development and application of a spatially-explicit ...

DEVELOPMENT AND APPLICATION OF A SPATIALLY-EXPLICIT MODEL FOR ESTIMATING GROWTH OF AGE-0 PALLID STURGEON IN THE MISSOURI RIVER

BY DAVID DESLAURIERS

A dissertation submitted in partial fulfillment of the requirements for the Doctor of Philosophy Major in Wildlife and Fisheries Sciences South Dakota State University 2015

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QUOTE

“If one were to allocate research effort to fishes scaled by weight stanzas (physiological time) rather than by years (calendar time), one would spend much less time on large adults (where body size does not change much) and would concentrate on dynamics in the first year of life” Miller et al., 1988

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This dissertation is dedicated to the memory of Dr. Robert A. Klumb, who taught me to never lose focus of the “Prime Directive”.

v ACKNOWLEDGEMENTS I would first like to start off by thanking my advisor Steve Chipps, for all of his support, in depth reviews and discussions, and his overall role as a mentor. I would also like to thank Rob Klumb, Brian Graeb, Pat Braaten and Brian McLaren for their constructive feedback and their will to always push me to think critically and outside of the box. I would also like to thank Lorna Wounded-Head for showing an interest in my project even though Pallid Sturgeon are as unrelated to her field of study as can be. To Terri, Kate, Di, and Dawn, you are really great at what you do and I thank you for making my everyday life easier. The NRM Department and Coop Unit are lucky to have you. I would like to thank the South Dakota State University Comprehensive Ecology and Fisheries Discussion Group, which included Cari-Ann Hayer, Mark Kaemingk, Jason Breeggemann, Dan Dembkowski and Tobi Rapp. Weekly meetings with this group greatly facilitated my transition to the United States. I am mostly proud of the article we published together, which was no small feat. I would also like to thank Tobi and Laura Heironimus for constructive discussions we had about Pallid Sturgeon ecology and physiology. It was good to be able to share my yearly anxiety about potentially not getting fish. I also thank both of you for providing me with quality data to be able to run my models. I am truly grateful to Adam Janke and Doug Armstrong who always took the time to answers questions I had about R programming. They have been a great source of liberation after headache prone days.

vi I would like to thank the many technicians who have made my project possible. They are, in order of appearance: Chris and Aaron Sundmark, Taylor Ignazewski, Ryan Johnston, Lauren Kreigel, Larissa Bruce, Beth Schmitz, Thomas Larson, Zach Jesse, Anna Robinson, Alex Rosburg, and Wesley Bowen. I would like to thank Craig Bockholt and Jeffrey Powell at Gavin’s Point National Fish Hatchery, as well as Dana Kruger of the Valentine State Hatchery for making every effort possible so that I could get enough fish for my experiments. I would also like to thank Schuyler Sampson of the Nebraska Game and Parks Division, Todd Gemeinhardt and Marcus Miller of the U.S. Army Corps of Engineers, and Dan James, Kristen Grohs, Dane Schuman and Landon Pierce from the US Fish and Wildlife Service for providing me with environmental data. Their contribution was greatly appreciated. I would like to acknowledge the encouragement and excitement received throughout the years from my parents Debbie and Jean. They have always shown a keen interest in what I do and have taken the time to come and visit me on multiple occasions, even though Brookings is not the nearest place to Quebec City. Lastly, I would like to thank my beautiful wife-to-be, Erinn. I was very fortunate to be able to share my South Dakota experience with her, and I am looking forward to the many chapters to come. This past year will have been one for the ages!

Dissertation Playlist: Hans Zimmer, Érik Satie, Camille Saint-Saëns, Claude DeBussy, Philip Glass, Xavier Ruud, Metric, and The National.

vii CONTENTS ABSTRACT ....................................................................................................................... ix Chapter 1. INTRODUCTION ............................................................................................ 1 LITERATURE CITED ..................................................................................................... 11 Chapter 2. DEVELOPMENT AND EVALUATION OF A FORAGING MODEL FOR AGE-0 PALLID STURGEON ......................................................................................... 19 INTRODUCTION ............................................................................................................ 19 METHODS ....................................................................................................................... 22 RESULTS ......................................................................................................................... 33 DISCUSSION ................................................................................................................... 36 LITERATURE CITED ..................................................................................................... 41 Chapter 3. CRITICAL AND LETHAL THERMAL MAXIMA FOR AGE-0 PALLID AND SHOVELNOSE STURGEON: IMPLICATIONS FOR SHALLOW WATER HABITAT DEVELOPMENT .......................................................................................... 63 INTRODUCTION ............................................................................................................ 63 METHODS ....................................................................................................................... 65 RESULTS ......................................................................................................................... 68 DISCUSSION ................................................................................................................... 68 LITERATURE CITED ..................................................................................................... 73 Chapter 4. TEST OF A FORAGING-BIOENERGETICS MODEL TO EVALUATE GROWTH DYNAMICS OF AGE-0 PALLID STURGEON .......................................... 81

viii INTRODUCTION ............................................................................................................ 81 METHODS ....................................................................................................................... 83 RESULTS ......................................................................................................................... 92 DISCUSSION ................................................................................................................... 95 LITERATURE CITED ................................................................................................... 100 Chapter 5. DETERMINING GROWTH POTENTIAL OF AGE-0 PALLID STURGEON IN THE MISSOURI RIVER: INSIGHT FROM AN INDIVIDUAL BASED MODEL 117 INTRODUCTION .......................................................................................................... 117 METHODS ..................................................................................................................... 120 RESULTS ....................................................................................................................... 129 DISCUSSION ................................................................................................................. 132 LITERATURE CITED ................................................................................................... 138 Chapter 6. SUMMARY AND RESEARCH NEEDS .................................................... 153 LITERATURE CITED ................................................................................................... 158

ix ABSTRACT DEVELOPMENT AND APPLICATION OF A SPATIALLY-EXPLICIT MODEL FOR ESTIMATING GROWTH OF AGE-0 PALLID STURGEON IN THE MISSOURI RIVER DAVID DESLAURIERS 2015 Endemic to the Missouri and Mississippi rivers, the Pallid Sturgeon (Scaphirhynchus albus) has been listed as an endangered species since 1990. Construction of six main-stem dams along the Missouri River has altered spawning and nursery habitats, while obstructing upstream migrations of adults and downstream drift of larvae. Because of their scarcity in the wild, the biotic and abiotic requirements of age-0 Pallid Sturgeon larvae are not fully understood. This knowledge gap has been deemed significant because it is this life stage that is believed to act as a bottleneck to the recovery of the species. The objectives of my study were to 1) parameterize and evaluate a foraging model for age-0 Pallid Sturgeon, 2) evaluate the critical and lethal temperature maxima for Pallid and Shovelnose Sturgeon (Scaphirhynchus platorynchus) of different sizes and acclimated to different temperatures, 3) evaluate the performance of a combined foraging-bioenergetics model using a series of long-term feeding and growth trials, and 4) apply the foraging-bioenergetics model using empirical data from the Missouri River. The foraging model encompassed a Type II functional feeding response along with gut evacuation and satiation parameters to allow us to reliably estimate daily prey

