Direct and Indirect Impacts of Turbidity and Diet on an African Cichlid Fish

Home , Turbidity

Living in a haze:

Direct and indirect impacts of turbidity and diet on an African cichlid fish

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the

Graduate School of The Ohio State University

Tiffany Lynn Atkinson

Graduate Program in Environment and Natural Resources

The Ohio State University

2019

Thesis Committee

Dr. Suzanne M. Gray, Advisor

Dr. Lauren M. Pintor

Dr. Roman P. Lanno

Dr. Lauren J. Chapman

Copyrighted by

Tiffany Lynn Atkinson

2019

Abstract

Worldwide, a major threat to aquatic systems is increased sediment runoff, which can lead to elevated levels of turbidity. In an increasingly variable world, the ability for animals to respond rapidly to environmental disturbance can be critical for survival. Chronic and acute turbidity exposure can have both indirect and direct effects on fish across large and small spatial scales. Indirect impacts include alteration of the sensory environment of fishes (disrupting communications) and shifts in prey availability; while direct impacts include damage to respiratory organs or eliciting physiological compensatory mechanisms that influence fitness- related traits associated with reproduction and survival. I used a combination of field and laboratory studies to examine the effects of elevated turbidity on an African cichlid fish

(Pseudocrenilabrus multicolor victoriae). This sexually dimorphic species is widespread across the Nile River basin and is found across extreme environmental gradients (e.g. dissolved oxygen, turbidity). I investigated if within-population variation in diet and male nuptial coloration are associated with turbidity on a microgeographic spatial-scale. Diet was investigated because many cichlid fish depend on dietary carotenoids (red and yellow pigments) for their reproductive displays and other physiological mechanisms associated with health. I found that fish from mostly clear waters ate a higher proportion of plant material and males were more colorful than fish found at more turbid locations. This could indicate that male reproductive traits are plastic across environmental extremes. In the laboratory study, I used a split-brood rearing experiment

iii to investigate the effects of turbidity level (high/low) and dietary carotenoid concentration

(trace/low) on reproductive traits in P. multicolor. I found that chronic turbidity and carotenoid diets had differential effects on males and females: nuptial coloration and gonadosomatic index were higher in males reared under high turbidity and the trace-carotenoid diet, while exposure to chronic turbidity (but not carotenoid diet) had a negative effect on the overall size of female P. multicolor. This could indicate that some level of stress from chronic turbidity and diet creates an environment where males invest more in immediate reproduction vs. future reproduction and long-term somatic health. It also indicates that the stress from turbidity negatively influenced female size, which is often correlated with fecundity, possibly due to reduced reaction distance and ability to acquire food. I also investigated the effect of acute and chronic turbidity exposure on the swimming performance of P. multicolor. I found that swimming performance was improved by acute turbidity exposure, and chronic turbidity exposure had no effect. This could mean that the aerobic capacity of P. multicolor, under low-to-moderate levels of chronic turbidity, is unaffected possibly due to compensatory adaptations. Additionally, the ability to perform better under acute turbidity exposure may point towards behavioral mechanisms as an attempt to remove themselves from an environmental stressor. This study has helped to emphasize that the impact of turbidity varies due to a number of circumstances such as concentration, duration of exposure, species, and sex. By further investigating the effects of turbidity as a stressor on traits associated with reproduction and survival of a fish found naturally across both extremes, we can further our understanding of the mechanisms that contribute to the persistence of fish facing human-induced environmental changes.

Acknowledgments

I would like to thank the Commissioner of Fisheries Resources Management and

Development, Uganda, for permission to export preserved specimens, and the Uganda National

Council for Science and Technology (UNCST) for research permission. I would also thank Dr.

Lauren Chapman for use of research facilities in Uganda (Lake Nabugabo Research Station); Dr.

Dennis Twinomigisha and Ugandan field assistants (Mutebi, Kiberu, Sseygoya, and Geoffrey) for invaluable help whilst in Uganda. A special thanks to Dr. Jessica Cooperstone for help with carotenoid analyses. I would also like to thank B. Tracy, N. Episcopo, R. MacDonald, H. Fried,

R. Oldham, T. Hrabak, B. Drohan, N. Steffensmeir, G. Ravary, C. Nieman, B. Williams, J

Evans, and K. Dean for assistance with fish rearing, laboratory work, and data entry; the Gray and Pintor lab members for their continued support; and my mother, Theresa Warner, for reminding me to breathe. This material is based upon work supported by the National Science

Foundation Graduate Research Fellowship Program under Grant No. DGE-1343012. Research support provided by state and federal funds appropriated to The Ohio State University, College of Food, Agricultural, and Environmental Sciences, Ohio Agricultural Research and

Development Center. Further funding was provided by The Ohio State University Office of

International Affairs Academic Enrichment Grant and American Cichlid Association Guy D.

Jordan Research Fund.

Vita

Education

2016-19 M.S. Environmental and Natural Resources, The Ohio State University

2010-16 B.S. Environmental Science- Water Science, The Ohio State University

Research Experience

2016-19 NSF Graduate Research Fellow, The Ohio State University

Supervisor- Dr. Suzanne M. Gray

2014-16 Undergraduate Honors Student Researcher, The Ohio State University

Supervisor- Dr. Suzanne M. Gray

2014 Research Experience for Undergraduates, Ohio Sea Grant’s Stone Laboratory

Supervisor- Dr. Doug Kane

Publications

Atkinson T., Desrosiers S., Townsend T., and Simon T. P. 2015. Length-weight relationships of

the Emerald Shiner (Notropis atherinoides, Rafinesque 1818) in the Western Basin of

Lake Erie. Ohio J. Sci. DOI: http://dx.doi.org/10.18061/ojs.v114i2.4719

Fields of Study

Major Field: Environment and Natural Resources

Table of Contents

Abstract ...... iii Acknowledgments...... v Vita ...... vi List of Tables ...... ix List of Figures ...... x Chapter 1...... 1 References ...... 6 Chapter 2 ...... 9 Abstract ...... 9 1. Introduction ...... 10 2. Materials and Methods ...... 17 3. Results ...... 22 4. Discussion ...... 25 References ...... 32 Figures...... 41 Chapter 3 ...... 45 Abstract ...... 45 1. Introduction ...... 46 2. Materials and Methods ...... 52 3. Results ...... 59 4. Discussion ...... 61 References ...... 72 Tables ...... 80 Figures...... 83 Chapter 4 ...... 87 References ...... 91 References ...... 92 Appendix A- Supplemental Materials: Chapter 2 ...... 108 A.Tables ...... 108

vii

A.Figures ...... 113 Appendix B- Supplemental Materials: Chapter 3 ...... 114 B.Tables ...... 114 B.Figures ...... 117

viii

List of Tables

Table 3.1 Male Reproductive Traits Across Treatments ...... 80 Table 3.2 Female Reproductive Traits Across Treatments ...... 81 Table 3.3 Swimming Performance Across Treatments ...... 82 Table A.1 AIC Model Selection for Male Coloration ...... 108 Table A.2 Multiple Comparisons of Turbidity and Temperature ...... 109 Table A.3 Macroinvertebrate Counts by Turbidity Level ...... 110 Table A.4 Relative Abundance of Prey Items ...... 111 Table A.5 Relative Volume of Prey Items ...... 112 Table B.1 Experimental Diet Recipe ...... 114 Table B.2 Environmental Rearing Conditions of Experimental Aquaria ...... 115 Table B.3 Transformations Used for Male and Female Reproductive Traits ...... 116

List of Figures

Figure 2.1 Satellite Image of Sample Location ...... 41 Figure 2.2 Temperature and Turbidity Across Station Types ...... 42 Figure 2.3 Relative Abundance and Volume of Prey Types in Diets of Wild P. multicolor ...... 43 Figure 2.4 Coloration and Size of Wild, Male P. multicolor ...... 44 Figure 3.1 Experimental Swimming Performance Chamber ...... 83 Figure 3.2 Reproductive Traits of Lab Reared, Male P. multicolor ...... 84 Figure 3.3 Reproductive Traits of Lab Reared, Female P. multicolor ...... 85 Figure 3.4 Swimming Performance of Lab Reared P. multicolor ...... 86 Figure A.1 Agglomerative Cluster Analysis of Sample Stations ...... 113 Figure B.1 Chromatogram of Carotenoids Present in Experimental Diets ...... 117

Chapter 1.

Introduction

As the human population grows, so does our impact on Earth’s ecosystems because of development pressures (Martinuzzi et al. 2014). Land-use change is being driven by the need to provide food, fiber, water, and shelter for over six billion people (Foley et al. 2005). Foley et al.

(2005) stressed that land-use practices worldwide are resulting in the degradation of environmental ecosystems to benefit humanity; however, this ultimately leads to the breakdown of ecosystem services. Some of the ways that humans are altering the terrestrial landscape include deforestation, subsistence agriculture, mining, and urbanization (Foley et al. 2005,

Dudgeon et al. 2006, Reid et al. 2018), while alteration of aquatic landscapes include flow modification, water extraction, and hydroelectric power generation (Dudgeon et al. 2006, Reid et al. 2018).

Freshwater ecosystems are some of the most diverse on the planet, but they are also some of the most threatened due to human activity (Kopf et al. 2015). Freshwater makes up only

0.01% of the water on earth, with habitable surface waters (rivers, lakes, reservoirs, and wetlands) covering only approximately 2% of the Earth’s surface (Lehner and Doll 2004, Kopf et al. 2015, Reid et al. 2018). Although they make up such a small amount of the Earth’s surface area, freshwater habitats are home to approximately 10% of all described species and

1 approximately 50% of the world’s fish species (Martinuzzi et al. 2014). Tropical and Subtropical freshwater systems tend to have the highest species richness worldwide, with South America,

Eastern Africa, and South-East Asia having the highest species richness (Tisseuil et al. 2013).

Unfortunately, extinctions rates of freshwater fauna are five times higher than terrestrial and three times higher than marine biota and are projected to remain high (Ricciardi and Rasmussen

1999, Reid et al. 2018). Specifically, freshwater fish extinction rates are 203 times higher than background extinction rates (Burkhead 2012). Biodiversity declines have been especially serious at tropical latitudes (Dudgeon et al. 2006). Human activity and land-use changes have been attributed to much of the threat to freshwater biodiversity (Ricciardi and Rasmussen 1999,

Dudgeon et al. 2006, Reid et al. 2018). Anthropogenic pressures on freshwater ecosystems are continuing to grow with increasing development and increased needs for domestic water-use and food production (Mekonnen and Hoekstra 2016, Reid et al. 2018), so it is important to understand how the stressors imposed by human-induced environmental change will continue to effect freshwater organisms. It is especially important to investigate how stressors affect tropical freshwater species, as these areas are not well studied (Chapman 2001, Chapman and Chapman

2001, Dudgeon et al. 2006).

Some of the major threats that global freshwater biodiversity face due to land-use changes include: chemical contamination, flow modification (e.g. channelization, impoundment, etc.), destruction or degradation of habitat, introduction and proliferation of invasive species, and increased runoff of sediments and nutrients (Allan and Flecker 1993, Dynesius and Nilsson

1994, Foley et al. 2005, Kemp et al. 2011, Reid et al. 2018). These threats can lead to reduced habitat availability, increased competition and predation from invasive species, increased

2 eutrophication and oxygen depletion, and elevated levels of turbidity (Allan and Flecker 1993,

Carpenter et al. 1998, Kemp et al. 2011). When faced with environmental disturbances, organisms have three main ways to respond in order to persist (Barrett and Hendry 2012). These include: immediate behavioral modification (i.e. moving or other behavior change), developmental alterations (i.e. phenotypic plasticity), and genetic changes to allele frequencies

(i.e. evolution) (Barrett and Hendry 2012). If populations are not able to respond through one of these three pathways, then they may face local extirpation or wide-range extinction (Barrett and

Hendry 2012).

Elevated turbidity above normal levels can cause considerable negative effects on aquatic ecosystems (Kemp et al. 2011). Elevated turbidity can be caused by both eutrophication and by an increase in sediment concentrations in the water column (Collin and Hart 2015). Some levels of suspended particulates are normal in aquatic systems and play an important part of aquatic ecosystem function (Wood and Armitage 1997, Owens et al. 2005, Kemp et al. 2011). In fact, some organisms can benefit from intermediate and short-term increases to turbidity. Some fish may experience enhanced foraging efficiency and growth if their prey are more impacted by turbidity (Gregory and Northcote 1993), while others may benefit from increased cover from predators (Gregory and Levings 1996). However, suspended sediment loads have been greatly elevated due to human impacts on river basins, such as land clearance and mining (Walling and

Fang 2003). When turbidity levels are elevated high above normal, shifts in community assemblages and food web structure have been observed (Wood and Armitage 1997, Owens et al. 2005, Kemp et al. 2011). This is especially true when aquatic systems experience chronic, long-term exposure to elevated turbidity (Kemp et al. 2011).

Turbidity can indirectly and directly affect fish through various routes. For example, by causing declines and community shifts in primary producers (Izagirre et al. 2009), zooplankton

(Hart 1992), and macroinvertebrates (Bo et al. 2007), the availability of resources can be altered.

Water quality can also be reduced due to nutrients and contaminants adhering to sediments

(Warren et al. 2003). Turbidity can also alter the underwater visual environment (van der Sluijs et al. 2011). The overall intensity of light decreases and, depending on the type of suspended particulates, the underwater light spectrum can shift from short-wavelength light (i.e. blues) to long-wavelength light (i.e. yellow-red) (Bowmaker 1995, Collin and Hart 2015). An altered visual environment can disrupt visual cues important for predator-prey interactions, foraging, male-male competition, and mate-selection (van der Sluijs et al. 2011).

The direct effects of turbidity on fish can be grouped into two main categories: sublethal and lethal effects (Newcombe and Macdonald 1991). The impact of direct effects will vary depending on many circumstances including: the concentration of particles, frequency and duration of exposure, size of particles, species and life stage, and degree of acclimation

(reviewed in Kemp et al. 2011). Sublethal impacts encompass both behavioral alterations and changes to physiology or histology which aren’t sever enough to cause mortality (Newcombe and Macdonald 1991). Shifts in behavior are an organism’s first line of defense when they are faced with stressors (Collin and Hart 2015). Elevated turbidity levels can also cause direct damage to gills through abrasion of tissues (Herbert and Merkens 1961), erosion of the mucus coating (Kemp et al. 2011), and clogging of gill rakers and filaments (Wong et al. 2013).

Physiological responses to elevated turbidity can include endocrine stress responses (elevated

4 plasma cortisol, glucose, and hematocrit levels) (Redding et al. 1987) and increased critical oxygen tension (Pcrit) (i.e. increased cost of oxygen uptake) (Gray et al. 2016).

This research aims to understand the indirect and direct effects that turbidity can have on reproductive and survival traits of a tropical, freshwater fish species, Pseudocrenilabrus multicolor victoriae. In chapter 2, we will explore the indirect effects of turbidity on diet and reproductive traits within a single population of wild P. multicolor experiencing varying levels of human disturbance. In chapter 3, we will explore the direct developmental effects of diet and chronic turbidity on reproductive traits in lab-reared, F1 P. multicolor. We will also explore the direct effects of acute and chronic turbidity on a survival trait (swimming performance) of lab- reared, F1 P. multicolor. Because freshwater extinction rates are so high, it is important to explore the effects of stressors on individual behavior and physiology. This step is critical to understand the changes we are seeing in fish population and community dynamics when faced with human-induced environmental stressors.

References

Allan J. D., and Flecker A. S. 1993. Biodiversity conservation in running waters. Bioscience 43:32-43.

Barrett R. D. H., and Hendry A. P. 2012. Evolutionary rescue under environmental change? Pages 216-233 in Candolin U., and Wong B. B. M., editors. Behavioural responses to a changing world: Mechanisms and consequences. Oxford Univ Press, New York.

Bo T., Fenoglio S., Malacarne G., Pessino M., and Sgariboldi F. 2007. Effects of clogging on stream macroinvertebrates: An experimental approach. Limnologica 37:186-192.

Bowmaker J. K. 1995. The visual pigments of fish. Progress in Retinal and Eye Research 15:1- 31.

Burkhead N. M. 2012. Extinction rates in North American freshwater fishes, 1900-2010. Bioscience 62:798-808.

Carpenter S. R., Caraco N. F., Correll D. L., Howarth R. W., Sharpley A. N., and Smith V. H. 1998. Nonpoint pollution of surface waters with phosphorus and nitrogen. Ecological Applications 8:559-568.

Chapman L. J. 2001. Fishes of African rain forests. Diverse adaptations to environmental challenges. Pages 263-290 in Weber W., White L. J. T., Vedder A., Naughton-Treves L., editors. African rain forest ecology and conservation. An interdisciplinary perspective. Yale University Press, New Haven and London.

Chapman L. J., and Chapman C. A. 2001. Tropical forest degradation and aquatic ecosystems. Our current state of knowledge. Pages 237-249 in: Collares-Pereira M. J., Cowx I. G., Coelho M. M. editors Conservation of freshwater fishes. Options for the future. Blackwell Science, Oxford, UK.

Collin S. P., and Hart N. S. 2015. Vision and photoentrainment in fishes: the effects of natural and anthropogenic perturbation. Integrative Zoology 10:15-28.

Dudgeon D., Arthington A. H., Gessner M. O., Kawabata Z. I., Knowler D. J., Leveque C., Naiman R. J., Prieur-Richard A. H., Soto D., Stiassny M. L. J., and Sullivan C. A. 2006. Freshwater biodiversity: Importance, threats, status and conservation challenges. Biological Reviews 81:163-182.

Dynesius M., and Nilsson C. 1994. Fragmentation and flow regulation of river systems in the northern 3rd of the world. Science 266:753-762.

Foley J. A., DeFries R., Asner G. P., Barford C., Bonan G., Carpenter S. R., Chapin F. S., Coe M. T., Daily G. C., Gibbs H. K., Helkowski J. H., Holloway T., Howard E. A., Kucharik C. J., Monfreda C., Patz J. A., Prentice I. C., Ramankutty N., and Snyder P. K. 2005. Global consequences of land use. Science 309:570-574.

