Science, Faculty of
Zoology, Department of
DSpace
UBCV
Kinney, Mackenzie
Doctor of Philosophy - PhD
University of British Columbia
Hybridization is the process of interbreeding between distinct genomic lineages. Environmental disturbances have been associated with increased hybridization between previously non-interbreeding lineages, suggesting that the production and survival of hybrids is influenced by the ecological conditions in which they occur. However, our understanding of hybridization, hybrid evolution, and the impact of natural selection on hybrid populations is limited compared to that of parent species. To address these gaps, my dissertation focused on investigating the effects of environmental changes on hybrid production and fitness, and the mechanisms driving the evolution of hybrid populations. Threespine stickleback fish served as a model for my thesis as they have diverged at least five times to form limnetic and benthic species capable of producing viable hybrid offspring. These species exhibit strong reproductive isolation and low hybrid fitness under natural conditions, but collapse into a hybrid swarm has been observed once in nature. In Chapter 2, I conducted experiments manipulating pond conditions to examine if eutrophication would disrupt reproductive isolation and influence hybrid survival as a consequence of reduced visibility and an altered ecological fitness landscape. Although our treatment did not appear to affect hybrid production or survival, we nonetheless observed an increase in hybrids independent of the treatment, highlighting the fragility of reproductive isolation in ecologically specialized species. In Chapter 3, inspired by the collapse of stickleback species in Enos Lake, I examined the fitness of F1 hybrids in the presence of crayfish. We observed a slight, but non-significant improvement in relative hybrid fitness as a consequence of changes in parent fitness. Chapter 4 focused on the evolution of three wild stickleback hybrid populations with varying proportions of parental ancestry inhabiting similar environments. We found parallel evolution in both genotypic and phenotypic traits across the hybrid populations, regardless of their ancestry, providing evidence for the significant role of ecological selection in shaping these populations. In summary, my dissertation sheds light on the crucial role of ecological context in mediating the outcomes of hybridization and emphasizes the need to improve our understanding of this process and its implications on the evolution and persistence of hybrid populations.
ENVIRONMENTAL IMPACTS ON HYBRIDIZATION OUTCOMES by Mackenzie Kinney B.Sc., The University of Waterloo, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate and Postdoctoral Studies (Zoology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2023 © Mackenzie Kinney, 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Environmental Impacts on Hybridization Outcomes Submitted by Mackenzie Kinney in partial fulfilment of the requirements for forfor the degree of Doctor of Philosophy in Zoology Examining Committee: Dolph Schluter, Professor, Zoology, UBC Supervisor Darren Irwin, Professor, Zoology, UBC Supervisory Committee Member Catherine Wagner, Associate Professor, Botany, University of Wyoming External Examiner Amy Angert, Professor, Botany & Zoology, UBC University Examiner John Richardson, Professor, Forest and Conservation Sciences, UBC University Examiner Additional Supervisory Committee Members: Loren Rieseberg, Professor, Botany, UBC Supervisory Committee Member Mary O’Connor, Professor, Zoology, UBC Supervisory Committee Member iii Abstract Hybridization is the process of interbreeding between distinct genomic lineages. Environmental disturbances have been associated with increased hybridization between previously non-interbreeding lineages, suggesting that the production and survival of hybrids is influenced by the ecological conditions in which they occur. However, our understanding of hybridization, hybrid evolution, and the impact of natural selection on hybrid populations is limited compared to that of parent species. To address these gaps, my dissertation focused on investigating the effects of environmental changes on hybrid production and fitness, and the mechanisms driving the evolution of hybrid populations. Threespine stickleback fish served as a model for my thesis as they have diverged at least five times to form limnetic and benthic species capable of producing viable hybrid offspring. These species exhibit strong reproductive isolation and low hybrid fitness under natural conditions, but collapse into a hybrid swarm has been observed once in nature. In Chapter 2, I conducted experiments manipulating pond conditions to examine if eutrophication would disrupt reproductive isolation and influence hybrid survival as a consequence of reduced visibility and an altered ecological fitness landscape. Although our treatment did not appear to affect hybrid production or survival, we nonetheless observed an increase in hybrids independent of the treatment, highlighting the fragility of reproductive isolation in ecologically specialized species. In Chapter 3, inspired by the collapse of stickleback species in Enos Lake, I examined the fitness of F1 hybrids in the presence of crayfish. We observed a slight, but non-significant improvement in relative iv hybrid fitness as a consequence of changes in parent fitness. Chapter 4 focused on the evolution of three wild stickleback hybrid populations with varying proportions of parental ancestry inhabiting similar environments. We found parallel evolution in both genotypic and phenotypic traits across the hybrid populations, regardless of their ancestry, providing evidence for the significant role of ecological selection in shaping these populations. In summary, my dissertation sheds light on the crucial role of ecological context in mediating the outcomes of hybridization and emphasizes the need to improve our understanding of this process and its implications on the evolution and persistence of hybrid populations. v Lay Summary Hybridization occurs when individuals from different species or populations mate and produce offspring. Hybridization is becoming more common, but the reasons why we see an increase in breeding between different species, and the outcomes of increased hybrid offspring survival in nature, are poorly understood. Using threespine stickleback fish as a model species, this thesis aims to study how environmental changes affect the production and evolution of offspring after species hybridize. We use a combination of experiments and observations to study hybrid populations at different stages: before hybrid formation, early generation hybrids, and long-term populations. By looking at these different timepoints, we hope to learn more about the complex processes involved in hybridization and how the environment influences the evolution and persistence of hybrid populations. My thesis improves our understanding of the fragility of species boundaries and how natural selection acts on different hybrid traits. vi Preface For Chapter 2, S. Rudman, D. Schluter and I conceived of the research questions. S. Rudman conceived of and carried out the experiment, and collected raw ecosystem data. I collected phenotypic and genotypic data from stickleback. K. Nikiforuk assisted with DNA quality control prior to sequencing. I analyzed all data with input from D. Schluter and wrote the manuscript. D. Schluter contributed to editing the manuscript. For Chapter 3, D. Schluter and I conceived of the project. S. Blain and I carried out the experiment and collected data. I analyzed the data with input from D. Schluter. I wrote the manuscript with input and editing from D. Schluter. For Chapter 4, D. Schluter and I conceived of the project. K. Chu and I collected present day specimens. All past specimens are from the Schluter Lab “Museum”. Photos of Paxton F2 fish are from G. Conte and M. Arnegard. I collected all data and performed all DNA extractions. F. Jones performed DNA library prep. I performed data analysis with assistance from S. Blain, K.P. Lin and D. Schluter. I wrote the manuscript with contributions from D. Schluter editing the manuscript. Animal care protocols were approved by the UBC animal care committee (A16-0044). Permits for sampling fish were obtained from the British Columbia Ministry for the Environment (NA-SU13-85151, SU17-258923, MRSU18-288855, SU18-322316, SU21-618979) and Fisheries and Oceans Canada SARA (17-PPAC-00002, 18-PPAC-00006, 18-PPAC-00007, 21-PPAC-00008, 21-PPAC-00009). vii Table of Contents Abstract ...................................................................................................................... iii Lay Summary ............................................................................................................... v Preface...………………………………………………………………...…………………………………………………..vi Table of Contents ...................................................................................................... vii List of Tables .............................................................................................................. xi List of Figures ............................................................................................................ xii List of Abbreviations ................................................................................................ xiii Acknowledgements .................................................................................................... xv Dedication……………………………………………………………………………………………………………….xvii Chapter 1: Introduction ............................................................................................... 1 1.1 Hybridization following environmental disturbance ................................................... 1 1.2 Hybrid fitness in a novel environmental context .................................................... 4 1.3 Study system ............................................................................................................... 7 1.4 Thesis overview .......................................................................................................... 9 1.4.1 Chapter 2 ................................................................................................................. 9 1.4.2 Chapter 3 ................................................................................................................ 10 1.4.3 Chapter 4 ................................................................................................................. 11 Chapter 2: An experimental test of eutrophication impacts on reproductive isolation ..................................................................................................................... 13 2.1 Introduction ............................................................................................................... 13 2.2 Methods ..................................................................................................................... 17 viii 2.2.1 Experimental design .............................................................................................. 17 2.2.2 Measuring ecosystem responses to nutrient addition ....................................... 20 2.2.3 Genotyping ............................................................................................................. 21 2.2.4 Estimating hybrid proportions ......................................................................... 23 2.2.5 Analysis of ecosystem impacts on hybridization ................................................ 25 2.3 Results ....................................................................................................................... 26 2.3.1 Ecosystem responses to nutrient addition ......................................................... 26 2.3.2 Influence of treatment and overwinter survival on hybrid proportion ........... 28 2.3.3 Hybrid proportion – ecosystem characteristic associations ............................. 29 2.4 Discussion .................................................................................................................. 31 Chapter 3: Experimental test of species collapse via altered hybrid fitness following biological invasion .................................................................................... 39 3.1 Introduction .............................................................................................................. 39 3.2 Methods .................................................................................................................... 45 3.2.1 Study populations ................................................................................................. 45 3.2.2 Mesocosm construction and experimental design ............................................ 46 3.2.3 Benthic invertebrate and zooplankton sampling and analysis ......................... 47 3.2.4 Growth and survival estimates ............................................................................ 49 3.2.5 Tests of selection .................................................................................................. 50 3.3 Results ........................................................................................................................ 51 3.3.1 Invertebrate biomass response ............................................................................. 51 3.3.2 Fish survival ........................................................................................................... 52 ix 3.3.3 Growth .................................................................................................................... 53 3.4 Discussion .................................................................................................................. 57 Chapter 4: When two become one: Evolution after hybridization .......................... 64 4.1 Introduction .............................................................................................................. 64 4.2 Methods .................................................................................................................... 70 4.2.1 Study populations ................................................................................................. 70 4.2.2 Specimen sampling ............................................................................................ 72 4.2.3 Phenotyping ........................................................................................................... 73 4.2.4 Phenotype analysis ........................................................................................... 76 4.2.5 Genotyping ......................................................................................................... 77 4.2.6 Principal component analysis .......................................................................... 79 4.2.7 Allele frequency changes ................................................................................. 80 4.3 Results ....................................................................................................................... 83 4.3.1 Phenotypic changes over time ............................................................................. 83 4.3.2 Genotypic changes over time .............................................................................. 89 4.4 Discussion ................................................................................................................ 100 Chapter 5: Conclusions ............................................................................................. 111 5.1 Fragility of ecological speciation .............................................................................. 111 5.2 Hybrid persistence in a novel ecological context .................................................. 114 5.3 Phenotypic hybrid evolution across time ............................................................... 116 5.4 Genomic parallel evolution of hybrids ................................................................... 118 5.5 Closing thoughts ..................................................................................................... 120 x Bibliography .............................................................................................................. 122 Appendices ............................................................................................................... 142 Appendix A - Supplementary Material for Chapter 2 ...................................................... 142 A.1 Phenol-Chlorofom Based DNA Isolation for Stickleback DNA ....................... 142 A.2 PCA cluster for stickleback classification. ......................................................... 144 A.3 Chlorophyll A concentration at 4m depth. ....................................................... 145 A.4 Light extinction changes during active nutrient addition. .............................. 146 A.5 Oxygen concentration during active nutrient addition. .................................. 147 A.6 Relationship of population estimate with treatment and hybrid proportion……………………………………………………………………….……………….………………………148 A.7 Proportion of hybrids remaining after overwinter survival ............................. 149 A.8 Hybrid proportion predicted by chlorophyll A concentration. ....................... 150 A.9 Hybrid proportion predicted by light availability .............................................. 151 A.10 Hybrid proportion predicted by oxygen availability. ....................................... 152 Appendix B Supplementary Material for Chapter 3 ......................................................... 153 B.1 Density dependant fish growth .......................................................................... 153 Appendix C Supplementary Material for Chapter 4 ......................................................... 154 C.1 Changes in hybrid index across individual chromosomes ............................... 154 xi List of Tables Table 4. 1: Stickleback specimens used in analysis.. ............................................................... 73 Table 4. 2: Description of the landmark positions ................................................................. 75 Table 4. 3: Changes in meristic trait values across populations.. ......................................... 89 Table 4. 4: Hybrid index value on each chromosome for each hybrid population.. ........... 94 Table 4. 5: Pearson’s correlation coefficient. ......................................................................... 95 Table 4. 6: Number of mapped phenotypic QTL per chromosome……..…………………………...98 xii List of Figures Figure 2. 1 : Experimental ponds used in study.. ..................................................................... 18 Figure 2. 2: Schematic illustrating experimental timeline and design ................................. 20 Figure 2. 3: Chlorophyll A concentration at 1m depth.. ......................................................... 27 Figure 2. 4: PAR and oxygen reduction during active nutrient addition ............................. 28 Figure 2. 5: Hybrid proportion in individual ponds .............................................................. 30 Figure 3. 1: Natural log-transformed invertebrate biomass at the end of the experiment….52 Figure 3. 2: Stickleback survival by treatment.. ...................................................................... 53 Figure 3. 3:Growth changes by treatment and cross type. ..................................................... 55 Figure 3. 4: Fish growth in relation to fish density ................................................................ 56 Figure 4. 1: A) Map of populations of interest. Priest, Paxton and Little Quarry Lakes. B) Morphological representations………………………………………………………………….........................71 Figure 4. 2: Landmark position (description in Table 2). ...................................................... 75 Figure 4. 3 : Density plot of changes in shape morphology over time.. ............................... 85 Figure 4. 4: Changes in meristic trait values over time. ...................................................... 86 Figure 4. 5: Changes in gill raker number within Enos Lake. ............................................... 87 Figure 4. 6: PCA plot of whole genome SNP variation. .......................................................... 91 Figure 4. 7: Changes in hybrid index across individual chromosomes based on SNP allele frequencies. Chromosomes I, IV, VII, XV, XX and XXI are shown.. ................................... 93 Figure 4. 8: Hybrid index (A) and change in hybrid index between time points (B and C) as a function of the number of diagnostic SNPs per 50Kbp window. ...................................... 99 xiii List of Abbreviations ANOVA – Analysis of Variance BC – British Columbia ChlA - Chlorophyll A ddRAD – Double Digest Restriction-site Associated DNA DMI - Dobzhansky-Muller Incompatibility DNA - Deoxyribose Nucleic Acid FS - Fisher Strand GATK – Genome Analysis Tool Kit GBS - Genotyping by Sequencing GQ - Genotype quality HZAM – Hybrid Zone with Assortative Mating LDA – Linear discriminant analysis LD - Linkage Disequilibrium LOESS - Locally Estimated Scatterplot Smoothing Mbp - Megabase pair MS-222 - Tricaine Methanesulfonate MQ – Mapping Quality P – Adult Parental Generation PAR - Photosynthetically Active Radiation PC1 – Principal Component 1 PC2 – Principal Component 2 xiv PCA – Principal Component Analysis PCR – Polymerase Chain Reaction P1 - First-generation Offspring P2 – Second-generation Offspring QD – Quality By Depth QTL – Quantitative Trait Locus SNP – Single Nucleotide Polymorphism SOR – Strand Odds Ratio xv Acknowledgements I am truly overwhelmed by how fortunate I am to have so many people to thank. Firstly, I need to thank my supervisor, Dolph Schluter. No words can encompass my endless gratitude for your support and guidance. You have made me an immeasurably better researcher, changed the way I think and interact with the world, supported me in my lowest moments, and celebrated my brightest. You have pushed me when I was procrastinating and uplifted me when I was struggling to see a way through it all, and somehow always knew which one I needed. Most importantly, you were patient and allowed me to grow as a person, even if it meant me taking off a few Thursdays to go skiing. I would also like to thank my supervisory committee, Darren Irwin, Mary O’ Connor and Loren Rieseberg for the irreplaceable time and advice you have given me over the years. My research has improved greatly from your continued support. This also extends to the members of Schluter lab. Steph for her companionship as we suffered through our first field season, and everything since. Ken, for his endless insights, and Kung Ping and Lucia for their encouragement as I finished up this thing. Marius for teaching me how to catch stickleback, Carling and Katie, for helping me keep those fish alive, and keeping the lab from devolving into chaos (because we know it would). Lastly Louise, for being the strong female academic role model I needed to encourage me to speak up and ask questions, even when I thought I didn’t belong. To Haley, a great officemate and friend, for always providing the right amount of distraction and encouragement, and for watering the plants I always bought and then left to die. Thank you to the BRC community, full of incredible researchers that I have had the privilege to work alongside, and a social atmosphere that has made my experience more full and enjoyable. HUTS, BEERS, EDG, BLISS, and other non-acronym activities like knitting club and coffee and donuts have all given me something to look forward to each day of the week. xvi Early on I found that maintaining a work-life balance was essential for keeping me mentally in a place to continue progressing in my academics. For this I owe great thanks to Katie, who was always ready for a “sick” day skiing. My time on the mountain with you has genuinely shaped my outlook on how life can be. I also owe a thank you to Whistler Blackcomb. Years ago I joked that skiing was the best way to make a PhD take 7 years, and then it took me 7 years…. but in all seriousness, my time in Vancouver has been shaped by my time on that mountain. Libby, Solaye, Hugo, Lucia, Brian and Maddie, for always being ready and willing to throw on a backpack and hike up a mountain to sleep in the cold, even if it was extremely last minute (as with all things I do). I owe an immeasurable amount of thanks to Cori for the light and laughter you have brought to my life. Thank you for always saying yes to a trip, whether it be a visit to Denver or a hike in the Pyrenees. The world has less wine in it because of us. It almost goes without saying that I owe my family immense gratitude. I’ve been truly blessed to have a large family of grandparents, aunts, uncles, and cousins that are kind, loving, full of laughs and ever-present. Throughout the entirety of my life, you have supported me in everything I do and everywhere I go, even when you didn’t understand why I was doing it. I wouldn’t be where I am without your confidence in me. Mom, I depended on your support and I couldn’t have done it without knowing I could call you anytime, anywhere, and you’d always pick up the phone to tell me you loved me. Maggie and Carson, I’m glad Mom didn’t let me send you back when she brought you home from the hospital. You were my first friends and mischief pals, and I can’t imagine my life without you. Aunt Sherry and Uncle Todd, when I needed help the most, you dropped everything to pick me up. Without you, I genuinely wouldn’t have made it through. And lastly to Peter, the love of my life and forever adventure companion. Your patience and compassion can never be overstated. Your unwavering support has made all the difference and I am unspeakably grateful to you for everything that you are and have brought to my life. Jeg elkser dig. xvii Dedicated to my dad, for inspiring my curiosity in nature and teaching me to never take a moment of this life for granted. 1 Chapter 1: Introduction The complexity and ever-changing nature of biodiversity on earth has fascinated naturalists for centuries. As children, it's hard not to marvel at the vastness of ecosystems and the species within them, inspiring questions about how and why such diversity exists. This childlike curiosity has motivated evolutionary biologists to investigate the mechanisms behind this diversity, resulting in an understanding of speciation - the process whereby a species diverges into two or more distinct species that are reproductively isolated from one another (Coyne & Orr, 2004). However, the development of this isolation is rarely instantaneous, leading to a continuum of speciation rather than a singular event. For thousands, sometimes millions of years, diverged species may still be capable of interbreeding and producing viable offspring (Mallet, 2005), making it difficult to draw clear species boundaries. This interbreeding is termed hybridization. 