University of Nevada, Reno

The Dynamics of Mysis diluviana and Other Zooplankton in Three Oligotrophic Lakes

A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Biology

by

Zachary Bess

Dr. Sudeep Chandra/Thesis Advisor

August 2020

Copyright by Zachary A. Bess 2020

All Rights Reserved

THE GRADUATE SCHOOL

We recommend that the thesis prepared under our supervision by

entitled

be accepted in partial fulfillment of the requirements for the degree of

Advisor

Committee Member

Committee Member

Graduate School Representative

David W. Zeh, Ph.D., Dean Graduate School i

Abstract

Mysids (Mysis diluviana) have been introduced to a number of temperate lakes to provide food to salmonids for recreational fishing. In many of these lakes, these mysids have changed the native zooplankton communities through predation. Mysids were introduced to Donner Lake, Fallen Leaf Lake, and Lake Tahoe in the mid-1960s and have changed the native zooplankton community of Lake Tahoe profoundly. We conducted mesocosm experiments to evaluate the effects of two native zooplankton taxa (Daphnia spp. and Epischura nevadensis) and juvenile and adult mysids on ecosystem function in

Lake Tahoe and its more productive embayment, Emerald Bay. The results of these experiments indicate that these zooplankton play significantly different roles in the

Emerald Bay ecosystem, but not in Lake Tahoe proper. This suggests that these zooplankton may play a larger role in shaping the ecosystem characteristics of the water column in Lake Tahoe if cultural eutrophication should eventually elevate Lake Tahoe’s trophic state to that of Emerald Bay’s.

Additionally, we measured the environmental factors that influence mysid growth rates in Lake Tahoe. We found that adult growth rates significantly correlate with the depth of winter mixing, but juvenile growth rates significantly correlate with the mean

summer. We also measured the pelagic reliance, trophic position, and carbon sources of mysids in Donner Lake, Fallen Leaf Lake, and Lake Tahoe and evaluated the role of wind-dispersed pollen in supporting mysid energetics. These analyses indicate that a variety of factors influence mysid production in these lakes, and the importance of the factors differs between the lakes.

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Acknowledgements

I would like to thank my graduate advisor, Dr. Sudeep Chandra, for providing

guidance, inspiration, funding, assurance, and a lab to work in. His tremendously broad

knowledge of and passion for aquatic ecology have been evident and invaluable. He

fostered an environment in which I was able to learn about many aspects of aquatic and

conservation ecology beyond just what was relevant for this thesis. Additionally, the get-

togethers at his home (complete with tandoori chicken and musical instruments) were a

great way to take a break from the work of this thesis. The other members of my

committee (Dr. Alan Heyvaert, Dr. Steve Sadro, and Dr. Zeb Hogan) honed the design of

the experiments and provided edits to this thesis, and I am thankful for their guidance as

well.

Two of Dr. Chandra’s former students significantly helped to smooth my path.

Karly Feher was an excellent mentor, especially in the early stages of working in Dr.

Chandra’s lab. By assisting her at Castle Lake, I learned many of the methods that I have

used in this thesis. She was also eager to offer her help when I needed it. Dr. Tim

Caldwell helped to brainstorm ideas with me that made their way into both chapters of

this thesis. He also offered his expertise in all things related to mysids.

The other members of Dr. Chandra’s lab also made for spectacular collaborators.

They include Erin Suenaga, Dr. Suzanne Kelson, Emily Carlson, Emily Carlson, Dr. Ed

Krynak, Dr. Flavia Tromboni, Dr. Facundo Scordo, Dr. Emanuele Ziaco, James

Simmons, Josh Culpepper, Teresa Campbell, Elizabeth Everest, and Loren Secor. Bonnie

Teglas patiently and persistently managed the funds and expenses that supported this work. iii

Several others were instrumental in helping me, often in ways that I did not initially realize and fully appreciate. In her graduate course at UNR, Dr. Mae Gustin provided me with advice when developing the project and helped me to develop a critical eye when reviewing others’ works. Likewise, another UNR professor, Dr. Kevin

Shoemaker, helped me with improving my understanding of computer coding and statistics and even made recommendations for the tests employed in this thesis. Dr. Jim

Hobbs of CA Department of Fish & Wildlife and Dr. Malte Willmes of UC Davis gave me my first exposure to the utility of stable isotope ecology. Dr. Peter Moyle of UC

Davis inspired me through his applications of aquatic biology to conservation ethics.

Brant Allen, Katie Senft, and Brandon Berry of the UC Davis Tahoe Environmental

Research Center offered training and advice in working at Lake Tahoe and provided samples that were analyzed in Chapter 2.

I thank my family for providing support while completing this endeavor.

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Table of Contents

General Introduction………………………………………………………………………1 General Introduction References………………………………………………….4

Chapter 1. Zooplankton influences on phytoplankton, water clarity, and nutrients in Lake Tahoe………………………………………………………………………………………6 Abstract……………………………………………………………………………7 Introduction………………………………………………………………………..8 Materials & Methods…………………………………………………………….11 Results……………………………………………………………………………17 Discussion………………………………………………………………………..19 References………….…...………………………………………………………..25 Tables…………………………………………………………………………….32 Figures……………………………………………………………………………36 Supplemental Table……………………………………………………………...43

Chapter 2. Factors Influencing the Production of Mysis diluviana in Three Oligotrophic Lakes……………………………………………………………………………………..44 Abstract…………………………………………………………………………..45 Introduction………………………………………………………………………46 Methods…………………………………………………………………………..48 Results……………………………………………………………………………55 Discussion………………………………………………………………………..57 References………………………………………………………………………..64 Table……………………………………………………………………………..72 Figures……………………………………………………………………………73 Supplemental Tables……………………………………………………………..80

General Summary of Findings…….……………………………………………………..93 General Summary References……………………………………………………95

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List of Tables

Chapter 1

1. Secchi depth, chlorophyll a concentrations, and SRP concentrations for Lake Tahoe and Emerald Bay. Lake Tahoe chlorophyll a and SRP concentrations were determined from an 18- meter depth; Emerald Bay chlorophyll a and SRP concentrations were determined from an 11- meter depth. Lake Tahoe chlorophyll a and Emerald Bay secchi measurements were measured in October 2019; all other measurements were performed in July 2019. 1) Schladow 2019………………………………………………………………………………………………..32

2. Description of the 5 treatments in each experiment. Each treatment consisted of 5 replicates. Each mesocosm contained approximately 27 mg dry weight of the study organism…………………………………………………………………………………………...33

3. Results for the Lake Tahoe experiment. The values outside of the parentheses are the percent increase (positive value) or decrease (negative value) in the parameter relative to the Control of the experiment. The values in parentheses are the p-values of the statistical tests. Values marked with a P indicate that a permutation test was used, all other values were determined with a Dunnett’s test. Values that are statistically significant (p < 0.05) are bolded...... 34

4. Results for Emerald Bay experiment. The values outside of the parentheses are the percent increase (positive value) or decrease (negative value) in the parameter relative to the Control of the experiment. The values in parentheses are the p-values of the statistical tests. Values marked with a P indicate that a permutation test was used, all other values were determined with a Dunnett’s test. Values that are statistically significant (p < 0.05) are bolded...... 35

Supplemental Table 1. Relative % error in cumulative particle (diameters ≥ 0.5 µm) concentrations for samples measured in duplicate………………………………………………...43

Chapter 2

1. Limnological variables of the study ecosystems. 1) Dong 1975; 2) Hanes 1981; 3) Morgan 1981...... 72

Supplemental Table 1. Bulk tissue δ13C and δ15N of mysids……………………………………...80

Supplemental Table 2. Bulk tissue δ15N of herbivorous zooplankton………………………….....84

Supplemental Table 3. Percentages of dietary items in mysid foregut analyses incorporated into the bioenergetics model. Matter classified in the “Other” category consists of unidentifiable matter that was not incorporated into the models…………………………………………………………86

Supplemental Table 4. Amino acid δ15N values of mysids and the calculated trophic positions…89

Supplemental Table 5. Energy density for prey items used in the bioenergetics models…………90

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List of Figures

Chapter 1

1. Chlorophyll a concentrations, pheophytin / chlorophyll a ratios, and biomass-specific PPR. The Lake Tahoe experiment values are shown in the graphs in the left-hand column, and the Emerald Bay experiment values are shown in the graphs in the right-hand column. Treatments that are significantly different (p < 0.05) from the Removal are marked with ** below the x-axis label; treatments that are marginally different (p < 0.1) are marked with *. The mean value of the Control is marked with a dashed line. For each boxplot, the solid horizontal line in the box signifies the median value for that treatment, while the edges of the box signify the first and third quartiles. Note that the y-axis scales are dissimilar……………………………………………….36

2. Concentrations of small (≥ 0.5 µm & < 5 µm), large (≥ 5 µm), and cumulative (≥ 0.5 µm) particles in the Lake Tahoe and Emerald Bay experiments. The Lake Tahoe experiment values are shown in the graphs in the left-hand column, and the Emerald Bay experiment values are shown in the graphs in the right-hand column. Treatments that are significantly different (p < 0.05) from the Removal are marked with ** below the x-axis label; treatments that are marginally different (p < 0.1) are marked with *. The mean value of the Control is marked with a dashed line. For each boxplot, the solid horizontal line in the box signifies the median value for that treatment, while the edges of the box signify the first and third quartiles. Note that the y-axis scales differ between subplots…………………………………………………………………………………………….37

3. Concentrations of TDC and DOC in the Lake Tahoe and Emerald Bay experiments. The Lake Tahoe experiment values are shown in the graphs in the left-hand column, and the Emerald Bay experiment values are shown in the graphs in the right-hand column. Treatments that are significantly different (p < 0.05) from the Removal are marked with ** below the x-axis label; treatments that are marginally different (p < 0.1) are marked with *. The mean value of the Control is marked with a dashed line. For each boxplot, the solid horizontal line in the box signifies the median value for that treatment, while the edges of the box signify the first and third quartiles. Note that the y-axis scales are dissimilar……………………………………………….38

4. Concentrations of nitrate, ammonium, and SRP, and the DIN/SRP ratios in the Lake Tahoe and Emerald Bay experiments. Details are the same as for Fig 1. Note that the y-axis scales are dissimilar…………………………………………………………………………………………..39

5. Non-metric multidimensional scaling (NMDS) analysis of the Lake Tahoe and Emerald Bay experiments. Dissimilarities were measured with Euclidean distances...... 40

6. Conceptual model showing the relationships among macrozooplankton and pelagic processes as demonstrated in the Lake Tahoe (oligotrophic) experiment. 1) Rybock 1978; 2) Sawyer 1985….41

7. Conceptual model showing the relationships among macrozooplankton and pelagic processes as demonstrated in the Emerald Bay (meso-oligtophic) experiment. Sources are the same as for Fig 6……………………………………………………………………………………………………42

Chapter 2

1. Map of study ecosystems created using QGIS Version 3.14. Shapefiles of the lakes and streams were accessed from the California Department of Fish & Wildlife GIS Clearinghouse (https://wildlife.ca.gov/Data/GIS/Clearinghouse). Shapefile of North America accessed from ESRI (https://www.arcgis.com/home/item.html?id=5cf4f223c4a642eb9aa7ae1216a04372)...... 73 vii

2. Growth rates of juvenile (A-G) and adult (H-N) mysids regressed with environmental variables in Lake Tahoe. Correlation coefficients of Pearson’s correlation analyses are outside the parentheses, and p-values are within the parentheses. Statistically significant p-values (p < 0.05) are marked with **, while marginally significant p-values (p < 0.1) are marked with *…………74

3. The reliance of mysids on pelagic carbon sources (%) in a) Donner Lake, b) Fallen Leaf Lake, and c) Lake Tahoe determined from bulk tissue analysis of δ13C. The box plots show the median values (horizontal line inside box), 1st and 3rd quartiles (box perimeter), and outlier values……..75

4. Trophic positions of mysids in a) Donner Lake, b) Fallen Leaf Lake, c) Emerald Bay, and d) Lake Tahoe. The trophic positions of Emerald Bay mysids and the 2018 (May, August) and 2019 (May) Lake Tahoe mysids were determined with amino acid δ15N analysis. All other trophic positions were determined with bulk tissue δ15N analysis. The box plots show the median values (horizontal line inside box), 1st and 3rd quartiles (box perimeter), and outlier values……………..76

5. Contributions (%) of primary carbon sources to mysids in Lake Tahoe from 5 sources of energy (cyanobacteria, chlorophytes, and C3 (including aquatic plants) and C4 terrestrial plants, and fungi. Contributions were determined with amino acid δ13C analyses……………………………77

6. Bioenergetics models representing the growth of mysids in a) Donner Lake, b) Fallen Leaf Lake, and c) Lake Tahoe. Solid lines represent observed growth of mysids, while dashed lines represent modeled growth with pollen providing no energetic contribution to mysids…………...78

7. Conceptual model of the factors that support Mysis diluviana based upon the general findings of this study…………………………………………………………………………………………..79

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General Introduction

Since regular limnological measurements began at Lake Tahoe, the lake has

undergone numerous changes due to anthropogenic influence. For instance, the Secchi

depth (a measurement of water clarity) has declined substantially from an annual mean

depth of 31.2 meters in 1968 to an annual mean of 21.6 meters in 2018 (Schladow 2019).