Gray S. M., McDonnell L. H., Mandrak N. E., and Chapman L. J. 2016. Species-specific effects of turbidity on the physiology of imperiled blackline shiners Notropis spp. in the Laurentian Great Lakes. Endangered Species Research 31:271-277.

Gregory R. S., and Levings C. D. 1996. The effects of turbidity and vegetation on the risk of juvenile salmonids, Oncorhynchus spp, to predation by adult cutthroat trout, O. clarkii. Environmental Biology of Fishes 47:279-288.

Gregory R. S., and Northcote T. G. 1993. Surface, planktonic, and benthic foraging by juvenile chinook salmon (Oncorhynchus tshawytscha) in turbid laboratory conditions. Canadian Journal of Fisheries and Aquatic Sciences 50:233-240.

Hart R. C. 1992. Experimental studies of food and suspended sediment effects on growth and reproduction of 6 planktonic cladocerans. Journal of Plankton Research 14:1425-1448.

Herbert D. W. M., and Merkens J. C. 1961. The effect of suspended mineral solids on the survival of trout. International Journal of Air and Water Pollution 5:46-55.

Izagirre O., Serra A., Guasch H., and Elosegi A. 2009. Effects of sediment deposition on periphytic biomass, photosynthetic activity and algal community structure. Science of the Total Environment 407:5694-5700.

Kemp P., Sear D., Collins A., Naden P., and Jones I. 2011. The impacts of fine sediment on riverine fish. Hydrological Processes 25:1800-1821.

Kopf R. K., Finlayson C. M., Humphries P., Sims N. C., and Hladyz S. 2015. Anthropocene baselines: Assessing change and managing biodiversity in human-dominated aquatic ecosystems. Bioscience 65:798-811.

Lehner B., and Doll P. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. Journal of Hydrology 296:1-22.

Martinuzzi S., Januchowski-Hartley S. R., Pracheil B. M., McIntyre P. B., Plantinga A. J., Lewis D. J., and Radeloff V. C. 2014. Threats and opportunities for freshwater conservation under future land use change scenarios in the United States. Global Change Biology 20:113-124.

Mekonnen M. M., and Hoekstra A. Y. 2016. Four billion people facing severe water scarcity. Science Advances 2:e1500323. 7

Newcombe C. P., and Macdonald D. D. 1991. Effects of suspended sediments on aquatic ecosystems. North American Journal of Fisheries Management 11:72-82.

Owens P. N., Batalla R. J., Collins A. J., Gomez B., Hicks D. M., Horowitz A. J., Kondolf G. M., Marden M., Page M. J., Peacock D. H., Petticrew E. L., Salomons W., and Trustrum N. A. 2005. Fine-grained sediment in river systems: Environmental significance and management issues. River Research and Applications 21:693-717.

Redding J. M., Schreck C. B, and Everest F. H. 1987. Physiological effects on coho salmon and steelhead of exposure to suspended solids. Transactions of the American Fisheries Society 116:737-744.

Reid A. J., Carlson A. K., Creed I. F., Eliason E. J., Gell P. A., Johnson P. T. J., Kidd K. A., MacCormack T. J., Olden J. D., Ormerod S. J., Smol J. P., Taylor W. W., Tockner K., Vermaire J. C., Dudgeon D., and Cooke S. J. 2018. Emerging threats and persistent conservation challenges for freshwater biodiversity. Biological Reviews brv.12480.

Ricciardi A., and Rasmussen J. B. 1999. Extinction rates of North American freshwater fauna. Conservation Biology 13:1220-1222.

Tisseuil C., Cornu J. F., Beauchard O., Brosse S., Darwall W., Holland R., Hugueny B., Tedesco P. A., and Oberdorff T. 2013. Global diversity patterns and cross-taxa convergence in freshwater systems. Journal of Animal Ecology 82:365-376. van der Sluijs I., Gray S. M., Amorim M. C. P., Barber I., Candolin U., Hendry A. P., Krahe R., Maan M. E., Utne-Palm A. C., Wagner H.J., and Wong B. B. M. 2011. Communication in troubled waters: Responses of fish communication systems to changing environments. Evolutionary Ecology 25:623-640.

Walling D. E., and Fang D. 2003. Recent trends in the suspended sediment loads of the world's rivers. Global and Planetary Change 39:111-126.

Warren N., Allan I. J., Carter J. E., House W. A., and Parker A. 2003. Pesticides and other micro-organic contaminants in freshwater sedimentary environments - a review. Applied Geochemistry 18:159-194.

Wong C. K., Pak I. A. P., and Liu X. J. 2013. Gill damage to juvenile orange-spotted grouper I (Hamilton, 1822) following exposure to suspended sediments. Aquaculture Research 44:1685-1695.

Wood P. J., and Armitage P. D. 1997. Biological effects of fine sediment in the lotic environment. Environmental Management 21:203-217.

Chapter 2

Turbidity as an environmental driver of within-population variation in diet and nuptial coloration of an African cichlid fish

Abstract

Human activities are drastically altering natural ecosystems and causing variability at large and small spatial scales. Human-altered environments can favor adaptive trait change and persistence in some species, while changes can be maladaptive in other species. Plastic phenotypic shifts are often among the first compensatory responses of animals to human disturbance. Elevated turbidity is among one of the most harmful stressors to aquatic systems and is often caused by human activity. When turbidity is elevated above normal, it alters the sensory environment of fishes and can disrupt communications, including mate-choice. Many fish species have been found to use carotenoid coloration (red and yellow) displays when choosing a mate to optimize fitness, but are unable to synthesize carotenoids, so they depend on dietary uptake for their carotenoid supply. However, different prey items can contain differing levels of carotenoid content, so dietary content could play are large role in carotenoid display.

Using the cichlid fish, Pseudocrenilabrus multicolor victoriae, as our focal species, we aimed to determine if there was within-population variation in fish diet and male nuptial coloration at a site that experiences varying levels of turbidity within different microhabitats. Our results suggest that there was relatively high overlap in diet across turbidity levels, but that plant/algae material was more important in the diet of fish from low turbidity conditions. We also found that fish from low turbidity conditions displayed significantly more carotenoid coloration than fish 9 from high turbidity conditions, and that standard length positively influenced carotenoid coloration irrespective of turbidity regime. Because of previous research that demonstrates high levels of within-population plasticity in P. multicolor, and because of high dietary overlap, we may be observing within-population variation of nuptial coloration due to differing turbidity regimes.

1. Introduction

When faced with rapid and severe environmental change, we expect animals to respond by dispersing and/or adapting plastically or genetically (Stockwell et al. 2003). Plastic responses are likely crucial for organisms faced with anthropogenic disturbances and often represents the first compensatory response to the new conditions (Hendry et al. 2008). Human-altered environments can favor adaptive trait change and persistence in some species, while changes can be maladaptive in others (Barrett and Hendry 2012). For example, the neotropical lizard, Anolis cristatellus, developed longer limbs, relative to body size, and more subdigital scales in urban environments. These adaptations allow the lizards better locomotion on broad, smooth surfaces found more readily in urban environments vs. forest environments (Winchell et al. 2016).

Alternatively, when faced with eutrophication and increased algal growth, three-spined stickleback, Gasterosteus aculeatus, males spent more time intensely courting females. The authors argue that this is a maladaptive behavioral adjustment, because courtship is time and energy intensive and did not enhance attractiveness of the males to females (Candolin et al.

2007). Ultimately, maladaptive responses are expected to lead to population declines and extirpation, while adaptive plastic and genetic trait change could promote persistence under anthropogenic change (reviewed in Crispo et al. 2010a, Ghalambor et al. 2007). Further, initial plastic responses under novel conditions can lead to adaptive genetic change (Ghalambor et al.

2007, West-Eberhard 2003). West-Eberhard (2003) argues for this “genes as followers” concept, because environmental change immediately affects many individuals at once, while a mutation only occurs in one individual. The widespread introduction of a stressor can increase the chance that a plastic response in some individuals will be advantageous (West-Eberhard 2003). While there is growing evidence for trait change associated with anthropogenically-disrupted environments across wild populations at large spatial-scales (e.g., Lorenzon et al. 2001, McNeil et al. 2016, Winchell et al. 2016), there are still knowledge gaps in our understanding of responses to rapid human-induced environmental change at finer, microgeographic spatial- scales, within wild populations.

Freshwater ecosystems are among the most diverse in the world per unit habitat area

(Kopf et al. 2015). However, with freshwater animals having extinction rates approximately five times greater than terrestrial animals and three times greater than marine animals (Ricciardi and

Rasmussen 1999, Kopf et al. 2015, Reid et al. 2018), they are also considered among the most threatened ecosystems on Earth (Dudgeon et al. 2006, Reid et al. 2018). Freshwater biodiversity declines have been linked to habitat degradation resulting from changes in, for example, siltation, sedimentation, deforestation, and drainage of wetlands for agricultural purposes (Dudgeon et al.

2006, Kemp et al. 2011, Reid et al. 2018). As biodiversity decreases globally, emphasis has been placed on understanding the mechanisms leading to species declines and how human-induced environmental change influences these mechanisms (Mrosso et al. 2005).

Elevated turbidity is among the most deleterious stressors on aquatic systems (Kemp et al. 2011), likely due to both direct and indirect effects of suspended particulates on aquatic organisms. Direct impacts include suffocating of benthic organisms and eggs, abrasion of sensitive gill structures, decreased respiratory capacity, and declines in growth rate (reviewed in

Gray et al. 2016). One indirect effect of turbidity is the alteration of the underwater visual landscape. Under clear conditions (i.e. low turbidity), as light travels deeper into the water column it shifts towards short wavelength light (blues-greens) (Levine and MacNichol 1982).

However, suspended particles (e.g. sediments, algal cells) absorb and scatter photons, resulting in rapid attenuation of light (decreased light intensity with depth) and a potential shift in the color of light underwater (van der Sluijs et al. 2011). Differential absorption and scattering of light results in shorter wavelength light (e.g. UV to blue) scattering more than longer wavelength light (e.g. yellows-reds) (Levine and MacNichol 1982). In the presence of algal or sedimentary turbidity, light therefore shifts towards long wavelength light (yellows-reds) more rapidly through the water column (Levine and MacNichol 1982). While grey sediments have been found to decrease the overall intensity of underwater light without significant shifts in spectral content

(Nieman et al. 2018), organic materials and red-brown sediments (e.g. iron-rich, tropical soils;

Radwanski 1960) tend to change the color of transmitted light to longer wavelengths, causing a redder hue (Levine and MacNichol 1982, Han 1997). Light scattering can also greatly reduce the contrast of objects in water and limit the distance at which objects, such as prey and mates, can be detected (Lythgoe 1979). Therefore, the reduction in light intensity and altered spectral composition of light underwater caused by turbidity is expected to alter the way fishes receive and send visual signals (van der Sluijs et al. 2011, Collin and Hart 2015). This may require compensatory responses to maintain adequate contrast and color signaling (e.g. increased strength of visual signals; Dugas and Franssen 2011) and perception (e.g. changes in visual sensitivity; Carleton 2009).

Understanding how human-induced environmental changes to the sensory environment affect signaling and signal reception is essential given the key role the sensory landscape plays in

12 survival and reproduction (Sih et al. 2011, van der Sluijs et al. 2011, Madliger 2012). Signals become harder to perceive through an increasingly noisy environment; thus masking of visual signals under turbid conditions can inhibit visual reception (van der Sluijs et al. 2011). For example, cultural eutrophication (i.e. increased algal turbidity) in East Africa’s Lake Victoria is thought to have contributed to hybridization of closely related species due to the masking of male nuptial color cues (Seehausen 1997). In clear waters, and without geographic isolation,

Seehausen et al. (2008) consistently found two differentiated species of the closely related Lake

Victoria cichlids Pundamilia pundamilia and P. nyererei based on water depth, long- wavelength-sensitive opsin genes (LWS alleles λmax ~565 nm), coloration, and female mate- preference. However, under turbid conditions, where steep light gradients were formed due to the rapid, shallow attenuation of light, they found single, panmictic populations with very little variation in LWS alleles. The different sensory environments produced by the absence or presence of high turbidity likely led to differential selection pressures on the LWS opsin gene – steep light gradients, in turbid waters, reduced selection on LWS alleles. Seehausen et al. (2008) suggest variation in the strength of selection across light gradients as a possible contributing mechanism for the collapse of cichlid diversity in Lake Victoria.

Colorful sexual signals often include long wavelength (yellow and red) pigments. Red, orange, and yellow coloration in animals is mostly caused by carotenoid-based pigments (Olson and Owens 1998, Leclercq et al. 2010, Pike et al. 2011, Svensson and Wong 2011, Sefc et al.

2014). Carotenoid displays are used by animals for a multitude of reasons, including camouflage, warning coloration, species recognition, and aggression (Svensson and Wong 2011), and are used for sexual selection in organisms such as birds and fishes. (Crozier 1974, Blount 2004).

These sexual signals are extremely important because they are thought to provide crucial

13 information about the quality of the signaling male (Michelangeli et al. 2015). For example,

Simons et al. (2012) found that male zebra finches, Taeniopygia guttata, with redder bills had higher survival rates than those with less saturated bill coloration. Additionally, Nicoletto and

Kodric-Brown (1999) found that male guppies with higher display rates, ornament complexity, and area of orange coloration could maintain higher sustained swimming speeds, which is often correlated with health and endurance.

Vertebrates are unable to synthesize carotenoid pigments and thus rely on dietary acquisition of carotenoids (Svensson and Wong 2011). Since carotenoids are therefore a limited resource, diet is expected to play a large role in carotenoid-based mating displays. Photosynthetic organisms can synthesize carotenoid pigments, therefore diets high in plants and algae have higher carotenoid concentrations than diets high in, for example, insect and fish materials (Olson

2006). In addition to colorful visual signals, carotenoids are also strong antioxidants, aid in immune defense and wound healing, help with vision development, and play a role in embryo development (Olson and Owens 1998, Blount 2004, Leclercq et al. 2010, Svensson and Wong

2011, Sefc et al. 2014). Thus, a trade-off between costly color displays and other physiological functions is expected: fish that display more saturated colors are thought to be in better overall condition, because they are able to allocate carotenoids for signaling purposes as opposed to using them for immune responses (Olson and Owens 1998, Blount 2004, Rahman et al. 2013,

Sefc et al. 2014).

We know human-induced environmental changes can alter the sensory environment of fishes, thus it is critical to understand the consequences of this for sexual selection and reproduction (van der Sluijs et al. 2011). Costly carotenoid-based color displays can be affected by physiological stress, such as elevated turbidity, if carotenoids are needed, for example, in an

14 immune response triggered by degraded water quality (Bortolotti et al. 2009). The intensity of courtship displays and sexual ornamentation is known to decrease as turbidity levels increase, leading to relaxed or dishonest signals (Seehausen 1997, Järvenpää and Lindström 2004,

Candolin et al. 2007, Wong et al. 2007). For example, Candolin et al. (2016) found that algal turbidity (cultural eutrophication) reduced the perceived difference in red coloration between paired, male three-spined stickleback likely resulting in relaxed male-male competition and dishonest signals of male quality in turbid conditions. In this case, however, Candolin et al.

(2016) found evidence of population increases, suggesting some beneficial trade-off in reduced sexual selection for three-spined sticklebacks. Dishonest signals can relax vision-based, sexual selection and potentially interfere with reproductive isolation between fish species and color morphs (Collin and Hart 2015). This could lead to hybridization and loss of species diversity if females mate indiscriminately in turbid conditions (Järvenpää and Lindström 2004, Witte et al.

2013).

African cichlids are a model for understanding sexual selection largely due to the prevalence of sexual dimorphism; in many cases, females use male nuptial coloration to choose mates (Kocher 2004). Some female cichlids, and a suite of other taxa (Olson and Owens 1998,

Blount and McGraw 2008), specifically use carotenoid-based male coloration (i.e. red and yellow pigments) to determine fitness of prospective mates. Females tend to prefer males with more saturated, red coloration (a trait found to be positively correlated with fitness) over males with duller, red coloration (Sefc et al. 2014). The haplochromine cichlid, Pseudocrenilabrus multicolor victoriae (Seegers 1990), is a sexually dimorphic, maternal mouth-brooding cichlid endemic to the Nile River basin of East Africa. Males display intense red-yellow body coloration laterally and ventrally, with a red spot on their anal fin, while females are grey in color and

15 smaller in size. Pseudocrenilabrus multicolor is widespread, found across divergent environments with different selection pressures, and is known to be plastically and genetically divergent in a number of traits (Chapman et al. 2008, Crispo and Chapman 2010, McNeil et al.

2016). Variation has been found across populations with respect to morphology, coloration, diet, and behavior (Chapman et al. 2000, McNeil et al. 2016, Oldham et al. 2018). Fish from swamp environments (stable environments with naturally low dissolved oxygen, low turbidity, and tannin-stained water) tend to have smaller brains, larger gills (Chapman et al. 2000, Chapman et al. 2008, Crispo and Chapman 2010), are redder in coloration (McNeil et al. 2016), have reduced metabolic rate (Reardon and Chapman 2010), and demonstrate fewer reproductive behaviors

(McNeil et al. 2016) relative to stream populations (variable environments with high oxygen, high turbidity) that are intensely impacted by human-alteration of the landscape. McNeil et al.

(2016) also found differences in diet across populations of P. multicolor, with approximately

58% diet overlap between swamp and river/lake populations. Given the extent of phenotypic and behavioral divergence previously found between P. multicolor populations, we may also expect divergence across similar environmental gradients at a microgeographic spatial-scale within a single population. Variation within a single population has been documented in other species such as the island scrub-jay (Aphelocoma insularis), which is endemic to a 250 km2 island; despite being a mobile taxonomic group, Langin et al. (2015) found evidence of adaptive differentiation in bill morphology and genetic discontinuities associated with a heterogeneous environmental gradient of pine and oak trees.

