ocean. 2.4.1 Impacts of urbanization on freshwater biogeochemical parameters The concentrations of biogeochemical parameters were generally significantly different between river and stormwater samples in Metro Vancouver. There was not a consistent pattern among parameters but generally NO"$ and Si(OH)! were higher in river samples and PO!"$, DOC, POC, PN, and FAs were higher in stormwater samples. The concentrations observed were similar to those reported in other studies of stormwater and rivers in other urban environments (Eganhouse et al., 1981b; McCabe et al., 2021; Smith et al., 2021; Yang & Lusk, 2018). Previous studies in Metro Vancouver found higher concentrations of NO"$ and DOC in stormwater than this study (MacDonald et al., 1997), but lower NO"$ and phosphate and higher DOC in rivers (MacDonald et al., 1997; Sakamaki & Richardson, 2008). Differences among studies may be due to local land-use changes (McCabe et al., 2021; Yan et al., 2024) or local restoration efforts (Walsh, et al., 2005). Specifically, Sakamaki & Richardson (2008) studied rivers in Port Moody and Richmond where impervious surfaces have increased by 2 % and 8.8 %, respectively (Metro Vancouver, 2024a), and MacDonald et al. (1997) studied the Brunette River, which has since 42 been the focus of restoration projects (Environment and Climate Change Canada, 2022). In comparison to seven rivers in non-urbanized watersheds on the Central Coast of BC, stormwater and urban rivers had higher concentrations of TDN, NO"$, PO!"$, and Si(OH)!, but not DOC. These results support idea that urban environments lead to increased nutrient concentrations in freshwater (Kaushal & Belt, 2012). FAs have not been previously measured in Metro Vancouver stormwater or rivers, however, measurements of stormwater and rivers have been made in other regions. In comparison to previous studies of FAs in other urban environments, stormwater TFA concentrations were within a similarly high range (400 to 800 µg L-1; Eganhouse et al., 1981a) and river TFA concentrations were similar compared to rivers in the city of Tangura, New Zealand (10 to 20 µg L-1; Culliford, 2015). TFA is expected to increase with urbanization (Boëchat et al., 2014; Lu et al., 2014), which aligns with our findings. I found higher TFA concentrations in Vancouver than in non-urban Chilean Patagonia rivers (Vargas et al., 2011), possibly due to the influence of urbanization. Boëchat et al. (2014) identified a correlation between domestic sewage FA markers (16:0 and 18:0) and urbanization in an adjacent river. Although 16:0 & 18:0 were the dominant FAs in Metro Vancouver, these FAs are ubiquitous in aquatic environments and can originate naturally from vascular plants, algae, and bacteria (Volkman et al., 1981; Wakeham, 1995). Additionally, Metro Vancouver rivers had lower 18:1n-9 and 18:2n-6 concentrations than non-urban Chilean rivers, which were important FAs in Metro Vancouver sewage and considered FA biomarkers in other sewage-related studies (Table A.6; Nichols & Espey, 1991; Quemeneur & Marty, 1992; Rocchetta et al., 2014; Sakdullah & Tsuchiya, 2009). Given the limited FA data available for Metro Vancouver rivers and the variability in sampling approaches among studies Vargas et al. (2011), Boëchat et al. (2014), and 43 Lu et al. (2014) focus on pristine rivers, tropical rivers, and headwater streams across different land types, respectively), further research is needed to better characterize urban influences on riverine FA composition. Nutrient and OM sources and freshwater hydrology could account for the differences in measured concentrations between stormwater and river samples. In urban environments, sources of OM and nutrients in freshwater include but are not limited to vegetation (Allison et al., 1998; Torres-Ruiz & Wehr, 2010), sewage (Kaushal et al., 2011), fertilizers (Yang & Lusk, 2018), pet waste (Hobbie et al., 2017), and vehicle derived compounds (Müller et al., 2020; Wada et al., n.d.) and these can be further affected by watershed processes such as weathering (Roy et al., 1999; Walker & Syers, 1976), fixation (Jones & Smol, 2023), and remineralization (Walker & Syers, 1976). Within an urbanized environment, these sources have the potential to contribute materials to both stormwater and rivers (Kaushal & Belt, 2012; Walsh et al., 2012), thus, concentration differences must be the result of proximity to or quantity of a source or hydrological differences. Impervious surfaces allow stormwater to effectively mobilize and transport POM and nutrients (McCabe et al., 2021; Yang & Lusk, 2018). This enables the rapid accumulation of OM in stormwater that is rich in biogenic FAs, carbon, and nitrogen, including leaf litter (Allison et al., 1998; Torres-Ruiz & Wehr, 2010) and microbial biomass (Zelles et al., 1994). In contrast, the lower concentrations of FAs, carbon, and nitrogen in rivers could be mostly attributed to a dilution effect. While stormwater delivers concentrated pulses of OM and nutrients during rain events (Walsh et al., 2005), even small “flashy” rivers may have more protracted flow events that integrate these inputs over longer periods and larger water volumes, resulting in lower concentrations (Allan & Castillo, 2007). Conversely, DHA:EPA ratio, NO"$ and Si(OH)! were higher in rivers than in stormwater, suggesting that the dilution effect is not 44 solely responsible for the concentration differences between stormwater and river samples. The elevated DHA:EPA ratio in rivers may reflect the production of PUFAs by microalgae, which are likely absent in stormwater (Gladyshev et al., 2013). Higher NO"$ in river samples could be the result of sustained biological sources, whereas NO"$ originating from leaf litter or fertilizers (Yang & Lusk, 2018) is quickly washed off impervious surfaces by rain events (Miguntanna et al., 2013). High riverine Si(OH)! concentrations may be due to local geology, water temperature, or pH (Jones & Smol, 2023), while the extremely high Si(OH)! (> 300 µmol L-1) concentrations observed in this study may have been caused by nearby point sources of silica locally elevating concentrations (Hatt et al., 2004; Kaushal & Belt, 2012). Similarly high Si(OH)! concentrations (> 300 µmol L-1) were recorded in the Hood Canal during a storm event in Washington State, USA (Ward et al., 2012). For all biogeochemical parameters, the influence of nearby anthropogenic point sources such as sewage leaks or fertilizer (Kaushal & Belt, 2012; Yang & Lusk, 2018) could be responsible for the high variability of measurements within stormwater and river samples. There was high variability across all biogeochemical parameters in both stormwater and river samples, and some of this variability could be attributed to differences between sampling locations, however, I could not statistically evaluate this. I would expect that OM and nutrient content in stormwater and rivers to vary spatially due to land-use type (e.g., residential, industrial, commercial) (Lucke et al., 2018; McElmurry et al., 2014) and vegetation abundance and composition (Vaidelys et al., 2020). Furthermore, I would expect the OM content to change seasonally in response to vegetation production (e.g., more leaf litter in the fall; Hill et al., 2022) and rainfall cycles (Yan et al., 2024). This study did not control for the “first flush” phenomenon: a heavy rain after a long dry period. The “first flush” is thought to affect the 45 concentration of constituents, with higher concentrations expected in the rising limb of a hydrograph (before peak flow; McCabe et al. 2021), while other studies have found little effect (Taebi & Droste, 2004). Most first flush studies are performed on contaminants (Peter et al., 2020), and future studies should investigate the effect of the first flush phenomenon OM. One difficulty I encountered while reviewing stormwater studies was the inconsistent definitions of stormwater. Some studies, like this one, defined stormwater as road runoff (Du et al., 2022; MacDonald et al., 1997), while others measured stormwater in culverts/ditches ( McCabe et al., 2021), streams during storm events (e.g., Peter et al., 2020), or stormwater ponds (Loucaides et al., 2007; Walsh et al., 2012; Yan et al., 2024). These differences in methodologies make it difficult to compare across studies. Notably, few studies measured stormwater in municipal pipes or at outfalls, perhaps due to the complexities of gaining access to this infrastructure. Future studies of stormwater would benefit from measuring biogeochemical parameters at outfalls and in pipes. 2.4.2 Impacts of urban inputs in the coastal marine ecosystem Concentrations of the OM and nutrients measured in this study were higher in stormwater and urban rivers than in the marine environment. This suggests that stormwater and urban river derived OM and nutrients could play a role in marine heterotrophic and autotrophic production, as has been demonstrated for other terrestrial inputs (Bidlack et al., 2021; Hunt et al., 2024). The urban rivers and stormwater in Metro Vancouver had N:Si:P ratios above or close to the Redfield ratio. This is important because changes in nutrient ratios can cause changes in the species composition (Corcoran et al., 2010; Varkey et al., 2018) and support harmful algal blooms (Cloern, 2001; Todd et al., 2019). In the Strait of Georgia, the spring bloom overlaps with a time 46 of high precipitation (Allen & Wolfe, 2013), which is when the highest flux of material from the land to the sea is expected to occur (Fellman et al., 2009; Johannessen et al., 2017; St Pierre et al., 2021). However, the high nutrient concentrations in Metro Vancouver stormwater and rivers raise the concern of whether localized eutrophication could occur (Cloern, 2001; Savage et al., 2010). Previous studies have argued that widespread eutrophication is not a concern in the Strait of Georgia because the marine environment is not nutrient limited (Davis et al., 2014; Sutton et al., 2013), however, this does not preclude the potential for eutrophication at more local scales such as Metro Vancouver. Furthermore, hypoxia is spreading in shallow regions of the Salish Sea, an increased contribution of terrestrial OM and nutrients from urban environments could be a contributing factor (Khangaonkar et al., 2018). If urbanization is increasing or altering the amount and ratios of OM and nutrients delivered to the coastal ocean during storm events, there could be implications for marine production and ecosystem functioning (Fuß et al., 2017; Todd et al., 2019). Stormwater’s nutritional profile has high TFA and EFA concentrations, indicating its potential as an energy-dense input to the marine ecosystem. TFAs provide a primary source of metabolic energy (Sargent et al., 2003), and EFAs are critical for growth but cannot be synthesized by consumers (Glencross, 2009). However, stormwater’s DHA:EPA ratio was considerably lower than marine POM. Elevated DHA:EPA ratios are correlated with improved growth and reproductive activity in zooplankton (Parrish, 2009). Rivers, by contrast, had lower TFA and EFA levels but a relatively higher DHA:EPA ratio, though still nearly half of the ratio in marine POM. Marine POM on the coast of BC had a DHA:EPA near the sufficient threshold, higher than both stormwater and urban rivers in our study (Table 2.2; McLaskey et al., 2022b). POM in marine environments exhibits highly dynamic FA availability, with seasonal and 47 phytoplankton community driven shifts influencing TFA, EFA, and DHA:EPA (McLaskey et al., 2022b). Overall, these FA measurements in stormwater and urban river samples suggest that urban freshwater inputs may contribute to energy budgets but likely sub-optimal to support zooplankton growth and reproduction, potentially disrupting trophic dynamics and ecosystem health. 