{"http:\/\/dx.doi.org\/10.14288\/1.0406219":{"http:\/\/vivoweb.org\/ontology\/core#departmentOrSchool":[{"value":"Science, Faculty of","type":"literal","lang":"en"},{"value":"Zoology, Department of","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/dataProvider":[{"value":"DSpace","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#degreeCampus":[{"value":"UBCV","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/creator":[{"value":"Penman, Rachael","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/issued":[{"value":"2022-01-07T17:28:08Z","type":"literal","lang":"en"},{"value":"2021","type":"literal","lang":"en"}],"http:\/\/vivoweb.org\/ontology\/core#relatedDegree":[{"value":"Master of Science - MSc","type":"literal","lang":"en"}],"https:\/\/open.library.ubc.ca\/terms#degreeGrantor":[{"value":"University of British Columbia","type":"literal","lang":"en"}],"http:\/\/purl.org\/dc\/terms\/description":[{"value":"Freshwater fish such as white sturgeon (Acipenser transmontanus) are particularly vulnerable to the effects of anthropogenic global warming; however, little is known about how acclimation to higher temperatures or rate of temperature increase affects their thermal tolerance. The Kenney dam on the Nechako River is home to the northern-most population of white sturgeon and is mandated to maintain water temperatures below 20\u00b0C for migrating sockeye salmon, but it remains unclear whether 20\u00b0C is an appropriate threshold for developing white sturgeon. To address this, 37-51 days post hatch (dph) and 66-80 dph juvenile white sturgeon were acclimated to one of four ecologically relevant temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) for two weeks, following which thermal tolerance (CTmax), size, condition factor, and survival were assessed. White sturgeon displayed highly plastic CTmax in response to acclimation, illustrated by a positive relationship between acclimation temperature and CTmax and large acclimation response ratios compared to other fish species. Acclimation to temperatures above 18\u00b0C was found to negatively affect condition factor, which suggests the presence of a sub-lethal threshold between 18\u00b0C and 21\u00b0C. Their highly plastic response to temperature was further demonstrated when the effect of heating rate (0.3\u00b0C\/min, 0.03\u00b0C\/min, 0.003\u00b0C\/min) on thermal tolerance, somatic indices, and Hsp mRNA expression was assessed. White sturgeon CTmax was highest in the slowest heating rate, contrary to what has been observed in most other fish species. Hepatosomatic index decreased in all heating rates relative to control fish, indicative of the metabolic costs of thermal stress. Expression of Hsp70 mRNA was increased in all heating rates relative to controls, whereas expression of Hsp90a and Hsp90b mRNA only increased in the two slower trials. Together these data indicate that while white sturgeon have a very plastic thermal response, acclimation to temperatures above 18\u00b0C may negatively affect overall health, indicated by lower condition factor. As such, in the best interest of white sturgeon conservation, the operators of the Kenney dam may want to reconsider whether the 20\u00b0C threshold is appropriate.","type":"literal","lang":"en"}],"http:\/\/www.europeana.eu\/schemas\/edm\/aggregatedCHO":[{"value":"https:\/\/circle.library.ubc.ca\/rest\/handle\/2429\/80595?expand=metadata","type":"literal","lang":"en"}],"http:\/\/www.w3.org\/2009\/08\/skos-reference\/skos.html#note":[{"value":"The effects of temperature acclimation and heating rate on the thermal tolerance of juvenile white sturgeon (Acipenser transmontanus)   by  Rachael Penman  B.Sc., Carleton University, 2016  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Zoology)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  December 2021  \u00a9 Rachael Penman, 2021   ii  The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, a thesis entitled:  The effect of temperature acclimation and heating rate on the thermal tolerance of juvenile white sturgeon (Acipenser transmontanus)   submitted by Rachael Penman in partial fulfillment of the requirements for the degree of Master of Science in The Faculty of Graduate and Postdoctoral Studies (Zoology)  Examining Committee: Dr Colin Brauner, Department of Zoology, UBC Supervisor  Dr Katie Marshall, Department of Zoology, UBC Supervisory Committee Member  Dr Patricia Schulte, Department of Zoology, UBC Supervisory Committee Member   iii Abstract Freshwater fish such as white sturgeon (Acipenser transmontanus) are particularly vulnerable to the effects of anthropogenic global warming; however, little is known about how acclimation to higher temperatures or rate of temperature increase affects their thermal tolerance. The Kenney dam on the Nechako River is home to the northern-most population of white sturgeon and is mandated to maintain water temperatures below 20\u00b0C for migrating sockeye salmon, but it remains unclear whether 20\u00b0C is an appropriate threshold for developing white sturgeon. To address this, 37-51 days post hatch (dph) and 66-80 dph juvenile white sturgeon were acclimated to one of four ecologically relevant temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) for two weeks, following which thermal tolerance (CTmax), size, condition factor, and survival were assessed. White sturgeon displayed highly plastic CTmax in response to acclimation, illustrated by a positive relationship between acclimation temperature and CTmax and large acclimation response ratios compared to other fish species. Acclimation to temperatures above 18\u00b0C was found to negatively affect condition factor, which suggests the presence of a sub-lethal threshold between 18\u00b0C and 21\u00b0C. Their highly plastic response to temperature was further demonstrated when the effect of heating rate (0.3\u00b0C\/min, 0.03\u00b0C\/min, 0.003\u00b0C\/min) on thermal tolerance, somatic indices, and Hsp mRNA expression was assessed. White sturgeon CTmax was highest in the slowest heating rate, contrary to what has been observed in most other fish species. Hepatosomatic index decreased in all heating rates relative to control fish, indicative of the metabolic costs of thermal stress. Expression of Hsp70 mRNA was increased in all heating rates relative to controls, whereas expression of Hsp90a and Hsp90b mRNA only increased in the two slower trials. Together these data indicate that while white sturgeon have a very plastic thermal response, acclimation to temperatures above 18\u00b0C may negatively affect overall health, indicated   iv by lower condition factor. As such, in the best interest of white sturgeon conservation, the operators of the Kenney dam may want to reconsider whether the 20\u00b0C threshold is appropriate.    v Lay Summary Freshwater fish such as the endangered white sturgeon are threatened by climate change induced warming.  White sturgeon are culturally and economically important and are native to the west coast of North America. The Kenney dam on the Nechako River in British Columbia is currently mandated to maintain water temperature below 20\u00b0C; however, this threshold originated from research on sockeye salmon and may not apply to white sturgeon. To protect white sturgeon populations, this thesis investigates how juvenile white sturgeon will cope with warming temperatures, in hopes of better informing dam management decisions and species conservation. To do so, the effects of temperature and warming rate on traits such as thermal tolerance, survival, size, and other bodily indicators were assessed. Warmer temperatures were found to increase thermal tolerance, but negatively affect overall health. This suggests that river temperatures above 18\u00b0C may not be appropriate for white sturgeon conservation.     vi Preface I conducted all of the research in Chapters 2 and 3 under the supervision of Dr. Colin Brauner (research questions, experimental design, and data analysis). William Bugg was a collaborator in Chapter 3. All experimental animals were treated according to the University of British Columbia Animal Protocol #A15-0266. I wrote all 4 chapters of this thesis and received editorial feedback from my committee members, Drs. Colin Brauner, Katie Marshall, and Patricia Schulte.   vii Table of Contents  Abstract ......................................................................................................................................... iii Lay Summary ................................................................................................................................ v Preface ........................................................................................................................................... vi Table of Contents ........................................................................................................................ vii List of Tables ................................................................................................................................. x List of Figures ............................................................................................................................... xi List of Abbreviations .................................................................................................................. xii Acknowledgements .................................................................................................................... xiv Chapter 1: Introduction ............................................................................................................... 1 1.1 Temperature effects and thermal tolerance ............................................................................... 2 1.2 Measuring thermal tolerance ....................................................................................................... 3 1.3 Acclimation .................................................................................................................................... 5 1.3.1 Quantifying thermal acclimation ............................................................................................. 6 1.4 Physiological indicators of temperature effects on fish ............................................................. 7 1.5 White sturgeon (Acipenser transmontanus) .............................................................................. 10 1.6 The Nechako River ..................................................................................................................... 11 1.7 Thesis objectives .......................................................................................................................... 12 1.7.1 Determine the effect of temperature acclimation on survival, condition factor and thermal tolerance ............................................................................................................................................. 13   viii 1.7.2 Determine the effect of heating rate during CTmax on thermal tolerance, somatic indices, and Hsp expression ................................................................................................................................... 13 Chapter 2: The effects of acclimation temperature and age on thermal tolerance in juvenile white sturgeon ............................................................................................................................. 15 2.1 Introduction ................................................................................................................................. 15 2.2 Methods ....................................................................................................................................... 18 2.2.1 White sturgeon broodstock and holding ................................................................................ 18 2.2.2 Temperature acclimation period ............................................................................................ 19 2.2.3 Thermal tolerance and critical thermal maximum testing ..................................................... 20 2.2.4 Mass, total length, and condition factor ................................................................................. 21 2.2.5 Statistical Analysis ................................................................................................................. 21 2.3 Results .......................................................................................................................................... 22 2.3.1 Effect of acclimation temperature and age on thermal tolerance and acclimation capacity . 22 2.3.2 Effect of acclimation temperature on size, condition factor, and survival ............................ 23 2.4 Discussion .................................................................................................................................... 28 Chapter 3: The effect of heating rate on thermal tolerance in juvenile white sturgeon ...... 32 3.1 Introduction ................................................................................................................................. 32 3.2 Methods ....................................................................................................................................... 35 3.2.1 White sturgeon broodstock and holding ................................................................................ 35 3.2.2 The effect of heating rate on thermal tolerance ..................................................................... 35 3.2.3 Post-trial sampling and somatic indices ................................................................................. 37 3.2.4 mRNA expression .................................................................................................................. 37 3.2.5 Statistical analysis .................................................................................................................. 39 3.3 Results .......................................................................................................................................... 40   ix 3.3.1 Effect of heating rate on thermal tolerance ............................................................................ 40 3.3.2 Effect of heating rate and performance on somatic indices ................................................... 40 3.3.3 Effect of heating rate and performance on Hsp expression ................................................... 41 3.3.3.1 Hsp47 ..............................................................................................................................................41 3.3.3.2 Hsp70 ..............................................................................................................................................41 3.3.3.3 Hsp90a ............................................................................................................................................42 3.3.3.4 Hsp90b ............................................................................................................................................42 3.4 Discussion .................................................................................................................................... 51 Chapter 4: General Discussion and Conclusion ....................................................................... 56 4.1 Thesis summary .......................................................................................................................... 56 4.2 Limitations and future directions .............................................................................................. 57 4.2.1 Chapter 2 ................................................................................................................................ 57 4.2.2 Chapter 3 ................................................................................................................................ 58 4.3 Policy recommendation .............................................................................................................. 58 Bibliography ................................................................................................................................ 60       x List of Tables  Table 2.1 The effect of acclimation temperature and age on the CTmax of juvenile white sturgeon ....................................................................................................................................................... 24\tTable 2.2 Acclimation response ratio of juvenile white sturgeon. ............................................... 24\tTable 2.3 The effect of acclimation temperature on various traits of juvenile white sturgeon .... 24\tTable 2.4 Effect of acclimation temperature and age on survival of juvenile white sturgeon. .... 24\tTable 2.5 Morphometrics for juvenile white sturgeon .................................................................. 25\tTable 3.1 List of forward and reverse primers and their efficiencies ........................................... 39\tTable 3.2 Somatic indices of juvenile white sturgeon in control conditions or one of three heating rates ............................................................................................................................................... 44\tTable 3.3 The effect of heating rate on CTmax, somatic indices, and Hsp expression in juvenile white sturgeon ............................................................................................................................... 44\tTable 3.4 The effect of heating rate and performance on various somatic indices and Hsp expression in juvenile white sturgeon ........................................................................................... 45\t   xi List of Figures  Figure 2.1 CTmax for juvenile white sturgeon ............................................................................... 