Similarly, the primary productivity of the pelagic zone has more than quadrupled due to

cultural eutrophication since the 1960s (Goldman 2000), and this increase has caused

changes to the benthic zone through “shading” of benthic primary producers and

increased sedimentation of pelagic carbon. Consequently, the reliance of zoobenthic

organisms upon pelagic carbon increased from 27% in 1963 to 62% in 2001 (Chandra et

al. 2005), and lake-wide densities of endemic benthic invertebrates have declined by 80–

100% since the 1960s (Caires et al. 2013). Nutrient dynamics of the lake have also

changed. For instance, the phytoplankton community has switched from nitrogen

limitation to colimitation with phosphorus, likely due to long-term atmospheric

deposition of anthropogenic nitrogen (Goldman et al. 1993).

Additionally, non-native species have been introduced to the lake, and these

introductions have resulted in profound ecological changes. For instance, lake trout

(Salvelinus namaycush), introduced in 1889, have replaced native Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) as the apex predator (Chandra 2003). High crayfish (Pacifastacus leniusculus) densities can reduce primary productivity of littoral periphyton and densities of Myriophyllum in the lake (Flint & Goldman 1975).

Warmwater invasive fishes, such as largemouth bass (Micropterus salmoides) and 2

bluegill (Lepomis macrochirus), are likely competing with and preying on native fishes

(Kamerath et al. 2008).

Mysids (Mysis diluviana) are yet another species introduced to the lake with detrimental effects. This species was introduced to Donner Lake, Fallen Leaf Lake, and

Lake Tahoe in the mid-1960s to supplement the diets of Kokanee salmon (Oncorhynchus nerka) and lake trout (Linn & Frantz 1965) following observed success with introductions to Kootenay Lake (Northcote 1991). However, because of Lake Tahoe’s depth and low productivity, mysid shrimp did not serve as a major food item for these salmonids. Instead, mysids caused the extirpation of native cladocerans (Daphnia pulicaria, Daphnia rosea, Bosmina longirostris) through predation (Goldman et al.

1979). Concomitantly, mysids caused a decrease in the size of kokanee salmon through competition for cladoceran prey (Morgan et al. 1978). Today, the macrozooplankton community in Lake Tahoe now consists of mysids and the calanoid copepods Epischura nevadensis and Diaptomus tyrelli. The dynamics of the mysids in Donner Lake, Fallen

Leaf Lake and Emerald Bay, all systems with higher productivity than the main body of

Lake Tahoe (Morgan 1981), have been less studied than the population in hyperoligotrophic Lake Tahoe.

The results of the mysid introduction in Lake Tahoe exemplify the unintended changes to ecosystems through species introductions. This thesis examines the dynamics of mysids and zooplankton in the ecosystems of Donner Lake, Fallen Leaf Lake, Lake

Tahoe, and Emerald Bay. Chapter 1 examines the effects of Daphnia, Epischura, and mysids on the phytoplankton, water clarity, and nutrient concentrations of Lake Tahoe and Emerald Bay. Chapter 2 examines the environmental factors that influence mysid 3 growth in Lake Tahoe as well as the percent pelagic reliance, trophic positions, and primary carbon sources of mysids in Lake Tahoe, Emerald Bay, Donner Lake, and Fallen

Leaf Lake. I use bioenergetics models to investigate the importance of pollen for mysid growth in the three lakes.

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General Introduction References

Caires, A. M., S. Chandra, B.L. Hayford, and M. Wittman. 2013. Four decades of change: dramatic loss of zoobenthos in an oligotrophic lake exhibiting gradual eutrophication. Freshw. Sci. 32: 692-705. doi:10.1899/12-064.1.

Chandra, S. 2003. The Impact of Nonnative Species and Cultural Eutrophication on the Lake Tahoe Food Web Over Time. Ph.D. Dissertation. Univ. of Calif. - Davis.

Chandra, S., M.J. Vander Zanden, A.C. Heyvaert, R.C. Richards, B.C. Allen, and C.R. Goldman. 2005. The Effects of Cultural Eutrophication on the Coupling between Pelagic Primary Producers and Benthic Consumers. Limnol. Oceanogr. 50: 1368- 1376. doi:10.4319/lo.2005.50.5.1368.

Flint, R.W., and C.R. Goldman. 1975. The effects of a benthic grazer on the primary of the littoral zone of Lake Tahoe. Limnol. Oceanogr. 20: 935-944. doi:10.4319/lo.1975.20.6.0935.

Goldman, C.R. 2000. Four decades of change in two subalpine lakes. Verh. Internat. Verein. Theor. Angew. Limnol. 27: 7-26. doi:10.1080/03680770.1998.11901200

Goldman, C.R., M.D. Morgan, S.T. Threlkeld, and N. Angeli. 1979. A population dynamics analysis of the cladoceran disappearance from Lake Tahoe, California‐ Nevada. Limnol. Oceanogr. 24: 289-297. doi:10.4319/lo.1979.24.2.0289

Kamerath, M., S. Chandra, and B. Allen. 2008. Distribution and impacts of warm water invasive fish in Lake Tahoe, CA, USA. Aquat. Invasions 3: 35-41. doi:10.3391/ai.2008.1.1.7.

LeConte, J. 1883. Physical Studies of Lake Tahoe. Overland Monthly and Out West Magazine, 2: 506-517. Available from https://tahoe.ucdavis.edu/sites/g/files/dgvnsk4286/files/inline- files/LeConte_PhysicalStudiesOfLakeTahoe_I_1883.pdf [Accessed 14 July 2020]

Linn, J.D., and T.C. Frantz. 1965. Introduction of the Opossum Shrimp (Mysis relicta Loven) into California and Nevada. Calif. Fish & Game 51: 48-51. Available from http://www.nativefishlab.net/library/textpdf/20345.pdf [Accessed 13 July 2020]

Morgan, M.D., S.T. Threlkeld, and C.R. Goldman. 1979. Impact of the Introduction of Kokanee (Oncorhynchus nerka) and Opossum Shrimp (Mysis relicta) on a Subalpine Lake. J. Fish. Res. Board Can. 35: 1572-1579. doi:10.1139/f78-247.

Northcote, T.G. 1991. Success, Problems, and Control of Introduced Mysid Populations 5

in Lakes and Reservoirs, p. 5-16. In T.P. Nesler & E.P. Bergerson [eds.], Mysids in Fisheries: Hard Lessons from Headlong Introductions. American Fisheries Society.

Schladow, S.G. 2019. Tahoe: State of the Lake Report 2019. UC Davis Tahoe Environmental Research Center. Available from https://tahoe.ucdavis.edu/sites/g/files/dgvnsk4286/files/inline- files/SOTL2019_reduced.pdf [Accessed 13 July 2020]

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A version of this paper has been submitted to Aquatic Sciences.

Zooplankton influences on phytoplankton, water clarity, and nutrients in Lake Tahoe

Zachary Bess1, Sudeep Chandra1,2, Alan Heyvaert3, Erin Suenaga1, & Suzanne Kelson1,2

1Department of Biology, University of Nevada—Reno, 1664 N Virginia St, Reno, NV, 89557, USA 2Global Water Center, University of Nevada—Reno, 1664 N Virginia St, Reno, NV, 89557, USA 3Desert Research Institute, 2215 Raggio Pkwy, Reno, NV, 89512, USA

Corresponding Author Contact: [email protected]

Acknowledgements Drs. Steve Sadro (UC Davis), Alan Heyvaert (Desert Research Institute), and Michael Brett (University of Washington) provided feedback in the design of the experiments. Dr. Kevin Shoemaker (University of Nevada, Reno) provided recommendations for the statistical analyses. Dan Shaw and Nita Suparek coordinated access and field collections from Emerald Bay. Cam McKay from the Glenbrook Water Facility assisted in water collections for the Lake Tahoe experiment. The following people assisted in the two semi-natural experiments: Dr. Tim Caldwell, Karly Feher, Emily Carlson, Dr. Emmanuele Ziaco, Elizabeth Everest, Dr. Facundo Scordo, Dr. Ed Krynak, James Simmons, Josh Culpepper, Loren Secor, Anna Cole, Shaye McMillen, and Logan Gregory.

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Abstract

The effects of zooplankton grazing, excretion, and nutrient recycling depend on the taxonomic makeup of the zooplankton community as well as the trophic state of the water body. We conducted mesocosm experiments to evaluate the effects of Daphnia spp., Epischura nevadensis, and juvenile and adult Mysis diluviana on ecosystem function in oligotrophic Lake Tahoe and its more productive embayment, Emerald Bay.

Chlorophyll a concentrations, grazing indices (pheophytin/chlorophyll a), primary productivity, particle concentrations (an indicator of water clarity), and dissolved nutrient concentrations from each of the species treatments were compared to a control treatment that contained no macrozooplankton. In the Lake Tahoe experiment, Daphnia and the

Adult Mysid treatments had lower dissolved organic carbon concentrations, and the

Epischura treatment had lower soluble reactive phosphorus concentrations when compared to the Control treatment. In the Emerald Bay experiment, the Daphnia treatment had lower chlorophyll a concentrations, the Daphnia and Juvenile Mysid treatments had lower small particle (diameter 0.5 – < 5 µm) concentrations, and each of the species treatments had higher ammonium concentrations and dissolved inorganic nitrogen/soluble reactive phosphorus ratios when compared to the Control. Analyses of similarities indicated that these taxa differed from one another in their overall effects on

Emerald Bay water, but not on less productive Lake Tahoe water. In light of the ongoing cultural eutrophication of Lake Tahoe, the Emerald Bay experiment suggests that these zooplankton may play a larger role in shaping the ecosystem characteristics of the water column in Lake Tahoe.

Keywords: oligotrophic lakes, mysids, grazing, mesocosms, water clarity 8

Introduction

Zooplankton grazing and excretion play important roles in structuring pelagic ecosystems. These organisms graze phytoplankton, bacterioplankton, detritus, and inorganic particles, and they prey upon rotifers and protists (Adrian & Schneider-Olt

1999; Burns & Schallenberg 2001; Kagami et al. 2002; Zollner et al. 2003). They contribute to particle concentrations through the release of fecal pellets and, in the case of some taxa, through the egestion of undigested food particles (“sloppy feeding”) (Turner

& Ferrante 1979; Mauchline 1998; Linden & Kuosa 2004). Zooplankton also supply dissolved nutrients that can stimulate bacterioplankton and phytoplankton productivity

(Lampert 1978; Madeira et al. 1982). These inputs and outputs from zooplankton are generally species-specific, and shifts in the taxonomic makeup of zooplankton communities can lead to significant ecosystem changes (Lampert et al. 1986; Elser et al.

1988). Because these zooplankton often occupy central positions in food webs (Richards et al. 1991; Ekvall et al. 2014), these organisms can mediate changes in the biomasses of lower trophic levels through top-down processes and upper trophic levels through bottom-up processes.

The abilities of these zooplankton to structure ecosystems can be limited by the trophic state of the water body. Specifically, the effects of zooplankton on algal concentrations are less pronounced in oligotrophic and eutrophic ecosystems than in mesotrophic ecosystems (Elser et al. 1990; Elser & Goldman 1991; Vrede et al. 1999). In eutrophic lakes, zooplankton grazing is less effective in reducing algal concentrations because of the abundance of inedible algae (Elser et al. 1990; Vrede et al. 1999). In low- nutrient and oligotrophic ecosystems, the effects of grazing are generally obscured by 9

zooplankton nutrient excretions that stimulate algal growth (Elser et al. 1990). These

contrast with mesotrophic lakes, where zooplankton grazing can have a measurable top-

down effect and can lead to a “clearwater” phase that follows the spring algal bloom

(Lampert et al. 1986; Elser et al. 1990; Elser & Goldman 1991). The fact that

zooplankton grazing effects are greater in mesotrophic lakes than in eutrophic and

oligotrophic lakes is referred to as the “Mesotrophic Maximum Hypothesis” by Benndorf

et al. 2002.

The role of zooplankton in lake ecosystems undergoing eutrophication is not well

understood. Cultural eutrophication is a leading stressor in lakes (U.S. Environmental

Protection Agency 1996; Smith 2003) and can lead to changes in zooplankton

communities (Straile & Geller 1998). Lake Tahoe has undergone progressive cultural

eutrophication due to atmospheric and watershed nutrient inputs, shifting from ultra-

oligotrophic to oligotrophic (Goldman et al. 1988; Goldman 2000; Schladow 2019), and

eutrophication has contributed to the precipitous decline in lake clarity (Schladow 2019).

Additionally, the planktonic community has been altered through the near-elimination of

cladocerans by non-native mysids (Mysis diluviana) (Richards et al. 1975; Threlkeld et

al. 1980; Byron et al. 1986; Richards et al. 1991). Yet, the role that each zooplankton taxa

plays in structuring factors such as algal biovolume, water clarity, and nutrient

concentrations is unknown.