2.4.3 Evaluating Stormwater Flux Estimates This study found that stormwater, like small coastal watersheds, has the potential to transport a large volume of freshwater, OM, and nutrients to the coastal ocean from a relatively small area (Hunt et al., 2024; McNicol et al., 2023). In small pluvial watersheds, water and material residence time is short, especially during storm events, thus, organic material exports tend to be untransformed and labile (Fellman et al., 2021; Hunt et al., 2024; Thom et al., 2018). Stormwater and rivers in urban environments mimic pluvial watersheds’ discharge (Hunt et al., 2024; Kaushal & Belt, 2012) such that during high precipitation events, they can deliver pulses of terrestrial nutrients (Walsh et al., 2005) and higher proportions of bioavailable OM (Parr et al., 2015; Smith et al., 2021), as shown by this study. Coastal watersheds on the Central Coast discharge less water and lower concentrations of materials (St Pierre et al., 2021) compared to Metro Vancouver stormwater, which transports more water and more materials. However, these Central Coast watersheds are in forested regions receiving much higher rainfall volume, both of which are factors that affect material and freshwater flux. Thus, it would be more accurate to compare stormwater flux to pre-development conditions; a study of the northeast Pacific found a 1099 % percent increase in freshwater total suspended solids in developed coastal areas relative to pre-development conditions (Levin et al., 2020). A future study could expand Levin et al.'s 48 (2020) model to the Metro Vancouver region to better understand how urbanization has changed material flux in this region. This study’s estimates of storm flux indicated that stormwater delivers more freshwater, nutrients, and OM than wastewater. Levin et al. (2020) estimated that stormwater from urban areas delivers 88 % of the total suspended solids load to the Northern California Current. These material inputs have largely been ignored or underestimated in nitrogen and carbon budgets for the Salish Sea (Johannessen et al., 2008; Khangaonkar et al., 2018; Sutton et al., 2013). Conversely, WWTP discharges are accounted for in these biogeochemical budgets and are widely accepted as a concerning pollution pathway (Todd et al., 2019). The results of this study demonstrated that stormwater transports a large volume of freshwater and high material loads with the potential for major impacts on the marine environment. Thus, there is an increasing need to refine our estimates of stormwater flux to understand the true threat to coastal environments. The total stormwater material flux presented here represents a theoretical upper limit of stormwater OM and nutrient flux. Our estimate does not account for non-uniform rainfall, seasonality of concentrations, stormwater treatment, or more sophisticated modeling of infiltration. The total stormwater flux for each biogeochemical parameter had high standard deviations, reflecting the variability of their measured concentrations. Improving flux estimates will require understanding the local drivers of variability for each biogeochemical parameter. Further, I expect future studies to refine this estimate using more sophisticated stormwater modeling and additional measurements of relevant materials to capture seasonality, thereby improving our ability to assess these fluxes in comparison to those of rivers and WWTPs. However, this methodology provides a useful framework for other studies to quickly estimate stormwater material flux. 49 2.4.4 Identifying Tracers of Urban Derived Organic Material To determine the fate of urban derived OM in the marine environment, it is necessary to develop tracers for materials from different sources. This study found that carbon and nitrogen isotopes were not sufficient to significantly distinguish river and stormwater OM. The carbon and nitrogen isotope values of stormwater and river OM were similar to those of other rivers in the region (Johannessen et al., 2005; Sakamaki & Richardson, 2008; St. Pierre et al., 2022), while stormwater isotope values were similar to those in Florida (Jani et al., 2020). Jani et al. (2020) attributed stormwater’s isotopic signature to oak leaves, grass, and acorns, all of which are common in Metro Vancouver (City of Vancouver, 2025; Metro Vancouver, 2024a). This is unsurprising as stormwater and rivers in the urban environment share the same sources of OM (Allison et al., 1998; Kaushal & Belt, 2012; Yang & Lusk, 2018) and thus, have the same isotopic sources. Furthermore, rivers are integrated into stormwater management systems (e.g., Lynn River is indicated as part of the stormwater network in North Vancouver; District of North Vancouver, 2015). Thus, during rainfall events, stormwater inputs are delivered directly to Metro Vancouver rivers, contributing to the overlap in their isotopic signatures. Of the 14 days on which river samples were collected, there was recorded precipitation on 13 days and >1 mm of recorded precipitation on 9 days. All river sites were downstream of roads and therefore likely receive road runoff. Thus, the precipitation and site location are additional explanatory factors for the similarities in isotopic signatures. The carbon and nitrogen isotopes of wastewater OM had a signature distinct from stormwater and wastewater. Wastewater OM originates from domestic and industrial discharges (Metro Vancouver Liquid Waste Services Environmental Management and Quality Control, 50 2024), so the underlying material is different from that of stormwater and rivers. The wastewater δ13C values measured in this study were similar to while the δ15N values were more negative than those made in WWTP in other places (Berto et al., 2013; Kelso & Baker, 2020; Liénart et al., 2016). Wastewater is subject to WWTP processing before entering the ocean, but our preliminary data found that this had no effect on isotope values. FAs successfully distinguished stormwater, river, and wastewater POM. This builds on existing literature of the utility of FAs in delineating sources (Brett et al., 2016; Parrish et al., 2015; Pickett et al., 2024). This separation can be explained by specific FAs driving variation for each POM source. For instance, rivers had uniquely high contributions from 16:0, 18:0, and EPA (20:5n-3; Table A6). The presence of EPA in rivers reflects the production of PUFAs by microalgae, which are likely absent in wastewater and stormwater. In contrast, the separation of stormwater and wastewater reflects high percentages of 18:1n-9 and 18:3n-3, respectively (Table A6). The high percentage of 18:1n-9 in wastewater aligns with previous studies (Christman, 2020; Mustapha et al., 2017; Quéméneur & Marty, 1994), and this FA is dominant in cooking oils (Bautista et al., 2009; Segura, 1988) and human feces (Williams et al., 1960). In contrast, the elevated 18:3n-3 in stormwater is likely driven by surficial runoff containing plant-derived material (Zhu et al., 2024). The strong correlation between FA variation and δ13C and δ15N values supports that differences in OM sources are an important driver of variation in FA profiles. More broadly, these carbon and nitrogen isotopes and FAs tracers are usable in more complex matrices, such as coastal environments, where phytoplankton and macrophytes also contribute to POM pools (Berto et al., 2013; Liénart et al., 2016; St. Pierre et al., 2022). Together, stormwater / freshwater and wastewater have distinct carbon and nitrogen isotopes and 51 FA profiles compared to marine phytoplankton (Johannessen et al., 2005; McLaskey et al., 2022b; St. Pierre et al., 2022) and macrophytes (Froese et al., 2019; Galloway et al., 2012; St. Pierre et al., 2022), which supports their utility as tracers of terrestrial and anthropogenic material in the coastal ocean. Future studies tracing stormwater and river derived OM should employ FAs and stable isotopes together to more effectively trace the fate of this material. Combined biotracer approaches have been applied in mixing models to estimate the contributions of source materials to marine POM (Liénart et al., 2020b; Neubauer & Jensen, 2015; O’Donovan et al., 2018; Pickett et al., 2024). Future studies should also investigate other potential tracers, such as oxygen, hydrogen, or sulfur stable isotopes or compound-specific stable isotope analysis (CSIA), to further delineate urban OM sources. 2.5 Conclusion This study demonstrated that stormwater can transport substantial quantities of biogeochemical materials relevant to marine ecosystems to the coastal ocean. I found that the concentrations of OM and nutrients were generally higher in stormwater compared to rivers, and annual stormwater PN, POC, and nitrate flux exceeded that of wastewater. Additionally, I demonstrated that together, fatty acids (FAs) and carbon and nitrogen stable isotopes could distinguish among urban river, stormwater, and wastewater OM. A multi-tracer approach, therefore, has promise for tracing these materials in coastal ecosystems. I also provide an estimate of the total material flux from stormwater. These results are important because stormwater-associated material has, to date, been largely neglected in biogeochemical budgets, and its fate in and impact on the marine environment remains poorly understood despite its potential to alter coastal ecosystems. As urbanization continues to expand (Barragán & De 52 Andrés, 2015), the transport of urban-modified freshwater material will likely intensify, further disrupting land-sea connections and processes. This study underscores the need for future research to disentangle how these changes will shape coastal biogeochemical cycles across diverse ecosystems. 53 Chapter 3: Wastewater, freshwater, phytoplankton, and marine macrophytes contribute to the particulate organic matter pool in the urban marine environment of Burrard Inlet, British Columbia. 3.1 Introduction Coastal marine environments are some of the most productive and biodiverse regions of the global ocean, with high cultural and economic importance (Martínez et al., 2007). A key component to the structure and functioning of coastal marine ecosystems is their location at the land-sea interface, where they receive freshwater and associated terrestrially derived nutrients and organic matter (OM) (Xenopoulos et al., 2017) in addition to marine nutrients (Foreman et al., 2011; Jackson et al., 2015). These inputs shape biogeochemical processes (Seitzinger et al., 2005; Ward et al., 2017) and create varied habitat types, often with steep environmental gradients that support diverse communities (Bidlack et al., 2021; Fredston-Hermann et al., 2016). Anthropogenic activities, particularly urbanization and associated coastal development, disrupt the land-sea connection. This can occur in several ways, including through reduced wetland and intertidal habitat (e.g., loss or replacement with riprap), reduced water infiltration via surface hardening and stormwater infrastructure, and production of novel materials such as wastewater (Crain et al., 2009; Todd et al., 2019). One outcome of urbanization is the modification of the detrital OM inputs to the coastal ocean. A key step towards understanding the effect of urbanization on the ecological and biogeochemical functioning of coastal systems is to determine how urbanization modifies the origin and relative contribution of sources to the marine OM pool. 54 In coastal waters, natural sources of OM include allochthonous materials transported by freshwater from the land and autochthonous inputs from marine primary producers (phytoplankton and macrophytes) (Liénart et al., 2018; St. Pierre et al., 2022). The quantity of terrestrial material reaching the coast is positively correlated with the volume of precipitation (Johannessen et al., 2017; McNicol et al., 2023; St. Pierre et al., 2020) but is also influenced by watershed size and type and vegetation type (Fellman et al., 2014; Hood & Scott, 2008). Terrestrially derived OM increases heterotrophic activity (Andersson et al., 2018; Crump et al., 2017; McNicol et al., 2023) and has been demonstrated to contribute to production in higher trophic levels (Arimitsu et al., 2018; Conway-Cranos et al., 2015; Vargas et al., 2018) but can also reduce phytoplankton growth (Andersson et al., 2018). In productive temperate coastal environments, phytoplankton are typically the main component of surface particulate organic matter (POM) year-round, but particularly during the spring / summer growth season (Liénart et al., 2016; McLaskey et al., 2022a; St. Pierre et al., 2022), and are the primary driver of food web production (Bode et al., 2006; Kundu et al., 2021; Tweddle et al., 2018). Marine macrophytes also contribute to the particulate (Ramshaw et al., 2017; St. Pierre et al., 2022) and dissolved (Jiménez-Ramos et al., 2023) OM pool, particularly during and after their peak growth period in the summer (Froese et al., 2019; St. Pierre et al., 2022). Macrophytes can contribute to higher trophic level diet, but much of macrophyte derived material is believed to sink out of the water column (Bode et al., 2006). Urbanization disrupts natural OM production and introduces novel OM sources. Terrestrial urbanization causes a large change to freshwater discharge volumes because of human water demand, channel modification, and impervious surfaces reducing water infiltration (Walsh et al., 2012). Stormwater, the product of rainwater flowing over impervious surfaces, increases 55 the amount of organic matter and solids delivered to the coastal ocean compared to pre-development conditions (Kaushal & Belt, 2012; Levin et al., 2020). Urbanization is suggested to increase the lability of OM compared to non-urban derived OM (McCabe et al., 2021; Parr et al., 2015; Smith et al., 2021). This may be a consequence of changes to terrestrial vegetation (Ruas et al., 2022), which is known to influence OM (Fellman et al., 2014; Hood & Scott, 2008). Additional terrestrial inputs from urban areas may increase heterotrophy in the marine environment (Andersson et al., 2018; Crump et al., 2017; Hosen et al., 2014; Smith et al., 2021). Urbanization can result in marine eutrophication due to increased nutrient input (Malone & Newton, 2020). Eutrophication can cause changes in phytoplankton production and composition, resulting in altered nutrient cycling and food web structure, as well as harmful algal blooms (Cloern, 2001). Eutrophication can also increase macrophyte production (Dillon & Chanton, 2008). Conversely, macrophyte production is reduced by habitat loss resulting from shoreline armoring and dredging (Dethier et al., 2016; Scherner