x consumption of age-0 Pallid Sturgeon. Factors such as water temperature, prey type (Daphnia spp., Chironomidae and Ephemeroptera larvae) and prey density were all shown to significantly affect consumption rates of larval fish. Additionally, simulations of daily energy return of larval fish (19-50 mm) showed that a diet comprised entirely of zooplankton would be insufficient for fish to gain weight, as opposed to fish feeding on Chironomidae or Ephemeroptera larvae. The second objective aimed to understand the physiological limits of age-0 Scaphirhynchus spp. to acute increases in temperature (Critical and Lethal Thermal Maxima). While neither Pallid nor Shovelnose differed in their response to increasing temperatures, they were both strongly affected by body size and acclimation temperatures. As such, smaller fish acclimated at colder temperatures were less tolerant of higher temperatures when compared to larger fish acclimated at warmer temperatures. CTM (29.49-34.39°C) and LTM (29.95-35.71°C) values generated for both species, regardless of size or acclimation temperature, were also found to be higher than the maximum water temperatures observed in 5 shallow water habitats during the growing season of 2011. For the third objective, three different size classes of fish were grown for 7 to 14 days under differing temperature and prey density regimes. Observed final weight, final length, and total number of prey consumed were compared to values generated from the foraging-bioenergetics model. The model provided reliable estimates (within 13% of observations) of fish weight, length, and prey consumed after the bioenergetics portion of the model had been calibrated to account for temperature and prey density effects.

xi Lastly, I used an individual-based modeling approach to estimate the influence of temperature, velocity, and prey abundance on age-0 Pallid Sturgeon growth. To do so, empirical data from three sites of the Missouri River were used to generate growth outputs (weight and length) for a 100-day growing season. Higher growth was shown to occur at sites where high densities of Ephemeroptera and Chironomidae larvae occurred throughout the growing season. Shallow water habitats with temperatures ranging from 17 to 25 °C and moderate water velocities (0.3 m/s) were also found to positively affect growth rates.

1 Chapter 1. INTRODUCTION Pallid Sturgeon (Scaphirhynchus albus Forbes and Richardson 1905) are an endemic species of the Missouri River, the middle and lower Mississippi River and the Atchafalaya River. They have been listed as a federally endangered species since 1990 (Dryer and Sandvol 1993) due to lack of natural recruitment owing to a) habitat modification, b) commercial harvest and, c) hybridization with the sympatric Shovelnose Sturgeon (Scaphirhynchus platorhynchus Rafinesque 1820). Historical population estimates for adult Pallid Sturgeon are scarce and variable between the different reaches of the Missouri and Mississippi Rivers (Duffy et al. 1996). This is due in part to morphological similarities between Pallid and Shovelnose Sturgeon, historically leading biologists and others (i.e., commercial fishermen) to categorize both species as the same (Keenlyne 1995). In the past 60 years populations have declined dramatically (Keenlyne 1989), with most remaining wild individuals characterized by large, old fish (Duffy et al. 1996, Jordan et al. 2006; Braaten et al. 2009; Steffensen et al. 2012). Natural reproduction, as evidenced by larvae capture and juvenile recruitment, has not been reported for any of the upper and middle Missouri River reaches until recently (Braaten 2014) while lower Missouri and Mississippi reaches had not generated data until 1998, when larval fish were collected in small numbers (Herzog et al. 2005, Hrabik et al. 2007). Small juveniles have been observed in the Atchafalaya River, which suggests that natural reproduction is occurring in this system (Bergman 2008). In order to avoid further extirpation of the species, the U.S. Fish and Wildlife Service implemented a propagation plan aimed at increasing the abundance of Pallid Sturgeon in the Missouri River (Dryer and Sandvol 1993, Bergman 2008). These efforts

2 have been successful so far in that stocked juvenile Pallid Sturgeon are being recaptured and are displaying positive growth (Jordan et al. 2006). However, sexual maturation of stocked individuals has not been observed so far (Steffensen et al. 2010). Many factors are believed to have contributed to the decline of Pallid Sturgeon populations. A series of six hydroelectric and flood control dams along the Missouri River have changed riverine conditions (Johnson et al. 2014), resulting in a) the disruption of natural flows, b) temperature regime alterations, c) decreased turbidity, and d) habitat loss. In addition, dams act as physical barriers to upstream spawning migrations and may limit downstream larval drift (Braaten et al. 2011). Channelization has also been found to negatively impact sturgeon species as it often reduces habitat availability (i.e., lateral connectivity) and increases water current velocities (Funk and Robinson 1974, Jacobson and Galat 2006). It has been shown that more than half of the original habitat available to sturgeon is now adversely affected by channels (e.g., flow, turbidity, availability; Phelps et al. 2010). This notion becomes particularly important for early life stages, where swimming abilities are poor, and where the odds of entrainment are increased due to high flows (Adams et al. 1999, Hoover et al. 2011) . The cumulative effect of habitat changes has no doubt contributed to the species decline in the Missouri-Mississippi River system. As a result, the US Fish and Wildlife Service developed a Biological Opinion (BiOp) in 2003 that argues for the construction of shallow water habitat (SWH) as part of the Missouri River recovery program (Schapaugh et al. 2010). The primary objective was to construct up to 5,000 ha of SWH by 2015 and 8,000 ha by 2020. The construction of SWH, by means of flow management, channel widening, chute and side channel restoration is meant, in part, to

3 increase nursery grounds for native fish larvae including Pallid Sturgeon (Gosch et al. 2015). Other objectives that may lead to the increase in native fish abundance, include a) the enhancement of primary and secondary production, b) the increase of channel complexity and, b) the even distribution of SWH throughout the targeted segments. In order to better comprehend the impact of mitigation efforts, there is a need for an understanding of basic ecological and biological processes about specific life stages (Bergman 2008, Wildhaber et al. 2011). In particular, the exogenous feeding stage is believed to act as a critical phase (i.e., bottleneck) in Pallid Sturgeon recruitment, and to be most susceptible to changes in SWH and migration corridors (Braaten et al. 2011, Gemeinhardt et al. 2015). Early life history and environmental requirements The larval stage of fishes is often seen as a recruitment bottleneck because of its increased vulnerability to environmental disturbances (Dettlaff et al. 1993, Scheidegger and Bain 1995, Humphries et al. 2002). Knowledge pertaining to early life stages is difficult to gather in a field setting due in part to low recruitment numbers combined with inefficient sampling protocols (Hrabik et al. 2007, Braaten et al. 2010). One of the main reasons for Pallid Sturgeon decline within its range can be attributed to inadequate environmental conditions for reproduction and/or larval growth and development (DeLonay et al. 2009). In naturally occurring temperate riverine environments, flow increases in the spring combined with the rise in temperatures are believed to trigger spawning migrations in most sturgeon species (Auer 1996). In the Missouri River, two peaks in flow occur during the spring, one associated with snow melt in the Northern Great Plains in April-May and another resulting from mountain snow melt from the