26\tFigure 2.2 Final condition factor of juvenile white sturgeon ........................................................ 27\tFigure 3.1 CTmax of juvenile white sturgeon at three different heating rates ............................... 46\tFigure 3.2 HSI of juvenile white sturgeon .................................................................................... 47\tFigure 3.3 Condition factor of juvenile white sturgeon ................................................................ 48\tFigure 3.4 Hsp mRNA expression in juvenile white sturgeon ..................................................... 49\tFigure 3.5 Hsp mRNA expression in low and high performing juvenile white sturgeon ............ 50\t     xii List of Abbreviations  ARR  Acclimation response ratio,  \ud835\udc34\ud835\udc45\ud835\udc45 = \ud835\udc36\ud835\udc47!\"#( \ud835\udc47!!)\u2212  \ud835\udc36\ud835\udc47!\"#(\ud835\udc47!!)(\ud835\udc47!! \u2212  \ud835\udc47!!)  BSI  Brain somatic index,  \ud835\udc35\ud835\udc46\ud835\udc3c =  \ud835\udc35\ud835\udc5f\ud835\udc4e\ud835\udc56\ud835\udc5b \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54) \ud835\udc4a\u210e\ud835\udc5c\ud835\udc59\ud835\udc52 \ud835\udc4f\ud835\udc5c\ud835\udc51\ud835\udc66 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54)\u00d7 100% CF  Condition factor,  \ud835\udc36\ud835\udc39 =\ud835\udc4a\u210e\ud835\udc5c\ud835\udc59\ud835\udc52 \ud835\udc4f\ud835\udc5c\ud835\udc51\ud835\udc66 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54)\u00d710!\ud835\udc47\ud835\udc5c\ud835\udc61\ud835\udc4e\ud835\udc59 \ud835\udc59\ud835\udc52\ud835\udc5b\ud835\udc54\ud835\udc61\u210e (\ud835\udc5a\ud835\udc5a)!  CSI   Cardiosomatic index,  \ud835\udc36\ud835\udc46\ud835\udc3c =  \ud835\udc3b\ud835\udc52\ud835\udc4e\ud835\udc5f\ud835\udc61 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54) \ud835\udc4a\u210e\ud835\udc5c\ud835\udc59\ud835\udc52 \ud835\udc4f\ud835\udc5c\ud835\udc51\ud835\udc66 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54)\u00d7 100% CSR  Cellular stress response CTM   Critical thermal methods CTmax   Critical thermal maximum  CTmin   Critical thermal minimum dph   Days post hatch HSI   Hepatosomatic index,  \ud835\udc3b\ud835\udc46\ud835\udc3c =  \ud835\udc3f\ud835\udc56\ud835\udc63\ud835\udc52\ud835\udc5f \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54) \ud835\udc4a\u210e\ud835\udc5c\ud835\udc59\ud835\udc52 \ud835\udc4f\ud835\udc5c\ud835\udc51\ud835\udc66 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54)\u00d7 100% Hsp   Heat shock protein ILT   Incipient lethal temperature  InSEAS Initiative for the Study of the Environment and its Aquatic Systems   xiii IPCC  Intergovernmental Panel on Climate Change LOE   Loss of equilibrium mRNA  Messenger ribonucleic acid NWSRI  Nechako White Sturgeon Recovery Initiative  OCLTT Oxygen capacity limited thermal tolerance theory Ta  Acclimation temperature UBC  University of British Columbia YSL   Yolk sac larvae   xiv Acknowledgements  Thank you to my supervisor, Dr Colin Brauner, for the help and guidance along the way and to my committee members, Drs Trish Schulte and Katie Marshall, who patiently explained concepts and provided meaningful feedback. Thank you to Tessa Blanchard, Will Bugg, Madison Earhart, and Bea Rost-Komiya without whom I\u2019d likely still be toiling away in my experimental chamber. Thank you to my parents, who supported me along my winding path to grad school.  Thank you to my comphy cohort for the endless support and good times. You all made my experience at UBC unforgettable and I\u2019m so stoked to have met you!    1 Chapter 1: Introduction Of the many freshwater fish species in North America affected by anthropogenic activity, white sturgeon (Acipenser transmontanus) has undergone severe population collapse (Hildebrand et al., 2016). As global temperatures continue to rise at rates predicted by the Intergovernmental Panel on Climate Change (IPCC), elevated water temperature will become increasingly problematic for developing white sturgeon (Chen et al., 2021).  The Nechako River in British Columbia, Canada, which is home to the northernmost population of endangered white sturgeon (Hildebrand et al., 2016), was dammed in the 1950s. Following the construction of the Kenney Dam, a water management program was developed, which led to the establishment of an upper water temperature threshold set at 20\u00b0C. This threshold temperature was established based on research conducted exclusively on migrating sockeye salmon (Oncorhynchus nerka; Macdonald et al., 2012). It remains unclear whether the 20\u00b0C threshold is an appropriate threshold for developing white sturgeon.  To better inform water management decisions and help prevent further population collapse, this thesis examines the effects of temperature acclimation and heating rate on juvenile white sturgeon as relatively little is known about the thermal biology of this species. The remainder of the introduction will broadly review the effects of temperature and thermal tolerance, acclimation, physiological indicators of temperature, and the life history of white sturgeon, which will lead to a discussion of the specific thesis objectives.    2 1.1 Temperature effects and thermal tolerance  Climate change is predicted to greatly impact global temperatures in the coming decades (Hassan et al., 2020; Hoegh-Guldberg et al., 2018). Northern regions of the globe are expected to be disproportionately affected by rising temperatures, having already experienced twice the global average of temperature increase of southern regions (Chen et al., 2021). In Canada, mean annual surface air temperatures have increased by 1.5\u00b0C from 1950 to 2010, with northernmost regions undergoing the largest increase (Vincent et al., 2012; Vincent et al., 2015).  Freshwater ecosystems are particularly susceptible to climate change because they are often overexploited environments that offer limited refugia and dispersal opportunities (Dudgeon et al., 2006; Hassan et al., 2020; Woodward, 2009). Accordingly, freshwater animals tend to have higher extinction rates than either terrestrial or marine species, particularly at higher latitudes.  Freshwater ecosystems in northern latitudes are some of the most threatened in the world, and so require focused scientific study and heightened conservation efforts (Strayer and Dudgeon, 2010). The impacts of anthropogenic global warming are especially significant for ectotherms such as fish, because their body temperature is directly influenced by the temperature of their environment. For ectotherms, temperature plays a critical role in determining population range, physiology, community dynamics, and survival (Bolta\u00f1a et al., 2017; Crozier et al., 2008; Li et al., 2015; O\u2019Gorman et al., 2016; Pankhurst and Munday, 2011; Schulte, 2015). All organisms have a defined thermal tolerance range in which they are able to function (Huey and Stevenson, 1979). Thermal tolerance extends from an organism\u2019s lower thermal limit to their upper thermal limit (Beitinger and Lutterschmidt, 2011). An organism\u2019s optimum temperature lies within this   3 range and is the temperature at which they function best (Schulte, 2015). When temperatures approach an animal's thermal limits, damage can be caused at all levels of biological organization (Abram et al., 2017; McArley et al., 2017; Schulte, 2015).  Thermal tolerance varies depending on developmental stage and consequently, an organism\u2019s most thermally sensitive life stage determines its vulnerability to global warming (Beitinger and Lutterschmidt, 2011; Dahlke et al., 2020). Some species display diurnal fluctuations in thermal tolerance, where thermal tolerance is highest during the day and lowest at night (Healy and Schulte, 2012). Thermal tolerance also fluctuates throughout the year; upper thermal tolerance is the highest in the summer when species are exposed to warmer weather and the lowest in the winter when ambient temperatures are lower (Schaefer et al., 1999; Sharma et al., 2015). In fish, thermal tolerance is generally the lowest during embryogenesis and spawning as these are the most oxygen-limited life stages (reviewed in P\u00f6rtner, 2001; Dahlke et al., 2020; P\u00f6rtner and Farrell, 2008). Early in development fish prioritize rapid growth \u2013 typical growth rates for larvae are 10-30% body mass per day. Consequently, they have less energy reserves to cope with abiotic stressors such as extreme temperatures (Rombough, 2011).   1.2 Measuring thermal tolerance Multiple laboratory tests have been developed to assess thermal tolerance in ectotherms, including the incipient lethal temperature (ILT) and the critical thermal methodology (CTM; Cowles and Bogert, 1944; Fry et al., 1942). Both techniques are standardized, repeatable, and assess upper and lower thermal limits; however, CTM is preferentially used as it requires fewer   4 fish, it is fast to conduct, and its sub-lethal endpoint allows endangered animals to be assessed and then released back in to their environment (Beitinger and Lutterschmidt, 2011). Critical thermal maximum (CTmax) and critical thermal minimum (CTmin) tests are used to determine upper and lower thermal limits respectively. The endpoint for upper thermal tolerance occurs when the animal\u2019s locomotion becomes disorganized (Cowles and Bogert, 1944). In fish, this endpoint is characterized by a loss of equilibrium (LOE) where the fish is no longer able to right itself. To conduct CTMs, temperature is increased (or decreased) at a constant rate that is fast enough to prevent acclimation but slow enough that inner body temperature remains in equilibrium with the environment. Typical rates of temperature change in CTMs range between 0.1\u00b0C\/min and 0.3\u00b0C\/min, but there is a wide range cited in the literature (Beitinger and Lutterschmidt, 2011; Kingsolver and Umbanhowar, 2018; Lutterschmidt and Hutchison, 1997).  CTmax is commonly used to predict species\u2019 vulnerability to climate change (Sandblom et al., 2016; Sunday et al., 2012). Yet, while CTMs are easy to conduct in laboratories, their ecological relevance is less clear as the rates of temperature change are far greater than most temperature increases observed in nature (a rate of 0.3\u00b0C\/min equates to 18\u00b0C\/hour and 432\u00b0C\/day;(Illing et al., 2020). Few studies in fish have directly compared the rate at which the temperature is increased (heating rate) during a CTmax trial to the final CTmax value. Those that have, typically revealed that faster heating rates resulted in higher CTmax values (Becker and Genoway, 1979; Illing et al., 2020; Mora and Maya, 2006). It is thought that slower heating rates result in lower CTmax values because the cumulative stress of prolonged heat exposure exhausts the animal (Rezende et al., 2014).     5 1.3 Acclimation In light of long-term climate forecasts predicting drastic increases in temperature, research has begun to focus on how animals will adjust to survive these changes. Faced with increasing temperature, fish can either migrate, acclimate, or adapt (Fuller et al., 2010; Somero, 2010). Migration is often not feasible for many freshwater fish because of natural and anthropogenic ecosystem fragmentation, such as dams, waterfalls, and catchment divides (Rahel, 2007; Strayer and Dudgeon, 2010). Furthermore, climate change may be acting too rapidly for organisms to mitigate its affects through adaptation (Radchuk et al., 2019). Thus, the ability to successfully acclimate is critical for freshwater fish species.  Temperature acclimation is defined as the reversible physiological and biochemical changes that occur in response to thermal stress, and is crucial for enabling organisms to cope with natural and anthropogenic changes in their environment (Hazel and Prosser, 1974; Kingsolver and Huey, 1998). The timescale over which acclimation occurs on depends on a number of factors, including latitude, habitat, taxon, and body size (Morley et al., 2019; Rohr et al., 2018). Polar fish typically require 5 \u2013 20 days to acclimate to temperature changes whereas tropical fish acclimate 2 \u2013 4 times faster and are able to increase their thermal tolerance in 2 \u2013 5 days (Bilyk and DeVries, 2011; Peck et al., 2014; Schmidt-Nielsen, 1990). Rohr and colleagues (2018) found that acclimation rate scales negatively with body size, with larger organisms (14g) taking longer to acclimate than smaller organisms (20mg). Most ectothermic vertebrates have some capacity for thermal acclimation. For instance, brook trout (Salvelinus fontinalis) acclimated to temperatures that span their thermal range (5\u00b0C \u2013 25\u00b0C), were subsequently able to increase their thermal tolerance. However this was limited to acclimation temperatures of up to   6 20\u00b0C, beyond which no further increase in thermal tolerance was observed (Morrison et al., 2020).   1.3.1 Quantifying thermal acclimation All organisms have a finite ability to acclimate, and upper thermal tolerance will eventually plateau even as the animal is acclimated to higher temperatures (Morrison et al., 2020). The difference between an organism\u2019s optimum temperature and the environmental temperature they experience is known as the thermal safety margin \u2013 as anthropogenic global warming continues, this margin will decrease (McArley et al., 2017; Sandblom et al., 2016). Another way to quantify an organism's capacity to acclimate is using the acclimation response ratio (ARR). ARR offers a metric of physiological plasticity that captures acclimation capacity. It is calculated as the ratio of the change in upper thermal tolerance (measured using CTmax), per degree change in acclimation temperature (Ta) (Claussen, 1977), as follows: \ud835\udc34\ud835\udc45\ud835\udc45 = \ud835\udc36\ud835\udc47!\"#( \ud835\udc47!!)\u2212  \ud835\udc36\ud835\udc47!\"#(\ud835\udc47!!)(\ud835\udc47!! \u2212  \ud835\udc47!!)  An ARR of 1 would indicate complete acclimation, where for example, a 5\u00b0C increase in acclimation temperature results in a 5\u00b0C increase in thermal tolerance. Conversely, an ARR of 0 indicates no acclimation (Claussen, 1977). ARR varies by taxa and by latitude (Morley et al., 2019; Rohr et al., 2018). Morley et al. (2019) found that the average ARR of tropical fish is significantly lower than mid- and high latitude species (0.26 versus 0.30 and 0.32). Juvenile lake sturgeon (Acipenser fulvescens) have higher ARRs (around 0.4) than most other species for similar latitudes, indicating a high degree of thermal plasticity (Bugg et al. 2020). This trait of a   7 high ARR may be general to all sturgeon as juvenile shortnose sturgeon (Acipenser brevirostrum), acclimated from 10\u00b0C to 15\u00b0C had an ARR of 0.78 (Zhang and Kieffer, 2014).  1.4 Physiological indicators of temperature effects on fish Temperature can affect fish in a multitude of ways, depending on the duration of exposure. In fish, condition factor is a commonly used indicator of overall health (Bolger and Connolly, 1989). It is calculated using the relationship between fish mass and length, as follows: \ud835\udc36\ud835\udc5c\ud835\udc5b\ud835\udc51\ud835\udc56\ud835\udc61\ud835\udc56\ud835\udc5c\ud835\udc5b \ud835\udc53\ud835\udc4e\ud835\udc50\ud835\udc61\ud835\udc5c\ud835\udc5f =\ud835\udc4a\u210e\ud835\udc5c\ud835\udc59\ud835\udc52 \ud835\udc4f\ud835\udc5c\ud835\udc51\ud835\udc66 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54)\u00d710!\ud835\udc47\ud835\udc5c\ud835\udc61\ud835\udc4e\ud835\udc59 \ud835\udc59\ud835\udc52\ud835\udc5b\ud835\udc54\ud835\udc61\u210e (\ud835\udc5a\ud835\udc5a)!  While healthy condition factor varies by species, within a species, a higher condition factor is broadly indicative of better \u201ccondition\u201d. Declining condition factor is a common attribute amongst stressed fish, particularly in fish undergoing heat stress, and may be attributed to non-optimal temperatures for energy assimilation (Bj\u00f6rnsson et al., 1989; Irons et al., 2007; Kappenman et al., 2009; Meffe, 1992; Yoon et al., 2019). Increased rearing temperature has been shown to lower condition in juvenile lake and shovelnose sturgeon (Kappenman et al., 2009; Yoon et al., 2019). Boucher et al. (2014) found the same trend in larval white sturgeon (Acipenser transmontanus).  Somatic indices of various organs are also used to quantify overall health of fish, including the:  hepatosomatic index (HSI), cardiosomatic index (CSI), and brain somatic index (BSI). These indices are all calculated based on the relationship between the mass of the individual organ and the total mass of the fish.   8 \ud835\udc46\ud835\udc5c\ud835\udc5a\ud835\udc4e\ud835\udc61\ud835\udc56\ud835\udc50 \ud835\udc56\ud835\udc5b\ud835\udc51\ud835\udc52\ud835\udc65 = \ud835\udc42\ud835\udc5f\ud835\udc54\ud835\udc4e\ud835\udc5b \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 \ud835\udc54\ud835\udc47\ud835\udc5c\ud835\udc61\ud835\udc4e\ud835\udc59 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 \ud835\udc54 \u00d7 100%  Like condition factor, HSI, CSI, and BSI are similarly affected by environmental stressors, but less is known about how they are affected by temperature especially on short time scales (e.g., hours to days; Eifert et al., 2015; Johansen et al., 2011; Medcalf et al., 2021). In addition to overall health, HSI can indicate changes to metabolism and lipid and glycogen reserves as a result of stress (Chellappa et al., 1995; Morrison et al., 2020). The HSI of two geographically distinct populations of juvenile lake sturgeon decreased as a result of a 30 day acclimation to higher rearing temperatures (Bugg et al., 2020). In species such as Arctic char (Salvelinus alpinus), heart rate increases in response to heat stress as animals increase their circulatory capacities to cope with increased tissue oxygen demand. This reaction may build heart muscle over time and increase CSI (Gilbert and Farrell, 2021; Gilbert et al., 2020). Finally, the brain uses a disproportionately high amount of energy relative to its weight because of the high metabolic demands associated with neural processing (Soengas and Aldegunde, 2002; Van Ginneken et al., 1996). During periods of heat stress, metabolic demand can overwhelm supply, which may result in the depletion of glucose reserves and decreased BSI (Schulte, 2015).  