et al., 2013). The altered production of OM from natural sources could change their contributions to the POM pool. In addition to modifying natural OM sources, urban centers necessitate wastewater treatment facilities that discharge high volumes, delivering novel OM to the coastal ocean (Ehalt Macedo et al., 2022; Jones et al., 2021). Sewage derived OM is relatively labile compared to marine derived OM (Ianson & Allen, 2002; Krogh et al., 2018). Studies have shown evidence of anthropogenic OM contribution from sewage in urban rivers (Kelso & Baker, 2020), lakes (Ngugi et al., 2017), and coastal regions (Berto et al., 2013; J. Tucker et al., 1999). Just as disruption to natural OM sources can impact the POM pool, the addition of novel OM sources could alter the composition of the marine POM pool. 56 Urbanization driven changes in the composition of marine OM may profoundly alter ecosystem function (Findlay & Sinsabaugh, 1999). In coastal environments, where terrestrial inputs subsidize food web production (Hunt et al., 2024), disruption by urbanization may alter the types, seasonal cycle, and volume of materials entering the coastal ocean. Urban runoff tends to have similar levels of organic matter to forested systems (McElmurry et al., 2014) but increased lability compared to their non-urban derived counterparts (Parr et al., 2015; Smith et al., 2021). In freshwater systems, increased impervious surface is associated with increased OM lability and higher heterotrophic activity (Hosen et al., 2014), and in marine systems, increased terrestrial material is associated with higher heterotrophy and reduced phytoplankton growth (Andersson et al., 2018; Crump et al., 2017; McNicol et al., 2023). A shift toward more bacteria-based food webs may reduce pelagic productivity at higher trophic levels, as observed in the Baltic Sea (Berglund et al., 2007). Further, anthropogenic pressures may lead to changes in phytoplankton species composition (Savage et al., 2010), which can alter their nutrition, affecting the success of higher trophic level organisms (Jónasdóttir, 2019). Changes to the availability and nutrition of basal resources have repercussions for food chain length and the health of individual organisms (Taipale et al., 2018), in turn altering entire ecosystem functioning and productivity. To better understand the ecological and biogeochemical disruption that urbanization causes to coastal systems, it is essential to quantify the relative contributions of allochthonous, autochthonous, and novel sources to the POM pool in urban systems. In this study, I used Metro Vancouver as a case study to investigate seasonal and spatial variation in the contribution of OM from urban freshwater, marine macrophytes, marine phytoplankton, and wastewater effluent to the POM of surface coastal waters. To do so, I used the distinct isotopic characteristics (δ13C and δ15N) and molar carbon-to-nitrogen ratios (C:N) of 57 OM sources to estimate their relative contributions using a Bayesian mixing model (Fry, 2006; St. Pierre et al., 2022; Stock et al., 2018). I predicted that contributions of OM sources would vary seasonally, with freshwater contributions being highest in the winter wet season, phytoplankton the highest during the spring wet bloom season and summer dry season, and macrophyte contribution being highest in the dry season. Wastewater was not expected to show a seasonal cycle but was expected to be spatially variable, reflecting proximity to points of entry. I discuss my findings in the context of the impacts of urbanization on the coastal ocean. 3.2 Methods 3.2.1 Study site: Burrard Inlet Metro Vancouver (British Columbia, Canada) is located on Səl̓ilw̓ət (Burrard Inlet including Indian Arm), within the traditional territory of the Coast Salish Peoples, specifically the xwməθkwəy̓əm (Musqueam), Skwxwú7mesh (Squamish), Stó:lō, and Səl̓ílwətaʔ/Selilwitulh (- Waututh) Nations. Burrard Inlet is a productive temperate marine environment within the North Pacific Temperate Coastal Rainforest ecoregion, and thus subject to high freshwater and material flux (Bidlack et al., 2021), that has been radically transformed by processes of colonialization and urbanization. Today, Vancouver is Canada’s largest port (Vancouver Fraser Port Authorityy, 2023) and home to over 2.6 million people (Statistics Canada, 2023). Burrard Inlet is 30 km in length and can be divided into the Outer Harbor, Inner Harbor, Central Harbor, Port Moody Arm, and False Creek, and it is connected to the fjord of Indian Arm, which is an additional 22 km long (Figure 3.1) (Haggarty, 2001; Tabata, 1971; Thomson, 1981). The Outer Harbor has a maximum depth of 100 m mid channel and an average depth of 45 m, the Inner and Central Harbors have a maximum depth of 66 m and an average depth of 21 58 m, Port Moody Arm has an average depth of 10 m, False Creek has a depth range of 4 m to 9 m, and Indian Arm has an average depth of 120 m and a maximum depth of 245 m (Haggarty, 2001; Tabata, 1971; Thomson, 1981; Tsleil-Waututh Nation, 2017). Tides are mixed, mainly semi-diurnal, with a mean tidal range of 3.3 m (Thomson, 1981). The coastal region of Burrard Inlet receives an average of 1,189 mm of precipitation annually (Environment and Climate Canada Change, 2013). Much of this precipitation is delivered to the inlet via natural rivers or stormwater infrastructure. There are approximately 122 rivers that discharge into Burrard Inlet (Tsleil-Waututh Nation, 2017). Historically, there were many more rivers that have either been filled in or converted into the storm and sewer network. In the Lower Fraser Valley, including Richmond, 117 streams no longer exist; within the City of Vancouver 120 km of rivers have been lost; and on the North Shore, an estimated 40 streams have vanished (Lesack & Proctor, 2019; Tsleil-Waututh Nation, n.d.). The Capilano, Seymour, Indian Rivers, and the Buntzen Lake diversion from the Coquitlam Reservoir are the largest sources of freshwater to Burrard Inlet (Haggarty, 2001; Tsleil-Waututh Nation, 2017). Burrard Inlet is also influenced by freshwater discharge from the Fraser River (Khangaonkar et al., 2018; Sutton et al., 2013; Thomson, 1981). Burrard Inlet has approximately 407 active and historical stormwater outfalls of which 320 are actively discharging stormwater runoff from urban and industrial areas(Rao, 2022). There are 24 active and 11 historic combined sewer overflow (CSO) outfalls (Rao, 2022). CSOs refer to a combined storm and sanitary system such that during high intensity rainfall, sewage and stormwater surpass the capacity of the pipes and overflows untreated into the inlet. There are an additional 8 sanitary sewer overflow or emergency overflow outfalls (Rao, 2022). From 2014 to 2022, an average of 31943 Mega Liters was discharged from CSOs each year (Metro 59 Vancouver, 2024b). In Chapter 2, I estimated the flux of stormwater to be 0.226 km3 in 2023. Additionally, there are 5 Wastewater Treatment Plants (WWTPs): Iona, Lulu Island, Lions Gate, Annacis Island, and Northwest Langley (Figure A.1). Lulu Island, Annacis Island, and Northwest Langley discharge into the Fraser River and are secondary treatment facilities (Metro Vancouver, n.d.). Iona is a primary treatment facility and discharges into the Strait of Georgia (Metro Vancouver, n.d.). Lions Gate WWTP performs primary treatment and discharges directly into Burrard Inlet. Lionsgate discharged 27,712 Mega Liters in 2023 (Metro Vancouver Liquid Waste Services Environmental Management and Quality Control, 2024). Primary treatment removes materials that settle or float and 50 % of dissolved organic materials, while secondary treatment uses biological processes to remove 90 % of materials including small suspended solids or soluble organic materials (Metro Vancouver, n.d.). Cumulatively, these WWTP’s treat around 1 billion Liters every day (Metro Vancouver, n.d.). 3.2.2 Field surveys 3.2.2.1 Pelagic survey In 2023, 21 pelagic sites were sampled seasonally in March, June, August, and November by boat, and an additional 2 sites were sampled from land in False Creek (Figure 3.1). Each survey was performed over two to three days. One additional survey was conducted on August 15th, 2023, in Indian Arm with the T’sleil-Waututh Nation’s field crew (Figure 3.1). Surface water was collected with a Niskin bottle, and a Pro30 YSI was used to measure the temperature and salinity of the sampled water. For POM samples, 4 L of water was collected into a triple-rinsed cubitainer. An additional 500 mL was collected into a dark bottle for chlorophyll analysis. A macronutrient sample was collected by filtering 13 mL through a 0.7 µm filter using a syringe 60 into a 15 mL falcon tube. While in the field, all samples were stored in a cooler with -80 ˚C Techni-ice until transported back to the lab for same-day processing. Figure 3.1 Map of the intertidal survey (red), pelagic survey (yellow), and Indian Arm pelagic survey led by Tsleil-Waututh (TWN) (orange) sites in Burrard Inlet. Basins are labeled. 3.2.2.2 Intertidal survey Four intertidal sites were sampled monthly from April 2023 to March 2024 (Figure 3.1). All sites were sampled from the shore during a low tide (3 m below chart datum) using a 20 L bucket. Samples were collected the same as for the pelagic survey. Outer HarborInner Harbor Central Harbor Port MoodyIndian ArmFalse Creek61 3.2.2.3 Macrophyte survey Macrophytes were collected from 14 sites around Metro Vancouver in April, June, August, and December of 2023 (Figure B.1). Sites were checked during each sampling period, and every species present at each site was sampled. Not all sites had macrophytes at every sampling event. Macrophytes were identified in the field, labeled, and stored in a cooler with -80 ˚C Techni ice. Upon returning to the lab, samples were rinsed with Milli-Q water. Any epiphytes, organisms, or decaying material was removed before storage at -80 ˚C until processing. 3.2.2.4 Freshwater survey Riverine and stormwater samples were collected from the Metro-Vancouver Area. Details of these surveys can be found in Chapter 2. Additional samples were included from Indian River, sampled in June, September, and December by TWN’s field crew (Figure B.2). The Fraser River at Hope (Figure B.2) was sampled monthly from March 2023 to April 2024. Briefly, the Fraser River and Indian River were sampled using a 20 L bucket, temperature and salinity measured with a YSI, transferred to triple-rinsed cubitainers and stored in a cooler with -80 ˚C Techni-ice until transported back to the lab for same-day processing. A macronutrient sample was collected by filtering 13 mL through a 0.7 µm filter using a syringe into a 15 mL falcon tube. 3.2.2.5 Wastewater survey Composite influent and effluent samples were collected from each of Vancouver’s five WWTPs (Iona, Lulu Island, Lions Gate, Annacis Island, and Northwest Langley) (Figure A.1). A 62 standard amount of material (~80 mL) was collected each hour from 07:00 on September 18th, 2024, to 07:00 on September 19th, 2024, into an acid washed sampling vessel to a maximum volume of two liters. Samples were kept cool between collections. After the final collection, samples were transported on -80 ˚C Techni-ice in coolers back to UBC for processing on September 19th, 2024. 3.2.3 Laboratory processing 3.2.3.1 Chlorophyll-a Bulk chlorophyll-a samples were collected by filtering 250 mL of water through a Sterlitech GF/F filter. All filtration was done under a pressure of -0.2 Bar. After filtration, samples were stored in falcon tubes in black roll-packs at -80 ˚C until processing. To measure chlorophyll, 8 mL of 90 % acetone was added to each falcon tube so that the filter was submerged and incubated for 24 hours in the dark at -20 ˚C. Samples were then warmed to room temperature and analyzed with a TD-700 fluorometer using the fluorometric method described in (Strickland & Parsons, 1972). The fluorometer was blanked before use using a room-temperature 90 % acetone solution. The sample liquid was transferred into a borosilicate tube, placed into the fluorometer, and the fluorescence reading recorded. Then, 2-3 drops of 10 % HCl were added to the sample, and the fluorescence reading was recorded again. The chlorophyll concentration was calculated using the following equation: Chl = 2.07339*(Fo-Fa)*0.8121*(vol_ex/vol_filt ) Fo= Flourometer reading before acidification Fa = Flourometer reading after acidification vol_ex = volume extracted from filter vol_filt= total volume filtered onto filter 63 3.2.3.2 Macronutrients In the lab, samples were frozen upright at -20 ˚C until analysis. Phosphate, nitrite+nitrate, and silicate were analyzed on a Lachat QuikChem 8500 Series 2 Flow Injection Analysis System. The nitrite+nitrate, orthophosphate, and silicate principles were derived from (Grasshoff, 1976) and methods for each analysis were from Smith and Bogren (2003), Knepel and Bogren (2008), and Tucker (2010), respectively. In this study, we will refer only to nitrate when reporting the results. All macronutrient samples were pre-filtered through a 0.7 µm filter using a syringe, except samples from the March 2023 pelagic survey. 