Our objective was to determine if elevated turbidity, caused by anthropogenic disturbance, elicits behavioral and phenotypic responses with respect to diet and male nuptial coloration, within a single population of wild P. multicolor. We predicted that fish found in low

16 turbidity waters would have more saturated red and yellow coloration and a diet higher in carotenoid content, while fish caught in high turbidity waters would have less saturated red and yellow coloration and a diet lower in carotenoid content. Alternatively, we could also observe variation in coloration without differences in diet, or differences in diet without variation in coloration.

2. Materials and Methods

2.1 Study system

We studied a single population of P. multicolor from the Lake Victoria basin near Lake

Nabugabo, a satellite lake of Lake Victoria in Uganda, East Africa. This region of Uganda includes dense papyrus (Cyperus papyrus) swamps, intensive agriculture, and remnant forests.

Our focal site was approximately 0.14 km2 and is located within the proposed Lake Nabugabo

Ramsar Site expansion (The Republic of Uganda 2017) near the town of Masaka, Uganda; however, it is heavily altered in a number of ways. Water flows through agriculture lands, a remnant forest patch, a papyrus-dominated swamp, and a portion of stream that is spring-fed

(Fig. 2.1). The entire study system is connected hydrologically, especially during the wet season; therefore, we consider it to be an open system with one population of P. multicolor. Previous research by Crispo and Chapman (2010b) demonstrated high gene flow between populations that are isolated by tens of kilometers in distance. Our study area has been extensively disturbed with modifications to hydrology, through draining of the wetlands, conversion to agriculture, and construction of channelized drainage ditches. The ditches are periodically dredged by local farmers to maintain adequate flow-through to avoid crop flooding (TLA; personal observation).

Additionally, slash-and-burn agricultural methods have been observed nearby, which can also affect water quality by greatly contributing to soil erosion (Blanco-Canqui and Lal 2010,

Misbahuzzaman 2016). The study area therefore represents a site disturbed by multiple human activities and contains a fish population experiencing a variety of environmental stressors that vary over a small spatial scale.

2.2 Field sampling

To determine the influence of turbidity on diet and reproductive traits in P. multicolor, we collected wild adult fish (n = 331) between the months June-August in 2016 and 2017. A total of 12 stations (at least 50 m apart) were sampled from three distinct areas of the site: agriculture, forest remnant/swamp, and spring-fed areas (Fig. 2.1). Each station was sampled multiple times per season, but not all locations were sampled during both sampling years. During each sampling period, a suite of environmental measurements was taken in triplicate, including point-in-time turbidity (NTU), dissolved oxygen (mg/L), temperature (˚C), conductivity (µs/cm), and chlorophyll-a (ppb). Water samples for turbidity and chlorophyll-a measurements were collected on-site and transported to the Lake Nabugabo Research Station for analyses using a

LaMotte 2020we Turbidity Meter and an Amiscience FluorQuik Fluorometer, respectively. All other water quality measurements were taken on-site using a Pro 2030 YSI portable handheld unit. We also collected one replicate per sample station of macroinvertebrate samples (n = 9) in

2017 to determine if prey availability varied with turbidity. The sampling methodology was modified from (Uzarski et al. 2017): twelve 0.5 m sweeps/station (6 benthic sweeps and 6 vegetative sweeps) were collected with a 30 cm d-frame net with 0.5 mm mesh size. Once collected, invertebrate samples were transferred to a white tray for sorting. Invertebrates were picked from the debris either until 150 organisms were collected or until 30 minutes passed. If 30 minutes was reached and 150 organisms had not been reached, additional macroinvertebrates were picked until the next multiple of 50 was obtained. After collection, invertebrates were

18 preserved in 70% ethanol. Preserved macroinvertebrate communities were identified to order- level resolution using a standard taxonomic key (Merritt and Cummins 1978).

Fish were caught using 6.4 mm-mesh minnow traps set for approximately two hours.

Upon capture, fish were photographed with a Canon G16 Powershot camera in a Plexiglas photo cuvette with a grey background and white standard for color analysis (following Maan et al.

2004). After being photographed, standard and total length (cm) and weight (g) were recorded, and fish were euthanized using a mixture of 2 ml clove oil solution (1:10 eugenol:ethanol) and

500 ml water. Fish abdominal cavities were injected with 10% buffered formalin to stop the digestion process (Binning and Chapman 2008). Whole fish specimens were fixed in 10% buffered formalin for stomach content analysis.

2.3 Diet analysis

The stomachs from a subsample of preserved specimens (male and female) were dissected (with esophagus, intestines, and fat bodies removed) (n = 92). Modified from Ball

(1961), stomachs were visually assigned a fullness category by three people: empty, ¼ full, ½ full, ¾ full, and completely full, and an average fullness was calculated for each stomach.

Stomach contents were identified to order-level resolution and grouped into categories that rank from high to low carotenoid concentrations (Olson 2006): plants/algae, insects, and fish, with an additional category ‘varia’ used to include debris and unidentified materials (McNeil et al. 2016).

Using the points method (reviewed in Hyslop 1980), each prey category was given a relative abundance percentage which was rounded to the nearest 10%. Next, the relative abundance of each prey category was multiplied by stomach fullness of the specimen, yielding the relative volume of each prey category, to account for importance of prey in stomachs of differing

19 fullness. This allowed us to analyze both the relative abundance (composition) and relative volume (importance) of prey categories.

2.4 Color analysis

Photos were analyzed using a standard color analysis technique (Maan et al. 2004) to determine the amount of red and yellow coloration displayed by male P. multicolor (n = 195).

First, fish photos were uploaded into Adobe Photoshop, where the white standard in each photo was used to balance brightness, holding it constant across photos. Next, the body of the fish was cropped out, excluding the fins and eyes due to different reflectance properties. Cropped photos were analyzed using a script (developed by Logan James) written for the statistical program R (R

Core Team 2018). The script calculates the total number of pixels in the body of the fish, the proportion of red pixels (proportion red = total red pixels/total pixels), and the proportion of yellow pixels (proportion yellow = total yellow pixels/total pixels). The analyses are based on a set of threshold color criteria using the RGB color scale; values used included red: hue = 0-26 plus 232-255 and yellow: hue = 27-45 (Maan et al. 2004). Since we were interested in assessing overall carotenoid coloration of male fish, we calculated the sum of proportion red + proportion yellow and used this metric (referred to as total carotenoid coloration) to test if the saturation of carotenoid-based coloration was associated with turbidity level at the station of capture.

2.5 Statistical analyses

All statistical analyses were completed using R 3.4.4 (R Core Team, 2018).

2.5.1 Environment

We used the vegan package to assign stations to general categories based on environmental variables (i.e. turbidity, dissolved oxygen, temperature) (Oksanen et al. 2018).

Using agglomerative cluster analysis with Euclidean distance and a Ward’s-linkage method, we

20 defined two distinct groups: spring-fed stations were grouped together as one group and agriculture and forest/swamp stations grouping together into another (see Appendix A, Fig. A.1).

To determine if male coloration was correlated with different environmental variables, we investigated if both turbidity and temperature differed across station-types (earlier research from

McNeil et al. (2016) determined that oxygen levels did not affect male coloration, so it was not included in our analyses). To determine if turbidity and temperature differed across these station- types, we used a non-parametric Kruskal Wallis Rank Sum Test with a Dunn’s Test for Multiple

Comparisons and a Bonferroni-adjusted p-value (to reduce type I error), because the data were uneven and did not meet normality assumptions.

2.5.2 Invertebrate community and diet

To examine if station-available macroinvertebrate communities varied with turbidity, we used multi-response permutation procedures (MRPP) with normalized community data and

Euclidean distance measures using the vegan package (Oksanen et al. 2018). MRPP is a multivariate, nonparametric test of differences between two or more pre-defined groups. It is common in community data analyses because it does not make assumptions about normality and homogeneity of variance, which community data often do not meet (McCune and Grace 2002).

To determine if there were overlaps in diet across high and low turbidity sample stations, similarity of diets was analyzed using Percent Similarity Index (PSI) (Schoener 1970) using the equation:

1 푃푆퐼 = 1 − (∑ |푝 − 푝 |) 2 푥푖 푦푖 where p represents the proportion of prey category “i” in fish from high (x) and low (y) turbidity stations. We analyzed both the relative abundance and relative volume of prey categories between high and low turbidity stations. Proportion data was analyzed using Generalized

Additive Models for Location, Scale, and Shape with a zero-one-inflated beta distribution

(relative abundance) and a zero-inflated beta distribution (relative volume), using the R package gamlss (Rigby and Stasinopoulos 2005), due to a large number of zeros in the data. We also used a Wilcoxon Signed-Rank Test to determine if there was a difference in stomach fullness between high and low turbidity stations.

2.5.3 Male carotenoid-based coloration

We tested if male coloration varied across station-type (low or high turbidity) using a

Linear Mixed-Model (LMM) with a Gaussian distribution using the lme4 package (Bates et al.

2015). The dependent variable, total carotenoid coloration (proportion red + proportion yellow), was arcsine transformed to remove skew and improve normality. Station nested within year was used as a random factor to account for stations being sampled multiple times per season and differences in stations being sampled across years. We used Akaike Information Criterion (AIC) for model selection to determine independent variables to include in the LMM (see Appendix A,

Table A.1). Independent variables considered for model selection included turbidity (two levels: high and low), temperature (three levels: high, medium, low), and fish standard length. Models chosen for analyses had a delta AIC of less than 2 (Symonds and Moussalli 2011). Additionally, we used the MuMIn package (Barton 2018) to calculate both marginal and conditional R2 values

(R2m and R2c, respectively) of the top model. LMMs were also used to determine if there was a difference in fish standard length across turbidity levels with the same random variable (station nested within year).

3. Results

3.1 Environment

Cluster analysis sorted the 12 sample stations into two separate groups (see Appendix A,

Fig. A.1), with all agriculture and forest/swamp stations being grouped together (n = 9) and 22

2 spring-fed stations grouped together (n = 3). We found a significant difference in turbidity (χ 2 =

2 78.304, p < 0.001) and temperature (χ 2 = 63.551, p < 0.001) across the three areas of the site.

Pairwise comparisons (Dunn’s) showed that turbidity at agriculture (mean ± SE = 16.75 ± 0.47

NTU, n=4) and forest (17.02 ± 0.61 NTU, n = 5) stations was significantly higher than at spring- fed stations (5.63 ± 0.47 NTU, n = 3), with no difference in turbidity between agriculture and forest stations (Fig. 2.2a; see Appendix A, Table A.2). Similar comparisons showed that there was a significant difference in temperature between all three regions of the site with the highest temperatures at spring stations (21.27 ± 0.11 ˚C), medium temperatures at agriculture stations

(19.85 ± 0.14 ˚C), and lowest temperatures at forest stations (19.19 ± 0.11 ˚C), (Fig. 2.2b; see

Appendix A, Table A.2).

3.2 Invertebrate community and diet

We determined there was no significant difference in macroinvertebrate communities

(identified to order) across high (n = 6) and low (n = 3) turbidity stations (delta = 0.348, A =

0.019, p = 0.191; see Appendix Table A.3). Relative prey abundance in fish diets (Fig. 2.3a; see

Appendix A, Table A.4), significantly differed for plants and invertebrates between high and low turbidity stations, with low turbidity stations having significantly more plant material (t5,87 =

6.132, p < 0.001), and significantly less invertebrate material (t5,87 = -1.986, p = 0.050) in their diet than high turbidity stations. There was no significant difference in the relative abundance of fish or varia in diets between high and low turbidity stations (fish: t5,87 = -1.389, p = 0.168; varia: t5,87 = 0.818, p = 0.416). Only plant material differed between high and low turbidity when we considered relative prey volume (Fig. 2.3b; See Appendix A, Table A.5), with low turbidity stations having significantly more plant material (t4,88 = 6.888, p < 0.001) in their diet than high turbidity stations. Again, there was no difference in the relative volume of invertebrates, fish, or

23 varia between high and low turbidity stations (Fig. 2.3b; See Appendix A, Table A.5). We also found no significant difference in stomach fullness between high and low turbidity stations (high turbidity: 3.04 ± 0.12, low turbidity: 3.07 ± 0.17; W = 851, p = 0.822). Based on relative prey abundance there was 49.7% similarity between the stomach contents of high and low turbidity stations, while PSI based on relative prey volume was higher at 73.2%.

3.3 Male carotenoid-based coloration

AIC model selection revealed that the additive model containing turbidity and fish standard length as independent variables was the best predictor of male P. multicolor carotenoid coloration, when using station nested within year as a random effect. Only models with ΔAICc scores of less than 2 were considered top models for analyses (Symonds and Moussalli 2011).

The second-best model (the interaction between turbidity and standard length) had a ΔAICc score of 5.42 and was not considered a top model or used during analyses (see Appendix A,

Table A.1). LMM revealed that both turbidity and standard length were significant predictors of male carotenoid coloration (turbidity: F14.5 = 5.293, P = 0.037; standard length: F192 = 250.637, P

< 0.001). Males from low turbidity stations displayed a significantly higher proportion of carotenoid coloration than males from high turbidity stations (low turbidity: 0.491 ± 0.022; high turbidity: 0.368 ± 0.015) (Fig. 2.4a). Total carotenoid coloration was positively associated with standard length at both high and low turbidity stations, meaning that as standard length increased, so did total carotenoid coloration (Fig. 2.4b). The variance in male total carotenoid coloration explained by turbidity and fish standard length was calculated as R2m = 0.60. When adding random effects to the model (station nested within year), the variance only increased by

0.09 (R2c = 0.69), revealing that turbidity and standard length comprise most of the variation in the model, but that the random effects also contribute a small amount to the variation. LMMs

24 also showed no significant difference in standard length (t14.1 = 0.504, p= 0.622) between high and low turbidity stations (high turbidity: 4.90 ± 0.07 cm; low turbidity: 5.18 ± 0.17 cm) (Fig.

2.4c).

4. Discussion

It is critical for animals to respond adaptively in the face of anthropogenic disturbances to avoid population declines and extirpation or extinction (Ghalambor et al. 2007). Because freshwater ecosystems are extremely threatened by anthropogenic activity (Ricciardi and

Rasmussen 1999, Kopf et al. 2015, Reid et al. 2018), it is important to understand how aquatic organisms are responding when faced with such disturbances on both large and small spatial scales. Despite relatively high dietary overlap, and no evidence for differences in prey availability, we found variation in male nuptial coloration within a single population of P. multicolor that experiences habitat heterogeneity due to human alteration of the environment.

This indicates that we can observe variation in ecological traits on small spatial scales when disturbances are present within different microhabitats. Below we explore the possibility of plastic adaptive responses and other possible driving mechanisms for the observed differences in diet and male nuptial coloration at a microgeographic scale.

4.1 Invertebrate community and diet

We found evidence that turbidity did not influence the invertebrate community (at order level resolution) between high and low turbidity stations. This is unlike previous research which demonstrated that turbidity reduced macroinvertebrate richness (Evans-White et al. 2009) and, at very high levels, decreased macroinvertebrate diversity (Phillips et al. 2016). A possible explanation for these contrasting results is that identifying organism to order was too coarse of a measurement to observe differences in macroinvertebrate communities between our sample stations; both Evans-White et al. (2009) and Phillips et al. (2016) identified organisms to lowest 25 taxon (usually genus or species). Alternatively, it is possible that the differences in turbidity level experienced between our sample stations were not extreme enough, or perhaps stable enough, to alter the composition of macroinvertebrate communities (low turbidity stations: range = 1.62 -

14.10 NTU; high turbidity stations: range = 7.25 - 31.20 NTU). Phillips et al. (2016) did not find a decrease in diversity until approximately 60 NTU which is well above our highest measured turbidity level in the field. Additionally, it is also important to note that the variation in spatial scales between studies could be driving these conflicting results. In comparison, Evans-White et al. (2009) studied sites across three U.S. states - Kansas, Nebraska, and Missouri representing approximately 600,000 km2, and Phillips et al. (2016) studied sites across a 600 km stretch on the Canadian Qu’Appelle River. Our sample stations were all within 0.14 km2. Due to macroinvertebrate dispersal abilities and the hydrological connections across the small spatial scale of our study, it may not be possible to detect variation in macroinvertebrate communities.

Even though prey availability did not differ among stations, the diet consumed by fish differed between high and low turbidity stations, based on point-in-time stomach content analyses. Fish from low turbidity conditions had more plant/algae material in their stomachs than fish from high turbidity conditions, and the stomachs of fish from high turbidity conditions contained more insect material than fish from low turbidity conditions based on relative abundance. We also found that the relative abundance of prey items between high and low turbidity stations only overlapped by 50%. This provides evidence that fish from high and low turbidity conditions are consuming significantly different diets. However, this only addresses the composition of food items being eaten by fish relative to other prey categories. Since it does not take into consideration the volume of the prey categories relative to stomach capacity, it does not fully address the importance of the prey categories in the diet of the fish (Hyslop 1980). In our

26 evaluation of the importance of prey items (i.e. relative volume) between high and low turbidity conditions, we found that plants/algae took up significantly more stomach volume of low turbidity fish. Additionally, there was an overlap in diet of 73%. These results suggest that plants/algae were more important in the diets of low turbidity fish, but that overall there is relatively high overlap in the importance of all prey categories between high and low turbidity stations. This is significant because plants and algae are photosynthetic and can synthesize carotenoids, making them much higher in carotenoid content than other prey categories (Olson

2006).

Of the possible mechanisms that could explain these differences in diet, two stand out as most likely: 1) elevated turbidity could be eliciting a behavioral response in P. multicolor, causing fish to search out other food items besides plants (behavioral plasticity), or 2) there is more primary productivity under clear conditions (Ryan 1991, Berry et al. 2003, Izagirre et al.