4 eastern Rocky Mountains in June. This second peak in flow has historically been linked to Pallid Sturgeon spawning events in the upper portion of the species range (Braaten et al. 2015). The increased flow also serves the purpose of dispersing free embryos downstream in order for them to reach nursery habitats (Kynard et al. 2007, Braaten et al. 2011). Larval Pallid Sturgeon are known to hatch in late spring to early summer when water temperatures range between 16 and 20C (DeLonay et al. 2009). Incubation of adhesive eggs is temperature-dependent and may take up to 14 days at 12C (Kappenman et al. 2013). Once hatched, free embryos (8-9 mm; Snyder 2002) drift downstream until they deplete their yolk-sac reserves (~200 cumulative thermal units; sum of daily water temperature, °C) and reach adequate habitat to begin exogenous feeding (Kynard et al. 2002, 2007, Braaten et al. 2008). Peak larval migration (i.e., longest drift distance traveled downstream) is believed to occur on days 0-3 post-hatch at 20C, after which migration decreases significantly, coinciding with the onset of exogenous feeding (Kynard et al. 2002). Migration has been estimated to exceed distances of 500 km depending on water velocity. Larval fish have been found to double in length during this period (Braaten et al. 2008) . As in most fish species, temperature has been found to be the most limiting factor for sturgeon in regulating metabolic rate (Brett and Groves 1979) and growth (Rome and Sosnicki 1990). Temperatures experienced during early life stages can influence growth and survival (i.e., fitness; Álvarez et al. 2006, Loizides et al. 2014). Juvenile Pallid Sturgeon have demonstrated optimal growth potential at temperatures ranging from 26-28C, with higher temperatures (30-35C) contributing to decreased foraging

5 efficiency and increased mortality rate (Chipps et al. 2008). It has been hypothesized that the ability of Pallid Sturgeon to cope with high temperatures (i.e., > 28C) would be reduced at earlier life stages (Blevins 2011). Evidence of this intolerance has been reported by Heironimus (2015) where decreased consumption rates were observed at temperatures higher than 24°C for age-0 fish. A limited number of studies have linked habitat attributes to the presence or absence of larval Pallid Sturgeon. A small number of larval Scaphirhynchus spp. have been captured along islands of the Mississippi River that are often associated with sandy substrates, moderate depth (2-5 m) and low water velocities (~10 cm s-1; Hrabik et al. 2007, Phelps et al. 2010). Similarly, it has been suggested that age-0 Pallid Sturgeon become more tolerant of environmental conditions (e.g., water velocity) as they get larger in size (Ridenour et al. 2011, Gemeinhardt et al. 2015). This might be due in part to sand troughs that act as a velocity shelter for larval and juvenile Pallid Sturgeon (27-200 mm), where individuals select positively for sandy substrates, negatively for woody debris and prefer dark areas associated with velocities ranging from 0-33 cm s-1 (Allen et al. 2006). Interestingly, a separate study has shown that Pallid Sturgeon are slightly photonegative during the first hours post hatch but become photopositive afterwards (i.e., day 1-9; Kynard et al. 2002). Foraging ecology During the first month post-hatch, larval fish go through important morphological and physiological changes where yolk is absorbed and tissue is produced (Kamler 2007). These changes can be differentiated morphologically into three distinct phases (i.e., protolarvae, mesolarvae and metalarvae) based mostly on fin ray appearance and

6 development (Snyder 2002). However, this descriptive approach does not necessarily delineate transitions between different physiological states. In this sense, a more appropriate nomenclature would be to determine larval stages based on energy sources, since it is the assimilation rate of the energy source that will dictate development. For Pallid Sturgeon, yolk-sac drifting larvae have been termed the free embryo stage while exogenously feeding fish are known as the larvae stage (Kynard et al. 2002, Wildhaber et al. 2011). Pallid Sturgeon, unlike Shovelnose Sturgeon, have been known to demonstrate ontogenetic diet shifts, switching from feeding exclusively on macroinvertebrates at sizes < 250 mm, to becoming piscivores at sizes > 600 mm (Grohs et al. 2009). At the onset of exogenous feeding, larval Pallid Sturgeon have been shown to select positively for Diptera spp. (Chironomidae), and neutrally for zooplankton and mayfly larvae (Ephemeroptera; Rapp 2015). Field observations appear to agree with results observed in the laboratory, where the majority of re-captured age-0 Pallid Sturgeon contained Chironomidae and Ephemeroptera larvae in their gut (Braaten et al. 2012) . Fish follow the traditional predatory sequence (i.e., search, orientation, pursuit, reject/strike, capture, ingest/expulse) when attempting to capture prey items (O’Brien 1979). This sequence results in fish typically displaying a type II functional feeding response (Holling 1959), where ingestion is directly correlated with prey density until handling time becomes limiting, resulting in the plateauing of prey capture at higher prey densities. Fish have also been shown to alter their feeding response when differences in biotic factors such as prey type (Galarowicz and Wahl 2005, Brachvogel et al. 2012), prey size (Vince et al. 1976, Wanzenböck 1995), predator size (Miller et al. 1992, Galarowicz and Wahl 2005), and inter-specific competition (Persson 1987, Alexander et

7 al. 2013) occur. Abiotic factors such as water temperature (Lefébure et al. 2014, Watz et al. 2014), light (Koski and Johnson 2002, Watz et al. 2013) and prey refuge (Buckel and Stoner 2000, Anderson 2001) have also been shown to affect capture rates. Thus, functional feeding responses can offer unique insight into prey consumption rates. However, these models have been found to over-estimate consumption when extrapolated beyond the period of time under which the trials are conducted (Jeschke et al. 2002). Functional feeding models can be linked with gut evacuation models (Persson 1982, Bochdansky et al. 2006) to help determine if a fish’s consumption rate is limited by its time spent handling prey or by its digestive process. This approach has been shown to provide more realistic estimates of food consumption (Jeschke and Hohberg 2008) . Growth Bioenergetics models can be used as a tool to estimate growth of fish under specific conditions in order to assess habitat suitability (Brandt and Kirsch 1993). These models are usually developed in a laboratory setting and corroborated against empirical data collected from the fish’s natural habitat. While bioenergetics work has been increasing in popularity since the work of Kitchell et al. (1977), models focusing on sturgeon species are limited (Cui et al. 1996, Bevelhimer 2002, Mayfield and Cech 2004, Chipps et al. 2008, Niklitschek and Secor 2009, Heironimus 2015). Furthermore, because of space availability or equipment restrictions, sturgeon bioenergetics models have been developed mostly for larvae and juveniles while none currently exist for adult fish. Bioenergetics work for earlier life stages is essential since extrapolation of older life stage parameters has been shown to underestimate consumption, metabolic rate and swimming speed in larval fish (Post 1990, Klumb et al. 2003).