To examine how zooplankton affect pelagic nutrient cycling and particle sizes in

this oligotrophic system, we conducted semi-natural mesocosm experiments with cladocerans (Daphnia spp.), calanoid copepods (Epischura nevadensis), and mysids using the oligotrophic waters of Lake Tahoe and its more productive embayment, 10

Emerald Bay. Previous studies have demonstrated differences in both feeding behaviors and diets between these taxa. Daphnia are filter-feeders preying on phytoplankton, bacterioplankton, and microzooplankton (Lampert 1987; Adrian & Schneider-Olt 1999).

Epischura in Lake Tahoe is omnivorous (Richards et al. 1991), and calanoid copepods generally use both filter-feeding as well as raptorial feeding (Mauchline 1998). Similarly, mysids are omnivorous and use filter-feeding and raptorial feeding (Rybock 1978;

Cooper & Goldman 1980; Grossnickle 1982; Ramcharan et al. 1985; Sawyer 1985;

Johannsson et al. 2001). To understand the effects of zooplankton on concentrations of algae, particles (an indicator of water clarity), and nutrients, we compared water incubated with each taxon to water that lacked macrozooplankton. Additionally, we compared the aggregated effects of these taxa in Lake Tahoe water to their effects in the more productive water of Emerald Bay.

We hypothesized that Daphnia would have the greatest effect on phytoplankton concentrations, algal productivity, and particle concentrations because of its indiscriminate grazing behavior, while copepods and mysids feed more selectively upon their prey items. We predicted that adult mysids should have the greatest effect on dissolved carbon because of the release of dissolved organic carbon through “sloppy feeding” (Sierszen & Brooks 1982). Finally, because of the stoichiometric differences between the excretions of these taxa, copepods and mysids should lead to lower nitrogen:phosphorus ratios (measured as dissolved inorganic nitrogen/soluble reactive phosphorus), while cladocerans should increase these ratios (Madeira et al. 1982;

Andersen & Hessen 1991; Brett et al. 1994; Walve & Larson 1999; McCarthy et al.

2005). Additionally, we predicted that the difference between the effects of the taxa 11

should be greater in Emerald Bay than in Lake Tahoe because of the bay’s greater

productivity.

Materials & Methods

Lake Tahoe is a subalpine oligotrophic lake (mean depth of 313 meters) that is

primarily limited by phosphorus and secondarily limited by nitrogen (Goldman et al.

1993; Goldman et al. 2000). Emerald Bay (maximum depth of 180 meters) is a semi-

isolated water body and separated from the main body of the lake by a sill that is 2-4 meters deep. It is more productive than the main body of Lake Tahoe (Morgan 1981;

Morgan et al. 1981). Table 1 compares the ambient concentrations of chlorophyll a and soluble reactive phosphorus and the Secchi depths of these two systems. Cladocerans were abundant in Lake Tahoe until the introduction of predatory mysids (Richerson 1969;

Richards et al. 1975; Goldman et al. 1979). Epischura nevadensis, Diaptomus tyrelli, and mysids now dominate the zooplankton community of the lake.

Experiment Design

We conducted two semi-natural, mesocosm experiments: an experiment using zooplankton and water collected from Lake Tahoe in October 2019 and an experiment using zooplankton and water collected from Emerald Bay in July 2019. We modeled our experiment design after that used in Brett et al. 1994. We collected the study organisms from each system using a 500-micron zooplankton net. Due to the low density of

Daphnia spp. in Lake Tahoe and Emerald Bay, we used Daphnia spp. from mesotrophic

Castle Lake, CA. Because individual size can influence the grazing rate and size selection of particles (Burns 1968), we compared the size of the Daphnia from Castle Lake to those from Emerald Bay. We randomly selected ten Daphnia from each system and 12

measured their lengths from the eye to the base of the tail spine. The mean lengths of

Castle Lake Daphnia were not significantly different from Emerald Bay Daphnia

(Student’s t-test p-value > 0.05; Castle Lake mean size: 1.2 ± SD 0.154 mm, Emerald

Bay mean size: 1.1 ± SD 0.161 mm).

We incubated the study organisms in 10-liter plastic containers filled with water

collected from Lake Tahoe and Emerald Bay. For the Lake Tahoe experiment, we used

water collected from the Glenbrook water pumping facility that retrieves water from 18

meters below the lake’s surface. For the Emerald Bay experiment, we used water

collected with a modified bilge pump from an 11-meter depth in the bay. We screened the

water through an 80-micron filter prior to remove zooplankton prior to adding it to the containers. We employed five treatments in each experiment: Control (no macrozooplankton added), Daphnia, Epischura, Juvenile Mysid (< 12 mm length), and

Adult Mysid (≥ 12 mm length). We included treatments for both adults and juvenile

mysids because the size of food items influences whether mysids ingest their prey

through suspension or raptorial feeding (Grossnickle 1982; Metillo 1995) and because

adult mysids rely more heavily than juveniles on zooplankton prey (Rybock 1978;

Lesutiene et al. 2007). Five replicates were used for each of these treatments in each

experiment.

We used the same dry-weight biomass for each of the zooplankton treatments in

our experiments (as in Cottingham et al. 1997). We used biomass equivalents, rather than

counts of each zooplankton, because a similar study (Brett et al. 1994) noted that their

species-dependent results were obscured by the use of treatments that contained unequal

biomasses. We measured the mean dry weight of each taxa and inoculated each 13 mesocosm (except the Control) with the number of individuals that is equivalent to the dry-weight biomass of 3 adult mysids (Table 2) using hand-pipettes. Therefore, the results of our experiments are all biomass-specific.

The experiments were maintained in a temperature-controlled chamber programmed with a mean temperature of 9.7 °C and a 16-hr fluorescent light: 8-hr dark diel cycle. We re-arranged the containers in the chamber daily to randomize the amount of light that each container received, and we gently rotated the containers to discourage settling of particulate matter. We incubated the Lake Tahoe experiment for 8 days and the

Emerald Bay experiment for 7 days.

Phytoplankton concentrations, grazing indices, and PPR

To determine chlorophyll a concentrations in each treatment, we filtered water from each container through a Whatman 1825-047 GF/F filter, and the filters were submerged in methanol in individual film canisters for 24 hours in a dark environment

(Arar & Collins 1997). We determined chlorophyll a concentrations in the methanol solution with a Turner 10-AU fluorometer, and pheophytin concentrations were determined from the same samples following acidification. Because pheophytin is a degradation product of chlorophyll a, the ratio of these compounds can be used as an indicator of grazing intensity (Carpenter & Bergquist 1984; Brett et al. 1994). In the Lake

Tahoe experiment, biomass-specific primary productivity (PPR) was determined for four of the five replicates from each treatment. PPR was determined with radioactive C14 using light and dark bottles incubated for 6 hours (Steeman-Nielsen 1951; Goldman

1960), and these values were divided by the chlorophyll a concentrations to calculate biomass-specific PPR. 14

The following formula was used to determine biomass-specific primary productivity (PPR):

14 3 14 Relative PPR = (( C AssimilatedLight Bottle – 14C AssimilatedDark Bottle) * 1.06 * DIC * (1000 liters/m ) * (VolumeBottle)) / (( C Added) *

6 2.22x10 * (Geiger Efficiency) * Time * VolumeFiltered * ChlA) where

Relative PPR = primary productivity relative to chlorophyll a concentration; units: mg carbon / mg chlorophyll a / hr

14 C AssimilatedLight Bottle= radioactivity of light bottle filter; units: counts per minute

(cpm)

14 C AssimilatedDark Bottle= radioactivity of dark bottle filter; units: counts per minute (cpm)

1.06 = isotopic discrimination factor of radioactively-labeled carbon

DIC = DIC concentration; units: mg carbon / liter

1000 liters/m3 = conversion factor to convert cubic meters to liters

VolumeBottle = volume of borosilicate glass bottles (145 ml)

14C Added = amount of 14C added to bottle (5 microcuries)

2.22 x 106 = conversion factor to convert microcuries into disintegrations per minute

(DPM)

Geiger Efficiency = efficiency of Planchet counter (0.33)

Time = length of incubation (6 hours)

VolumeFiltered = volume of water filtered (50 ml)

ChlA = concentration of chlorophyll a; units: mg chlorophyll a / m3

Particle concentrations 15

We measured the concentration and sizes of total organic and inorganic particles

from each container with a Liquilaz SLS-1040. The instrument measured concentrations

of all particles with diameters of 0.5 microns and larger (up to 20 µm). Each sample was

serially diluted with ultrapure deionized water to achieve a concentration less than 10,000

particles/milliliter so as to minimize interference in the analyzer (Heyvaert et al. 2011). A

magnetic stir bar was used to stir the sample and suspend particles during measurement.

Between sample measurements, we flushed the analyzer with ultrapure deionized water

until the readings fell below 20 particles/milliliter. We classified all particles with

diameters smaller than 5 microns as small particles and particles with diameters of 5

microns and greater as large particles. There is no distinction between organic and

inorganic particles with this laser backscattering method.

Nutrient concentrations

To analyze nutrient concentrations, we first filtered water from each container

through Whatman 1825-025 GF/F filters (pre-combusted at 450 °C for 4 hours). Total dissolved carbon (TDC) concentrations were measured with a Shimadzu TOC-V, and

dissolved organic carbon (DOC) concentrations were measured from the same samples

following acidification (Shimadzu 2003). Concentrations of ammonium, nitrate, and

soluble reactive phosphorus (SRP) were determined spectrophotometrically. We

measured nitrate following reduction with a hydrazine-copper solution (Lamphake et al.

1967). This method determines the combined concentration of nitrate and nitrite, and we hereafter refer to these measurements as nitrate concentrations. We measured ammonium concentrations following reaction with phenol, sodium hypochlorite, and potassium nitroferrocyanide (U.S. Environmental Protection Agency 1993). We measured soluble 16

reactive phosphorus (SRP) concentrations following acidification with ammonium

molybdate and reduction with ascorbic acid (Murphy & Riley 1962). The DIN/SRP ratio

was calculated by dividing the sum of the ammonium and nitrate concentrations by the

SRP concentrations.

Statistical Analyses

We used pairwise comparisons to compare each post-hoc measurement from each

of the zooplankton treatments to the Control. Prior to analyzing these comparisons, a

Shapiro-Wilk test (Shapiro & Wilk 1965) was used to determine if the residuals of each

response variable were normally distributed, and a Bartlett’s test (Snedecor & Cochran

1989) was used to test for homoscedasticity. The data were log-transformed if they did not initially pass these tests. If the data passed these tests, they were analyzed with a

Dunnett’s test to compare each of the response variables from each of the zooplankton treatments (Daphnia, Epischura, Juvenile Mysid, Adult Mysid) with those of the Control.

A Dunnett’s test is a multiple comparison test that compares the dependent values of any number of treatments with those of a control (Dunnett 1955). We used the DescTools package (Andri Signorell et al. 2019) in R version 3.6.3 for the Dunnett’s tests.

If the data did not pass either the Shapiro-Wilk and Bartlett’s tests following log transformation, we instead used two-sample permutation tests to test for differences in each response variable between each treatment and the Control. A two-sample permutation test is a non-parametric test that calculates a test statistic by re-assigning the observations of the dependent variable to the two sample groups N! times, in which N is the pooled number of observations of the dependent variable in both of the treatment 17

groups (Ross 2014). We used the coin package (Hothorn et al. 2006) in R version 3.6.3

for these two-sample permutation tests.

Analyses of similarities (ANOSIMs) were used to determine the differences

between the treatments. ANOSIM is a nonparametric test that calculates a test statistic

from within-group and among-group dissimilarities (Clarke 1993). We used separate tests

for the Lake Tahoe and Emerald Bay experiments to determine if among-species

dissimilarities differed between the two systems. The ANOSIMs considered the

concentrations of chlorophyll a, pheophytin, small and large particles, nitrate,

ammonium, and SRP, and we measured the dissimilarities with Euclidean distances. We

excluded measurements that were not independent. For example, the DIN/SRP ratios

were excluded from the analysis because the ammonium, nitrate, and SRP concentrations

were included instead. The vegan package (Oksanen et al. 2019) in R version 3.6.3 was

used for these ANOSIMs and for the non-metric multidimensional scaling (NMDS)

graphic presented in Fig 5.

Results

Lake Tahoe

None of the zooplankton taxa significantly affected phytoplankton biovolume,

phytoplankton productivity, or particle concentrations in the Lake Tahoe experiment.

Specifically, none of the zooplankton treatments yielded chlorophyll a concentrations,

pheophytin/chlorophyll a ratios, or biomass-specific PPRs that were significantly different from those of the Control (Fig 1a, c, e; Table 3). However, juvenile mysids did have a marginal effect on large particle concentration. The mean concentration of large 18

particles in the Juvenile Mysid treatment was 52% lower (p = 0.06) than that in the

Control (Fig 2c; Table 3).