3.2.3.3 POM stable isotopes At each sampling event, replicate samples of no more than 2 L of water were filtered through separate pre-weighed and pre-combusted (at 475 ˚C for 4 hrs.) ~ 0.7 µm 25 mm Sterlitech GF/F filters. One of the replicates was acidified with 2 mL of 1 M HCl to remove particulate inorganic carbon (Lorrain et al., 2003), using HCl diluted with milli-Q water for freshwater samples and diluted with particle-free seawater for marine samples. Samples were immersed for 30 seconds, after which they were rinsed with Milli-Q water (freshwater samples) or filtered salt water (marine samples). The second filter was untreated. Each filter was folded and stored in an aluminum-foil packet at -20 ˚C. Filters were oven dried for 24 hours at 50 ˚C and weighed to the nearest 0.01mg on a Cubis Sartorius Semi-Micro Balance. Filters were then encapsulated in a crimped tin capsule using a fulcrum press. Except for the March 2023 pelagic survey, all samples were sent to the University of Windsor Fisk Lab for carbon and nitrogen stable isotope analysis. Samples were 64 analyzed on a Delta V Advantage Mass spectrometer (Thermo) coupled to Costech 4010 Elemental Combustion system and a ConFlo IV gas interface. Precision, assessed by the standard deviation of replicate analyses of four standards (NIST1577c, internal lab standard (tilapia muscle), USGS 40 and Urea, measured ≤ 0.17 ‰ for δ15N and ≤ 0.16 ‰ for δ13C for all the standards. Final δ13C and δ15N isotopic values are expressed relative to the international standards Vienna PeeDee Belemnite (VPDB) and atmospheric nitrogen (AIR), respectively. The acidified filter was used for Particulate organic carbon (POC) concentration and δ13C values, and the unacidified filters were used for Particulate Nitrogen (PN) concentration and δ15N values and C:N molar ratio. Samples from the March 2023 pelagic survey were sent to the stable isotope facility at the University of California Davis. These samples were analyzed on a Elementar Vario EL Cube or Micro Cube elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany) interfaced to either an Isoprime VisION IRMS (Elementar UK Ltd, Cheadle, UK) or a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK). The samples were interspersed with at least four internal reference materials (including IAEA-600, USGS-40, USGS-41, USGS-42, USGS-43, USGS-61, USGS-64, and USGS-6500). The long-term standard deviation is 0.2 ‰ for δ13C and 0.3 ‰ for δ15N. 3.2.3.4 Macrophyte stable isotopes Each macrophyte sample was freeze dried for a minimum of 24 hrs. or until dry and homogenized using a mortar and pestle. The material was stored at -80 ˚C until analysis at the University of Windsor as specified above. 65 3.2.4 Data analysis All statistical analyses and visualizations were completed in R 4.4.1(R Core Team, 2024). We constructed line plots, scatter plots, and bar charts to visualize differences, similarities, and results. 3.2.4.1 Mixing model The relative contributions of organic matter inputs (freshwater, macrophytes, wastewater, and phytoplankton) to the particulate organic matter was quantified using a Bayesian mixing model, specified with the MixSIAR and rjags packages in R (Plummer, 2024; R Core Team, 2024; Stock et al., 2018; Stock & Semmens, 2016b, 2016a). Discrimination was set to 0 for all sources, assuming no trophic transfer within the POM. An uninformative prior was used, giving equal probabilities to all four sources. (i.e., freshwater, macrophytes, effluent, and phytoplankton contribution). Basin was specified as a fixed effect. There are five basins: Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek (Figure 1.1). A separate model was run for three seasons, each with seasonally specific model inputs. Seasons were defined as follows: the wet season from October 1st to February 29th, the wet bloom from March 1st to May 30th, and the dry season from June 1st to September 30th. The seasons were defined using the yearly rainfall (Figure 2.2) and historical phytoplankton bloom dates for the Strait of Georgia (Allen & Wolfe, 2013). There was 8.3 times more rain during the wet season than the dry season and 2.4 times more rain during the wet bloom season than the dry season. The model was fit using residual process error structure estimates (Stock & Semmens, 2016b). 66 3.2.4.2 Model inputs Each model had four organic matter sources: freshwater POM, macrophytes, wastewater POM, and phytoplankton (Table 3.1). Stormwater and river water POM could not be distinguished based on δ13C and δ15N, and they were, therefore, grouped as the freshwater endmember. The freshwater source included samples from 12 rivers within Metro Vancouver (n = 31), 16 stormwater sites (n = 37), monthly samples from the Fraser River (n = 12) at Hope, and samples from the Indian River (n = 3). Freshwater data were not seasonally resolved and were the same for all models (total n = 83) because there was no significant difference in seasonal δ13C or δ15N values (p > 0.05) (ANOVA) The wastewater source data included data from 4 WWTPs, 2 of which were effluent and 4 of which were influent (n = 6). These data were not seasonally resolved and were the same for all models. The macrophyte source was determined using data from 7 species collected from 14 sites around Burrard Inlet (Table B.1). Macrophyte source data were seasonally resolved for the wet (n = 18), wet bloom (n = 13), and dry (n = 65) seasons because there were significant seasonal differences in the δ13C (p < 0.01) and δ15N (p = 0.03) values (ANOVA). To isolate a marine phytoplankton source, marine POC samples (regardless of basin) with a threshold of a POC:CHL g g-1 ratio less than 75 were assumed to be primarily marine phytoplankton (Burt et al., 2018). We seasonally resolved the phytoplankton source data for the wet (n = 10), wet bloom (n = 19), and dry season (n = 3) because there were statistically significant seasonal differences in the C:N (p < 0.01) and δ13C (p < 0.01) values (ANOVA). 67 3.2.4.3 Mix data The “mix data” for which source contributions were estimated by the model included the pelagic and nearshore POM dataset for Burrard Inlet, separated into the three seasons, comprising 30, 43, and 32 discrete measurements for the wet, wet bloom, and dry seasons, respectively. These data were then separated by basin for each season (Table 3.2). Data from the Indian Arm Survey were excluded. There were significant differences in the mix data between basins for δ13C and δ15N values (p < 0.01 for both; ANOVA), and there were significant differences in the mix data between seasons for δ13C, δ15N, and C:N Values (all p < 0.01; ANOVA). 3.2.4.4 Model run, fit, and interpretation The “very long” Markov Chain Monte Carlo setting was run in MixSIAR for the models with 3 chains, each with a run length of 1,000,000, burn-in of 500,000, and a thin of 500. MixSIAR employs two metrics of model convergence: the Geweke Factor and the Gellman-Rubin diagnostic. Both indicated convergence for each model. The deviance information criterion (DIC) was 101.30, 114.40, and 47.38 for the wet, wet bloom, and dry seasons, respectively. Model outputs are described as means and 95 % Bayesian credible intervals. 3.2.4.5 POM biomass calculations POM biomass was calculated by dividing the weight of material on the unacidified filter by the volume filtered. I used these measurements to calculate the mean and standard deviation per basin for each season. The March 2023 samples from the pelagic survey were missing 68 sample specific filter weights, so we used an average weight of 34.81 mg (± 1.04 mg) calculated from 435 filters. 3.3 Results 3.3.1 Average basin environment variables All five basins had similar season cycles of ocean properties, and properties showed similar patterns for intertidal and pelagic samples (Figure 3.2). Average salinity across basins and seasons was 22.53 ppt, and the lowest values across all basins were recorded in May, during the peak Fraser River flow, especially in the Outer Harbor and False Creek. Temperature was highest in summer, between June and August, with the highest values recorded in False Creek (22.6 ˚C) and the lowest values recorded in the Outer Harbor during March (6.0 ˚C). Phosphate and nitrate showed similar seasonal cycles, with peak values in November and lowest values in May, after the spring phytoplankton bloom. In Central Harbor, Port Moody, and False Creek, nitrate levels remained depleted in July. Silicate values had a less pronounced seasonal cycle, only becoming depleted in the Central Harbor and Port Moody in May. A maximum silicate value of 89.21 µmol.L-1 was measured in intertidal False Creek in August. Chlorophyll-a biomass showed different seasonal cycles in the different basins. In the Outer Harbor and False Creek, chl-a peaked between May and August (up 8.39 mg.m-3). Chl-a peaked in May in the Inner Harbor (16.78 mg.m-3), April in the Central Harbor (12.08 mg.m-3), and March in Port Moody (17.89 mg.m-3). Average chl-a values across all basins were highest in April (7.69 mg.m-3) and lowest in February (0.73 mg.m-3). 69 Figure 3.2 Salinity (ppt), temperature (˚C), phosphate (µmol.L-1), silicate (µmol.L-1) nitrate (µmol.L-1), chlorophyll mg.m-3 in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek for intertidal (light blue) and pelagic (dark blue) surveys. The points represent the mean value, and the bars show the standard deviation. In the bottom seasons are shown as shaded areas and defined as follows: the wet 70 season from October 1st and February 29th (blue), the wet bloom from March 1st to May 30th (green), and the dry season from June 1 to September 30th (orange). 3.3.2 Source isotope values Source endmembers were determined to have significantly different values for δ13C-POC (p < 0.001), δ15N-PN (p < 0.001), and C:N ratios (p < 0.001) using ANOVA, supporting their use as endmembers in the mixing model. Mean δ13C-POC was highest and lowest for macrophytes (-15.99 ± 2.57 ‰) and freshwater (-28.12 ± 1.36 ‰), respectively (Figure 3.3). Phytoplankton (-23.32 ± 1.99 ‰) and wastewater (-24.29 ± 0.48 ‰) had similar intermediate mean δ13C-POC values. Mean δ15N-PN was highest for macrophytes (6.82 ± 0.61 ‰) and lowest for wastewater (-1.37 ± 1.32 ‰). Freshwater had a mean δ15N-PN of 2.20 ± 2.04 ‰, while phytoplankton had a higher mean δ15N-PN of 5.55 ± 1.78‰. The C:N ratio was higher and similar for the macrophyte (18.05 ± 8.22) and freshwater (16.33 ± 7.39), while it was similar and lower for the effluent (7.49 ± 2.38) and phytoplankton (7.11. ± 1.74). There were significant seasonal differences (ANOVA; p < 0.05) in phytoplankton δ13C-POC values and C:N ratios, as well as macrophyte δ13C-POC and δ15N-PN values, so seasonally explicit endmembers were used for these sources in the model (Table 3.1). For the freshwater end member, only the C:N ratio differed significantly between seasons (p < 0.05), so I did not use a seasonally explicit endmember in the model. There were no seasonal data for wastewater. For the phytoplankton source data, mean δ13C-POC was highest during the wet bloom season (-22.34 ± 1.80 ‰) and lowest during the wet season (-24.17 ± 1.33 ‰) (Table 3.1). The dry season had an intermediate mean δ13C-POC value of -24.17 ± 1.66 ‰. The mean δ15N-PN was highest, intermediate, and lowest in the wet (6.43 ± 2.20 ‰), wet bloom (5.37 ± 1.70 ‰), 71 and dry (4.61 ± 0.29 ‰) seasons, respectively. The same pattern was true for the C:N molar ratio, with mean values being highest in the wet season (8.41 ± 2.90), lowest in the dry season (5.46 ± 2.37), and intermediate in the wet bloom season (6.90 ± 1.08). Macrophyte source data had lower mean δ13C-POC signatures in the wet (-17.60 ± 1.87 ‰) and wet bloom (-17.91 ± 2.50 ‰) seasons than the dry season (-15.16 ± 2.35 ‰). Macrophyte mean δ15N-PN signatures were higher in the wet season (7.01 ± 0.42 ‰) and lower in the wet bloom (6.44 ± 0.36 ‰) and dry season (6.84 ± 0.67 ‰). The mean C:N molar ratio for macrophytes was similar between seasons, though values showed high variability. Mean C:N molar ratios were lower in the wet season (16.25 ± 5.62 ‰) and wet bloom season (16.82 ± 4.56 ‰), and highest during the dry season (18.80 ± 9.28 ‰). 72 Table 3.1 Mean and standard deviations (SD) for δ13C-POC (‰), δ15N-PN (‰), and C:N molar ratio for the source data used in the mixing model. The freshwater data were seasonally averaged, while the phytoplankton and macrophyte data were seasonally resolved for the wet, wet bloom, and dry seasons. Wastewater data were collected from one time point. Source Season Mean δ13C ± SD (‰) Mean δ15N ± SD (‰) Mean C:N ± SD n Freshwater N/A -28.12 ± 1.36 2.12 ± 2.04 16.33 ± 7.39 83 Wastewater N/A -24.29 ± 0.48 -1.37 ± 1.32 7.49 ± 2.38 6 Phytoplankton Wet -25.18 ± 0.81 6.43 ± 2.20 8.41 ± 2.90 6 Wet Bloom -22.34 ± 1.80 5.37 ± 1.70 6.90 ± 1.08 14 Dry -24.17 ± 1.66 4.61 ± 0.29 5.45 ± 2.37 3 Macrophyte Wet -17.60 ± 1.87 6.84 ± 0.67 16.25 ± 5.62 18 Wet Bloom -17.91 ± 2.50 6.49 ± 0.36 16.82 ± 4.56 13 Dry -15.16 ± 2.35 6.84 ± 0.67 18.80 ± 9.28 65 73 Figure 3.3 Seasonally and spatially averaged values for sources–wastewater (square cross), freshwater (square), phytoplankton (asterix), and macrophyte (diamond)–and POM data for δ13C vs. δ15N (A), δ15N vs. C:N (B), and δ13C vs. C:N (C). POM data are for the Outer Harbor (blue), Inner Harbor (yellow), Central Harbor (dark pink), Port Moody (light pink), and False Creek (orange) basins. POM data are seasonally separated by wet (cross), wet bloom (triangle), and dry (circle) seasons. 