To mitigate the effects of heat stress, fish can acclimate and alter their thermal tolerance by regulating the expression of heat shock proteins (Hsps). Hsps are one facet of a set of cellular responses known collectively as the cellular stress response (CSR). The CSR is a highly conserved collection of cellular responses that maintain and restore protein homeostasis (K\u00fcltz, 2005). Hsps are similarly highly conserved and have been found in every organism studied to date (Fangue et al., 2006; Garbuz and Evgen\u2019ev, 2017; Krebs and Feder, 1997). They are   9 grouped according to their molecular weights and there are three major families: Hsp90s (85-90kDa), Hsp70 (69-73kDa), and low molecular weight Hsps (16-47kDa) (Garbuz and Evgen\u2019ev, 2017). Unlike low-molecular-weight Hsps, some members of the Hsp90 and Hsp70 families are expressed constitutively (known as heat shock cognates) in cells when an organism is not stressed. When expressed constitutively, they aid with protein metabolism and act as molecular chaperones (Chen et al., 2018; Garbuz and Evgen\u2019ev, 2017). Inducible Hsps are preferentially transcribed during periods of thermal stress and their presence, which can increase by multiple orders of magnitude in a matter of minutes, has been linked to increased thermotolerance (Tomanek and Somero, 2002). While there is not a 1:1 relationship between mRNA transcription and protein translation, increased transcription of Hsp mRNA has been found to lead to a similarly rapid increase in Hsp translation (Buckley et al., 2006; Mirault et al., 1977). In insects, studies have shown that inhibition of Hsp expression suppressed thermal tolerance, while additional expression increased it (Feder et al., 1996; Lu et al., 2016; Rinehart et al., 2007). Once upregulated, Hsps help mitigate cellular damage by binding and stabilizing proteins. Hsps then either catalyze protein refolding or, if the protein is damaged beyond repair, Hsps transfer the protein to a degradation pathway (Chen et al., 2018; Fangue et al., 2006). Hsp70 upregulation appears to be the most conserved response to heat shock (Bugg et al., 2020; Werner et al., 2007; Yebra-Pimentel et al., 2020). In white sturgeon, acute heat shock increased Hsp60 and Hsp70 expression, the latter being the most upregulated and thus a more sensitive biomarker (Deng et al., 2009).     10 1.5 White sturgeon (Acipenser transmontanus) White sturgeon (Acipenser transmontanus) are part of the genus Acipenser, which is comprised of 17 extant sturgeon species, which inhabit freshwater and estuarine water systems in Asia, Europe, and North America (Birstein and Bemis, 1997). All sturgeon are characterized by a number of traits: they are large, cartilaginous, benthic feeders that have long lifespans, mature slowly, migrate extensively, and spawn intermittently (Lebreton et al., 2004). Sturgeon are known as \u2018living fossils\u2019 because their morphology has remained largely unchanged relative to the earliest sturgeon fossil records from the Upper Crustaceous period (Gardiner, 1984). White sturgeon are the largest freshwater fish in North America, growing up to 6m long and weighing up to 800kg (Hildebrand et al., 2016). Their range extends along the West coast of North America, from Northern Mexico to Alaska, but they are typically confined to a few river basins, including: the Sacramento \u2013 San Joaquin, the Columbia, and the Fraser (Ruiz-Campos et al., 2011). After surviving for millennia, sturgeon populations have been devastated by human activity over the last 150 years, to the point where many species are in danger of extinction (Gessner et al., 2006; Hildebrand et al., 2016; Lebreton et al., 2004).  In Canada, there are six distinct populations (Lower Fraser River, Mid Fraser River, Upper Fraser River, Upper Columbia River, Nechako River, and Kootenay River), four of which are considered endangered (Upper Fraser River, Upper Columbia River, Nechako River, and Kootenay River; Fisheries and Oceans Canada, 2014; Hildebrand et al., 2016). Population decline has been caused by several anthropogenic activities including overexploitation through commercial fishing in the early 1900s. Despite a ban on commercial fishing, and the development of hatchery programs, white sturgeon populations continue to decline (Hildebrand et al., 2016). White sturgeon are particularly susceptible to anthropogenic   11 impacts due to their life history and requirement for different habitats throughout different life stages (Auer, 1996; Boreman, 2005; Jager et al., 2001; Parsley and Kappenman, 2000). White sturgeon have five defined life history stages \u2013 egg\/embryo, yolk sac larvae (YSL), feeding larvae, juvenile, and adult (Deng et al., 2002; Hildebrand et al., 2016). The focus of this thesis on the early portion of the juvenile stage, which begins between 20 and 45 days post-hatch (dph) when white sturgeon metamorphose from their feeding larval stage, having developed a full complement of scutes and fins (Deng et al., 2002). Their early life stages are particularly challenging and are marked by multiple bottlenecks to survival and consequent high mortality rates (Hildebrand et al., 2016). Recovering from population collapse is especially difficult for white sturgeon as they take a long time to reach sexual maturity and reproduce infrequently (Boreman, 2005). Consequently, minimizing mortality during the first year of life is critical to white sturgeon population recovery (Gross et al., 2002).  To reduce early life mortality, it is paramount that we gain a better understanding of the environmental factors that affect white sturgeon during this precarious period.   1.6 The Nechako River The Nechako River, which continues to suffer from white sturgeon population collapse, has been impounded by the Kenney dam since the 1950s in order to supply electricity and smelt aluminum at Rio Tinto Alcan\u2019s nearby Kitimat plant (4Thought Solutions Inc., 2005). Saik\u2019uz and Stellat\u2019en First Nations, whose land on which the Kenney dam was built, have described environmental degradation and harm to salmon and white sturgeon populations since the dam was built (Bennett, 2021; Saik\u2019Uz First Nation, 2019).    12 In addition to negatively altering habitats, dams may compound the effects of climate change and global warming (Mantua et al., 2010; Nilsson et al., 2005). Specifically, reduced flow rates in the summer can lead to increased water temperatures downstream. To mitigate this, many dams utilize spillways to increase water flow in order to keep water temperatures within an acceptable range (Pittock and Hartmann, 2011).  On the Nechako River, dam operators are able to effect water temperature downstream of the Kenney Dam by releasing surface water from the Nechako Reservoir via the Skins Lake Spillway. In the 1980s, a water management program was devised for the Nechako River, which established an upper temperature threshold for the river. This threshold was based upon research on migrating sockeye salmon (Oncorhynchus nerka) and was set at 20\u00b0C (Macdonald et al., 2012). However, due to the lack of research on the thermal tolerance of white sturgeon, it is unclear whether this 20\u00b0C threshold is acceptable. This thesis aims to fill this void. By understanding the thermal tolerance of the early life stages of white sturgeon from the Nechako River system and how temperatures around and above 20\u00b0C affect various somatic indices and thermal tolerance, this thesis addresses whether the 20\u00b0C threshold mandate is appropriate for white sturgeon.  1.7 Thesis objectives The overall goal of this thesis was to investigate the effect of temperature acclimation and rate of temperature increase on the physiology of juvenile white sturgeon at various levels of biological organization, including mRNA expression of Hsps, size, somatic indices, thermal   13 tolerance, and survival. These experiments will provide valuable information on the temperature sensitivity and thermal tolerance of juvenile white sturgeon during their first summer of development, which will help inform conservation efforts and reservoir management decisions.  This thesis can be divided into two main objectives, which are as follows:  1.7.1 Determine the effect of temperature acclimation on survival, condition factor and thermal tolerance To do this, juvenile white sturgeon were acclimated to one of four ecologically relevant temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) for two weeks. It was hypothesized that thermal tolerance, final condition factor, final size, capacity to acclimate, and survival would all be affected by acclimation temperature. Sturgeon acclimated to warmer temperatures were predicted to have increased thermal tolerance (measured by CTmax). Alternatively, if 20\u00b0C were above the thermal limit of juvenile white sturgeon, then capacity to acclimate (measured by ARR), final condition factor, final size, and survival would be lower in the higher acclimation treatments.   1.7.2 Determine the effect of heating rate during CTmax on thermal tolerance, somatic indices, and Hsp expression To do this, juvenile white sturgeon underwent CTmax trials using one of three heating rates (0.3\u00b0C\/min (a typical rate of heating during CTmax tests), 0.03\u00b0C\/min, and 0.003\u00b0C\/min). It was hypothesized that heating rate would affect thermal tolerance and Hsp expression. Sturgeon were predicted to have lower thermal tolerance and higher Hsp mRNA expression in   14 the slower heating rates. Furthermore, mRNA expression of HSP was quantified in high and low CTmax performers to determine if expression levels differed between these two groups. This thesis also sought to characterize the effect of heating rate on various somatic indices (condition factor, BSI, CSI, and HSI) as these metrics have not been measured after short-term thermal stress. If the duration (or amount) of stress was sufficient, then condition factor, BSI, and HSI would be expected to decrease, while CSI would be expected to increase with an increase in heating rate.   15 Chapter 2: The effects of acclimation temperature and age on thermal tolerance in juvenile white sturgeon  2.1  Introduction  Temperature has been coined the \u201cabiotic master factor\u201d as it affects physiology, behaviour, and ecology (Abram et al., 2017; Brett, 1971; Bugg et al., 2020; McArley et al., 2017). Ectotherms are especially sensitive to temperature changes as their internal body temperatures are dependent on environmental temperature (Hochachka and Somero, 2002; Schulte, 2015). In fish, early life stages are the most vulnerable to extreme temperatures (Dahlke et al., 2020; P\u00f6rtner and Farrell, 2008; Rombough, 1988). As temperatures increase worldwide due to climate change, more species will be exposed to temperatures that exceed their thermal range (Beitinger and Lutterschmidt, 2011; Dahlke et al., 2020). Increasing temperatures are predicted to decrease the abundance of freshwater habitats, which will disproportionately affect cold-water fish (Comte et al., 2013).  Temperature acclimation is the reversible physiological and biochemical changes in response to a thermal stressor and it allows organisms to shift their thermal tolerance range (Hazel and Prosser, 1974; Kingsolver and Huey, 1998; Lagerspetz, 2006). Acclimation to warmer temperatures can increase an organism\u2019s upper thermal limit and help organisms cope with the unprecedented environmental change brought about climate change (Bugg et al., 2020; McArley et al., 2017; Somero, 2010; Zhang and Kieffer, 2014).   Most studies used to inform the thermal tolerance range for juvenile white sturgeon have been conducted on southern populations \u2013 primarily from the Sacramento-San Joaquin Delta \u2013   16 that experience warmer water temperatures than white sturgeon in Northern British Columbia (Cech et al., 1984; Deng et al., 2002; Deng et al., 2009; Wang et al., 1985). Growth of the juvenile white sturgeon (0.6g) native to the Sacramento-San Joaquin Delta is maximized at 20\u00b0C, which is the mean water temperature of their native nursery habitat (Cech et al., 1984; Lebreton et al., 2004). Above 20\u00b0C, there was increased mortality and growth was reduced, indicating that temperatures above 20\u00b0C may impact survival (Cech et al., 1984). Increased mortality above 20\u00b0C has also been observed in the embryonic and YSL phase of development in white sturgeon from the Sacramento-San Joaquin Delta and the Nechako River (Cech et al., 1984; Cheung, pers. comm; McAdam, pers. comm; Wang et al., 1985). While no studies have directly compared the thermal tolerance of white sturgeon from different river systems, independent studies have found that white sturgeon from more southern rivers have higher upper thermal limits than those from more northern rivers (Golder Associates Ltd., 2010; Wang et al., 1985). These findings demonstrate the need for population specific studies on thermal tolerance especially for conservation efforts. The Nechako White Sturgeon Recovery Initiative (NWSRI) rears sturgeon at 15\u00b0C to maximize growth and survival as it mimics the natural environment (pers. comms. Steve McAdam). The aim of this thesis was to provide more insight on the effects of temperature on juvenile white sturgeon in the Nechako River. White sturgeon transition to their juvenile stage during the summer months when river temperatures are at their warmest (Hildebrand et al., 2016). The Kenney dam on the Nechako River in northwestern British Columbia is currently mandated to keep water temperatures below 20\u00b0C; however, this threshold was established for migrating sockeye salmon and did not take into account the white sturgeon (Macdonald et al., 2012). Despite this mandate, as a result of a record-breaking heat wave in British Columbia in   17 Summer 2021, water temperature on the Nechako River rose above 20\u00b0C for nearly four weeks throughout July and August, with maximum temperatures reaching 22.36\u00b0C. Average water temperature between June 1, 2021 and August 31, 2021 was 17.63 \u00b1 2.86\u00b0C (Extracted from the Environment and Climate Change Canada Real-time Hydrometric Data website [https:\/\/wateroffice.ec.gc.ca\/mainmenu\/real_time_data_index_e.html] on September 20, 2021). To better inform dam management strategies and determine whether the 20\u00b0C threshold is appropriate for early life stages of white sturgeon, Chapter 2 examined the effects of acclimation temperature on juvenile white sturgeon survival, final size, final condition factor, and thermal tolerance at two different ages. To address these questions, juvenile white sturgeon obtained from the Vanderhoof hatchery on the Nechako River were acclimated to one of four temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) for one of two, two-week trials. The acclimation temperatures were selected based on current and projected water temperatures on the Nechako River, with the mandated 20\u00b0C falling in the middle. The trials took place in July and August 2019, when rivers would be at their warmest. Following acclimation, CTmax and final condition factor were used as proxies for upper thermal tolerance and general health respectively. Previous research on the development of thermal tolerance by Cheung (2019) and Hines (pers. comms.) found that white sturgeon thermal tolerance plateaued by 40 and 54 dph respectively. Since white sturgeon in the current experiment underwent CTmax trials at 51 and 80 dph, it was predicted that thermal tolerance would have plateaued and not differ between age cohorts. It was hypothesized that CTmax, final condition factor, final size, and survival would all be significantly affected by acclimation temperature. Acclimation to warmer temperatures was predicted to increase thermal tolerance. If acclimation to temperatures in excess of 20\u00b0C was approaching (or above) the thermal limit of the fish, then it is predicted their capacity to acclimate (measured by   18 ARR), final condition factor, final size, and survival would be decreased in the 21\u00b0C and 24\u00b0C treatments.   2.2 Methods 2.2.1 White sturgeon broodstock and holding In June 2019, 600 juvenile white sturgeon from four families (150 per family) were acquired through induced wild broodstock spawning at the White Sturgeon Recovery Facility in Vanderhoof, BC. The four families were created by crossing each female (4A0C59156C, 452A4D4A58, 6C00072619, 7F7D782004) with mixed milt from nine males (6C00072501, 6C00072551, 412466701E, 7F7B0B2B22, 0A1820245D, 0A1820507E, 7F7D7A574F, 4124705139, 4A0C480815). At 28 dph, the white sturgeon were transported by plane in plastic bags filled with oxygen and cooled by ice packs to the Department of Zoology at the University of British Columbia. Prior to the start of the experiment, the white sturgeon were held in a large flow-through holding tank (700L) in dechlorinated city water maintained at 15\u00b0C. Fish were held for one week to allow them to recover from transport stress before experiments were initiated. Fish were fed ad libitum three times daily with a hatchery mixture (EWOS #0 and #1, mysis crumble, and krill powder). The light:dark cycle was kept at 16h light:8h dark to mimic the natural environment at this time of year. Water quality was assessed daily by measuring ammonia, pH, and dissolved oxygen levels. Water quality was maintained within an acceptable range for the duration of the study (ammonia < 0.25ppm, 6.8 < pH < 7.2, dissolved oxygen > 90%). All experiments were approved by the University of British Columbia animal care committee in accordance with the Canadian Council for Animal Care, protocol number A19-0284-A005.   