2009) and so there is a higher proportion of plant/algae material readily available compared to other prey items. Grether et al. (2001) found that increased canopy cover (or a decrease in light availability) decreased the biomass of available algae, shifted algal community composition, shifted nutritional values of available algal communities, and constrained growth in guppies

(Poecilia reticulata). Evidence also shows that some fish will alter their diets under different habitat conditions; for example, Shoup and Wahl (2009) found that largemouth bass

(Micropterus salmoides) preferentially selected different prey items under varying turbidity regimes; specifically, they consumed less northern crayfish (Orconectes virilis) and gizzard shad

(Dorosoma cepedianum) and more bluegill (Lepomis macrochirus) at higher levels of turbidity

(~60 NTU). More field research, including surveys of plant/algae and larval fish biomass, to assess availability of all prey items across station conditions is needed to address this

27 uncertainty. Additionally, while our point-in-time diet analysis provides an initial indication of diet preferences across environmental conditions at the time of sampling, stable isotope analysis may better address the long-term diet composition and importance of different prey items for P. multicolor (Gu et al. 1997)

4.2 Male carotenoid-based coloration

Despite finding relatively high dietary overlap in prey importance between turbidity regimes, our study provides evidence that male P. multicolor show variation in nuptial coloration across environmental conditions at a microgeographic scale. In general, this result mirrors the population-level color investigation by McNeil et al. (2016) which found evidence of divergent nuptial coloration in P. multicolor associated with contrasting environmental conditions (high and low dissolved oxygen and turbidity) at larger spatial scales and across multiple populations.

Specifically, their study found that fish from high turbidity and high oxygen river habitats displayed more yellow coloration, while fish from low turbidity and low oxygen swamp environments displayed more red coloration. Similarly, we found that that fish from low turbidity conditions expressed more overall carotenoid coloration (or total red and yellow coloration) than those captured at high turbidity stations. Because our study found relatively high dietary similarity across environmental conditions, we can infer that turbidity played a larger role in the variation of male nuptial coloration than diet, but we did not directly test this.

If turbidity is the key driver of the observed differences in carotenoid coloration, then the altered light environment could be the possible driver of color variation. Males could be adjusting coloration to optimize contrast with the surrounding water to better facilitate mate- choice with females (phenotypic plasticity), which has previously been observed among closely related cichlid species (Maan et al. 2006). Alternatively, our findings could be evidence of

28 matching habitat choice which occurs when organisms move to habitats where they are better adapted (Ravigne et al. 2004), or in this situation where fish contrast with their surroundings better in a mating context. In the case of matching habitat choice, phenotype is held constant and individuals actively seek environments in which their phenotype functions best to increase overall fitness (Edelaar et al. 2008). Edelaar et al. (2008) argues that matching habitat choice can cause clusters of phenotypically similar individuals with environmentally favored ecological traits, which could ultimately lead to local adaptation.

There is extensive empirical evidence that P. multicolor demonstrates a great deal of trait plasticity between and within populations when faced with a variety of environmental stressors

(Chapman et al. 2000, Chapman et al. 2008, McNeil et al. 2016, Oldham et al. 2018). For example, Crispo and Chapman (2010a) found high phenotypic plasticity in the size of gills and brains within multiple populations of P. multicolor based on a lab rearing study. Overall, they found that fish reared in low dissolved oxygen conditions exhibited larger gills and smaller brains than fish reared under high dissolved oxygen. Additionally, a common garden rearing experiment conducted on P. multicolor found that F1s from a river population (i.e. fluctuating environments with elevated turbidity) exhibited more between-individual variance of behavioral traits (boldness and general activity) than F1, swamp population fish (i.e. stable environment)

(Oldham et al. 2018). This suggests that fish from variable, turbid habitats display more plasticity in behavioral responses than fish that historically experience more environmental homogeneity. Many aquatic systems can experience environmental heterogeneity over spatial and temporal scales, especially when faced with human disturbance, and there is a growing body of evidence that variable environments can select for greater plasticity in ecological traits

(Murren et al. 2015, Hendry 2016, Edelaar et al. 2017). Due to prior evidence of within-

29 population phenotypic plasticity in P. multicolor, and because the study population used here is from a variable environment, there is a possibility that the variation we observed in male coloration across turbidity zones represents a plastic response to human-induced habitat disturbance. However, the nature of our field study does not allow us to directly test for plasticity.

There is also a possibility that fish across turbidity regimes are expressing differences in carotenoid coloration due to the small differences we found in diet. Although there was relatively high overlap (73%) in diet across turbidity levels, we found evidence that plant/algae material was a more important prey category for fish from low turbidity stations. The increase in carotenoid display in fish from clear conditions could, therefore, be a function of a diet higher in carotenoid content; fish from clear conditions may have more carotenoid resources available for signaling purposes. However, our field-based, survey design does not allow us to disentangle the effects of turbidity vs. diet on the observed variation in P. multicolor male nuptial coloration. A controlled, laboratory rearing experiment with high and low turbidity and high and low carotenoid diets to determine color differences between treatments is underway (SMG and TLA, unpublished data) and could shed light on the relative influence of turbidity and diet on color expression in P. multicolor.

4.3 Conclusion

Elevated turbidity alters the sensory environment and can be harmful to aquatic systems

(Kemp et al. 2011, van der Sluijs et al. 2011, Reid et al. 2018). Human-induced turbidity has also been found to exert pressure on aquatic organisms leading them to respond flexibly in both physiological and behavioral traits. For example, Gray et al. (2012) found evidence that, irrespective of population of origin (e.g., swamp or river) or rearing treatment (e.g., clear or

30 turbid), male P. multicolor displayed more aggressive behaviors when faced with a competitor under turbid vs. clear conditions. Other research has found that guppies reared in high turbidity water shifted from mid-wavelength-sensitive to long-wavelength-sensitive opsin gene expression

(Ehlman et al. 2015). In our study, we found evidence of within-population variation of diet and nuptial coloration in P. multicolor experiencing differing levels of turbidity. Although we were not able to test the mechanism driving this variation, we expect plasticity to play a role in these observed responses to human disturbance.

In an increasingly variable world, the ability for animals to respond rapidly to environmental disturbance can be critical for survival (Hendry et al. 2008). Human disturbance, specifically, is a strong driver of phenotypic change in animal populations (Hendry et al. 2008).

Evidence of phenotypic change associated with anthropogenic disturbances among populations is growing (Chapman et al. 2000, Candolin 2009, Schwartz and Hendry 2010, McNeil et al. 2016), but less evidence exists at a microgeographic scale. While it is important to understand how stressors affect organisms on large spatial scales, human land-use and pollution can also cause disturbances and habitat heterogeneity on small spatial scales (Richardson et al. 2014).

Microgeographic adaptations and genetic variation resulting from small scale disturbances could help to buffer organisms against future environmental change (Richardson et al. 2014).

References

Barton K. 2018. MuMIn: multi-model inference. R package version 1.40.4. https://CRAN.R- project.org/package=MuMIn

Bates D., Maechler M., Bolker B., Walker S. 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1-48. https://cran.r-project.org/package=lme4

Berry W., Rubenstein N., Melzian B. 2003. The biological effects of suspended and bedded sediment (SABS) in aquatic systems: a review. United States Environmental Protection Agency Internal Report; 102.

Binning S. A., and Chapman L. J. 2008. Feeding ecology and diet overlap in riverine cichlids from western Uganda. Verhandlungen Internationale Vereinigung Limnologie 30:283- 286.

Blanco-Canqui H., and Lal R. 2010. Principles of soil conservation and management. Springer, International.

Blount J. D. 2004. Carotenoids and life-history evolution in animals. Archives of Biochemistry and Biophysics 430:10-15.

Blount J. D., and McGraw K. M. 2008. Signal functions of carotenoid colouration. Pages 213- 236 in Britton G., Liaaen-Jensen S., Pfander H., editors. Carotenoids, Vol 4. Birkhäuser, Basel.

Bortolotti G. R., Mougeot F., Martinez-Padilla J., Webster L. M., and Piertney S. B. 2009. Physiological stress mediates the honesty of social signals. PloS ONE 4:e4983.

Candolin U. 2009. Population responses to anthropogenic disturbance: lessons from three-spined sticklebacks Gasterosteus aculeatus in eutrophic habitats. Journal of Fish Biology 75:2108-2121.

Candolin U., Salesto T., and Evers M. 2007. Changed environmental conditions weaken sexual selection in sticklebacks. Journal of Evolutionary Biology 20:233-239.

Candolin U., Tukiainen I., and Bertell E. 2016. Environmental change disrupts communication and sexual selection in a stickleback population. Ecology 97:969-979.

Carleton K. 2009. Cichlid fish visual systems: mechanisms of spectral tuning. Integrative Zoology 4:75-86.

Chapman L., Albert J., and Galis F. 2008. Developmental plasticity, genetic differentiation, and hypoxia-induced trade-offs in an African cichlid fish. The Open Evolution Journal 2: 75- 88.

Chapman L. G., Galis F., and Shinn J. 2000. Phenotypic plasticity and the possible role of genetic assimilation: Hypoxia-induced trade-offs in the morphological traits of an African cichlid. Ecology Letters 3:387-393.

Collin S. P., and Hart N. S. 2015. Vision and photoentrainment in fishes: the effects of natural and anthropogenic perturbation. Integrative Zoology 10:15-28.

Crispo E., and Chapman L. J. 2010a. Geographic variation in phenotypic plasticity in response to dissolved oxygen in an African cichlid fish. Journal of Evolutionary Biology 23:2091- 2103.

Crispo E., and Chapman L. J. 2010b. Temporal variation in population genetic structure of a riverine African cichlid fish. Journal of Heredity 101:97-106.

Crozier G. 1974. Pigments of Fishes. Pages 509-521 in Florkin M. and Scheer B. T., editors. Deuterostomians, cyclostomes, and fishes. Academic Press, New York.

Dugas M. B., and Franssen N. R. 2011. Nuptial coloration of red shiners (Cyprinella lutrensis) is more intense in turbid habitats. Naturwissenschaften 98:247-251.

Edelaar P., Jovani R., and Gomez-Mestre I. 2017. Should I change or should I go? Phenotypic plasticity and matching habitat choice in the adaptation to environmental heterogeneity. American Naturalist 190:506-520.

Edelaar P., A. M. Siepielski, and J. Clobert. 2008. Matching habitat choice causes directed gene flow: A neglected dimension in evolution and ecology. Evolution 62:2462-2472.

Ehlman S. M., Sandkam B. A., Breden F., and Sih A. 2015. Developmental plasticity in vision and behavior may help guppies overcome increased turbidity. Journal of Comparative Physiology A- Neuroethology Sensory Neural and Behavioral Physiology 201:1125- 1135.

Evans-White M. A., Dodds W. K., Huggins D. G., and Baker D. S. 2009. Thresholds in macroinvertebrate biodiversity and stoichiometry across water-quality gradients in Central Plains (USA) streams. Journal of the North American Benthological Society 28:855-868.

Ghalambor C. K., McKay J. K., Carroll S. P., and Reznick D. N. 2007. Adaptive versus non- adaptive phenotypic plasticity and the potential for contemporary adaptation in new environments. Functional Ecology 21:394-407.

Gray S. M., McDonnell L. H., Cinquemani F. G., and Chapman L. J. 2012. As clear as mud: Turbidity induces behavioral changes in the African cichlid Pseudocrenilabrus multicolor. Current Zoology 58:146-157.

Grether G. F., Millie D. F., Bryant M. J., Reznick D. N., and Mayea W. 2001. Rain forest canopy cover, resource availability, and life history evolution in guppies. Ecology 82:1546-1559.

Gu B. H., Schelske C. L., and Hoyer M. V. 1997. Intrapopulation feeding diversity in blue tilapia: Evidence from stable-isotope analyses. Ecology 78:2263-2266.

Han L. 1997. Spectral reflectance with varying suspended sediment concentrations in clear and algae-laden waters. Photogrammetric Engineering and Remote Sensing 63:701-705.

Hendry, A. P. 2016. Key Questions on the role of phenotypic plasticity in eco-evolutionary dynamics. Journal of Heredity 107:25-41.

Hendry A. P., Farrugia T. J., and Kinnison M. T. 2008. Human influences on rates of phenotypic change in wild animal populations. Molecular Ecology 17:20-29.

Hyslop E. J. 1980. Stomach contents analysis- A review of methods and their application. Journal of Fish Biology 17:411-429.

Järvenpää M., and Lindström K. 2004. Water turbidity by algal blooms causes mating system breakdown in a shallow-water fish, the sand goby Pomatoschistus minutus. Proceedings: Biological Sciences 271:2361-2365.

Kemp P., Sear D., Collins A., Naden P., and Jones I. 2011. The impacts of fine sediment on riverine fish. Hydrological Processes 25:1800-1821.

Kocher T. D. 2004. Adaptive evolution and explosive speciation: the cichlid fish model. Nature Reviews Genetics 5:288-298.

Langin K. M., Sillett T. S., Funk W. C., Morrison S. A., Desrosiers M. A., and Ghalambor C. K. 2015. Islands within an island: Repeated adaptive divergence in a single population. Evolution 69:653-665.

Leclercq E., Taylor J. F., and Migaud H. 2010. Morphological skin colour changes in teleosts. Fish and Fisheries 11:159-193.

Levine J. S., and MacNichol E. F. 1982. Color Vision in Fishes. Scientific American 246: 108- 117.

Lorenzon P., Clobert J., and Massot M. 2001. The contribution of phenotypic plasticity to adaptation in Lacerta vivipara. Evolution 55:392-404.

Lythgoe J. N. 1979. The ecology of vision. Clarendon Press, Oxford.

Maan M. E., Hofker K. D., van Alphen J. J. M., and Seehausen O. 2006. Sensory drive in cichlid speciation. American Naturalist 167:947-954.

Maan M. E., Seehausen O., Soderberg L., Johnson L., Ripmeester E. A. P., Mrosso H. D. J., Taylor M. I., van Dooren T. J. M., and van Alphen J. J. M. 2004. Intraspecific sexual selection on a speciation trait, male coloration, in the Lake Victoria cichlid Pundamilia nyererei. Proceedings of the Royal Society B-Biological Sciences 271:2445-2452.

Madliger C. L. 2012. Toward improved conservation management: a consideration of sensory ecology. Biodiversity and Conservation 21:3277-3286.

McCune B., and Grace J. B. 2002. Analysis of ecological communities. MjM Software Design, Gleneden Beach, Oregon

McNeil G. V., Friesen C. N., Gray S. M., Aldredge A., and Chapman L. J. 2016. L Male colour variation in a eurytopic African cichlid: the role of diet and hypoxia. Biological Journal of the Linnean Society 118:551-568.

Merritt R. W., and Cummins K. W. 1978. An introduction to the aquatic insects of North America. Kendall/Hunt Pub. Co., Iowa.

Michelangeli M., Tuomainen U., Candolin U., and Wong B. B. M. 2015. Habitat alteration influences male signaling effort in the Australian desert goby. Behavioral Ecology 26:1164-1169.

Misbahuzzaman K. 2016. Traditional farming in the mountainous region of Bangladesh and its modifications. Journal of Mountain Science 13:1489-1502.

Mrosso H. D. J., Msuku B. S., and Seehausen O. 2005. Relationship between water transparency and species richness of surviving Haplochromines in selected habitats in Mwanza gulf - Lake Victoria. Tanzania Journal of Science 30:101-108.

Murren C. J., Auld J. R., Callahan H., Ghalambor C. K., Handelsman C. A., Heskel M. A., Kingsolver J. G., Maclean H. J., Masel J., Maughan H., Pfennig D. W., Relyea R. A., Seiter S., Snell-Rood E., Steiner U. K., and Schlichting C. D. 2015. Constraints on the evolution of phenotypic plasticity: limits and costs of phenotype and plasticity. Heredity 115:293-301.

Nicoletto P. F., and Kodric-Brown A. 1999. The relationship among swimming performance, courtship behavior, and carotenoid pigmentation of guppies in four rivers of Trinidad. Environmental Biology of Fishes 55:227-235.

Nieman C. L., Oppliger A. L., McElwain C. C., and Gray S. M. 2018. Visual detection thresholds in two trophically distinct fishes are compromised in algal compared to sedimentary turbidity. Conservation Physiology 6:coy044.

Oksanen J., Blanchet F. G., Friendly M., Kindt R., Legendre P., McGlinn D., Minchin P. R., O'Hara R. B., Simpson G. L., Solymos P., Stevens M. H. H., Szoecs E., and Wagner H. 2018. vegan: community ecology package. R package version 2.5-3. https://CRAN.R- project.org/package=vegan

Oldham R. C., L. M. Pintor, and S. M. Gray. 2018. Behavioral differences within and among populations of an African cichlid found in divergent and extreme environments. Current Zoology 35:33-42.

Olson V. A. 2006. Estimating nutrient intake in comparative studies of animals: An example using dietary carotenoid content in birds. Oikos 112:620-628.

Olson V. A., and Owens I. P. F. 1998. Costly sexual signals: are carotenoids rare, risky or required? Trends in Ecology & Evolution 13:510-514.

Phillips I. D., Davies J. M., Bowman M. F., and Chivers D. P. 2016. Macroinvertebrate communities in a Northern Great Plains river are strongly shaped by naturally occurring suspended sediments: implications for ecosystem health assessment. Freshwater Science 35:1354-1364.

Pike T. W., Bjerkeng B., Blount J. D., Lindstrom J., and Metcalfe N. B. 2011. How integument colour reflects its carotenoid content: a stickleback's perspective. Functional Ecology 25:297-304.

R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Radwanski S. A. 1960. The soils and land-use of Buganda: A reconnaissance survey. Uganda Protectorate Department of Agriculture.

Rahman M. M., Kelley J. L., and Evans J. P. 2013. Condition-dependent expression of pre- and postcopulatory sexual traits in guppies. Ecology and Evolution 3:2197-2213.

Ravigne V., Olivieri I., and Dieckmann U. 2004. Implications of habitat choice for protected polymorphisms. Evolutionary Ecology Research 6:125-145.

Reardon E. E., and Chapman L. J. 2010. Energetics of hypoxia in a mouth-brooding cichlid: Evidence for interdemic and developmental effects. Physiological and Biochemical Zoology 83:414-423.