3.3.3 Mix data isotope values Across all basins and seasons, the POM data were well bounded by the source endmember values (Figure 3.3). There were significant differences (ANOVA; p < 0.005) in POM δ13C-POC and δ15N-PN values but not C:N molar ratios among basins. Additionally, there 74 were significant differences (ANOVA; p < 0.001) among seasons in the POM δ13C-POC, δ15N-PN, and C:N values. The interaction of season and basin was also significant for all parameters. POC, δ13C-POC, PN, δ15N-PN, C:N ratios, chl-a, and POC:Chl-a values of the mixing data were variable among seasons and basins (Table 3.2). POC concentrations were generally highest during the dry season for most basins, ranging between 56.45 µmol.L⁻¹ in False Creek and 27.39 µmol.L⁻¹ in the Inner Harbor. However, the Inner Harbor had higher median POC concentrations in the wet bloom season (46.21 µmol.L⁻¹). Lower median POC concentrations were generally observed during the wet season, ranging between 10.03 µmol.L⁻¹ in the Inner Basin and 24.44 µmol.L⁻¹ in False Creek. The δ13C-POC values were generally lower during the wet season across all basins, ranging from -26.63 ‰ in the Outer basin to -24.10 ‰ in the Central Harbor. Values tended to be higher during the wet bloom and dry seasons. PN concentrations were generally higher during the wet bloom season (3.52 µmol. L⁻¹ to 6.12 µmol.L⁻¹), except in the Central Harbor (7.49 µmol.L⁻¹) and False Creek (8.49 µmol.L⁻¹), where values were higher in the dry season. Median PN concentrations tended to be lower during the wet season, ranging from 1.10 µmol.L⁻¹ in the Inner Harbor to 3.69 µmol.L⁻¹ in False Creek. Across all seasons, the PN median concentrations were highest in the Central Harbor and False Creek. Median δ15N-PN values were highest in Port Moody during the wet season (6.88‰) and the dry season (6.83 ‰). Median δ15N-PN values were lowest in False Creek during the wet season (3.68 ‰) and wet bloom season (4.14 ‰). Median C:N molar ratios ranged from 5.97 mol.mol-1 in the Inner Harbor during the wet bloom season to 10.88 mol.mol-1 during the wet season in the False Creek. There were no strong seasonal or spatial trends. Median chlorophyll-a concentrations were higher during the wet bloom and dry seasons (1.60 - 4.25 mg.m-3) than in the wet season, though Port Moody had 75 relatively high values during the wet season (2.84 mg.m-3). The median POC:chl-a ratios tended to be higher during the wet season, ranging between 248.65 g.g-1 in False Creek and 77.32 g.g-1 in Port Moody. Median POC: chl-a values during the wet bloom season ranged between 165.68 g.g-1 in False Creek to 117.42 g.g-1 in the Central Harbor. Similarly, median POC: chl-a values during the dry season ranged between 119.90 g.g-1 in the Central Harbor to 171.10 g.g-1 in the False Creek. There were not strong spatial trends for median POC: chl-a ratios. 76 Table 3.2 Median [interquartile range] for particulate organic carbon (POC; µmol.L-1), δ13C-POC (‰), particulate nitrogen (PN; µmol.L-1), δ15N-PN (‰), C:N (mol.mol-1), Chlorophyll-a (chl-a; mg.m-3), POC: chl-a (g.g-1) in each basin for each season. These data were the inputs in each model. Basin Season n POC (µmol.L-1) δ13C- POC (‰) PN (µmol.L-1) δ15N-PN (‰) C:N (mol.mol-1) Chl-a (mg.m-3) POC : Chl-a (g.g-1) Outer Harbor Wet 11 10.91 [3.29] -26.63 [2.37] 1.36 [0.70] 6.52 [0.87] 9.20 [1.18] 0.81 [0.40] 183.40 [68.78] Wet Bloom 17 27.89 [17.99] -23.74 [3.41] 4.95 [4.27] 4.02 [0.87] 6.60 [1.39] 1.60 [1.95] 136.69 [120.11] Dry 9 28.14 [7.31] -24.21 [1.27] 4.24 [0.94] 5.24 [0.68] 9.20 [1.18] 2.35 [1.61] 179.73[160.07] Inner Harbor Wet 8 10.03 [3.48] -26.04 [1.19] 1.10 [0.14] 5.16 [1.68] 9.57 [1.83] 0.67 [0.89] 129.45 [190.87] Wet Bloom 7 46.21 [34.87] -21.51 [2.61] 5.67 [5.20] 4.79 [0.73] 5.97 [1.83] 4.67[5.78] 122.46 [39.25] Dry 7 27.39 [10.24] -23.80 [0.47] 3.75 [1.85] 5.32 [0.99] 6.77 [0.52] 3.14 [2.69] 119.90 [70.24] Central Harbor Wet 5 18.23 6.24] -24.10 [0.88] 2.01 [0.71] 6.26 [1.09] 9.33 [1.81] 1.22 [0.50] 144.24 [40.09] Wet Bloom 37.47 [13.11] -21.33 [0.23] 5.14 [2.02] 5.91 [0.97] 7.48 [1.89] 4.25 [3.60] 117.42 [65.05] Dry 5 51.54 [6.74] -22.26 [2.08] 7.49 [2.30] 6.19 [0.96] 7.33 [2.72] 3.99 [1.19] 155.27 [39.40] Port Moody Wet 3 23.48 [10.91] -25.74 [0.61] 3.55 [1.16] 6.88 [0.98] 9.06 [0.71] 2.84 [1.10] 77.32 [27.70] Wet Bloom 8 37.43 [5.81] -21.47 [0.89] 6.12 [1.13] 5.38 [0.60] 7.96 [1.25] 3.74 [2.85] 110.40 [54.24] Dry 7 42.46 [10.82] -22.43 [2.15] 6.03 [1.96] 6.83 [0.75] 7.10 [0.23] 1.98 [1.17] 212.20 [108.47] Wet 4 24.44 [14.04] -25.62 [1.98] 3.69 [0.77] 3.68 [0.97] 10.88 [3.19] 2.11 [1.84] 248.65 [145.05] 77 False Creek Wet Bloom 8 25.48 [10.89] -23.62 [1.51] 3.52 [1.99] 4.14 [1.41] 7.15 [0.75] 1.65 [1.03] 165.68 [72.71] Dry 5 56.45 [25.90] -23.60 [1.22] 8.49 [2.32] 5.02 [0.63] 6.75 [0.60] 3.96 [2.51] 171.10 [9.61] 78 3.3.4 Relative contributions of sources to POM Phytoplankton contributed the most to POM across all basins and seasons (average = 80 %) (Figure 3.4). In the wet season, combined freshwater and wastewater contributed almost equally to phytoplankton (46 % wastewater and freshwater compared to 48% for phytoplankton) in False Creek. Macrophytes were the second largest contributor to POM (average = 7.9 %), followed by wastewater (average = 6.1 %), and freshwater (average = 5.8 %). Across all basins, the highest mean estimated relative contribution of phytoplankton materials to POM was in the wet bloom season (81-91 %), freshwater materials in the wet season (6.3-20 %), and macrophytes in the dry season (11-26 %). Macrophyte contributions were highest in the Central Harbor and Port Moody (≥ 20 %). Wastewater contributed > 1-26 % to POM across all basins and was always highest for False Creek. There was higher wastewater contribution during the wet and wet bloom seasons than the dry season. 79 Figure 3.4 Relative contributions of wastewater (red), freshwater (light blue), macrophyte (purple) and phytoplankton (green) to the surface (0-1 m) particulate organic matter (POM) pool in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek basins in Burrard Inlet during the wet, wet bloom, and dry seasons. Mean values for all contributions exceeding 7 % rounded to 2 decimal places. Mean Bayesian credible intervals are shown and 95 % credible intervals are presented in Table B.2. 3.3.5 Composition of POM biomass There were no significant differences in POM biomass among basins within each season, however, there were significant differences in average biomass between seasons across basins (ANOVA; p < 0.05). POM biomass was lowest in all basins during the wet season, with a mean 80 of 3138.42 mg.m-3, with a minimum of 2052 mg.m-3 in False Creek and a maximum of 4723.14 mg.m-3 in Port Moody (Figure 3.5). Mean POM biomass during the wet bloom season was 5443.13 mg.m-3, with a maximum value in the Central Harbor (6263.07 mg.m-3) and a minimum value in False Creek (3811.03 mg.m-3). POM biomass was highest during the dry season with a mean of 5919.64 mg.m-3 and a maximum value in False Creek (8628.12 mg.m-3) and a minimum value in the Inner Harbor (4437.06 mg.m-3). Phytoplankton biomass contributed the most to POM biomass across all basins and seasons (mean = 4833.73 mg.m-3). The POM biomass in False Creek in the wet season had much higher contribution from freshwater (841.99 mg.m-3) and wastewater (1104.32 mg.m-3) than other basins which when combined (1942.31 mg.m-3) compared to the phytoplankton contribution (2051.08 mg.m-3) (Figure 3.5; Table B.3). In the wet season freshwater was the second largest contributor to POM biomass (average = 510.67 mg.m-3), while in the dry season macrophytes were the second largest contributor (average = 1275.88 mg.m-3). During the wet bloom season, the contribution of freshwater, macrophyte, and wastewater biomass was similar and much lower than phytoplankton, with contributions ranging from 113.20 mg.m-3 to 585.96 mg.m-3. The biomass contribution of wastewater was consistent among basins and seasons. The minimum contribution of wastewater biomass was in the dry season in the Inner Harbor, 47.20 mg.m-3, while the maximum was in False Creek during the wet season, 1104.32 mg.m-3. 81 Figure 3.5 Mean contributions of wastewater (red), freshwater (light blue), macrophyte (purple) and phytoplankton (green) to the average surface (0-1 m) total particulate organic matter biomass (POM; mg.m-3) in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek in Burrard Inlet during the wet, wet bloom, and dry seasons. Mean values are presented on the bar for each component. Standard deviations are in Table B.2. 3.4 Discussion Using Burrard Inlet and Metro Vancouver as a case study of urbanization, this study found seasonal and spatial variations in the contribution of OM from urban freshwater, marine macrophytes, marine phytoplankton, and wastewater to the POM of surface coastal waters. My results showed that while phytoplankton was the main contributor to the surface POM pool, 82 contributing on average 80.2% to surface marine POM biomass, while freshwater (combined rivers and stormwater inputs) and wastewater contributed 5.8 % and 6.1 %, respectively. Freshwater and wastewater contributions reached a maximum of 20 % and 26 %, respectively, demonstrating urban derived OM can make a sizable contribution to the surface POM pool. Below, I discuss possible physical, chemical, and biological explanations for observed seasonal and spatial differences in freshwater, macrophyte, marine phytoplankton, and wastewater contributions. Finally, I discuss the implications and limitations of the model and then suggest future work. 3.4.1 Temporal and spatial variability in the contribution of OM sources to POM During all seasons and across all basins, phytoplankton contributed the most to surface POM biomass. There was a higher relative contribution of phytoplankton during the wet bloom season when the spring phytoplankton bloom occurred, though phytoplankton contribution was high across all seasons. Notably, the wet season contribution of phytoplankton was higher than observed in a similar study on the central coast of British Columbia, where freshwater contributed > 50% to wet season POM biomass (St. Pierre et al., 2022). Two factors likely contributed to this difference. First, the central coast receives almost three times the precipitation of Burrard Inlet, so the terrestrial material flux is expected to be greater (Environment and Climate Change Canada, n.d.a; St. Pierre et al., 2022). Secondly, Burrard Inlet is shallower compared to other fjord systems (Thomson, 1981), which reduces winter mixing of phytoplankton out of the photic zone, enabling higher winter time primary production. For example, Port Moody, which has a mean depth of 10 m, has been observed to be productive year-round (Tsleil-Waututh Nation, 2017) , and I measured median chl-a values of 2.84 mg.m-3 83 during the winter wet season compared to 0.14 - 1.49 mg.m-3 on the central coast (St. Pierre et al., 2022). The highest contribution of freshwater biomass to the OM pool occurred in the wet season, indicating that rainfall driven discharge was driving freshwater OM contributions. Small-pluvial watersheds are estimated to be responsible for 56 % of the terrestrial DOC transported to the coastal ocean in the North Pacific coastal temperate rainforest (McNicol et al., 2023), and rainfall events are associated with a high flux of material to the ocean (Johannessen et al., 2017; St. Pierre et al., 2020). Notably, the highest contribution of freshwater biomass to the OM pool occurred in False Creek and the Inner Harbor. Although I was unable to separate stormwater from riverine POM using carbon and nitrogen isotopes, the terrestrial environments of these two basins had the highest percentage of impervious surfaces (Metro Vancouver, 2024a) and a high number of stormwater outflows (Rao, 2022), and stormwater was, therefore, likely the dominant source of freshwater OM. The other major freshwater source for Burrard Inlet is the Fraser River freshet, which occurred between May and June, at the end of the wet bloom season and the beginning of the dry season. However, the freshwater OM contribution was twice as high in the wet season. It is possible that OM from Fraser River freshet sediments out of the water column before reaching Burrard Inlet (Johannessen et al., 2005). Though detectable during all seasons, macrophyte contributions were highest during the dry season. This corresponds with the macrophyte growth season when biomass is highest (Froese et al., 2019; St. Pierre et al., 2022). A previous study on the BC coast also found the summer period to be the period of the highest macrophyte detritus contribution to surface POM (Ramshaw et al., 2017). Macrophyte contributions were highest in Central Harbor and Port Moody basins, where eelgrass and kelp beds have been reported (SeaChange Marine 84 Conservation Society, n.d.; Tseil-Waututh Nation, 2021). The macrophyte source data included 7 kelp samples (Table B.1), however, these were collected on shore from washed-up kelp rather than living specimens. Though