8 Conceptually, bioenergetics models balance food consumption with 1) metabolic demands (i.e., standard/active metabolic rates (Ms/Ma) and specific dynamic action (SDA)), 2) waste losses (i.e., excretion (U) and egestion (F)) and 3) growth processes (i.e., somatic and gonadal growth (C); Winberg 1956, Hanson 1997). The conceptual model can be expressed mathematically, where standard metabolism is modeled as a function of body mass and water temperature, while other parameters are usually defined as either a constant proportion of consumed energy (i.e., SDA, F, and U) or as a fixed multiplier of standard metabolism (i.e., Ma; Kitchell et al. 1977). Activity levels have been shown to be higher in larval fish than for their adult counterpart (Post 1990, Hartman and Brandt 1995), and have often been found to increase with prey density (Madon and Culver 1993) and temperature (Mayfield and Cech 2004). Individual-based models Valuable insight can be gained when foraging and bioenergetics models are combined. One popular method that allows for this is the application of individual-based models (IBMs; DeAngelis and Grimm 2014). Traditionally, IBMs applied to fisheries have attempted to elucidate recruitment mechanisms (Winkle et al. 1993). IBMs allow for discrete entities (e.g., individual fish) to interact with each other and their environment (in a virtual environment) following a series of predetermined biological and physical rules that are usually derived from laboratory and empirical data (Goto et al. 2015). Many of these models are placed in a spatially-explicit context (Clark et al. 2001) that allows for individuals to encounter a variety of conditions that will positively or negatively affect the output of interest (e.g., fish growth). Outputs range from size distributions, fitness indicators (e.g., egg production), mortality rates to habitat use and are termed

9 emergent properties since results could not have been predicted by well-established population dynamic models (DeAngelis and Grimm 2014). These model outputs can help explain the mechanism behind field observations and can serve an important role in hypothesis testing (Rose et al. 2008). In that sense, IBMs have proven useful in facilitating work on rare or endangered species (Letcher et al. 1998, Rose et al. 2013). Research Objectives There is a critical need for physiological and behavioral information pertaining to early life stages of Pallid Sturgeon. To address these needs, my dissertation has been divided into five chapters. In the first chapter (chapter 2), the objectives were to parameterize and evaluate the performance of a foraging model for age-0 Pallid Sturgeon. To do so, functional feeding responses were quantified for varying sizes of fish feeding at different densities of zooplankton, Chironomidae and Ephemeroptera larvae. The effects of temperature, prey size, and substrate were also tested. In addition, the foraging model included a gut evacuation and satiation component, meant to regulate the amount of prey that could be consumed over the course of a day. In chapter 3, the critical (i.e., CTM; temperature at which the fish lose equilibrium) and lethal temperature maxima (i.e., LTM; temperature at which fish die) for Pallid and Shovelnose Sturgeon of different sizes and acclimated to different temperatures were quantified. The values generated in this chapter will serve as guidelines for the development and evaluation of SWH. The models generated from chapter 2 and 3 served as inputs for the bioenergetics model (Heironimus 2015). To evaluate the model performance, a series of growth trials (7-14 d) were performed where growth observations were compared to model predictions (chapter 4). Lastly, the foraging-bioenergetics model was applied using empirical data from the

10 Missouri River (Chapter 5). To do so, I used an individual-based modeling approach to evaluate the influence of spatial variation in prey composition, prey abundance, water temperature, and water velocity on larval Pallid Sturgeon growth. This chapter also explores two hypotheses that relate to the influence of environmental conditions that are believed to affect growth of Pallid Sturgeon larvae. In the concluding chapter (Chapter 6), recommendations are made towards future directions and research needs that should be considered in the conservation and management of Pallid Sturgeon.

11 LITERATURE CITED Adams, S.R., J.J. Hoover, and K.J. Killgore. 1999. Swimming endurance of juvenile pallid sturgeon, Scaphirhynchus albus. Copeia 3: 802-807. Alexander, M.E., J.T.A. Dick, and N.E. O’Connor. 2013. Trait‐ mediated indirect interactions in a marine intertidal system as quantified by functional responses. Oikos 122(11): 1521-1531. Álvarez, D., J.M. Cano, and A.G. Nicieza. 2006. Microgeographic variation in metabolic rate and energy storage of brown trout: countergradient selection or thermal sensitivity? Evolutionary Ecology 20(4):345-363. Anderson, T.W. 2001. Predator responses, prey refuges, and density-dependent mortality of a marine fish. Ecology 82: 245-257. Auer, N.A. 1996. Importance of habitat and migration to sturgeons with emphasis on lake sturgeon. Canadian Journal of Fisheries and Aquatic Sciences 53(S1): 152-160. Bergman, H. L. 2008. Research needs and management strategies for pallid sturgeon recovery. Proceedings of a Workshop held July 31-August 2, 2007, St. Louis, Missouri, Bevelhimer, M.S. 2002. A bioenergetics model for white sturgeon Acipenser transmontanus: assessing differences in growth and reproduction among Snake River reaches. Journal of Applied Ichthyology 18(4-6):550-556. Blevins, DW. 2011. Water-quality requirements, tolerances, and preferences of pallid sturgeon (Scaphirhynchus albus) in the lower Missouri River. U.S. Geological Survey, 2011-5186, Reston, Virginia, 24 pp. Bochdansky, A.B., N.D. Brunemeyer, and W.C. Leggett. 2006. Model evaluation of linear gut evacuation in the larval radiated shanny using a combination of laboratory and field Data. Transactions of the American Fisheries Society 135(2): 390-398. Braaten, PJ. 2014. Spawning of Endangered Pallid Sturgeon in the Yellowstone River, Montana and North Dakota. American Fisheries Society Annual Meeting Abstract, August 17-21, Québec, Canada. Braaten, P., D. Fuller, L. Holte, R. Lott, W. Viste, T. Brandt, and R. Legare. 2008. Drift dynamics of larval pallid sturgeon and shovelnose sturgeon in a natural side channel of the upper Missouri River, Montana. North American Journal of Fisheries Management 28(3):808-826. Braaten, P.J., D. Fuller, R.D. Lott, M.P. Ruggles, and R.J. Holm. 2010. Spatial distribution of drifting pallid sturgeon larvae in the Missouri River inferred from two net designs and multiple sampling locations. North American Journal of