Ricciardi A., and Rasmussen J. B. 1999. Extinction rates of North American freshwater fauna. Conservation Biology 13:1220-1222.

Richardson, J. L., Urban M. C., Bolnick D. I., and Skelly D. K. 2014. Microgeographic adaptation and the spatial scale of evolution. Trends in Ecology & Evolution 29:165-176.

Rigby R.A., and Stasinopoulos D.M. (2005). Generalized additive models for location, scale and shape. Applied Statistics 54:507-554. https://cran.r-project.org/package=gamlss

Ryan P. A. 1991. Environmental effects of sediment on New Zealand streams- A review. New Zealand Journal of Marine and Freshwater Research 25:207-221.

Schoener T.W. I970. Nonsynchronous spatial overlap of lizards in patchy habitats. Ecology 5: 408-48.

Schwartz A. K., and Hendry A. P. 2010. Testing the influence of local forest canopy clearing on phenotypic variation in Trinidadian guppies. Functional Ecology 24:354-364.

Seehausen O. 1997. Cichlid fish diversity threatened by eutrophication that curbs sexual selection. Science 277:1808-1811.

Seehausen O., Terai Y., Magalhaes I. S., Carleton K. L., Mrosso H. D., Miyagi R., van der Sluijs I., Schneider M. V., Maan M. E., Tachida H., Imai H., and Okada N. 2008. Speciation through sensory drive in cichlid fish. Nature 455:620-626.

Sefc K. M., Brown A. C., and Clotfelter E. D. 2014. Carotenoid-based coloration in cichlid fishes. Comparative Biochemistry and Physiology, Part A 173:42-51.

Shoup D. E., and Wahl D. H. 2009. The Effects of turbidity on prey selection by piscivorous largemouth bass. Transactions of the American Fisheries Society 138:1018-1027.

Sih A., Ferrari M. C. O., and Harris D. J. 2011. Evolution and behavioural responses to human- induced rapid environmental change. Evolutionary Applications 4:367-387.

Simons M. J. P., Briga M., Koetsier E., Folkertsma R., Wubs M. D., Dijkstra C., and Verhulst S. 2012. Bill redness is positively associated with reproduction and survival in male and female zebra finches. PloS ONE 7:e40721

Stockwell C. A., Hendry A. P., and Kinnison M. T. 2003. Contemporary evolution meets conservation biology. Trends in Ecology & Evolution 18:94-101.

Svensson P. A., and Wong B. B. M. 2011. Carotenoid-based signals in behavioural ecology: A review. Behaviour 148:131-189.

Symonds M. R. E., and Moussalli A. 2011. A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike's information criterion. Behavioral Ecology and Sociobiology 65:13-21.

The Republic of Uganda. 2017. The Lake Nabugabo wetlands system RAMSAR site management plan 2017-2027.

Uzarski D. G., Brady V. J., Cooper M. J., Wilcox D. A., Albert D. A., Axler R. P., Bostwick P., Brown T. N., Ciborowski J. J. H., Danz N. P., Gathman J. P., Gehring T. M., Grabas G. P., Garwood A., Howe R. W., Johnson L. B., Lamberti G. A., Moerke A. H., Murry B. A., Niemi G. J., Norment C. J., Ruetz C. R., Steinman A. D., Tozer D. C., Wheeler R., O'Donnell T. K., and Schneider J. P. 2017. Standardized measures of coastal wetland condition: Implementation at a Laurentian Great Lakes basin-wide scale. Wetlands 37:15–32. van der Sluijs I., Gray S. M., Amorim M. C. P., Barber I., Candolin U., Hendry A. P., Krahe R., Maan M. E., Utne-Palm A. C., Wagner H. J., and Wong B. B. M. 2011. Communication in troubled waters: Responses of fish communication systems to changing environments. Evolutionary Ecology 25:623-640.

West-Eberhard M.J. 2003. Developmental plasticity and evolution. Oxford University Press, New York.

Winchell K. M., Reynolds R. G., Prado-Irwin S. R., Puente-Rolon A. R., and Revell L. J. 2016. Phenotypic shifts in urban areas in the tropical lizard Anolis cristatellus. Evolution 70:1009-1022.

Witte F., Seehausen O., Wanink J. H., Kishe-Machumu M. A., Rensing M., and Goldschmidt T. 2013. Cichlid species diversity in naturally and anthropogenically turbid habitats of Lake Victoria, East Africa. Aquatic Sciences 75:169-183.

Wong B. B. M., Candolin U., and Lindstrom K. 2007. Environmental deterioration compromises socially enforced signals of male quality in three-spined sticklebacks. American Naturalist 170:184-189.

Figures

Figure 2.1. Satellite imagery of sample site location in the Lake Nabugabo region of Uganda.

Spring sample stations are displayed in blue, forest/swamp stations are displayed in green, and agriculture stations are displayed in brown. Water flows from top to bottom through the spring stations and from right to left through the agriculture stations and then forest/swamp stations.

a) b)

a a c

b b

Figure 2.2. Mean a) turbidity (± 1 SE NTU) and b) temperature (± 1 SE ˚C) across station types

(agriculture, brown; forest, green; spring, blue). Letters represent significantly different values at alpha = 0.05.

a) b) *

* *

Figure 2.3. a) Mean relative abundance of prey types across low and high turbidity stations. b.)

Mean (± 1 SE) relative volume of prey types across low and high turbidity stations Stars indicate significant differences at alpha = 0.05.

b) c) b

Figure 2.4. a) Regression of proportion of carotenoid coloration and fish standard length (cm) separated by high (brown) and low (blue) turbidity stations with 95% confidence intervals.

Mean (± 1 SE) b) total carotenoid coloration (proportion red + proportion yellow) of male fish and c) Male standard length (cm) for high and low turbidity stations. Letters denote significant differences at alpha = 0.05.

Chapter 3

Diet and turbidity exposure can affect the reproductive and survival traits of an African cichlid fish

Abstract

Freshwater ecosystems are some of the most diverse on the planet, but they are also some of the most threatened due to human activity and land-use change. Tropical and Subtropical freshwater systems tend to have the highest species richness worldwide, but biodiversity declines have been especially serious at tropical latitudes. One major threat to aquatic systems worldwide is increased runoff which can lead to elevated levels of turbidity. Chronic and acute turbidity exposure can have behavioral, sublethal, or lethal impacts on fishes both directly and indirectly.

Indirectly, turbidity can influence prey availability, causing shifts in diet composition. This can potentially lead to changes in the amount of carotenoids consumed. Directly, turbidity can cause damage to organs or elicit physiological compensatory mechanisms, both of which can influence fitness related traits including reproductive and survival traits. Here, we examine changes to reproductive traits (standard length, weight, nuptial coloration, gonadosomatic index) of

Pseudocrenilabrus multicolor victoriae associated with trace- and low- carotenoid diets and chronic exposure to turbidity using a 2 x 2 factorial rearing experiment. We found that male GSI was significantly increased in fish experiencing chronic turbidity, and this increase was

45 intensified when fed a trace-carotenoid diet. Additionally, male carotenoid coloration was significantly increased in trace-carotenoid treatments. We also found that female size (standard length and weight) was significantly reduced in fish experiencing chronic turbidity. These results provide evidence that at least one chronic stressor impacts sex-specific reproductive traits. We also examined impacts on P. multicolor swimming performance due to chronic and acute turbidity exposure. We found that swimming performance was increased by acute turbidity exposure, regardless of chronic turbidity exposure. These results provide evidence that aerobic performance of P. multicolor was not affected by chronic turbidity. This study emphasizes that the impacts of turbidity varies due to several circumstances including: concentration, duration of exposure, species, and sex. By further investigating the effects of turbidity as a stressor on reproductive and survival traits of fish found across both extremes, we can further our understanding of the mechanisms contributing to persistence of fish facing human-induced environmental changes.

1. Introduction

Land-use change is being driven by the need to provide food, fiber, water, and shelter for over six billion people (Foley et al. 2005). Foley et al. (2005) stressed that land-use practices worldwide are resulting in the degradation of environmental ecosystems to benefit humanity; however, this ultimately leads to the breakdown of ecosystem services. Freshwater ecosystems are some of the most diverse on the planet, but they are also among the most threatened due to human activity and land-use change (Dudgeon et al. 2006, Kopf et al. 2015, Reid et al. 2018).

Tropical and Subtropical freshwater systems tend to have the highest species richness worldwide

(Tisseuil et al. 2013). Unfortunately, biodiversity declines have been especially serious at tropical latitudes (Dudgeon et al. 2006). It is important to understand how stressors imposed by human-induced environmental change will continue to affect freshwater organisms, especially tropical species, as these areas are not well studied (Chapman 2001, Chapman and Chapman

2001, Dudgeon et al. 2006).

Some of the major threats that freshwater organisms face due to land-use changes include: chemical contamination, flow modification (e.g. channelization, impoundment, etc.), destruction or degradation of habitat, introduction and proliferation of invasive species, and increased runoff of sediments and nutrients (Allan and Flecker 1993, Dynesius and Nilsson

1994, Foley et al. 2005, Kemp et al. 2011, Reid et al. 2018). These threats can lead to reduced habitat availability, increased competition and predation from invasive species, increased eutrophication and oxygen depletion, and elevated levels of turbidity (Allan and Flecker 1993,

Carpenter et al. 1998, Kemp et al. 2011). Elevated turbidity can negatively impact fishes indirectly and directly and can have both sublethal and lethal effects (Newcombe and Macdonald

1991, Kemp et al. 2011). Here, we focus on the sublethal effects of sedimentary turbidity on reproductive traits and performance metrics of a tropical fish.

There are a number of ways that turbidity can indirectly influence the reproduction and survival of fish. For example, by causing declines and community shifts in primary producers

(Izagirre et al. 2009), zooplankton (Hart 1992), and macroinvertebrates (Bo et al. 2007), the availability of resources can be altered. Water quality can also be reduced due to nutrients and contaminants adhering to sediments (Warren et al. 2003). And, through the effects of the scattering and absorption of light, turbidity can alter the underwater visual environment, thereby

47 changing the way that visually-mediated activities (e.g. sexual signaling, finding food and avoiding predators) work (van der Sluijs et al. 2011).

By altering the availability of prey items, turbidity could result in fewer carotenoid-rich food sources (see Chapter 2). Since animals are unable to synthesize carotenoids, they rely entirely on dietary acquisition (Svensson and Wong 2011). Olson (2006) found that different prey items have varying concentrations of carotenoids, so a fish’s carotenoid intake depends on the composition of their diet. Once ingested, carotenoids can be allocated for a number of different physiological processes (Svensson and Wong 2011). For example, carotenoids are powerful antioxidants (Krinsky 1989), play a role in the immune system (Chew and Park 2004), and are responsible for much of the red-yellow pigmentation in the animal kingdom (Fox and

Vevers 1960). Carotenoids contribute to antioxidation by deactivating reactive oxygen species

(free radicals) caused by internal photochemical and biochemical processes (reviewed in Krinsky

1989). If these free radicals are produced faster than they can be neutralized, they can cause oxidative stress and damage to DNA (Kiokias and Gordon 2004). The physiological processes for which carotenoids are utilized contribute to both the survival and the reproduction of the individual. However, because carotenoids are a limited resource, this could result in a trade-off between survival and reproduction in animals that rely on carotenoid coloration for sexual selection (Blount 2004).

The direct impacts of turbidity can vary depending on many circumstances including: frequency and duration of exposure, the concentration of particles, size of particles, species and life stage encountering turbidity, and degree of acclimation (reviewed in Kemp et al. 2011).

Shifts in behavior are an organism’s first line of defense when faced with external stressors. The

48 primary response of fish to elevated turbidity is avoidance (Collin and Hart 2015), e.g. seeking refuge or moving to lower turbidity areas (Barton 1977). Other behavioral responses of fish to turbidity include: increased coughing and gill flaring (Carlson 1984, Berg and Northcote 1985), changes to feeding (Berg and Northcote 1985, Henley et al. 2000) and schooling (Gray et al.

2014), and altered aggression and activity levels (Gray et al. 2012). For example, Gardner (1981) found that bluegill (Lepomis machrochirus) reduced feeding rates in elevated turbidity. Reduced feeding and ability to obtain food can to lead to reduced growth rates (Shaw and Richardson

2001). This can directly affect female fecundity, because in fish, fecundity shares a positive relationship with size, e.g. larger females are more fecund (Coates 1988, Buckley et al. 1991,

Morita and Takashima 1998).

Direct effects of turbidity may compromise the fitness of an individual; these sublethal effects encompass impacts to the physiology and histology of the organism that aren’t severe enough to cause mortality (Newcombe and Macdonald 1991). Elevated turbidity levels can cause direct damage to gills through abrasion of tissues (Herbert and Merkens 1961) and erosion of the mucus coating (Kemp et al. 2011). Gill rakers and filaments can also become clogged when suspended sediments bind to the gill epithelium (Wong et al. 2013). To combat the effects of suspended sediments, fish have been found to increase mucus secretion in the area and even thicken the gill lamellae (Sutherland and Meyer 2007, Wong et al. 2013). When sediments bind to the gill epithelium, or when mucus secretion occurs, gaseous exchange (i.e. oxygen uptake) can be interrupted (Wilber and Clarke 2001, Wong et al. 2013). If oxygen uptake is hindered, the aerobic capacity of the fish could be compromised, affecting its ability to perform regular activities dependent on aerobic metabolism, like swimming.

Physiological responses to elevated turbidity include endocrine stress responses (elevated plasma cortisol, glucose, and hematocrit levels) (Redding et al. 1987) and decreased critical oxygen tension (Pcrit) (i.e. increased cost of oxygen uptake) (Gray et al. 2016). Endocrine stress responses can have a multitude of effects on fish including reduced fecundity (Schreck et al.

2016), growth, and gonadal development, and increased susceptibility to disease (Pickering

1993). Elevated stress in fish can be metabolically costly; Barton and Schreck (1987) found that steelhead (Salmo gairdneri) with elevated plasma cortisol (a stress hormone) levels also exhibited higher oxygen consumption rates. This means that fish with high levels of stress have less energy for other metabolically demanding activities (i.e. smaller aerobic scope) (Barton and

Schreck 1987). The physiological stress response to turbidity, along with direct gill damage that can lead to respiratory impairment, could negatively impact metabolically demanding activities like swimming (Gray et al. 2014). A fish’s ability to swim is critical for it to acquire food, avoid predation, and migrate, making swimming performance important for the survival fish (Beamish

1978, Plaut 2001). As such, swimming performance has been cited as a factor influencing fitness

(Plaut 2001) and a useful criterion to evaluate the sublethal effects of pollutants on fish (Sprague

1971, Beamish 1978).

The swimming performance of fish can be grouped into three categories: burst, sustained, and prolonged swimming speeds (reviewed in Beamish 1978, Plaut 2001). Burst swimming speeds are fueled by anaerobic mechanisms and rely on white muscle cells, while sustained and prolonged swimming speeds are fueled by aerobic mechanisms and depend on red muscle cells

(Beamish 1978). Prolonged swimming speeds result in exhaustion or muscular fatigue (Beamish

1978); because prolonged swimming speeds end in fatigue, they are easy to measure in the laboratory and are often used to assess the swimming performance of fishes (Plaut 2001).

Brett (1964) first defined critical swimming speed (Ucrit) as a method for measuring prolonged swimming speed by determining the maximum velocity maintained by a fish for a set amount of time (Beamish 1978). A fish’s maximum oxygen uptake or maximum metabolic rate is commonly measured when it reaches its Ucrit (Roche et al. 2013). Because of this, critical swimming speed is a relative measure of the fish’s maximum aerobic capacity (Hammer 1995).

This means fish with a higher Ucrit have a larger aerobic scope, thus they have more energy for metabolically demanding activities (e.g. growth and reproduction) (McDonnell and Chapman

2016).

Due to stress responses and the impairment of oxygen uptake from gill damage, it seems logical that fish experiencing chronic exposure to elevated turbidity would exhibit reduced swimming performance. Because swimming performance is important for fish survival, it is important to understand how it is affected when fish are introduced to a stressor. As an example,

Gray et al. (2014) tested the chronic effects of turbidity on swimming performance and found that the imperiled pugnose shiner (Notropis anogenus) exhibited diminished swimming performance after acclimation to turbidity but found the opposite result for the more tolerant bridle shiner (N. bifrenatus). Another study by Hildebrandt and Parsons (2016) examined the acute effects of turbidity on swimming performance and found that golden shiner (Notemigonus crysoleuscas) tested in high levels of turbidity had increased critical swimming speeds vs. fish tested in clear waters. These differences in the effect of turbidity on swimming performance could be attributed to the tolerance levels of the fish being tested.

We examined the effects of chronic and acute turbidity exposure on a tolerant, African cichlid fish, Pseudocrenilabrus multicolor victoriae. Pseudocrenilabrus multicolor is widespread throughout the Nile River basin and can be found across a number of stressful environments including low dissolved oxygen and high suspended sediments (Reardon and Chapman 2009,

McNeil et al. 2016). It is a good indicator of adaptability to human-induced environmental change due to its high level of tolerance and plasticity (Chapman et al. 2000, Greenwood 1965).

We already know from Chapter 2 that P. multicolor from high turbidity conditions tend to consume different diets than fish from low turbidity habitats, even within a single population.

Specifically, P. multicolor from turbid sites consumed prey items that were lower in carotenoid content than fish from low turbidity conditions. For this reason, we are interested in the sublethal effects of turbidity on fish with lower quality diets. The objectives of this research were to 1) investigate if reproductive traits are impacted by chronic exposure to turbidity throughout development when fed diets with trace and low carotenoid concentrations, and 2) investigate if swimming performance, as a proxy for aerobic capacity, is impacted by both acute and chronic exposure to elevated turbidity. We predicted that exposure to turbidity and being fed trace carotenoid diets throughout development (i.e. chronic) would negatively impact reproductive traits (e.g. size, sexual nuptial coloration, and gonadosomatic index- GSI) in P. multicolor. We also predicted that both acute and chronic exposure to turbidity would negatively impact swimming performance in P. multicolor.