Overall, the effects of these taxa on the nutrient concentrations in the Lake Tahoe

experiment were minimal. However, Daphnia and adult mysids significantly influenced

DOC concentrations. Specifically, relative to the control, DOC was 25% lower in the

Daphnia treatment and 26% lower in the Adult Mysid treatment (p = 0.04, p = 0.04, respectively). Additionally, DOC concentrations were marginally lower in the Juvenile

Mysid treatment compared to the Control (by 22%; p = 0.06) (Fig 3c; Table 3).

Additionally, Epischura significantly reduced SRP concentrations, which were 35% lower (p < 0.01) than in the Control (Fig 4e; Table 3).

Emerald Bay

In the Emerald Bay experiment, Daphnia significantly affected phytoplankton

biovolume and particle concentrations, and juvenile mysids also affected small particle

concentrations. The Daphnia treatment contained a mean chlorophyll a concentration that

was 64% lower than the Control (p < 0.01) (Fig 1b, Table 4). Additionally, the mean

pheophytin/chlorophyll a ratio, which is an indicator for grazing rates, for the Daphnia

treatment was marginally higher (by 33%) than the Control (p = 0.08). (Fig 1c, Table 4).

Mean small particle concentrations were 53% lower (p = 0.03) in the Daphnia treatment

and 23% lower (p = 0.02) in the Juvenile Mysid treatment relative to the Control (Fig 2a;

Table 4). Large particle concentrations in the Daphnia treatment were marginally

different (p = 0.05) from the Control and were 44% lower than the Control (Fig 2b; Table

4). 19

In the Emerald Bay experiment, ammonium was the only nutrient influenced by

the taxa. The mean ammonium concentration in each of the zooplankton treatments was

significantly higher than that of the Control (Fig 4d; Table 4). Ammonium concentrations

were 428% (p < 0.01), 216% (p < 0.01), 572% (p < 0.01), and 391% (p = 0.01) higher in

the Daphnia, Epischura, Juvenile Mysid, and Adult Mysid treatments, respectively,

relative to the Control. Consequently, the DIN/SRP ratio for each of the zooplankton

treatments were also significantly higher than those of the Control (Fig 4h; Table 4).

Mean DIN/SRP ratios were 222% (p < 0.01), 240% (p < 0.01), 230% (p < 0.01), and

174% (p < 0.01) higher in the Daphnia, Epischura, Juvenile Mysid, and Adult Mysid

treatments, respectively, relative to the Control.

Comparisons between Lake Tahoe and Emerald Bay

The treatments were significantly different from each other in the Emerald Bay

experiment, but not in the Lake Tahoe experiment. The ANOSIM results for the Lake

Tahoe experiment indicate that the differences between the treatments were statistically

indistinguishable from the differences between the replicates (R = 0.05, p-value = 0.19).

In contrast, the ANOSIM results for the Emerald Bay experiment indicate that these taxa

generated different pelagic ecosystem structures (R = 0.35, p-value < 0.01). Fig 5 illustrates with an NMDS that the treatments have a lesser degree of overlap in the

Emerald Bay experiment than the Lake Tahoe experiment.

Discussion

Because Daphnia significantly depleted phytoplankton biovolume in the Emerald

Bay experiment but not in the Lake Tahoe experiment, we suggest that Daphnia’s ability

to reduce algal biovolume depends on the trophic state of the water. This finding is 20 consistent with other studies showing that Daphnia is a less effective grazer in low- nutrient oligotrophic systems (DeMott 1982; DeMott & Kerfoot 1982; Cottingham et al.

1997; Cyr 1998; Cyr & Curtis 1999). DeMott 1982 found that Daphnia’s inability to specifically target suitable prey items while filtering made the taxa ill-adapted to systems with low concentrations of phytoplankton. For this reason, Daphnia has recolonized Lake

Tahoe only during times of relatively high algal primary productivity that supported

Daphnia’s filtering limitations. At these times of high primary productivity, birth rates of cladocerans were high enough to overcome predation due to mysids (Byron et al. 1986).

Given that the final chlorophyll a concentrations in the Lake Tahoe and Emerald Bay

Daphnia treatments were similar (Lake Tahoe Daphnia mean: 0.58 ± 0.37 µg chlorophyll a / milliliter; Emerald Bay Daphnia mean: 0.44 ± 0.11 µg chlorophyll a / milliliter),

Daphnia may not have been able to graze phytoplankton to a lower concentration than was present in the ambient Lake Tahoe water.

Our results contrast with those of Elser et al. 1990, which found that algal biomass in Lake Tahoe decreased with increasing Daphnia densities. Because the

Daphnia densities in our experiments were higher than those used in the experiments of

Elser et al. 1990, it is possible that nutrient recycling by Daphnia may have stimulated algal growth in the Lake Tahoe experiment enough to obscure any grazing effects. Other prey items besides phytoplankton likely existed in the mesocosms, such as bacterioplankton and microzooplankton (rotifers and protozoa). Because the phytoplankton concentrations and grazing indices in the other zooplankton treatments

(Epischura, Juvenile Mysid, Adult Mysid) were not significantly different from the 21

Controls, this suggests that these organisms likely relied upon these other prey items

(bacterioplankton and/or microzooplankton) to a greater extent than Daphnia did.

Through grazing, Daphnia concomitantly increased water clarity in the Emerald

Bay experiment by removing small particles (diameter < 5 microns). Previous research has indicated that small particles (diameter < 5 microns) account for 75% of light scattering in Lake Tahoe (Swift et al. 2006). Using a chlorophyll a-to-particle conversion factor developed for the lake (Swift et al. 2006) along with the chlorophyll a and particle concentrations of the Controls, we determined that 17% of particles were algal in the

Emerald Bay experiment. Only 10% of particles were algal in the Lake Tahoe experiment. Previous studies have found that Daphnia remove food items from their carapace gap when unsuitable items are ingested, and these removed items can even include edible algae (Lampert 1987; Kirk 1991). Therefore, the abundance of non-algal particles may have further contributed to the ineffectiveness of Daphnia in controlling particle size in Lake Tahoe.

The results for the Daphnia and Juvenile Mysid treatments in each experiment suggest that these organisms selected different particle types. While both Daphnia and juvenile mysids were effective in removing small particles in the Emerald Bay experiment, juvenile mysids did not affect chlorophyll a concentrations, suggesting that juvenile mysids may have selected for non-algal particles when grazing. Likewise, in the

Lake Tahoe experiment, juvenile mysids were marginally effective at removing large particles. Lasenby and Langford 1973 suggested that mysids may select non-algal particles with high surface areas, passing the particles through the digestive system and gleaning microbiota from the particle surface. Similarly, other studies have shown that 22 mysids select detrital and inorganic particles from the benthos during daytime feeding

(Van Duyn-Henderson & Lasenby 1986; Bigelow & Lasenby 1991), and this same behavior may explain mysid particle selection in the pelagic zone. Excretion of fecal pellets by the zooplankton taxa may also have contributed to differences in the particle concentrations between the treatments. For instance, because Daphnia fecal pellets more easily disintegrate than those of copepods and mysids (Rigler 1971; Lampert 1987; Evans

1998), the differences in excretions between the taxa may have influenced differences in particle concentrations between the treatments. Further studies into particle selection by mysids in low-nutrient water can help to further illuminate the role of mysids in removing light-attenuating and light-scattering particles.

Contrary to our predictions, none of the zooplankton treatments contributed to an elevation of TDC or DOC concentrations. Instead, Daphnia and juvenile mysids led to a decrease in DOC concentrations in the Lake Tahoe experiment. Furthermore, the mean

DOC concentrations for each of the treatments containing macrozooplankton were lower than the Controls in both experiments, though not all of these differences were statistically significant. The lack of large zooplankton in the Controls may have allowed for an accumulation of DOC that did not occur in the treatments containing the macrozooplankton, and the results suggest that these organisms may have utilized particulate organic carbon as a food source before this matter disaggregated into dissolved forms. This contrasts with previous studies showing that elevated DOC concentrations can result from Daphnia and mysid feeding (Lampert 1978; Sierszen &

Brooks 1982). The lack of difference in TDC concentrations when compared to the 23

Controls suggests that the release of carbon dioxide from the macrozooplankton through

cellular respiration was insignificant in the experiments.

The results for nitrogen and phosphorus compounds did not conform with the

differences in tissue stoichiometry and excretion stoichiometry of these taxa found by

previous studies (Madeira et al. 1982; Andersen & Hessen 1991; Brett et al. 1994; Walve

& Larson 1999; McCarthy et al. 2005). For instance, while we predicted that Epischura

would lead to an increase in SRP because of the relatively phosphorus-rich excretions from calanoid copepods noted in other studies, we instead found that Epischura led to low SRP concentrations. The relatively low concentrations of nitrogen and phosphorus compounds in the low-nutrient waters of Lake Tahoe and Emerald Bay may have negated the stoichiometric differences between these taxa found in other studies. Considering that

Lake Tahoe is primarily limited by phosphorus and secondarily limited by nitrogen

(Goldman et al. 1993), our results suggest that there is no general difference between these taxa in their abilities to stimulate algal growth through nutrient excretions.

As eutrophication increases for freshwater systems, lake ecosystem processes will change as a result (Smith 2003; Vadeboncoeur et al. 2003). As Lake Tahoe continues to undergo progressive cultural eutrophication (Van Landingham 1987; Goldman 1988;

Schladow 2019), its pelagic ecosystem may eventually resemble that of Emerald Bay

(Fig 6). As the lake’s trophic state increases, the differences between the effects of its zooplankton taxa may magnify, as suggested by their general effects on Emerald Bay.

For instance, despite that the lake currently lacks a Daphnia population, Daphnia may play a role in managing the lake’s summer algal concentrations and its summer clarity.

Additionally, because these taxa and mysid life stages dominate during different seasons 24

(Richerson 1969; Morgan & Threlkeld 1982), these zooplankton may generate greater temporal heterogeneity in Lake Tahoe’s planktonic ecosystem with increasing eutrophication. These differences may also be reflected in other oligotrophic lakes undergoing eutrophication.

25

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Richerson PJ (1969) Community Ecology of the Lake Tahoe Plankton. Dissertation, University of California, Davis.

Lampert W (1987) Feeding and nutrition in Daphnia. In: Peters RH, De Bernardi R (ed) Daphnia. Mem Istit ital Idrobiol 45, pp 143–192.

Rigler FH (1971) Laboratory measurements of processes involved in secondary production: zooplankton. In: Edmondson WT, Winberg GG (ed) A Manual on Methods for the Assessment of Secondary Productivity in Fresh Waters. IBP Handbook, No. 17. Blackwell Scientific Publishers, Oxford, pp 228-250.

Ross SM (2014) Introduction to Probability and Statistics for Engineers and Scientists, 5th edn. Elsevier.

Rybock JT (1978) Mysis relicta (Loven) in Lake Tahoe: vertical distribution and nocturnal predation. Dissertation, University of California—Davis.

Shapiro S, Wilk MB (1965) An analysis of variance test for normality (complete samples). Biometrika 52: 591-611. https://doi.org/10.1093/biomet/52.3-4.591 30

Schladow, S. G. 2019. Tahoe: State of the Lake Report 2019. UC Davis Tahoe Environmental Research Center.

Shimadzu Corporation. 2003. TOC-VCPH/CPN & TOC-Control V Software: User Manual. Retrieved from http://www.ecs.umass.edu/eve/facilities/equipment/TOC/TOCV/TOC- V_CP_Users_Manual_E.pdf.

Sierszen ME, Brooks AS (1982) The release of dissolved organic carbon as a result of diatom fragmentation during feeding by Mysis relicta. Hydrobiologia 93: 155- 161. https://doi.org/10.1007/BF00008108

Smith VH (2003) Eutrophication of freshwater and coastal marine ecosystems a global problem. Environ Sci & Pollut Res 10: 126-139. http://dx.doi.or~10.1065/esor2002.12.142

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Steeman-Nielsen ES (1952) The Use of Radio-active Carbon (C14) for Measuring Organic Production in the Sea. J Cons Int Expl Mer 18: 117-140. https://doi.org/10.1093/icesjms/18.2.117

Straile D, Geller W (1998) Crustacean zooplankton in Lake Constance from 1920 to 1995: response to eutrophication and re-oligotrophication. Adv Limnol 53: 255- 274.

Swift TJ, Perez-Losada J, Schladow SG, Reuter JE, Jassby AD, Goldman CR (2006) Water clarity modeling in Lake Tahoe: Linking suspended matter characteristics to Secchi depth. Aquat Sci 68: 1-15. https://doi.org/10.1007/s00027-005-0798-x

Threlkeld ST, Rybock JT, Morgan MD, Folt CL, Goldman CR (1980) The effects of an introduced invertebrate predator and food resource variation on zooplankton dynamics in an ultraoligotrophic lake. In: Kerfoot WC (ed) Evolution and Ecology of Zooplankton Communities. University Press of New England, 555- 568.