I was unable to sample the eelgrass and kelp beds directly, stable isotope values for these species are in line with the macrophytes sampled in this study (Froese et al., 2019; St. Pierre et al., 2022), and the mixing model likely captured their contribution. The highest percentage of wastewater contribution in Burrard Inlet was measured in False Creek during the wet and wet bloom seasons. The wastewater biomass was highest in the wet season (1104.32 mg.m3) and second highest in the wet bloom season (558.51 mg.m3) in False Creek. This was unsurprising as this relatively small basin has four CSOs (Tsleil-Waututh Nation, n.d.), reflected by high levels of E. coli (Rao, 2022). Further, False Creek has reduced connection to the Strait of Georgia (SOG) and likely slower dilution (Thomson, 1981; Wu et al., 2019). The Outer Harbor had the second highest wastewater contribution during the wet bloom season. The Central and Inner Harbors had higher wastewater contributions also during the wet bloom season. The Outer Harbor has five CSOs, the Central Harbor has two CSOs, and the Inner Harbor has nine CSOs and one Sanitary Sewer overflow outfall (Tsleil-Waututh Nation, n.d.). The frequency and volume of material released by these points of entry into the marine environment are unknown. Though the majority of CSO discharge occurs during the wet season, a non-negligible volume of dry weather overflows happen each year (Metro Vancouver, 2022), which may help to explain the contribution of wastewater to surface POM during the dry season. Lionsgate is the only WWTP that discharges directly into Burrard Inlet at First Narrows (the narrowest point between the Outer and Inner Harbors). The discharge point is below 60 m depth and is thought to quickly mix and disperse due to strong tides (Li & Hodgins, 2010; Wu et al., 2019), which may be one factor explaining the low contribution of wastewater OM to surface 85 POM. In the SOG, the estimated annual POC flux from wastewater is 350 times less than that of phytoplankton production (Johannessen et al., 2015), therefore, a high contribution of wastewater OM to surface POM is not expected. Further, a study on the Iona outfall (located 7 km from land into the SOG, at a depth between 70 to 105 m in the plume of the Fraser River; Liquid Waste Services, 2019) found that effluent did not contribute significant organic material to the water column, but was detectable in the sediments of the immediate receiving environment (Johannessen et al., 2015). Another factor contributing to the lower percentage of wastewater in surface POM may be wastewater OM’s high lability (Ianson & Allen, 2002; Krogh et al., 2018) and, therefore, undergoing rapid processing and modification in the environment (Back et al., 2021). Wastewater OM has been shown to increase bacterial growth efficiency and production (Vaquer-Sunyer et al., 2016) (Solagaistua et al., 2018). Wastewater OM can also be taken up directly by suspension feeders and transferred to higher trophic levels (Gaston & Suthers, 2004; J. Tucker et al., 1999). Overall, wastewater contributed ≤ 26 % throughout the year across all basins. This was slightly lower than estimates for Venice Lagoon, Italy (mean ~32 %) (Berto et al., 2013), but higher than estimates for the Bay of Biscay, France (~ 10 %) (Liénart et al., 2016). The lower values of the Bay of Biscay are likely a result of physical differences between the two regions: the Bay of Biscay is a large gulf off the coast of Western Europe open to the Atlantic, while Venice Lagoon is a closed lagoon surrounded by agriculture and industry. These differences are similar to those between False Creek, which exchanges less water (mean = 13 %) than the Outer Harbor (mean = 4.7 %) with the SOG, indicating the importance of water exchange in the dilution of effluent OM. 86 3.4.2 Missing sources and model refinements There are a few other potential sources of POM that were not explicitly accounted for in the mixing model, such as heterotrophic bacteria or microzooplankton. Bacteria may be abundant in the coastal environment because of terrestrial inputs (Liénart et al., 2020a) , especially in an urban environment where sewage inputs and bacteria abundance are correlated (Rabelo et al., 2024; Sbrilli et al., 1997). The contribution of heterotrophic bacteria to POM biomass is difficult to isolate as their isotopic signature reflects their substrate (Liénart et al., 2020a), and bacteria are known to utilize wastewater organic matter (Vaquer-Sunyer et al., 2016). Like bacteria, nano (20-20µm) and microzooplankton (20 – 200µm) are difficult to sample due to their size and difficult to separate in isospace as they consume bacteria and phytoplankton but may contribute to POM (Aytan et al., 2018; Redalje et al., 1994). Nano and microzooplankton may alter the POM pool due to preferentially utilizing N-rich compounds, lowering the C:N ratio of the POM (Talmy et al., 2016). Approaches such as fatty acid or compound-specific stable isotope analysis (CSIA) could improve understanding of the contribution of heterotrophic bacteria, nano and microzooplankton to the POM. Solely using δ13C, δ15N, and C:N ratios did not allow for the separation of urban organic material sources. I was unable to separate river and stormwater organic material as only their C:N ratios were significantly different. Further, I did not have the statistical power to evaluate the differences between wastewater influent and effluent, though the data indicated that their respective δ13C, δ15N, and C:N values were similar when visually evaluated. A larger dataset could help resolve these differences and improve our understanding of the transport and fate of urban organic material in the urban environment. Future work should consider additional 87 analyses such as CSIA and additional isotopes (sulfur, hydrogen, oxygen) to distinguish between sources in the highly complex matrix that is the “urban ocean”. I recognize that the mixing model would benefit from higher spatial and seasonal resolution. In particular, phytoplankton and macrophyte isotopic signatures can vary in space and time; thus, having higher resolution seasonal and spatial source data would improve the model. The `mix data` would benefit from higher seasonal coverage and give more seasonally specific model results that could improve our understanding of basal resource seasonality in Burrard Inlet. Many more samples would be needed to build a model with this spatial and temporal resolution. 3.4.3 Fate of material in the marine environment POM in Burrard Inlet is subjected to the same fate as POM in all coastal waters: sinking or biological uptake. Due to the increased lability of urban derived organic matter (either in wastewater or in urban freshwater), biological uptake may have increased efficiency (Parr et al., 2015; Smith et al., 2021; Vaquer-Sunyer et al., 2016). These bioavailable urban inputs may be quickly utilized by heterotrophic bacteria or nano zooplankton and made available to the rest of the marine food web (Haggarty, 2001). If urban organic material resembles young riverine organic material, it may be more readily incorporated into the marine food web than other types of terrestrial organic material (Arimitsu et al., 2018). Across coastal temperate rainforests, terrestrially derived material can be traced through marine food webs to higher trophic levels (Arimitsu et al., 2018; Conway-Cranos et al., 2015; Vargas et al., 2018). It is unknown how urban derived organic material will affect the food web processes. 88 Though the effects of urbanization on burial efficiency in this region have not been studied, burial efficiency of carbon is considered high in the North Pacific Coastal Temperate Rainforest, especially within fjords (Hage et al., 2020, 2022; Johannessen et al., 2003). Terrestrial contributions to sediments in fjords tend to scale with distance from river mouth (Nuwer & Keil, 2005; Walsh et al., 2008), but it is unknown how diffused freshwater inputs, like urban runoff, affect sedimentation. Future studies should examine sedimentation rates in Burrard Inlet, especially near stormwater and CSO outfalls, as associated material flux may affect benthic and intertidal communities (Kinsella & Crowe, 2015; Schiff & Bay, 2003). Additionally, studying sedimentation rates helps to understand the fate of urban derived materials and contributes to biogeochemical budgets. 3.4.4 Future directions for research on urban impacts on marine OM By altering the terrestrial hydrology, urban environments disrupt the land-sea connection, which impacts marine processes at the coastal margin. From this research, I identify three key areas necessitating further research to enhance our understanding of an urbanized land-sea connection. First, the lability of urban derived OM in the marine environment and what organisms can utilize this material needs to be determined. Second, better tracers to separate urban derived organic matter are required; options include fatty acids, compound-specific stable isotopes, or additional isotope signatures such as hydrogen, sulfur, or oxygen. Finally, a better understanding of stormwater and its organic matter load is necessary; in Chapter 2, I estimated that 0.226 km3 of stormwater enters Burrard Inlet each year and quantified material flux, but refining these estimates would improve our understanding of the magnitude of OM contribution from stormwater. In comparison, 5 WWTPs discharged 0.428 km3 and 15 CSOs discharged 89 0.018 km3 of freshwater in 2023 (Metro Vancouver Liquid Waste Services Environmental Management and Quality Control, 2024), but few OM measurements have been made, and thus there are only approximations of OM flux. Improving our understanding of OM flux from anthropogenic sources is particularly important as these inputs may compare to those of pluvial watersheds common to coastal temperate rainforests, delivering tremendous amounts of material annually (Hunt et al., 2024). Finally, the results of this study indicate that phytoplankton are still the main contributor to marine surface POM pools. As such, it is critical to study how anthropogenic pressures and urban inputs change phytoplankton communities and nutrition. Studies have indicated that stormwater (Corcoran et al., 2010; Varkey et al., 2018) and wastewater (Gierach et al., 2017; Reifel et al., 2013; Vaquer-Sunyer et al., 2016) can alter the species composition and phytoplankton production. Zooplankton, and therefore their predators, depend on phytoplankton for survival (Brett et al., 2009; McLaskey et al., 2024), thus, future studies need to understand how terrestrial and marine urbanization affects phytoplankton in coastal environments. 3.5 Conclusion In the urbanized marine environment of Burrard Inlet, the surface POM was primarily composed of phytoplankton derived OM with smaller contributions from freshwater, wastewater, and macrophytes OM. Generally, among all seasons and basins, phytoplankton was the main source of POM, indicating that despite urbanization, Burrard Inlet remains a productive marine environment. Freshwater and wastewater contributions to the surface POM pool indicate that urbanization has the potential to disrupt surface POM pools. Contributions of freshwater and wastewater OM were highest during the wet season, most likely originating from CSOs and 90 stormwater runoff as contributions were higher in basins with greater terrestrial imperviousness and higher CSO outfalls. Climate predictions suggest that there will be an increase in total precipitation (Bidlack et al., 2021) and that Metro Vancouver will continue to expand (Metro Vancouver Growth Projections, 2024), suggesting that the role of these urban derived inputs in disrupting marine ecosystems will increase in the future without our intervention. 91 Chapter 4: Conclusion 4.1 The urban ocean Processes of urbanization have altered the land-sea interface, thereby creating a novel ecosystem: the urban ocean. Urbanization alters coastal environments in a myriad of ways (Airoldi et al., 2021; Todd et al., 2019), the impacts of which are understudied. Thus, there remain many outstanding research questions and knowledge gaps in our understanding of the processes disrupted by urbanization at the land-sea interface. A concerted research agenda is needed to address the many ecological questions in this novel environment; however, first, it is critical to understand changes that alter organic matter (OM) as changes in its composition have repercussions for the entire marine ecosystem. To date, there have been few studies investigating these urban disrupted biogeochemical cycles in coastal environments. Despite urbanization and human activity having been identified as disruptors of land-sea connection (Hunt et al., 2024; Xenopoulos et al., 2017), stormwater and urban impacted rivers have rarely been studied as sources of resources for marine food webs. Further, upon reaching the marine system, the fate of this material is poorly understood because of the need to identify tracers of urban derived OM from stormwater and rivers. In urban marine systems, quantifying the composition of marine particulate organic matter (POM) improves our understanding of the resources and energy available to the marine food web and, thus, ecosystem productivity and functioning. This study is an initial step to understanding how urbanization alters land-sea connections, contributing to a broader comprehension of the urban ocean: an expanding global ecosystem. 