19 2.2.2 Temperature acclimation period Two separate acclimation trials were conducted, one starting in July at 37 dph and the other in August at 66 dph. White sturgeon were haphazardly selected from the holding tank and assigned to one of four temperature acclimation treatments (15, 18, 21, or 24\u00b0C), each consisting of a 200L temperature controlled water bath with three replicate aquaria (20L) per temperature. Fish were transferred to their replicate aquaria with the water bath initially at 15\u00b0C. Then the temperature of the water bath was increased at a rate of 3\u00b0C\/day until the respective target acclimation temperatures were reached at which point fish were allowed to acclimate to the respective temperature for two weeks. During this time, they were fed ad libitum three times daily with the same feed as above. Uneaten food and feces were siphoned from the bottom of the tank within one hour after each feeding. All aquaria for each temperature treatment received inflowing water from a header tank that was maintained at the target temperature. Header tanks and water baths were heated using heater sticks (finnex TITANIUM 300+) controlled by temperature controllers (Fisher Scientific Traceable Digital Temperature Controller), and water pumps (VicTsing 400GPH) were used to ensure homogenous mixing. The system was designed so that there was no water mixing between replicate aquaria by ensuring that water flow was unidirectional. Each replicate aquarium was equipped with an air stone to ensure adequate aeration and water mixing. To minimize water fouling, a flow-through system was used, which allowed for around 20 turnovers per day. One aquarium per temperature treatment was equipped with a temperature logger (HOBO Tidbit MX2203) to allow for continuous temperature monitoring. Temperature in every aquarium was measured manually twice daily using a temperature probe (HANNA checktemp   20 1). Additionally, ammonia, pH, and dissolved oxygen were monitored, with measurements being taken once daily. Water quality was maintained within the same acceptable range as above for the duration of the study.  2.2.3 Thermal tolerance and critical thermal maximum testing Thermal tolerance was assessed using a standard CTmax assay. Three CTmax systems were built using 5L aquariums. Each aquarium was equipped with an air stone, a water pump (VicTsing 80GPH submersible water pump) and a heater stick (finnex TITANIUM 300+). The water pump and heater stick were isolated from the rest of the aquarium using a mesh screen to ensure that fish were not able to directly contact with either. During the CTmax trial, temperature was continuously recorded using a temperature probe (HANNA checktemp 1). Food was withheld 24 hours prior to the start of CTmax. The following day five fish were randomly selected and removed from each of the three replicates for a given temperature (n=15 per temperature treatment) to measure CTmax. The CTmax trials of all three replicates for each acclimation temperature were run concurrently. Prior to the trial, the fish were placed in the CTmax aquaria for one hour to allow them to become accustomed to their surroundings. For the CTmax trial, water temperature was increased at a constant rate of 0.3\u00b0C\/minute, as described by Becker and Genoway (1979). CTmax was determined as the temperature at which a fish experienced LOE and was no longer able to right itself in response to two consecutive tail prods. At this point, water temperature and time from the start of the trial were recorded. After LOE, fish were removed and euthanized using 200mg\/L MS-222 buffered with 400mg\/L sodium bicarbonate.    21 2.2.4 Mass, total length, and condition factor After fish were euthanized, total length (mm) and mass (g) were immediately measured.  Fish were blotted dry using Kimwipes prior to being weighed (Sartorius B120S-0KR). Condition factor was then calculated, as follows: \ud835\udc36\ud835\udc5c\ud835\udc5b\ud835\udc51\ud835\udc56\ud835\udc61\ud835\udc56\ud835\udc5c\ud835\udc5b \ud835\udc53\ud835\udc4e\ud835\udc50\ud835\udc61\ud835\udc5c\ud835\udc5f =\ud835\udc4a\u210e\ud835\udc5c\ud835\udc59\ud835\udc52 \ud835\udc4f\ud835\udc5c\ud835\udc51\ud835\udc66 \ud835\udc5a\ud835\udc4e\ud835\udc60\ud835\udc60 (\ud835\udc54)\u00d710!\ud835\udc47\ud835\udc5c\ud835\udc61\ud835\udc4e\ud835\udc59 \ud835\udc59\ud835\udc52\ud835\udc5b\ud835\udc54\ud835\udc61\u210e (\ud835\udc5a\ud835\udc5a)!   2.2.5 Statistical Analysis All statistical analyses were performed using R Studio (Version 1.1.423) and alpha was set at 0.05 throughout. Prior to analyzing the dataset, the tank effect on CTmax for each acclimation temperature was assessed using a one-way analysis of variance (ANOVA) with tank ID (A, B, or C) as the factor. There was no effect of tank on CTmax for any of the acclimation temperatures in either age cohort, so tank effect was excluded as a random effect.  The effect of acclimation temperature and age on survival was tested using a logistic regression. The effect of acclimation temperature and age on CTmax was tested using a two-way ANOVA, followed by a post-hoc Tukey HSD, with age cohort (37-51 dph or 66-80 dph), and acclimation temperature (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) as factors. The effect of acclimation temperature on final condition factor, mass, and length was assessed using a one-way ANOVA, followed by a post-hoc Tukey HSD, with acclimation temperature (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) as a factor. For final length and mass, the two age cohorts were analyzed independently because the fish were developing rapidly. Final condition factor of the two age cohorts was also analyzed independently because condition factors in the two 15\u00b0C acclimation treatments were   22 significantly different. The difference in final condition factor between the two groups was hypothesized to be due to the different feeding regimes employed at the Nechako White Sturgeon Recovery Initiative (NWSRI) and the aquatics facility at the aquatic facility (Initiative for the Study of the Environment and its Aquatic Systems [InSEAS]) at University of British Columbia (UBC). Assumptions of normality and homogeneity of variances were determined through visual inspection and all data met assumptions for these analyses.  2.3 Results 2.3.1 Effect of acclimation temperature and age on thermal tolerance and acclimation capacity Thermal tolerance was significantly affected by acclimation temperature and age (two-way ANOVA, F3,111 = 204.89, p < 0.0001 and F1,111 = 6.40, p < 0.05; Table 2.1 and Figure 2.1). There was also a significant interaction between the two (two-way ANOVA, F3,11 = 5.07, p < 0.005). Thermal tolerance differed with age in the 18\u00b0C and 21\u00b0C acclimation treatments (p < 0.01 and p < 0.01 respectively), in which the 37-51 dph white sturgeon had a higher CTmax. Warmer acclimation temperature significantly increased CTmax in both age groups (p < 0.001), except between 21\u00b0C and 24\u00b0C treatments in the 37-51 dph white sturgeon. Average CTmax in the 15\u00b0C acclimation treatment was 30.28 \u00b1 0.14\u00b0C for 37-51 dph fish and 30.20 \u00b1 0.12\u00b0C for 66-80 dph fish. In the 18\u00b0C acclimation treatment, average CTmax was 32.08 \u00b1 0.11\u00b0C for the 37-51 dph fish and 31.43 \u00b1 0.18\u00b0C for the 66-80 dph fish. Average CTmax in the 21\u00b0C treatment was 33.11 \u00b1 0.12\u00b0C for the 37-51 dph fish and 32.6 \u00b1 0.15\u00b0C for the 66-80 dph fish. Finally, in the 24\u00b0C treatment average CTmax was 33.57 \u00b1 0.2\u00b0C in the 37-31 dph fish and 33.87 \u00b1 0.13\u00b0C.    23 ARR remained relatively consistent between acclimation temperatures in the 66-80 dph white sturgeon (at a value of about 0.4), but the ARR of the 37-51 dph white sturgeon decreased as acclimation temperature increased (Table 2.2), from a value of 0.6 at 15-18\u00b0C to about 0.15 at 21-24\u00b0C.  2.3.2 Effect of acclimation temperature on size, condition factor, and survival Final length and mass did not differ between acclimation treatments at the end of the two-week acclimation (p > 0.05; Table 2.3). Survival was not affected by acclimation temperature or age (p > 0.05; Table 2.4). Final condition factor differed significantly between acclimation temperatures in both 37-51 dph and 66-80 dph white sturgeon (F3,103 = 5.95, p < 0.001 and F3,101 = 11.11, p < 0.0001, respectively; Table 2.3; Figure 2.2). Condition factor for 37-51 dph white sturgeon was significantly lower between 15\u00b0C and 21\u00b0C (p < 0.01); 15\u00b0C and 24\u00b0C (p < 0.05); and 18\u00b0C and 21\u00b0C (p < 0.05). For 66-80 dph, the white sturgeon acclimated to 21\u00b0C and 24\u00b0C had significantly lower condition factor than those acclimated to 15\u00b0C and 18\u00b0C (p < 0.05). Morphometrics of both age cohorts are reported in Table 2.5.     24 Table 2.1 The effect of acclimation temperature and age on the CTmax of juvenile white sturgeon, from a two-way ANOVA. Asterisk (*) denotes significance at alpha = 0.05. Measurement Variables d.f. F p-value CTmax TA 3 204.893 <0.001* Age 1 6.404 0.01278* TA x Age 3 5.068 0.00251*    Table 2.2 Acclimation response ratio of 37-51 dph and 66-80 dph juvenile white sturgeon. Change in Ta(\u00b0C) 37-51 dph 66-80 dph                                                  ARR 15-18 0.60 0.4 18-21 0.33 0.4 21-24 0.17 0.43    Table 2.3 The effect of acclimation temperature on various traits of 37-51 dph and 66-80 dph juvenile white sturgeon, from a two-way ANOVA. Asterisk (*) denotes significance at alpha = 0.05.  Measurement d.f. F p-value 37-51 dph Mass 3 0.997 0.397  Length 3 2.132 0.101  Condition factor 3 5.951 <0.001* 66-80 dph Mass 3 0.166 0.919  Length 3 0.315 0.815  Condition factor 3 11.11 <0.001*   Table 2.4 Effect of acclimation temperature and age on survival of juvenile white sturgeon, from a logistic regression. Measurement Variables d.f. Deviance (explained) p-value Survival Ta 3 3.559 0.313 Age 1 0.042 0.837 Ta x Age 3 6.678 0.083   25  Table 2.5 Morphometrics for 37-51 dph and 66-80 dph juvenile white sturgeon at the end of a two-week acclimation to one of four temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C). Final average mass and length \u00b1 standard error (sample size indicated in brackets). Statistical analysis for morphometric data in Table 2.3. Ta(\u00b0C) 37-51 dph 66-80 dph                 Mass (g) 15 0.45 \u00b1 0.048 (n = 23) 1.24 \u00b1 0.088 (n = 28) 18 0.41 \u00b1 0.022 (n = 28) 1.26 \u00b1 0.096 (n = 28) 21 0.48 \u00b1 0.023 (n = 29) 1.17 \u00b1 0.107 (n = 26) 24 0.44 \u00b1 0.039 (n = 27) 1.14 \u00b1 0.104 (n = 24)                       Length (mm) 15 44.3 \u00b1 1.75 (n = 23) 65.38 \u00b1 1.88 (n = 23) 18 43.72 \u00b1 0.89 (n = 28) 66.47 \u00b1 2.07 (n = 28) 21 47.85 \u00b1 0.97 (n = 29) 67.32 \u00b1 2.15 (n = 29) 24 45.56 \u00b1 1.52 (n = 27) 66.86 \u00b1 2.12 (n = 27)     26  Figure 2.1 CTmax for juvenile white sturgeon following a two-week acclimation to one of four temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C) and one of two age groups (37-51 dph and 66-80 dph). Black dots represent individual data points, while the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistically significance a given age cohort. Asterisk (*) denotes a statistically significant difference between 37-51 dph and 66-80 dph sturgeon acclimated to the same temperature at alpha = 0.05. N= 15 per acclimation temperature per age cohort.        **abccabcd2931333515 18 21 24Acclimation temperature (\u00b0C)CTmax (\u00b0C)37\u221251dph66\u221280dph  27  Figure 2.2 Final condition factor of 37-51 dph (A) and 66-80 dph (B) juvenile white sturgeon following a two-week acclimation to one of four temperatures (15\u00b0C, 18\u00b0C, 21\u00b0C, and 24\u00b0C). Black dots represent individual data points, while the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistically significance a given age cohort at alpha = 0.05.  For 37-51 dph sturgeon N15\u00b0C = 23, N18\u00b0C = 28, N21\u00b0C = 29, and N24\u00b0C = 27. For 66-80 dph sturgeon N15\u00b0C = 28, N18\u00b0C = 28, N21\u00b0C = 26, and N24\u00b0C = 24.     aacbbc0.30.40.50.615 18 21 24Acclimation temperature (\u00b0C)Condition factorAaabb0.30.40.50.615 18 21 24Acclimation temperature (\u00b0C)B  28 2.4 Discussion The objective of this chapter was to assess the effects of acclimation temperature and age on thermal tolerance, survival, final size, final condition factor, and capacity to acclimate in juvenile white sturgeon to help inform conservation efforts on the Nechako River and determine whether the current 20\u00b0C upper water temperature mandate is appropriate. Broadly, the data indicated that while acclimation to warmer temperature conferred higher CTmax, overall condition decreased above 18\u00b0C indicating that the 20\u00b0C mandate may be too warm. There were effects of acclimation temperature and age on thermal tolerance, as well as an interaction effect between the two. Acclimation to warmer temperatures increased thermal tolerance for both age cohorts and interestingly the 37-51 dph sturgeon had significantly higher thermal tolerance (as indicated by CTmax values) than the 66-80 dph sturgeon following acclimation to 18\u00b0C and 21\u00b0C. Final mass, final length, and survival did not differ between temperature treatments. For both age cohorts, condition factor was lower in the 21\u00b0C and 24\u00b0C acclimation treatment compared to the 15\u00b0C treatment.  As predicted, and consistent with results of studies on multiple species of fish, the current findings indicate that acclimation to warmer temperatures confers greater thermal tolerance in juvenile white sturgeon (Becker and Genoway, 1979; Bugg et al., 2020; Fangue et al., 2006; Zhang and Kieffer, 2014). In 37-51 dph fish, CTmax increased progressively from about 30.3\u00b0C in fish acclimated to 15\u00b0C, to 33.6\u00b0C in fish acclimated to 24\u00b0C. In 66-80 dph sturgeon, CTmax increased progressively from 30.2\u00b0C in fish acclimated to 15\u00b0C to 33.9\u00b0C in fish acclimated to 24\u00b0C. The current study does not address the mechanisms through which acclimation occurs, therefore more research is required to understand the biological underpinnings of thermal tolerance. Bugg et al. (2020) found that acclimation affected juvenile lake sturgeon metabolic   29 rate, as well as the mRNA expression of transcripts of several genes related to heat shock (Hsp70, 90a, and 90b), hypoxia (HIF-1\u03b1), and the sodium-potassium pump (Na+\/K+ ATPase-\u03b11). As this is a closely related species, these potential thermal tolerance mechanisms warrant further research in white sturgeon and Hsp levels are measured in the experiments of chapter 3. The ability to acclimate and increase thermal tolerance will be paramount to species\u2019 survival as climate change not only drives an increase in mean water temperature, but also more extreme maximum temperatures. While both age groups (37-51 dph and 66-80 dph) were able to increase their thermal tolerance in response to acclimation, the relationship between acclimation temperature and CTmax differed between the groups. The older sturgeon increased their thermal tolerance by the same amount between each acclimation temperature, which yielded a consistent ARR of about 0.4 in fish acclimated to higher temperatures. Other fish species from similar latitudes have a mean ARR of around 0.32 (Morley et al., 2019). In the younger sturgeon, the relationship between acclimation temperature and thermal tolerance was curvilinear and their ARR decreased progressively with temperature from 0.6 in fish acclimated from 15 to 18\u00b0C, to 0.33 in fish acclimated to 21\u00b0C and 0.17 in those acclimated to 24\u00b0C. Despite the younger sturgeon having significantly higher CTmax at 18\u00b0C and 21\u00b0C, their thermal tolerance was nearly identical to the older sturgeon at 24\u00b0C. These findings may indicate that within a specified temperature range, 37-51 dph white sturgeon experience a window of heightened thermal plasticity. The curvilinear relationship and decreasing ARR illustrates that the 37-51 dph white sturgeon were less thermally plastic at higher temperatures and may indicate that they have reached their capacity to acclimate to higher temperatures. Juvenile shortnose and lake sturgeon have similarly exhibited decreasing ARRs when acclimation temperatures were increased from 15\u00b0C to 20\u00b0C and 20\u00b0C to   30 24\u00b0C, respectively (Bugg et al., 2020; Zhang and Kieffer, 2014).  The relatively constant ARR in the 66-80 dph could indicate that these animals still have the capacity to acclimate to even higher temperatures than 24\u00b0C. In the current study, both cohorts of juvenile white sturgeon exhibited relatively high thermal plasticity, which combined with studies on other sturgeon species, indicates that this characteristic may be a general trait of the sturgeon family (Bugg et al., 2020; Zhang and Kieffer, 2014).  