1.1 Hybridization following environmental disturbance Hybridization refers to the mating of individuals from two genetically distinct species or populations, which can be hetero- or conspecifics, but are distinguishable by heritable characteristics (Abbott et al., 2013; Arnold, 1997; Todesco et al., 2016). Hybridization is generally viewed as a negative process because, by definition, it counteracts divergence and can lead to the homogenization of populations, ultimately increasing the risk of species extinction (Dobzhansky, 1937; Mayr, 1942). Furthermore, hybrids are often maladapted to their environment and have difficulty competing for resources with parental species, leading to poor survival and reproductive success (Hatfield & Schluter, 1999; Pfennig et al., 2 2007; Rundle & Whitlock, 2001). In nature, multiple barriers have evolved that hinder hybrid formation between species. These barriers act to restrict gene flow between populations and can be categorized as pre- and postzygotic. Prezygotic isolating barriers operate before fertilization and prevent populations from interbreeding (Coyne & Orr, 2004). They encompass temporal, spatial, behavioral, mechanical, and gametic factors that impede mating and fertilization between individuals of different species. Conversely, postzygotic isolating mechanisms occur after fertilization and involve biological mechanisms that reduce the fitness of hybrid offspring (Coyne & Orr, 2004). This can result in sterility, inviability, or hybrid individuals that are poorly adapted to their environment. Selection acting against hybrids will strengthen these barriers, which is known as reinforcement (Butlin, 1987). The strength of these reproductive barriers has traditionally shaped our understanding of hybridization as a rare and disadvantageous process that promotes genetic homogenization between populations. However, recent research has challenged this notion, revealing that hybridization is more widespread than previously believed. In fact, conservative estimates suggest that at least 25% of plant species and 10% of animal species have been found to exhibit some level of hybridization (Arnold, 1997; Mallet, 2005). Species that have recently diverged are particularly susceptible to hybridization events because they may lack well-established pre- and postzygotic isolating mechanisms, allowing for the production of viable hybrid offspring (Coyne & Orr, 2004; Lackey & Boughman, 2013). Having not yet developed strong intrinsic barriers, mate selection and reduced hybrid 3 fitness are the primary mechanisms that maintain species boundaries in these recently diverged species. It is worth noting that hybrid fitness is context-dependent and can be influenced by various environmental factors (Hatfield & Schluter, 1999; Schluter, 1996; Thompson et al., 2022) . In recent years, there has been an increasing number of cases of hybridization between previously stable sympatric species, suggesting elevated interbreeding rates, enhanced hybrid fitness within the environment, or both (Grabenstein & Taylor, 2018). This phenomenon has been observed across diverse taxa, including invertebrates (e.g., Daphnia longispina and Daphnia galeata), plants (e.g., Crimson pitcherplant and yellow trumpets), amphibians (e.g., barking tree frog and American green tree frog ), fish (e.g., Sheepshead swordtail and highland swordtail), birds (e.g., black-capped and mountain chickadees), and mammals (e.g., shadow chipmunk and lodgepole chipmunk) (Alric et al., 2016; Fisher et al., 2006; Frare et al., 2017; Grabenstein et al., 2023; G.w, 1982; Schlefer et al., 1986). This list is not exhaustive, as recent hybridization has also been documented in numerous other species. Environmental disturbances such as vegetation removal, drought, eutrophication, and human infrastructure have led to diverse outcomes from hybridization events. These outcomes encompass numerous possibilities, including narrow hybrid zones characterized by sharp clines, or unidirectional introgression and genetic admixture, where parental species retain their distinct identities but incorporate foreign alleles into their genomes (Grabenstein & Taylor, 2018). In some cases, hybridization can lead to the complete 4 collapse of parent populations, resulting in the emergence of hybrid swarms (Taylor et al., 2005; Vonlanthen et al., 2012). 1.2 Hybrid fitness in a novel environmental context Understanding the mechanisms underlying the persistence, rather than extinction, of hybrid populations under novel environmental contexts poses an intriguing and complex research question. Mate choice plays a crucial role in maintaining reproductive isolation between young species, ensuring that hybrid production remains limited (Lackey & Boughman, 2013). However, the observed rise in hybrid production after environmental disturbance is indicative of the potential instability of reproductive isolation between ecologically specialized species (Gow et al., 2006). When environmental conditions change, these barriers that once effectively prevented hybridization can become disrupted (Schlefer et al., 1986; Seehausen et al., 1997; Vonlanthen et al., 2012). Nevertheless, it is important to note that the relaxation of reproductive barriers caused by environmental changes does not guarantee a corresponding increase in the prevalence of hybrid individuals. The breakdown of prezygotic isolation, while facilitated by environmental shifts, does not automatically translate into a surge in hybrid populations. Irwin (2020) demonstrated that if there is a significant reduction in reproductive isolation, we would not necessarily expect to see an increase in hybrids. When hybrid fitness is low, increased hybridization can drive species towards extinction rather than cause the formation of hybrid swarms. This indicates that the mere increase in hybridization alone may not be sufficient to drive the formation of hybrid swarms; rather, the fitness of hybrid individuals plays a crucial role. This raises a 5 fundamental question regarding the intricate relationship between environmental changes, hybrid offspring production, and changes in hybrid fitness in these novel conditions. Lewontin & Birch (1966) provided valuable insights for our understanding of the role of hybridization in adaptation, stating that "the introduction of genes from another species can serve as the raw material for an adaptive evolutionary advance." This suggests that hybridization may supply the necessary genetic variation for natural selection to act upon, which is particularly important in the context of novel or disturbed environments (Anderson, 1948). Within populations, de novo mutations occur at low frequencies and are often deleterious, and standing genetic variation within a single species may not provide sufficient variation for adaptation to the new environment (Barrett & Schluter, 2008). By combining genetic variation from two parental lineages, hybridization can instantaneously increase genetic diversity at multiple loci, incorporating functional variants from different genomic backgrounds. These novel combinations may allow for adaptation at a pace that is more rapid than is possible based on other evolutionary mechanisms, explaining the observed increase in hybrid individuals (and perceived hybrid fitness) after environmental change (Anderson & Stebbins, 1954). Simulation studies have provided support for this idea by demonstrating that in a novel environment, where neither the parent species nor hybrids are well adapted, hybrid individuals can exhibit faster rates of adaptation compared to the parent species (Kulmuni 6 et al., 2023). This effect becomes even more pronounced when the parental populations are further from the optimum in the novel environmental context. Therefore, the observed increase in hybrid fitness after environmental disturbance could be attributed to the unique capacity of hybridization to generate new combinations of genetic variants, allowing for more rapid adaptation in response to changing environmental conditions. Despite this evidence supporting the beneficial role of hybridization in facilitating adaptation, it is crucial to acknowledge that not all hybrid allele combinations are advantageous and conducive to adaptation. In many cases hybrids exhibit reduced fitness, highlighting the dual nature of hybridization as both a creative force for evolution and a potential threat to biodiversity (Arnold & Hodges, 1995; Barton & Hewitt, 1985). While natural selection operates on hybrid populations similarly to how it acts on all species, there are nuances associated with hybrid populations that complicate our understanding of how natural selection specifically acts on hybrids. The integration of different populations through hybridization introduces challenges such as hybridization load and Dobzhansky-Muller Incompatibilities (DMIs) (Schumer et al., 2015). Hybridization load occurs when a parental population with a higher genetic load transfers an excess of deleterious mutations into the hybrid population (Gagnaire, 2020). DMIs refer to negative epistatic interactions between alleles at different loci that can be detrimental to hybrid offspring (Dobzhansky, 1937). These factors do not exert the same influence on evolution within a single parental population, but they can have profound impacts on shaping the evolutionary trajectory of hybrid populations. Understanding how these mechanisms 7 interact with natural selection in hybrid populations remains an area of limited knowledge. The intricate interplay between hybridization load, DMIs, and natural selection and how they collectively shape the evolutionary outcomes of hybrid populations are still not well understood. To better understand the formation and maintenance of hybrids in nature, it is crucial to perform experiments in different species within diverse environmental contexts. Unfortunately, such studies are noticeably absent from the literature (Todesco et al., 2016). Conducting experiments in different species and environments can provide valuable insights into how different environmental contexts play a role in both initiating the formation of hybrid individuals and facilitating their persistence. The threespine stickleback (Gasterosteus aculeatus) adaptive radiation serves as an excellent study system to conduct these much-needed experiments. 1.3 Study system Threespine stickleback comprise an adaptive radiation of fish that are widely distributed, inhabiting both marine and coastal freshwater environments throughout the Northern Hemisphere. Freshwater threespine stickleback species are relatively young on evolutionary timescales, estimated to have diverged from their marine ancestors 10,000-15,000 years ago, and becoming locally adapted to freshwater environments (Bell & Foster, 1994). It is thought that these freshwater stickleback arose numerous times when marine individuals colonized depauperate lakes formed by receding glaciers at the end of the last 8 ice age. These new populations diverged from the marine ancestral form in morphology, behaviour and physiology, and present-day freshwater populations are believed to have evolved by natural selection on the same ancestral pool of genetic variation brought to freshwater by the marine colonists (McKinnon & Rundle, 2002). Of particular interest are the sympatric benthic and limnetic stickleback species pairs, which have arisen independently at least five times. Within a single lake, species pairs exhibit observable differences in morphology, diet, and habitat, and these distinct traits persist consistently across all five lakes, indicating parallel adaptations within the species pairs (McPhail, 1993; Schluter & McPhail, 1992). In each pair, one species is a benthic ecotype that is deep-bodied and preys primarily on benthic invertebrates found in the sediments of the littoral zone. The other species is a limnetic ecotype that is much smaller and more streamlined, preying upon zooplankton in the open water, pelagic zones of lakes (McPhail, 1993; Schluter & McPhail, 1992). In nature, these species pairs have high reproductive isolation and have a 2% hybridization rate, with those hybrids that are produced having low fitness compared to parents (Hatfield & Schluter, 1999; Rennison et al., unpublished). Despite this, collapse into a hybrid swarm has been observed in the Enos Lake population, but three populations in Priest Lake, Paxton Lake and Little Quarry Lake remain (Taylor et al., 2005). The species pair in the fifth lake, Hadley Lake on Lasqueti Island, has gone extinct following brown bullhead introduction. Post-glacial fish species, such as freshwater threespine stickleback, are excellent models for studies on hybridization because of their comparatively new speciation history, wide distribution of phenotypes and ability to readily hybridize and produce viable and fertile hybrid offspring (Jones, Grabherr, et al., 2012; Taylor & McPhail, 9 2000). For this reason, threespine stickleback species pairs and their hybrid offspring were used as a model of study for all data chapters of my thesis. 1.4 Thesis overview This thesis aims to investigate the impact of specific environmental changes on hybridization, and on the evolution and direction of selection after species hybridization. Hybridization barriers are pre- and post-zygotic, and similarly, the effects of environmental change on the production and evolution of hybrid populations are also multi-faceted. This thesis utilizes a combination of experimental and observational approaches to examine hybrid populations and aims to contribute to a comprehensive understanding of the impact of the environment on hybridization and evolution at three different stages of the hybridization continuum: pre-hybrid formation, during hybrid formation, and post-hybrid formation. By examining these timepoints, this thesis seeks to shed light on the complex processes involved in hybridization and the role that the environment plays in shaping the evolution of hybrid populations. 1.4.1 Chapter 2 In chapter 2 of this dissertation, I investigated the effects of altered environmental conditions on hybrid formation by experimentally manipulating nutrient levels and trophic status of pond ecosystems and investigating its effect on hybrid production in threespine stickleback species pairs. Eutrophication has been shown to disrupt the delicate balance that maintains separation of young species in some natural systems through a reduced 10 ability for individuals in one population to distinguish between hetero and conspecifics, or through habitat homogenization bringing heterospecifics into more frequent contact during the breeding season (Ansari et al., 2011; Seehausen et al., 1997; Vonlanthen et al., 2012). Eutrophication has also been shown to change the ecological fitness landscape, altering selection pressures (Alexander et al., 2017). To examine the impact of eutrophication on species maintenance in threespine stickleback fish (Gasterosteus acculeutus), I conducted a large-scale pond experiment where limnetic and benthic species of threespine stickleback were added to experimental ponds, half of which were made eutrophic using fertilizer. These individuals were left to breed for 1.5 years to investigate the impact on both hybrid production and hybrid survival. The experiment revealed an increased rate of hybridization compared to wild populations in both the control and treatment conditions, however hybridization rates were independent of treatment conditions, suggesting that the species barriers maintaining separation of young stickleback species are fragile and possibly dependent on factors not related to those researchers deem important. 1.4.2 Chapter 3 A recent example of increased hybridization after environmental disturbance is in Enos Lake on Vancouver Island, a lake that once contained both a benthic and a limnetic species of threespine stickleback but collapsed into a hybrid swarm following the invasion by American signal crayfish in the 1990s (Kraak et al., 2001; E. B. Taylor et al., 2005). In chapter 3 of my dissertation, I employed an experimental approach using mesocosms to investigate 11 the impact of this environmental change, in the form of crayfish presence, on the fitness of first generation hybrids of threespine stickleback. I investigated whether crayfish addition would alter the prey community structure in the environment, and whether this would alter hybrid fitness of threespine stickleback, providing potential insights into the causes of the Enos species collapse. Theory has made predictions about how environmental change leads to increased hybridization, potentially as a result of increased fitness of hybrids in a novel environment, but few of these theories have been experimentally tested. I found that crayfish addition depleted benthic invertebrate biomass and negatively impacted survival of all stickleback cross types. Growth differences between treatments were absent in hybrid crosses but showed a small decrease for benthic and limnetic crosses in the presence of crayfish, and high-density environments appeared to exaggerate this difference. Overall, hybrid fitness did not change but small reductions in parental fitness were observed, suggesting that an altered environment does not necessarily increase absolute hybrid fitness. However, the presence of fitness changes can still be observed through variations in relative fitness. In the context of the of Enos Lake collapse, biological invasion likely affected relative fitness of hybrids but is unlikely to be the sole reason for the collapse. 1.4.3 Chapter 4 Chapter 4 of this dissertation investigated evolution in established hybrid populations. Evolution of hybrid populations is potentially unique because hybridization generates additional selection forces such as hybridization load and genetic incompatibilities. The 12 ways in which all of these selection forces act in concert are not well understood (Moran et al., 2021). This study examined the evolution of three wild populations of hybrid stickleback over the course of 35+ years, using a combination of genomic and phenotypic analyses to understand which of hybridization load, intrinsic Dobzhansky-Muller Incompatibilities or ecological selection is the primary selection mechanism shaping the evolution of these populations with different parental ancestry proportions. Our results showed that ecological selection is the primary force driving evolution in all of our populations, as demonstrated by parallel phenotypic evolution in similar environments and parallel shifts in allele frequencies for SNPs located at the same regions of the genomes across populations. However, heterogeneity in phenotypic traits between populations still exists, likely as a result of heterogeneity between environments, despite an abundance of qualitative similarity. This study contributes to a better understanding of the complex selection forces at play in hybrid populations and their long-term evolutionary outcomes. 13 Chapter 2: An experimental test of eutrophication impacts on reproductive isolation 2.1 Introduction Species loss generally occurs through two processes: demographic decline and species hybridization (Rhymer & Simberloff, 1996). In the process of hybrid collapse, two distinct species can hybridize to such an extent that distinct parental lineages are no longer present and are instead replaced by a single population composed of both lineages (P. R. Grant & Grant, 2014; Seehausen, 2006; E. B. Taylor et al., 2005). Sympatric species that diverged as a consequence of ecological speciation are particularly susceptible to extinction via hybrid collapse, whereby ecological speciation is defined as “the process by which barriers to gene flow evolve between populations as a result of ecologically based divergent selection” (Nosil, 2012). This susceptibility to hybridization arises because assortative mating may be incomplete and these species can lack strong intrinsic postzygotic isolation, thereby producing viable hybrids whose fitness is determined by extrinsic environmental factors (Gow et al., 2006). Environmental changes can alter the ecology upon which reproductive isolation is based and lead to the merging of previously separated lineages (Seehausen et al., 2008; Vonlanthen et al., 2012). An escalating environmental threat worldwide is increased eutrophication in lakes resulting from increased nutrient inputs. In many agricultural areas, fertilizers added to fields run off and add nitrogen and phosphorous into the water system (Ansari et al., 2011). Phosphorous is usually limiting in aquatic systems, so this nutrient excess initiates a 14 cascade of changes, whereby phosphorous surplus increases primary productivity and phytoplankton biomass. Consequently, this increases overall water turbidity as well as microbial activity in the benthos, leading to reduced dissolved oxygen, and thus altered resource abundance (Harper, 1992). In multiple natural systems eutrophication has been suspected to disrupt the delicate balance between selection and gene flow that maintains species boundaries (Alexander et al., 2017; Arnold, 1997). This is particularly problematic in post-glacial temperate lakes, in which young, recently diverged species may be maintained through pre-zygotic reproductive isolation. In Swiss lake whitefish, eutrophication resulted in an increase in primary productivity and decreased oxygen levels in deep-water habitats, reducing viable spawning grounds for more benthic whitefish species, and breaking down reproductive isolation between closely related species (Vonlanthen et al., 2012). In African cichlids of Lake Victoria, urbanization and agricultural practices have rapidly made the lake eutrophic, increasing water turbidity and reducing the visual cues necessary for assortative mating (Seehausen et al., 1997, 2008). However, these are observational studies, and cases of eutrophication leading to species collapse have yet to be tested experimentally. In this work, I examine the impact of excess nutrient addition and experimental eutrophication on maintenance of species boundaries. Threespine stickleback (Gasterosteus aculeatus) are an excellent system to study the impacts of environmental change on reproductive isolation. Sympatric benthic and limnetic stickleback species pairs diverged as a result of ecological speciation ~12,000 years ago, and exhibit character displacement driven by resource competition (McKinnon & 15 Rundle, 2002). These species pairs have distinct morphological characteristics and dietary preferences, with limnetic stickleback being small and streamlined with numerous gill rakers and feeding primarily on zooplankton in the pelagic zone of lakes. In contrast, benthic stickleback are larger with a wider body, have fewer gill rakers than limnetic stickleback, and feed primarily on benthic invertebrates in the vegetated near-shore and deeper sediments (Schluter & McPhail, 1992). During mating, males make nests and display to females who lay eggs inside. Both species make nests near one another in the littoral zone, but mating is assortative. Females of both species choose mates based on male nuptial colouration characterized by red throats (Boughman et al., 2005) and similarity in body size (Conte & Schluter, 2013; Nagel & Schluter, 1998) however benthic females have also been shown to discriminate between heterospecific males using olfactory signals (Rafferty & Boughman, 2006). Previous lab studies have shown that premating reproductive isolation between these sympatric species is strong, even in no-choice trials (Rundle et al., 2000). Additionally, experiments in Paxton Lake indicate that hybrids have lower fitness in nature than their parents (Schluter, 1995), and hybridization in the wild occurs at ~2% rate (Rennison et al., unpublished). We manipulated nutrient addition to ponds containing two species of stickleback to test the hypothesis that excess nutrients would alter water conditions and reduce visibility due to increased algal growth, potentially disrupting the visual processes involved in mate choice, ultimately resulting in changes of hybridization rate. Wild caught fish from a sympatric species-pair lake (Little Quarry Lake) were brought to semi-natural experimental ponds and 16 allowed to breed in both natural conditions and with excess nutrient addition. Nutrient excess frequently increases turbidity and decreases visibility in pond ecosystems (Harper, 1992) and previous work in European marine stickleback has shown that under turbid conditions, females will shift to relying on olfactory cues rather than visual cues for mate choice (Heuschele et al., 2009). Since visual cues (i.e. size discrimination and nuptial colouration) are critical in mate choice for threespine stickleback species pairs, this reduced visibility was expected to affect mate choice. Excess nutrient addition and eutrophication have also been shown to alter resource availability in a pond ecosystem, observed as an increase in phytoplankton and a decrease in benthic invertebrates and general invertebrate biodiversity (Harper, 1992). Stickleback species pairs are relatively specialized in their dietary niche, and a shift in resources could have negative fitness consequences on these dietary specialists. Recent work in European stickleback lineages found that when subjected to a change in environmental conditions, both parental lineages suffered fitness disadvantages that were not observed in hybrids, increasing relative hybrid fitness and showing hybrid individuals to be less sensitive to environmental change (Best et al., 2017). As such, we also tested whether hybrid offspring have higher overwinter survival in the presence of excess nutrients compared to non-hybrid offspring as a secondary component to this experiment. In this context, we predicted that in eutrophic conditions we would observe altered mate choice that would increase hybridization in eutrophic ponds, and that altered resource availability would decrease parental overwinter survival more than in hybrids. 17 2.2 Methods 2.2.1 Experimental design The experiment was conducted in seven semi-natural ponds located on the University of British Columbia campus in Vancouver, Canada. The ponds were constructed in 2008 and measure 25m x 15m, totaling ~ 750,000L of water. Ponds contain both a 6m deep open water zone and a vegetated littoral zone, as well as natural food assemblages (zooplankton and benthic invertebrates) and nesting sites for both benthic and limnetic stickleback (Fig 2.1). Though these semi-natural ponds are not the same as lakes, previous work has shown that they are large enough to allow for differential resource use, and thus allow for natural selection to occur (Arnegard et al., 2014). Aquatic macrophytes were homogenized March 27 - 29, 2013 by removing as much macrophyte cover as possible from the deep portion of each pond, pooling into a common reservoir, and adding back a portion of this pool to the areas of vegetation in the shallow areas of the ponds. In four treatment ponds, nitrogen and phosphorous was added biweekly for 2 months from April 28-June 29, 2013 to a total of 206 g of KH2PO4 and 1765 g KNO3 of phosphorous per pond and an N:P ratio of 5.22:1 g. Agricultural fertilizers commonly have an N:P ratio of 4:1 g, while balanced aquatic systems have a ratio of 7.53:1 g. A ratio of 5.22:1 provides excess phosphorous to the aquatic system, which has been shown to promote algal growth. Nutrient inputs to experimental treatments translated to 62 ug/L phosphorous and 326 ug/L nitrogen, where > 30 ug/L total phosphorous is considered eutrophic (Yang et al., 2008). The three control ponds had a single addition of 2.82 g of KH2PO4 and 22 g of KNO3 on April 28, 2013 to simulate natural spring nutrient inputs. Ponds are uncovered and exposed to natural light and weather 18 Figure 2. 1 : Experimental ponds used in study. Left) Photograph is of one of the experimental ponds located at UBC South Campus. Right) Schematic profile of the pond. Image from (Arnegard et al., 2014). conditions, as well as all avian and invertebrate predators such as herons and dragonfly naiads. Adult sympatric benthic and limnetic species were caught from Little Quarry Lake on Nelson Island, British Columbia on May 11, 2013. These stickleback adults were transported to the University of British Columbia campus, where benthic (n=16) and limnetic (n=22) individuals (different numbers to account for biomass) were fin clipped and immediately introduced into each of the seven experimental ponds. Sex determination was not possible as individuals were not yet in breeding condition, but numbers of males and females were assumed to be approximately equal. Wild adults (P) lived freely in the ponds, allowing for natural reproduction and rearing of first-generation offspring (G1). During September 2013, individuals were caught using minnow traps and 50 G1 individuals were chosen at random from each pond. G1 individuals were distinguished from P individuals based on size, as P individuals were notably larger at this point in time, and on scarring from prior fin clipping. Trapped G1 fish had fin clips 19 taken and preserved in 95% ethanol for later genetic analysis. Clipped fish were returned to the ponds, which were trapped two weeks later to perform mark-capture for population estimation. Population size per pond was estimated using the Lincoln-Petersen model for closed populations, using binomial confidence intervals since the recapture/capture proportion was consistently >0.10 (Seber, 1982). All stickleback, both pure and potential hybrids, remained in the ponds overwinter. No collection was made during May 2014, so G1 stickleback (now adults), as well as any surviving P individuals, reproduced and generated offspring that were potentially a mixture of surviving parental, hybrid and backcross genotypes. In June 2014 the experiment was terminated, and all generations of stickleback were collected with unbaited minnow traps and dipnetting, and humanely euthanized using an overdose of buffered tricaine methanesulfonate (MS-222). Afterwards, ponds were treated with rotenone (1 L of 5% liquid rotenone per pond) and any remaining fish were collected with seine nets. P and G1 fish were separated from the second generation (G2) based on size, as G2 individuals were juveniles and were visibly smaller. G2 individuals are not utilized going forward. A random sample of 100 P/G1 generation stickleback was collected from each experimental pond, where all fish were labeled, caudal fins were clipped, and both fish and clips were preserved separately in 95% ethanol (Fig 2.2). 