92 4.2 Biogeochemical properties of river and stormwater in the urban environment The focus of Chapter 2 was to characterize marine relevant biogeochemical parameters in stormwater and urban influenced rivers, estimate stormwater material flux to the coastal ocean, and identify tracers of urban derived OM in Metro Vancouver, British Columbia. In this chapter, I estimated the concentration of dissolved organic carbon (DOC), total dissolved nitrogen (TDN), particulate organic carbon (POC), particulate nitrogen (PN), fatty acids (FAs), nitrate, silicate, and phosphate in stormwater and urban impacted freshwaters. I found that average concentrations of these biogeochemical parameters were generally higher in stormwater than urban rivers, with the exception of DOC. I estimated an annual stormwater flux of 0.226 km3 and 1.07 km3 from impervious surfaces in the Burrard Inlet catchment basin and the total area of Metro Vancouver, respectively. With this freshwater flux, I identified that stormwater has the potential to transport large amounts of marine relevant nutrients and organic matter to the coastal ocean. Finally, I found that a combined tracer approach of carbon and nitrogen stable isotopes and FAs was able to distinguish OM from stormwater, rivers, and wastewater and, therefore, hold promise for tracing this material’s passage through marine systems. This chapter highlighted the importance of considering stormwater as an important source of materials to coastal oceans in urban environments. 4.3 Urban marine particulate organic matter composition The aim of Chapter 3 was to quantify the contribution of freshwater, wastewater, macrophytes, and phytoplankton derived OM to surface POM pool among basins and seasons in Burrard Inlet. Throughout all seasons and basins, phytoplankton was the highest contributor to POM biomass (average = 80 %). Macrophytes were the second highest contributor (average = 93 7.9 %), followed by wastewater (average = 6.1 %), and finally freshwater (average = 5.8%). Source contributions to OM differed among seasons and basins. There was higher phytoplankton contribution in the wet bloom season (spring), higher macrophyte contributions in the dry season (summer), and higher freshwater contributions in the wet season (winter). Across all seasons, False Creek had higher wastewater and freshwater contributions. The results of this study suggest that both the seasonality of primary production and the surrounding urban infrastructure may affect POM composition. Finally, this study highlighted the need for research on the fate of OM in urban marine environments and its effect on food web processes (e.g., heterotrophic production) in urban marine environments. 4.4 Implications in a changing climate In conjunction with urbanization, climate change will alter the delivery of freshwater and the material it transports to the marine environment. Climate modeling suggests that rainfall will become less frequent, with higher volumes during extreme events (Bidlack et al., 2021). In B.C., climate change is estimated to increase precipitation by 10 % in the next 20 to 50 years (Morrison et al., 2014). Thus, without management, stormwater discharge from urban environments will increase. Runoff in Metro Vancouver is expected to increase by 51 % by 2050 from 2015 (Hamilton et al., 2021). There is work underway to address this problem; City of Vancouver has set the goal of capturing 90 % of annual rainfall using green infrastructure (Conger et al., 2019). However, the introduction of green stormwater infrastructure needs to explicitly consider pre-urbanized land-sea regimes and understand that the structure and function of coastal marine environments are dependent on freshwater and terrestrial inputs. Globally, stormwater should be given more consideration, especially as climate regimes change and 94 intensify, as stormwater can transport high loads of OM, nutrients, and contaminants to coastal oceans over a short time scale. 4.5 Implications for expanding cities As cities expand (Barragán & De Andrés, 2015), so does the disruption of freshwater movement from land to sea. An estimated 40 % of the world’s population lives within 100 km of the coast (United Nations, 2017). Coastal cities experience disproportionate growth (Barragán & De Andrés, 2015), resulting in continued land-use change to the surrounding terrestrial environment. In Metro Vancouver, the population (Metro Vancouver Growth Projections, 2024) and the area of impervious surfaces (Hamilton et al., 2021) are expected to continue increasing. Growing urbanization increases the volume of stormwater and wastewater discharge while decreasing vegetation coverage. Thus, in Metro Vancouver and globally, the impact on coastal ecosystems will increase unless cities adopt management strategies for healthy coastal oceans. This includes plans for managing stormwater and wastewater, protecting rivers, increasing urban vegetation, supporting soil functionality, and reducing pollution (Todd et al., 2019). 4.6 Future directions Like any successful scientific endeavor, this research has produced more questions than it has answered. Multi-disciplinary approaches with the involvement of multiple stakeholders are needed to address many of these questions and create solutions to challenges arising from expanding cities during a climate crisis. From the results of Chapter 2, future studies should make additional measurements of marine relevant biogeochemical parameters such as micronutrients, δ13C-DOC, δ15N-TDN, 95 microbial assays, and OM lability. These measurements could be useful for a greater understanding of the sources, fate, and impact of urban derived OM on the marine environment. Measurements should be made in a variety of urban influenced freshwater sources, including rivers, CSOs, stormwater outfalls, and industrial runoff. Additionally, better estimates of stormwater and local river discharge and material flux are needed for Metro Vancouver with a reproducible methodology in order to improve our understanding of the quantity and fate of this material entering the marine environment. Finally, additional tracers should be investigated to distinguish urban OM sources in complex urban matrixes. Possible options to explore include compound-specific isotope analysis (CSIA) and additional stable isotopes (hydrogen, oxygen, sulfur). Globally, these measurements and flux estimates should be made in and built for a diverse range of coastal urban environments in different bioregions to build a global estimate and understanding of how urban environments are changing biogeochemical cycles. The estimates of POM composition in Chapter 3 reveal the need for further studies on how urban environments alter phytoplankton community composition and production in this region and globally because this study found that POM in an urban marine environment is primarily composed of phytoplankton. Additionally, further studies are needed to understand the fate of POM via uptake and sinking to understand whether the urban environment alters biogeochemical cycling or food web connectivity. Finally, with the identification of tracers with improved source delineation, future studies should investigate how stormwater versus river OM contributes to marine POM pools and if their fate in marine ecosystems is similar. 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Trends in Food Science & Technology, 152, 104676. https://doi.org/10.1016/j.tifs.2024.104676 133 134 Appendices Appendix A Table A.1 The latitude (˚), longitude (˚), zoning, and traffic volume of stormwater collection sites. Zoning information retrieved from (City of Vancouver, 2023) and traffic volume qualitatively assessed from (City of Vancouver, 2024). (*) These sites are zoned by the Province of B.C. and were reclassified to match the City of Vancouver (Campus and Community Planning, 2023; University Endowment Lands Act, 1996). Site Latitude (˚) Longitude (˚) Zoning Traffic Volume VSW01 49.258362 -123.21442 Residential Medium VSW02 49.25774 -123.18079 Residential Medium VSW03 49.246117 -123.1797 Residential Light VSW04 49.256951 -123.13896 Commercial / Residential / Comprehensive Development Heavy VSW05 49.261159 -123.11486 Commercial / Comprehensive Development Heavy VSW06 49.264899 -123.12185 Residential Medium VSW07 49.271368 -123.20909 Residential Light VSW08 49.26575 -123.24928 Commercial* Medium VSW09 49.274297 -123.24239 Residential* Light VSW10 49.269929 -123.15298 Residential Light VSW11 49.267925 -123.14576 Commercial Heavy VSW12 49.277696 -123.13522 Residential Medium VSW13 49.290207 -123.13559 Commercial Heavy VSW14 49.280056 -123.11451 Comprehensive Development Heavy VSW15 49.275031 -123.10153 Comprehensive Development Medium VSW16 49.267408 -123.11342 Industrial / Commercial / Comprehensive Development Heavy 135 Figure A.1 Map of Environmental weather station (`Vancouver Harbor CS`), river discharge sites (Seymour, McKay, and Capilano Rivers), and sampled Metro Vancouver wastewater treatment plants (WWTP). 136 Table A.2 Number samples taken per sample date of silicate (𝐒𝐢(𝐎𝐇)𝟒), phosphate, (𝐏𝐎𝟒𝟑#), nitrate (𝐍𝐎𝟑#), dissolved organic carbon (DOC), total nitrogen (TDN), particulate organic carbon (POC), particulate nitrogen (PN), carbon and nitrogen stable isotopes (δ13C & δ15N), carbon to nitrogen ratio (C:N), and Fatty Acids (FA). The total number of measurements made in river, stormwater, and wastewater shown. (𝐍𝐎𝟑$) 𝐒𝐢(𝐎𝐇)𝟒 𝐏𝐎𝟒𝟑$ DOC TDN POC PN δ13C & δ15N C:N FAs River 2023-04-17 2 2 2 2 2 2 2 2 2 2 2023-04-21 2 2 2 2 2 2 2 2 2 2 2023-06-13 4 4 4 4 4 4 4 4 4 4 2023-06-15 4 4 4 4 4 4 4 4 4 4 2023-06-16 2 2 2 2 2 2 2 2 2 2 2023-06-27 1 1 1 1 1 1 1 1 1 1 2023-08-29 5 5 5 ND 5 5 5 5 5 ND 2023-08-30 4 4 4 ND 4 4 4 4 4 ND 2023-08-31 1 1 1 ND 1 1 1 1 1 ND 2023-09-26 1 1 1 1 1 1 1 1 1 ND 2023-12-05 2 2 2 2 2 2 2 2 2 ND 2023-12-06 4 4 4 4 4 4 4 4 4 ND 2023-12-07 4 4 4 4 4 4 4 4 4 ND 2023-12-20 1 1 1 1 1 1 1 1 1 ND Total 37 37 37 27 37 37 37 37 37 15 Stormwater 2023-09-25 7 7 7 6 6 7 7 7 7 ND 2023-10-10 4 4 4 4 4 4 4 4 4 ND 2023-10-18 6 6 6 6 6 6 6 6 6 6 2023-12-01 3 3 3 3 3 3 3 3 3 ND 2023-12-04 1 1 1 1 1 1 1 1 1 ND 2023-12-07 2 2 2 2 2 2 2 2 2 ND 2024-02-28 4 4 4 4 4 4 4 4 4 2 2024-03-01 4 4 4 4 4 4 4 4 4 1 Total 31 31 31 31 31 31 31 31 31 9 Wastewater influent 2024-09-19 ND ND ND ND ND 4 4 4 4 5 Wastewater effluent 2024-09-19 ND ND ND ND ND 2 2 2 2 5 All wastewater ND ND ND ND ND 6 6 6 6 10 137 Figure A.2 Map of the percent (%) impervious surface within Metro Vancouver Administrative Boundary (red) and Burrard Inlet Catchment Area (yellow). Impervious surface data from Metro Vancouver (2024a) and Burrard Inlet Catchment area from Tsleil-Waututh Nation (2017). 138 Table A.3 Concentrations of materials measured in stormwater and river samples. Mean, median, minimum, maximum, standard deviation (SD) and sample number (n) are given for silicate (𝐒𝐢(𝐎𝐇)𝟒), phosphate, (𝐏𝐎𝟒𝟑#) (µmol L-1), nitrate (𝐍𝐎𝟑#) (µmol L-1), dissolved organic carbon (DOC) (mg L-1), total nitrogen (TDN) (mg L-1), particulate organic carbo (POC) (mg L-1), particulate nitrogen (PN) (mg L-1). An independent two-sample t-test was performed between river and stormwater on each measurement type. P-values reported as significant (*) if p-value <0.05. Measurement River Stormwater T-test P-value Mean Median Min Max SD n Mean Median Min Max SD n 𝐒𝐢(𝐎𝐇)𝟒 (µmol L-1) 114.98 39.88 2.43 696.71 168.91 37 8.88 4.76 0.54 52.69 12.29 31 <0.001* 𝐏𝐎𝟒𝟑$ (µmol L-1) 0.40 0.12 0.01 4.05 0.70 37 1.36 0.47 0.10 13.00 2.53 31 0.048* 𝐍𝐎𝟑$ (µmol L-1) 38.52 35.38 3.5 134.19 31.95 37 8.81 7.03 0.5 27.15 6.46 31 <0.001* DOC (mg L-1) 4.57 3.17 0.83 15.58 4.37 27 10.26 5.80 0.57 67.81 13.55 30 0.036* TDN (mg L-1) 3.43 1.96 0.46 18.51 3.94 37 2.41 1.90 0.19 8.00 1.71 30 0.164 POC (mg L-1) 0.97 0.26 0.08 20.77 3.37 37 15.92 7.73 0.67 106.11 21.46 31 <0.001* PN (mg L-1) 0.06 0.02 0.01 0.32 0.08 37 0.81 0.54 0.09 3.49 0.84 31 <0.001* 139 Table A.4 Median, interquartile range [IQR], minimum, and maximum concentrations measured in river locations and stormwater are given for silicate (𝐒𝐢(𝐎𝐇)𝟒), phosphate, (𝐏𝐎𝟒𝟑#) (µmol L-1), nitrate (𝐍𝐎𝟑#) (µmol L-1), dissolved organic carbon (DOC) (mg L-1), total nitrogen (TDN) (mg L-1), particulate organic carbon (POC) (mg L-1), particulate nitrogen (PN) (mg L-1). Location 𝐒𝐢(𝐎𝐇)𝟒 (µmol L-1) 𝐏𝐎𝟒𝟑# (µmol L-1) 𝐍𝐎𝟑# (µmol L-1) DOC (mg L-1) TDN (mg L-1) POC (mg L-1) PN (mg L-1) Median [ IQR] Min Max Median [ IQR] Min Max Median [ IQR] Min Max Median [ IQR] Min Max Median [ IQR] Min Max Median [ IQR] Min Max Median [ IQR] Min Max Brunette River 111.62 [44.90] 35.14 124.93 0.32 [0.16] 0.13 0.45 52.17 [27.30] 24.56 79.16 3.57 [2.36] 1.17 5.88 1.81 [8.42] 1.66 18.51 0.72 [0.44] 0.52 1.39 0.11 [0.08] 0.07 0.23 Coquitlam River 11.49 [17.49] 4.29 39.27 0.03 [0.03] 0.02 0.08 6.29 [2.34] 3.50 8.19 2.64 [1.63] 1.01 4.27 1.12 [1.31] 0.85 3.47 0.20 [0.04] 0.14 0.22 0.02 [0.01] 0.01 0.02 Capilano River 6.531 [21.10] 6.28 48.47 0.07 [0.03] 0.02 0.08 11.92 [3.30] 