2. Materials and Methods

2.1 Split-brood rearing experiment

Wild-caught, adult fish were collected from a variable, stream site (i.e. frequent human disturbances and fluctuating levels of turbidity and oxygen) (latitude: -0.3277975, longitude:

31.775841) within the Lake Nabugabo drainage of Uganda, Africa during June-August of 2015-

2017. Across a 0.14 km2 area, this stream population experiences high and low dissolved oxygen and both seasonal and human-caused fluctuations in turbidity (see Chapter 2). Adult wild-caught fish were live-transported to The Ohio State University, held under 12-hour day:night cycles, and housed in clear water, high oxygen conditions. (Institutional Animal Care and Use Committee

Protocol #2014A00000055). To assess the effects of turbidity on P. multicolor, we used a 2 x 2 factorial, split-brood rearing design with eight families. Treatments included (1) High

Turbidity/Trace-Carotenoid Diet, (2) High Turbidity/Low-Carotenoid Diet, (3) Low

Turbidity/Trace-Carotenoid Diet, and (4) Low Turbidity/Low-Carotenoid Diet. To obtain the largest amount of genetic diversity possible between families we used offspring (broods) with known parentage (i.e. all broods had different parents). We placed one adult male in a 38 L tank with three to four adult females. Once a female was found with eggs in her mouth, the male was removed and placed in separate aquarium so that he was unable to fertilize more broods. The brooding female was then isolated in an aquarium for approximately 21 days until the brood was released. Offspring produced from each brood were counted and randomly assigned among the four treatments (8 broods x 4 treatments = 32 experimental tanks), following a split-brood design protocol (Gray et al. 2012).

Newly released fry were reared under clear water conditions and fed Brine Shrimp Direct

Golden Pearl fry food for 21 days (fed twice daily ad libitum). After 21 days, we began introducing treatment conditions. Bentonite clay was gradually introduced in high turbidity tanks

53 at a rate of approximately two Nepholometric Turbidity Units (NTU) per day (Gray et al. 2012).

Fry were also gradually introduced to the trace and low carotenoid experimental diets and were fed ad libitum (McNeil et al. 2016). The experimental diets were based on the recipe reported in

Grether (2005) and were manufactured by Ocean Star International, Inc. (Snowville, Utah). The two diets were nutritionally identical except that the low carotenoid diet was supplemented with beta-carotene and lutein (McNeil et al. 2016) (Appendix B, Table B.1 for diet recipe).

High performance liquid chromatography (HPLC) was used to determine the concentrations of beta-carotene and lutein in both the trace and low carotenoid diet. Carotenoids were extracted from fish diets using methods outlined in Kopec et al. (2014) and the carotenoid analysis by HPLC were completed following the methods outlined in Cooperstone et al. (2015).

Both lutein and beta-carotene were found in the low-carotenoid diet, but not in the trace- carotenoid diet (Fig. B.1). The only carotenoids present in the trace carotenoid diet were tunaxanthins (also present in the low carotenoid diet, probably derived from the fishmeal component of diet), but at such low concentrations that they were almost below detection thresholds (see Appendix B, Fig. B.1) (J. Cooperstone, personal communication). The low carotenoid diet contained 8.04 µg/g beta-carotene and 6.19 µg/g lutein (as both mono and di- esters). These concentrations are comparable to low carotenoid diets used in other studies

(Grether et al. 2005, Pike et al. 2007).

All four treatments were evenly distributed across aquaria to account for any variation that may occur due to position on racks (e.g., differences in light, temperature, etc.). Each aquarium had a submersible Maxi-Jet 400 circulation pump to keep turbidity suspended. Pumps were only turned on after fish had been under experimental conditions for 28 days (aged 49 days

54 total) and had grown large enough to withstand water flow from the pump. For the first 28 days of treatment conditions, turbidity was stirred manually multiple times a day. We monitored turbidity level three times weekly using a LaMotte 2020we Turbidity Meter, and general water quality (dissolved oxygen, temperature, conductivity, ammonia, nitrite) was monitored once weekly using a Pro 2030 YSI portable handheld unit. We maintained optimal water quality via water changes performed twice weekly. Low turbidity treatments were maintained at turbidity <

2 NTU and high turbidity treatments were maintained at turbidity > 10 NTU (see Appendix B,

Table B.2 for mean environmental conditions of each treatment).

2.2 Effects of chronic turbidity and diet on reproductive traits

To assess the effects of chronic turbidity and trace- and low-carotenoid diets on reproductive traits of P. multicolor we assessed a number of metrics of fish from the 2 x 2 factorial rearing experiment including body size, nuptial coloration, and GSI once they reached reproductive maturity (approximately 9-12 months). Every fish was photographed in a Plexiglas cuvette with a gray background and white standard for color analysis using methods outlined in

Chapter 2 (Maan et al. 2004). Standard length (SL), total length (TL) (cm), and weight (g) were recorded, and fish were euthanized using a mixture of 2 ml clove oil solution (1:10 eugenol:ethanol) in 500 ml water. Fish were dissected to determine sex, and gonads were removed and weighed (g) for the calculation of GSI (gonad mass ÷ full body mass * 100). Fish were preserved in 10% buffered formalin.

2.3 Effects of chronic and acute turbidity exposure on performance

To assess the effects of acute and chronic exposure to elevated turbidity on P. multicolor we measured the swimming performance of fish in a repeated measures experimental design.

Each fish was tested twice, once in clear (turbidity < 2 NTU) and once in turbid (turbidity > 10

NTU) swimming performance trials (n = 2 trials/individual fish). We tested a subset of fish reared in high or low turbidity conditions (n = 40; high turbidity n = 20, low turbidity n = 20), but only tested fish from the low-carotenoid treatments to ensure that turbidity was the only chronic stressor contributing to differences in swimming performance. The swimming chamber used was modified from Vogel and LaBarbera (1978). It consisted of a 35 cm clear, PVC flume that was partially wrapped in black plastic mesh (16 cm) as a refugia for swimming fish. A

Leader Ecovort 520 pump was used to maintain water flow throughout the chamber. Water was first passed through a 3.8 L plastic reservoir and a 14 cm baffle of straws before reaching the swimming chamber to produce a laminar flow (Bell and Terhune 1970) (Fig. 3.1). The end of the swimming tunnel was covered with mesh to confine the fish to the swimming chamber (Gray et al. 2014). Water flow was adjusted using a Variac Transformer IDGC-1KM voltage regulator and was calibrated using a Geopack MFP51 flow meter. We calibrated flow before every swimming performance trial. The entire swimming performance apparatus was housed within a standard 210 L glass aquarium. Two swimming performance systems were used, one for turbid water trials and one for clear water trials.

Food was withheld for 24 hours prior to each experiment to limit energy used for digestion (Reardon and Chapman 2010a, Roche et al. 2013). Fish were randomly chosen from low-carotenoid rearing aquaria for trials, one from the low and one from the high turbidity rearing treatments, tested simultaneously. The order of clear and turbid trials was alternated.

Each fish was acclimated in the swimming tunnel at a velocity of 10 cm/s for 2 hours. Due to logistical constraints, the acclimation speed was faster than previous swimming performance

56 studies conducted on P. multicolor, which used 5 cm/s (Gotanda et al. 2012, Gray et al. 2014,

McDonnell and Chapman 2016). A length of two hours was used for acclimation because P. multicolor has been found to return to its standard metabolic rate after 90 minutes post-handling

(Reardon and Chapman 2010b).

During trials, the water velocity was increased by 5 cm/s (Brett 1964) every 15 minutes

(Hammer 1995). Turbidity and temperature were measured and recorded at the beginning and end of acclimation and then at each velocity increment. The high turbidity trial conditions were maintained by using a turkey-baster to keep turbidity suspended at low velocities (turbid trials-

10.71 NTU ± 0.06; clear trials- 0.47 NTU ± 0.01). Temperature was maintained constant using

AquaEuro USA Max Chill 1/10 HP chillers and bagged ice (turbid trials- 25.06 ˚C ± 0.02; clear trials- 25.15 ˚C ± 0.05). Trials ended when fish became fatigued (i.e. when the fish could no longer swim, was pushed by the flow of water against the mesh, and did not respond to three gentle prods). Once fatigue was confirmed, the velocity was reduced to 10 cm/s for a 15 min recovery period. If it was the first time a fish was tested, they were housed individually in isolated aquaria under their home turbidity conditions. To alleviate any stress of isolation, aquaria were situated so that fish could maintain visual contact with fish in other aquaria. Fish were re-tested under the alternate trial condition two days later, following the same protocol.

After completing the second trial, fish were photographed for color analysis, measured, sexed, euthanized, and preserved as described above. Critical swimming speed was calculated following

Brett (1964):

Ucrit = Ui + [Uii (Ti/Tii)]

57 where Ui was the highest speed maintained for an entire 15 min interval, Uii was the flow rate increment (5 cm/s), Ti was time elapsed during the interval that the fish became fatigued, and Tii was the time interval (15 min). We calculated body lengths/s (BL/s) by dividing Ucrit (cm/s) by fish length (cm).

2.4 Statistical Analyses

All statistical analyses were completed using R 3.4.4 (R Core Team 2018).

2.4.1 Effects of chronic turbidity and diet on reproductive traits

We tested if body size, nuptial coloration, and GSI were influenced by rearing treatment using Linear Mixed-Models (LMMs) with a Gaussian distribution using the lme4 package (Bates et al. 2015). Separate tests were used for each dependent variable (i.e. due to multicollinearity among traits). All fish (n = 108) were used for these analyses (including fish used for swimming performance trials), and, because P. multicolor is sexually dimorphic, we analyzed reproductive traits of males (n = 25) and females (n = 83) separately. To normalize the dependent variables

(SL, weight, coloration, and GSI), we used a number of transformations that varied between male and female datasets (see Appendix B, Table B.3 for transformations). Independent variables were turbidity treatment (clear or turbid) and diet treatment (trace- or low-carotenoids).

When interaction terms were significant, we included them in the model. We included aquarium nested within brood as a random factor to account for relatedness within broods and any unintentional differences in aquaria placement. We also used regression analysis to examine relationships between dependent variables.

2.4.2 Effects of chronic and acute turbidity exposure on performance

We tested if swimming performance was affected by acute or chronic exposure to turbidity using LMMs with a Gaussian distribution using the lme4 package (Bates et al. 2015).

Both males (n = 11) and females (n= 29) were analyzed together (n = 40) to retain power in the analyses. To account for the influence of fish size on variation in swimming performance, we used BL/s as the dependent variable. BL/s was log10 transformed to meet normality assumptions. When investigating differences in BL/s across rearing (chronic exposure) and trial

(acute exposure) conditions, we again included the random factor aquarium nested within brood to account for relatedness and aquaria placement on racks, and an additional random factor

(individual fish) to account for repeated testing of each fish in both clear and turbid trials.

3. Results

3.1 Effects of chronic turbidity and diet on reproductive traits

3.1.1 Males

There was no significant difference in SL (turbidity treatment- F1,24 = 0.0004, p = 0.985; diet treatment- F1,24 = 3.58, p = 0.070) or weight (turbidity treatment- F1,24 = 0.124, p = 0.727; diet treatment- F1,24 = 1.81, p = 0.191) between males across turbidity or diet treatments (Table

3.1). There was a significant difference in coloration across diet treatment (diet treatment- F1,23 =

8.14, p = 0.009) (Table 3.1). Males exhibited significantly more carotenoid coloration when reared in the trace-carotenoid diet treatment than males reared in the low-carotenoid diet treatment (Fig. 3.2a), with males in the trace-carotenoid diet treatment having 16 times more carotenoid coloration, on average, than males in the low-carotenoid diet treatment. However, male coloration did not vary across turbidity treatment (turbidity treatment- F1,23 = 1.20, p =

0.285). Regression analysis showed that male coloration was positively influenced by SL in both 59 the trace- and low-carotenoid diet treatments, with the trace-carotenoid diet exhibiting a stronger

2 2 correlation (trace diet- F1,10 = 11.44, p = 0.006, R = 0.49; low diet- F1,9 = 5.86, p = 0.039, R =

0.33) (Fig. 3.2b). There was a significant difference in male GSI across turbidity treatments

(turbidity treatment- F1,15 = 7.71, p = 0.014) with males from turbid treatments having 68% higher GSI, on average, than males from clear treatments (Table 3.1). Male GSI did not vary across diet treatment (diet treatment- F1,15 = 2.62, p = 0.126), but we did find a significant interaction between turbidity treatment and diet treatment (interaction- F1,15 = 4.87, p = 0.043)

(Fig. 3.2c). Additionally, we found that, overall, GSI had a significant positive relationship with

2 male coloration when all treatments were pooled (F1,21 = 8.41, p = 0.009, R = 0.25) (Fig. 3.2d).

3.1.2 Females

In females, there was a significant difference in SL among turbidity treatments (turbidity treatment- F1,76 = 9.47, p = 0.003), with females reared in clear treatments being 7% longer, on average, than females from turbid treatments (Table 3.2; Fig. 3.3a). However, there was no effect of diet treatment on SL (diet treatment- F1,76 = 0.50, p = 0.483). Female weight also varied significantly between turbidity treatments (turbidity treatment- F1,76 = 14.59, p < 0.001) (Table

3.2; Fig. 3.3b), with females reared in clear treatments being 27% heavier, on average, than females from turbid treatments. Female weight was not affected by diet treatment (diet treatment- F1,76 = 0.58, p = 0.447). Female coloration did not vary among either turbidity (F1,25 =

2.36, p = 0.136) or diet (F1,22 = 0.37, p = 0.549; Table 3.2) treatments. We also found no evidence that GSI was influenced by turbidity (F1,77 = 0.10, p = 0.751) or diet (F1,75 = 0.91, p =

0.344; Table 3.2) treatments.

3.2 Effects of chronic and acute turbidity exposure on performance

We found that P. multicolor swimming performance was not affected by chronic turbidity exposure (rearing treatment- F1,31 = 0.12, p = 0.732). However, P. multicolor swimming performance did vary with acute turbidity exposure, as experienced by individual fish in clear and turbid swimming performance trials (trial condition- F1,40 = 15.67, p < 0.001; Table 3.3). We found that fish performed better in turbid trial conditions compared to clear trial conditions, regardless of the rearing environment (Fig. 3.4).

4. Discussion

Our goal was to tease apart the influence of turbidity and dietary carotenoid availability on reproductive traits and a performance metric of P. multicolor. We found that chronic turbidity exposure during development (i.e. turbidity treatment) affected both male and female reproductive traits, while the level of carotenoids in the diet (i.e. diet treatment) only affected males. Interestingly, and contrary to our expectations, males fed diets with only trace-carotenoid levels displayed significantly more carotenoid coloration than males fed higher levels of carotenoids (low-carotenoid diet). Additionally, carotenoid coloration was positively associated with SL and GSI across all males, such that larger males were more colorful and had devoted a higher proportion of mass toward gonad development. Males exposed to chronic turbidity had higher GSI, but a diet higher in carotenoid content decreased the difference in GSI between turbid and clear treatments. We also found that body size of female P. multicolor was found to be significantly smaller when exposed to chronic turbidity. Finally, our results revealed that chronic turbidity exposure did not affect swimming performance, but that acute turbidity exposure increased swimming performance of P. multicolor. Below, we discuss these findings in

61 the context of behavioral and physiological mechanisms that may be driving responses to these stressors.

4.1 Effects of chronic turbidity and diet on reproductive traits

4.1.1 Males

Our results provided evidence that chronic turbidity exposure resulted in larger testes relative to male body size (i.e. higher GSI). However, being fed a diet with more carotenoids decreased the difference in GSI between clear and turbid treatments. Males facing chronic turbidity and fed only trace amounts of carotenoids exhibited the highest GSI. We postulate that this could be due to the multi-stressor environment experienced by these fish; gonad development could have been stimulated due to the stressful nature of the rearing treatment. In another species, Shankar and Kulkarni (2000) found that exposure to cortisol (a stress hormone), even at high levels, activated spermatogenesis and increased the GSI of immature Notropterus notropterus. Schreck (2010) outlines the phenomena of hormesis in fish, which occurs when high and low levels of stress elicit alternate responses in organisms. For example, low levels of stress might positively impact fish reproduction, while high levels of stress might negatively impact fish reproduction. Ozaki et al. (2006) found that low to moderate doses of cortisol stimulated DNA replication and mitosis in spermatogonia of the Japanese eel (Anguilla japonica), while high doses inhibited spermatogonia proliferation. Similarly, Shankar and

Kulkarni (2000) found that low levels of cortisol had no effect on mature N. notropterus spermatogenesis, but high levels of cortisol inhibited spermatogenesis. It is possible that we witnessed a hormetic stress response, in that the level of turbidity that fish were exposed to,

62 along with a diet with little to no carotenoids, caused just enough stress to stimulate increased gonadal development in male P. multicolor.

Contrary to our predictions, male P. multicolor fed trace-carotenoid diets displayed significantly more carotenoid coloration than males fed low-carotenoid diets, regardless of turbidity rearing treatment. It should be noted that, although trace-carotenoid males displayed more coloration, it was still much lower than wild males from Chapter 2 caught under high turbidity conditions (reared, trace-carotenoid males: 0.023 ± 0.013; wild, high turbidity males-

0.368 ± 0.015). While we did not expect males from the trace-carotenoid diet to display more carotenoid coloration, Pike et al. (2007) found that three-spined stickleback (Gasterosteus aculeatus) fed low concentrations of carotenoids allocated a much larger portion of overall carotenoids toward nuptial displays (80%) than the rest of their body (20%), compared to fish fed high-carotenoid diets, in which the pattern was reversed (20% nuptial display, 80% body). They also found that male fish fed low-carotenoid diets were more susceptible to oxidative stress and senesced earlier (i.e. had shorter lifespans) than males fed high-carotenoid diets and females regardless of diet. Due to this trade-off, Pike et al. (2007) suggested that males fed a low- carotenoid diet were potentially investing more of their resources in current reproduction (i.e. sexual coloration) instead of long-term somatic maintenance (individual health). The trade-off between reproduction and somatic health could explain why male P. multicolor fed diets with only trace carotenoids displayed more overall red and yellow coloration than those fed a higher concentration of carotenoids; thus, males could have been trading-off future reproductive opportunities and health for immediate sexual attractiveness.