12 Fisheries Management 30(4): 1062-1074. Braaten, P.J., D.B. Fuller, R.D. Lott, M.P. Ruggles, T.F. Brandt, R.G. Legare, and R.J. Holm. 2011. An experimental test and models of drift and dispersal processes of pallid sturgeon (Scaphirhynchus albus) free embryos in the Missouri River. Environmental Biology of Fishes 93(3):377-392. Braaten, P.J., D.B. Fuller, R.D. Lott, T.M. Haddix, L.D. Holte, R.H. Wilson, M.L. Bartron, J.A. Kalie, P.W. DeHaan, W.R. Ardren, R.J. Holm, and M.E. Jaeger. 2012. Natural growth and diet of known-age pallid sturgeon (Scaphirhynchus albus) early life stages in the upper Missouri River basin, Montana and North Dakota. Journal of Applied Ichthyology:1-9. Braaten, P.J., D.B. Fuller, R.D. Lott, and G.R. Jordan. 2012. An estimate of the historic population size of adult pallid sturgeon in the upper Missouri River Basin, Montana and North Dakota. Journal of Applied Ichthyology 25(Suppl. 2):2-7. Braaten, P.J., C.M. Elliott, J.C. Rhoten, D.B. Fuller, and B.J. McElroy. 2015. Migrations and swimming capabilities of endangered pallid sturgeon (Scaphirhynchus albus) to guide passage designs in the fragmented Yellowstone River. Restoration Ecology 23(2):186–195. Brachvogel, R., L. Meskendahl, J.-P. Herrmann, and A. Temming. 2012. Functional responses of juvenile herring and sprat in relation to different prey types. Marine Biology 160(2): 465-478. Brandt, S.B., and J. Kirsch. 1993. Spatially explicit models of striped bass growth potential in Chesapeake Bay. Transactions of the American Fisheries Society 122(5): 845-869. Brett, J.R., and T.D.D. Groves. 1979. Physiological Energetics. Fish Physiology 8: 279352. Buckel, J.A., and A.W. Stoner. 2000. Functional response and switching behavior of young-of-the-year piscivorous bluefish. Journal of Experimental Marine Biology and Ecology 245: 25-41. Chipps, S.R., R.A. Klumb, and E.B. Wright. 2008. Development and application of juvenile pallid sturgeon bioenergetics model. South Dakota Department of Game, Fish and Parks, Pierre, South Dakota, 40 pp. Clark, M.E., K.A. Rose, and D.A. Levine. 2001. Predicting climate change effects on Appalachian trout: Combining GIS and individual-based modeling. Ecological Applications 11(1): 161-178. Cui, Y., S.S.O. Hung, and X. Zhu. 1996. Effect of ration and body size on the energy budget of juvenile white sturgeon. Journal of Fish Biology 49(5): 863-876.

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DeAngelis, D.L., and V. Grimm. 2014. Individual-based models in ecology after four decades. F1000Prime Reports: 6-39. DeLonay, A.J., R.B. Jacobson, and D.M. Papoulias. 2009. Ecological requirements for pallid sturgeon reproduction and recruitment in the Lower Missouri River: a research synthesis 2005–08. U.S. Geological Survey Scientific Investigations Report 2009–5201, 59 pp. Dettlaff, T.A., A.S. Ginsburg, O.I. Schmalhausen, and G.G. Gause. 1993. Sturgeon fishes: developmental biology and aquaculture. Springer-Verlag Berlin Heidelberg, 300 pp. Dryer, M.P., and A.J. Sandvol. 1993. Recovery plan for the pallid sturgeon (Scaphirhynchus albus). U.S. FIsh And Wildlife Service, Denver, Colorado, 64pp. Duffy, W.G., C.R. Berry, and K.D. Keenlyne. 1996. The pallid sturgeon biology and annotated bibliography through 1994. South Dakota Cooperative Wildlife Research Unit, South Dakota State University, 32 pp. Funk, J.L., and J.W. Robinson. 1974. Changes in the channel of the lower Missouri River and effects on fish and wildlife. Missouri Department of Conservation , Jefferson City, Missouri, 52 pp. Galarowicz, T.L., and D.H. Wahl. 2005. Foraging by a young-of-the-year piscivore: the role of predator size, prey type, and density. Canadian Journal of Fisheries and Aquatic Sciences 62(10): 2330-2342. Gemeinhardt, T.R., N.J.C. Gosch, D.M. Morris, M.L. Miller, T.L. Welker, and J.L. Bonneau. 2015. Is shallow water a suitable surrogate for assessing efforts to address pallid sturgeon population declines? River Research and Applications. Gosch, N.J.C., M.L. Miller, T.R. Gemeinhardt, S.J. Sampson, and J.L. Bonneau. 2015. Age-0 sturgeon accessibility to constructed and modified chutes in the Lower Missouri River. North American Journal of Fisheries Management 35: 75-85. Goto, D., M.J. Hamel, J.J. Hammen, M.L. Rugg, M.A. Pegg, and V.E. Forbes. 2015. Spatiotemporal variation in flow-dependent recruitment of long-lived riverine fish: Model development and evaluation. Ecological Modelling 296: 79-92. Grohs, K.L., R.A. Klumb, S.R. Chipps, and G.A. Wanner. 2009. Ontogenetic patterns in prey use by pallid sturgeon in the Missouri River, South Dakota and Nebraska. Journal of Applied Ichthyology 25(s2): 48-53. Hanson, P.C., T.B. Johnson, D.E. Schindler, and J.F. Kitchell. 1997. Fish bioenergetics 3.0 for Windows. University of Wisconsin Sea Grant, 116 pp.

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15 Transactions of the American Fisheries Society 135: 1499-1511. Kalie, P.W. DeHaan, W.R. Ardren, R.J. Holm, and M.E. Jaeger. 2012. Natural growth and diet of known-age pallid sturgeon (Scaphirhynchus albus) early life stages in the upper Missouri River basin, Montana and North Dakota. Journal of Applied Ichthyology 28(4): 496-504. Kamler, E. 2007. Resource allocation in yolk-feeding fish. Reviews in Fish Biology and Fisheries 18(2): 143-200. Kappenman, K.M., M.A.H. Webb, and M. Greenwood. 2013. The effect of temperature on embryo survival and development in pallid sturgeon Scaphirhynchus albus (Forbes & Richardson 1905) and shovelnose sturgeon S. platorynchus (Rafinesque, 1820). Journal of Applied Ichthyology 29(6): 1193-1203. Keenlyne, K.D. 1989. A report on the pallid sturgeon. U.S. Fish and Wildlife Service, Pierre, South Dakota. Keenlyne, K.D. 1995. Recent North American studies on pallid sturgeon Scaphirhynchus albus (Forbes and Richardson). VNIRO Publishing, Moscow, Russia. 225–234. Kitchell, J.F., D.J. Stewart, and D. Weininger. 1977. Applications of a bioenergetics model to yellow perch (Perca flavescens) and walleye (Stizostedion vitreum vitreum). Journal of the Fisheries Research Board of Canada 34(10): 1922-1935. Klumb, R.A., L.G. Rudstam, and E.L. Mills. 2003. Comparison of alewife young-of-theyear and adult respiration and swimming speed bioenergetics model parameters: Implications of extrapolation. Transactions of the American Fisheries Society 132(6): 1089-1103. Koski, M.L., and B.M. Johnson. 2002. Functional response of kokanee salmon (Oncorhynchus nerka) to Daphnia at different light levels. Canadian Journal of Fisheries and Aquatic Sciences 59: 707-716. Kynard, B., E. Henyey, and M. Horgan. 2002. Ontogenic behaviour, migration, and social behaviour of pallid sturgeon and shovelnose sturgeon with notes on the adaptive significance of body color. Environmental Biology of Fishes 63(4): 389403. Kynard, B., E. Parker, D. Pugh, and T. Parker. 2007. Use of laboratory studies to develop a dispersal model for Missouri River pallid sturgeon early life intervals. Journal of Applied Ichthyology 23(4): 365-374. Lefébure, R., S. Larsson, and P. Byström. 2014. Temperature and size-dependent attack rates of the three-spined stickleback (Gasterosteus aculeatus); are sticklebacks in the Baltic Sea resource-limited? Journal of Experimental Marine Biology and