20 2.2.2 Measuring ecosystem responses to nutrient addition To measure ecosystem responses, measurements of chlorophyll A, photosynthetically active radiation (PAR), and oxygen concentration were taken at multiple time points and depths between April and August 2013. Chlorophyll A (ChlA) data was collected in vivo Figure 2. 2: Schematic illustrating experimental timeline and design. Large green fish represent benthic adults, large blue fish represent limnetic adults, and small fish represent offspring of all cross types. Drawings of stickleback done by K. Chu. using a fluorometer (Trilogy Designs) eight times between April 28 and August 30 at regular intervals, at depths of 5 cm, 1 m and 4 m. Chlorophyll A concentration is used to estimate phytoplankton biomass and is frequently employed to classify the trophic level of a body of water (Doering et al., 2006). PAR and dissolved oxygen concentration were collected using a multiparameter photometer at three timepoints (April, June and August) on sunny days with no cloud cover. PAR was measured at depths of 10 cm (treated as the 21 surface measurement going forward), 30 cm, 50 cm, 1 m, 2 m, 3 m, 4 m and 5 m, and dissolved oxygen concentration was measured at depths of 1 m, 2 m, 3 m and 4 m. The effects of nutrient addition on ecosystem responses were tested using linear mixed effects models. To analyze ChlA concentration, we used separate linear mixed effects models for ChlA concentration at 1 m and 4 m depths. In these models, the response variables were ChlA concentration at the specified depth, while using treatment as a categorical explanatory variable, date as a continuous explanatory variable, the interaction between treatment and date of measurement, and pond as a random factor. We assumed no temporal autocorrelation between residuals on different dates. Oxygen concentration and PAR were only measured three times during the experiment and so linear models for these responses used date as a categorical variable rather than a continuous. For each of oxygen concentration (1 m, 2 m and 4 m), oxygen depletion (1-4 m), light extinction (surface-1 m, surface-2 m and surface-4 m) and PAR (1 m), we ran a separate linear mixed effect model with the ecosystem response as the response variable, treatment, date and their interaction as predictor variables, and pond as a random effect. 2.2.3 Genotyping Using a modified phenol-chloroform extraction protocol, DNA was extracted from all caudal fin clips (Appendix A.1). Fifty fin clips from each pond at the fall timepoint collection, and 100 fin clips from each pond at the final timepoint collection, totalling 1050 samples, were processed. DNA from the fall timepoint had lower DNA quality and 22 underwent ethanol precipitation using a protocol from the Barrick lab (Li et al, 2021). DNA quality was determined using a NanoDrop 2000 spectrophotometer and quantified using a Qubit 2.0 fluorometer with the dsDNA Broad Range assay kit. DNA was prepared for ddRAD Illumina Sequencing using enzymes PstI and MspI following a modified genotyping by sequencing protocol from Poland et al, 2012 (Todesco, unpublished). Modifications included steps of cleaning and concentrating samples using SPRI beads, as well as PCR amplification prior to pooling of samples. 1050 individuals were uniquely barcoded using 192 unique forward adaptors and 12 common reverse adaptors and combined into a single library. Gel size selection was performed for fragments of 300-500 bp in length, and DNA extracted from gel using the QIAquick™ Gel Extraction Kit. Sequencing of this library was performed by Genome Quebec on the NovaSeq6000 in a single lane, producing 375 M paired end reads of 150 bp in length. Sequences were demultiplexed, after which Trimmomatic-0.39 (Bolger et al., 2014) was used to remove adaptors and redundant primer sequences from short fragments and filter out low quality sequences. Trimmed, sorted sequences were aligned to the stickleback reference genome v5 (Nath et al., 2021) using BWA from Picard-1.120 (Li & Durbin, 2009). The GATK-4.1.9.0 pipeline workflow was followed with the exception of MarkDuplicates. HaplotypeCaller was used to identify single nucleotide polymorphisms (SNPs) in individuals, and GenomicsDBImport was used to generate databases for each chromosome. Genotyping was done per chromosome across all individuals using GenotypeGVCFs, and then combined into to a single VCF file containing all variable sites. This file was split into SNPs and indels using the SplitVcfs 23 command in GATK. The VariantFiltration command was used to hard filter SNPs as follows: QD>2.0, SOR>3, FS>60, MQ<40 and a minimum quality score 30. Whole genome sequences of twenty-five benthic and limnetic stickleback from a 2018 collection of Little Quarry Lake were generated as part of a separate project (see Chapter 4 of thesis) were used as a reference of species type. DNA was extracted from fin clips of the collected sticklebacks using DNeasy® Blood & Tissue Kit (Qiagen, Hilden, Germany). Library preparation was performed with Nextera XT DNA Library Preparation Kit (Illumina). The whole-genome libraries were sent to Genome Quebec for sequencing on an Illumina Hi-Seq 4000. Data processing was as described above except we included MarkDuplicates and a base quality recalibration of sequencing reads using the BaseRecalibrator program of GATK 4. The reference dataset of known SNPs was generated from a previously published SNP dataset of 21 marine and freshwater sticklebacks (Jones, Grabherr, et al., 2012), which includes only SNPs that have at least 8 reads supported at all individuals. Coordinates were transferred from the reference genome v1 (Jones et al., 2012) to the v5 stickleback reference genome using the file v1withChrUn_to_v5.chain.txt provided by M. White (https://stickleback.genetics.uga.edu). 2.2.4 Estimating hybrid proportions The impact of eutrophication on assortative mating was measured indirectly as the proportion of hybrid offspring present in the fall (after the first breeding season). Eutrophication impact on hybrid survival was estimated as the change in hybrid proportion 24 from fall to spring, after selection overwinter. Experimental fish samples (G and P1) were labelled by time of collection (fall vs summer). SNPs that passed the quality metrics and those from our additional wild fish were converted to table format using genotypeToSnpMatrix() in the R VariantAnnotation package (Obenchain et al., 2014). SNPs that were shared between the ddRAD and reference whole genome data sets were filtered to include only those found in at least 80% of all samples, leaving 4146 biallelic markers. Using these markers, a principle component analysis was performed on all samples from both the fall and summer sampling period using the pca() command of the pcaMethods package with argument method = rnipals to impute missing values (Stacklies et al., 2007). The first principal component separated wild benthics and limnetics and two corresponding groups of pond individuals, which we designated as pure limnetics and benthics. A third, intermediate cluster of pond individuals were designated as hybrids. Clusters of pond fish were delimited using the Mclust() command of the R package mclust including only PC1 and PC2 and using argument modelNames = "VVI". The method identified 7 clusters: 3 benthic, 3 hybrid, and 1 limnetic, with the 3 clusters in benthics and hybrids representing variation in PC2 values among families within ponds. This classification was used to determine hybrid proportion for each of the seven experimental ponds across both the summer and fall timepoint (Appendix A.2). Hybrid proportion within a pond was calculated as [#F1 hybrids in sample/all fish in sample] and compared between both treatment (control and nutrient addition) and timepoints (fall and summer). The classification indicated that limnetic stickleback were 25 absent or scarce in samples from all ponds in fall (October 2013) and in summer (June 2014). This could potentially be because of the time of collections. Both trap sessions were after the breeding season, when limnetic fish are difficult to trap (personal observation). For both the fall and summer timepoint, differences in hybrid proportion between control and treatment was determined with a permutation test using the lmp function in the R package lmPerm(). Changes in the proportion of hybrids within a pond between October 2013 and June 2014 were analyzed with a linear mixed effect model using the lme4 package in R. Hybrid proportion was treated as the response variable, with treatment and timepoint used as predictor variables, with pond as a random effect. 2.2.5 Analysis of ecosystem impacts on hybridization Ecosystem parameters were analyzed initially at a depth of 1m, as this is the approximate depth of stickleback breeding sites, however further analysis was performed at all measured depths. We calculated the mean oxygen concentration of treatment and control ponds at 1 m, 2 m, 4 m and the concentration difference through the water column [=1 m-4 m] during April, June and August 2013. Differences in photosynthetically active radiation (PAR) between treatments was analyzed as the mean PAR at 1m depth in April, June and August. Light extinction was measured as the amount of PAR extinguished per centimeter of water depth ((PAR 10 cm below surface – PAR maximum depth)/difference in depths in centimeters). The mean value of light extinction of treatment and control ponds from surface- 1 m, surface-2 m and surface- 4 m was determined during April, June and August 26 2013. Ecosystem impacts on hybrid proportion were analyzed using linear mixed effect models in the lme4 R package. In all cases, hybrid proportion was treated as the response variable, with the concentrations of a particular ecosystem impact and time of measurement used as predictor variables, and pond as a random effect. 2.3 Results 2.3.1 Ecosystem responses to nutrient addition Nutrient addition in the form of nitrogen and phosphorous was shown to make ponds more eutrophic in all ecosystem responses. Ponds with excess nutrients showed an increase in ChlA, light extinction, and oxygen depletion between depths. Nutrient addition began in April, and linear regressions showed that ponds immediately diverged in ChlA concentrations, with ponds having excess nutrients exhibiting average ChlA levels more than 2.5 times that of the control pond by the end of August (Fig. 2.3, Appendix A.3). This indicated that both time and treatment were significant in generating the difference observed (interaction: F 1,40 : 17.80, p= 0.00014). All other ecosystem responses showed a similar trend. Photosynthetically active radiation (PAR) at a depth of ~1m decreased in all ponds over the summer (Fig. 2.4a), with month sampled showing the strongest effect (date: F 2,10 = 28.27, p= 7.668 x 10-5). Differences in PAR between treatments were small in April and June, but 30% reduced in eutrophic ponds in August (interaction: F2,10= 8.79, p= 0.0063). Light extinction differences grew over time and showed a 55% increase in treatment ponds compared to control ponds by August (interaction: F 2,15 = 9.44, p = 0.0022) (Appendix A.4). The loss of dissolved oxygen between the surface and 4m was highest in 27 June and August and found to be 2-fold higher in the treatment ponds than control ponds (treatment: F1,15 = 12.07, p= 0.0034, interaction: F4,15=4.19, p=0.018) (Fig. 2.4b). Dissolved oxygen concentration was similar between treatment and control ponds at all depths, but interestingly was actually higher in ponds with excess nutrients than control ponds, though not significantly (Appendix A.5). Oxygen concentration was highest in June, comparatively decreasing in August; this is likely associated with high chlorophyll A concentrations in August, which could have increased oxygen demand. Figure 2. 3: Chlorophyll A concentration for all ponds (7) at 1 m depth. Day of the year corresponds to the number of days that have passed since January 1, with the x-axis displaying dates between April 20 and August 21st. Yellow lines are the eutrophic ponds and green lines are control ponds, with thin lines showing measurements from each individual pond over time, and thick lines representing linear regressions for each treatment type. Dashed horizontal lines indicate the chlorophyll A concentration threshold for water to be considered mesotrophic (2.5 ug/L) or eutrophic (>7 ug/L)(A.M et al., 2010). MesotrophicEutrophic01234567891011110 130 150 170 190 210 230Day of the YearChlorophyll A Conc. (ug/L)TreatmentControlEutrophic 28 Figure 2. 4: PAR and oxygen reduction during active nutrient addition. A) Amount of photosynthetically active radiation detected at 1m depth and B) reduction in oxygen concentration throughout the water column, calculated as the difference in dissolved oxygen concentration at 4 m depth compared to the surface. Measurements were taken at three timepoints; once in April, June and August. Concentrations for each timepoint has treatment (in yellow) and control (in green) paired. In both plots, points are individual ponds and thick horizontal lines are the treatment means. 2.3.2 Influence of treatment and overwinter survival on hybrid proportion All ponds showed an increase in the number of fish at the time of collection compared to the time of introduction, providing evidence of reproduction in the ponds. At introduction each pond had a total of 38 fish, and at the time of collection population sizes were estimated to be approximately 300-1200. Population size was not related to treatment (Appendix A.6a). Hybrid proportion after the first breeding season was determined from samples taken at the fall timepoint. This proportion varied widely across all ponds, with percentage of hybrids ranging from 2% to 99%; however the hybrid proportion was not related to treatment: mean hybrid proportion was approximately equal between treatments (control = 0.31, treatment = 0.28, df1,5= 0.0072, p=0.94) (Fig. 2.5a). We observed species 29 collapse into a hybrid swarm (> 90% hybrids) in two ponds, one treatment and one control pond. The same result was observed during the summer collection timepoint, with no significant difference between treatments in hybrid proportion (control = 0.27, treatment = 0.28, df1,5= 0.0068, p=0.97) (Appendix A.7). Very little change in hybrid proportions was observed over winter, where treatment ponds showed no change at all, and control ponds showed a decreased proportion of only 0.03 (timepoint: F1,5= 0.083, p=0.80; interaction: F1,5=0.13 p=0.74) (Fig. 2.5b), suggesting that treatment had no detectable effect on hybrid fitness. No change in hybrid proportion was observed in any pond with nutrient excess, but in control ponds we saw one pond increase in hybrid proportion while another decreased, resulting in an overall minor decrease. 2.3.3 Hybrid proportion – ecosystem characteristic associations Variation among ponds in hybrid proportion was unrelated to any measured ecosystem characteristics of ponds. For all characteristics (ChlA, PAR, light extinction, and oxygen concentration) there was no correlation at any timepoint between the characteristic and hybrid proportion, nor the change in hybrid proportion over winter. ChlA concentration at 1 m and 4 m was plotted against hybrid proportion for each timepoint that ChlA was measured during the summer of 2013 (Appendix A.8a,b). At all timepoints, the relationship between hybrid proportion and ChlA concentration was nonsignificant (concentration: F1,25=0.45, p=0.51; interaction: F4,25= 0.47, p= 0.99), and in most cases the relationship was 30 negative. Only during early May is there a positive correlation between hybrid proportion and ChlA, however this relationship is also non-significant (F1,5=0.07, p= 0.80). The change in hybrid proportion from fall to the following summer was also not significantly related to chlorophyll A concentration at any timepoint when ChlA was measured (Appendix A.8c). There was no significant correlation between hybrid proportion and PAR at any timepoint (PAR: F1,15= 0.117, p=0.737; interaction: F2,15= 0.051, p=0.951) (Appendix A.9a). Hybrid proportion showed no consistent relationship with light extinction, oxygen concentration Figure 2. 5: Hybrid proportion in individual ponds. A) Proportion of hybrids after a single reproductive season, determined using samples collected during our fall sampling period. Hybrid proportion within a pond is binned in increments of 0.1, and the y axis shows the number of ponds with a proportion within that binned category. Each pond is treated separately, with treatment ponds in yellow and control ponds in green. B) Change in hybrid proportion over winter. Samples were collected in each pond in the fall and following summer, and the lines connecting points indicate the change of hybrid proportion within a single pond. Green lines are control ponds and yellow lines are treatment ponds. 31 or oxygen reduction, having different direction of slopes at each timepoint measured (Appendix A.9b, A.10). Lastly, there was no relationship between population estimates in October and the hybrid proportion at that timepoint (F1,33= 1.610, p= 0.213) (Appendix A.6b). 2.4 Discussion We experimentally investigated whether increasing nutrient addition in semi-natural pond ecosystems would result in a decrease in premating reproductive isolation between benthic and limnetic stickleback as a consequence of predicted increased water turbidity. Additionally, we investigated whether the increase in nutrients would alter chlorophyll A concentration, photosynthetically active radiation or dissolved oxygen concentration, changing resource availability and potentially result in an increase in hybrid survival overwinter. We found that despite an increase in chlorophyll A, a greater loss of dissolved oxygen throughout the water column, and a reduction in PAR, we observed little or no difference in hybrid proportion nor hybrid persistence across treatments. These results suggest that eutrophication does little to increase the fitness or production of hybrids in this experimental system. The experiment nevertheless revealed instances of species collapse when none was expected. Absence of effects from nutrient addition on the production of hybrids can likely be attributed to the peak of the stickleback breeding season being temporally different from the peak of observed ecosystem impacts. All treatment ponds showed an increase in ChlA concentration, an increase in light extinction and a greater reduction of dissolved oxygen, 32 as expected. Chlorophyll A levels in the treatment ponds peaked in August, and regressions suggest that, on average, ponds reached eutrophic status (ug/L >7) around July 30. However, the stickleback breeding season begins in late April and is largely over by the end of June. It is possible that the long delay in peak ChlA concentration is a consequence of pond starting conditions being oligotrophic (ug/L <2) in April. A near complete absence of ChlA at the beginning of the experiment suggests that these experimental ponds had very little productivity prior to the beginning of the experiment, likely resulting from dormancy due to over-winter cold temperatures. Control ponds did reach a mesotrophic level of productivity over the course of the experiment, just as ponds with nutrient excess achieved eutrophic status, but the low initial productivity baseline leads to a delay in productivity that maintains clear water conditions during the critical period of mating. This might explain why our experimental treatment did not appear to impact the frequency of hybrid offspring production. Despite high nutrient inputs in the first year of the experiment, the cessation of nutrient addition over winter (which reflects the reality of agricultural nutrient inputs) led to all ponds returning to an oligotrophic status of ChlA <2ug/L by April of year 2. This suggests that it may take numerous years of nutrient buildup before eutrophic conditions persist long enough that they impact the stickleback breeding season. A fluctuation in dissolved oxygen concentration was observed over the course of the experiment, peaking in June, and was higher in the ponds with nutrient addition. Nutrient addition was expected to lead to a decrease in oxygen concentration as the excess in algae growth leads to increased dead algae, and as a consequence, increased microbial 33 decomposition depleting dissolved oxygen (Harper, 1992). Additionally, a reduction in water clarity generally reduces photosynthetically active radiation reaching deep into the water, slowing photosynthesis in algae and macrophytes that reduces oxygen production (Harper, 1992). We observed the opposite in our experiment, potentially attributed to the increase of phosphorous and nitrogen, which provided a greater availability of nutrients for photosynthesizing algae and plants without leading to excessive growth. As previously stated, initial pond conditions were oligotrophic, and thus nutrient addition might have initially been advantageous in facilitating primary productivity and transitioning the ponds to a mesotrophic state. However, these initial positive impacts were not maintained with continued nutrient inputs, as oxygen concentration decreased by August. Irrespective of surface oxygen concentration, ponds that received additional nutrients exhibited a more pronounced decrease in oxygen concentration between the surface and the bottom, suggesting that despite oxygen levels being higher overall, decomposition continued to deplete oxygen at the bottom of the ponds. Nevertheless, observed oxygen depletion was not detrimental to fish survival, as fish require a minimum of 5mg/L and oxygen concentration in our experimental ponds was depleted to a low of 7.5mg/L. Since stickleback breed in shallow water around 1m depth, it is likely that repeated incidents of eutrophication over numerous years would be necessary for sufficient oxygen depletion to disrupt stickleback breeding habitat. When treated as continuous variables, none of the collected ecosystem metrics predicted hybrid proportion. This is largely because of the large proportion of hybrid individuals 34 (>90%), in two of the seven ponds, one a treatment pond and one a control pond. Our post-hoc analysis of environmental variables found little to distinguish the ponds with high hybrid proportion from those with low hybrid proportion. Population size was also similar between the ponds. This suggested that the breakdown in reproductive isolation in the two ponds was not caused by an increase in water turbidity or other environmental variables measured over the course of the experiment. Thus, we lack an environmental explanation for the collapse in the two ponds. Under normal circumstances, stickleback species pairs maintain high reproductive isolation and naturally hybridize at a rate of 2%. Despite this, we observed near complete collapse within a single generation, and so we believe this unexpected result requires further investigation. It is important to acknowledge that in our study, we assessed the breakdown of reproductive isolation indirectly by measuring hybrid proportion rather than directly quantifying the number of inter-species mating events. While it is plausible that a few mating events involving highly fecund females could contribute to a large hybrid proportion, we believe this explanation alone does not sufficiently account for a hybrid proportion as high as 99%. Ponds with 99% hybrids at the fall timepoint had population estimates of >450 individuals, and a single stickleback clutch typically consists of around 60 eggs. Furthermore, not all offspring from a clutch survive to adulthood, further diminishing the likelihood that a small number of mating events could explain the observed hybrid proportions. Another possible explanation for the high hybrid proportions is that sex ratios upon introduction were skewed since we introduced ~20 of each species, 35 but the number of those that were male vs female is unknown. Female limnetic stickleback are harder to catch in the wild than males, leaving open the possibility that there may have been limnetic males added but a shortage of limnetic females. Benthic females will select limnetic males of a similar size on occasion, leading to hybridization (Nagel & Schluter, 1998). We are unable to explore this possibility as there are no mitochondrial diagnostic SNPs distinguishing benthic from limnetic stickleback (unpublished data), meaning we cannot use mitochondrial DNA to determine if the hybridization events were biased in one direction. However, a pond containing 99% hybrids indicates few individuals of the pure benthic species either, suggesting that both the benthic and limnetic sex ratios were skewed in opposite directions (i.e. males of one species, females of the other). However, this explanation requires a severely skewed sex ratio that would have occurred twice out of seven trials, making this explanation improbable. This leaves the observed species collapse in 2 out of 7 cases without an explanation. Our experiment also tested whether increased nutrients would alter hybrid proportion over winter, indicating improved hybrid survival compared to the parental species. We observed no significant change in hybrid proportion in response to treatment. This suggests that there was no observable trend for the effect of nutrient addition on overwinter survival. Our results are nevertheless complicated by the notable absence of limnetic fish in collections from all ponds. We know that reproduction took place, but only four ponds indicated the presence of limnetic fish at the end of the experiment, and only two of those had higher than 3% limnetic individuals despite large population increases. This could be 36 a consequence of an actual absence of limnetic individuals resulting from a reduction in limnetic reproduction or a reduction in limnetic offspring survival, or low trappability of limnetics at the end of the experiment. In previous pond experiments, limnetic individuals are easily maintained in the ponds, making low survival as a sole explanation unlikely. Though it should be noted that the pond with the lowest population estimate had the highest proportion of limnetic fish (15%), so density within the ponds could have had disproportionately negative consequences on limnetics. The presence of hybrids provides proof that some limnetic fish survived introduction, so it is possible that limnetic fish were more likely to hybridize. Although precautions were taken, potentially skewed sex ratios at introduction could have led to low limnetic numbers to begin with, inevitably leading to low opportunities for mate selection within species. A final consideration as to the low number of limnetic fish is that limnetic individuals are less likely to swim into mesh traps than benthic and hybrid fish, particularly in the nonbreeding season. To compensate, we treated ponds with rotenone at the end of the experiment and used a seine-net to collect the fish after trapping with minnow traps, ensuring we left no fish in the ponds. We set out to test whether an increase in nutrient addition would lead to a decrease in reproductive isolation between benthic and limnetic stickleback, and if the resulting hybrids would differ in their ability to survive overwinter. We found that excess nutrients allowed for higher productivity in the ponds, but not quickly enough to impact the breeding season, and so likely did not impact stickleback mate choice. The stickleback breeding season in freshwater lakes on the British Columbia coast takes place from late 37 April until early June, meaning that the timeframe where mate choice is happening is before water clarity would be impacted by nutrient inputs in our experiment. Additionally, the cold temperatures of Vancouver over winter, and the lack of sun from the months of October-March, effectively ceased productivity overwinter, indicated by the return to oligotrophic conditions by the April following the experiment. This suggests that it may take numerous years of nutrient buildup before eutrophic conditions persist long enough that they impact the stickleback breeding season. We found no difference in hybrid proportion resulting from differential overwinter survival, suggesting that altered environments don’t necessarily favor hybrids. However, despite our experimental manipulation not impacting hybrid proportion, we did observe an increase in hybrid offspring in two of the seven ponds that is unrelated to treatment or any of the ecosystem measurements we took. We observed a breakdown in reproductive isolation independent of the ecosystem factors we manipulated, suggesting that perhaps ecological speciation and species barriers dependant on pre-zygotic reproductive isolation may be even more fragile than previously realized. This could have broader implications not only on our understanding of the maintenance of species boundaries, but also the fragility of ecosystems in ways that are not always obvious, as was observed in a natural stickleback species collapse (E. B. Taylor et al., 2005). When conducting experiments, researchers should think more broadly about what other factors could be impacted by their manipulations beyond what they have considered. Additionally, when restoring or conserving habitat, it is important to recognize that the factors that humans may define as 38 important are not necessarily those that are the most significant for the organisms within the system. 