Contrary to predictions, there was no effect of acclimation temperature on survival or final size. It could be that that the two-week acclimation period was too short to see any changes. In southern populations, increased mortality and inhibited growth has been reported in early juvenile white sturgeon acclimated to temperatures above 20\u00b0C for 30 days (Cech et al., 1984). However, consistent with predictions, condition factor decreased significantly with acclimation temperature within each age cohort studied here. Condition factor in the 15\u00b0C acclimated fish differed between the two age cohorts (0.49 in the 37-51 dph relative to 0.43 in the 66-80 dph); however, this was thought to be due to a change in feeding regime between the NWSRI and UBC, rather than a developmental trend. In a study where sturgeon were reared continuously at one facility from embryos to 80 dph, condition factor remained relatively constant at around 0.5 (Cheung, 2019). In both age cohorts in this study, the condition factor of white sturgeon acclimated to 21\u00b0C and 24\u00b0C was significantly lower than 15\u00b0C acclimated fish. In 37-51 dph sturgeon, condition factor decreased from 0.49 at 15\u00b0C to 0.44 for both 21\u00b0C and 24\u00b0C. In 66-80 dph sturgeon, condition factor decreased from 0.43 at 15\u00b0C to 0.37 and 0.36 for 21\u00b0C and 24\u00b0C, respectively. Decreased condition factor may be indicative of a reduction in overall health, which may result in lowered fitness. In Atlantic cod (Gadus morhua), decreased condition factor has been found to correlate with reduced recruitment (R\u00e4tz and Lloret, 2003). In lake sturgeon,   31 higher condition factor prior to a juvenile\u2019s first winter increases the likelihood of overwintering success (Yoon et al., 2019). These results highlight how early rearing environments are critical for long-term success and how a sub-lethal threshold in one environment may be fatal in other circumstances.  While juvenile sturgeon were able to acclimate to temperatures above 20\u00b0C, and acclimation to higher temperatures conferred higher thermal tolerance as indicated by CTmax, these temperatures may have negatively affected health in both the 37-51 dph and 66-80 dph white sturgeon as suggested by changes in condition factor. This may indicate a sub-lethal threshold between 18\u00b0C and 21\u00b0C that could affect an individual\u2019s ability to survive, particularly when exposed to multiple stressors. Follow-up studies should be completed to examine the effects of temperatures within the temperature range (18\u00b0C - 21\u00b0C) that condition factor was found to decrease over. In the absence of better resolution over this range, I recommend considering reducing the upper water temperature limit from 20\u00b0C to 18\u00b0C on the Nechako River. More research is also needed to elucidate the long-term effects of temperature in isolation, and in conjunction with other stressors likely to be experienced in the environment.     32 Chapter 3: The effect of heating rate on thermal tolerance in juvenile white sturgeon  3.1 Introduction Under global warming, mean water temperatures and the frequency of extreme weather events are expected to increase and northern latitudes are predicted to be disproportionately affected by these changes (Hoegh-Guldberg et al., 2018; Vincent et al., 2015). As such, it is vital for conservation efforts to better understand of how organisms respond to temperature stress. Critical thermal tests (CTMs) were developed to assess the thermal limits of organisms (Cowles and Bogert, 1944). However, the ecological relevance of CTmax has been questioned because the rates of temperature increase used for the test far exceed those seen in nature \u2013 the conventional rate for CTmax is 0.3\u00b0C\/min or 432\u00b0C\/day (Beitinger and Lutterschmidt, 2011). The few studies that have used more ecologically relevant heating rates have found that faster heating rates result in higher CTmax, which suggests that current approximations of thermal tolerance based upon CTmax values may greatly overestimate thermal tolerance in nature (Becker and Genoway, 1979; Illing et al., 2020; Kovacevic et al., 2019; Mora and Maya, 2006). This discrepancy is especially relevant considering climate change, as laboratory measurements are used to help inform conservation efforts. When organisms undergo conventional CTmax tests, upper thermal tolerance is thought to be limited by either cardiac or neurological failure (Andreassen et al., 2020; Christen et al., 2018). At slower heating rates, upper thermal tolerance may be limited by a gradual accumulation of cellular damage that incurs from organisms spending prolonged time at temperatures where the rate of cellular damage exceeds the rates of repair (Rezende et al., 2014).    33 The effects of heat stress can be observed at all levels of biological organization (Schulte, 2015). At the whole body level, condition factor is commonly used as measure of overall health and has been found to decrease as a result of thermal stress (Boucher et al., 2014; Bugg et al., 2020; Morrison et al., 2020). At the organ level, changes in BSI, CSI, and HSI have been observed as results of stress (Bugg et al., 2020; Gilbert and Farrell, 2021; Soengas and Aldegunde, 2002). Alteration to heat shock protein (Hsp) transcription is an indicator of heat stress and is also a proposed mechanism to cope with heat stress (Somero, 2020). Hsps are ubiquitous in all species and upregulation at both the mRNA and protein levels can occur in minutes in response to thermal stress (Tomanek and Somero, 2000). mRNA expression of Hsps can be upregulated many fold and while there is not a 1:1 relationship with protein translation, upregulation does lead to a similar pattern of protein translation (Buckley et al., 2006; Mirault et al., 1977). Hsps may help cells cope with the effects of thermal stress by mitigating damage caused by malfunctioning proteins; binding to and stabilizing proteins at risk of degrading; refolding or breaking down damaged proteins (Chen et al., 2018; Garbuz and Evgen\u2019ev, 2017; Tomanek and Somero, 2000). The magnitude of Hsp upregulation has been found to correlate with thermal tolerance (Krebs and Feder, 1997; Tomanek and Somero, 2000). In rainbow trout (Oncorhynchus mykiss) fibroblasts, inhibition of Hsp synthesis prevented the development of thermal tolerance (Mosser and Bols, 1988). In insects, transgenic inhibition of Hsp expression was found to decrease thermal tolerance while activation had the opposite effect (Feder and Krebs, 1998; Feder et al., 1996). Many populations of white sturgeon, including the Nechako River population, are endangered and despite their perilous status, little is known about how they respond to heat stress (Hildebrand et al., 2016). Water temperature on the Nechako River, home to the northernmost   34 population of white sturgeon, fluctuates daily at a rate of 0.004\u00b0C\/min in the summer (Extracted from the Environment and Climate Change Canada Real-time Hydrometric Data web site [https:\/\/wateroffice.ec.gc.ca\/mainmenu\/real_time_data_index_e.html] on September 20, 2021). No known studies have examined how ecologically relevant warming affects the upper thermal tolerance of juvenile white sturgeon. Given this, in Chapter 3 my objective was to determine the effect of heating rate during CTmax assays on thermal tolerance, somatic indices and Hsp expression.  To address this objective, the thermal tolerance of juvenile white sturgeon was examined using three different heating rates during CTmax trials. Of the three heating rates that were tested, one was the conventional rate used by most research groups (0.3\u00b0C\/min), one mimicked natural temperature changes that could be experienced in this river system (0.003\u00b0C\/min) and the other was an intermediate rate (0.03\u00b0C\/min). The thermal tolerance of juvenile white sturgeon was predicted to decrease at slower heating rates as observed in other fish species (Kovacevic et al., 2019). Little is known about the effects of short-term thermal stress on various somatic indices. Thus, in addition to assessing thermal tolerance, this study sought to characterize the effects of heating rate on condition factor, HSI, BSI, and CSI. If the duration (or amount) of thermal stress was sufficient to affect these variables, then condition, HSI, and BSI would be expected to decrease while CSI would be expected to increase. Finally, gill samples were also taken from the bottom eight and the top eight performers during the CTmax trials to measure mRNA expression of various Hsps (Hsp 47, 70, 90a, and 90b). It was hypothesized that heating rate would affect Hsp expression. Hsp expression was expected to be upregulated by the end of the CTmax trials relative to controls. Additionally, . mRNA expression of HSP was quantified in high and low CTmax performers to determine if expression levels differed between these two groups.   35  3.2 Methods 3.2.1 White sturgeon broodstock and holding In August 2020, 300 juvenile white sturgeon (Family 4: one female 0A1820543F, crossed with three males 4527276447, 0A1820505C, 7F7B04052A) were acquired through induced wild broodstock spawning at the White Sturgeon Recovery Facility in Vanderhoof, BC. At 60 dph, the white sturgeon were transported from the White Sturgeon Recovery Facility in Vanderhoof, BC by air in plastic bags filled with aerated water and cooled by ice packs to the Department of Zoology at UBC Vancouver in August, 2020. Fish were randomly divided and held for two weeks in two large flow-through tanks (700L), filled with dechlorinated city water maintained at 15\u00b0C. Fish were fed bloodworms twice a day ad libitum. The light:dark cycle was set to 16h:8h to mimic the natural environment at that time. Water quality was maintained for the duration of holding.  All experiments were approved by the University of British Columbia animal care committee in accordance with the Canadian Council for Animal Care, protocol number A19-0284-A005.  3.2.2 The effect of heating rate on thermal tolerance White sturgeon were haphardly selected from the two 15\u00b0C holding tanks for experimental CTmax trials to assess thermal tolerance.  In each of the CTmax trials, temperature was increased at a constant rate of either 0.3\u00b0C\/min, 0.03\u00b0C\/min, or 0.003\u00b0C\/min until LOE, which was defined as inability to right after two consecutive tail prods. CTmax was recorded as the water temperature at LOE. Once fish attained LOE, they were removed from the aquarium and euthanized with 200mg\/L MS-222 buffered with 400mg\/L sodium bicarbonate.   36 Five trials (45 fish per trial) were run sequentially over the course of two weeks. Three CTmax heating rates were used where temperature was increased at 0.3\u00b0C\/min (taking 1 hour total), 0.03\u00b0C\/min (taking 6 hours total), and 0.003\u00b0C\/min (taking 4.5 days total). Because of the possibility of diurnal effects on thermal tolerance, an additional two trials (second 0.3\u00b0C\/min and third 0.3\u00b0C\/min) were completed to ensure CTmax and Hsp expression were not affected by time of day (Healy and Schulte, 2012).  For all trials, fish were randomly selected from the two large flow-through holding tanks and evenly divided between three aquaria (15L) that were placed within a larger water table (200L). For the first three trials (first 0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min), 45 fish were used. For the finals two trials (second 0.3\u00b0C\/min and third 0.3\u00b0C\/min) 30 fish were used. Fish were weighed (Mettler Toledo, New Classic SG) and total length was measured prior to the start of CTmax. The fish were given one hour to recover from handling stress before CTmax started. The water table was aerated using air stones and water was circulated using multiple water pumps (VicTsing 400GPH). For the 0.3\u00b0C\/min trials, the water in the water table was heated directly by immersed heater sticks (finnex TITANIUM 300+) and the heating rate was monitored using a temperature probe (HANNA checktemp 1). For the 0.03\u00b0C\/min and 0.003\u00b0C\/min trials, a sump (200L) was used to double the total water volume of the system, to ensure water quality over the much longer CTmax trials and allow for slower heating rates. Temperature controllers (Fisher Scientific Traceable Digital Temperature Controller) were used in conjunction with heater sticks (finnes TITANIUM 300+) to slowly increase temperature at the respective rates. Temperature was monitored using both a temperature probe (HANNA checktemp 1) and temperature logger (HOBO Tidbit MX2203) in each aquarium. For the 0.003\u00b0C\/min trial, an infrared security camera (geeni GNC-CW020) was used to monitor the fish 24 hours a day. Prior to the start of the   37 trials, food was withheld for 12 hours, however if the trial lasted more than 12 hours (ie the 0.003\u00b0C\/min trial) then feeding was resumed ad-libitum two times a day within the CTmax trial.   3.2.3 Post-trial sampling and somatic indices  After fish were euthanized, fish were blotted dry with kimwipes and then total mass (Mettler Toledo, New Classic SG) and total length were measured. Gill samples were immediately removed from the top eight (the last eight fish to reach CTmax) and bottom eight performers (the first eight fish to reach CTmax) during each CTmax trial and placed into RNAlater (Thermofisher Scientific, Waltham, USA) and stored at -80\u00b0C for quantification of mRNA expression. Brain, liver, and heart were dissected out and weighed (Sartorius CP124S) and the somatic index for each was calculated ([tissue mass \/ body mass] x 100). Condition factor was calculated using the formula listed above in Section 2.2.4.   3.2.4 mRNA expression Samples in RNAlater were left at room temperature for 24 hours and then placed in a -80\u00b0C freezer. Sample order was randomized for all RNA analysis. Total RNA was extracted from homogenized tissue using a Qiagen RNeasy mini kit according to manufacturer\u2019s protocols. A Nanodrop (Nanodrop 2000, Thermofisher Scientific, Waltham, USA) was used to determine total RNA quantity and quality. Total RNA was stored at -30\u00b0C until further analysis. To treat total RNA with DNase, 1uL of total RNA from each sample was diluted with ultrapure water to a final volume of 8uL and then mixed with 1uL of both DNase 1 reaction buffer and DNase in a 96-well plate. This solution was incubated in a thermal cycler (BIO-RAD T100 Thermal Cycler) at 25\u00b0C for 15 minutes. Next, to inactivate the DNase, 1uL of 25mM EDTA was added, and the   38 solution was incubated at 65\u00b0C for 10 minutes. Complementary DNA (cDNA) was synthesized from the extracted RNA using a Quantabio qScript cDNA Synthesis Kit (Quantabio, Beverly, USA). To synthesize cDNA, 10\u00b5L of master mix (5\u00b5L nuclease-free water, 4\u00b5L 5x reaction buffer, 1uL reverse transcriptase) was added to each well and the plate was incubated at 22\u00b0C for 5 minutes, 42\u00b0C for 30 minutes, 85\u00b0C for 5 minutes, and then held at 4\u00b0C. The cDNA was stored at -30\u00b0C until further analysis. mRNA expression in the sample was measured using quantitative polymerase chain reaction (qPCR). Forward and reverse primers were designed for the reference genes RPS18 and RSP6, and the target genes hsp47, hsp70, hsp90a, and hsp90b (Table 3.1). RSP6 and RPS18 were selected as reference genes because they displayed stable expression across all treatments. All reactions contained 0.075uL of both the forward and reverse primers, 7.5\u00b5L of SYBR Green Mastermix (Thermofisher Scientific), 5.85\u00b5L of ultrapure H2O, and 2\u00b5L of cDNA. For both reference genes, cDNA was undiluted 1:1 with nuclease-free water and for the target Hsp genes a 1 cDNA:10 nuclease-free water dilution was used. The qPCR was performed with a BIO-RAD CFX96 Real-Time System on a 96-well plate. To measure mRNA expression, the following protocol was used: denaturation at 95\u00b0C for 10 min, 40 cycles of denaturation at 95\u00b0C for 15s, annealing at 60\u00b0C for 30s, and extension at 72\u00b0C for 30s. The qPCR was followed by conducting a melt curve. Expression of the gene of interest was normalized to the reference genes (RSP6 and RPS18) using the Vandesompele method and expressed as a relative change compared the controls (Vandesompele et al., 2002).     39 Table 3.1 List of forward and reverse primers and their efficiencies for white sturgeon Rsp6, Rps18, Hsp47, Hsp70, Hsp90a, and Hsp90b. Gene Forward Reverse Efficiency  RPS6 GGACAGGTTGAAGAGCTTGC ATCATCAAGAAGGGCGAGAA 93% RSP18 TCTCTCCAGATCCTCACGCA AAGGACGGCAAATACAGCCA 86%  Hsp47 GACTCCAACGCCTTCAAGAG TGTGATCATGGCTGAGAAGC 100% Hsp70 GAGAGGCTCATTGGAGATGC AAACAGTGTTGCTGGGGTTC 100% Hsp90a GCAGAGGTTCTCGAACTTGG AGACCCTGGTGTCTGTGACC 93% Hsp90b GCAACTTGGTCCTTGCTCTC AGCTCTCAGTCTGGGGATGA 89%   3.2.5 Statistical analysis All statistical analyses were performed using R Studio (Version 1.1.423) and alpha was set at 0.05 throughout. Prior to analyzing the dataset, the effect of aquaria on CTmax for each heating rate was assessed using a one-way ANOVA with tank ID (A, B, or C) as the factor. There was no effect of tank on CTmax for any of the heating rates, so effect of aquaria was excluded as a random effect. The CTmax, Hsp expression, and somatic indices of the three 0.3\u00b0C\/min trials were assessed using a one-way ANOVA. There was no difference between the three 0.3\u00b0C\/min trials so trials were pooled.  Each measurement was analyzed using a one-way ANOVA, followed by a post-hoc Tukey HSD with heating rate as the factor (control, 0.3\u00b0C\/min, 0.03\u00b0C\/min, or 0.003\u00b0C\/min). Each variable (except CTmax) was also analyzed using a two-way ANOVA, followed by a post-hoc Tukey HSD, with CTmax performance (high performer or low performer) and heating rate (0.3\u00b0C\/min, 0.03\u00b0C\/min, or 0.003\u00b0C\/min) as factors. Assumptions of normality and homogeneity of variances were determined through visual inspection and Hsp data was log 2 transformed. All data met assumptions for these analyses.   