Turner JT, Ferrante JG (1979) Zooplankton fecal pellets in aquatic ecosystems. BioScience 29: 670-677. https://doi.org/10.2307/1307591

U.S. Environmental Protection Agency. 1978. Method 365.3: Phosphorus, All Forms (Colorimetric, Ascorbic Acid, Two Reagent). Retrieved from https://www.epa.gov/sites/production/files/2015-08/documents/method_365- 3_1978.pdf 31

U.S. Environmental Protection Agency. 1993. Method 350.1: Determination of Ammonia Nitrogen by Semi-Automated Colorimetry. Environmental Monitoring Systems Laboratory, Revision 2.0.

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Vadeboncoeur Y, Jeppesen E, Vander Zanden MJ, Schierup H, Christoffersen K, Lodge DM (2003) From Greenland to green lakes: Cultural eutrophication and the loss of benthic pathways in lakes. Limnol Oceanogr 48: 1408-1414. https://doi.org/10.4319/lo.2003.48.4.1408

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Zollner E, Santer B, Boersma M, Hoppe H, Jurgens K (2003) Cascading predation effects of Daphnia and copepods on microbial food web components. Freshw Biol 48: 2174-2193. https://doi.org/10.1046/j.1365-2426.2003.01158.x

32

Secchi Depth Chlorophyll a SRP (micrograms / (meters) (micrograms / liter) liter)

Lake Tahoe 21.61 0.4 3.01

Emerald 14 0.92 3.0 Bay

Table 1. Secchi depth, chlorophyll a concentrations, and SRP concentrations for Lake Tahoe and Emerald Bay. Lake Tahoe chlorophyll a and SRP concentrations were determined from an 18-meter depth; Emerald Bay chlorophyll a and SRP concentrations were determined from an 11-meter depth. Lake Tahoe chlorophyll a and Emerald Bay secchi measurements were measured in October 2019; all other measurements were performed in July 2019. 1) Schladow 2019

33

Treatment Description

Control No zooplankton added

Daphnia 360 Daphnia spp. individuals

Epischura 1,680 E. nevadensis individuals

Juvenile Mysid 21 juvenile mysid individuals (length < 12 mm)

Adult Mysid 3 adult mysid individuals (length ≥ 12 mm)

Table 2. Description of the 5 treatments in each experiment. Each treatment consisted of 5 replicates. Each mesocosm contained approximately 27 mg dry weight of the study organism.

34

Daphnia Epischura Juvenile Mysid Adult Mysid

-20 87 98 5 Chlorophyll a (0.98) (0.17) (0.10) (1)

Pheophytin / 28 95 -68 96 Chlorophyll a (0.77P) (0.49P) (0.24P) (0.20P) Ratio

Biomass-specific 93 -180 -61 25 PPR (0.22P) (0.12P) (0.20P) (0.32P)

Small Particles -19 15 -48 3 (≥ 0.5 µm & < 5 (0.96) (1) (0.11) (1) µm)

Large Particles -45 -31 -52 -2 (≥ 5 µm) (0.38) (0.38) (0.06) (1)

-4 1 -7 -3 TDC (0.48P) (0.79P) (0.17P) (0.48P)

-25 -17 -22 -26 DOC (0.04P) (0.12P) (0.06P) (0.04P)

9 0 17 4 NO3 (0.55P) (1P) (0.25P) (0.74P)

-47 -43 -4 -24 NH4 (0.27) (0.49) (1) (0.70)

-7 -35 12 -14 SRP (0.91) (< 0.01) (0.65) (0.51)

-25 9 -12 -5 DIN/SRP Ratio (0.56) (0.98) (0.94) (1)

Table 3. Results for the Lake Tahoe experiment. The values outside of the parentheses are the percent increase (positive value) or decrease (negative value) in the parameter relative to the Control of the experiment. The values in parentheses are the p-values of the statistical tests. Values marked with a P indicate that a permutation test was used, all other values were determined with a Dunnett’s test. Values that are statistically significant (p < 0.05) are bolded.

35

Daphnia Epischura Juvenile Mysid Adult Mysid

-64 25 5 16 Chlorophyll a (< 0.01) (0.81) (1) (0.88)

Pheophytin / 33 2 2 4 Chlorophyll a (0.08) (1) (1) (0.99) Ratio

Small Particles -53 -17 -23 -9 (≥ 0.5 µm & < 5 (0.03P) (0.18P) (0.02P) (0.12P) µm)

Large Particles -44 11 -37 -13 (≥ 5 µm) (0.05) (0.99) (0.25) (0.98)

-8 1 -5 -1 TDC (0.16) (1) (0.51) (1)

-10 -12 -12 -13 DOC (0.22P) (0.13P) (0.12P) (0.11P)

3 -29 14 0 NO3 (0.93P) (0.35P) (0.64P) (1P)

428 216 572 391 NH4 (< 0.01P) (< 0.01P) (< 0.01P) (0.01P)

-26 -35 -10 -13 SRP (0.43) (0.19) (0.96) (0.88)

222 240 230 174 DIN/SRP Ratio (< 0.01) (< 0.01) (< 0.01) (< 0.01)

Table 4. Results for Emerald Bay experiment. The values outside of the parentheses are the percent increase (positive value) or decrease (negative value) in the parameter relative to the Control of the experiment. The values in parentheses are the p-values of the statistical tests. Values marked with a P indicate that a permutation test was used, all other values were determined with a Dunnett’s test. Values that are statistically significant (p < 0.05) are bolded.

36

Fig 1. Chlorophyll a concentrations, pheophytin / chlorophyll a ratios, and biomass-specific PPR. The Lake Tahoe experiment values are shown in the graphs in the left-hand column, and the Emerald Bay experiment values are shown in the graphs in the right-hand column. Treatments that are significantly different (p < 0.05) from the Removal are marked with ** below the x-axis label; treatments that are marginally different (p < 0.1) are marked with *. The mean value of the Control is marked with a dashed line. For each boxplot, the solid horizontal line in the box signifies the median value for that treatment, while the edges of the box signify the first and third quartiles. Note that the y-axis scales are dissimilar. 37

Fig 2. Concentrations of small (≥ 0.5 µm & < 5 µm), large (≥ 5 µm), and cumulative (≥ 0.5 µm) particles in the Lake Tahoe and Emerald Bay experiments. The Lake Tahoe experiment values are shown in the graphs in the left-hand column, and the Emerald Bay experiment values are shown in the graphs in the right-hand column. Treatments that are significantly different (p < 0.05) from the Removal are marked with ** below the x-axis label; treatments that are marginally different (p < 0.1) are marked with *. The mean value of the Control is marked with a dashed line. For each boxplot, the solid horizontal line in the box signifies the median value for that treatment, while the edges of the box signify the first and third quartiles. Note that the y-axis scales differ between subplots.

38

Fig 3. Concentrations of TDC and DOC in the Lake Tahoe and Emerald Bay experiments. The Lake Tahoe experiment values are shown in the graphs in the left-hand column, and the Emerald Bay experiment values are shown in the graphs in the right-hand column. Treatments that are significantly different (p < 0.05) from the Removal are marked with ** below the x-axis label; treatments that are marginally different (p < 0.1) are marked with *. The mean value of the Control is marked with a dashed line. For each boxplot, the solid horizontal line in the box signifies the median value for that treatment, while the edges of the box signify the first and third quartiles. Note that the y-axis scales are dissimilar.

39

Fig 4. Concentrations of nitrate, ammonium, and SRP, and the DIN/SRP ratios in the Lake Tahoe and Emerald Bay experiments. Details are the same as for Fig 1. Note that the y-axis scales are dissimilar. 40

Fig 5. Non-metric multidimensional scaling (NMDS) analysis of the Lake Tahoe and Emerald Bay experiments. Dissimilarities were measured with Euclidean distances.

41

Fig 6. Conceptual model showing the relationships among macrozooplankton and pelagic processes as demonstrated in the Lake Tahoe (oligotrophic) experiment. 1) Rybock 1978; 2) Sawyer 1985

42

Fig 7. Conceptual model showing the relationships among macrozooplankton and pelagic processes as demonstrated in the Emerald Bay (meso-oligotrophic) experiment. Sources are the same as for Fig 6.

43

Supplemental Table 1. Relative % error in cumulative particle (diameters ≥ 0.5 µm) concentrations for samples measured in duplicate.

44

This paper will be submitted to Journal of Great Lakes Research or PEERJ.

Factors Influencing the Production of Mysis diluviana in Three Oligotrophic Lakes

1 2,3 1,3 Zachary Bess , Tim Caldwell , & Sudeep Chandra

1Department of Biology, University of Nevada—Reno, 1664 N Virginia St, Reno, NV, 89557, USA 2McBain Associates, 980 7th St, Arcata, CA, 95521, USA 3Global Water Center, University of Nevada—Reno, 1664 N Virginia St, Reno, NV, 89557, USA

Corresponding Author Contact: [email protected]

Acknowledgements Katie Senft and Brant Allen of the UC Davis Tahoe Environmental Research Center (TERC) provided mysid samples collected from Lake Tahoe in 2018 and 2019. Mysid growth rates were determined from field collections performed by various students and scholars under the guidance of Dr. Charles R. Goldman and Dr. David Beauchamp and from notes of the California and Nevada Bistate fisheries meetings maintained by Robert C. Richards (UC Davis TERC, retired).

45

Abstract

Mysids (Mysis diluviana) were introduced into four deep, stratified, oligotrophic ecosystems (Donner Lake; Fallen Leaf Lake; and Lake Tahoe and its embayment,

Emerald Bay) in the western United States in the mid-1960s. We determine the biotic and abiotic factors that support mysid growth and energetics in these ecosystems. Using Lake

Tahoe mysids, we tested for correlations between growth rates and water clarity, primary productivity, water temperature, depth of winter mixing, stratification duration, mysid density, and zooplankton density. Water temperature significantly correlated with juvenile growth rates, and mixing depth significantly correlated with adult growth rates.

Stable isotope analyses revealed that Donner Lake and Lake Tahoe mysids were supported almost exclusively by pelagic carbon and occupied the third trophic level, indicating a carnivorous diet. In contrast, Fallen Leaf Lake mysids relied on both pelagic and benthic carbon and occupied a trophic position of ~2.5, indicating an omnivorous diet. Analysis of amino acid δ13C from Lake Tahoe and Emerald Bay mysids indicate the relative importance of seasonal contributions of allochthonous carbon, with 9-18% of carbon in mysid tissues from fungal origin. Bioenergetics modeling suggested that pollen played a greater role for Lake Tahoe mysids than for Donner Lake and Fallen Leaf Lake mysids. Our data suggest that both abiotic and bottom-up food web processes support mysid growth in these systems.

Keywords: mysids, amino acid stable isotope analysis, pollen, allochthony

46

Introduction

Mysids (Mysis diluviana) are omnivorous zooplankton that occupy an important functional role in the zooplankton communities of many temperate lakes in western North

America (Johannsson et al. 2001, Ellis et al. 2011, Schindler et al. 2012, Caldwell et al.

2015). Mysids act as both a predator and grazer (Branstrator et al. 2000; O’Malley &

Bunnell 2014) while also serving as an important source of food for fishes (Larkin 1948,

Gamble et al. 2011). Exhibiting strong diel vertical migration, these organisms occupy benthic habitats during the day and the pelagic zone during the night (Rybock 1978).

Previous investigations have identified several factors that influence mysid production and growth (Rudstam 1989; Chipps and Bennett 2000). Because of the plasticity in mysid feeding and vertical migration between pelagic and benthic habitats, an examination of the biotic and abiotic factors that influence mysid production can be useful for understanding how production is regulated in zooplankton communities.

Zooplankton production (e.g. increased generation time or increased specific growth rate) is supported by factors such as water temperature, salinity, water depth, and body size of the organisms (Shuter & Ing 1997; Gillooly 2000; Mathews et al. 2008;

Musialik-Koszarowska et al. 2019). Overall rates of zooplankton production are driven predominately by temperatures (Shuter & Ing 1997), but biotic factors may also play a role in production. For instance, high rates of zooplankton production generally correspond with high algal primary productivity, while detritus generally plays a minimal role (Wetzel 2000). 47

The role of allochthonous subsidies in supporting zooplankton production has been researched for several temperate zooplankton populations. While some studies have suggested that terrestrial materials play a significant role in supporting secondary production of zooplankton by some studies (Graham et al. 2006; Cole et al. 2011), others have found that it plays a minimal role (Brett et al. 2009; Kelly et al. 2014; Brett et al.

2017). For instance, Brett et al. 2017 showed that terrestrial material is of limited importance to lake zooplankton production because most terrestrial material is poor in quality and indigestible by zooplankton. In contrast, in systems such as the boreal lakes examined by Graham et al. 2006, pollen can induce bottom-up effects that lead to higher phytoplankton densities and, consequently, higher herbivorous zooplankton densities.

In other ecosystems, several biotic and abiotic factors influence mysid production.

For instance, higher temperatures lead to higher molting rates in mysids, thereby increasing the length of the organisms (Berrill & Lasenby 1983). Additionally, mysids in lakes with high primary productivity display higher growth rates than those in low- productivity lakes (Morgan 1980; Beeton & Gannon 1991). Feeding rates of mysids are influenced by light (Viherluoto & Vitaalsalo 2001), and adults rely more heavily upon zooplankton prey than juveniles (Rybock 1978; Lesutiene et al. 2007). Furthermore, the role of the benthic zone has been underrepresented in studies of mysid ecology

(Stockwell et al. 2020), though benthic prey items can be important for mysids (Sierszen et al. 2011).