39 Chapter 3: Experimental test of species collapse via altered hybrid fitness following biological invasion 3.1 Introduction Closely related species that coexist in sympatry maintain species boundaries through pre-zygotic and post-zygotic isolating mechanisms that restrict interspecific gene flow. Incomplete isolating mechanisms can result in inter-species mating and production of hybrids (Coyne & Orr, 2004). Increased hybridization between natural populations is frequently observed after environmental disturbance (Lamont et al., 2003; Mecham, 1960; Seehausen et al., 1997). Human-mediated environmental changes, ranging from pollution and introduction of invasive species, to habitat changes through deforestation and eutrophication, are increasingly common (Hendry et al., 2017). These changes can reduce divergent selection and disrupt the isolating mechanism maintaining species separation, subsequently producing hybrid individuals. The evolutionary outcomes of these hybridization events are variable, from a population in which occasional F1 individuals are produced, to formation of a hybrid swarm, when late generation hybrids persist, eventually replacing parent taxa, and lead to complete species collapse. Numerous instances of increased hybridization between sympatric species are known, including southern tree frogs, Galapagos finches, Banksia, and mule deer (B. R. Grant & Grant, 1996; P. R. Grant & Grant, 1992, 1996; Kleindorfer et al., 2014; Lamont et al., 2003; Latch et al., 2011; Mecham, 1960), with some cases such as African cichlids, whitefish and threespine stickleback resulting in complete species collapse (Gow et al., 2006; Seehausen et al., 1997; E. B. Taylor et al., 2005; Vonlanthen et al., 2012). 40 Environmental perturbations are thought to contribute to increased hybrids between sympatric species in two ways: an increase to the frequency of inter-species mating or an increase in hybrid fitness. The first of these occurs when environmental changes reduce the ability of individuals to select conspecific mates, resulting in a breakdown in premating reproductive isolation (Seehausen et al., 1997). The second of these occurs when hybrids possess traits that increase survival or reproductive success in the novel environment, where the increase in genetic variation through hybridization generates novel allele combinations for selection to act on (Rieseberg et al., 2007). This may allow for more rapid adaptation of hybrid classes than parental lineages relying on standing genetic variation and mutation (Hedrick, 2013; Kulmuni et al., 2023). It can be difficult to estimate which of these mechanisms is the primary driver of an increase in the frequency of hybrids in each given system. Previous work has attempted to disentangle the importance of these two mechanisms in explaining the rise in hybrid frequencies following shifts in the environment, though this research has been primarily observational or theoretical. Ribeiro & Caticha (2009) developed a model to investigate the conditions under which ecological selection leads to increased hybridization and the formation of a hybrid swarm and found that sexual selection against hybrid phenotypes would likely prevent species collapse unless ecological selection favouring hybrids was strong. Similarly, Gilman & Behm (2011) modelled species collapse under different degrees of environmental disturbance, and found that a weakening of premating barriers, even for a short duration, might lead to increased hybridization and 41 species collapse. Recent work has suggested that a circumstance with moderate premating reproductive isolation and low hybrid fitness is more effective than high premating isolation at preventing collapse, supporting a model of collapse under improved hybrid fitness (Irwin & Schluter, 2022). These models have all been instrumental in understanding the potential mechanisms causing collapse, but there is not universal agreement on the importance of increased hybrid fitness vs reduced assortative mating in promoting species collapse. Despite model support for both hypotheses, researchers frequently attribute the cause of hybridization in observed species collapses to presumed changes in mate choice based on evidence of reduction in population size or habitat degradation (Mullen et al., 2012; Vaz Pinto et al., 2016). However these analyses do not actually test the cause of these collapses, and extensive evidence of adaptive introgression in evolutionary rescue supports a model of improved hybrid fitness (Chen & Pfennig, 2020; Whitehead et al., 2017). Conducting experiments plays a crucial role in comprehending the extent to which these factors influence hybridization and adaptive evolution in response to environmental changes. However, the existing literature is lacking in such experiments (Todesco et al., 2016). The threespine stickleback (Gasterosteus aculeatus) adaptive radiation presents an unique study system for experimentally testing these hypotheses. Threespine stickleback fish are widely distributed along coastal habitats in the northern hemisphere and inhabit both marine and freshwater environments. Of particular interest are the sympatric benthic and limnetic stickleback species, which have arisen independently at least five times over the 42 past 12,000 years (Bell & Foster, 1994). In every pair, the limnetic species is streamlined in body shape and feeds primarily on zooplankton in the open water zone within lakes. This is distinct from the benthic species, which are larger, deeper bodied, and forage in the shallow vegetated region of lakes for benthic invertebrates (Schluter & McPhail, 1992). In the early 1990s the Enos Lake species pair collapsed, resulting in the formation of a hybrid swarm and the extinction of distinct benthic and limnetic species (Behm et al., 2010; Kraak et al., 2001; E. B. Taylor et al., 2005; E. B. Taylor & Piercey, 2018). Reproductive isolation in all stickleback species pairs is strong and maintained primarily through assortative mating, so this collapse was a sudden change in a previously balanced system. The collapse coincided with an invasion by American Signal crayfish (Pascifiasticus leniusculus) to the lake, though the crayfish has not been conclusively determined to be the cause of the collapse (Foster et al., 2003). In Priest and Paxton lakes, where the species pairs still persist, assortative mating remains strong. In all extant species pair lakes, approximately 2% of individuals are first-generation hybrids or backcross individuals, with these hybrids having moderately reduced survival compared to the parental limnetic and benthic species (Rennison et al, unpublished data). In experimental enclosures in Paxton Lake, F1 hybrids had reduced growth performance in both the littoral zone and open water habitats, and each of the two backcrosses (benthic backcross and limnetic backcross) had relatively higher growth than the other when enclosed in the habitat of its genetic majority parent species (Rundle & Schluter, 2004; Schluter, 1995). In contrast, survival of hybrids and parent taxa is similar in laboratory aquaria (Hatfield & Schluter, 1999). These results indicate that the species pairs persist in a balance between a low rate of hybrid production and their 43 removal by natural selection via primarily ecological mechanisms. The same was likely true in Enos Lake, and it is not clear which of these two processes principally changed and precipitated the collapse. Two possible explanations have been proposed for the collapse of the Enos Lake stickleback species pair. The first, which we will refer to as the Altered Fitness hypothesis, suggests that in a novel environment, there is an increase in hybrid fitness compared to the previous environment, and this increase leads to a higher survival rate for hybrids that is not necessarily coincident with an increase is hybrid offspring being produced. The second hypothesis, which we refer to as the Reduced Premating Isolation hypothesis, proposes that changes in the environment can influence mate choice and lead to an increase in hybrid offspring. In this case, even without an increase in hybrid fitness, we observe a higher number of hybrid offspring. Previous studies on Enos Lake stickleback have offered support for both hypotheses, though they are not mutually exclusive. Laboratory studies conducted on benthic and limnetic stickleback have shown that the presence of crayfish affects male nesting behavior, potentially impacting premating reproductive isolation (Velema et al., 2012). This finding provides support for our Reduced Premating Isolation hypothesis. Conversely, Behm et al., (2010) found evidence for reduced selection against hybrids in Enos Lake, and the HZAM model suggests that low hybrid fitness is more effective than high premating isolation at preventing collapse in general (Irwin & Schluter, 2022). These findings provide support for the Altered Hybrid Fitness hypothesis. 44 The present study aims to experimentally examine the Altered Hybrid Fitness hypothesis by investigating the influence of crayfish on environmental conditions and natural selection on hybrid genotypes. To investigate this, we measured growth and survival of juvenile limnetic and benthic stickleback from an extant species pair, as well as their F1 hybrids, in the presence and absence of crayfish in mesocosms. Crayfish inhabit the benthos of lakes, increasing water turbidity through vegetation disturbance, and are omnivorous, with a diet that ranges from algae to live or decomposing animals (Vaeßen & Hollert, 2015). We predicted that as a consequence of shared niche space, crayfish presence would deplete benthic resources and disproportionately impact benthic stickleback. Additionally, we predicted that this interaction could potentially induce a shift in the fitness landscape, improving fitness in hybrid individuals relative to parents. Intuitively, one might expect that the hindrance of benthic ecotypes by crayfish would provide an advantage to limnetic ones. However, contrary to these expectations, field observations in Enos Lake indicate an increase in hybrid individuals rather than limnetics (Taylor & Piercey, 2018). This intriguing finding serves as the motivation behind our investigation into the Altered Hybrid Fitness hypothesis. Within this context, we predicted an observed change in hybrid fitness, characterized by a smaller reduction in both growth and survival of hybrids compared to parent species when raised in the presence of crayfish. 45 3.2 Methods 3.2.1 Study populations Using unbaited minnow traps, adult sympatric benthic and limnetic species pairs were caught from Priest Lake on Texada Island during April and May 2017. Priest Lake is one of the remaining species pair lakes and was chosen for its accessibility and reliability in obtaining both benthic and limnetic individuals. Crosses were made from wild adults, generating 15 pure benthic, 20 pure limnetic, and 15 F1 hybrid (limnetic male x benthic female) crosses. Fertilized egg clutches were transported to the University of British Columbia and raised in aquaria in the University of British Columbia aquatics facility until their introduction into the mesocosms. Fertilized egg clutches were kept in aerated 100L tanks of freshwater with dilute methylene blue to prevent fungal growth. Upon hatching, fry were fed a diet of live brine shrimp twice daily, with fragmented blood worms being added to their diet after ~2 months. Once fish were juveniles (~1.5-2cm in length), both benthic and limnetic fish were fed whole blood worms once daily. During October 2017, juvenile stickleback (now 3-4cm in length) were elastomer tagged in the dorsal musculature, with location and colour varied for unique individual identification. Immediately prior to introduction to the experimental mesocosms, fish were weighed to the nearest 0.01g and the left side photographed. Also during October 2017, American Signal crayfish individuals were collected using baited minnow traps from Garden Bay Lake and Lily Lake on the Sunshine Coast, BC. Crayfish (7- 46 11cm in length) were transported back to the University of British Columbia and added to mesocosm tanks immediately. 3.2.2 Mesocosm construction and experimental design To estimate the effect of crayfish on survival and performance of stickleback, juvenile limnetic, benthic and F1 hybrid stickleback were placed in outdoor mesocosms in either the presence or absence crayfish. The experiment was performed in an array of 50 circular mesocosms each having a volume of 1136 L, a depth of 64 cm, and a diameter of 175 cm. In May 2017, mesocosms were prepared outdoors with 12.5 kg dry weight play sand to generate an ~1cm thick substrate layer and filled with water, and subsequently seeded with ~1.5 kg of loosely packed benthic mud from nearby reservoir ponds as well as ~1L of water containing densely packed zooplankton collected from adjacent experimental ponds using plankton net with a mesh size of 66 µm. 1L zooplankton additions came from a 50L stock, keeping community composition similar between mesocosms. Mesocosms were left unmanipulated from May-August 2017 to allow for the aquatic community to establish. In August of 2017, 0.976 g KNO3 and 0.067 g KH2PO4 were added to each mesocosm to provide nutrients and stimulate phytoplankton growth. In October 2017, macrophyte beds (comprised primarily of Chara sp. and Potamogeton amplifolius) were collected from adjacent experimental ponds, and a patch ~30cm in diameter was added to each mesocosm. Additionally, three clay tiles to provide a standardized substrate for algal growth (2cmx2cm) and two PVC pipes (30cm in length and 6.4cm in diameter) were added to each mesocosm to provide hiding places for both crayfish and stickleback. Mesocosms were then 47 randomly assigned to either treatment or control, totaling 25 of each treatment. All mesocosms were treated identically with the exception of two crayfish that were added to each assigned treatment tank. There was no risk of reproduction as crayfish eggs typically hatch in April (Karjalainen et al., 2015). One week after crayfish addition, six juvenile fish of each cross type (18 total) were introduced into the cattle tanks so that each tank contained all three cross types. The experiment began in October 2017 when juvenile fish were large enough to be safely elastomer tagged, and were removed 8 weeks later, at which point unseasonably low temperatures led to water freezing in the mesocosms, and consequently experimental termination. During the experiment, mesocosms were surveyed biweekly for mortalities that were subsequently removed but not replaced. At experiment termination, fish were recovered using minnow traps and dip nets, humanely euthanized using buffered MS-222 (0.5g/L), identified by elastomer tag placement and colour, weighed to the nearest 0.01g and left side photographed. Growth rate and survival were measured in these juveniles as proxies for fitness, as growth rate is linked to feeding performance and fecundity in threespine stickleback(Arnegard et al., 2014; Bolnick & Lau, 2008; Schluter, 1995a). 3.2.3 Benthic invertebrate and zooplankton sampling and analysis After the 8-week experiment period, but before fish collection, four zooplankton samples were collected from the full depth of the water column in each cattle tank (~55cm) using a 2-inch diameter PVC pipe. A tennis ball attached to a rope acted as a stopper once the pipe 48 was filled with water. Samples were strained using a 66 µm mesh to retain most adult zooplankton that were subsequently stained and preserved with iodine. Zooplankton were measured using an ocular micrometer in a dissecting microscope, and specimens were identified to a taxonomic level ranging from family to subclass. Length measurements of specimens were used to estimate biomass (in ug), using length-weight regressions from Dumont et al., (1975)⁠. At the time of zooplankton collection, two 120 cm2 samples of full-depth benthic substrate (~1cm) was also collected from each mesocosm. Locations were consistent in each mesocosm, with one near the mesocosm edge and one near the center (Ingram et al., 2012). The entirety of the samples was searched for benthic invertebrates by hand immediately after collection. Benthic invertebrates were preserved in ethanol, and an ocular micrometer in a dissecting microscope was used for identification and length determination. Identification was essential for accurate biomass estimates and ranged from family to class level. Length measurements were converted to biomass (in mg) using published length-weight regressions (Baumgärtner & Rothhaupt, 2003; Benke et al., 1999; McKinney et al., 2004; Miyasaka et al., 2008). Benthic invertebrate biomass was converted to 𝜇g so that all invertrebrate measures were in the same units, and total biomass per mesocosm was calculated as the combined mass of zooplankton and benthic invertebrates. Biomass estimates were right-skewed, so 49 estimates were calculated as the natural log after which data were much more normally distributed. To test if crayfish impacted zooplankton and benthic invertebrate communities differently, benthic invertebrate biomass and zooplankton biomass were treated separately. Some tanks had no estimate for either zooplankton or benthic invertebrates, meaning they had zero values when datasets were separated. To correct for this, 1 was added to each value in both dataset before being log transformed, allowing for zeros to be included in the dataset. 3.2.4 Growth and survival estimates All juvenile fish were weighed and photographed before introduction and after removal from mesocosms. The proportion survived was calculated as the number of fish surviving at the end of the experiment compared to survival on Day 3. Individuals that died before Day 3 were assumed to have died as a result of stress from introduction rather than experimental impacts. Exact growth and survival of each fish was determined individually because each fish could be uniquely identified from elastomer tags applied before introduction. Using the program ImageJ, length of each fish was measured and growth was calculated as the log final length – log initial length. Weight differences were calculated similarly, as log final weight – log initial weight. For all mesocosms, we calculated average change in length and weight for each cross type. There were three different response variables: (1) length change, (2) weight change, and (3) survival in individually marked fish. 50 3.2.5 Tests of selection Treatment effects on the relative fitness of hybrids were tested using the interaction term between treatment and cross type in linear models fitted to survival and growth measures. To determine if crayfish impacted overall fish survival, we ran a linear model with proportion of all fish surviving (as determined above) as the response variable and Treatment as the only explanatory variable. Surviving fish were then classified into either benthic, limnetic or hybrid, and the proportion of fish surviving within each cross type was calculated as number of fish (within a cross type) at the end of the experiment / number of fish present (within that cross type) on Day 3 of the experiment. This was again done for each mesocosm. We fit a linear mixed effects model to proportion survived with cross type, treatment, and their interaction as predictors, and mesocosm as a random effect. Treatment effects on somatic growth were determined by running separate linear mixed effect models on length and weight tank averages calculated above. In both cases treatment, cross type and their interaction were predictor variables and mesocosm was a random effect. Previous research has shown that notable variation exists in individual fitness even among hybrids within the F1 generation, indicating that relying solely on population-level assessments of hybrid fitness may not capture the entirety of fitness changes (Burke & Arnold, 2001; Liu et al., 2021). Large variation in growth within a cross type may be indicative of wide variation in individual fitness. To explore this we tested treatment effects 51 on this measure by calculating the coefficient of variation for each cross type. This was calculated as (sd of length difference/mean length difference)*100 for each cross type in each mesocosm, generating 3 values per tank. We then ran a linear mixed effect model with coefficient of variation as the response variable, and Treatment, cross type and their interaction as predictor variables and mesocosm as a random effect since multiple cross types were raised within a single mesocosm. Fish density was not equal between tanks at the end of the experiment. To account for different densities, we fitted a linear model with change in length (log scaled) as the response variable, and Treatment, cross type and the number of fish present at the end of the experiment as predictors, as well as the interaction between treatment and cross type. When considering other model interactions, AIC values showed all models to be equal. As such, the model with only interactions between treatment and cross type was selected as this model directly addresses our hypothesis of differential growth based on cross type under treatment conditions. For visualization purposes, plotting of these data (Fig 3.4) was done using predicted values based on a multiple regression with cross ID, treatment and fish denisty as predictors, as well as the interaction between treatment and ID. 3.3 Results 3.3.1 Invertebrate biomass response Total invertebrate community biomass was 2.2x higher on average in the control (no crayfish treatment) than in the crayfish treatment (linear model; F1,47=19.045, p= 6.949 x 52 10-5). Zooplankton biomass was similar between treatments (Fig 3.1A) and did not differ significantly between control and treatment (F1,48=0.0157, p = 0.901). However, benthic invertebrate biomass in the crayfish treatment was depleted to about half the amount compared with control mesocosms (Fig 3.1B) (F1,47= 19.91, p= 5.06 x 10-5), suggesting that crayfish are significant consumers of benthic invertebrates. Figure 3. 1: Natural log-transformed invertebrate biomass at the end of the experiment. Violin plots of A) mesocosm mean zooplankton biomass (𝛍g) and B) mesocosm mean benthic invertebrate biomass (mg) in the two treatments. Black dots (n=50) indicate individual tank means. Horizontal lines indicate mean biomass per treatment. 3.3.2 Fish survival Mean survival of all stickleback was negatively impacted by the presence of crayfish, with control mesocosms having 1.25x more fish at the end of the experiment than treatment mesocosms (Fig 3.2A) (linear mixed model; F1,48=11.23, p=0.00158). Furthermore, survival was not equal among cross types. Benthic individuals had the highest survival, hybrids had 53 intermediate survival and limnetic individuals had the lowest survival across both treatments (F 2,96 =13.08, p<0.001). It should be noted that mesocosms do not contain significant limnetic habitat relative to benthic habitat. Between cross types there was no difference in the magnitude of the survival differences observed between control and treatment (interaction term, F 2,96=1.297, p=0.278), though limnetic survival appeared to decline the most in the presence of crayfish (Fig.3.2B). Figure 3. 2: Stickleback survival by treatment. Violin plots of fish survival by A) Treatment and by B) Treatment and cross type. Black dots indicate individual tank means. Horizontal lines indicate median survival. Cross types are benthic (B), limnetic (L) and F1 hybrid (H). 3.3.3 Growth Mean growth, as measured by length change, differed significantly among cross types but not between treatments. Growth was largest in benthics, followed by hybrids and limnetics (linear mixed effects model, F2,88=147.974 p<2 x 10-16). It should be noted that mesocosms 54 do not contain significant limnetic habitat relative to benthic habitat. Treatment did not predict length change (interaction, F2,88=1.250, p=0.292), observed as no difference in mean growth of hybrids between treatments, and both benthic and limnetic individuals showing only a ~10% reduction in growth in the presence of crayfish (Fig. 3.3A). Weight change showed a near identical pattern to length change with a significant difference between growth of cross types, with benthic individuals showed the largest change, followed by hybrids and limnetic individuals (F2,88=38.900 p=6.665 x 10-15). Again, treatment did not predict length change (interaction, F2,88=0.612, p=0.544). However, we did observe a ~20% reduction in growth of benthic and limnetic crosses in the presence of crayfish, while no difference was observed in hybrid crosses (Fig 3.3B). Coefficient of variation showed the opposite pattern of length and growth change, with limnetics the most variable, followed by hybrids and benthics the least (F2,133=24.813, p= 6.954 x 10-10) (Fig. 3.3C). In all cases, there was a significant difference between control and treatment (F1,133=5.158, p= 0.0248), but a linear mixed effects model showed the interaction between treatment and cross type was not significant (F2,133=0.574, p=0.565) (Fig 3C). The growth analyses above are possibly confounded by treatment effects on survival, and hence density, resulting in different final fish density between tanks. A linear mixed effects model showed treatment, cross type and density were all significant in predicting growth 55 Figure 3. 3:Growth changes by treatment and cross type. Violin plots of natural log-transformed fish growth by treatment and cross type as indicated by A) Length and B)Weight. C) Coefficient of variation in log-transformed fish growth (length) for each cross type by treatment. Cross types are benthics (B), limnetic(L) and F1 hybrids. Black dots (n=50 per cross type) indicate individual tank means and horizontal lines indicate means per cross type. difference (F1,133 = 6.810 p=0.0101, F2,133 = 102.560 p< 2.2 x 10-16 and F1,133 = 10.244 p=0.00172 respectively). However, the interaction between treatment and cross type was 56 not significant. At high fish density, the benthic individuals showed a greater reduction in growth compared to other cross types (Appendix B.1). When controlling for density, we observed the largest reduction in growth in benthic crosses, though this was not significant. Limnetic crosses showed a relatively intermediate growth reduction in treatment tanks, and hybrid crosses showed very little change (Fig.3.4). Figure 3. 