40 3.3 Results 3.3.1 Effect of heating rate on thermal tolerance There were no diurnal effects on CTmax when fish were heated at 0.3\u00b0C\/min (p > 0.05). Thermal tolerance was significantly affected by heating rate (F2,135 = 515.2, p < 0.0001; Table 3.2; Figure 3.1), with slower heating rates yielding significantly higher CTmax results. Average CTmax increased by about 5\u00b0C between the fast and slowest heating rates. Average CTmax in the conventional heating rate was 29.2\u00b0C \u00b1 0.24\u00b0C and the trial lasted about 1.5 hours. Average CTmax in the 0.03\u00b0C\/min trial was 31.3\u00b0C \u00b1 0.24\u00b0C and the trial lasted about 8 hours.  Average CTmax in the 0.003\u00b0C\/min trial was 34.2\u00b0C \u00b1 0.15\u00b0C and the trial lasted about 4.5 days.    3.3.2 Effect of heating rate and performance on somatic indices Average somatic indices are summarized in Table 3.2. There was no significant effect of heating rates on BSI or CSI (p > 0.05; Table 3.3). For the top and bottom performers, there was no significant effect of heating rate or performance \u2013 or an interaction effect between the two \u2013 for condition factor, BSI, CSI, or HSI (p > 0.05 for all). HSI differed significantly between heating rates and controls (F3,121 = 4.48, p < 0.01) \u2013 controls had significantly greater HSI than sturgeon that experienced heating rates of 0.03\u00b0C\/min (p < 0.05) and 0.003\u00b0C\/min (p < 0.01; Table 3.2; Table 3.4; Figure 3.2). Condition factor was significantly affected by heating rate (F2,153 = 8.23, p < 0.0001) (Figure 3.3). However, condition factor did not differ significantly between controls and sturgeon exposed to different heating rate (p > 0.05 for all).     41 3.3.3 Effect of heating rate and performance on Hsp expression There were no diurnal effects on the expression of any Hsps measured when fish were heated at 0.3\u00b0C\/min (p > 0.05).  3.3.3.1 Hsp47 Expression of Hsp47 was significantly affected by heating rate (F3,94 = 3.26, p < 0.05; Figure 3.4). Sturgeon in the 0.003\u00b0C\/min group had significantly more Hsp47 expression than sturgeon in the 0.03\u00b0C\/min (p < 0.05). When performance was included, Hsp47 expression was affected by heating rate (F2, 72 = 6.47, p < 0.01; Figure 3.5). In the 0.3\u00b0C\/min group, high performers had significantly lower Hsp47 expression than low performers (p < 0.05). Within high performers, Hsp47 expression was significantly greater in sturgeon heated at 0.003\u00b0C\/min than those heated at 0.03\u00b0C\/min (p < 0.01) and 0.3\u00b0C\/min (0.05).  3.3.3.2 Hsp70 Expression of Hsp70 was significantly affected by heating rate (F3,94 = 298.9, p < 0.0001; Figure 3.4). Hsp70 expression of sturgeon in the 0.03\u00b0C\/min and 0.003\u00b0C\/min trials did not differ significantly (p > 0.05), but both had significantly greater Hsp70 expression than controls and sturgeon in the 0.3\u00b0C\/min trial (all p < 0.0001). Fish heated at 0.3\u00b0C\/min had significantly greater expression than control fish (p < 0.0001). When performance was included, there was a significant effect of heating rate (F2,72 = 285.81, p < 0.0001) and performance (F1,72 = 46.84, p < 0.0001) as well as an interaction effect between the two (F2,72 = 5.89, p < 0.005; Figure 3.5). High performers had greater Hsp70 expression than low performers in in the 0.3\u00b0C\/min and 0.003\u00b0C\/min trials (p < 0.0001 and p < 0.01, respectively). For both high and low performers,   42 sturgeon heated at 0.3\u00b0C\/min had significantly lower Hsp70 expression than those heated at 0.03\u00b0C\/min (p < 0.001 for both) and 0.003\u00b0C\/min (p < 0.001 for both).  3.3.3.3 Hsp90a Hsp90a expression was significantly affected by heating rate (F3, 94 = 31.8, p < 0.0001; Figure 3.4). Hsp90a expression was significantly lower in controls and fish heated at 0.3\u00b0C\/min than fish that were in the 0.03\u00b0C\/min (p < 0.01 and p < 0.0001) and 0.003\u00b0C\/min trials (both p < 0.0001). When performance was included, Hsp90a expression was significantly affected by heating rate (F2,72 = 69.13, p < 0.0001; Figure 3.5). Hsp90a expression in high performing sturgeon heated at 0.3\u00b0C\/min was significantly lower than those heated at 0.03\u00b0C\/min (p < 0.001) and 0.003\u00b0C\/min (p < 0.001).  Hsp90a expression of low performing sturgeon increased significantly between each heating rate, with the slowest heating rate having the highest expression.   3.3.3.4 Hsp90b Hsp90b expression was significantly affected by heating rate (F3, 94 = 55.83, p < 0.0001) (Figure 3.4). Controls and sturgeon heated at 0.3\u00b0C\/min did not have significantly different Hsp90b expression. Hsp90b expression increased significantly as heating rate slowed (all p < 0.0001). When performance was included, Hsp90b expression was significantly affected by heating rate (F2,72 = 67.59, p < 0.0001; Figure 3.5). Hsp90b expression in high performing sturgeon heated at 0.3\u00b0C\/min was significantly lower than those heated at 0.03\u00b0C\/min (p < 0.001) and 0.003\u00b0C\/min (p < 0.0001).  Hsp90b expression in high performers was significantly lower in the 0.03\u00b0C\/min than the 0.003\u00b0C\/min trial (p < 0.05). Hsp90b expression of low   43 performing sturgeon increased significantly between each heating rate, with the slowest heating rate having the highest expression (all p < 0.001).  44 Table 3.2 Somatic indices of juvenile white sturgeon in control conditions or one of three heating rates. Average condition factor, BSI, CSI, and HSI with standard error and sample size are provided. Treatments that differ from controls are indicated with an asterisk (*) at alpha = 0.05. Heating rate   Condition factor Control (n = 20) 0.4124 \u00b1\t0.010\t(n\t=\t20) 0.3 (n = 105) 0.4440 \u00b1\t0.006\t(n\t=\t105) 0.03 (n = 45) 0.4148 \u00b1\t0.008\t(n\t=\t45) 0.003 (n = 45) 0.3920 \u00b1\t0.008\t(n\t=\t45)            BSI Control  0.0076 \u00b1\t0.0004\t(n\t=\t20) 0.3 0.0071 \u00b1\t0.0003\t(n\t=\t45) 0.03 0.0076 \u00b1\t0.0003\t(n\t=\t45) 0.003 0.0074 \u00b1\t0.0003\t(n\t=\t45)            CSI Control 0.0034 \u00b1\t0.0003\t(n\t=\t20)\t 0.3 0.0031 \u00b1\t0.0001\t(n\t=\t45) 0.03 0.0033 \u00b1\t0.0002\t(n\t=\t45) 0.003 0.0029 \u00b1\t0.0002\t(n\t=\t45)            HSI Control 0.0199 \u00b1\t0.0013\t(n\t=\t20) 0.3 0.0160 \u00b1\t0.0007\t(n\t=\t45)\t* 0.03 0.0164 \u00b1\t0.0007\t(n\t=\t45)\t* 0.003 0.0152 \u00b1\t0.0007\t(n\t=\t45)\t*   Table 3.3 The effect of heating rate on CTmax, somatic indices, and Hsp expression in juvenile white sturgeon, from a one-way ANOVA. Asterisk (*) denotes significance at alpha = 0.05. Measurement d.f. F p-value  CTmax 3 631.9 <0.001* Condition factor 3 9.406 <0.001* BSI 3 0.726 0.538 CSI 3 1.011 0.39 HSI 3 4.547 0.00443* Hsp47 3 3.256 0.0251* Hsp70 3 298.9 <0.001* Hsp90a 3 31.8 <0.001* Hsp90b 3 55.83 <0.001*   45  Table 3.4 The effect of heating rate and performance on various somatic indices and Hsp expression in juvenile white sturgeon, from a two-way ANOVA. Asterisk (*) denotes significance at alpha = 0.05. Measurement Variable d.f.  F p-value Condition factor Heating rate 2 6.677 0.002* Performance 1 0.031 0.860  Heating rate \u00d7 performance 2 1.631 0.203 BSI Heating rate 2 1.332 0.275  Performance 1 1.418 0.241  Heating rate \u00d7 performance 2 0.285 0.753 CSI Heating rate 2 1.032 0.365  Performance 1 0.716 0.402  Heating rate \u00d7 performance 2 0.123 0.885 HSI Heating rate 2 1.273 0.290  Performance 1 0.001 0.979  Heating rate \u00d7 performance 2 0.635 0.535 Hsp47 Heating rate 2 6.474 0.003*  Performance 1 2.484 0.119  Heating rate \u00d7 performance 2 2.703 0.074 Hsp70 Heating rate 2 285.806 <0.001*  Performance 1 46.836 <0.001*  Heating rate \u00d7 performance 2 5.887 0.004* Hsp90a Heating rate 2 69.13 <0.001*  Performance 1 0.266 0.608  Heating rate \u00d7 performance 2 1.62 0.205 Hsp90b Heating rate 2 67.585 <0.001*  Performance 1 1.029 0.314  Heating rate \u00d7 performance 2 0.213 0.809   46  Figure 3.1 CTmax values of 15\u00b0C acclimated juvenile white sturgeon at three different heating rates (0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min). Black dots represent individual data points and the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistically significant at alpha = 0.05. N = 105 for 0.3\u00b0C\/min and N = 45 for 0.03\u00b0C\/min and 0.003\u00b0C\/min. cba283032340.3 0.03 0.003Ramp rate (\u00b0C\/min)CTmax (\u00b0C)  47  Figure 3.2 HSI of juvenile white sturgeon following CTmax trials at different heating rates (control, 0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min). Black dots represent individual data points, while the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistical significance at alpha = 0.05. N = 20 for control and N = 45 for 0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min. abbb0.010.020.03Control 0.3 0.03 0.003Ramp rate (\u00b0C\/min)HSI  48  Figure 3.3 Condition factor of juvenile white sturgeon following CTmax trials at different heating rates (control, 0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min). Black dots represent individual data points, while the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistical significance at alpha = 0.05. N = 20 for control; N = 105 for 0.3\u00b0C\/min; and N = 45 for 0.03\u00b0C\/min, and 0.003\u00b0C\/min.  ababb0.30.40.50.60.7Control 0.3 0.03 0.003Ramp rate (\u00b0C\/min)Condition factor  49   Figure 3.4 Relative expression of (A) Hsp47, (B) Hsp90a, (C) Hsp90b, and (D) Hsp70 (log 2 scale) of juvenile white sturgeon following CTmax trials at different heating rates (control, 0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min). Black dots represent individual data points, while the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistical significance at alpha = 0.05. N = 20 for control; N = 48 for 0.3\u00b0C\/min; and N = 16 for 0.03\u00b0C\/min, and 0.003\u00b0C\/min. \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cfababab0.51.01.52.02.53.0Log 2A\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cfaabc0.51.01.52.02.53.0B\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cfaab c0.51.01.52.02.53.0Control 0.3 0.03 0.003Ramp rate (\u00b0C\/min)Log 2C\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cfabc c24681012Control 0.3 0.03 0.003Ramp rate (\u00b0C\/min)DHsp47Hsp90b Hsp70Hsp90a  50  Figure 3.5 Relative expression of (A) Hsp47, (B) Hsp90a, (C) Hsp90b, and (D) Hsp70 (log 2 scale) of low and high performing juvenile white sturgeon following CTmax trials at different heating rates (0.3\u00b0C\/min, 0.03\u00b0C\/min, and 0.003\u00b0C\/min). Black dots represent individual data points, while the boxplot represents group data. The horizontal line in the boxplot is the median, while the whiskers represent the maximum and minimum. Letters that differ indicate statistically significance a given performance group. Asterisk (*) denotes a statistically significant difference between high and low performers with the same heating rate at alpha = 0.05. N = 24 in the 0.3\u00b0C\/min trial and N = 8 in the 0.03\u00b0C\/min, and 0.003\u00b0C\/min trials per performance level (low and high).    \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf*aabaaa0.51.01.52.02.53.0Log 2Low performerHigh performerA\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cfabbabc0.51.01.52.02.53.0B\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cfab cabc0.51.01.52.02.53.00.3 0.03 0.003Ramp rate (\u00b0C\/min)Log 2C\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf \u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf\u25cf**ab babb57911130.3 0.03 0.003Ramp rate (\u00b0C\/min)DHsp47 Hsp90aHsp90b Hsp70  51 3.4 Discussion This chapter sought to determine how the heating rate used during a CTmax test affects thermal tolerance, Hsp expression, and somatic indices of juvenile white sturgeon. Notably, the relationship between heating rate and CTmax was the opposite of what was predicted, with CTmax increasing at slower rates of warming. HSI of controls was significantly greater than in any of the heating rates. Condition factor, BSI, and CSI were not significantly affected. Hsp70, Hsp90a, and Hsp90b expression was upregulated in accordance with the duration of heat stress. Hsp47 expression was not affected by heating rate. There were no diurnal effects on CTmax or Hsp expression in the 0.3\u00b0C\/min heating rate, unlike in the Atlantic killifish (Fundulus heteroclitus) where CTmax and Hsp70-2 expression was greatest at midday (Healy and Schulte, 2012).  Unlike the majority of fish species studied to date, juvenile white sturgeon were able to rapidly adjust their thermal tolerance resulting in higher thermal tolerance in the slower heating rates (see review by Kovacevic et al., 2019). Given these data, the operators of the Kenney dam should consider the rate at which river temperatures are allowed to increase, as slower heating rates may allow white sturgeon time to increase their upper thermal tolerance. Zebrafish (Danio rerio) is the only fish species studied to date to show the same pattern as sturgeon in this study. Zebrafish fish display different trends depending on their initial acclimation temperature \u2013 when acclimated to supra-optimal temperatures (34\u00b0C), they had higher thermal tolerance when heated at 0.3\u00b0C\/min relative to 0.025\u00b0C\/min, whereas zebrafish acclimated to sub-optimal temperatures (22\u00b0C) were able to increase their thermal tolerance when heated at 0.025\u00b0C. In 22\u00b0C acclimated zebrafish, CTmax increased by 1.53\u00b0C, from 38.83\u00b0C in the 0.3\u00b0C\/min trial to 40.36\u00b0C in the 0.025\u00b0C\/min trial (\u00c5sheim et al., 2020). In comparison, sturgeon were able to increase their thermal tolerance by 2.1\u00b0C when the heating rate was reduced from 0.3\u00b0C\/min (CTmax of 29.2\u00b0C)   52 to 0.03\u00b0C\/min (CTmax of 31.3\u00b0C). In the slowest heating rate (0.003\u00b0C\/min), sturgeon were able to increase their thermal tolerance by 5\u00b0C to 34.2\u00b0C. In conventional CTmax, thermal tolerance is thought to be limited by a neurological and\/or cardiac malfunction (Andreassen et al., 2020; Christen et al., 2018). Whereas in slower heating rates, fish are expected have lower thermal tolerance because it is thought to be limited by the accumulation of heat damage as organisms spend more time at temperatures where the rate of cellular damage exceeds the rate of repair (Rezende et al., 2014). Therefore, this data suggests that white sturgeon possess some physiological or biochemical mechanism(s) that allows for rapid acclimation. \u00c5sheim and colleagues (2020) proposed Hsp production as a possible explanation for their findings in zebrafish, which may be involved in sturgeon as discussed below. Juvenile white sturgeon displayed a highly plastic Hsp mRNA response. Modulation of Hsp mRNA expression is one proposed mechanism by which ectotherms are able to regulate their thermal tolerance in response to changing environments (Feder and Hofmann, 1999; Hochachka and Somero, 2002; Somero, 2020). It is important to note, however, that the relationship between mRNA transcription and downstream processes such as protein translation vary temporally and are not directly linked. The upregulation of transcription does not correlate 1:1 with upregulation of translation, but not surprisingly, there are reports of increased mRNA levels increasing protein levels of Hsps (Buckley et al., 2006).   Of the four Hsps examined, expression of Hsp47 mRNA was the only one that remained relatively unchanged between controls and heating rate. The expression of Hsp47 mRNA in response to heat shock is less conserved and more species-specific than the other Hsps studied (Hsp70 and Hsp90; Mohanty et al., 2018). Previous studies have found variable expression patterns in response to acute heat shock \u2013 juvenile Atlantic sturgeon upregulated expression of   53 Hsp47, while juvenile brook trout did not alter expression levels (Mackey et al., 2021; Yebra-Pimentel et al., 2020).  Unlike Hsp47 expression, which changed relatively little, expression of Hsp90a, Hsp90b, and Hsp70 mRNA were all elevated in response to heat stress as hypothesized. The upregulation of these Hsps, which function as molecular chaperones, can help renature damaged proteins and prevent cellular apoptosis (Beere, 2004). Acute (Hsp90a and Hsp70) and constitutive (Hsp90b) expression depends on the severity and duration of the stressor (Chen et al., 2018; Somero, 2020). Therefore, it is interesting that both isoforms of Hsp90 had very similar induction profiles. They were significantly upregulated in the two longer trials (0.03\u00b0C\/min and 0.003\u00b0C\/min) and neither was differentially expressed between high and low performers. Temperature and time are two confounding possible explanations as to why the Hsp90 isoforms were not upregulated in the conventional CTmax (0.3\u00b0C\/min). It could be that their activation is time dependent and the 0.3\u00b0C\/min trial may not have lasted long enough to see upregulation. Alternatively, it could be that they are temperature dependent and the sturgeon in the conventional CTmax did not experience temperatures high enough to trigger Hsp90 expression. A study that allowed for continuous sampling throughout CTmax trials at different heating rates would help tease apart these potential mechanisms. The speed and extent to which juvenile white sturgeon can upregulate Hsp70 expression, highlights the scope of their plasticity and may help explain why they show an opposite CTmax pattern to what was predicted. Hsp70 expression plateaus between the two slower trials (0.03\u00b0C\/min and 0.003\u00b0C\/min), and there are many possible explanations for why this may be the case. Given the extent of Hsp70 upregulation, it could be that cells are saturated and further upregulation would provide no additional advantage. Hsp70 production requires a lot of energy   54 and thus further upregulation may be metabolically constrained (Han et al., 2011). While Hsps are preferentially synthesized during periods of stress and can be upregulated in a matter of minutes, it could be that on longer timescales, sturgeon are able to enlist some other physiological processes that can help them cope with heat stress (Tomanek and Somero, 2000).  