16 Ecology 451: 82-90. Letcher, B.H., J.A. Priddy, J.R. Walters, and L.B. Crowder. 1998. An individual-based, spatially-explicit simulation model of the population dynamics of the endangered red-cockaded woodpecker, Picoides borealis. Biological Conservation 86: 1-14. Loizides, M., E. Georgakopoulou, M. Christou, M. Iliopoulou, I. Papadakis, P. Katharios, P. Divanach, and G. Koumoundouros. 2014. Thermally-induced phenotypic plasticity in gilthead seabream Sparus aurata L. (Perciformes, Sparidae). Aquaculture 432: 383-388. Madon, S.P., and D.A. Culver. 1993. Bioenergetics model for larval and juvenile walleyes: an in situ approach with experimental ponds. Transactions of the American Fisheries 122(5): 797-813. Mayfield, R.B., and J.J. Cech Jr. 2004. Temperature effects on green sturgeon bioenergetics. Transactions of the American Fisheries 133(4): 961-970. Miller, T.J., L.B. Crowder, J.A. Rice, and F.P. Binkowski. 1992. Body size and the ontogeny of the functional response in fishes. Canadian Journal of Fisheries and Aquatic Sciences 49: 805-812. Niklitschek, E.J., and D.H. Secor. 2009. Dissolved oxygen, temperature and salinity effects on the ecophysiology and survival of juvenile Atlantic sturgeon in estuarine waters: I. Laboratory results. Journal of Experimental Marine Biology and Ecology 381(S1): S150-S160. O’Brien, WJ. 1979. The predator-prey interaction of planktivorous fish and zooplankton. American Scientist 67(5): 572-581. Persson, L. 1982. Rate of food evacuation in roach (Rutilus rutilus) in relation to temperature, and the application of evacuation rate estimates for studies on the rate of food consumption. Freshwater Biology 12(3): 203-210. Persson, L. 1987. Effects of habitat and season on competitive interactions between roach (Rutilus rutilus) and perch (Perca fluviatilis). Oecologia 73(2): 170-177. Phelps, Q.E., S.J. Tripp, J.E. Garvey, D.P. Herzog, D.E. Ostendorf, J.W. Ridings, J.W. Crites, and R.A. Hrabik. 2010. Habitat use during early life history infers recovery needs for shovelnose sturgeon and pallid sturgeon in the Middle Mississippi River. Transactions of the American Fisheries Society 139(4): 10601068. Post, J. 1990. Metabolic allometry of larval and juvenile yellow perch (Perca flavescens): In situ estimates and bioenergetic models. Canadian Journal of Fisheries and Aquatic Sciences 47(3): 554-560.

17 Rapp, T. 2015. Determinants of growth and survival of larval pallid sturgeon: A combined laboratory and field approach. South Dakota State University, Brookings, South Dakota, 189 pp. Ridenour, C.J., W.J. Doyle, and T.D. Hill. 2011. Habitats of age-0 Sturgeon in the Lower Missouri River. Transactions of the American Fisheries Society 140(5): 13511358. Rome, L.C., and A.A. Sosnicki. 1990. The influence of temperature on mechanics of red muscle in carp. The Journal of Physiology 427: 151-169. Rose, K.A., W.J. Kimmerer, K.P. Edwards, and W.A. Bennett. 2013. Individual-based modeling of delta smelt population dynamics in the Upper San Francisco Estuary: II. Alternative baselines and good versus bad Years. Transactions of the American Fisheries Society 142(5): 1260-1272. Rose, K.A., E.S. Rutherford, D.S. McDermot, J.L. Forney, and E.L. Mills. 2008. Individual-based model of yellow perch and walleye populations in Oneida Lake. Ecological Monographs 69(2): 127-154. Schapaugh, A., T.L. Miller, and A.J. Tyre. 2010. The pallid sturgeon habitat assessment and monitoring program 2007‐ 2009. U.S. Army Corps of Engineers, 39 pp. Scheidegger, K.J., and M.B. Bain. 1995. Larval fish distribution and microhabitat use in free-flowing and regulated rivers. Copeia 1: 125-135. Snyder, D.E. 2002. Pallid and shovelnose sturgeon larvae - morphological description and identification. Journal of Applied Ichthyology 18(4-6): 240-265. Steffensen, K.D., L.A. Powell, and J.D. Koch. 2010. Assessment of hatchery-reared pallid sturgeon survival in the Lower Missouri River. North American Journal of Fisheries Management 30(3): 671-678. Steffensen, K.D., L.A. Powell, and M.A. Pegg. 2012. Population size of hatchery-reared and wild Pallid Sturgeon in the Lower Missouri River. North American Journal of Fisheries Management 32: 159-166. Vince, S., I. Valiela, N. Backus, and J.M. Teal. 1976. Predation by the salt marsh killifish Fundulus heteroclitus (L.) in relation to prey size and habitat structure: Consequences for prey distribution and abundance. Journal of Experimental Marine Biology and Ecology 23(3): 255-266. Wanzenböck, J. 1995. Changing handling times during feeding and consequences for prey size selection of 0+ zooplanktivorous fish. Oecologia 104(3): 372-378. Watz, J., E. Bergman, J. Piccolo, and L. Greenberg. 2014. Prey capture rates of two

18 species of salmonids (Salmo trutta and Thymallus thymallus) in an artificial stream: effects of temperature on their functional response. Marine and Freshwater Behaviour and Physiology 47(2): 93-99. Watz, J., J. Piccolo, E. Bergman, and L. Greenberg. 2013. Day and night drift-feeding by juvenile salmonids at low water temperatures. Environmental Biology of Fishes 97(5): 505-513. Wildhaber, M.L., A.J. DeLonay, D.M. Papoulias, D.L. Galat, R.B. Jacobson, D.G. Simpkins, P.J. Braaten, C.E. Korschgen, and M.J. Mac. 2011. Identifying structural elements needed for development of a predictive life-history model for pallid and shovelnose sturgeons. Journal of Applied Ichthyology 27(2): 462-469. Winberg, GG. 1956. Rate of metabolism and food requirements of fishes. Fisheries Research Board of Canada, Nanaimo, British Colombia, 202 pp. Winkle, W.V., K.A. Rose, and R.C. Chambers. 1993. Individual-based approach to fish population dynamics: An overview. Transactions of the American Fisheries Society 122(3): 397-403.