4: Fish growth in relation to fish density. Natural log-transformed fish growth (length) in relation to the number of fish within each tank present at the end of the experiment at the end of the experiment. Regression lines are predicted values based on a multiple regression with cross ID, treatment and fish density as predictors, as well as the interaction between treatment and ID. All slopes were assumed to be equal. Colours are different cross types, and shapes of points are treatment categories. Individual species plots that do not assume equal slopes can be found in Appendix B.1. 0.040.060.085 10 15Density (# of Fish)Log(Final Length/Initial Length) IDBenthicHybridLimneticTreatmentControl Crayfish 57 3.4 Discussion Hybridization of species is increasingly observed after environmental change (Anderson, 1948; Lamont et al., 2003; Mecham, 1960; Seehausen et al., 1997) and can be attributed to either a change in hybrid fitness (Grant & Grant, 1996) or a breakdown in premating reproductive isolation (Seehausen et al., 1997), which we have termed the Altered Hybrid Fitness hypothesis and Reduced Premating Isolation hypothesis, respectively. We experimentally tested the Altered Hybrid Fitness hypothesis and investigated whether there would be an observed increase in relative hybrid fitness following environmental change, inspired by the species collapse of threespine stickleback in Enos Lake on Vancouver Island. There, the benthic and limnetic stickleback species pairs formerly coexisted with stable reproductive isolation between species for thousands of years, but rapidly collapsed into a hybrid swarm following the invasion by signal crayfish (Foster et al., 2003; E. B. Taylor et al., 2005). As such, this experiment investigated the effect of crayfish presence on resource availability, and subsequent changes in hybrid fitness. Overall, we observed a consistent negative impact of crayfish on the growth and survival of all stickleback individuals, although there was a slightly greater negative effect on the growth of benthic fish compared to other cross types. Additionally, we found evidence that crayfish negatively impacted abundance of benthic invertebrates. Fish survival was lower in the presence of crayfish, but there were no significant differences in the decline between cross types. We did not observe any significant differences in hybrid growth between the treatments; however, there was a trend suggesting that crayfish had a slightly more 58 negative effect on the growth of benthic stickleback, particularly at higher densities, although this difference was not statistically significant. Overall, these results do not provide conclusive evidence either supporting or disproving the hypothesis that crayfish alter the fitness of hybrids. When extrapolating these findings to Enos Lake, it is possible that altered hybrid fitness played a role in the collapse, but our results suggest that this role may have been minor and not sufficient to explain the collapse entirely. Previous work on Enos Lake after the collapse has shown that crayfish can have multiple impacts on the environment. This includes increases in water turbidity, as well as loss of vegetation and benthic stickleback breeding habitat (Behm et al., 2010; E. B. Taylor et al., 2005; Vaeßen & Hollert, 2015). Crayfish are known to be omnivorous, with a diet that ranges from algae to live or decomposing animals. Our experiment shows that crayfish reduce benthic invertebrate biomass. Since benthic invertebrates are the primary food source of benthic stickleback, crayfish should have an unequal impact on resource availability of benthic and limnetic stickleback, as crayfish directly compete with benthic stickleback for resources. In cases where resources are limited, such as when fish density, and thus competition, is high, this should have a disproportionately negative impact on benthic individuals. However, we did not detect large differences in impact between cross types in our study. Crayfish could have impacted stickleback through competition, predation, and stress. We would expect competition for resources to negatively impact growth, but found that 59 benthic and hybrid individuals were unaffected by fish density in control tanks, suggesting that competition was not high in the absence of crayfish. This differed in the presence of crayfish, where we observed a greater reduction in growth as fish density increased, indicating that further depletion of benthic invertebrates by crayfish became a strain on resources. A nonsignificant greater growth reduction was observed in benthic stickleback, whose diet consists primarily of benthic invertebrates, than in hybrid crosses, suggesting competition as a potential cause for reduction in growth in the presence of crayfish. However, observed growth decline was also relatively high in limnetics, which is unlikely to be explained by resource depletion, though it may be contributed to by a lack of limnetic habitat in the mesocosms relative to benthic habitat. We also observed a significant reduction in total stickleback survival when coexisting with crayfish (Fig 3.2). Not all dead stickleback were recovered during the experiment, suggesting that crayfish may have been eating stickleback; this was confirmed when crayfish were observed eating dead stickleback on two occasions. Whether crayfish preyed upon stickleback or scavenged on already deceased stickleback is unknown; however, this does suggest that crayfish may be predators, as well as competitors, of threespine stickleback. Lastly, the presence of crayfish may have had behavioural impacts on fish. Chronic stress from adverse heterospecific interactions has been shown to negatively impact growth of multiple fish species (Clinchy et al., 2013; Valenzuela et al., 2018) and when resources are scarce and density is high, stickleback would be put into more frequent conflict with crayfish in the benthos of mesocosms. Benthic stickleback compete directly with crayfish for dietary resources, and limnetics appear to be less stress-tolerant than other cross types, showing higher mortality 60 during transportation and introduction to aquaria (field observation, unpublished). This may explain why we saw a large reduction in limnetic growth and survival despite occupying different dietary niches; limnetic fish may be impacted more by the stress of crayfish presence than reduction of resources. There has been much discussion as to the mechanism of action that led to the Enos Lake collapse. Some cases of hybrid swarm formation can be clearly attributed to the breakdown in a particular isolating mechanism. This is true of hybridization in African cichlids being attributed to turbidity negatively impacting discriminatory mate choice, and in hybrid Galapagos finches, where fluctuating dietary resources led to improved hybrid fitness (B. R. Grant & Grant, 1996; Seehausen et al., 1997). Both mechanisms seemed to be important in the case of the Enos Lake hybrid collapse. Previous work has suggested the cause may be a breakdown in premating reproductive isolation as a result of changes in mating behaviour of limnetic stickleback in the presence of crayfish (Velema et al., 2012). Other studies of present day Enos Lake stickleback show no reduction in growth rate of fish having intermediate phenotypes, and that body shape does not predict diet as it does in extant species pairs lakes (Behm et al., 2010). Our data suggests that crayfish addition might have improved relative hybrid fitness slightly, likely as a result of resource competition between benthic individuals and crayfish. However, it should be noted that limitations in our study mean that fitness in our experiment may not accurately reflect relative hybrid and parental fitness in Enos Lake. 61 Biological systems are complicated, with many aspects simultaneously affecting individuals, making it hard to tease apart the likely causes and importance of observed changes. Experiments are necessary to provide further insights into the causes of changes in complex systems and providing clear and controlled tests of hypotheses grounded in theory. In this case, we present experimental evidence that even over the short timescale of eight weeks, the introduction of crayfish resulted in a significant decrease in growth and survival of threespine stickleback, but that hybrid fitness appears not to have been impacted, whereas parental classes trended towards a decrease in fitness. However, these results are limited by various components of the experimental design. Firstly, and most notably, is that mesocosms are on a very small scale, and thus do not accurately represent all of the complexity observed in a lake. When introducing a predator into a confined space, it limits the stickleback’s ability to flee and hide, which could have a different magnitude of impact on different species classes. Furthermore, mesocosms are notably lacking a pelagic open water zone, inherently reducing the niche space for limnetic stickleback. This is a limitation in all mesocosm experiments involving limnetic stickleback and might explain why limnetic individuals were heavily impacted by the addition of crayfish despite them having different dietary niches in the wild. Secondly, this experiment took place in the autumn when juvenile stickleback were small enough to support a large sample size, but large enough to be safely elastomer tagged. The daily temperature in the cattle tanks was 2-12°C during the experiment and fish were likely more sluggish and productivity in the tanks was likely significantly slowed compared with summer, resulting in slower growing fish, and occasionally reductions in weight compared to starting sizes. This effect 62 was equal across all mesocosm tanks, but it might have limited the magnitude of changes possible, compared with a more productive time of year. Similarly, despite seeing some treatment effects in eight weeks, a longer experiment might produce larger changes, exaggerating trends we observed. Lastly, our experiment only had benthic, limnetic and F1 hybrids when in reality, the Enos lake ecosystem has numerous hybrid classes, including late generation hybrids and backcrosses (Taylor & Piercey, 2018). Often, hybrid fitness in a novel environment is improved as a consequence of novel combinations of standing genetic variation, but those improvements are rarely, if ever, observed on a population scale in an F1 generation (Arnold, 1997). Later generation hybrids might have allowed for purging of deleterious combinations and selecting on those that are most beneficial. This generates a scenario in which early in a hybrid collapse we see low average hybrid fitness, but can have some individuals with high hybrid fitness that propagate later in a collapse (Arnold, 1997). The reality of hybrid fitness in Enos Lake could therefore be obscured by only using F1 hybrids in our experiment. Irwin (2020) has suggested that hybrid fitness can be more significant than mate choice in maintaining species boundaries. A small reduction in hybrid fitness can be more impactful in species maintenance, when combined with strong assortative mating, than high premating reproductive isolation alone because reduced hybrid fitness removes those hybrid individuals produced by incomplete premating isolation. Without sufficiently low hybrid fitness, a system with strong but incomplete assortative mating will eventually collapse (Irwin, 2020). Even slight alterations in relative hybrid fitness have the potential 63 to significantly influence the trajectory of a hybridizing population (Buerkle et al., 2003). Our study sought to experimentally test these theoretical findings. Although our present study did not yield conclusive results regarding the role of crayfish in altering hybrid fitness, we did observe clear evidence of depleted benthic dietary resources. Over an 8-week period, we observed modest changes in relative hybrid fitness, suggesting that further depletion of benthic resources over an extended timeframe, along with other factors specific to Enos Lake that were not present in our experimental system, could potentially lead to altered hybrid fitness mediated by crayfish. While our experiment may not have provided strong evidence in this regard, it remains possible that stickleback populations in Enos Lake were close to a tipping point and experienced changes in relative hybrid fitness that were not detected in our study, resulting in collapse despite strong assortative mating. Regardless, the mechanisms behind the Enos Lake collapse remain elusive and further investigation is warranted to understand the underlying causes of this collapse. 64 Chapter 4: When two become one: Evolution after hybridization 4.1 Introduction Evolutionary biologists have long been investigating the diverse array of species to comprehend variation in phenotypic traits. This variation is typically explained as adaptation to distinct environments and was considered to evolve via a primarily stepwise process, where traits gradually diverged from the existing phenotype. Hybridization was viewed as a rare, often detrimental process (Arnold, 1997; Dobzhansky, 1937; Mayr, 1942). However, the advent of genome sequencing has provided evidence that not only is hybridization common, but that the outcomes of ancient hybridization events are still prevalent in the genomes of species today (Moran et al., 2021). Certain taxa, including Heliconius butterflies, sunflowers, and swordtail fish, have gained notoriety for having genomes containing significant genetic material resulting from historic introgression, with some estimates exceeding 10% (Cui et al., 2013; Massardo et al., 2020; Rieseberg, 1997). Moreover, in the case of the Lake Victoria cichlids, an ancient hybridization event has been proposed as the driving force behind their adaptive radiation (Meier et al., 2017). Despite this, how selection acts on hybrid genomes remains an area of uncertainty. Hybridization, by definition, generates new combinations of traits from distinct genomic lineages, whether those traits be behavioural, genotypic or phenotypic (Arnold, 1997). Phenotypic trait combinations may be intermediate or transgressive to parental types, or may even produce phenotypic mismatch, whereby hybrids resemble one parent population for some traits and the other parent population for other traits (Chhina et al., 2022). 65 Genomic ancestry of hybrid populations can be attributed to a major and minor parent, with proportions depending on the contributions of each parent species to the overall genome of an individual or population (Schumer et al., 2018). Hybridization is often assumed to reduce fitness, and hybrid populations in the first few generations after formation display more rapid selection and allele frequency changes than in older hybrid populations (Veller et al., 2021). The evolution of hybrid genomes involves changes in genomic ancestry following hybridization. There are various mechanisms of selection that act on these genomes but can broadly be described as involving three processes: hybrid incompatibilities, hybridization load, and ecological selection. We expect these processes to affect the genome in different ways, and changes in ancestry patterns in hybrid populations can provide insights into which of the selection mechanisms is acting on the genome after hybridization. Dobzhansky-Muller hybrid incompatibilities (DMIs) occur when populations that diverged from a common ancestor produce hybrid offspring that experience negative epistatic interactions between alleles at different loci. These interactions arise due to the accumulation of mutations in loci that may produce similar phenotypes in the parent populations but are incompatible when combined in hybrids (Dobzhansky, 1937). The presence of DMIs is predicted to change allele frequencies over time at the effected loci in favor of alleles inherited from the major parent. All else being equal, selection on DMIs should lead to reductions in frequency of minor-parent alleles in a hybrid population regardless of which species is the minor parent because these alleles interact 66 antagonistically with loci found in the majority of the genome (Schumer et al., 2018). Selection is thus predicted to be frequency dependent. In contrast, hybridization load refers to a scenario where, upon formation of a hybrid population, the parental population with a higher genetic load introduces an excess of deleterious mutations into the hybrid population (Gagnaire, 2020). Parent populations may exhibit different genetic loads, which can arise from variations in mutation rate, genetic drift, and selection pressure. In populations with lower effective population sizes or those experiencing inbreeding, genetic diversity is typically reduced, and selection pressures are weakened (Mathur & DeWoody, 2021). As a result, these populations are more susceptible to the accumulation of mildly deleterious mutations over time as it is more challenging for natural selection to effectively eliminate these mildly deleterious mutations despite purging highly deleterious mutations from the population (Hedrick & Garcia-Dorado, 2016). Over time, selection in hybrids is predicted to remove the unfavorable mutations and the haplotypes linked to them, leading to a gradual reduction in ancestry from the parent having the larger mutational load regardless of frequency in the hybrid genome (Moran et al., 2021). Finally, ecological selection refers to the process by which environmental factors determine the survival and reproductive success of individuals varying in phenotypic traits (Vamosi et al., 2000). The direction and intensity of ecological selection’s effect on the hybrid genome are highly dependent on the specific environment in which individuals exist. In 67 hybrid populations, the process predicts that the parental alleles most advantageous in the local environment are expected to be favored, irrespective of whether they derive from the minor or major parent (Schumer et al., 2018). This process predicts that multiple independently evolved hybrid populations inhabiting similar environments should evolve in parallel phenotypically and in the genome. Parallel evolution under similar environmental conditions is strong evidence of natural selection, as has been shown in numerous taxa, including Anolis lizards, Mexican cavefish, and threespine stickleback species pairs (Gross et al., 2009; Schluter & Nagel, 1995; Schoener, 1969). Under ecological selection the same principle applies to hybrid populations. On the other hand, studies have shown that parallel evolution of phenotype does not necessarily translate to parallel evolution in genotype (Poore et al., 2023). This is because similar phenotypes can arise from different mutations, particularly when populations have evolved independently and without gene exchange (Stuart et al., 2017). Testing the ecological selection mechanism can be additionally challenging because it can be difficult to determine whether environments truly are similar. Given the diverse and often conflicting forms of selection acting on genomes, the relative importance of these three mechanisms of selection on hybrid populations is not well understood. To address this question, we tested their effects on phenotypic and genome evolution in natural and introduced hybrid populations of threespine stickleback (Gasterosteus aculeatus). Limnetic and benthic species pairs of threespine stickleback have evolved independently on five occasions ~12,000 years ago in small lakes of southwestern 68 British Columbia (Bell & Foster, 1994). The sympatric species exploit different ecological niches within lakes and have diverged in numerous traits such as body shape, feeding behavior, and defensive armor (McPhail, 1993; Schluter & McPhail, 1992). Although microsatellites and mtDNA revealed that the pairs result from independent colonization of lakes at the end of the ice age, they are divergent at many of the same loci (Conte et al., 2015; Jones, Chan, et al., 2012), which is thought to result from selection on a similar pool of ancient standing genetic variation present in the marine ancestral population (Colosimo et al., 2004; Conte & Schluter, 2013; Roberts Kingman et al., 2021). In all lakes, limnetic stickleback are characterized by a small and streamlined body shape which is adapted for swimming in open water and feeding on zooplankton in the pelagic zone of lakes. These species have a higher number of gill rakers that aid in filtering their food, and they also possess long dorsal and pelvic bony spines (McPhail, 1993; Schluter & McPhail, 1992). In contrast, benthic stickleback species are larger, deep-bodied, and have shorter pelvic and dorsal spines. They specialize primarily on macroinvertebrates in the sediments of the littoral zone and have fewer, shorter gill rakers (McPhail, 1993; Schluter & McPhail, 1992). These sympatric species have strong assortative mating but still produce fertile hybrid offspring, though these have been shown to be less fit in the wild (Rundle & Schluter, 2004). Despite this, at least three hybrid populations of benthic and limnetic threespine stickleback are known along the BC coast, each with unique genetic ancestry compositions: Enos Lake, Second Lake, and Murdo Frazer Pond (see Figure 4.1A). In Enos Lake the benthic species is its majority parent (E. B. Taylor et al., 2005) and in Murdo Frazer Pond the limnetic species is the majority parent (E. B. Taylor & Piercey, 2018). The third population, 69 Second Lake, is comprised of descendants of F1 hybrids of equal parentage contributors that were introduced to a stickleback depauperate lake as a part of an experiment (McPhail, 1993). All three hybrid populations inhabit small, coastal freshwater lakes, and in the species pairs lakes that contributed to the hybrid populations, the benthic species consistently exhibited a smaller census population size compared to the limnetic contributor.(Schluter et al., 2017.). We took advantage of these three hybrid populations to investigate the effects of different selection forces driving their evolution. We collected contemporary samples of all three populations and compared them with historical samples, enabling us to perform multiple phenotypic analyses and whole-genome comparisons to answer three critical questions: (1) What is the direction of phenotypic evolution in the hybrid populations? (2) What is the direction of genomic evolution? and (3) Are the chromosomes that underlie known phenotype QTL evolving in the same direction as the phenotypes in these hybrids? These questions provide insight into the underlying selection mechanisms driving hybrid evolution and can help us better understand the consequences of hybridization in natural populations. If DMIs were the primary selection force, we predict a shift towards the major parent, resulting in divergent evolution between populations of opposite majority parentage. Under hybridization load, we predict a shift towards a more limnetic parent ancestry in all populations. This prediction is based on observations from the Paxton Lake parent population, where benthic stickleback have a smaller effective population size (Wang, 2018). Additionally, Paxton Lake benthics have a reduced census population size compared to limnetics, which 70 corresponds to their lower effective population size. We extend this reasoning to all species pairs in other lakes that similarly exhibit lower benthic census population sizes (Schluter et al., 2017). In contrast, if ecological selection is the primary selection force, we would expect all populations to converge to be more similar (to the extent that their environments are similar) regardless of their major/minor parent ancestry contribution. In the case of ecological selection we would predict the areas of the genome associated with phenotypic QTLs to have the largest shifts in parental ancestry. Under the other selection mechanisms, selection would be highest in areas of incompatibilities and mutations that are not necessarily associated with phenotypic QTLs. 4.2 Methods 4.2.1 Study populations Enos Lake, located on Vancouver Island, BC is a natural hybrid population. The benthic and limnetic populations that once persisted in the lake interbred and collapsed into a hybrid swarm following lake invasion by the American Signal crayfish around 1990 (Fig. 4.1B) (Behm et al., 2010; Kraak et al., 2001; E. B. Taylor et al., 2005; E. B. Taylor & Piercey, 2018). Microsatellite genotyping close to the time of the collapse indicated that the benthic species was the majority parent of the new hybrid population (E. B. Taylor et al., 2005). The hybrid stickleback population in Second Lake on Texada Island, BC was formed when F1 crosses between benthic and limnetic stickleback from nearby Paxton Lake were introduced by J.D. McPhail in 1981 (McPhail, 1993). Second Lake previously contained no stickleback, and so the population began with neither benthic nor limnetic as a major 71 parent contributor. The third hybrid population, in Murdo Frazer Pond in North Vancouver, was formed when the "limnetic" stickleback species from Enos Lake was introduced in 1991 (E. B. Taylor & Piercey, 2018). The pond previously contained no stickleback. The introduced fish were phenotypically limnetic; however, subsequent analyses revealed regions of the genome with benthic alleles present, indicating they likely included hybrids (E. B. Taylor & Piercey, 2018) and we treat them here as a hybrid population with limnetic as the majority parent. Figure 4. 1:A) Map of populations of interest. Yellow dots indicate extant benthic and limnetic species pairs lakes: Priest, Paxton and Little Quarry Lakes. Green dots indicate populations that contain hybrid populations: Enos, Murdo Frazer, and Second Lake. Enos Lake once contained a species pair but has since collapsed into a hybrid population. Murdo Frazer is an introduced population of “limnetic” fish from Enos Lake after the collapse began, and Second Lake is an introduced population of F1 hybrids from Paxton Lake. B) Morphological representations of a (top) benthic (middle) limnetic and (bottom) intermediate/hybrid threespine stickleback Vancouver Island 72 The three lakes, Enos Lake, Second Lake, and Murdo Frazer Pond, are all temperate, coastal, freshwater lakes located 50-350 m above sea level sharing similar ecological characteristics. Murdo Frazer Pond is a small, shallow lake with a surface area of 1300m2. It lacks a pelagic zone and supports only threespine stickleback, with no other fish species present (personal observation). In contrast, Second Lake is much larger, with an open water surface area of 26500 m2 and is also shallow with little pelagic zone. This lake supports both stickleback and cutthroat trout (personal observation). Enos Lake is the largest of the three lakes, with a surface area of 180,000 m2 and a depth of approximately 12m. It has a well-developed pelagic zone that once supported the limnetic species of the species pairs, though there are no other recorded fish species in this lake despite attempted introduction of rainbow trout in the 1940s (Rodgers, 2022). However, as of ~1990, American Signal crayfish now inhabit Enos lake and recent studies have documented a trend away from limnetic morphology (Taylor et al., 2005). 