Mysids have been introduced to many lakes in the western United States and have often led to changes in the zooplankton and fish communities of these lakes (Northcote

1991; Hyatt et al. 2018). Mysids were introduced to Donner Lake, Fallen Leaf Lake, and 48

Lake Tahoe in the mid-1960s to improve the production of Kokanee Salmon

(Oncorhynchus nerka) (Linn & Frantz 1965). By the early 1970s, mysid predation had caused the extirpation of the native cladoceran community in Lake Tahoe (Daphnia rosea, D. pulicaria, Bosmina longirostris) (Richards et al. 1975; Goldman et al. 1979) and fluctuations in other zooplankton species (Threlkeld et al. 1980). Concomitantly, the mysids caused a decrease in the size of kokanee salmon because of their competition with kokanee salmon for cladocerans (Morgan et al. 1978; Beauchamp et al. 1994). Although the effects of mysids on food webs have been heavily researched in Lake Tahoe and other lakes, the biotic and abiotic factors that influence mysid growth in these lakes have not been examined. We investigated the factors that influence mysid production in these ecosystems by answering the following questions:

A) Given the complexity of environmental factors, which of these factors influence

mysid population growth rates?

B) Given the strong diel vertical migration of mysids, which habitat (pelagic or

benthic) predominately supports mysid production?

C) What is the trophic niche (trophic position and source of carbon) that supports

production?

Methods

We collected mysids from Donner Lake, Fallen Leaf Lake, Lake Tahoe, and

Emerald Bay (a semi-isolated embayment to the main body of Lake Tahoe) to examine the factors influencing growth and bioenergetics in these ecosystems. The lakes are each oligotrophic but vary in maximum depth and surface area (Table 1, Figure 1, Morgan

1981). Lake Tahoe was originally hyperoligotrophic and has become oligotrophic due to 49 progressive cultural eutrophication, changes to the food web, and climate change

(Goldman 2000). The shoreline length and surface area of Lake Tahoe are significantly greater than the other systems (Table 1).

Historical Data for Lake Tahoe Environmental Factors and Plankton Densities

Historical data was used to assess the factors influencing growth rates in Lake

Tahoe mysids. We used long-term measurements collected by the UC Davis Tahoe

Environmental Research Center of mean summer Secchi depth, primary productivity

(PPR), mean summer water temperature (collected from a 20-meter depth), depth of winter mixing, duration of stratification, mysid density, and zooplankton density.

Duration of stratification was obtained from Schladow 2019. PPR was determined with radioactive 14C using light and dark bottle incubations suspended at discrete depths throughout the water column (Steeman-Nielsen 1952; Goldman 1960). Approximately 20 measurements from April to September of each year taken from a 20-meter depth were used to calculate mean summer water temperature. Depth of winter mixing was determined by measuring nitrate concentrations at discrete depths. Duration of stratification was determined by the number of days on an annual basis when the stratification index (the amount of energy required to fully mix the water column) exceeded 600 kilograms per square meter (Sahoo et al. 2016). Zooplankton densities (the combined densities of rotifers, cladocerans, and copepods) were determined with vertical hauls of an 80-micron zooplankton net. Mysid densities were determined with vertical hauls of a 500-micron zooplankton net from the bottom of the lake to the surface.

Growth Rates 50

Historical data was used to calculate the growth rates of Lake Tahoe mysids.

These mysids were collected with a 500-micron zooplankton net from 100-meter depths to the surface. Mysids were measured from the eyestalk to the tip of the telson. Juvenile and adult mysids were distinguished by plotting the size distribution of the collected mysids and assigning each mysid to one of the two dominant cohorts. Six hundred mysids were measured each year and for each cohort. Growth rates were determined with the following formula:

Growth Rate = (Mean Length in Fall – Mean Length in Spring / (# of days between Fall and Spring Collection)

Data Analysis

Because Pearson’s correlation analyses allow for the determination of the strength and direction of correlation, Pearson’s correlation analyses were used to determine the relationship between the environmental variables and the growth rates of the juvenile and adult mysids. These analyses calculate a coefficient that ranges from −1 to 1. A value of 1 signifies that there is a perfect linear relationship between the variables. In contrast, a value of −1 signifies that there is no relationship between the variables. These analyses were conducted using R version 3.6.3. Observations and measurements from nine years were used in the analyses: 1977, 1978, 1981, 1982, 1983, 1984, 1993, 1994, and 2012.

Prior to conducting the analyses, the data used in each of the analyses were tested to assure that the residuals were normally distributed (Shapiro-Wilk Test, p-value > 0.05) and that the data was homoscedastic (Breusch-Pagan Test, p-value > 0.05). Due to missing values, observations from 1981 were not included in any analyses with 2-year- old mysids, observations from 1978 and 1993 were not included in any temperature 51 analyses, observations from 1993 and 2012 were not included in analyses with mysid densities, and observations from 1977 and 2012 were not included in analyses with zooplankton densities.

Percent Pelagic Reliance

We modeled reliance on pelagic carbon sources using mysids that were collected from Donner Lake in 2012 (January, May, July, August, November), and 2013

(February); from Fallen Leaf Lake in 2012 (January, May, June, August); and from Lake

Tahoe in 2011 (November) and 2012 (January, May). Vertical tows were taken from 100- meter depths to the surface at least 1 hour after sunset using a 500-micron zooplankton net. Approximately ten individuals collected from each lake and collection date were dried in tin capsules, ground to a fine powder, and analyzed by the UC Davis Stable

Isotope Facility for bulk tissue δ13C using mass spectrometry. Only adult mysids that exceeded 12 mm in length from the tip of the eyestalk to the end of the telson were analyzed. The bulk tissue δ13C values of the samples were standardized to the δ13C value of Pee Dee Belemnite gas (Hecky & Hesslein 1995). The pelagic δ13C values from each lake were determined from Daphnia, and the littoral-benthic δ13C values were determined from snail and chironomid primary consumers collected in 2003 (Vander Zanden et al.

2011). We used a two-end-member mixing model to determine the percentage of pelagic reliance; i.e., the degree to which mysids rely on pelagic resources (i.e. phytoplankton, zooplankton) relative to littoral/benthic resources (i.e. periphyton, benthic invertebrates)

(Chandra et al. 2005):

13 13 13 13 Percent Pelagic Reliance = ((δ CMysid - δ CLittoral/Benthic) / (δ CPelagic - δ CLittoral/Benthic)) *

100 52

Values that exceeded 100 were assigned a value of 100 because this indicates that the mysids had a more negative value than the pelagic end member, suggesting that the organism received all of its carbon from pelagic resources.

Trophic position

These same mysids were also analyzed for bulk tissue δ15N, and values were

15 standardized to the δ N value of N2 gas. The following equation was used to determine the trophic position of the mysids (Vander Zanden et al. 1999):

15 15 Trophic position = ((δ NMysid - δ NZooplankton) / 3.4) + 1

15 15 δ N of zooplankton for each of the lakes was determined from bulk tissue δ N analysis of 500-1000 Diaptomus, Holopedium, and Bosmina individuals. Additionally, the trophic positions of mysids collected from Lake Tahoe in 2018 (May, August) and 2019 (May) and from Emerald Bay in 2018 (May, August) and 2019 (May, August) were determined with amino acid δ15N analysis.

When calculating trophic position using compound specific isotope analysis, there are several analytical advantages. First, the need to quantify source signatures at the base of the food web is eliminated because the amino acid signatures are conserved across broad taxonomic groups of primary producers (i.e. green algae, cyanobacteria), unlike bulk tissue signatures (Thorp & Bowes 2017). Therefore, the amino acid δ13C signatures of the primary producers in the ecosystem do not need to be measured. Second, the trophic position of the study organism can be determined without measuring the amino acid δ15N signatures of the primary producers in the ecosystem (Thorp & Bowes 2017).

Three individuals from each of these seasons and from each lake were combusted at 60 53

°C for 1 hour and ground to a fine powder. The following equation was used to determine the trophic position of these samples (Bowes & Thorp 2015):

15 15 Trophic Position = (((δ NGlutamic Acid + Glutamine – δ NPhenylalanine) - 3.4) / 7.6) + 1

Mean trophic position ± standard deviation is presented.

Carbon sources at the base of the food web supporting mysids

Amino acid δ13C analyses of mysids collected from Lake Tahoe in 2018 (May,

August) and 2019 (May) and from Emerald Bay in 2018 (May, August) and 2019 (May,

August) were used to determine the primary carbon sources supporting these mysids.

Mean ± standard deviation is presented. Three mysids from each of the systems and from each collection season were combusted at 60 °C for 1 hour and ground to a fine powder.

δ13C was determined for eleven amino acids (alanine, asparagine, aspartic acid, glutamine, glutamic acid, glycine, isoleucine, leucine, phenylalanine, proline, and valine) by the UC Davis Stable Isotope Laboratory. The mean δ13C values and standard deviation for each amino acid in each sample were analyzed with FRUITS (Food Reconstruction

Using Isotopic Transferred Signals), a Bayesian mixing model used to determine the relative contributions of carbon sources to the diets of organisms (Fernandes 2014).

Because amino acid δ13C values are highly conserved within taxonomic groups of primary producers, previously published δ13C values for these amino acids in cyanobacterial, green algal, fungal, C3 plants, and C4 plants were used as sources in the model (Thorp & Bowes 2017). We used an unweighted FRUITS model with uninformed priors to generate posterior distributions of the percent contributions of each potential food source to the consumer.

Bioenergetics model to determine the role of terrestrial C3 plant pollen 54

Approximately 10 mysids (length > 12 mm) were collected from Donner Lake in

May 2012, June 2012, and July 2012; from Fallen Leaf Lake in May 2012 and June 2012; and from Lake Tahoe in May 2018 and August 2018. The foreguts were carefully dissected out of those individuals and mounted with glycerin gel onto a microscope slide, and examined with a compound microscope (Caldwell et al. 2016). The identifiable contents were classified into the following categories as a percentage of the total identifiable contents in the foregut: pollen, phytoplankton, rotifers, cladocerans, copepods, and pollen. These contents (and the unidentifiable material not included in the models) is reported in Supplemental Table 3. Previously published data for the dry weight energy densities of these prey items was used to calculate a mean caloric value of each of the categories (Supplemental Table 5). The mysid module of FishBio 4.0 was used to fit a bioenergetics model with this diet data to determine the energetic role of pollen in mysid growth (DesLauriers et al. 2017).

Two steps were used in the models used for each of the three lakes:

Step 1) The late spring and late summer lengths of adult mysids in each system was determined from collections of 100-500 mysids from each system. These mean lengths were converted to masses using a mysid length-weight relationship (Chipps 1997). A mysid oxycalorific coefficient of 13,600 J / g O2 was used as an input to the model

(Rudstam 1989). For the Donner Lake model, previously published temperature recordings from a 20-meter depth from 1973 were used as an input to the model (Dong

1975). These are the most recent measurement of water temperature taken from Donner

Lake throughout the mysid growing season. For the Fallen Leaf Lake model, recordings from a 20-meter depth from 2002 were used (Allen et al. 2006). For the Lake Tahoe 55 model, recordings from a 20-meter depth from 2012 were used (Schladow 2013). We assumed that all of the prey items are fully digestible and that their energy density does not change with time. The model was fitted to the initial and final masses to interpolate the growth trajectory throughout the summer and to calculate the CMax value, the proportion of prey that is consumed relative to maximum possible consumption. This model produced a CMax of 0.09.

Step 2) The model was run again but with an assumption that pollen had no caloric value

(dry weight energy density = 0 J/g). The model was fitted to the late spring mean masses and the calculated CMax value (0.09) from step 1. This model was used to calculate the predicted growth trajectory and predicted final late summer mass. Therefore, it estimates the growth of mysids without pollen as an energetic source.

Results

Growth Rates and Environmental Factors

Mean summer water temperature was negatively correlated with the growth rate of juvenile mysids (correlation coefficient = -0.8, p-value = 0.03) (Figure 2C). Depth of winter mixing was significantly correlated with the growth rate of adult mysids

(correlation coefficient = 0.8, p-value = 0.08), with greater mixing depths correlating with higher growth rates. The correlation between Secchi depth and adult mysid growth rate was marginally significant (correlation coefficient = -0.7, p-value = 0.07), with higher water clarity marginally relating to lower growth rates (Figure 2K).

Percent pelagic reliance

Lake Tahoe and Donner Lake mysids derived a majority of their carbon from the pelagic habitat and relied minimally upon the benthos. For Donner Lake mysids, pelagic 56 reliance ranged from 82% ± 6.6 (mean and uncertainty in mixing model output) in

January 2012 to 99% ± 6.6 in February 2013 (Figure 3A). In Lake Tahoe mysids, pelagic reliance was greater than 98% in each of the time periods analyzed (Figure 3C). This differed from mysids in Fallen Leaf Lake which relied less on pelagic sources in both winter and summer 2012. These values ranged from 53% ± 1.1 in January 2012 to 66% ±

7.7 in June 2012 (Figure 3B).