If fish were allocating more resources towards immediate reproduction, this would also explain why carotenoid coloration had a positive relationship with GSI, however investment in gonadal development comes at a cost to somatic growth (Wootton and Smith 2015), so this investment in gonadal development could have affected the overall health of male fish.

Additionally, we observed a very skewed number of male fish (n = 25) vs. female fish (n = 83) in our rearing experiment due to high mortality in males. We believe that this may further reinforce the idea that male P. multicolor responded to trace- and low-carotenoid diets in a similar manner as three-spined stickleback, by being more susceptible to oxidative stress, senescing earlier, and putting all their energy into the immediate reproduction vs. long-term somatic maintenance (Pike et al. 2007). These relationships could be better explored by conducting experiments with P. multicolor to determine susceptibility to oxidative stress, length of lifespans, and gonadal development when fed diets of different carotenoid concentrations.

4.1.2 Females

We found no relationship between any of the reproductive traits of female P. multicolor and diet; however, we did find that female size was reduced when exposed to chronic turbidity throughout development. Pseudocrenilabrus multicolor is an active, visual feeder; however, this type of foraging strategy can be affected by turbid conditions (reviewed in Kemp et al. 2011).

Elevated turbidity can reduce reaction distance (maximum distance at which an object is detected) and/or foraging ability in some fish species, including lake trout (Salvelinus namaycush), rainbow trout (Oncorhynchus mykiss), cutthroat trout (Oncorhynchus clarki) (Vogel and Beauchamp 1999), coho salmon (Oncorhynchus kisutch) (Berg and Northcote 1985), and

Acanthochromis polyacanthus (a coral reef damsel fish) (Wenger et al. 2012). For example, Berg

64 and Northcote (1985) found that coho salmon had decreased reaction distance, capture success per strike, and percentage of prey ingested under turbid conditions. This inability to successfully detect and capture prey could consequently affect growth rates and overall fitness. Wenger et al.

(2012) discovered that A. polyacanthus was less able to acquire food under turbid conditions, and as a result, had smaller growth rates compared to fish tested in clear water. Because female P. multicolor were smaller under chronic turbidity, regardless of diet treatment, it is possible that females were smaller because of reduced reaction distance and ability to acquire food.

4.2 Effects of chronic and acute turbidity exposure on performance

To our knowledge, this is the first study examining both the acute and chronic response of turbidity on swimming performance. We found that, regardless of rearing environment (clear or turbid), P. multicolor had higher critical swimming speeds under acute turbidity exposure

(turbid test conditions). This means that the aerobic performance of fish reared at an ecologically low to moderate level of turbidity was not decreased compared to fish reared in clear water.

Given the negative impacts that chronic and acute turbidity have on a range of fish behaviors and physiology (e.g., endocrine stress response, gill damage, reaction distance, foraging, etc.)

(reviewed in Kemp et al. 2011), this was unexpected. It is possible that we saw no significant effect of chronic turbidity because the turbidity levels used for rearing were too low to negatively impact swimming performance given how tolerant P. multicolor can be to environmental stressors. Research by Gray et al. (2014) found that chronic exposure to turbidity only negatively impacted the aerobic performance of the endangered pugnose shiner but did not affect the aerobic performance of the blacknose shiner (N. heterolepis), blackchin shiner (N. heterodon), or mimic shiner (N. volucellus), which were also more tolerant to turbidity based on behavioral

65 measures. In that study, another imperiled species, bridle shiner, had higher swimming performance after long-term turbidity exposure than fish held in clear water. In that case, however, all fish were tested in clear water and the authors argued that bridle shiner were able to quickly adjust from a turbid holding environment to a clear test environment (Gray et al. 2014).

This explanation does not apply here, as we were specifically testing fish under both clear and turbid conditions. An alternative explanation may rely on the fact that the parent population we used to produce broods for this experiment comes from a high turbidity environment. Therefore, this population could have plastic or genetic adaptations that allow them to perform well even after chronic exposure to turbidity. Previous research has found evidence for heritable adaptive responses to other stressors in P. multicolor; genetic adaptations to combat hypoxia stress have been found to influence brain mass, brain plasticity (Crispo and Chapman 2010), and hematocrit and lactate dehydrogenase activity (Martinez et al. 2009). For example, a rearing experiment by

Crispo and Chapman (2010), found both environmental and population levels effects on P. multicolor brain size and brain size plasticity associated with hypoxia, indicating some level of both plastic and genetic adaptations to external stressors.

Another study testing the acute effects of turbidity on swimming performance found that golden shiner also performed better when tested under turbid conditions (Hildebrandt and

Parsons 2016). They attributed this to the hydrodynamics of the turbid water vs. clear water trial conditions. A number of hydrological studies have found a drag reduction and/or lower friction factor in waters with suspended clay sediments (Zandi 1967, Patterson et al. 1969, Chanson

1994, Li and Gust 2000); however, none have examined this in relation to the change in drag imposed on fishes or other relevant ecological processes.

Another possible explanation for fish having higher critical swimming speeds in turbid vs. clear water is that fish can exhibit both physiological exhaustion and behavioral fatigue

(Peake and Farrell 2006). Studies that used chase-tests to examine fish exhaustion found that swimming failure (and physiological exhaustion) corresponded with glycogen depletion and lactate accumulation in the white muscle, resulting from anaerobic metabolism (Kieffer 2000).

However, McFarlane and McDonald (2002) found that fatigue of rainbow trout in critical swimming speed experiments did not coincide with white muscle glycogen depletion, just a 32% reduction in ATP. Additionally, they observed repeatable results within individuals after very short periods of recovery, suggesting that fish were fatiguing as a mechanism to preserve energy stores. Peake and Farrell (2006) also explored this relationship and found that smallmouth bass

(Micropterus dolomieu) tested in critical swimming speed trials had significantly more white muscle glycogen than fish tested in chase trials. In another study, Peake and Farrell (2004) tested swimming performance in smallmouth bass in a confined respirometer and in unconfined experimental raceways. They found that fish in the experimental raceways could swim at speeds more than double that of the Ucrit determined in the closed respirometer. Therefore, Peake and

Farrell (2006) argue that the observed fatigue in swimming performance trials is a behavioral response and does not represent physiological exhaustion.

Previous research has found that fish respond behaviorally to elevated turbidity and attempt to avoid the plume by swimming to a different location (McLeay et al. 1987), while others have found that fish can become more active under turbid conditions (Gradall and

Swenson 1982). Since behavioral fatigue in critical swimming speed tests does not always coincide with physiological exhaustion (McFarlane and McDonald 2002, Peake and Farrell

2006), this might suggest that P. multicolor tested under acute turbidity were using up more of their energy stores to escape a stressful environment. Although Beamish (1978) outlined that anaerobic swimming was only maintainable for 10-20s, Peake and Farrell (2004) found that smallmouth bass could maintain unsteady, burst swimming speeds for approximately 50-70s.

Thus, it is possible that fish experiencing acute turbidity exposure could have utilized anaerobic mechanisms to push past the point of behavioral fatigue, which they exhibited in clear water trials. Unfortunately, much of this is outside the scope of this study, and additional research that investigates further physiological mechanisms (e.g. glycogen concentrations in both red and white muscle, additional swimming performance metrics) and behavior (e.g. duration of burst swimming) could better help us understand why P. multicolor exhibited increased performance during acute turbidity exposure.

4.3 Consequences of turbidity and diet for reproduction and survival

We found only minimal negative impacts on reproductive traits of P. multicolor due to chronic turbidity or diet. Interestingly, we found that at least one stressor seemed to impact traits that are directly related to fitness in each sex. For P. multicolor, each sex has a different parental investment. Males often have much less of an investment in rearing young (Trivers 1972) (as is the case for P. multicolor), so to increase reproductive success they must increase their number of offspring. Because this species relies on sexual selection for reproduction, two things a male could invest in to positively influence fitness include: 1. their sexual display and 2. their gonad development/spermatogenesis (both functions of male-male competition) (Wootton and Smith

2015). So, for males, coloration and GSI are important reproductive traits. Contrary to our predictions, our stressful treatments (chronic turbidity and trace-carotenoid diets) actually had a

68 positive impact on these traits. For male P. multicolor, exposure to turbidity over development increased male GSI, especially when paired with a trace-carotenoid diet. In fact, diet played a bigger role in male reproductive traits than female reproductive traits. We also found that trace- carotenoid diets seemed to positively influence male carotenoid coloration. This was opposite of what we expected, and we believe that it may have been an attempt of fish from trace-carotenoid treatments to increase their attractiveness and immediate reproduction vs. future reproduction.

Studies examining mate-choice under these laboratory conditions could better elucidate if these efforts did increase attractiveness to females. We know from Chapter 2 that turbid conditions can lead to diets lower in carotenoid content and, since previous research has shown that fish with low carotenoid diets are more susceptible to oxidative stress and senesce earlier (Pike et al.

2007), this could have lasting effects on wild populations experiencing chronic turbidity.

Females often have a very large investment in their offspring (Trivers 1972), which is also the case for mouthbrooding P. multicolor females. Being larger is an advantage and can positively influence fitness in two ways: 1. larger teleost fish tend to be more fecund and can lay more eggs (Gross and Sargent 1985), and 2. mouthbrooding is very costly, especially since females do not eat while brooding (~21 days) (reviewed in Reardon and Chapman 2010b), so they depend entirely on energy stored prior to reproduction (Mrowka and Schierwater 1988).

This energy contributes to female survival during brooding (i.e. ability to reproduce in the future)

(reviewed in Pike et al. 2007) and to care for young until they mature enough to survive on their own (Mrowka 1987), both of which contribute to fitness. So, for females, size is an important reproductive trait. For female P. multicolor, chronic turbidity did negatively impact overall size

(length and weight), which is often positively correlated with fecundity (Coates 1988, Buckley et

69 al. 1991, Morita and Takashima 1998). For example, the number of oocytes per female was found to increase with the size of Tilapia nilotica (another mouthbrooding species) (Babiker and

Ibrahim 1979). Although we did not directly measure female fecundity, we can postulate that female fecundity was negatively impacted by chronic turbidity, because females were smaller when reared in turbid conditions. Female GSI was not influenced by turbidity, but larger females tend to have larger ovaries overall, so female size could be used as a proxy for fecundity. More studies in the future could examine the effects of turbidity on the number of eggs and egg size to directly measure fecundity. If females are less fecund under turbid conditions, it could have negative impacts on P. multicolor populations experiencing chronic turbidity.

We also found that chronic turbidity did not affect the swimming performance of P. multicolor, but acute turbidity did. In fact, it unexpectedly increased the swimming performance of P. multicolor. The only other study we could find that tested fish under acute turbidity, also came to the same result with golden shiner. More research is needed to determine if this was due to water hydromechanics, differences in behavioral fatigue vs. physiological exhaustion, or adaptations to variable turbidity.

4.4 Conclusion

In many ways, this study has helped to emphasize that the impact of turbidity varies due to a number of circumstances such as concentration, duration of exposure, species, and sex

(reviewed in Kemp et al. 2011). Here we found that chronic and acute exposure to turbidity can have positive and negative impacts on the reproductive and survival traits of a tolerant, tropical fish species, but that these impacts can vary by sex and according to diet. Because of the contrasting results from this study with other studies, more research is necessary to fully

70 understand the impacts that turbidity can have on the physiology and behavior of aquatic organisms and how this can translate into population and community level dynamics.

References

Allan J. D., and Flecker A. S. 1993. Biodiversity conservation in running waters. Bioscience 43:32-43.

Babiker M. M., and Ibrahim H. 1979. Studies on the biology of reproduction in the cichlid Tilapia nilotica (L.): Gonadal maturation and fecundity. Journal of Fish Biology 14:437- 448.

Barton B. A. 1977. Short-term effects of highway construction on the limnology of a small stream in southern Ontario. Freshwater Biology 7: 99-108.

Barton B. A., and Schreck C. B. 1987. Metabolic cost of acute physical stress in juvenile steelhead. Transactions of the American Fisheries Society 116:257-263.

Bates D., Maechler M., Bolker B., Walker S. 2015. Fitting linear mixed-effects models using lme4. Journal of Statistical Software, 67, 1-48. https://cran.r-project.org/package=lme4

Beamish F. W. H., 1978. Swimming capacity. Pages 101-187 in: Hoar S., Randall, D. J. editors. Fish Physiology, vol. VII. Academic Press, New York.

Bell W. H., and Terhune L. D. B. 1970. Water tunnel design for fisheries research. Fisheries Research Board of Canada Technical Report 1-69.

Berg L., and Northcote T. G. 1985. Changes in territorial, gill-flaring, and feeding-behavior in juvenile coho salmon (Oncorhynchus kisutch) following short-term pulses of suspended sediment. Canadian Journal of Fisheries and Aquatic Sciences 42:1410-1417.

Blount J. D. 2004. Carotenoids and life-history evolution in animals. Archives of Biochemistry and Biophysics 430:10-15.

Bo T., Fenoglio S., Malacarne G., Pessino M., and Sgariboldi F. 2007. Effects of clogging on stream macroinvertebrates: An experimental approach. Limnologica 37:186-192.

Brett J. R. 1964. The Respiratory Metabolism and Swimming Performance of Young Sockeye Salmon. Journal of the Fisheries Research Board of Canada 21:1183-1226.

Buckley L. J., Smigielski A. S., Halavik T. A., Caldarone E. M., Burns B. R., and Laurence G. C. 1991. Winter flounder Pseudopleuronectes americanus reproductive success. II. Effects of spawning time and female size on size, composition and viability of eggs and larvae. Marine Ecology Progress Series 74:125-135.

Carlson R. W. 1984. The influence of pH, dissolved oxygen, suspended solids or dissolved solids upon ventilatory and cough frequencies in the bluegill Lepomis machrochirus and brook 72

trout Salvelinus fantinalis. Environmental Pollution Series a-Ecological and Biological 34:149-169.

Chanson H. 1994. Drag reduction in open channel flow by aeration and suspended load. Journal of Hydraulic Research 32: 87-101.

Chew B. P., and Park J. S. 2004. Carotenoid action on the immune response. Journal of Nutrition 134:257S-261S.

Coates D. 1988. Length-dependent changes in egg size and fecundity in females, and brooded embryo size in males, of fork-tailed catfishes (Pisces: Ariidae) from the Sepik River, Papua New Guinea, with some implications for stock assessments. Journal of Fish Biology 33:455-464.

Collin S. P., and Hart N. S. 2015. Vision and photoentrainment in fishes: the effects of natural and anthropogenic perturbation. Integrative Zoology 10:15-28.

Cooperstone J. L., Ralston R. A., Riedl K. M., Haufe T. C., Schweiggert R. M., King S. A., Timmers C. D., Francis D. M., Lesinski G. B., Clinton S. K., and Schwartz S. J. 2015. Enhanced bioavailability of lycopene when consumed as cis-isomers from tangerine compared to red tomato juice, a randomized, cross-over clinical trial. Molecular Nutrition & Food Research 59:658-669.

Crispo E., and Chapman L. J. 2010. Geographic variation in phenotypic plasticity in response to dissolved oxygen in an African cichlid fish. Journal of Evolutionary Biology 23:2091- 2103. 73

Dynesius M., and Nilsson C. 1994. Fragmentation and flow regulation of river systems in the northern 3rd of the world. Science 266:753-762.

Fox H. M., Vevers G., 1960. The Nature of Animal Colors. Macmillan, New York.

Gardner M. B. 1981. Effects of turbidity on feeding rates and selectivity of bluegills. Transactions of the American Fisheries Society 110:446-450.

Gotanda K. M., Reardon E. E., Murphy S. M. C., and Chapman L. J. 2012. Critical swim speed and fast-start response in the African cichlid Pseudocrenilabrus multicolor victoriae: convergent performance in divergent oxygen regimes. Canadian Journal of Zoology 90:545-554.

Gradall K. S., and Swenson W. A. 1982. Responses of brook trout and creek chubs to turbidity. Transactions of the American Fisheries Society 111:392-395.

Gray S. M., Bieber F. M. E., McDonnell L. H., Chapman L. J., and Mandrak N. E. 2014. Experimental evidence for species-specific response to turbidity in imperiled fishes. Aquatic Conservation-Marine and Freshwater Ecosystems 24:546-560.

Greenwood P. H. 1965. The cichlid fishes of Lake Nabugabo, Uganda. Bulletin of British Museum of Natural History (Zool.) 12:313–357.

Grether G. F., Kolluru G. R., Rodd F. H., de la Cerda J., and Shimazaki K. 2005. Carotenoid availability affects the development of a colour-based mate preference and the sensory 74

bias to which it is genetically linked. Proceedings of the Royal Society B: Biological Sciences 272:2181-2188.

Gross M. R., and Sargent R. C. 1985. The evolution of male and female parental care in fishes. American Zoologist 25:807-822.

Hammer C. 1995. Fatigue and exercise tests with fish. Comparative Biochemistry and Physiology A- Molecular & Integrative Physiology 112:1-20.

Hart R. C. 1992. Experimental studies of food and suspended sediment effects on growth and reproduction of 6 planktonic cladocerans. Journal of Plankton Research 14:1425-1448.

Henley W. F., Patterson M. A., Neves R. J., and Lemly A. D. 2000. Effects of sedimentation and turbidity on lotic food webs: A concise review for natural resource managers. Reviews in Fisheries Science 8:125-139.

Herbert D. W. M., and Merkens J. C. 1961. The effect of suspended mineral solids on the survival of trout. International Journal of Air and Water Pollution 5:46-55.

Hildebrandt E. K., and Parsons G. R. 2016. Effect of turbidity on the swimming performance of the golden shiner, Notemigonus crysoleucas. Copeia 104:752-755.