4.2.2 Specimen sampling We caught threespine stickleback for genotyping and phenotyping in both May 2018 and May 2021 (see Table 4.1) using unbaited minnow traps and dip nets. Hybrid stickleback collected at this time from Second Lake, Enos Lake and Murdo Frazer pond represent our “current” population samples. Benthic and limnetic stickleback were collected in May 2018 from Paxton Lake, Priest Lake and Little Quarry Lake as “pure” species references for genomic comparison. All fish samples were humanely euthanized in the field with buffered MS-222 and preserved in 95% ethanol. Historic hybrid stickleback specimens were taken 73 from the Schluter lab collections, with the oldest available formalin fixed specimens being used for phenotypic analyses. Historic samples from Enos Lake in 1980 (pre-collapse) were used as our phenotypic reference for benthic and limnetic comparison. DNA cannot be extracted from specimens that have been fixed in formalin, so the oldest samples for each hybrid population that were preserved in 95% ethanol were selected for genomic analysis (See Table 4.1). Table 4. 1: Stickleback specimens used in analysis. Historic samples are the oldest available in the Schluter lab collection for each lake, where those fixed in formalin are used for phenotyping and those preserved in 95% ethanol are used for genotype analysis. Modern populations were collected in the field. No historic collection of Second Lake exist, so these samples were reconstructed from Paxton Lake F1 and F2 collections in the Schluter lab. Lake Genotype Phenotype Historic Present Historic Present Enos Lake 1999 2018 1980* 1999** 2002 2021 Murdo Frazer 2011 2018 1991 2018 Second Lake Reconstructed Paxton F1 2018 2009 Paxton Lake F2, 1985 gill raker estimates*** 2021 *Enos Lake 1980 samples are benthic and limnetic populations prior to collapse **Enos Lake 1999 sample only used for shape analysis and gill raker counts ***Gill raker estimates are taken from McPhail (1993). 4.2.3 Phenotyping Hybrid stickleback (n=25-30) from each present-day collection were gradually transitioned from 95% ethanol to water (70%, 50%, 20% and 0% ethanol) before being fixed in 10% formalin for 48 hours. Bony features of all fish were stained using 0.001-0.002% w/v alizarin red powder in a 2% w/v potassium hydroxide solution following standard procedures (Peichel et al., 2001). Historic hybrid stickleback samples were already fixed and stained. It 74 is unknown whether samples were prepared following the same procedure, or if after euthanasia went directly into 10% formalin for a few weeks before being stained in alizarin red. We measured the shape of ~250 individuals (25-50 individuals from each lake and timepoint). Twenty-nine landmarks (see Fig 4.2) were chosen to highlight features known to be associated with differences between benthic and limnetic stickleback, such as the insertion points of spines, orbital size, extent of maxilla and overall body depth (see Table 4.2). These landmarks are similar to those used in (Albert et al., 2008). Digital x and y coordinates for these 29 landmarks were obtained by taking photographs of each fish on the left-hand side in a standardized position, and then placing the landmarks on each digital photograph using ImageJ. We also obtained photographs of Paxton F2 fish from previous work to use as an ancestral comparison for Second Lake. We performed a Procrustes analysis in R to superimpose, scale, and align landmarks within lakes using “gpagen()” in the geomorph package, and used these scaled landmarks for further downstream analysis (Adams & Otárola-Castillo, 2013). We counted lateral plates on the right-hand side of each specimen and recorded the presence/absence of a pelvic girdle, as this trait is polymorphic in Second Lake. Presence was counted if any staining was present, even if the pelvic girdle was greatly reduced. We counted the number of gill rakers on both the upper and lower sections of the first gill arch using a dissecting microscope. The lengths of the first and second dorsal spine, as well as the pelvic spine, were measured using ImageJ. If a given trait was absent it was given a value of zero. Spine lengths scale with body size, so trait values were size corrected to compare 75 Figure 4. 2: Landmark position. Bony tissue is highlighted using alizarin red stain. Twenty-nine landmarks are placed in reference to this bony tissue (description in Table 2). Table 4. 2: Description of the landmark positions Landmark Number Landmark position 1 Posterior extent of caudal peduncle 2 Ventral insertion of caudal fin 3 Posterior insertion of anal fin 4 Anterior insertion of anal fin 5 Posterior extent of ectocorocoid 6 Dorsal extent of ectocorocoid 7 Anterior extent of ectocorocoid 8 Ventral extent of operculum 9 Posteriodorsal extent of operculum 10 Anterioventral extent of preopercular 11 Dorsal extent of preopercular 12 Posterioventral extent of preopercular 13 Anterioventral extent of preopercular 14 Posterior extent of premaxilla 15 Posterior extent of maxilla 16 Anterior tip of lower maxilla 17 Anteriodorsal extent of maxilla 18 Anterior extent of nasal 19 Lachrymal at nasal capsule 20 Anterior extent of orbit 21 Ventral extent of orbit 22 Posterior extent of orbit 23 Dorsal extent of orbit 24 Posterior extent of supraoccipital 25 Anterior insertion of first dorsal spine 26 Anterior insertion of second dorsal spine 27 Anterior insertion of third dorsal spine 76 28 Posterior insertion of dorsal fin 29 Dorsal insertion of caudal fin between individuals of different sizes. Traits were size corrected using the equation 𝑌i = Xi – 𝛽(Li –𝐿 ̅) (Vamosi & Schluter, 2002) where Yi is the size-adjusted armour trait, Xi is the original trait for individual i, 𝛽 is the regression coefficient of the un-adjusted armour trait values on body length, Li is the standard length of the individual and 𝐿 ̅ is the 44.5 mm, the average length of all fish. We combined all fish in a single, univariate regression, thus assuming equal slopes across populations and timepoints. Population averages did not differ significantly when using a different slope for each population. 4.2.4 Phenotype analysis Benthic and limnetic stickleback differ in their overall body shape, feeding traits (gill raker number) and defensive traits (dorsal spine length, pelvic spine length, pelvic girdle presence and lateral plate number) (Schluter & McPhail, 1992). To evaluate shifts in individual phenotypic traits, we compared each of these traits for each lake between timepoints. Morphological analysis was done by performing a linear discriminant function analysis to separate benthic from limnetic body shape along a single axis. We used 13 benthic and 13 limnetic stickleback from Enos Lake (pre-collapse) as a training data set, and then used the predict() command in R on the entire dataset to classify all stickleback populations on the same axis. Mean LD score was calculated for each population, where negative LD is benthic-like and positive LD score is limnetic-like, and pooled standard deviation was calculated for the historic and present day samples of each lake. Shifts in 77 body shape were calculated as the number of standard deviations the present-day mean has moved away from the historic mean. A one-way ANOVA was used to test if there were significant differences in body shape between Enos Lake fish collected at different timepoints. For all meristic measurements, Enos Lake timepoints are 2002 and 2021, Murdo Frazer Pond timepoints are 1991 and 2018, and Second Lake timepoints are samples from 2021 with photos of Paxton F2 individuals from Arnegard et al., (2014) as a representative historic sample. The exception to this is gill raker number in Second Lake, where no physical specimens were available, so the historic value is a mean value reported from 1985 (McPhail, 1993). The significance of shifts in meristic trait values were calculated by performing a paired t-test between historic and present day timepoints for each of Enos, Murdo Frazer and Second Lakes. In the case of gill raker number, only the historic mean is known for Second Lake, so a one sample t-test was performed using the historic mean and the full contemporary sample. Individuals whose trait value was 0 were excluded from comparisons of spine lengths. 4.2.5 Genotyping Whole genome sequences of 25-40 stickleback from each population of interest were collected. Present day samples (2018 collection date) had DNA extracted from stickleback fin clips using DNeasy® Blood & Tissue Kit (Qiagen, Hilden, Germany) for each of the populations of interest: Paxton limnetic, Paxton benthic, Priest benthic, Priest limnetic, 78 Little Quarry limnetic, Little Quarry benthic, Enos Lake, Murdo Frazer Pond and Second Lake. Historic fish samples (Enos Lake 1999 and Murdo Frazer Pond 2011) had DNA extracted using a standard phenol-chloroform procedure. In cases where DNA failed to be extracted from fin clips due to age of the sample, specimen muscle tissue was used for extraction. Library preparation was performed with Nextera XT DNA Library Preparation Kit (Illumina). The whole-genome libraries were sent to Genome Quebec for sequencing on an Illumina Hi-Seq 4000 which was successful for Paxton benthic n=31, Paxton limnetic n= 33, Priest benthic n=31, Priest limnetic n= 28, Little Quarry benthic n=30, Little Quarry limnetic n= 27, Second Lake 2018 n= 16, Murdo Frazer 2018 n= 25, Murdo Frazer 2011 n=6 and Enos Lake 2018 n=25. Historic samples for Enos Lake were not successfully sequenced due to poor quality. Sequences were demultiplexed, after which Trimmomatic-0.39 (Bolger et al., 2014) was used to remove adaptors and redundant primer sequences from short fragments and filter out low quality sequences. Trimmed, sorted sequences were aligned to the stickleback reference genome v5 using BWA from Picard-1.120 (Li & Durbin, 2009). The GATK-4.1.9.0 pipeline workflow was followed including MarkDuplicates and a base quality recalibration of sequencing reads using the BaseRecalibrator program of GATK 4. The reference dataset of known SNPs was generated from previously published SNP dataset of 21 marine and freshwater sticklebacks (Jones, Grabherr, et al., 2012), which includes only SNPs that have 8 reads supported at all individuals. Coordinates were lifted over from the reference genome v1 (Jones, Grabherr, et al., 2012) to the v5 stickleback reference genome using the file 1withChrUn_to_v5.chain.txt provided by M. White (https://stickleback.genetics.uga.edu). HaplotypeCaller was used to identify single 79 nucleotide polymorphisms (SNPs) in individuals, and GenomicsDBImport was used to generate databases for each chromosome separately. VariantFiltration hard filtered for QD<2.0, SOR>3, FS>60, MQ<40, ExcessHet>54.69 and a minimum quality score 20, and sequences that passed these thresholds were saved in vcf files for downstream analysis. 4.2.6 Principal component analysis Filtered vcf files for each chromosome were combined into a single vcf file using GatherVcfs in GATK 4. To generate PCAs of genomic data, we used PLINK v2 (Chang et al., 2015) without pruning, using only biallelic SNPs, a minor allele frequency cutoff of 0.01 and a king cutoff (kinship coefficient) of 0.499. This generated eigenvectors for the whole genome, from which PC1 and PC2 were plotted for each population separately. PC1 values for all limnetic individuals from Little Quarry Lake, Paxton Lake and Priest Lake were averaged to obtain a singular mean limnetic PC score. The same was done for all benthic individuals from the same three populations. Average PC score was also calculated for each separate hybrid population of Murdo Frazer 2011, Murdo Frazer 2018, Enos Lake 2018 and Second Lake 2018. Hybrid index values were determined for each hybrid population by : ℎ = (𝑏𝑒𝑛𝑡ℎ𝑖𝑐 𝑚𝑒𝑎𝑛 𝑃𝐶1 𝑠𝑐𝑜𝑟𝑒 − ℎ𝑦𝑏𝑟𝑖𝑑 𝑚𝑒𝑎𝑛 𝑃𝐶1 𝑠𝑐𝑜𝑟𝑒)(𝑏𝑒𝑛𝑡ℎ𝑖𝑐 𝑚𝑒𝑎𝑛 𝑃𝐶1 𝑠𝑐𝑜𝑟𝑒 − 𝑙𝑖𝑚𝑛𝑒𝑡𝑖𝑐 𝑚𝑒𝑎𝑛 𝑃𝐶1 𝑠𝑐𝑜𝑟𝑒) Changes in genome ancestry for Murdo Frazer was determined by comparing hybrid index score of Murdo Frazer 2011 compared to Murdo Frazer 2018. Hybrid index of the historic 80 Second Lake population was assumed to be 0.5 and was compared to the calculated present day hybrid index. A single hybrid index value of Enos Lake was determined. 4.2.7 Allele frequency changes Allele frequencies at diagnostic SNPs were measured in hybrid populations and compared with the frequencies of a baseline benthic and limnetic species pair. Priest Lake 2018 benthic and limnetic stickleback were used as the comparison pair, where allele frequencies were determined for each SNP in the genome, and SNPs whose allele frequency difference was >0.7 between the benthic and limnetic populations were treated as diagnostic SNPs to differentiate between populations. A hybrid index for allele frequency was calculated for each diagnostic SNP using the equation: ℎ = (𝑏𝑒𝑛𝑡ℎ𝑖𝑐 𝑎𝑙𝑙𝑒𝑙𝑒 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 − ℎ𝑦𝑏𝑟𝑖𝑑 𝑎𝑙𝑙𝑒𝑙𝑒 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦)(𝑏𝑒𝑛𝑡ℎ𝑖𝑐 𝑎𝑙𝑙𝑒𝑙𝑒 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦 − 𝑙𝑖𝑚𝑛𝑒𝑡𝑖𝑐 𝑎𝑙𝑙𝑒𝑙𝑒 𝑓𝑟𝑒𝑞𝑢𝑒𝑛𝑐𝑦) Hybrid index was then averaged across 50 kbp windows along the genome. Hybrid index (h) for each window was plotted against its position on the chromosome to visualize variation along chromosomes. An h value close to 0 indicates that the hybrid populations is more similar to a benthic ancestry in allele frequency within that SNP window, whereas an index of 1 indicates the hybrid populations is more similar to a limnetic ancestry in allele frequency. An index of h = 0.5 indicates that allele frequencies within the hybrid population are intermediate to the two parent populations. This procedure was use for Enos 2018, Second Lake 2018, Murdo Frazer 2018 and Murdo Frazer 2011 hybrid populations. To 81 estimate the historic population for Second Lake, the allele frequencies for each SNP in the Paxton benthic and Paxton limnetic 2018 population were added together and divided by 2 to generate a representative F1 population. The allele frequencies from this constructed historic Second Lake population were used as the “hybrid allele frequency” in the above equation. This was done for every chromosome of the stickleback genome, excluding mitochondrial DNA. Despite having allele frequencies for each of the three species pair populations, our study uses Priest Lake as the baseline population for comparison. While Paxton Lake serves as the parent population for Second Lake, we lack benthic and limnetic allele frequencies for the parent population of Enos and Murdo Frazer. Due to this limitation, we selected a species pair population that is not the parental population for any of our hybrid populations, aiming to establish a standardized relationship for all comparisons. Little Quarry Lake also provided a standardized relationship to all hybrid populations. However, a genomic PCA (shown in section 4.3.3) revealed that the differences between benthic and limnetic stickleback in Little Quarry Lake are smaller compared to those in Priest and Paxton Lake. Consequently, Little Quarry Lake exhibited fewer diagnostic SNPs between benthic and limnetic individuals, making Priest Lake the optimal population for baseline allele frequencies comparisons. Average hybrid index score for each chromosome of every population was calculated using a weighted averaged, where the number of diagnostic SNPs within a 50 kbp window was 82 used as the weighting factor for h within that window. Mean hybrid index score across each chromosome were visualized using a loess regression. For Second Lake and Murdo Frazer Pond, where two genomic timepoints are available, change in hybrid index over time was calculated as the change from the historic timepoint to the present timepoint using a two sample Welch’s weighted t-test. For Enos Lake, where no historic genomic sample is available, no change in hybrid index could be calculated. We conducted a simple linear regression analysis to examine the relationship between the number of diagnostic SNPs within a 50kbp window and the subsequent change in the hybrid index between timepoints within that window. Specifically, we used the number of diagnostic SNPs as the predictor variable and the change in hybrid index as the response variable. For Enos Lake, where no historical timepoint is available, we assessed this relationship by using the number of diagnostic SNPs within a 50 kbp window as the predictor variable and the absolute hybrid index score in 2018 as the response variable. To investigate the extent to which hybrid index scores in different lakes were correlated, we used Pearson's correlation coefficient. We applied this analysis across all chromosomes to each lake pair: Murdo Frazer-Second, Murdo Frazer-Enos, and Enos-Second, Furthermore, we aimed to explore the potential relationship between the number of phenotypic QTL on a chromosome and the corresponding changes in hybrid index. In order to investigate this association, we calculated Pearson's correlation coefficient between the hybrid index and the number of phenotypic QTL for each chromosome within each lake. QTL estimates per chromosomes were obtained from the supplement of Peichel 83 & Marques (2017) and in Conte et al. (2015). We dropped 63 redundant QTL identified in the combined scan. Our reference genome is v5, but the original QTL chromosome locations use the v1 genome positions (Jones, Grabherr, et al., 2012), and so to correct for this, chromosome locations were lifted over to the v5 genome positions using the file v1withChrUn_to_v5.chain.txt provided by M. White https://stickleback.genetics.uga.edu. 4.3 Results 4.3.1 Phenotypic changes over time We observed a shift towards a more benthic phenotype in all three hybrid populations regardless of their starting mean phenotype. Changes in overall body shape were observed in populations of all three lakes (Fig 4.3). Enos Lake shape in 1980, prior to the species collapse, showed two distinct peaks: one corresponding to the benthic species (mean LD score = -5.93) and the other to the limnetic (mean LD score = 5.54) (Fig 4.3). In 1999, the mean body shape is observed as a unimodal peak with a wide, right-skewed distribution indicative of a majority of individuals having a benthic-like morphology, but some individuals having an intermediate or limnetic-like morphology. By 2002, the mean body shape is further shifted in the benthic direction with a shorter tail in the limnetic direction, and by 2021 Enos Lake stickleback have a sharp, unimodal peak similar to pure benthic species in LD score (mean LD score = -4.976). There is no significant difference in the average shape of Enos Lake populations between 1999, 2002 and 2021 (F81= 0.405, p= 0.668), and this is also not significantly different from the pure benthic population (F93= 1.115, p= 0.347) (Fig 4.3A). The primary difference between timepoints in Enos Lake is the reduction 84 of individuals with a limnetic-like morphology, indicated by a reduction in standard deviation from 1999 to 2021 (sd = 3.93, 2.71 and 2.22 respectively). The shift to a benthic-like morphology over time is even more apparent in Murdo Frazer Pond. In 1991 the hybrid population had a body shape that was highly limnetic-like, with a long tail in the limnetic direction, possibly suggesting that some individuals were pure limnetic. By 2018, after ~ 27 generations, the overall body shape distribution had a mean that is mostly intermediate in phenotype, having moved 1.8 standard deviation units in the benthic direction (Fig 4.2B). The same is true in Second Lake where in 2021, within 40 generations since introduction, mean body shape is closer to the benthic than to the limnetic species in Paxton Lake. The mean lies well to the left of the mean of the reference Paxton F2 cross (Fig 4.2C). In two of the three hybrid populations studied, we found a trend of decreasing gill raker number over time. Specifically, we observed a significant decrease in gill raker number in Second Lake (-1.12, t24 = -5.115, p = 3.105 x 10-5) and a non-significant decrease in Murdo Frazer Pond (as shown in Figure 4.4A). However, in Enos Lake, we observed a reversal of this trend, with an increase in gill raker number of 0.81 in the most recent time point (t128= -2.870, p=0.0048). Of note, when examining an additional timepoint for Enos Lake, we observe a shift towards fewer gill rakers from 1999 to 2002, but this trend changed direction to an increase in gill raker number by 2021 (Figure 4.5). 85 Figure 4. 3 : Density plot of changes in shape morphology show shift to benthic-like morphology over time. Dark blue bimodal peaks are benthic and limnetic fish, while teal peaks represent the historic population morphology and yellow peaks represent the present-day morphology of A) Enos Lake B) Murdo Frazer Pond and C) Second Lake. The green peak in A) is an additional historic timepoint for Enos Lake. All populations are plotted along the same LD axis but are grouped by lake population. Vertical dashed lines represent the mean LD score for the peak it lies within. Negative LD scores are benthic-like while positive LD scores are limnetic-like. 86 Figure 4. 4: Changes in meristic trait values show Murdo Frazer and Second Lake generally evolve to more benthic-like traits over time. In panels A-E, yellow bars are historic population values and blue bars are present day population values (Table 4.1). Black horizontal bars represent population means. Different lake populations are grouped along the x axis. Second Lake has no historic samples for A) gill raker number, so the mean value from MacPhail (1992) was taken. B) Length first dorsal spine, C) length of second dorsal spine and D) length of pelvic spine have all been size corrected. E) Lateral plate number show counts of plates on the left side, and F) the proportion of individuals within a lake having a pelvic girdle across two time points. Enos and Murdo Frazer, yellow and green respectively, showed no change in proportion while Second Lake, in blue, did. 87 Figure 4. 5: Changes in gill raker number within Enos Lake. Each colour shows a different point in time when gill raker number was measured within the population. Dark blue shows Enos Lake in 1980, before the collapse, and teal shows Enos Lake in 1999, shortly after the collapse, while green shows 2002 and yellow shows 2021. Vertical black dashed lines represent mean gill raker number within each population. From left to right, mean lines are 1980 benthic, 2002, 2021, 1999 and 1980 limnetic. Benthic species have fewer gill rakers than limnetic species, meaning that Enos Lake fish had a large initial reduction in gill raker number before a small reversal and increase in gill raker number in contemporary populations. Threespine stickleback species pairs exhibit variation in their armour traits, with limnetic fish typically displaying longer spines and more lateral plates than their benthic counterparts. In Paxton Lake, the benthic stickleback also lack a pelvic girdle, whereas the limnetic stickleback have retained it, resulting in a polymorphic trait in the Second Lake hybrid population. In our study, we found that Second Lake and Murdo Frazer Pond populations consistently exhibited a shift towards more benthic-like traits across all measurements taken, while Enos Lake populations either remained stable or showed a 88 trend towards more limnetic-like traits. Of the armour traits, we observed a slight reduction in the average length of the first dorsal spine in all three lakes, though this reduction was only significant in Murdo Frazer Pond (14%, t45= 2.37, p= 0.022 ) and Second Lake (22%, t32= 2.76, p=0.0094) (Fig 4B ). We found a significant change in second dorsal spine length for all three lakes, with Enos Lake showing a 10% increase (t44= -2.74, p=0.0089), while Murdo Frazer exhibited a 13% decrease (t47= 2.701, p=0.0096) and Second Lake showed the most substantial decrease of 26% (t47= 10.436, p=8.46 x 10-14) (Fig 4.4C). We observed a similar pattern in pelvic spine length, with a significant increase of 9% in Enos Lake (t48=-2.06, p=0.041) and a significant reduction of 17% in Murdo Frazer Pond (t46=4.20, p=0.00013). Second Lake also showed a decrease of 22% in pelvic spine length, but the change was not significant likely due to the small sample size (Fig 4.4D). It should be noted that only 30% of the Second Lake population had a pelvic spine and pelvic girdle, with the rest lacking one entirely. Therefore, the sample size for the present-day Second Lake population was relatively small. In contrast, all but one individual in Enos Lake and Murdo Frazer Pond had a pelvic girdle. With only 30% of individuals in Second Lake retaining a pelvic girdle, this indicates a 65% reduction from historic samples (t39=5.26, p=5.39 x 10-6) (Fig. 4E). When spine lengths are treated as zero rather than removing them from sample, we observe a highly significant 90% reduction in average pelvic spine length (t47=5.14, p=3.945 x 10-11). Lateral plate number showed a similar trend to pelvic girdle reduction, where we observed no change in Enos and Murdo Frazer, but a 45% reduction in average plate number in Second Lake (t36=5.18, p= 8.21 x 10-6)(Fig 4.4F). See Table 3 for all traits and statistics. 89 Table 4. 3: Changes in meristic trait values across populations. Each hybrid population shows the historic and present-day trait value, and the change observed. Negative change values show a change in the benthic direction. Positive values show a change towards the limnetic direction. Statistical significance of the change between historic and present-day values are shown as p-values, with significant changes bolded. Lake Value 1st Spine 2nd Spine Pelvic Spine Gill Raker # Plate # Girdle (Proportion) Enos Lake Time 1 2.51 2.93 3.98 19.27 5.00 1 Time 2 2.41 3.23 4.34 20.08 4.88 0.96 Change -0.10 +0.30 +0.36 + 0.81 -0.12 -0.04 P value 0.38 0.0089* 0.041 0.0048* 0.62 NA Murdo Frazer Pond Time 1 2.13 2.88 3.98 22.12 4.45 1 Time 2 1.84 2.52 3.29 21.65 4.54 1 Change -0.29 -0.36 -0.69 -0.47 +0.09 0 P value 0.022 0.0096* 0.00013* 0.21 0.58 NA Second Lake Time 1 2.31 3.06 3.51 20.85 3.67 0.90 Time 2 1.81 2.27 2.74 19.73 1.96 0.32 Change -0.5 -0.79 -0.77 -1.12 -1.71 -0.58 P value 0.0094* 8.46 x 10-14 ** 0.55 5.022 x 10-5** 8.209 x 10-6** 3.034 x 10-5** 4.3.2 Genotypic changes over time In our analysis of whole-genome SNP variation, we observed that hybrid populations in all three lakes have a genomic composition that is, on average, more benthic-like than limnetic-like, and in populations with multiple timepoints available this trend appears to be increasing over time (as shown in Fig. 4.6). The first principal component of SNP variation consistently distinguished benthic from limnetic stickleback in all three species pairs. PC1 scores in the hybrid populations were used to calculate hybrid index values (h). Values close to 0 indicate a more benthic-like genotype and values close to 1 indicate a 90 more limnetic-like genotype. Enos Lake in 2018 had a hybrid index of 0.036, which is almost completely benthic-like. Second Lake had a hybrid index of 0.058, which is well below the expected value of 0.50 for the F1s originally introduced to the lake. Even in the case of Murdo Frazer Pond, which were phenotypically limnetic at the time of introduction, we find that present day populations have a hybrid index of 0.044. This was also more benthic than the 2011 sample, when h was 0.116. This result shows that the genome of the Murdo Frazer population is continuing to evolve in a more benthic direction, detectable over even the past 10 years. In order to gain further insights into changes in hybrid index, we conducted additional analyses utilizing the allele frequencies of diagnostic SNPs within 50kbp windows along each chromosome. This approach allowed us to identify specific regions of the genome that exhibited the most pronounced and subtle shifts in allele frequencies. Overall, the majority of chromosomes consistently demonstrated a shift towards a more benthic hybrid index across all lakes. Notably, Second Lake and Murdo Frazer Pond also displayed a reduction in hybrid index scores between the available timepoints, indicating a shift towards a more benthic genotype over time. To examine the relationship between hybrid index scores and the position along the chromosome, we employed a Loess model regression. The resulting curves exhibited similar overall shapes across different hybrid populations, suggesting a shared pattern of changes in allele frequencies. Additionally, specific regions with lower hybrid index scores on a given chromosome were consistently observed across the different hybrid populations (Figure 4.7, Appendix C.1). 91 Figure 4. 