Hsp70 was differentially expressed between high and low performers. High-performing sturgeon in both the 0.3\u00b0C\/min and 0.003\u00b0C\/min trials upregulated Hsp70 expression significantly more than low performers. Additionally, while not statistically significant, the same trend is apparent in the 0.03\u00b0C\/min trial. Importantly, both time and temperature are possible confounds in all three trials as high performers were exposed to higher temperatures and heat stress for longer durations than low performers. Thus, any difference between the groups may simply be due to the temperature and\/or length of heat exposure. These findings merit further investigation in order to independently assess possible confounds. If time and temperature do not explain the variation between performers, then this finding may suggest that greater upregulation of Hsp70 mRNA expression may protective and allow sturgeon to increase their thermal tolerance to a greater extent.  Condition factor, BSI, and CSI were not affected by heating rate. In studies that have found significant differences in these metrics, it has typically been after a longer exposure to stress (Gilbert and Farrell, 2021; Raspopov et al., 2017; Soengas and Aldegunde, 2002). Thus, it may be that the trials in the current study were too short in duration to cause any significant changes. HSI in all three trials was significantly lower than in the controls, but it did not differ between heating rates. Lower HSI may indicate the metabolic costs of coping with heat stress. Decreases in HSI have been observed in lake sturgeon following temperature acclimation, and in white sturgeon and three-spined sticklebacks, decreases in HSI have been linked to decreased   55 glycogen reserves (Bugg et al., 2020; Chellappa et al., 1995; Hung et al., 1990). Glycogen reserves are stored in the liver and they are a readily available source of energy that are utilized in bursts of activity (Goolish, 1991). Additionally, glycogen is bound to water (in humans 1 gram of glycogen binds 3 grams of water), so as glycogen reserves are diminished, water is released (King et al., 2018). It is possible that the observed decrease in HSI is in part due to water loss caused by glycogen catabolism, further reducing overall liver mass. Measuring changes in glycogen reserves as well as changes in dry mass are possible avenues for future research. This study indicates that white sturgeon are able to rapidly adjust their thermal tolerance. A possible mechanism for this change is associated with Hsp expression as Hsp70, Hsp90a, and Hsp90b were all greatly upregulated in response to thermal stress. HSI decreased significantly, possibly because sturgeon are using glycogen reserve to cope with heat stress. To my knowledge, this is the first study to show a decrease in HSI in fish following an acute heat stressor (0.3\u00b0C\/min). More research is needed to determine if other fish species experience this and whether glycogen depletion is behind the change. Future studies should be conducted to determine if rapid thermal acclimation is a trait common amongst all sturgeon species, or whether this is specific to white sturgeon.       56 Chapter 4: General Discussion and Conclusion 4.1 Thesis summary The Kenney dam on the Nechako River is currently mandated to maintain water temperatures below 20\u00b0C, but it is unclear whether this is an appropriate upper temperature limit for white sturgeon. To provide conservation recommendations for the dam, I examined the effects of acclimation temperature, age, and heating rate on the upper thermal tolerance, somatic indices, and Hsp expression of juvenile white sturgeon. The results show that juvenile white sturgeon are able to acclimate to temperatures above 20\u00b0C over a two-week period, and that acclimation confers higher thermal tolerance. Their high ARRs relative to other species from similar latitudes suggest that white sturgeon have an unusually large capacity to acclimate to increased temperature. The plasticity of their thermal tolerance was further demonstrated when \u2013contrary to predictions\u2013 their CTmax increased significantly at slower heating rates. A heating rate of 0.03\u00b0C\/min resulted in 15\u00b0C-acclimated fish (trial lasted ~6.5hrs) having the same thermal tolerance as fish acclimated to 18\u00b0C for two weeks then heated at 0.3\u00b0C\/min. An even slower heating rate (0.003\u00b0C\/min; trial lasted ~4.5 days) allowed 15\u00b0C-acclimated fish to further increase their thermal tolerance to match the CTmax of the fish acclimated to 24\u00b0C for two weeks and then ramped at 0.3\u00b0C\/min. In other words, the slower heating rates (Chapter 3) yield the same thermal advantage over a shorter time-course, as conventional heating rates following two-week acclimation (Chapter 2). To date, white sturgeon are one of the only fish species that show this trend (\u00c5sheim et al., 2020; Kovacevic et al., 2019).  Despite their impressive ability to acclimate to higher temperatures, the condition factor of white sturgeon decreased following two weeks of acclimation to temperatures above 18\u00b0C (21\u00b0C and 24\u00b0C). These findings imply that although these fish are able to tolerate temperatures   57 above the 20\u00b0C upper temperature limit, there may be a sub-lethal threshold between 18\u00b0C and 21\u00b0C, above which their overall health may be negatively affected. In order to get better resolution within this temperature range (18\u00b0C - 21\u00b0C) more studies are required. In the absence of more information, I recommend considering reducing the upper temperature limit to 18\u00b0C to protect developing juvenile white sturgeon.   4.2 Limitations and future directions 4.2.1 Chapter 2 Mass and length were only measured at the end of the experiment. For the purposes of analysis, it was assumed that initial size was equal between fish at all acclimation temperatures; however, to draw conclusions about growth, future studies should take initial mass and length measurements prior to experimentation.  The current study did not observe increased mortality due to acclimation to temperatures up to 24\u00b0C, but it is possible that survival would decrease if sturgeon were exposed to high temperatures for longer durations, or if temperature were studied in conjunction with other stressors. Water temperature in the Nechako River exceeded 20\u00b0C for a total of four weeks in 2021. Given that climate change is predicted to continue to exacerbate temperature increases, more long-term acclimation studies are essential for understanding how these temperature changes will affect white sturgeon. Furthermore, white sturgeon have shown heightened vulnerability when temperature is one of multiple stressors; larval white sturgeon acclimated to warm temperatures (17.5\u00b0C) without adequate substrate experienced higher mortality rates relative to fish acclimated to the same temperature with proper substrate (Boucher et al., 2014). Temperature is one of six recognized factors that may be affecting the success of white sturgeon   58 in the Nechako River. Other stressors include water flow, predation, food availability, turbidity, and hypoxia. Designing factorial studies that more closely mimic the challenges of this natural environment will provide more ecologically relevant results.   4.2.2 Chapter 3 Given the decrease in HSI that was observed at all heating rates, future studies using white sturgeon should examine how energy reserves are affected by heat stress. Moreover, studies should be conducted to determine if lower HSI after acute heat stress is common across fish species, or whether it is unique to white sturgeon.  Because mRNA expression was only measured at the end of each trial, it remains unclear whether Hsp90a and Hsp90b upregulation was triggered by the duration of heat stress, or by the temperature of the water. Of the few studies that have looked at the time-course of Hsp expression during heat shock, none were conducted using sturgeon (Tomanek and Somero, 2000). Continuous sampling would help elucidate the trigger for Hsp90 upregulation in white sturgeon and would allow for the quantification of protein levels. This would allow researchers to better understand how the magnitude and timing of upregulation are connected between Hsp expression at the mRNA and protein levels.  4.3 Policy recommendation The objective of this thesis was to gather information on juvenile white sturgeon thermal biology in order to better inform dam management decisions on the Nechako River in northern BC.    59 I sought to determine whether the current 20\u00b0C mandate is appropriate for developing juvenile white sturgeon. I found that while juvenile white sturgeon have a highly plastic thermal response, their condition factor decreased when reared at temperatures above 18\u00b0C for two weeks. These data suggest the existence of a sub-lethal threshold between 18\u00b0C and 21\u00b0C, beyond which the overall health of the animal may be affected. Moreover, in this thesis I examined the effects of temperature in isolation, yet this is rarely the only stressor white sturgeon will experience at a given time in nature. Studies have shown that when white sturgeon experience high temperatures in conjunction with other stressors, condition factor decreases more than when they are exposed only to temperature stress (Boucher et al., 2014). As a result of my findings, my policy recommendation is to consider lowering the current upper temperature limit in the Nechako River below the Kenney dam to 18\u00b0C.    60 Bibliography 4Thought Solutions Inc. (2005). Assessment of potential flow regimes for the Nechako waterhsed. Vancouver. Abram, P. K., Boivin, G., Moiroux, J. and Brodeur, J. (2017). Behavioural effects of temperature on ectothermic animals: unifying thermal physiology and behavioural plasticity. Biol. Rev 92, 1859\u20131876. Andreassen, A. H., Hall, P., Khatibzadeh, P., Jutfelt, F. and Kermen, F. (2020). Neural dysfunction at the upper thermal limit in the zebrafish. bioRxiv. \u00c5sheim, E. R., Andreassen, A. H., Morgan, R. and Jutfelt, F. (2020). Rapid-warming tolerance correlates with tolerance to slow warming but not growth at non-optimal temperatures in zebrafish. J. Exp. Biol. 223,. Auer, N. A. (1996). Importance of habitat and migration to sturgeons with emphasis on lake sturgeon. Can. J. Fish. Aquat. Sci. 53, 152\u2013160. Becker, C. D. and Genoway, R. G. (1979). Evaluation of the critical thermal maximum for determining thermal tolerance of freshwater fish. Environ. Biol. Fishes 4, 245\u2013256. Beere, H. M. (2004). \u201cThe stress of dying\u201d: The role of heat shock proteins in the regulation of apoptosis. J. Cell Sci. 117, 2641\u20132651. Beitinger, T. L. and Lutterschmidt, W. I. (2011). Temperature | Measures of Thermal Tolerance. In Encyclopedia of Fish Physiology, pp. 1695\u20131702. Elsevier. Bennett, N. (2021). Can Nechako River be saved without killing industry? Bus. Intell. B.C. Bilyk, K. T. and DeVries, A. L. (2011). Heat tolerance and its plasticity in Antarctic fishes. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 158, 382\u2013390. Birstein, V. J. and Bemis, W. E. (1997). How many species are there within the genus Acipenser? In Environmental Biology of Fishes, pp. 157\u2013163. Bj\u00f6rnsson, B. T., Thorarensen, H., Hirano, T., Ogasawara, T. and Kristinsson, J. B. (1989). Photoperiod and temperature affect plasma growth hormone levels, growth, condition factor and hypoosmoregulatory ability of juvenile Atlantic salmon (Salmo salar) during parr-smolt transformation. Aquaculture 82, 77\u201391.   61 Bolger, T. and Connolly, P. L. (1989). The selection of suitable indices for the measurement and analysis of fish condition. J. Fish Biol. 34, 171\u2013182. Bolta\u00f1a, S., Sanhueza, N., Aguilar, A., Gallardo-Escarate, C., Arriagada, G., Valdes, J. A., Soto, D. and Qui\u00f1ones, R. A. (2017). Influences of thermal environment on fish growth. Ecol. Evol. 7, 6814\u20136825. Boreman, J. (2005). Sensitivity of North American sturgeons and paddlefish to fishing mortality. In Sturgeon Biodiversity and Conservation, pp. 399\u2013405. Springer, Dordrecht. Boucher, M. A., McAdam, S. O. and Shrimpton, J. M. (2014). The effect of temperature and substrate on the growth, development and survival of larval white sturgeon. Aquaculture 430, 139\u2013148. Brett, J. R. (1971). Energetic responses of salmon to temperature. A study of some thermal relations in the physiology and freshwater ecology of sockeye salmon (Oncorhynchus nerkd). Integr. Comp. Biol. 11, 99\u2013113. Buckley, B. A., Gracey, A. Y. and Somero, G. N. (2006). The cellular response to heat stress in the goby Gillichthys mirabilis: A cDNA microarray and protein-level analysis. J. Exp. Biol. 209, 2660\u20132677. Bugg, W. S., Yoon, G. R., Schoen, A. N., Laluk, A., Brandt, C., Anderson, W. G. and Jeffries, K. M. (2020). Effects of acclimation temperature on the thermal physiology in two geographically distinct populations of lake sturgeon (Acipenser fulvescens). Conserv. Physiol. 8,. Cech, J. J., Mitchell, S. J. and Wragg, T. E. (1984). Comparative growth of juvenile white sturgeon and striped bass: Effects of temperature and hypoxia. Estuaries 7, 12\u201318. Chellappa, S., Huntingford, F. A., Strang, R. H. C. and Thomson, R. Y. (1995). Condition factor and hepatosomatic index as estimates of energy status in male three-spined stickleback. J. Fish Biol. 47, 775\u2013787. Chen, D., M. Rojas, B. H. Samset, K. Cobb, A. Diongue Niang, P. Edwards, S. Emori, S. H. Faria, E. Hawkins, P. and Hope, P. Huybrechts, M. Meinshausen, S. K. Mustafa, G. K. Plattner, A. M. T. (2021). Framing, Context, and Methods. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (ed. Masson-Delmotte, V., P.), Zhai, A. Pirani, S.L. Connors, C. P\u00e9an, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. L.), and E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelek\u00e7i, R. Yu,  and B. Z.), .   62 Chen, B., Feder, M. E. and Kang, L. (2018). Evolution of heat-shock protein expression underlying adaptive responses to environmental stress. Mol. Ecol. 27, 3040\u20133054. Cheung, K. (2019). The effects of embryonic incubation temperature on subsequent development, growth, and thermal tolerance through early ontogeny of white sturgeon (Acipenser transmontanus). Christen, F., Desrosiers, V., Dupont-Cyr, B. A., Vandenberg, G. W., Le Fran\u00e7ois, N. R., Tardif, J. C., Dufresne, F., Lamarre, S. G. and Blier, P. U. (2018). Thermal tolerance and thermal sensitivity of heart mitochondria: Mitochondrial integrity and ROS production. Free Radic. Biol. Med. 116, 11\u201318. Claussen, D. L. (1977). Thermal acclimation in ambystomatid salamanders. Comp. Biochem. Physiol. - Part A Physiol. 58, 333\u2013340. Comte, L., Buisson, L., Daufresne, M. and Grenouillet, G. (2013). Climate-induced changes in the distribution of freshwater fish: Observed and predicted trends. Freshw. Biol. 58, 625\u2013639. Cowles, R. B. and Bogert, C. M. (1944). A preliminary study of the thermal requirements of desert reptiles. 83, 265\u2013296. Crozier, L. G., Zabel, R. W. and Hamlet, A. F. (2008). Predicting differential effects of climate change at the population level with life-cycle models of spring Chinook salmon. Glob. Chang. Biol. 14, 236\u2013249. Dahlke, F. T., Wohlrab, S., Butzin, M. and P\u00f6rtner, H. O. (2020). Thermal bottlenecks in the life cycle define climate vulnerability of fish. Science (80-. ). 369, 65\u201370. Deng, X., Van Eenennaam, J. P. and Doroshov, S. I. (2002). Comparison of early life stages of green and white sturgeon. Am. Fish. Soc. Symp. 237\u2013248. Deng, D. F., Wang, C., Lee, S., Bai, S. and Hung, S. S. O. (2009). Feeding rates affect heat shock protein levels in liver of larval white sturgeon(Acipenser transmontanus). Aquaculture 287, 223\u2013226. Dudgeon, D., Arthington, A. H., Gessner, M. O., Kawabata, Z. I., Knowler, D. J., L\u00e9v\u00eaque, C., Naiman, R. J., Prieur-Richard, A. H., Soto, D., Stiassny, M. L. J., et al. (2006). Freshwater biodiversity: Importance, threats, status and conservation challenges. Biol. Rev. Camb. Philos. Soc. 81, 163\u2013182. Eifert, C., Farnworth, M., Schulz-Mirbach, T., Riesch, R., Bierbach, D., Klaus, S., Wurster,   63 A., Tobler, M., Streit, B., Indy, J. R., et al. (2015). Brain size variation in extremophile fish: Local adaptation versus phenotypic plasticity. J. Zool. 295, 143\u2013153. Fangue, N. A., Hofmeister, M. and Schulte, P. M. (2006). Intraspecific variation in thermal tolerance and heat shock protein gene expression in common killifish, Fundulus heteroclitus. J. Exp. Biol. 209, 2859\u20132872. Feder, M. E. and Hofmann, G. E. (1999). Heat-shock proteins, molecular chaperones, and the stress response: Evolutionary and ecological physiology. Annu. Rev. Physiol. 61, 243\u2013282. Feder, M. E. and Krebs, R. A. (1998). Natural and genetic engineering of the heat-shock protein Hsp70 in drosophila melanogaster: Consequences for thermotolerance. Am. Zool. 38, 503\u2013517. Feder, M. E., Carta\u00f1o, N. V, Milos, L., Krebs, R. A. and Lindquist, S. L. (1996). Effect of engineering Hsp70 copy number on Hsp70 expression and tolerance of ecologically relevant heat shock in larvae and pupae of Drosophila melanogaster. J. Exp. Biol. 199, 1837\u20131844. Fisheries and Oceans Canada (2014). Species at Risk Act: Recovery Strategy for White Sturgeon (Acipenser transmontanus) in Canada. Fuller, A., Dawson, T., Helmuth, B., Hetem, R. S., Mitchell, D. and Maloney, S. K. (2010). Physiological mechanisms in coping with climate change. Physiol. Biochem. Zool. 83, 713\u2013720. Gabriel, J. E., Ferro, J. A., Stefani, R. M. P., Ferro, M. I. T., Gomes, S. L. and Macari, M. (1996). Effect of acute heat stress on heat shock protein 70 messenger RNA and on heat shock protein expression in the liver of broilers. Br. Poult. Sci. 37, 443\u2013449. Garbuz, D. G. and Evgen\u2019ev, M. B. (2017). The evolution of heat shock genes and expression patterns of heat shock proteins in the species from temperature contrasting habitats. Russ. J. Genet. 