Trophic position

δ15N analysis indicated that mysids were consistent secondary consumers (trophic position ~ 3) in Donner Lake, Emerald Bay, and Lake Tahoe (Figure 4A, C, D). The lowest positions occurred in Lake Tahoe mysids in January (2.8 ± 0.2) and May 2012

(2.8 ± 0.3), while the highest, occurred in mysids in Donner Lake in July 2012 (3.2 ± 0.2) and Lake Tahoe mysids in November 2011 (3.2 ± 0.2). This contrasts with Fallen Leaf

Lake, where positions ranged from 2.2 ± 0.2 in June 2012 to 2.5 ± 0.1 in August 2012

(Figure 4B). These values indicate an omnivorous diet consisting of primary producers and primary consumers.

Primary carbon sources at the base of the food web contributing to mysid growth

In Emerald Bay and Lake Tahoe, C3 plants (terrestrial plants or aquatic macrophytes) or green algae consistently provided the majority of primary carbon for mysids (Figure 5). C3 plants were the dominant carbon source for Lake Tahoe mysids in

May 2018 and May 2019 and for Emerald Bay mysids in August 2018, providing 61% ±

2.4, 59% ± 1.1, and 69% ± 3.5 of primary carbon, respectively. In Lake Tahoe, green algae provided 79% ± 1.5 of primary carbon for mysids in August 2018. In Emerald Bay, green algae provided 87% ± 1.8, 86% ± 1.4, and 90% ± 0.9 of primary carbon for 57

Emerald Bay mysids in May 2018, May 2019, and August 2019, respectively. Fungus contributed 9-18% of primary carbon. Cyanobacteria and C4 plants contributed minimally as a source of carbon, and the highest contribution from these carbon sources was a 4% ± 0.01 contribution from cyanobacteria to Emerald Bay mysids in August

2018.

Bioenergetics model to determine the role of C3 plant pollen

For both Donner Lake and Fallen Leaf Lake, bioenergetics modeling showed that mysids continue to grow throughout the summer even without pollen providing an energetic contribution (Figure 6A, B). The mean mass of Donner Lake mysids in May

-2 -2 2012 was 2.8 x 10 g and 4 x 10 g in July 2012 with pollen serving as an energetic source. The modeled mean length for July 2012 without pollen as an energetic source was 3.5 x 10-2 g mm. For Fallen Leaf Lake mysids, the observed mean mass in May 2012 was 2.4 x 10-2 g and 3 x 10-2 g mm in July 2012, while the modeled mean mass without energetic pollen was 2.5 x 10-2 g mm. In contrast, Lake Tahoe mysid mass declined throughout the summer growing season without pollen as a dietary item (Figure 6C). For these mysids, the mean mass was 2.4 x 10-2 g and 2.9 x 10-2 g in May and November

2012, respectively, while the predicted mean mass without pollen as a dietary item for

November 2012 was 1.5 x 10-2 g.

Discussion

We found that juvenile growth rates of mysids in Lake Tahoe negatively correlate with summer water temperature, while adult growth rates positively correlate with the depth of winter mixing. Mysids in Lake Tahoe and Donner Lake are secondary consumers, relying almost exclusively upon the pelagic zone. In contrast, mysids in 58

Fallen Leaf Lake are omnivores relying equally upon the littoral/benthic and pelagic zones. Mysids are supported by green algae, C3 plants, and fungi as primary carbon sources, but the relative contributions of these sources vary among ecosystems and between seasons. Bioenergetics modeling showing the importance of pollen suggests that some of the carbon derived from C3 plants is of terrestrial origin. No fragments of vascular plants were found in the mysid foreguts other than the pollen.

What environmental factors influence mysid population growth rates?

The abiotic factors in lakes influencing juvenile and adult mysids differ and may depend on the life stage of the organism. Our data show that juvenile growth rates are negatively affected by temperature, and this correlation could be due to warm temperatures that may be detrimental to juvenile growth. Juvenile mysids horizontally migrate to shallower water during the summer (Morgan & Threlkeld 1982), and the higher temperature and light preferences of juveniles allow these organisms to inhabit higher positions in the water column than adults (Boscarino et al. 2010). This spatial segregation of adults and juveniles may have acted in conjunction with thermal stress to decrease juvenile growth rates. Other studies suggest that temperature is a primary abiotic factor controlling the production of mysids. Higher temperatures can lead to increased mortality and can perhaps contribute to lower densities in the summer (Mayor and

Chigbu 2018).

Lake mixing depth correlated with adult growth rates, but not with juvenile growth rates. We suggest that deep mixing may have benefitted the prey items of adult mysids. Specifically, mixing may have remobilized nutrients and organic matter into the epilimnion and stimulated mysid growth through bottom-up processes that supported 59 zooplankton production. Because adult mysids consume more zooplankton than juveniles, this may explain why deep mixing only increased the growth rates of adults

(Branstrator et al. 2000; Viherluoto et al. 2000; Lehtinimieni et al. 2002). Lake Tahoe water temperatures have risen considerably over the past half-century (Schladow 2019), and these increases in temperature lead to an increase in the resistance to mixing (Coats et al. 2016). Therefore, if these warming trends continue, increased water temperatures may directly decrease juvenile growth rates and indirectly decrease adult growth rates through a lack of deep mixing.

Which habitat (pelagic or benthic) supports mysid production?

Only the mysids collected from Fallen Leaf Lake derived carbon equally from the pelagic and littoral-benthic habitat. The mysids from the other systems relied almost exclusively upon pelagic carbon. Since isotopic signatures are a reflection of the prey incorporated into the animal, mysids from Fallen Leaf Lake appear to be utilizing a mix of food resources that are from the pelagic and sublittoral-littoral benthic habitats. It is not clear why this may be occurring in this lake and not the others given that Fallen

Leaf’s Lake’s size and depth is similar to Donner Lake. One possible explanation is that bathymetry may play a role in the vertical migrations of the taxa. Because of the relatively shallow region at the terminal end of the lake, mysids in Fallen Leaf Lake may be able to more easily access the benthic zone in this lake. Furthermore, the Fallen Leaf

Lake ecosystem may be receiving benthic matter produced in the shallower water bodies in the Fallen Leaf Lake watershed.

The role of the pelagic habitat may be overestimated in our analyses for all lakes because of the sedimentation of pelagic algal materials to the lake bottom. It is possible 60 that some of the pelagic carbon incorporated into mysid tissues may be derived from the consumption of benthic invertebrates that feed upon sedimented pelagic material, especially considering that other studies have noted the importance of benthic invertebrates to mysid diets (Johannsson et al. 2001; Sierszen et al. 2011). In Lake Tahoe,

Chandra et al. 2005 showed that benthic invertebrates within the sublittoral zone have shifted their feeding energetics to pelagic energy sources as sedimentation has increased due to progressive cultural eutrophication. Tahoe sucker (Catostomus tahoensis), an obligate benthic feeding fish, also shifted to reliance upon pelagic carbon.

What is the trophic niche (position and source of carbon) that supports production?

Mysids in Donner Lake and Lake Tahoe are secondary consumers, while Fallen

Leaf Lake mysids are omnivores relying upon both primary consumers and primary producers. Plankton populations in Donner Lake and Fallen Leaf Lake are less studied than in Lake Tahoe, and studies into the plankton dynamics of these two lakes are necessary to draw any further conclusions into why mysid diets differ between these ecosystems.

While the amino acid δ13C analyses reveal the relative contributions of broad taxonomic groups (i.e. cyanobacteria, vascular plants, green algae) to mysids, we cannot infer from this analysis whether this carbon was incorporated through direct consumption of prey items belonging to these taxonomic groups or through transfer from lower trophic levels. The mysids in Lake Tahoe and Emerald Bay are supported by green algae and C3 plants. However, contributions from C3 plants are generally more important to Lake

Tahoe mysids than Emerald Bay mysids, and the amino acid δ13C analysis alone does not indicate whether these C3 plants are terrestrial or aquatic. The authors have observed 61 mysids in the plant beds along the west shore of the lake, but whether these aquatic plants contribute to mysid energetics is not well understood. Furthermore, despite that diatoms are the dominant phytoplankton group in Lake Tahoe, the amino acid δ13C values of diatoms have not been previously published. Therefore, we were unable to include diatoms as a carbon source in our model.

It is possible that despite the lower shoreline:surface area ratio of Lake Tahoe relative to Emerald Bay, allochthonous material may play a greater role as a subsidy in

Lake Tahoe because of the ecosystem’s lower primary productivity. A similar conclusion was reached by Carpenter et al. 2005, which found that zooplankton rely less on allochthonous material in high-nutrient lakes than in low-nutrient lakes. Allochthonous inputs may indeed be greater in Emerald Bay than in Lake Tahoe, but the abundance of this terrestrial matter may be minimal relative to the higher quantity of phytoplankton.

Similarly, Wetzel 1995 and Taipale 2016 proposed that allochthonous materials support aquatic organisms when superior autochthonous carbon is not generally available.

Our study is the first to show that fungi play a role in mysid production. While the contribution from fungi is minimal, the contribution is consistent (ranging from 9 to 18% of all mysid carbon) for Emerald Bay and Lake Tahoe in both early and late summer.

Fungi such as chytridiomycota were not observed in any of the mysid foreguts. However, zooplankton such as Daphnia can ingest fungal parasites of phytoplankton (Frenken et al.

2020). This ingestion of fungal carbon through the mycoloop may be similar to how fungal carbon is incorporated into mysid tissues. Further research is needed to understand whether fungal carbon is incorporated into mysid tissues through the consumption of fungus or through the consumption of prey items infected with fungus. 62

The bioenergetics models indicate that pollen is an important part of the diet of mysids in these lakes, indicating that terrestrial carbon may indeed play a role in mysid growth. When considered with the amino acid δ13C analyses, this lends credence to the possibility that at least a portion of the C3 plant carbon present in mysid tissues may have been incorporated through direct consumption of this pollen. The modeling suggests that pollen is relatively unimportant for Donner Lake and Fallen Leaf Lake mysids compared to Lake Tahoe mysids. However, the role of pollen may be overestimated given that the foregut analyses only reflect feeding that took place during the night in the pelagic zone.

Therefore, the benthic prey items that are ingested during the day are inherently not reflected in the analysis. Because these mysids are relatively larger zooplankters capable of ingesting these pollen grains that are unavailable to smaller zooplankton, this suggests that mysids may utilize terrestrial carbon that is unavailable to the other species in the zooplankton community.

Despite that pollen has been likewise noted in the foreguts of mysids in other studies (Bonsdorff & Bonsdorff 2005; O’Malley & Bunnell 2014), it remains possible that mysids may not digest and metabolize pollen tissues fully. Other studies have noted that pollen is generally digestible for other animals (reviewed in Roulston & Caine 2000), and we, therefore, assume that it is digestible for mysids. Further research is needed to determine the digestibility of pollen by mysids. The pollen observed in the foreguts in this study is likely contributed by Abies and Pinus, two genera of conifers which produce pollen that is dispersed into Lake Tahoe (Richerson et al. 1970).

Summary 63

Our findings suggest that mysid production is determined by factors that influence other zooplankton taxa, such as water temperature and the availability of animal and phytoplankton prey items. However, the relative degree to which mysids rely upon these prey items varies across ecosystems. We found that mysids are also influenced by factors that likely do not influence production of other zooplankton taxa. For instance, the role that pollen pulses play in for mysids in these lakes likely differs from the role that these pulses play for smaller zooplankton taxa that are unable to ingest large pollen grains.

Likewise, mysid production can also be influenced by benthic production, and this likely differs from production of other zooplankton taxa that are exclusively pelagic. Because agencies and organizations are now attempting to control mysid populations in order to restore the food webs of lakes throughout the temperate zone, our research indicates that a variety of factors would need to be managed in order to limit mysid production through bottom-up processes.

64

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Donner Fallen Leaf Emerald Bay Lake Tahoe Lake Lake Mean Depth Maximum Depth: 33 72 305 (meters) 60 Surface Area (sq. 3.4 5.7 2.0 495 kilometers) Shoreline Length 13 12 6.4 121 (kilometers) Watershed Area: Lake 10.591 7.832 Unknown 2.62 Surface Area Ratio Primary Productivity (mg. carbon / 5.3 5.9 6.3 1.9 sq. meter / day)3

Table 1. Limnological variables of the study ecosystems. 1) Dong 1975; 2) Hanes 1981; 3) Morgan 1981.

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Figure 1. Map of study ecosystems created using QGIS Version 3.14. Shapefiles of the lakes and streams were accessed from the California Department of Fish & Wildlife GIS Clearinghouse (https://wildlife.ca.gov/Data/GIS/Clearinghouse). Shapefile of North America accessed from ESRI (https://www.arcgis.com/home/item.html?id=5cf4f223c4a642eb9aa7ae1216a04372).