19 Chapter 2. DEVELOPMENT AND EVALUATION OF A FORAGING MODEL FOR AGE-0 PALLID STURGEON

INTRODUCTION Factors affecting the growth and survival of fishes during early life history can have an important influence on recruitment dynamics (Madenjian and Carpenter 1991, Fulford et al. 2006). More often than not, early life stages are elusive to sampling gear or visual observation because of the heterogeneity of habitats they live in, and are thus difficult to assess (Paradis et al. 2008). Because of this, the capacity to estimate nutritional requirements of early life stages of fishes poses a challenge because ecological behaviors and physiological requirements are often unknown (Nunn et al. 2011). However, modeling approaches exist (e.g., individual-based models) that can, if implemented correctly, compensate for the lack of empirical data. The development and application of reliable models have proven to be an important assessment approach (Winkle et al. 1997, Nes et al. 2002), especially when the species of interest is rare or endangered (Morita and Yokota 2002, Bestgen et al. 2006) . One approach for quantifying feeding rate of larval fishes is the development of functional foraging models (Holling 1959). Foraging models have been useful in understanding predator-prey interactions that can affect short (e.g., growth) and long (e.g., fitness) term dynamics of the species involved (Moustahfid et al. 2010, Hunsicker et al. 2011, Rall et al. 2012). From a modeling perspective, the simplicity of quantifying and applying functional feeding responses makes them an appealing methodology to implement in a foraging model framework. Studies of functional feeding responses often rely on short-term ( 50 mm (Rapp 2015). Feeding trials were conducted in aquaria (900 mL for 18-30 mm size classes and 2600 mL for 40-70 mm size classes) that were placed in a water bath (450 L raceways) where water temperature was controlled using either a bayonet heater (1700W; Process Technology, Mentor, OH) or a chiller unit (Frigid Units, model D1-33, Toledo, OH) set to maintain target temperatures of 14, 18, or 24°C. Small pumps were placed at either end of the raceways to ensure a uniform temperature was maintained. The range of prey densities used in the feeding trials was chosen based on values reported for the Missouri River (Grohs 2009; Rapp 2015). Daphnia spp. densities ranged from 15 to 90/L, whereas Chironomidae and Ephemeroptera densities ranged from approximately 150 to 900/m2 (Grohs 2009). Chironomidae larvae were collected in a local pond and transported to the laboratory where they were sorted using 250, 500 and 750 μm sieves. Mean size of prey (mm) used on the day a feeding trial was completed

26 was quantified from digital pictures (n=3) of 10 individual prey items. Pictures were imported into Image J (Abràmoff et al. 2004) and prey size distributions were generated. Because Chironomidae represent an important component of young Pallid Sturgeon diets (Braaten et al. 2012, Sechler et al. 2012, Harrison et al. 2014), I conducted feeding trials using four size groups of chironomids that included small (6.07 mm ± 1.52 S.D.; 0.002 g ± 0.001 S.D.), medium (9.17 mm ± 1.49 S.D.; 0.005 g ± 0.001 S.D.), large (11.49 mm ± 1.63 S.D.; 0.010 g ± 0.002 S.D.) or mixed (9.38 mm ± 2.71 S.D.) size classes. Moreover, feeding trials using the “mixed” size chironomids were performed with or without sand substrate. These additional trials were conducted because pilot studies indicated that chironomids build sand casings within the first 30 min of being introduced to the aquaria. This behavior was thus hypothesized to affect the foraging efficiency of Pallid Sturgeon. Fine silica sand (Granusil Silica) was used as a substrate to facilitate the burrowing behavior of chironomid larvae and was placed to cover a depth of ~1 cm off the bottom of the containers. Trials using small, medium or large size classes of Chironomidae were performed in aquaria without sand substrate. Prey were released into the aquaria to allow them to bury if sand was present. Then, the sturgeon were placed on a fine meshed screen that was installed midway through the water column of the aquaria. This allowed the sturgeon to acclimate to the aquaria without having access to the prey. After a 30-min period had elapsed, the screen was removed and the fish could begin foraging on the prey. I collected mayfly naiads (Baetidae, Ephemeridae, and Heptageniidae) in a local stream using a kick net. In the laboratory, mayfly naiads were carefully removed from the samples but were not sorted since the range of sizes was small, as opposed to

27 Chironomidae larvae. Methods for mayfly feeding trials were similar to those for chironomids; the only difference being that sand substrate was not used because pilot studies showed that mayflies did not display a burrowing behavior. Mayfly larvae averaged 3.83 mm ± 1.55 S.D. in length and 0.006 g ± 0.010 S.D. in weight. Daphnia spp. (1.90 mm ± 0.58 S.D.; 0.125 mg ± 0.100 S.D.) were collected in a local pond and processed through a 2 mm sieve to remove large individuals (>2 mm) that exceeded the gape limitation of the first-feeding sturgeon size-class (Snyder 2002). Daphnia spp. were introduced after the sturgeon had acclimated to the container. Feeding trials were replicated five times for each combination of fish size, water temperature, prey density, and(or) prey size (i.e., Chironomidae). Thus, for 20 mm Pallid Sturgeon maintained at 14 °C, a total of 30 fish were used to evaluate predation rates on Daphnia at densities of 15 to 90/L (i.e., five fish per density; Table 1). Similarly, for 50 mm Pallid Sturgeon feeding at 24 °C on small Chironomidae (180 to 900 individuals/m2), a total of 25 fish were used (Table 1). After being transferred to aquaria, fish (1 per aquarium) were acclimated for 30 min before allowed to feed for 15 min. At the end of each trial, I removed fish from the aquaria and remaining prey items were counted. Consumption rates (number of prey eaten/15 min) were used to generate parameter estimates for equation 1 for each feeding trial. Parameters for Th and a were estimated by the nlsLM function in R that uses the Levenberg-Marquardt nonlinear least-squares algorithm (Elzhov et al. 2013). Prey depletion was taken into account using the Lambert W function from the emdbook package (Bolker 2013). In some cases, small Pallid Sturgeon (≤ 30 mm) had difficulty capturing prey items resulting in the absence of a significant effect of prey density on the

28 number of prey consumed. In these cases, the mean number of prey eaten, Nm, was used instead of N. Using estimates of N or Nm, I developed a multiple regression model for predicting prey consumption N’ as a function of Pallid Sturgeon size (L), prey type (Prey), water temperature (Temp), and prey density (Prp) (see equation 2). Prey types (Prey) were analyzed as a categorical variable and included small, medium, mixed or large chironomids on bare substrate, mixed chironomids on a sandy substrate, mayfly, or zooplankton treatments (total of 7 prey treatments). Estimates of N’ for each prey types were calculated by multiplying 1 to the regression coefficient associated with the prey type of interest, and multiplying all other prey type coefficients by 0. Because zooplankton and benthic invertebrate densities are presented in different units (individuals per L or per m2), prey density was expressed as a proportion (Prp) of maximum prey density to explain the variability associated with prey abundance. For example, a Prp value of 0.5 is equivalent to 45 Daphnia/L or 450 chironomids/m2. 2. Satiation Satiation was calculated using short term (90-180 minute) feeding trials that quantified the maximum amount of food a fish could eat when offered an ad-libitum ration. Trials were performed using four size groups of age-0 Pallid Sturgeon that were acclimated to 24°C; mean length of each size group was 19 (± 0.09 S.E.), 25 (± 1.30 S.E.), 68 (± 1.30 S.E.), or 122 (± 2.31 S.E.) mm. Individual fish were placed in 900 mL aquaria and allowed to acclimate for 24 h without being fed. Following the acclimation period, smaller Pallid Sturgeon (19 and 25 mm) were fed 10 live Chironomidae larvae (0.001 and 0.005 g wet weight/chironomid) whereas larger sturgeon (67.5 and 122.2 mm)