6: PCA plot of whole genome SNP variation. A PCA analysis was performed on whole genome data for all populations of interest. The first principal component is a benthic to limnetic axis. Each population was plotted separately, where yellow points are known benthic individuals, blue dots are known limnetic individuals, and green points are hybrid populations. Little Quarry LakePriest LakePaxton LakeSecond LakeMurdo Frazer 2018Murdo Frazer 2011Enos Lake 2018−0.05 0.00 0.05 0.10−0.10−0.050.000.05−0.10−0.050.000.05−0.10−0.050.000.05−0.10−0.050.000.05−0.10−0.050.000.05−0.10−0.050.000.05−0.10−0.050.000.05PC1PC2SpeciesBenthicHybridLimnetic 92 0.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30Chromosome 1 Position (Mbp)Hybrid IndexEnos Lake Chromosome 1−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30Chromosome 1 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 1−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30Chromosome 1 Position (Mbp)Hybrid IndexSecond Lake Chromosome 1−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32Chromosome 4 Position (Mbp)Hybrid IndexEnos Lake Chromosome 4−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32Chromosome 4 Position(Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 4−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32Chromosome 4 Position (Mbp)Hybrid IndexSecond Lake Chromosome 4−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28Chromosome 7 Position (Mbp)Hybrid IndexEnos Lake Chromosome 7−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28Chromosome 7 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 7−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18 20 22 24 26 28Chromosome 7 Position (Mbp)Hybrid IndexSecond Lake Chromosome 70.00.20.40.60.81.00 2 4 6 8 10 12 14 16Chromosome 15 Position (Mbp)Hybrid IndexEnos Lake Chromosome 15−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16Chromosome 15 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 15−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16Chromosome 15 Position (Mbp)Hybrid IndexSecond Lake Chromosome 150.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18Chromosome 20 Position (Mbp)Hybrid IndexEnos Lake Chromosome 200.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18Chromosome 20 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 20−0.20.00.20.40.60.81.00 2 4 6 8 10 12 14 16 18Chromosome 20 Position (Mbp)Hybrid IndexSecond Lake Chromosome 20−0.20.00.20.40.60.81.02 4 6 8 10 12 14Chromosome 21 Position (Mbp)Hybrid IndexEnos Lake Chromosome 21−0.20.00.20.40.60.81.02 4 6 8 10 12 14Chromosome 21 Position (Mbp)Hybrid IndexSecond Lake Chromosome 21−0.20.00.20.40.60.81.02 4 6 8 10 12 14Chromosome 21 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 21 93 Figure 4. 7: Changes in hybrid index across individual chromosomes based on SNP allele frequencies. Priest Lake was used as the reference when calculating hybrid index for each hybrid population. From left to right, columns are Enos Lake, Murdo Frazer Pond and Second Lake. Chromosomes I, IV, VII, XV, XX and XXI are shown. X axis is the position along the chromosome and the y-axis is the calculated hybrid index score. Black dots represent each 50Kbp window at the present-day timepoint. Windows that did not have at least one diagnostic SNP are absent from the plots. Blue lines are loess regression for the present-day timepoint, whereas yellow lines are loess regressions for the historic timepoint, whose data points are not shown. Grey bands around the coloured lines represent the 95% confidence interval on the loess regression estimates. Horizontal black lines show an h index of 0.5, where values above this line are limnetic-like and values below this line are benthic-like. See Appendix C.1 for plots of additional chromosomes. The window-by-window correlations for hybrid index scores were generally high, with the strongest correlations consistently observed between Murdo Frazer and Enos Lake. However, the correlation coefficients between Enos Lake and Second Lake, as well as between Murdo Frazer and Second Lake, were lower than expected based on qualitative observations of the Loess regression curves (refer to Table 4.4). For instance, on ChrI, the region spanning from 0 to 6Mbp exhibited a limnetic hybrid index, while the region from 6Mbp to 16Mbp showed a shift towards a more benthic hybrid index on average. In contrast, the region from 16Mbp to 30Mbp remained benthic in Enos Lake but displayed an intermediate hybrid index in Murdo Frazer and Second Lake. Despite Murdo Frazer and Second Lake appearing more similar qualitatively, the correlation coefficients were as follows: Murdo Frazer-Enos = 0.81, Murdo Frazer-Second = 0.49, and Second-Enos = 0.41. Despite the considerable variation in these coefficients, all lakes demonstrated a high degree of correlation in hybrid index (as shown in Table 4.5). The weighted average of hybrid index across the entire chromosome were similar, with Enos Lake = 0.354, Second Lake = 0.343, and Murdo Frazer = 0.389. These scores collectively indicate a benthic-like 94 hybrid index and signify a statistically significant change in hybrid index towards a benthic direction compared to the historic population (as depicted in Table 4.4). Table 4. 4: Hybrid index value on each chromosome for each hybrid population. Enos Lake, Second Lake and Murdo Frazer Pond have h index values calculated based on a weighted average. Change in h index is determined for those that have two timepoints, and is calculated at the historic date – the present date. Significance is shown as -log10(pvalue), and values that are bolded indicate the five smallest h index values for each lake. ENOS LAKE MURDO FRAZER POND SECOND LAKE CHROMOSOME Hybrid Index 2018 Hybrid Index 2018 Change -log10(P) Hybrid Index 2018 Change -log10(P) I 0.35 0.39 -0.37 15.66 0.34 -0.22 15.66 II 0.21 0.18 -0.22 15.66 0.26 -0.17 15.66 III 0.48 0.68 -0.01 0.09 0.45 -0.11 4.01 IV 0.31 0.26 -0.08 7.75 0.18 -0.25 15.66 V 0.37 0.49 -0.14 6.02 0.40 -0.17 7.21 VI 0.36 0.47 -0.02 0.22 0.30 -0.13 8.00 VII 0.22 0.18 -0.22 15.66 0.07 -0.36 15.66 VIII 0.22 0.29 0.02 0.40 0.23 -0.25 15.66 IX 0.37 0.37 -0.05 1.33 0.20 -0.25 15.66 X 0.41 0.64 -0.07 1.97 0.35 -0.14 6.28 XI 0.26 0.42 -0.11 4.76 0.35 -0.07 3.79 XII 0.34 0.36 -0.08 4.10 0.14 -0.38 15.66 XIII 0.41 0.43 -0.16 8.58 0.21 -0.31 15.66 XIV 0.45 0.50 0.01 0.08 0.41 -0.02 0.25 XV 0.43 0.47 0.00 0.03 0.43 0.00 0.03 XVI 0.37 0.58 -0.07 1.45 0.23 -0.24 15.66 XVII 0.33 0.31 -0.10 8.70 0.54 0.00 0.03 XVIII 0.35 0.61 -0.07 1.60 0.32 -0.16 9.01 XIX 0.29 0.45 -0.19 15.66 0.20 -0.24 15.66 XX 0.30 0.16 -0.05 4.59 0.15 -0.31 15.66 XXI 0.18 0.38 0.10 3.46 0.14 -0.24 15.66 95 Table 4. 5: Pearson’s correlation coefficient. Coefficients are calculated between each lake pair at each chromosome. Chromosomes Enos- Murdo Frazer Enos-Second Second- Murdo Frazer 1 0.81 0.41 0.49 2 0.86 0.53 0.46 3 0.80 0.61 0.45 4 0.80 0.24 0.31 5 0.88 0.49 0.49 6 0.90 0.41 0.33 7 0.82 0.47 0.26 8 0.85 0.48 0.40 9 0.89 0.16 0.16 10 0.75 0.46 0.39 11 0.79 0.42 0.37 12 0.93 0.50 0.42 13 0.93 0.40 0.34 14 0.83 0.51 0.49 15 0.87 0.49 0.52 16 0.77 0.49 0.36 17 0.85 0.50 0.49 18 0.74 0.46 0.35 19 0.77 0.51 0.31 20 0.83 0.29 0.28 21 0.79 0.36 0.11 On ChrIV, the hybrid index values remained relatively consistent across all windows of the chromosome, except for a notable peak in hybrid index around 18Mbp, accompanied by a slight reduction on either side of that location. All lakes exhibited a significant reduction in hybrid index with present-day hybrid index values ranging between 0.184 and 0.310. On ChrVII, the hybrid index regression curves displayed a U-like pattern in all lakes, with a distinct block of SNPs showing minimal changes around 14Mbp. Interestingly, Chromosome VII demonstrated the three lowest hybrid index scores across all lakes. 96 Specifically, the present-day hybrid index values were Enos=0.218, Murdo Frazer=0.175, and Second=0.0694 for Chromosome VII. Notably, Chromosome VII also harbors the third-highest number of phenotypic QTL in the stickleback genome (Table 4.4). As with Chr1, regardless of the shape of the Loess regression, an Murdo Frazer-Enos correlation is notably higher (~0.8 in both cases) than between Enos-Second or Murdo-Second (values ~0.2-0.5) (Table 4.5). Hybrid index values also tended to show a significant reduction from historic to current timepoints in the lakes where two samples are available. However, this trend is not observed in all chromosomes. For example, ChrXVI and ChrXX show little change between timepoints in Murdo Frazer Pond, but a significant change is observed between timepoints in Second Lake. However, in all three lakes, the pattern of hybrid index values shown by the Loess regression is similar, indicating the same pattern of change in hybrid index is shared across lakes. In numerous cases, the change in hybrid index score in Murdo Frazer is notably smaller than in Second Lake. This lesser change could be a reflection of the different timescales used, since timepoints for Second Lake are ~40 generations apart, and here the time between measurements of Murdo Frazer is only 7. Some chromosomes, such as ChrXV, have few SNP windows that distinguish benthic from limnetic stickleback, and those SNPs show very little change in hybrid index across timepoints or lakes, maintaining average hybrid index value of 0.426 to 0.472. 97 In general, the chromosomes that exhibited the largest changes in hybrid index were also the ones with the highest number of mapped phenotypic QTL (Table 4.6). For instance, Chromosome XXI displayed the second-highest estimates of phenotypic QTL and correspondingly had very low hybrid index scores in Enos Lake (h=0.180) and Second Lake (h=0.139), while Murdo Frazer Pond had a hybrid index of 0.380, representing a statistically significant decrease from the previous measured timepoint (as depicted in Figure 4.7 and Table 4.4). When examining the ten chromosomes with the lowest hybrid index scores, each lake demonstrated that at least 7 out of 10 of these chromosomes were also among the top 10 chromosomes with the most mapped QTL. Specifically, Murdo Frazer had 8 out of 10, Second Lake had 7 out of 10, and Enos Lake had 7 out of 10 chromosomes in common between the two categories. When the h index of a chromosome is averaged across all lake populations, 6 of the 7 lowest h values correspond to chromosomes with over 40 QTL (Table 4.6). The fascinating exception to this is chromosome 2, which has a very low hybrid index in all populations, averaging 0.22 across all three lakes, yet has very few QTL mapped to it. The Pearson's correlation coefficient between the hybrid index value and the number of QTL on a chromosome revealed a strong negative correlation across all three lakes. The correlation coefficients were as follows: Enos Lake (-0.398), Murdo Frazer Pond (-0.470), and Second Lake (-0.514), indicating a consistent inverse relationship between hybrid index and the number of mapped QTL. The correlation between hybrid populations in the pattern of h index and SNP position is partly explained by variation in the number of diagnostic SNPs, which varied with 98 Table 4. 6: Number of mapped phenotypic QTL per chromosome relative to average h index. Body shape QTL are those QTL associated only with fish body shape, and all phenotypic QTL are all known QTL associated with shape as well as feeding, defence, behaviour and sensory system, swimming, pigmentation, respiration, body size and reproduction in threespine stickleback. Average h index is the average of the 2018 h index of all three hybrid populations. Table is order by h index value, from lowest to highest. Bolded QTL are those chromosomes with more than 40 QTL mapped. CHROMOSOME AVERAGE H INDEX ALL PHENOTYPIC QTL BODY SHAPE QTL VII 0.16 102 36 XX 0.20 78 19 II 0.22 30 7 XXI 0.23 107 36 VIII 0.25 43 11 IV 0.25 203 57 XII 0.28 56 40 IX 0.31 18 4 XIX 0.31 24 9 XI 0.34 27 3 XIII 0.35 31 19 I 0.36 89 44 VI 0.38 14 3 XVI 0.39 72 50 XVII 0.39 35 7 V 0.42 24 5 XVIII 0.43 24 14 XV 0.44 13 4 XIV 0.45 29 13 X 0.47 26 2 III 0.54 12 6 chromosome position. We found a negative relationship between hybrid index score and the number of diagnostic SNPs within windows. Windows with more diagnostic SNPs had more benthic ancestry overall. This pattern is illustrated for Enos Lake in Fig 4.8A. We found a 99 similar relationship between number of diagnostic SNPs and the average change in hybrid index between timepoints, (Fig 4.8B Murdo Frazer and 4.8C Second Lake), indicating that the windows that contained the most SNPs differentiating benthic from limnetic stickleback also had the greatest shift toward a benthic ancestry allele frequency. Figure 4. 8: Hybrid index (A) and change in hybrid index between time points (B and C) as a function of the number of diagnostic SNPs per 50Kbp window. A) Enos Lake h-values; change in h between time points in B) Murdo Frazer Pond and C) Second Lake. Black dots indicate SNP windows for all chromosomes combined. The blue line is the regression line and the grey area around it is the 95% confidence interval. The horizonal dashed line is an h value of 0.5 in A) but is a change in h of 0 in B) and C). 100 4.4 Discussion Across the tree of life, hybridization between closely related species is common, and there are numerous cases of species with genomes comprised of more than one parental ancestry (Brennan et al., 2014; Massardo et al., 2020; Meier et al., 2017; Schley et al., 2022; S. A. Taylor & Larson, 2019). Despite this, the evolution of hybrid genomes, and the contributions of different forms of selection on those genomes, is poorly understood. In this study, we sought to investigate the role of different forms of selection on the evolution of hybrid genomes and use shifts in ancestry proportion over time to disentangle the contribution of ecological selection, hybridization load and hybrid incompatibilities acting on hybrid populations of threespine stickleback. Our three focal populations were all hybrids between a limnetic and benthic threespine stickleback species but they differed in the proportions each parent form contributed to the hybrid genome. Through the use of phenotypic and genotypic analyses, we were able to observe changes in the ancestry proportion and use these patterns to infer the primary selection mechanism acting on our stickleback populations. Our three populations of interest were Enos Lake (benthic majority ancestry), Murdo Frazer Pond (limnetic majority ancestry) and Second Lake (equal parental contribution). We found that both phenotypically and across the genome, all populations evolved in a more benthic-like direction, suggesting ecological adaptation to lake environments that favour benthic phenotypes, irrespective of starting parental ancestry. Beyond this, we also found that the chromosomes that showed the largest changes in hybrid index value were 101 the same chromosomes that have major known phenotype QTL mapped to them, suggesting that in our system we observed joint parallel phenotypic and genotypic evolution. Phenotypically, we found that all three present-day populations were significantly more benthic in overall shape compared to historic samples, though their present-day morphology differed in position along a benthic-limnetic axis. Murdo Frazer Pond is presently intermediate in overall shape between benthic and limnetic parents, having started at a limnetic-like body shape, while Enos Lake is presently not statistically different from a pure benthic fish in morphology. In terms of feeding and armour traits, Second Lake and Murdo Frazer pond consistently became more benthic-like in all traits measured. However, in some trait values Enos Lake appeared initially to become more limnetic-like, despite having a limnetic minor parental ancestry. Broad scale genomic patterns showed that populations became more benthic-like overall, though some chromosomes contributed more to this benthic shift than others. Chromosomes 1, 4, 7, 16, 20 and 21 were all shown to have benthic-like hybrid index scores. Interestingly, these are the same chromosomes that diverge primarily along a benthic-limnetic axis, and major phenotypic trait QTL have also been shown to map to these same chromosomes. Loess regressions show that the same SNP windows across populations experienced the largest changes in hybrid index along individual chromosomes, and this is partly explained by variation in the density of diagnostic SNPs. Parallel evolution is a strong indication of natural selection, and so the observation of parallel phenotypic evolution, where these three populations exhibit similar phenotypic 102 changes that align with the similar environmental conditions they inhabit, provides evidence that natural selection is the strongest mechanism acting on these stickleback populations. However, an absence of parallel evolution does not necessarily mean an absence of natural selection in favour of another selection mechanism but may actually reflect environmental heterogeneity that is overlooked when qualitatively describing an environment. This might explain the contrasting phenotypic results for Enos Lake in comparison to the other lake populations. Murdo Frazer Pond and Second Lake are both small, shallow bodies of water with muddy bottoms and an absence of a large pelagic zone. In nature, solitary populations that are found in small, shallow lakes tend to be more benthic-like (Bolnick & Ballare, 2020). All of the measured traits in these populations moved in a benthic direction to adapt to these conditions; this is remarkable to observe in only 35 generations. Second Lake was established from F1s and had no opportunity for backcrossing, meaning these rapid increases in benthic phenotypes are exclusively a result of selection against limnetic ancestry and not through further additions of benthic ancestry into the hybrid population. This is an even more remarkable observation in Murdo Frazer Pond, considering this population was phenotypically a limnetic form. At the time of introduction, all individuals were selected to be those most limnetic-like in phenotype and not randomly selected. Despite this, some benthic alleles were clearly present at low frequency, and over 30 generations have become so prominent that many phenotypic trait values in Murdo Frazer are more benthic-like than was the case in the historic Enos Lake benthic population (see second dorsal spine and pelvic spine, Fig 4c,d). 103 In contrast, Enos Lake showed evolution of body shape in a more benthic direction, but changes in gill raker number, dorsal spine and pelvic spine length appear to be evolving in a more limnetic direction, though gill raker number notably evolved towards a benthic phenotype before reversing direction to be more limnetic-like. This may suggest that Enos Lake is not evolving in parallel with the other two populations. However, it should be noted that in this population limnetic ancestry was the minor parent contributor, and so an increase in frequency of these traits suggests selection acting in favour of these alleles rather than removal of an incompatible combination. This makes sense when considered in the context of a major environmental difference between Enos Lake and the other two bodies of water, namely the presence of crayfish. Crayfish consume benthic invertebrates and compete with benthic stickleback for benthic resources (see Ch.3 of this thesis), which might lead us to expect that stickleback would evolve towards a more limnetic phenotype. However, field observations have revealed morphological changes in Enos Lake that suggest a shift towards a more benthic shape, contradicting previous assumptions. It now appears that both a shift towards a benthic-like morphology and a shift towards other limnetic-like phenotypes may be occurring simultaneously. Previous studies, such as the one conducted by Velema et al. (2012) have suggested that limnetic males exhibit more aggressive territorial defense behavior compared to benthic males. In light of this, it is possible that the observed increase in spine length can be attributed to the presence of crayfish as a novel egg predator, necessitating a more defensive benthic stickleback phenotype. While the exact role and effectiveness of spine length in defense against crayfish remain unclear, it is plausible that stickleback in Enos Lake are evolving towards a 104 more robust and heavily armored phenotype, potentially as a defense mechanism against crayfish. Simultaneously, there might be selection for an increased number of gill rakers, allowing stickleback to feed more efficiently on zooplankton and reducing direct competition with crayfish for dietary resources. In this context, it appears that despite the phenotypic evolution of this population not being in complete parallelism with the other populations, it remains likely that natural selection, and not incompatibilities or hybridization load, is the primary force of selection acting on this population in a phenotypic context. Past work has shown that parallelism in phenotype does not necessarily translate into parallelism in genotype (Poore et al., 2023). As different populations adapt to a similar novel environment, parallel phenotypic changes may be caused by different genotypic variants (Stuart et al., 2017). While this may still be true of our study, we did not look at specific loci, but rather focused on allele frequency changes at SNPs that could be assigned mainly to either a benthic or limnetic species and are averaging over many SNPs per window. This means that in claiming we observed parallel genome evolution, we are speaking to the simple classification of a SNP belonging to either a benthic or limnetic individual and thus are not excluding the possibility that different linkage groups may be responsible for the same phenotypic pattern. Nevertheless, we observed near universal changes in hybrid index scores to a more benthic genotype across the genome. This was observed both at the whole genome level, and on a chromosomal level. All lakes exhibited a shift towards a benthic weighted average hybrid index score, with the average influenced by the number 105 of diagnostic SNPs within each window on individual chromosomes. Notably, chromosomes known to harbor numerous QTL, many of which contribute to phenotypic differences between benthic and limnetic stickleback, displayed particularly large shifts in hybrid index. The correlation coefficients further demonstrated a strong negative correlation between the hybrid index score and the number of QTL on a chromosome, providing support for the observation that chromosomes with more QTL generally exhibited lower, more benthic hybrid index scores. In contrast, chromosomes with fewer QTL displayed less pronounced shifts towards the benthic direction, with a few exceptions such as chromosomes 3 and 10, which showed no change and had hybrid index scores close to 0.5. However, it is important to note that chromosome 2 did not conform to the expected pattern of high QTL and low hybrid index. Intriguingly, chromosome 2 exhibited one of the lowest hybrid index scores observed, with two out of three lakes demonstrating chromosome 2 to have the second lowest hybrid index. This contradicted the number of mapped QTL on chromosome 2, which was relatively low with only 30 QTL identified. This suggests that chromosome 2 may play a more significant role in distinguishing benthic from limnetic species pairs than previously recognized. Additionally, our observations revealed a correlation between the number of diagnostic SNPs within a window and the magnitude of shifts in hybrid index. Windows with a lower number of diagnostic SNPs exhibited smaller observed changes in hybrid index, whereas those windows with a higher density of SNPs that distinguished benthic from limnetic stickleback displayed both lower initial hybrid index values and larger changes in hybrid 106 index over time. However, the role of recombination rate should not be overlooked when interpreting these findings. Genomic regions that exhibit high differentiation between species, such as the regions containing our diagnostic SNPs, tend to be located in areas of low recombination (Geraldes et al., 2011). This implies that these regions have experienced limited genetic recombination over the past 35+ generations, leading to the presence of long ancestry tracks that have not been broken up. Consequently, a large number of SNP windows would exhibit consistent changes in allele frequency. However, it is important to note that the influence of recombination rate on these patterns likely pertains to the number of SNPs within a haplotype, rather than the specific direction of the shift. Therefore, the alignment observed between the presence of diagnostic SNPs and the windows showing the most pronounced benthic-like shifts provides further support for the idea that natural selection is the primary driving force acting on these populations. One of the most remarkable qualitative findings we observed in our study was the striking parallelism in the locations of hybrid index changes across the chromosomes. By employing Loess regression across the SNP windows of each chromosome, we were able to identify distinct patterns that indicated which regions of the chromosome were shifting further away from or closer to a benthic-like or limnetic-like hybrid index. Remarkably, these patterns remained consistent across populations, irrespective of their parental ancestry. This means that the same general locations on the chromosome were undergoing similar magnitudes of shifts in the same direction across different populations. As mentioned previously, the role of recombination rate influencing this pattern should be considered. 