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Figure 2. Growth rates of juvenile (A-G) and adult (H-N) mysids regressed with environmental variables in Lake Tahoe. Correlation coefficients of Pearson’s correlation analyses are outside the parentheses, and p-values are within the parentheses. Statistically significant p-values (p < 0.05) are marked with **, while marginally significant p-values (p < 0.1) are marked with *.

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Figure 3. The reliance of mysids on pelagic carbon sources (%) in a) Donner Lake, b) Fallen Leaf Lake, and c) Lake Tahoe determined from bulk tissue analysis of δ13C. The box plots show the median values (horizontal line inside box), 1st and 3rd quartiles (box perimeter), and outlier values.

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Figure 4. Trophic positions of mysids in a) Donner Lake, b) Fallen Leaf Lake, c) Emerald Bay, and d) Lake Tahoe. The trophic positions of Emerald Bay mysids and the 2018 (May, August) and 2019 (May) Lake Tahoe mysids were determined with amino acid δ15N analysis. All other trophic positions were determined with bulk tissue δ15N analysis. The box plots show the median values (horizontal line inside box), 1st and 3rd quartiles (box perimeter), and outlier values.

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Figure 5. Contributions (%) of primary carbon sources to mysids in Lake Tahoe from 5 sources of energy (cyanobacteria, chlorophytes, and C3 (including aquatic plants) and C4 terrestrial plants, and fungi. Contributions were determined with amino acid δ13C analyses.

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Figure 6. Bioenergetics models representing the growth of mysids in a) Donner Lake, b) Fallen Leaf Lake, and c) Lake Tahoe. Solid lines represent observed growth of mysids, while dashed lines represent modeled growth with pollen providing no energetic contribution to mysids.

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Figure 7. Conceptual model of the factors that support Mysis diluviana based upon the general findings of this study.

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Supplemental Table 1. Bulk tissue δ13C and δ15N of mysids.

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Lake Organism Month & Year δ15N Donner Diaptomus Jan 2012 7.3 Donner Diaptomus Jan 2012 8.6 Donner Diaptomus May 2012 6.1 Donner Diaptomus May 2012 6.4 Donner Diaptomus Jul 2012 6.0 Donner Diaptomus Jul 2012 4.8 Donner Holopedium Aug 2012 1.5 Donner Holopedium Aug 2012 1.9 Donner Holopedium Aug 2012 2.4 Donner Diaptomus Nov 2012 3.1 Donner Diaptomus Nov 2012 5.0 Donner Diaptomus Nov 2012 5.0 Donner Diaptomus Nov 2012 4.9 Donner Bosmina Nov 2012 4.1 Donner Diaptomus Feb 2013 7.9 Donner Diaptomus Feb 2013 7.5 Donner Diaptomus Feb 2013 7.2 Mean δ15N of Donner Lake Herbivorous Zooplankton: 5.3 Fallen Leaf Diaptomus Jan 2012 7.1 Fallen Leaf Diaptomus May 2012 3.8 Fallen Leaf Diaptomus May 2012 3.4

Fallen Leaf Bosmina Aug 2012 5.0

Fallen Leaf Diaptomus Aug 2012 4.8 85

Fallen Leaf Diaptomus Aug 2012 3.3

Fallen Leaf Diaptomus Aug 2012 6.8

Mean δ15N of Fallen Leaf Lake Herbivorous Zooplankton: 4.9 Tahoe Diaptomus Jan 2012 1.7 Tahoe Diaptomus Jan 2012 1.8 Tahoe Diaptomus Jan 2012 1.9 Tahoe Diaptomus Jan 2012 1.9 Tahoe Diaptomus Jan 2012 2.0 Tahoe Diaptomus Jan 2012 2.6 Tahoe Diaptomus May 2012 2.8 Tahoe Diaptomus May 2012 2.6 Tahoe Diaptomus May 2012 2.4 Tahoe Diaptomus May 2012 2.7 Tahoe Diaptomus May 2012 2.6 Tahoe Diaptomus May 2012 2.4 Tahoe Diaptomus Aug 2012 2.2 Tahoe Diaptomus Aug 2012 2.4 Tahoe Diaptomus Aug 2012 2.3 Tahoe Diaptomus Aug 2012 2.3 Tahoe Diaptomus Aug 2012 1.8 Tahoe Diaptomus Aug 2012 2.1 Mean δ15N of Lake Tahoe Herbivorous Zooplankton: 2.2

Supplemental Table 2. Bulk tissue δ15N of herbivorous zooplankton

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Lake Month Year Copepods Cladocerans Phytoplankton Rotifers Pollen Other Donner May 2012 12 12 0 23 23 31 Donner May 2012 0 8 8 23 23 38 Donner May 2012 9 36 0 18 18 18 Donner May 2012 0 14 0 34 34 17 Donner May 2012 0 20 0 24 24 32 Donner May 2012 0 10 0 10 10 70 Donner May 2012 0 38 0 10 10 43 Donner May 2012 0 8 0 23 23 46 Donner May 2012 0 0 0 17 17 67 Donner May 2012 0 26 0 17 17 39 Donner July 2012 12 12 0 23 23 31 Donner July 2012 0 8 8 23 23 38 Donner July 2012 9 36 0 18 18 18 Donner July 2012 0 14 0 34 34 17 Donner July 2012 0 20 0 24 24 32 Donner July 2012 0 10 0 10 10 70 Donner July 2012 0 38 0 10 10 43 Donner July 2012 0 8 0 23 23 46 Donner July 2012 0 0 0 17 17 67 Donner July 2012 0 26 0 17 17 39 Donner August 2012 12 12 0 23 23 31 Donner August 2012 0 8 8 23 23 38 Donner August 2012 9 36 0 18 18 18 Donner August 2012 0 14 0 34 34 17 Donner August 2012 0 20 0 24 24 32 Donner August 2012 0 10 0 10 10 70 Donner August 2012 0 38 0 10 10 43 Donner August 2012 0 8 0 23 23 46 Donner August 2012 0 0 0 17 17 67 Donner August 2012 0 26 0 17 17 39 Donner November 2012 12 12 0 23 23 31 Donner November 2012 0 8 8 23 23 38 Donner November 2012 9 36 0 18 18 18 Donner November 2012 0 14 0 34 34 17 Donner November 2012 0 20 0 24 24 32 Donner November 2012 0 10 0 10 10 70 Donner November 2012 0 38 0 10 10 43 Donner November 2012 0 8 0 23 23 46 Donner November 2012 0 0 0 17 17 67 87

Donner November 2012 0 26 0 17 17 39 Fallen May 2012 12 12 0 23 23 31 Leaf Fallen May 2012 0 8 8 23 23 38 Leaf Fallen May 2012 9 36 0 18 18 18 Leaf Fallen May 2012 0 14 0 34 34 17 Leaf Fallen May 2012 0 20 0 24 24 32 Leaf Fallen May 2012 0 10 0 10 10 70 Leaf Fallen May 2012 0 38 0 10 10 43 Leaf Fallen May 2012 0 8 0 23 23 46 Leaf Fallen May 2012 0 0 0 17 17 67 Leaf Fallen May 2012 0 26 0 17 17 39 Leaf Fallen June 2012 12 12 0 23 23 31 Leaf Fallen June 2012 0 8 8 23 23 38 Leaf Fallen June 2012 9 36 0 18 18 18 Leaf Fallen June 2012 0 14 0 34 34 17 Leaf Fallen June 2012 0 20 0 24 24 32 Leaf Fallen June 2012 0 10 0 10 10 70 Leaf Fallen June 2012 0 38 0 10 10 43 Leaf Fallen June 2012 0 8 0 23 23 46 Leaf Fallen June 2012 0 0 0 17 17 67 Leaf Fallen June 2012 0 26 0 17 17 39 Leaf Fallen August 2012 12 12 0 23 23 31 Leaf Fallen August 2012 0 8 8 23 23 38 Leaf Fallen August 2012 9 36 0 18 18 18 Leaf Fallen August 2012 0 14 0 34 34 17 Leaf Fallen August 2012 0 20 0 24 24 32 Leaf Fallen August 2012 0 10 0 10 10 70 Leaf Fallen August 2012 0 38 0 10 10 43 Leaf Fallen August 2012 0 8 0 23 23 46 Leaf 88

Fallen August 2012 0 0 0 17 17 67 Leaf Fallen August 2012 0 26 0 17 17 39 Leaf Tahoe May 2018 10 0 5 10 20 55 Tahoe May 2018 0 0 0 0 5 95 Tahoe May 2018 0 0 5 0 40 60 Tahoe August 2018 10 0 0 30 5 60 Tahoe August 2018 5 0 5 5 5 90 Tahoe August 2018 10 0 0 5 5 80 Tahoe August 2018 0 0 5 0 30 70 Tahoe August 2018 0 0 0 5 5 95 Tahoe December 2018 0 10 0 5 5 80 Tahoe December 2018 10 5 0 10 10 65 Tahoe December 2018 10 5 5 5 5 85 Tahoe December 2018 15 5 5 10 5 70 Tahoe December 2018 15 5 0 20 10 60 Tahoe December 2018 5 5 0 0 5 90 Tahoe December 2018 15 5 5 5 5 90 Tahoe December 2018 15 5 0 10 5 70 Tahoe December 2018 0 0 0 0 5 0

Supplemental Table 3. Percentages of dietary items in mysid foregut analyses incorporated into the bioenergetics model. Matter classified in the “Other” category consists of unidentifiable matter that was not incorporated into the models.

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Supplemental Table 4. Amino acid δ15N values of mysids and the calculated trophic positions.

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Supplemental Table 5. Energy density for prey items used in the bioenergetics models.

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General Summary of Findings

Species introductions can influence ecosystems in a number of ways. While previous research at Lake Tahoe has indicated that mysids have changed the food web of the lake, the research in this thesis demonstrates that mysid introductions into low- productivity lakes may contribute to ecosystem changes beyond just changes in food webs. Furthermore, as productivity in these lake increases, the effects of these mysids on the ecosystem may diverge from the roles of other zooplankton, as shown in Chapter 1 of this thesis. Therefore, with increasing productivity, lakes that contain mysid populations may be increasingly subject to seasonal changes in phytoplankton dynamics, clarity, and nutrient dynamics with seasonal changes in the zooplankton community.

Future changes to lakes with mysid populations may also be brought about by climate change. Based upon the analyses presented in Chapter 2 of this thesis, climate change may lead to a decrease in juvenile growth rates of mysids through increased water temperatures. Likewise, climate change may also lead to a decrease in adult growth rates of mysids because of the lack of deep mixing as a result of higher water temperatures and thermal stability. However, the effect of these changes on the densities of mysids will need to be investigated further. Furthermore, mysid growth rates in other ecosystems may be regulated by other factors than those observed for Lake Tahoe.

While previous research has indicated that allochthonous subsidies play a minimal role in supporting zooplankton (Brett et al. 2009; Brett et al. 2017), mysids may be an exception to this rule if they are supplied with terrestrial carbon of higher quality that can support their growth. Because these mysids are larger than other zooplankton, they are thereby more likely to take advantage of large allochthonous materials such as pollen 94 grains. This relationship could potentially be investigated further by examining the relationship between terrestrial primary productivity and mysid secondary productivity.

The degree to which mysid populations rely on the pelagic or benthic zones is relevant for the management of all mysid populations. However, it is especially important for lakes in which algal primary productivity is increasing. Increases in algal primary productivity can lead to decreases in benthic productivity through “shading”

(Vadeboncouer et al. 2003), and this phenomenon has been observed in Lake Tahoe

(Chandra 2005). Therefore, the degree to which mysids in other lakes rely upon benthic or pelagic zones could explain future changes in the productivity of these mysid populations.

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General Summary References

Brett, M.T., Kainz, M.J., Taipale, S.J., and Seshan, H. 2009. Phytoplankton, not allochthonous carbon, sustains herbivorous zooplankton production. PNAS 106(50): 21197-21201. doi:10.1073/pnas.0904129106. Brett, M.T., Bunn, S.E., Chandra, S., Galloway, A.W.E., Guo, F., Kainz, M.J., Kankaala, P., Lau, D.C.P., Moulton, T.P., Power, M.E., Rasmussen, J.B., Taipale, S.J., Thorp, J.H., and Wehr, J.D. 2017. How important are terrestrial organic carbon inputs for secondary production in freshwater ecosystems? Freshw. Biol. 62(5): 833-853. doi:10.1111/fwb.12909.

Chandra, S., Vander Zanden, M.J., Heyvaert, A.C., Richards, R.C., Allen, B.C., and Goldman, C.R. 2005. The effects of cultural eutrophication on the coupling between pelagic primary producers and benthic consumers. Limnol. Oceanogr. 50(5): 1368-1376. doi:10.4319/lo.2005.50.5.1368.

Vadeboncoeur, Y., Jeppesen, E., Vander Zanden, M.J., Schierup, H., Christoffersen, K., Lodge, D.M. 2003. From Greenland to green lakes: Cultural eutrophication and the loss of benthic pathways in lakes. Limnol. Oceanogr. 48: 1408-1414. doi:10.4319/lo.2003.48.4.1408.