Kemp P., Sear D., Collins A., Naden P., and Jones I. 2011. The impacts of fine sediment on riverine fish. Hydrological Processes 25:1800-1821.

Kieffer J. D. 2000. Limits to exhaustive exercise in fish. Comparative Biochemistry and Physiology A-Molecular and Integrative Physiology 126:161-179.

Kiokias S., and Gordon M. H. 2004. Antioxidant properties of carotenoids in vitro and in vivo. Food Reviews International 20:99-121.

Kopec R. E., Cooperstone J. L., Schweiggert R. M., Young G. S., Harrison E. H., Francis D. M., Clinton S. K., and Schwartz S. J. 2014. Avocado consumption enhances human postprandial provitamin A absorption and conversion from a novel high-beta-carotene tomato sauce and from carrots. Journal of Nutrition 144:1158-1166.

Krinsky N. I. 1989. Antioxidant functions of carotenoids. Free Radical Biology and Medicine 7:617-635.

Li M. Z., and Gust G. 2000. Boundary layer dynamics and drag reduction in flows of high cohesive sediment suspensions. Sedimentology 47:71-86.

Maan M. E., Seehausen O., Söderberg L., Johnson L., Ripmeester E. A. P., Mrosso H. D. J., Taylor M. I., van Dooren T. J. M., and van Alphen J. J. M. 2004. Intraspecific sexual selection on a speciation trait, male coloration, in the Lake Victoria cichlid Pundamilia nyererei. Proceedings: Biological Sciences 271:2445-2452.

Martinez M. L., Chapman L. J., and Rees B. B. 2009. Population variation in hypoxic responses of the cichlid Pseudocrenilabrus multicolor victoriae. Canadian Journal of Zoology 87:188-194.

McDonnell L. H., and Chapman L. J. 2016. Effects of thermal increase on aerobic capacity and swim performance in a tropical inland fish. Comparative Biochemistry and Physiology A-Molecular & Integrative Physiology 199:62-70.

McFarlane W. J., and McDonald D. G. 2002. Relating intramuscular fuel use to endurance in juvenile rainbow trout. Physiological and Biochemical Zoology 75:250-259.

McLeay D. J., Birtwell I. K., Hartman G. F., and Ennis G. L. 1987. Responses of arctic grayling (Thymallus arcticus) to acute and prolonged exposure to Yukon placer mining sediment. Journal of Fisheries and Aquatic Sciences 44:658-673.

McNeil G. V., Friesen C. N., Gray S. M., Aldredge A., and Chapman L. J. 2016. Male colour variation in a eurytopic African cichlid: The role of diet and hypoxia. Biological Journal of the Linnean Society 118:551-568.

Morita K., and Takashima Y. 1998. Effect of female size on fecundity and egg size in white- spotted charr: comparison between sea-run and resident forms. Journal of Fish Biology 53:1140-1142.

Mrowka W. 1987. Filial cannibalism and reproductive success in the maternal mouthbrooding cichlid fish Pseudocrenilabrus multicolor. Behavioral Ecology and Sociobiology 21:257- 265.

Mrowka W., and Schierwater B. 1988. Energy expenditure for mouthbrooding in a cichlid fish. Behavioral Ecology and Sociobiology 22:161-164.

Newcombe C. P., and Macdonald D. D. 1991. Effects of suspended sediments on aquatic ecosystems. North American Journal of Fisheries Management 11:72-82.

Olson V. A. 2006. Estimating nutrient intake in comparative studies of animals: An example using dietary carotenoid content in birds. Oikos 112:620-628.

Ozaki Y., Higuchi, M., Miura, C., Yamaguchi, S., Tozawa, Y., and Miura, T. 2006. Roles of 11b-hydroxysteroid deheydrogenase in fish spermatogenesis. Endocrinology 147:5139–5146.

Patterson G. K., Zakin J. L., and Rodriguez J. M. 1969. Drag reduction: Polymer solutions, soap solutions, and solid particle suspensions in pipe flow. Industrial and Engineering Chemistry 61:22-30.

Peake S. J., and Farrell A. P. 2004. Locomotory behaviour and post-exercise physiology in relation to swimming speed, gait transition and metabolism in free-swimming smallmouth bass (Micropterus dolomieu). Journal of Experimental Biology 207:1563- 1575.

Peake S. J., and Farrell A. P. 2006. Fatigue is a behavioural response in respirometer-confined smallmouth bass. Journal of Fish Biology 68:1742-1755.

Pickering A. D. 1993. Growth and stress in fish production. Aquaculture 111:51-63.

Pike T. W., Blount J. D., Bjerkeng B., Lindstrom J., and Metcalfe N. B. 2007. Carotenoids, oxidative stress and female mating preference for longer lived males. Proceedings of the Royal Society B-Biological Sciences 274:1591-1596.

Plaut I. 2001. Critical swimming speed: Its ecological relevance. Comparative Biochemistry and Physiology A-Molecular and Integrative Physiology 131:41-50.

R Core Team. 2018. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.

Reardon E. E., and Chapman L. J. 2009. Hypoxia and life-history traits in a eurytopic African cichlid. Journal of Fish Biology 75:1795-1815.

Reardon E. E., and Chapman L. J. 2010a. Energetics of hypoxia in a mouth-brooding cichlid: evidence for interdemic and developmental effects. Physiological and Biochemical Zoology 83:414-423.

Reardon E. E., and Chapman L. J. 2010b. Hypoxia and energetics of mouth brooding: Is parental care a costly affair? Comparative Biochemistry and Physiology a-Molecular & Integrative Physiology 156:400-406.

Redding J. M., Schreck C. B, and Everest F. H. 1987. Physiological effects on coho salmon and steelhead of exposure to suspended solids. Transactions of the American Fisheries Society 116:737-744. 77

Roche D. G., Binning S. A., Bosiger Y., Johansen J. L., and Rummer J. L. 2013. Finding the best estimates of metabolic rates in a coral reef fish. Journal of Experimental Biology 216:2103-2110.

Schreck C. B. 2010. Stress and fish reproduction: The roles of allostasis and hormesis. General and Comparative Endocrinology 165:549-556.

Schreck C. B., Tort L., Farrell A., and Brauner C. J. 2016. Biology of stress in fish. Academic Press-Elsevier, London.

Shankar D. S., Kulkarni R. S., 2000. Effect of cortisol on testis of freshwater fish Notopterus notopterus (Pallas). Indian Journal of Experimental Biology 38, 1227–1230.

Shaw E. A., and Richardson J. S. 2001. Direct and indirect effects of sediment pulse duration on stream invertebrate assemblages and rainbow trout (Oncorhynchus mykiss) growth and survival. Canadian Journal of Fisheries and Aquatic Sciences 58:2213-2221.

Sprague J. B. 1971. Measurement of pollutant toxicity to fish. III. Sublethal effects and “safe” concentrations. Water Res. 5:245-266.

Sutherland A., and Meyer J. 2007. Effects of increased suspended sediment on growth rate and gill condition of two southern Appalachian minnows. Environmental Biology of Fishes 80:389-403.

Svensson P. A., and Wong B. B. M. 2011. Carotenoid-based signals in behavioural ecology: a review. Behaviour 148:131-189.

Trivers R. 1972. Parental investment and sexual selection. Pages 136-179 in Campbel B. G., editor. Sexual Selection and the Descent of Man 1871-1971. Aldine Pub. Co, Chicago, Illinois. van der Sluijs I., Gray S. M., Amorim M. C. P., Barber I., Candolin U., Hendry A. P., Krahe R., Maan M. E., Utne-Palm A. C., Wagner H.J., and Wong B. B. M. 2011. Communication

in troubled waters: Responses of fish communication systems to changing environments. Evolutionary Ecology 25:623-640.

Vogel J. L., and Beauchamp D. A. 1999. Effects of light, prey size, and turbidity on reaction distances of lake trout (Salvelinus namaycush) to salmonid prey. Canadian Journal of Fisheries and Aquatic Sciences 56:1293-1297.

Vogel S., and Labarbera M. 1978. Simple flow tanks for research and teaching. Bioscience 28:638-643.

Wenger A. S., Johansen J. L., and Jones G. P. 2012. Increasing suspended sediment reduces foraging, growth and condition of a planktivorous damselfish. Journal of Experimental Marine Biology and Ecology 428:43-48.

Wilber D. H., and Clarke D. G. 2001. Biological effects of suspended sediments: A review of suspended sediment impacts on fish and shellfish with relation to dredging activities in estuaries. North American Journal of Fisheries Management 21:855-875.

Wong B. B. M., Candolin U., and Lindstrom K. 2007. Environmental deterioration compromises socially enforced signals of male quality in three-spined sticklebacks. American Naturalist 170:184-189.

Wong C. K., Pak I. A. P., and Liu X. J. 2013. Gill damage to juvenile orange-spotted grouper Epinephelus coioides (Hamilton, 1822) following exposure to suspended sediments. Aquaculture Research 44:1685-1695.

Wootton R. J., and Smith C. 2015. Reproductive biology of teleost fish. John Wiley and Sons, Ltd., Blackwell, London.

Zandi I. 1967. Decreased head losses in raw-water conduits. Journal - American Water Works Association 59:213-226.

Tables

Table 3.1. Male reproductive traits across rearing treatments (mean ± 1 SE).

Treatment n SL (cm) Weight (g) Color GSI High Turbidity 8 4.30 ± 0.25 2.47 ± 0.42 0.002 ± 0.0006 0.36 ± 0.05 Low Carotenoid

Low Turbidity 4 4.25 ± 0.33 3.57 ± 0.60 0.001 ± 0.0003 0.29 ± 0.06 Low Carotenoid

High Turbidity 9 4.70 ± 0.21 3.05 ± 0.34 0.030 ± 0.0176 0.55 ± 0.04 Trace Carotenoid

Low Turbidity 3 4.67 ± 0.44 3.14 ± 0.69 0.003 ± 0.0017 0.26 ± 0.11 Trace Carotenoid

Table 3.2. Female reproductive traits across rearing treatments (mean ± 1 SE).

Treatment n SL (cm) Weight (g) Color GSI High Turbidity 22 3.57 ± 0.10 1.39 ± 0.12 0.003 ± 0.0012 3.53 ± 0.56 Low Carotenoid

Low Turbidity 20 3.79 ± 0.09 1.67 ± 0.10 0.003 ± 0.0018 2.56 ± 0.52 Low Carotenoid

High Turbidity 20 3.62 ± 0.10 1.43 ± 0.13 0.001 ± 0.0002 2.65 ± 0.68 Trace Carotenoid

Low Turbidity 21 3.91 ± 0.11 1.89 ± 0.15 0.003 ± 0.0008 2.23 ± 0.41 Trace Carotenoid

Table 3.3. Swimming performance across rearing treatment and trial conditions (mean ± 1 SE).

Treatment n BL/s Reared High Turbidity 20 11.01 ± 0.45 Tested Low Turbidity

Reared Low Turbidity 20 11.14 ± 0.74 Tested Low Turbidity

Reared High Turbidity 20 12.34 ± 0.64 Tested High Turbidity

Reared Low Turbidity 20 13.16 ± 0.63 Tested High Turbidity

Figures

Figure 3.1. Experimental swimming performance chamber. A pump was used to maintain water flow throughout the chamber. Water was first passed through a 3.8 L plastic reservoir and a baffle of straws before reaching the swimming chamber made of clear PVC. The end of the swimming tunnel was covered with mesh to confine the fish to the swimming chamber.

Figure 3.2. Mean a) male coloration (± 1 SE) across turbidity treatment, split by trace (black) and low (grey) carotenoid diets. b) Regression of male standard length and male carotenoid coloration, with regression lines and color split between diet treatment. Shapes refer to high

(circle) and low (triangle) turbidity treatments c) Mean male GSI (± 1 SE %) across turbidity treatment, split by trace and low carotenoid diets. d) Regression of male GSI and male coloration, with regression line pooled across all treatments.

Figure 3.3 a) Mean female SL (± 1 SE cm) across turbidity treatment, split by trace (black) and low (grey) carotenoid diets. b) Mean female weight (± 1 SE g) across turbidity treatment, split by trace and low carotenoid diets.

Figure 3.4 a) Swimming performance results of each individual fish tested under high and low turbidity trial conditions, split by high (brown circle) and low (blue triangle) turbidity rearing treatments. Black points refer to mean speed for each trial condition pooled across rearing treatment. b) Mean swimming performance (± 1 SE BL/s) across trial condition, split by high

(brown) and low (blue) turbidity rearing treatments.

Chapter 4

Discussion

In an increasingly variable world, the ability for animals to respond rapidly to environmental disturbance can be critical for survival (Hendry et al. 2008). Because extinction rates are higher in tropical systems (Dudgeon et al. 2006), we chose to focus on a tropical

African cichlid which can be found naturally across a number of stressful environments including low dissolved oxygen and high suspended sediments (Reardon and Chapman 2009,

McNeil et al. 2016). In this study, we investigated how a common stressor, turbidity (which can be influenced by human activity), could affect the diet, and reproductive and survival traits of P. multicolor.

In chapter 2, we found evidence of within-population variation in wild male nuptial coloration across varying levels of turbidity, despite relatively high overlap in diet, and no difference in available invertebrate communities. This could indicate that P. multicolor’s nuptial coloration is a plastic trait and can respond to environmental stressors such as turbidity. By altering their coloration, male P. multicolor may remain conspicuous for female conspecifics to facilitate mate-choice. If it is a plastic trait associated with an environmental stressor, there is potential for a genes-as-followers effect leading to a shift in allele frequencies associated with more adaptive phenotypes (West-Eberhard 2003). Alternatively, P. multicolor could be relaxing their signal to allocate costly carotenoid resources towards other physiological functions because 87 of elevated stress or individual health reasons (Olson and Owens 1998). This could cause a mating system breakdown and potentially lead to hybridization between P. multicolor and other closely related haplochromine cichlids, which has been documented in other cichlid species under turbid condition in Lake Victoria (Seehausen et al. 2008). This could have community level consequences in tropical systems.

Some potential next steps for this this research include investigating stable isotope data to address longer-term diet analyses. This would be most useful over both large and small spatial scales and across a number of environmental conditions. The results from a study of this nature could help guide future laboratory experiments. For example, rearing experiments assessing the effects of alternative, ecologically relevant diets (algae/plant-based vs. invertebrate based) in combination with turbidity and/or other environmental variables (e.g. temperature, tannins) could help to tease apart the mechanisms driving variation in male P. multicolor nuptial coloration.

Ideally, it would be nice to perform these experiments on both wild-caught fish and reared F1 offspring across multiple populations to test for genetic and plastic components. Additionally, pairing these tests with physiological and behavioral tests can help to shed light on the mechanisms responsible for observed variation; for example, investigating the concentrations and allocation of carotenoids within the body and skin of P. multicolor found across environmental gradients. This would give us a more accurate measurement of carotenoid coloration across environmental extremes and allow us to determine if populations are investing carotenoids into different physiological mechanisms and at what proportions. Behaviorally, mate-choice experiments in both clear and turbid conditions, between populations, could help us determine if females prefer their home color variant or prefer redder males, overall.

In chapter 3, we found evidence of variation in reproductive traits of both male and female lab-reared, F1 P. multicolor associated with high and low turbidity and low and trace carotenoid diets. The reproductive traits affected by these stressors varied across sexes, with male coloration and GSI, and female size, being impacted. Interestingly, male coloration and

GSI were positively influenced by more stressful treatments (chronic turbidity and trace carotenoid diets). As discussed earlier, this could point to a hormetic effect in that low levels of a stressor may have a positive effect, while higher levels of the stressor may have a differing effect

(Schreck 2010). It could also indicate that male fish were investing more in immediate reproduction vs. future reproduction and health. Alternatively, we found that female size was negatively influenced by chronic turbidity. We think that this was caused by decreased reaction distance and ability to forage efficiently under chronic turbidity, as has been seen in other species

(Wenger et al. 2012). Additionally, we found that swimming performance was improved by acute turbidity exposure, regardless of turbidity rearing treatment. The mechanism for this is unknown, but two possible scenarios include: 1) that this population of fish has an adaptation to perform better in turbid conditions or 2) that we witnessed behavioral fatigue in clear swimming performance trials.

Some potential next steps for this this research include additional rearing experiments examining the effects of environmental stressors (e.g. turbidity, temperature) and diet on organismal physiology and behavior. For example, investigating stress hormones (e.g. cortisol) across treatments in the laboratory could help to elucidate if turbidity or diet cause an endocrine stress response in P. multicolor. Here, I drew from research conducted on other species that high turbidity and trace-carotenoid diets can cause stress in fishes, but tests on P. multicolor

89 examining stress hormones would help remove speculation. This could help to determine if a stress response is what potentially caused differences in reproductive traits across treatments. I’m also very intrigued by the findings from Pike et al. (2007), which examined susceptibility to oxidative stress. A study examining the oxidative stress of P. multicolor reared using low and high carotenoid diets (or plant/algae-based and invertebrate-based diets) combined with turbidity would be a great measure of the trade-offs between reproduction and other physiological functions (important for survival) that depend on carotenoids. This could be combined with High

Performance Liquid Chromatography to examine the concentrations on carotenoids in the skin vs. other organs of P. multicolor. Furthermore, I think additional swimming performance experiments should be performed after chronic exposure to varying levels of turbidity and at varying levels of acute turbidity. These tests should be paired with physiological tests examining muscle glycogen levels, and an analysis of swimming behavior, once burst swimming speeds begin, to be able to determine mechanisms behind variation in swimming performance.

This research helped to improve our knowledge of the effects of turbidity and diet on the reproductive traits and swimming performance of P. multicolor, however much more research is needed to understand the effects stressors can have on tropical fish species. This study has helped to emphasize that the impact of turbidity varies due to a number of circumstances such as concentration, duration of exposure, species, and sex. By further investigating the effects of turbidity as a stressor on traits associated with reproduction and survival of a fish naturally found across both extremes, we can further our understanding of the mechanisms that contribute to the persistence of fish facing human-induced environmental changes.