53, 21\u201338. Gardiner, B. G. (1984). Sturgeons as Living Fossils.pp. 148\u2013152. Springer-Verlag. Gessner, J., Arndt, G. M., Tiedemann, R., Bartel, R. and Kirschbaum, F. (2006). Remediation measures for the Baltic sturgeon: Status review and perspectives. In Journal of Applied Ichthyology, pp. 23\u201331. John Wiley & Sons, Ltd. Gilbert, M. J. H. and Farrell, A. P. (2021). The thermal acclimation potential of maximum heart rate and cardiac heat tolerance in Arctic char (Salvelinus alpinus), a northern cold-  64 water specialist. J. Therm. Biol. 95, 102816. Gilbert, M. J. H., Harris, L. N., Malley, B. K., Schimnowski, A., Moore, J. S. and Farrell, A. P. (2020). The thermal limits of cardiorespiratory performance in anadromous Arctic char (Salvelinus alpinus): A field-based investigation using a remote mobile laboratory. Conserv. Physiol. 8,. Golder Associates Ltd. (2010). White sturgeon spawning at Waneta, 2009 investigations. Castlegar, BC. Goolish, E. M. (1991). Aerobic and anaerobic scaling in fish. Biol. Rev. Camb. Philos. Soc. 66, 33\u201356. Gross, M. R., Repka, J., Robertson, C. T., Secor, D. H. and Van Winkle, W. (2002). Sturgeon conservation: Insights from elasticity analysis. Am. Fish. Soc. Symp. 13\u201330. Han, D., Huang, S. S. Y., Wang, W.-F., Deng, D.-F. and Hung, S. S. O. (2011). Starvation reduces the heat shock protein responses in white sturgeon larvae. Environ. Biol. Fishes 2011 933 93, 333\u2013342. Hassan, B., Qadri, H., Ali, M. N., Khan, N. A. and Yatoo, A. M. (2020). Impact of Climate Change on Freshwater Ecosystem and Its Sustainable Management. In Fresh Water Pollution Dynamics and Remediation, pp. 105\u2013121. Springer, Singapore. Hazel, J. R. and Prosser, C. L. (1974). Molecular mechanisms of temperature compensation in poikilotherms. Physiol. Rev. 54, 620\u2013677. Healy, T. M. and Schulte, P. M. (2012). Factors affecting plasticity in whole-organism thermal tolerance in common killifish (Fundulus heteroclitus). J. Comp. Physiol. B Biochem. Syst. Environ. Physiol. 182, 49\u201362. Hildebrand, L. R., Drauch Schreier, A., Lepla, K., McAdam, S. O., McLellan, J., Parsley, M. J., Paragamian, V. L. and Young, S. P. (2016). Status of White Sturgeon (Acipenser transmontanus Richardson, 1863) throughout the species range, threats to survival, and prognosis for the future. J. Appl. Ichthyol. 32, 261\u2013312. Hochachka, P. and Somero, G. (2002). Biochemical Adaptation: Mechanism and Process in Physiological Evolution. Hoegh-Guldberg, O. D., Jacob, M., Taylor, M., Bindi, S., Brown, I., Camilloni, A., Diedhiou, R., Djalante, K. L., Ebi, F., Engelbrecht, J., et al. (2018). Impacts of 1.5oC Global Warming on Natural and Human Systems. In Global Warming of 1.5\u00b0C. An IPCC   65 Special Report on the impacts of global warming of 1.5\u00b0C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, (ed. Masson-Delmotte, V., P. Zhai, H.-O. P\u00f6rtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. P\u00e9an, R. P.) and S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I.Gomis, E. Lonnoy, T.Maycock, M.Tignor,  and T. W.), . Huey, R. B. and Stevenson, R. D. (1979). Integrating thermal physiology and ecology of ectotherms: A discussion of approaches. Integr. Comp. Biol. 19, 357\u2013366. Hung, S. S. O., Groff, J. M., Lutes, P. B. and Fynn-Aikins, F. K. (1990). Hepatic and intestinal histology of juvenile white sturgeon fed different carbohydrates. Aquaculture 87, 349\u2013360. Illing, B., Downie, A. T., Beghin, M. and Rummer, J. L. (2020). Critical thermal maxima of early life stages of three tropical fishes: Effects of rearing temperature and experimental heating rate. J. Therm. Biol. 90,. Irons, K. S., Sass, G. G., McClelland, M. A. and Stafford, J. D. (2007). Reduced condition factor of two native fish species coincident with invasion of non-native Asian carps in the Illinois River, U.S.A. Is this evidence for competition and reduced fitness? J. Fish Biol. 71, 258\u2013273. Jager, H. I., Chandler, J. A., Lepla, K. B. and Van Winkle, W. (2001). A theoretical study of river fragmentation by dams and its effects on white sturgeon populations. Environ. Biol. Fishes 60, 347\u2013361. Johansen, I. B., Lunde, I. G., R\u00f8sj\u00f8, H., Christensen, G., Nilsson, G. E., Bakken, M. and \u00d8verli, \u00d8. (2011). Cortisol response to stress is associated with myocardial remodeling in salmonid fishes. J. Exp. Biol. 214, 1313\u20131321. Kappenman, K. M., Fraser, W. C., Toner, M., Dean, J. and Webb, M. A. H. (2009). Effect of Temperature on Growth, Condition, and Survival of Juvenile Shovelnose Sturgeon. Trans. Am. Fish. Soc. 138, 927\u2013937. King, R. F. G. J., Jones, B. and O\u2019Hara, J. P. (2018). The availability of water associated with glycogen during dehydration: a reservoir or raindrop? Eur. J. Appl. Physiol. 118, 283\u2013290. Kingsolver, J. G. and Huey, R. B. (1998). Evolutionary analyses of morphological and physiological plasticity in thermally variable environments. Am. Zool. 38, 545\u2013560. Kingsolver, J. G. and Umbanhowar, J. (2018). The analysis and interpretation of critical   66 temperatures. J. Exp. Biol. 221,. Kovacevic, A., Latombe, G. and Chown, S. L. (2019). Rate dynamics of ectotherm responses to thermal stress. Proc. R. Soc. B Biol. Sci. 286,. Krebs, R. A. and Feder, M. E. (1997). Natural variation in the expression of the heat-shock protein hsp70 in a population of Drosophila melanogaster and its correlation with tolerance of ecologically relevant thermal stress. Evolution (N. Y). 51, 173\u2013179. K\u00fcltz, D. (2005). Molecular and evolutionary basis of the cellular stress response. Annu. Rev. Physiol. 67, 225\u2013257. Lagerspetz, K. Y. H. (2006). What is thermal acclimation? J. Therm. Biol. 31, 332\u2013336. Lebreton, G. T. O., Beamish, F. W. H. and Mckinley, Scott, R. (2004). Sturgeons and Paddlefish of North America. Springer Netherlands. Li, A. J., Leung, P. T. Y., Bao, V. W. W., Lui, G. C. S. and Leung, K. M. Y. (2015). Temperature-dependent physiological and biochemical responses of the marine medaka Oryzias melastigma with consideration of both low and high thermal extremes. J. Therm. Biol. 54, 98\u2013105. Lu, K., Chen, X., Liu, W. and Zhou, Q. (2016). Characterization of heat shock cognate protein 70 gene and its differential expression in response to thermal stress between two wing morphs of Nilaparvata lugens (St\u00e5l). Comp. Biochem. Physiol. -Part A  Mol. Integr. Physiol. 199, 47\u201353. Lutterschmidt, W. I. and Hutchison, V. H. (1997). The critical thermal maximum: History and critique. Can. J. Zool. 75, 1561\u20131574. Macdonald, J. S., Morrison, J. and Patterson, D. A. (2012). The efficacy of reservoir flow regulation for cooling migration temperature for sockeye Salmon in the Nechako river watershed of British Columbia. North Am. J. Fish. Manag. 32, 415\u2013427. Mackey, T. E., Hasler, C. T., Durhack, T., Jeffrey, J. D., Macnaughton, C. J., Ta, K., Enders, E. C. and Jeffries, K. M. (2021). Molecular and physiological responses predict acclimation limits in juvenile brook trout (Salvelinus fontinalis). J. Exp. Biol. 224,. Mantua, N., Tohver, I. and Hamlet, A. (2010). Climate change impacts on streamflow extremes and summertime stream temperature and their possible consequences for freshwater salmon habitat in Washington State. Clim. Chang. 2010 1021 102, 187\u2013223.   67 McArley, T. J., Hickey, A. J. R. and Herbert, N. A. (2017). Chronic warm exposure impairs growth performance and reduces thermal safety margins in the common triplefin fish (Forsterygion lapillum). J. Exp. Biol. 220, 3527\u20133535. Medcalf, K., Hutchings, J., Fast, M., Kuparinen, A. and Godwin, S. (2021). Warming temperatures and ectoparasitic sea lice impair internal organs in juvenile Atlantic salmon. Mar. Ecol. Prog. Ser. 660, 161\u2013169. Meffe, G. K. (1992). Plasticity of Life-History Characters in Eastern Mosquitofish (Gambusia holbrooki: Poeciliidae) in Response to Thermal Stress. Copeia 1992, 94. Mirault, M. E., Goldschmidt-Clermont, M., Moran, L., Arrigo, A. P. and Tissi\u00e8res, A. (1977). The effect of heat shock on gene expression in Drosophila melanogaster. Cold Spring Harb. Symp. Quant. Biol. 42, 819\u2013827. Mohanty, B. P., Mahanty, A., Mitra, T., Parija, S. C. and Mohanty, S. (2018). Heat Shock Proteins in Stress in Teleosts. In Asea A., Kaur P. (eds) Regulation of Heat Shock Protein Responses. Heat Shock Proteins, vol 13, pp. 71\u201394. Springer, Cham. Mora, C. and Maya, M. F. (2006). Effect of the rate of temperature increase of the dynamic method on the heat tolerance of fishes. J. Therm. Biol. 31, 337\u2013341. Morley, S. A., Peck, L. S., Sunday, J. M., Heiser, S. and Bates, A. E. (2019). Physiological acclimation and persistence of ectothermic species under extreme heat events. Glob. Ecol. Biogeogr. 28, 1018\u20131037. Morrison, S. M., Mackey, T. E., Durhack, T., Jeffrey, J. D., Wiens, L. M., Mochnacz, N. J., Hasler, C. T., Enders, E. C., Treberg, J. R. and Jeffries, K. M. (2020). Sub-lethal temperature thresholds indicate acclimation and physiological limits in brook trout Salvelinus fontinalis. J. Fish Biol. 97, 583\u2013587. Mosser, D. D. and Bols, N. C. (1988). Relationship between heat-shock protein synthesis and thermotolerance in rainbow trout fibroblasts. J. Comp. Physiol. B 158, 457\u2013467. Nilsson, C., Reidy, C. A., Dynesius, M. and Revenga, C. (2005). Fragmentation and flow regulation of the world\u2019s large river systems. Science (80-. ). 308, 405\u2013408. O\u2019Gorman, E. J., \u00d3lafsson, \u00d3. P., Demars, B. O. L., Friberg, N., Gu\u00f0bergsson, G., Hannesd\u00f3ttir, E. R., Jackson, M. C., Johansson, L. S., McLaughlin, \u00d3. B., \u00d3lafsson, J. S., et al. (2016). Temperature effects on fish production across a natural thermal gradient. Glob. Chang. Biol. 22, 3206\u20133220.   68 Pankhurst, N. W. and Munday, P. L. (2011). Effects of climate change on fish reproduction and early life history stages. Mar. Freshw. Res. 62, 1015. Parsley, M. J. and Kappenman, K. M. (2000). White sturgeon spawning areas in the lower Snake River. Northwest Sci. 74, 192\u2013201. Peck, L. S., Morley, S. A., Richard, J., Clark, M. S., Davies, S. A., Dow, J. A. T. and Lukowiak, K. (2014). Acclimation and thermal tolerance in Antarctic marine ectotherms. J. Exp. Biol. 217, 16\u201322. Pittock, J. and Hartmann, J. (2011). Taking a second look: Climate change, periodic relicensing and improved management of dams. Mar. Freshw. Res. 62, 312\u2013320. P\u00f6rtner, H. (2001). Climate change and temperature-dependent biogeography: Oxygen limitation of thermal tolerance in animals. Naturwissenschaften 88, 137\u2013146. P\u00f6rtner, H. O. and Farrell, A. P. (2008). Physiology and climate change. Science (80-. ). 322, 690\u2013692. Radchuk, V., Reed, T., Teplitsky, C., van de Pol, M., Charmantier, A., Hassall, C., Adam\u00edk, P., Adriaensen, F., Ahola, M. P., Arcese, P., et al. (2019). Adaptive responses of animals to climate change are most likely insufficient. Nat. Commun. 2019 101 10, 1\u201314. Rahel, F. J. (2007). Biogeographic barriers, connectivity and homogenization of freshwater faunas: It\u2019s a small world after all. Freshw. Biol. 52, 696\u2013710. Raspopov, V., Sergeyeva, Y., Aseynov, D., Phung Nguyen, D., Attaala, A. M., Ali Attaala, C. M. and Aseynov, D. (2017). Comparative morphophysiological indices of Russian sturgeon from different years catch in the Volga River. Int. J. Fish. Aquat. Stud. 5, 306\u2013313. R\u00e4tz, H. J. and Lloret, J. (2003). Variation in fish condition between Atlantic cod (Gadus morhua) stocks, the effect on their productivity and management implications. Fish. Res. 60, 369\u2013380. Rezende, E. L., Casta\u00f1eda, L. E. and Santos, M. (2014). Tolerance landscapes in thermal ecology. Funct. Ecol. 28, 799\u2013809. Rinehart, J. P., Li, A., Yocum, G. D., Robich, R. M., Hayward, S. A. L. and Denlinger, D. L. (2007). Up-regulation of heat shock proteins is essential for cold survival during insect diapause. Proc. Natl. Acad. Sci. U. S. A. 104, 11130\u201311137.   69 Rohr, J. R., Civitello, D. J., Cohen, J. M., Roznik, E. A., Sinervo, B. and Dell, A. I. (2018). The complex drivers of thermal acclimation and breadth in ectotherms. Ecol. Lett. 21, 1425\u20131439. Rombough, P. J. (1988). Respiratory gas exchange, aerobic metabolism, and effects of hypoxia during early life. In Fish Physiology, pp. 59\u2013161. Academic Press. Rombough, P. J. (2011). The energetics of embryonic growth. Respir. Physiol. Neurobiol. 178, 22\u201329. Ruiz-Campos, G., Castro-Aguirre, J. L. and Garcia-De Leon, F. J. (2011). First specimen of the white sturgeon (acipenser transmontanus richardson, 1836) in coastal waters of Mexico with data on its genetic identity. Calif. Fish Game 97, 36\u201342. Saik\u2019Uz First Nation (2019). Saik\u2019uz & Stellat\u2019en First Nations v. Rio Tinto Alcan, Inc., British Columbia, & Canada\u2009:: Saik\u2019uz First Nation. Saik\u2019uz. Sandblom, E., Clark, T. D., Gr\u00e4ns, A., Ekstr\u00f6m, A., Brijs, J., Sundstr\u00f6m, L. F., Odelstr\u00f6m, A., Adill, A., Aho, T. and Jutfelt, F. (2016). Physiological constraints to climate warming in fish follow principles of plastic floors and concrete ceilings. Nat. Commun. 7,. Schaefer, J. F., Lutterschmidt, W. I. and Hill, L. G. (1999). Physiological performance and stream microhabitat use by the centrarchids Lepomis megalotis and Lepomis macrochirus. Environ. Biol. Fishes 54, 303\u2013312. Schmidt-Nielsen, K. (1990). Animal Physiology: Adaptation and Environment. 4th ed. Cambridge: Cambridge University Press. Schulte, P. M. (2015). The effects of temperature on aerobic metabolism: Towards a mechanistic understanding of the responses of ectotherms to a changing environment. J. Exp. Biol. 218, 1856\u20131866. Sharma, N. K., Akhtar, M. S., Pandey, N., Singh, R. and Singh, A. K. (2015). Seasonal variation in thermal tolerance, oxygen consumption, antioxidative enzymes and non-specific immune indices of Indian hill trout, Barilius bendelisis (Hamilton, 1807) from central Himalaya, India. J. Therm. Biol. 52, 166\u2013176. Soengas, J. L. and Aldegunde, M. (2002). Energy metabolism of fish brain. Comp. Biochem. Physiol. -- Part B Biochem. Mol. Biol. 131, 271\u2013296. Somero, G. N. (2010). The physiology of climate change: how potentials for acclimatization and genetic adaptation will determine \u2018winners\u2019 and \u2018losers.\u2019 J. Exp. Biol. 213, 912\u2013920.   70 Somero, G. N. (2020). The cellular stress response and temperature: Function, regulation, and evolution. J. Exp. Zool. Part A Ecol. Integr. Physiol. 333, 379\u2013397. Strayer, D. L. and Dudgeon, D. (2010). Freshwater biodiversity conservation: Recent progress and future challenges. J. North Am. Benthol. Soc. 29, 344\u2013358. Sunday, J. M., Bates, A. E. and Dulvy, N. K. (2012). Thermal tolerance and the global redistribution of animals. Nat. Clim. Chang. 2, 686\u2013690. Tomanek, L. and Somero, G. N. (2000). Time course and magnitude of synthesis of heat-shock proteins in congeneric marine snails (genus Tegula) from different tidal heights. Physiol. Biochem. Zool. 73, 249\u2013256. Van Ginneken, V., Nieveen, M., Van Eersel, R., Van den Thillart, G. and Addink, A. (1996). Neurotransmitter levels and energy status in brain of fish species with and without the survival strategy of metabolic depression. Comp. Biochem. Physiol. - A Physiol. 114, 189\u2013196. Vandesompele, J., Preter, K. De, Pattyn, F., Poppe, B., Roy, N. Van, Paepe, A. De and Speleman, F. (2002). Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 3, research0034.1. Vincent, L. A., Wang, X. L., Milewska, E. J., Wan, H., Yang, F. and Swail, V. (2012). A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis. J. Geophys. Res. Atmos. 117, 18110. Vincent, L. A., Zhang, X., Brown, R. D., Feng, Y., Mekis, E., Milewska, E. J., Wan, H. and Wang, X. L. (2015). Observed trends in Canada\u2019s climate and influence of low-frequency variability modes. J. Clim. 28, 4545\u20134560. Wang, Y. L., Binkowski, F. P. and Doroshov, S. I. (1985). Effect of temperature on early development of white and lake sturgeon, Acipenser transmontanus and A. fulvescens. Environ. Biol. Fishes 14, 43\u201350. Werner, I., Linares-Casenave, J., Van Eenennaam, J. P. and Doroshov, S. I. (2007). The effect of temperature stress on development and heat-shock protein expression in larval green sturgeon (Acipenser mirostris). Environ. Biol. Fishes 79, 191\u2013200. Woodward, G. (2009). Biodiversity, ecosystem functioning and food webs in fresh waters: Assembling the jigsaw puzzle. Freshw. Biol. 54, 2171\u20132187. Yebra-Pimentel, E. S., Reis, B., Gessner, J., Wuertz, S. and Dirks, R. P. H. (2020).   71 Temperature training improves transcriptional homeostasis after heat shock in juvenile Atlantic sturgeon (Acipenser oxyrinchus). Fish Physiol. Biochem. 46, 1653\u20131664. Yoon, G. R., Deslauriers, D. and Gary Anderson, W. (2019). Influence of a dynamic rearing environment on development of metabolic phenotypes in age-0 Lake Sturgeon, Acipenser fulvescens. Conserv. Physiol. 7,. Zhang, Y. and Kieffer, J. D. (2014). Critical thermal maximum (CTmax) and hematology of shortnose sturgeons (Acipenser brevirostrum) acclimated to three temperatures. Can. J. Zool. 92, 215\u2013221.  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