5.44 12.05 3.24 [1.74] 1.50 4.98 2.04 [1.58] 0.71 3.87 0.22 [0.12] 0.16 0.39 0.03 [0.01] 0.01 0.04 Dundarave Pipe 140.90 [70.51] 115.28 196.49 0.90 [0.70] 0.23 4.05 55.39 [17.91] 38.55 92.34 2.68 [3.03] 0.94 10.9 2.20 [1.42] 1.02 7.92 0.12 [0.06] 0.08 1.52 0.02 [0.01] 0.01 0.17 Lawson’s Creek 114.92 [56.62] 12.81 126.05 0.26 [0.06] 0.20 0.32 45.11 [15.45] 20.21 63.43 2.34 [1.12] 1.23 3.46 1.68 [3.63] 0.67 7.93 0.72 [0.35] 0.13 0.84 0.07 [ 0.03] 0.01 0.08 Lynn River 42.79 [25.49] 8.30 92.82 0.07 [0.01] 0.04 1.18 15.45 [9.85] 6.92 45.11 3.17 [2.37] 1.58 6.32 2.62 [0.86] 1.96 3.19 0.19 [5.27] 0.09 20.77 0.02 [0.09] 0.01 0.27 Seymour River 18.35 [18.21] 5.47 41.89 0.03 [0.02] 0.02 0.06 6.40 [1.17] 4.35 6.68 2.62 [2.62] 1.03 4.21 1.44 [0.95] 0.60 2.50 0.26 [0.12] 0.12 0.37 0.02 [0.01] 0.01 0.03 Mossom Creek 352.77 [175.38] 22.91 373.68 0.64 [0.30] 0.11 0.70 40.83 [4.09] 35.38 43.56 2.15 [1.21] 0.94 3.36 1.63 [3.51] 0.46 7.47 0.14 [0.03] 0.12 0.19 0.01 [0.01] 0.01 0.02 Noon’s Creek 21.724 [17.23] 2.88 37.34 0.07 [0.01] 0.07 0.09 32.57 [25.00] 5.31 55.31 3.91 [3.08] 0.83 6.99 1.20 [1.39] 0.77 3.55 0.86 [0.42] 0.09 0.94 0.03 [0.02] 0.01 0.05 Spanish Creek 509.86 [389.13] 25.12 696.71 0.71 [0.44] 0.39 0.94 67.93 [17.28] 66.98 134.19 10.33 [6.65] 1.27 14.57 2.37 [3.64] 1.39 10.67 0.32 [0.20] 0.16 0.82 0.10 [0.18] 0.02 0.32 Stanley Park Culvert 6.86 [ 17.42] 2.43 37.27 0.10 [0.13] 0.07 0.33 18.73 [45.15] 13.89 104.20 11.48 [7.30] 0.99 15.58 4.04 [6.27] 1.83 14.38 0.87 [0.24] 0.44 0.91 0.10 [0.02] 0.07 0.10 140 Stormwater 4.76 [5.28] 0.54 52.69 0.47 [0.65] 0.10 13.00 7.03 [6.52] 0.50 27.15 5.80 [7.21] 0.57 67.81 1.9 0.19 8.00 7.73 [12.70] 0.67 106.11 0.55 [0.65] 0.09 3.49 141 Table A.5 Statistical test summary for fatty acid (FA) markers. Kruskal-Wallis p-value, z-value and Dunn’s Test p-value (Bonferroni-adjusted) for total fatty acid (TFA), essential fatty acid (EFA), saturated fatty acid (SFA), monounsaturated fatty acid (SFA), polyunsaturated fatty acid (PUFA), DHA:EPA for river, stormwater and wastewater particulate organic matter (POM) samples. _-values reported as significant (*) if p-value <0.05. Measurement Kruskal-Wallis p-value Comparison z-value Dunn’s Test p-value Total Fatty Acid (TFA) <0.001* River - Stormwater -2.84 0.0134* River - Wastewater -5.25 <0.001* Stormwater - Wastewater -2.05 0.120 Essential Fatty Acid (EFA) <0.001* River - Stormwater -2.96 0.0091* River - Wastewater -5.19 <0.001* Stormwater - Wastewater -1.89 0.176 Saturated Fatty Acid (SFA) <0.001* River - Stormwater -2.78 0.0161* River - Wastewater -5.19 <0.001* Stormwater - Wastewater -2.06 0.119 Monounsaturated Fatty Acid (MUFA) <0.001* River - Stormwater -2.88 0.0118* River - Wastewater -5.26 <0.001* Stormwater - Wastewater -2.03 0.127 Polyunsaturated Fatty Acid (PUFA) <0.001* River - Stormwater -2.91 0.0108* River - Wastewater -5.24 <0.001* Stormwater - Wastewater -1.98 0.142 142 DHA:EPA 0.0022* River - Stormwater 2.39 0.0512 River - Wastewater -1.44 0.447 Stormwater - Wastewater -3.47 0.0016* 143 Table A.6 Mean ± standard deviation of percentage contributions (% of total fatty acid) of individual fatty acids for particulate organic matter (POM) samples separated by POM type. Wastewater (Combined) includes both effluent and influent samples. Also indicated are mean ± standard deviation for total concentration (ug L-1) of all fatty acids (TFA), percentage contributions of total essential fatty acid (EFA), total saturated fatty acid (SFA), total monounsaturated fatty acid (MUFA), total polyunsaturated fatty acid (PUFA), mean ± standard deviation for DHA:EPA ratio and the number of samples per POM type (n). Rivers Stormwater Wastewater (Combined) Wastewater Effluent Wastewater Influent 8:0 0.47 ± 0.19 0.52 ± 0.33 0.29 ± 0.09 0.34 ± 0.09 0.24 ± 0.07 10:0 0.4 ± 0.21 0.28 ± 0.22 0.44 ± 0.12 0.46 ± 0.08 0.43 ± 0.15 11:0 - 0.02 ± 0.03 0.02 ± 0.03 0.02 ± 0.04 0.03 ± 0.01 12:0 1.47 ± 0.6 1.44 ± 0.37 1.54 ± 0.3 1.56 ± 0.3 1.51 ± 0.33 13:0 0.08 ± 0.16 0.06 ± 0.08 0.36 ± 0.28 0.17 ± 0.05 0.55 ± 0.29 14:0 4.64 ± 1.25 3.33 ± 0.44 3.57 ± 0.86 3.28 ± 0.47 3.86 ± 1.1 14:1 0.39 ± 0.26 0.78 ± 0.62 0.1 ± 0.11 0.04 ± 0.05 0.17 ± 0.11 15:0 1.27 ± 0.37 0.68 ± 0.19 0.9 ± 0.21 0.87 ± 0.2 0.93 ± 0.25 16:0 33.27 ± 7.42 23.99 ± 2.37 19.46 ± 10.64 23.46 ± 3.33 15.47 ± 14.26 16:1n-7 7.49 ± 4.2 3.98 ± 0.83 5.63 ± 2.56 7.27 ± 2.7 3.99 ± 0.82 16:2n-4 0.22 ± 0.33 0.08 ± 0.11 - - - 16:3n-4 0.15 ± 0.27 - - - - 16:4n-1 0.15 ± 0.24 0.14 ± 0.2 0.22 ± 0.32 0.4 ± 0.37 0.03 ± 0.06 17:0 1.67 ± 0.55 1 ± 0.22 0.6 ± 0.15 0.57 ± 0.09 0.63 ± 0.21 18:0 18.87 ± 7.21 11.34 ± 2.84 12.97 ± 6.25 12.46 ± 3.9 13.49 ± 8.48 18:1n-7 3.42 ± 1.29 3.77 ± 0.65 3.99 ± 1.39 4.61 ± 1.63 3.36 ± 0.85 18:1n-9 8.33 ± 3.63 18.16 ± 6.79 32.12 ± 9.68 26.45 ± 5.84 37.79 ± 9.81 144 18:2n-6 3.89 ± 1.62 10.26 ± 5.28 8.25 ± 2.26 7 ± 1.19 9.5 ± 2.49 18:3n-3 2.37 ± 1.71 6.92 ± 2.69 1.6 ± 0.58 1.36 ± 0.19 1.84 ± 0.75 18:3n-6 0.01 ± 0.05 0.11 ± 0.12 0.19 ± 0.3 0.35 ± 0.37 0.03 ± 0.03 18:4n-3 0.66 ± 0.94 - 0.19 ± 0.19 0.19 ± 0.16 0.18 ± 0.23 20:0 1.37 ± 0.51 2.06 ± 0.94 0.81 ± 0.2 0.79 ± 0.14 0.83 ± 0.27 20:1n-11 - - 0.09 ± 0.2 0.18 ± 0.26 - 20:1n-9 0.01 ± 0.03 0.22 ± 0.16 0.6 ± 0.17 0.51 ± 0.11 0.68 ± 0.19 20:3n-6 - 0.04 ± 0.09 0.05 ± 0.1 0.09 ± 0.14 0.01 ± 0.02 20:3n-3 0.02 ± 0.07 0.16 ± 0.32 0.04 ± 0.12 - 0.09 ± 0.17 20:4n-3 0.01 ± 0.06 - 0.07 ± 0.15 0.11 ± 0.21 0.02 ± 0.02 20:4n-6 0.3 ± 0.3 0.46 ± 0.3 0.37 ± 0.53 0.6 ± 0.7 0.13 ± 0.05 20:5n-3 1.44 ± 0.83 0.58 ± 0.4 0.43 ± 0.51 0.68 ± 0.65 0.18 ± 0.05 22:0 1.48 ± 0.73 2.7 ± 1.58 0.8 ± 0.49 0.91 ± 0.68 0.69 ± 0.21 22:1n-11 - - - - - 22:1n-9 0.18 ± 0.2 0.2 ± 0.18 0.18 ± 0.13 0.19 ± 0.11 0.17 ± 0.16 22:4n-6 - - 0.02 ± 0.03 0.02 ± 0.03 0.02 ± 0.04 22:5n-6 0.11 ± 0.21 - 0.02 ± 0.04 0.01 ± 0.03 0.02 ± 0.05 22:5n-3 0.2 ± 0.51 - - - - 22:6n-3 0.55 ± 0.45 0.04 ± 0.13 0.18 ± 0.17 0.23 ± 0.24 0.13 ± 0.04 24:0 1.81 ± 0.74 3.5 ± 3.32 0.52 ± 0.14 0.52 ± 0.16 0.51 ± 0.14 24:1n-9 - 0.02 ± 0.07 0.57 ± 0.51 0.31 ± 0.12 0.82 ± 0.63 ant-15:0 1.25 ± 0.75 1.71 ± 0.62 1.18 ± 0.47 1.37 ± 0.59 1 ± 0.26 iso-15:0 1.58 ± 0.86 1.29 ± 0.75 1.21 ± 0.9 1.73 ± 1.05 0.69 ± 0.19 iso-17:0 0.42 ± 0.35 0.15 ± 0.13 0.42 ± 0.77 0.85 ± 0.94 - TFA ug L-1 18.1 ± 14.62 467.65 ± 465.36 16362.15 ± 13030.93 4943.12 ± 4290.07 27781.19 ± 6137.68 EFA 9.11 ± 4.13 18.23 ± 5.99 11.18 ± 3.01 10.4 ± 2.73 11.97 ± 3.36 SFA 67.21 ± 11.72 51.26 ± 6.32 42.38 ± 11.78 45.51 ± 6.28 39.24 ± 15.75 MUFA 19.56 ± 6.26 26.94 ± 5.95 43.21 ± 9.36 39.5 ± 4.36 46.92 ± 11.99 145 PUFA 9.98 ± 4.67 18.65 ± 5.94 11.59 ± 3.14 11.03 ± 3.02 12.15 ± 3.51 DHA:EPA 0.4 ± 0.4 0.05 ± 0.16 0.64 ± 0.37 0.49 ± 0.46 0.78 ± 0.22 n 15 9 10 5 5 146 Table A.7 Mean, Median, Min, Max, Standard Deviation (SD) and sample number (n) for particulate organic carbon (POC) (mg L-1), particulate nitrogen (PN) (mg L-1), δ13C (‰), δ15N (‰), and C:N molar ratio of wastewater POM samples including 4 influent and 2 effluent samples. An independent two-sample t-test was performed between wastewater and river or stormwater values. P-values reported as significant (*) if p-value <0.05. Mean Median Min Max SD n Stormwater T-test P-value River T-test P-value POC (mg L-1) 0.07 0.08 0.002 0.153 0.06 6 <0.001* 0.11 δ13C (‰) -24.29 -24.31 -24.93 -23.46 0.48 6 <0.001* <0.001* PN (mg L-1) 0.01 0.01 0.001 0.03 0.01 6 <0.001* <0.001* δ15N (‰) -1.37 -0.66 -3.78 -0.48 1.32 6 <0.001* <0.001* C:N 7.49 8.54 4.45 10.12 2.38 6 <0.001* <0.001* 147 Table A.8 Mean, median, min, max, standard deviation (SD) and sample number (n) for δ13C (‰), δ15N (‰), and C:N molar ratio of river and stormwater POM samples. An independent two-sample t-test was performed between river and stormwater values. P-values reported as significant (*) if p-value <0.05. Measurement River Stormwater T-test P-value Mean Median Min Max SD n Mean Median Min Max SD n δ13C (‰) -28.15 -27.8 -32.61 -24.15 1.76 37 -28.35 -28.40 -29.05 -27.61 0.41 31 0.537 δ15N (‰) 2.37 2.23 -0.96 6.79 1.52 37 2.22 2.83 -2.53 5.84 2.12 31 0.750 C:N 13.18 12.57 8.27 22.43 2.98 37 23.58 23.78 11.28 -34.79 6.52 31 <0.001* 148 Table A.9 Statistical test summary for δ13C, δ15N, and C:N molar ratios for of river, stormwater, and wastewater particulate organic material (POM) samples. ANOVA P-Values and Tukey Test P-Values reported. P-values reported as significant (*) if p-value <0.05. Measurement ANOVA P-Value Comparison Tukey Test P-Value δ13C <0.001* River - Stormwater <0.001* River - Wastewater 0.80 Stormwater - Wastewater <0.001* δ15N <0.001* River - Stormwater 0.94 River - Wastewater <0.001* Stormwater - Wastewater <0.001* C:N <0.001* River - Stormwater 0.022 River - Wastewater 0.02* Stormwater - Wastewater 0.022 149 Appendix B Figure B.3 Map of macrophyte collection sites (purple) around Burrard Inlet. 150 Figure B.4 Map of Indian River and Fraser River at Hope sampling sites. 151 Table B.10 Mean and standard deviations (SD) for δ13C (‰), δ15N (‰), C:N molar ratio, and number of samples (n) for each macrophyte species. Species Mean δ13C ± SD (‰) Mean δ15N ± SD (‰) Mean C:N ± SD n Fucus spp. -16.73 ±2.47 6.75 ±0.59 25.70 ±6.22 41 Laminaria spp. (Kelp) -13.88 ±1.65 7.46 ±0.44 14.15 ±1.50 6 Mastocarpus sp. -16.38 ±2.48 6.66 ±0.74 12.13 ±1.31 10 Pyropia sp. -19.26 ±1.51 6.44 ±0.31 9.84 ±0.99 4 Saccharina latissima -14.20 ±1.91 7.11 ±0.43 17.07 ±3.58 4 Sargassum muticum -15.29 6.24 20.34 1 Ulva spp. -15.09 ±2.38 6.86 ±0.60 11.49 ±3.66 30 152 Table B.11 The relative contributions of phytoplankton, macrophyte, freshwater (combined rivers and stormwater), and effluent to the surface (0-1 m) particulate organic matter (POM) pool in the Outer Harbor, Inner Harbor, Central Harbor, Port Moody, and False Creek basins in Burrard Inlet during the wet, wet bloom, and dry seasons. Mean ± standard deviation (SD) and 95% Bayesian credible intervals are presented. Season Location Phytoplankton Macrophyte Freshwater Effluent Mean ±SD 95 % Mean ±SD 95 % Mean ±SD 95 % Mean ±SD 95 % Wet Outer Harbor 0.86 ±0.086 0.971 0.025 ±0.026 0.078 0.081 ±0.066 0.209 0.034 ±0.031 0.096 Inner Harbor 0.723 ±0.105 0.90 0.028 ±0.027 0083 0.174 ±0.106 0.355 0.075 ±0.057 0.187 Central Harbor 0.744 ±0.089 0.88 0.054 ±0.047 0.147 0.115 ±0.068 0.242 0.086 ±0.048 0.175 Port Moody 0.862 ±0.086 0.972 0.029 ±0.034 0.098 0.063 ±0.062 0.186 0.046 ±0.043 0.133 False Creek 0.485 ±0.119 0.88 0.056 ±0.05 0.155 0.199 ±0.137 0.449 0.261 ±0.107 0.426 Wet Bloom Outer Harbor 0.874 ±0.066 0.964 0.017 ±0.017 0.051 0.039 ±0.038 0.118 0.088 ±0.061 0.086 Inner Harbor 0.884 ±0.07 0.98 0.024 ±0.03 0.086 0.022 ±0.026 0.074 0.069 ±0.058 0.182 Central Harbor 0.874 ±0.056 0.952 0.035 ±0.036 0.111 0.032 ±0.028 0.086 0.059 ±0.039 0.135 Port Moody 0.909 ±0.061 0.987 0.042 ±0.049 0.14 0.02 ±0.023 0.066 0.028 ±0.028 0.086 False Creek 0.812 ±0.081 0.951 0.027 ±0.029 0.084 0.042 ±0.043 0.131 0.119 ±0.076 0.246 Dry Outer Harbor 0.855 ±0.068 0.961 0.119 ±0.059 0.219 0.018 ±0.025 0.07 0.008 ± 0.013 0.032 Inner Harbor 0.846 ±0.072 0.96 0.127 ±0.063 0.231 0.009 ±0.013 0.071 0.009 ± 0.013 0.032 Central Harbor 0.723 ±0.077 0.852 0.245 ±0.073 0.36 0.02 ±0.021 0.064 0.012 ±0.013 0.039 Port Moody 0.724 ±0.079 0.859 0.257 ±0.077 0.378 0.012 ±0.015 0.044 0.007 ±0.009 0.024 False Creek 0.867 ±0.07 0.969 0.106 ±0.06 0.214 0.016 ± 0.022 0.063 0.011 ±0.019 0.047 153 Table B.12 Mean contribution of phytoplankton, macrophyte, freshwater and effluent contributions and standard deviations (SD) (mg.m-3) to measured mean total biomass (mg.m-3) for each basin and season. Season Location Phytoplankton Biomass ±SD (mg.m-3) Macrophyte Biomass ±SD (mg.m-3) Freshwater Biomass ±SD (mg.m-3) Effluent Biomass ±SD (mg.m-3) Total Biomass ±SD (mg.m-3) Wet Outer Harbor 3570.36 ±1271.11 103.79 ±113.69 336.28 ±297.42 141.15 ±137.55 4151.58 ±1427.99 Inner Harbor 2363.24 ±1189.97 91.52 ±98.67 568.75 ±441.86 245.15 ±220.64 3268.66 ±1575.94 Central Harbor 2983.32 ±1253.98 216.53 ±207.68 461.13 ± 329.96 344.85 ±237.39 4009.84 ±1615.76 Port Moody 4723.14 ±1298.57 158.90 ±190.69 345.20 ±351.04 252.07 ±244.30 5479.29 ±1403.78 False Creek 2052.08 ±1133.80 236.94 ±241.90 842.00 ±713.97 1104.32 ±709.81 4231.10 ±2094.58 Wet Bloom Outer Harbor 5699.76 ±3098.72 113.20 ±128.55 259.69 ±289.06 585.96 ±514.22 6658.60 ±3583.41 Inner Harbor 5886.68 ±2319.82 159.82 ±209.084 146.50 ±182.14 459.48 ±425.01 6659.14 ±2570.70 Central Harbor 6263.07 ±1281.86 250.81 ±262.54 229.31 ±205.54 422.79 ±291.31 7165.98 ±1392.94 Port Moody 5555.08 ±1942.72 256.67 ±312.14 122.22 ±146.68 171.11 ±180.91 6111.20 ±2097.49 False Creek 3811.03 ±1702.66 126.72 ±146.87 197.12 ±219.31 558.51 ±431.73 4693.38 ±2043.93 Dry Outer Harbor 5127.69 ±1501.59 713.68 ±407.01 107.95 ±152.99 47.98 ±79.13 5997.30 ±1690.23 Inner Harbor 4437.06 ±2648.69 666.08 ±513.87 99.65 ±153.36 47.20 ±73.67 5244.75 ±3098.85 Central Harbor 6447.00 ±2550.40 2184.67±1056.67 178.34 ±199.20 107.00 ±122.88 8917.01 ±3397.42 Port Moody 4958.35 ±2440.79 1760.08 ±995.93 82.18 ±110.04 47.94 ±65.79 6848.55 ±3287.40 False Creek 8628.12 ±8413.96 1054.88 ±1186.38 159.23 ±268.10 109.47 ±216.96 9951.70 ±9671.37
Thesis/Dissertation
eng
Oceans and Fisheries
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Hunt, Brian P. V.
Urban disruption of the land-sea connection : understanding stormwater and river inputs from Metro Vancouver and particulate organic matter composition in Burrard Inlet British Columbia
Text