29 were fed thawed Chironomidae larvae (Hikari Bio-Pure) representing ~5 % of their body weight. The smaller groups of fish were allowed to feed for 30, 60, 90, 120, 150, or 180 min while the larger group of fish were allowed to feed for 15, 30, 45, 60, 75, or 90 min. A total of 5 replicates per foraging time were used for each size class of fish. After each feeding trial had ended, the remaining chironomids were quantified and converted to biomass. To account for the change in thawed chironomid weight that might occur over time, control trials without fish were performed and prey weight loss was added to the weight of the recovered food. At the end of the trial, the fish were weighed wet (ingested food weight was subtracted), and measured for total length. For each Pallid Sturgeon size group, a one-way ANOVA was performed with foraging time as the independent factor and food consumed (in g) as the dependent variable. The mean consumption value that corresponded to satiation (i.e., when the fish could no longer ingest additional prey; Sat) was identified as a result of the ANOVA test for each size group and was expressed according to the following model Sat = S0 er∙L

(6)

where Sat is the maximum amount of food a fish can eat (in g), S0 and r are intercept and slope coefficients and L is fish length in mm. The satiation index, (S), indicates the relative amount of a given prey that can be stored in the gut and was calculated as S = 1/Sat/preyi

(7)

where preyi is the weight (g wet weight) associated with an average prey item (Daphnia, mayfly or chironomid). Values for S vary positively with mean size of individual prey; small prey have lower S values whereas larger prey have greater S values. It is assumed

30 that all prey items have a similar specific gravity and thus a similar volume (Spaargaren 1979), implying that a fish of a given size can fit the same amount of weight in its gut regardless of the prey taxon. 3. Gut evacuation Because stomach fullness in fishes can affect feeding rate, I quantified gut evacuation rate in Pallid Sturgeon as a function of body size and water temperature (14, 18, and 24°C). For each temperature treatment, fish were divided into groups of 5 for each 4-hour interval (0, 4, 8, 12, 16, 20 and 24 h) and placed individually in 900 mL aquaria. Fish (40-110 mm) were fed a known amount of thawed chironomids (~ 5% Body Weight) for 30 min and the amount of food consumed was calculated after correcting for uneaten chironomids. At the end of the 4-hour time intervals, fish were removed from the aquaria and euthanized using Tricaine-S (Western Chemical inc.; [200 mg/L]) and dissected immediately. The foregut was cut open and food items were removed with forceps, blotted dry to remove excess water, and weighed to the nearest mg. Individual fish were also weighed and measured before the gut was removed. Gut evacuation data followed an exponential decline over time (Bochdansky & Deibel, 2001) that could be described as Vt = V0 e−rt

(8)

where Vt is the proportion of food left in the gut based on the amount of food ingested, V0 is the intercept coefficient, r is the slope coefficient and t is the time interval. A multiple regression model was constructed using the slopes (r; dependent variable) generated from the different fish size (L) and temperature (Temp) combinations (N=9) as

31 r = a0 + a1 L + a2 Temp

(9)

where a0, a1 and a2 are the intercept and respective slope coefficients. The model was then used to estimate tg, or the time to it takes to empty the gut as tg =

log(0.01) −r

(10)

Model evaluation To evaluate the performance of the model, I conducted a series of 24 h feeding trials using a range of fish sizes (19-130 mm), prey densities and water temperatures (14, 18 and 24°C; Table 3). Each treatment was replicated 5 times. Fish were allowed to acclimate to their aquaria for 24h where food was not provided. Prey items were introduced following the acclimation period, and fish were given 24 h to forage. Each aquarium contained a sand substrate to allow for the chironomids to burrow. After the 24 h period, the fish were removed and measured (total length in mm) and any prey not consumed were quantified. Observed consumption values were compared to those predicted by the foraging model using linear regression analysis. To generate consumption estimates, integration of equations 3, 4, and 5 was performed over 24 hours (i.e., 24 iterations). The hunger level was set to 1 at the beginning of the model run to indicate that fish started with an empty gut. From the regression model, 97.5% joint confidence intervals for the intercept and slope coefficients were used to test the null hypothesis that the intercept and slope coefficients were equal to 0 and 1, respectively. Additionally, the decomposition of mean square error (MSE) was used to partition the variance into error associated with

32 differences in the means (observed and predicted), error associated with the slope differing from 1, and error linked to residual variation. Daily energy return Daily maximum energy return (Emax) for each Pallid Sturgeon size group (up to 50 mm) was calculated as Emax = y24 ∙ wi ∙ EDi

(11)

where y24 is the number of prey items consumed over a period of 24 h (see equations 3, 4 and 5), while wi and EDi represent average weight (in g) or energy density (in J/g) associated with prey i. Prey energy densities used were 2310, 2922 or 3368 J/g for zooplankton, Chironomidae and Ephemeroptera larvae, respectively (James et al. 2012). For each prey taxon, Emax was calculated for all prey density (pct from 0 to 1; prey depletion was not allowed) and temperature combinations (14, 18 and 24°C). Emax outputs were compared to the minimal amount of energy required for a fish of a given size to maintain its weight over the course of a day. This maintenance ration provides sufficient energy for metabolic and waste processes, but does not allow for growth to occur and does not account for energy that might be required for movement. To do so, the bioenergetics model developed by Heironimus (2015) was used. Fish of a given size class (19-50 mm) were converted to weight using the following length-weight regression (Heironimus 2015) log10 W =

(log10 L−1.865) 0.367

(12)

where W is the weight of the fish (g) and L is the total length (mm). The initial weight calculated for each size class was also used as the final weight value. Model simulations

33 lasted 1 d and a value of 2736 J/g was used for the predator energy density (Heironimus 2015). The output used to generate maintenance ration value corresponded to the total amount of ingested prey converted to energy (J).

RESULTS Functional feeding response Age-0 Pallid Sturgeon displayed a type II functional response once they had reached a size of 40 mm, regardless of temperature, prey type, prey size, and substrate treatment. Prior to reaching that size, prey density did not influence capture rates during most trials, and thus, no functional feeding coefficients were generated. As fish grew in size, capture rates for all three prey (zooplankton, Chironomidae and Ephemeroptera larvae) increased (Figure 2; Table 4). On average, fish were able to capture more Ephemeroptera larvae per unit of time, with 14% and 19% less zooplankton and Chironomidae larvae being consumed, respectively. The presence of a sandy substrate decreased foraging efficiency on chironomids by 86% compared to feeding off a bare substrate (Figure 2; Table 4). Prey size also influenced capture rates, with large (avg. 11 mm) and medium (avg. 9 mm) sized chironomids being captured 58% and 18% less often than small chironomids (Figure 3; Table 5). As a result, the maximum amount that could be ingested over a period of 15 min (N’) was calculated for the different prey densities and a multiple regression was generated. Both N’ and fish length (L) were transformed using a natural logarithmic transformation in order to respect assumptions of normality and homogeneity of variance. The model (F9,1160 = 425.1; R2=0.77; P