107 The presence of large tracts that move in parallel between populations is suggestive of extensive genomic regions with limited recombination between the limnetic and benthic species (Smith & Haigh, 1974). Although recombination rate may play a role in shaping the patterns observed, recombination maps for threespine stickleback reveal numerous locations across the genome where regions of high recombination correspond to regions that exhibit high correlation of allele frequency shifts between populations in our study (Roesti et al., 2013). In future investigations, we aim to quantify the extent to which recombination rate covaries with changes in hybrid index. Regardless the direction of change being consistent across populations, even as linked ancestry blocks, provides compelling evidence for genomic parallel evolution occurring on a chromosomal scale. However, despite the general similarity in the pattern of SNP shifts across the lakes, the correlation coefficients suggest that the window-by-window correlation between lakes is not equal. Specifically, the correlation coefficient between Murdo Frazer and Enos Lake consistently falls within the range of approximately 0.8, indicating a stronger correlation. On the other hand, the correlation between Second Lake and either of the other lakes generally ranges between 0.2 and 0.4, reflecting a lower degree of correlation at the specific SNP window level. This suggests that while the broad-scale patterns correlate well across lakes, the correlations are less pronounced when examining correlations at the level of individual SNP windows. One intriguing aspect of our study is the dynamic evolution of gill raker counts observed in Enos Lake following the hybridization event. The changes in trait values over time are 108 not consistent, as the initial generations displayed a significant shift towards a benthic-like morphology, followed by a reversal in a more limnetic-like direction. This pattern of evolution may be attributed to the gradual process of hybridization occurring over multiple years. Previous research has indicated that limnetic males in Enos Lake spent a considerable amount of time defending their territories in the presence of crayfish, often leading them to neglect nest building and subsequently leave them without mates (Velema et al., 2012). Consequently, it is suspected that during the early stages of the population collapse, individuals with pure benthic ancestry or hybrids with benthic male parents were favored. This overrepresentation of benthic ancestry likely resulted in a shift in trait values, such as gill raker number, towards a benthic-like morphology. However, hybrid genomes are not always optimally adapted to their environment, and competition with crayfish may have driven selection for stickleback individuals with more gill rakers that are advantageous for a pelagic dietary niche. This shift in gill raker number would have been observed as a subtle change in the benthic direction if only two timepoints were considered, rather than the larger shift followed by a reversal observed when utilizing multiple timepoints. By capturing multiple timepoints, we were able to unveil the intricate dynamics of trait evolution and gain deeper insights into the evolutionary processes after hybridization. This exemplifies the importance of using repeated measurements when studying evolutionary changes over time. Our results are most consistent with hybrid populations evolving in response to ecological selection as the primary mechanism. However, this does not exclude the possibility that 109 other selection mechanisms could also be acting on our populations. Mechanisms of selection do not act in a vacuum, and it is in fact unlikely that ecological selection is the only mechanism acting on our populations. Since hybridization load has been found to be less strong in other hybrid populations (Moran et al., 2021), we will focus on the potential importance of DMIs on the evolution of our hybrid populations. DMIs can be either based purely on intrinsic interactions within the genome or can be reliant on ecological context, only negatively impacting hybrids in the environment but not in the lab (Thompson et al., 2022). Ecologically based DMIs are caused by genes underlying ecologically relevant traits. Irrespective of the cause, accumulation of incompatibilities increases with divergence time between populations (Matute et al., 2010; Moyle & Nakazato, 2010). Threespine stickleback species pairs are relatively young species, having diverged ~12,000 year ago, suggesting that they have likely accumulated fewer incompatibilities than many other systems. Although selection against DMIs is likely present in our system, our results suggest that it is not strong enough to override ecological selection. This contrasts with other systems, such as swordtail hybrids, where previous work found that selection against DMIs was more important than ecological selection in shaping contemporary hybrid genomes (Schumer et al., 2015). However, these swordtail populations are notably older than our stickleback populations, having diverged ~125,000 years ago (assuming 2 generations per year), making it likely that these populations had accumulated more incompatibilities for selection to act on (Powell et al., 2020). Thus the contrasting findings of these studies investigating the relative importance of the different selection mechanisms suggests that each ones prevalence in the ‘shaping’ of genomes post-hybridization event is unlikely to be the same 110 in all cases, and instead depends on a variety of factors such as ecological context, genetic architecture, age of divergent species, and the time since the hybridization event. We sought to use differences in genetic architecture, and its concordance with phenotype, to infer the role of different selection mechanisms acting on hybrid genomes with differing ancestry proportions. Broadly we found that for our relatively young, recently hybridized populations, ecological selection was the primary force shaping the direction of evolution of their phenotypes and genotypes, though this does not exclude the possibility that other forces of selection are acting concurrently, but to a lesser degree. This study is particularly interesting because we were able to utilize both natural and experimental populations of hybrids in a natural setting and showed that both circumstances, irrespective of ancestral starting position, evolved in parallel resulting from ecological selection. Though we still have much to investigate in trying to understand the diversity of outcomes of hybrid evolution, this study provides insight into the mechanisms of natural selection in shaping hybrid evolution, much as it does in the species that evolutionary biologists have been fascinated with for centuries. 111 Chapter 5: Conclusions Hybridization between species is a widespread phenomenon observed across numerous taxa on the tree of life. Despite its prevalence, our understanding of the consequences of hybridization, the evolution of hybrids, and the ways in which natural selection acts on hybrids is limited compared to that of parent species. My dissertation sought to fill in some of these knowledge gaps by investigating effects of environmental perturbations on the production and fitness of hybrids and the mechanisms of evolution in hybrid populations. Utilizing a combination of experiments and field data from natural hybrid populations, our study focused on assessing the impact of environmental change on reproductive isolation, evaluating changes in early-generation hybrid fitness within a novel ecological context, and examining the phenotypic and genomic evolution of existing hybrid populations over time. 5.1 Fragility of ecological speciation Our understanding of the role of ecology in speciation has evolved over time, undergoing various iterations of interest and comprehension. In 1859, Charles Darwin spoke of the “divergence of character….being preserve and accumulated by natural selection”, providing the first notion of the role of natural selection on species divergence. In 1963)Ernst Mayr further expanded our understanding by highlighting how adaptation to different environments could inadvertently lead to speciation and the development of reproductive isolation. Later, in 2012, Patrik Nosil succinctly outlined the key components of ecological speciation as divergent selection, reproductive isolation, and the genetic mechanisms that link the two. Work by Dolph Schluter has made thinking of ecological speciation 112 synonymous with threespine stickleback, yet chapter 2 of my thesis reveals that there are still numerous unanswered questions in the study of ecological speciation, even in threespine stickleback. In Chapter 2 of my thesis, we sought to investigate the impact of eutrophication and decreased visibility on the breakdown of reproductive isolation in stickleback species pairs. Previous studies have indicated the importance of visual mating cues for mate differentiation in not only threespine stickleback, but other fish systems as well (Seehausen et al., 1997). However, our results did not provide clear answers and instead raised more questions. We found that despite our experimental ponds increasing in trophic status and decreasing in light penetrance, these changes occurred long after the breeding season had commenced and did not result in an increase in hybridization. We did, however, observe extensive hybridization in two of our seven experimental units, completely independent of our applied treatment. Despite our efforts to identify a cause for these collapses, a satisfying explanation remains elusive. Our main conclusion is that our understanding of ecological speciation and the factors involved in maintaining reproductive isolation, as outlined by Nosil in 2012, may not be as comprehensive as previously believed, even in well-studied systems. Saying “we saw complete hybrid collapse and we don’t know why” is a particularly unsatisfying conclusion to draw from an experiment, and it emphasizes the need for further investigation. It highlights the fragility of the maintenance of reproductive isolation in the 113 context of ecological speciation and raises new questions regarding species boundaries. Future research based on this experiment could continue to search for an explanation behind the collapse, such as conducting in-depth genomic analyses of the fish collected. Examining the frequency of hybridization among different families and investigating any patterns or directionality in hybridization events (e.g., benthic males and limnetic females) could provide valuable insights into particular weaknesses in maintaining reproductive isolation. On a broader scale, it is important to consider the possibility that the factors previously believed to be crucial in species maintenance may not provide the complete picture. There may be other critical factors influencing reproductive isolation that we, as researchers, do not attribute much influence to. Even more likely, the process might be multifactorial rather than solely dependent on a singular environmental component that could easily be identified in this experiment. To advance our understanding of ecological speciation, future studies in this field should aim to examine the roles and relative strengths of individual selective pressures in driving speciation compared to the cumulative effects of multiple traits and subsequently apply these to other well-studied systems. This study has several limitations that should be considered. Firstly, the small number of replicates limits the statistical power of our findings. While conducting experiments under conditions similar to natural environments is valuable, in our case it comes at the cost of having a limited number of experimental units, hampering our ability to provide a comprehensive explanation for our observations. Another limitation is the uncertainty regarding the sex ratios of the individuals introduced into the ponds. Biased sex ratios could 114 have influenced the reproductive outcomes and potentially confounded our results. Lastly, our original hypothesis was based on the effects of increased turbidity and decreased visual mating cues. However, our systems did not achieve the desired turbidity levels during the breeding season. As a result, the role of turbidity in stickleback mate choice remains unresolved. Exploring this aspect could be relevant not only to our study but also to other systems, such as the Enos Lake species collapse, where turbidity has been proposed as a potential contributing factor. 5.2 Hybrid persistence in a novel ecological context In numerous systems, closely related sympatric species have the potential to interbreed and produce viable, fertile offspring, yet hybridization rates have historically been low. However, there are cases where previously stable sympatric species now exhibit higher rates of hybridization, often linked to environmental changes, such as the introduction of crayfish leading to the species collapse in Enos Lake (Behm et al., 2010; E. B. Taylor et al., 2005; E. B. Taylor & Piercey, 2018). Theory has proposed that this increase in hybrids after environmental disturbance could be attributed to higher fitness of hybrids in novel ecological contexts, where neither parent species nor hybrids are particularly well adapted (Kulmuni et al., 2023). The unique gene combinations in hybrid individuals may facilitate rapid adaptation to the new environment compared to the parent populations depending on standing genetic variation and mutation (Barrett & Schluter, 2008). In Chapter 3 of my thesis, we tested this idea experimentally using threespine stickleback species pairs and their hybrids by examining their growth and survival in the presence or absence of crayfish, inspired by the Enos Lake collapse. Our findings revealed that crayfish significantly altered 115 the ecosystem by depleting benthic resources and reducing the overall survival of all stickleback cross types. While hybrid growth remained unchanged, we observed reduced growth specifically in benthic cross types, indicating a disproportionately negative impact of crayfish on these individuals. However, we did not observe an increase in absolute hybrid fitness as we had predicted. Instead, we observed changes in hybrid fitness relative to the parental types. These findings align with the results from Chapter 2, where eutrophic ponds showed no change in hybrid survival over winter, while control ponds exhibited changes in hybrid survival, albeit in opposite directions. A significant limitation of our studies is the relatively short time frame in which they were conducted. While simulations suggest that hybrid individuals may adapt more quickly than parent populations in response to a novel environment, such adaptation occurs over multiple generations. In contrast, our studies were limited to a single generation, preventing us from addressing questions related to long-term adaptation and certain aspects of fitness. It is important to note that fitness encompasses not only survival but also reproduction. Unfortunately, our study did not assess the reproductive success of F1 hybrids in comparison to parental ecotypes. The absence of changes in hybrid growth and survival does not provide insights into their reproductive abilities. This aspect becomes particularly crucial considering that first-generation hybrids do not exhibit the full range of phenotypic combinations observed in later-generation hybrids. 116 Future research should aim to continue assessing the fitness of hybrids relative to their parents under diverse ecological contexts, allowing them to breed over multiple generations. It is crucial for researchers to shift their focus from population-level observations to individual-level success. Given the vast range of possible gene combinations present in early-generation hybrid populations, it’s likely that many individuals may exhibit lower fitness. However, a few individuals with favorable genotypes may have a disproportionate contribution to future generations. Michael Arnold highlighted this idea when he stated that once hybrid offspring are initially formed, individuals are exposed to selection pressures and leading to the loss of many F1 individuals while favoring certain novel genotype combinations in specific environments (Burke & Arnold, 2001). Declaring that hybrid individuals are less fit than parentals based solely on the overall success of the F1 generation is not capturing the adaptive evolutionary potential exhibited by hybrids overall. Rather than considering hybrid fitness within a single generation, future work should adopt a long-term perspective by evaluating the prospects of specific hybrid genotypes. By shifting the metric by which hybrid fitness is measured and considering the success of certain hybrid genotypes over multiple generations, researchers can better test the theories surrounding hybrid success in novel ecological contexts. 5.3 Phenotypic hybrid evolution across time Parallel phenotypic evolution is strong evidence of natural selection acting on populations (Schluter & Nagel, 1995). However, hybrid populations have a wide variety of phenotypic combinations and underlying incompatibilities that could prevent hybrid populations from 117 evolving in parallel in similar environments much like other populations do. In chapter 4 of my thesis, I looked at three different hybrid populations, each with different phenotypic starting positions, that lived in similar environmental contexts. This study revealed that all hybrid populations exhibited morphological changes over time in the same direction, despite present day populations having slightly different trait values from one another. These differences reflect their different phenotypic starting positions. These findings provide robust evidence that hybrid populations possess the capacity to undergo parallel evolution, akin to parent populations, and underscore the significant role of ecological selection as a driving force. An unexpected discovery emerged regarding the change in gill raker number in the Enos Lake population. Individuals collected shortly after the hybridization event were found to have changed phenotypically in a benthic direction, but then reversed this direction of evolution to limnetic-like in present-day samples. The significance of this suggests that the initial phenotypic characteristics of a population immediately after a hybridization event may not necessarily be those that are optimal for the environment. We do not know the forces that changed the direction of evolution in the population, but we do know that our conclusions would have been different had we not looked at this population from multiple timepoints, as this change would have appeared to be a small change in the benthic direction rather than two large changes in opposing directions. A limitation of our study is the lack of access to multiple timepoints for each hybrid population, which would have allowed for a more comprehensive understanding of the 118 process of phenotypic evolution. We found that data from multiple timepoints can provide valuable insights into the dynamics of population-level phenotypic changes as hybrid populations adapt with novel allele combinations. Future studies focusing on hybrid populations should prioritize collecting data from multiple timepoints to capture the full spectrum of evolutionary change and enhance our understanding of how these populations undergo adaptation and phenotypic evolution. By incorporating a temporal perspective, researchers can gain a more nuanced understanding of the mechanisms of selection after hybridization. 5.4 Genomic parallel evolution of hybrids The genomic architecture of populations is shaped by a range of selection mechanisms as they adapt to their ever-changing environment. Hybrid populations, resulting from the combination of two parental genotypes, experience additional selection forces, but our understanding of how these populations evolve and the selection mechanisms that shape them remains limited (Moran et al., 2021). In Chapter 4 of my thesis, we utilized whole genome sequencing across multiple timepoints to investigate genotype changes in the same three hybrid populations examined for phenotypic evolution addressed in 5.3. Using changes in parental ancestry proportions, we aimed to elucidate the primary selection mechanisms acting on these populations: hybridization load, intrinsic Dobzhansky-Muller incompatibilities, or ecological selection. Our findings consistently demonstrated that ecological selection was the predominant force of selection in all cases. This was evidenced by parallel evolution at both the whole genome and chromosomal levels. 119 Across all chromosomes, we consistently observed that the regions of the genome that exhibited the greatest deviation from a hybrid index of 0.5 were highly consistent. These regions, which displayed the most pronounced shifts in allele frequencies, were remarkably similar across all three hybrid populations. Additionally, we identified a high correlation between per-SNP hybrid index values across lakes, further supporting the prevalence of parallel evolution. These results differ from previous studies that have attributed intrinsic incompatibilities as the primary source of selection in hybrid populations of different systems. A notable limitation of our study was the unavailability of parental reference samples for Enos Lake and Murdo Frazer Pond. As a consequence, we had to rely on an intermediate parental reference from Priest Lake for all populations. In future work related to this specific study, it would be valuable to obtain historic benthic and limnetic individuals from Enos Lake as parental reference populations. Our lab does not possess any sample from Enos Lake predating the species collapse that are not fixed in formalin, but it is possible that such samples exist elsewhere. Alternatively, ongoing developments in DNA extraction methods from formalin-fixed specimens may eventually yield DNA of high enough quality for whole genome sequencing. Our study's findings differ from previous research that indicate DMIs to be the predominant selection mechanism acting on a population, underscoring the existing knowledge gaps regarding the mechanisms of selection acting on hybrid populations on a 120 broader scale. Hybrid populations are subject to numerous factors that can influence how selection acts on them, which can differ based on the parental populations' age of divergence, time since hybridization and evolutionary history. It is crucial to conduct extensive research in this field to unravel the intricate interactions and effects of these factors, thereby elucidating the primary selection mechanisms in different contexts. Understanding how distinct evolutionary histories can alter the impact of different selection mechanisms is going to be instrumental in comprehending the genomics of species following hybridization and potentially developing predictive frameworks for evolutionary outcomes in diverse evolutionary contexts. 5.5 Closing thoughts As scientists, we learn early on that we should avoid anthropomorphizing evolution and stay away from language that implies it is goal-oriented or purposeful. Anthropomorphizing can lead to misconceptions and hamper our understanding of the natural world and its processes. Interestingly, in the study of speciation, hybridization tends to be discussed in terms of its negative impacts on species. Hybridization is seldom viewed as more than a means to study reinforcement and is often regarded as an impediment to divergent evolution. There is a tendency for researchers to treat hybridization as a means to understand the process of speciation and use hybrid zones as natural laboratories to study reproductive isolation. However, I think it is essential to study hybridization for its own merits and recognize it as a process that can facilitate rapid adaptation and has the potential to contribute to species' survival and persistence under 121 different environmental contexts. This perspective allows scientists to explore new avenues of curiosity and ask critical questions that contribute to our understanding of the world around us. By embracing hybridization as a fundamental aspect of evolutionary processes, we can uncover its true significance and its potential role in shaping future populations. 122 Bibliography Abbott, R., Albach, D., Ansell, S., Arntzen, J. W., Baird, S. J. E., Bierne, N., Boughman, J., Brelsford, A., Buerkle, C. A., Buggs, R., Butlin, R. K., Dieckmann, U., Eroukhmanoff, F., Grill, A., Cahan, S. H., Hermansen, J. S., Hewitt, G., Hudson, A. G., Jiggins, C., … Zinner, D. (2013). Hybridization and speciation. Journal of Evolutionary Biology, 26(2), 229–246. https://doi.org/10.1111/j.1420-9101.2012.02599.x Adams, D. C., & Otárola‐Castillo, E. (2013). geomorph: An R package for the collection and analysis of geometric morphometric shape data. Methods in Ecology and Evolution, 4(4), 393–399. Albert, A. Y. K., Sawaya, S., Vines, T. H., Knecht, A. K., Miller, C. T., Summers, B. R., Balabhadra, S., Kingsley, D. M., & Schluter, D. (2008). The genetics of adaptive shape shift in stickleback: Pleiotropy and effect size. Evolution; International Journal of Organic Evolution, 62(1), 76–85. https://doi.org/10.1111/j.1558-5646.2007.00259.x Alexander, T. J., Vonlanthen, P., & Seehausen, O. (2017). Does eutrophication-driven evolution change aquatic ecosystems? Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1712), 20160041. https://doi.org/10.1098/rstb.2016.0041 Alric, B., Möst, M., Domaizon, I., Pignol, C., Spaak, P., & Perga, M.-E. (2016). Local human pressures influence gene flow in a hybridizing Daphnia species complex. Journal of Evolutionary Biology, 29(4), 720–735. https://doi.org/10.1111/jeb.12820 A.M, S., Letha, J., & Joseph, S. (2010). Environmental status of a tropical lake system. Environmental Monitoring and Assessment, 180, 427–449. https://doi.org/10.1007/s10661-010-1797-5 123 Anderson, E. (1948). Hybridization of the Habitat. Evolution, 2(1), 1–9. https://doi.org/10.2307/2405610 Anderson, E., & Stebbins, G. L. (1954). Hybridization as an Evolutionary Stimulus. Evolution, 8(4), 378–388. https://doi.org/10.2307/2405784 Ansari, A. A., Gill, S. S., & Khan, F. A. (2011). Eutrophication: Threat to Aquatic Ecosystems. In A. A. Ansari, S. Singh Gill, G. R. Lanza, & W. Rast (Eds.), Eutrophication: Causes, consequences and control (pp. 143–170). Springer Netherlands. https://doi.org/10.1007/978-90-481-9625-8_7 Arnegard, M. E., McGee, M. D., Matthews, B., Marchinko, K. B., Conte, G. L., Kabir, S., Bedford, N., Bergek, S., Chan, Y. F., Jones, F. C., Kingsley, D. M., Peichel, C. L., & Schluter, D. (2014). Genetics of ecological divergence during speciation. Nature, 511(7509), 307–311. https://doi.org/10.1038/nature13301 Arnold, M. L. (1997). Natural hybridization and evolution. Oxford University Press on Demand. Arnold, M. L., & Hodges, S. A. (1995). Are natural hybrids fit or unfit relative to their parents? Trends in Ecology & Evolution, 10(2), 67–71. https://doi.org/10.1016/S0169-5347(00)88979-X Barrett, R. D. H., & Schluter, D. (2008). Adaptation from standing genetic variation. Trends in Ecology & Evolution, 23(1), 38–44. https://doi.org/10.1016/j.tree.2007.09.008 Barton, N. H., & Hewitt, G. M. (1985). Analysis of Hybrid Zones. Annual Review of Ecology and Systematics, 16, 113–148. Baumgärtner, D., & Rothhaupt, K.-O. (2003). Predictive length–dry mass regressions for freshwater invertebrates in a pre‐alpine lake littoral. International Review of 124 Hydrobiology: A Journal Covering All Aspects of Limnology and Marine Biology, 88(5), 453–463. Behm, J. E., Ives, A. R., & Boughman, J. W. (2010). Breakdown in postmating isolation and the collapse of a species pair through hybridization. The American Naturalist, 175(1), 11–26. Bell, M. A., & Foster, S. A. (1994). Introduction to the evolutionary biology of the threespine stickleback. The Evolutionary Biology of the Threespine Stickleback, 1–27. Benke, A. C., Huryn, A. D., Smock, L. A., & Wallace, J. B. (1999). Length-Mass Relationships for Freshwater Macroinvertebrates in North America with Particular Reference to the Southeastern United States. Journal of the North American Benthological Society, 18(3), 308–343. Best, R. J., Anaya-Rojas, J. M., Leal, M. C., Schmid, D. W., Ole, S., & Matthews, B. (2017). Transgenerational selection driven by divergent ecological impacts of hybridizing lineages. Nature Ecology & Evolution, 1(11), 1757–1765. https://doi.org/10.1038/s41559-017-0308-2 Bolger, A. M., Lohse, M., & Usadel, B. (2014). Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics, 30(15), 2114–2120. https://doi.org/10.1093/bioinformatics/btu170 Bolnick, D. I., & Ballare, K. M. (2020). Resource diversity promotes among-individual diet variation, but not genomic diversity, in lake stickleback. Ecology Letters, 23(3), 495–505. https://doi.org/10.1111/ele.13448 Bolnick, D. I., & Lau, O. L. (2008). Predictable patterns of disruptive selection in stickleback in postglacial lakes. The American Naturalist, 172(1), 1–11. 125 Boughman, J. W., Rundle, H. D., & Schluter, D. (2005). Parallel Evolution of Sexual Isolation in Sticklebacks. Evolution, 59(2), 361–373. https://doi.org/10.1111/j.0014-3820.2005.tb00995.x Brennan, A., Woodward, G., Seehausen, O., Muñoz-Fuentes, V., Moritz, C., Guelmami, A., Abbott, R., & Edelaar, P. (2014). Hybridization due to changing species distributions: Adding problems or solutions to conservation of biodiversity during global change? Evolutionary Ecology Research, 16. Buerkle, C. A., Wolf, D. E., & Rieseberg, L. H. (2003). The Origin and Extinction of Species Through Hybridization. In C. A. Brigham & M. W. Schwartz (Eds.), Population Viability in Plants: Conservation, Management, and Modeling of Rare Plants (pp. 117–141). Springer. https://doi.org/10.1007/978-3-662-09389-4_5 Burke, J. M., & Arnold, M. L. (2001). Genetics and the Fitness of Hybrids. Annual Review of Genetics, 35(1), 31–52. https://doi.org/10.1146/annurev.genet.35.102401.085719 Butlin, R. (1987). Speciation by reinforcement. Trends in Ecology & Evolution, 2(1), 8–13. Chang, C. C., Chow, C. C., Tellier, L. C., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015). Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience, 4(1), s13742-015-0047–0048. Chen, C., & Pfennig, K. S. (2020). Female toads engaging in adaptive hybridization prefer high-quality heterospecifics as mates. Science, 367(6484), 1377–1379. Chhina, A. K., Thompson, K. A., & Schluter, D. (2022). Adaptive divergence and the evolution of hybrid trait mismatch in threespine stickleback. Evolution Letters, 6(1), 34–45. https://doi.org/10.1002/evl3.264 126 Clinchy, M., Sheriff, M. J., & Zanette, L. Y. (2013). Predator-induced stress and the ecology of fear. Functional Ecology, 27(1), 56–65. https://doi.org/10.1111/1365-2435.12007 Colosimo, P. F., Peichel, C. L., Nereng, K., Blackman, B. K., Shapiro, M. D., Schluter, D., & Kingsley, D. M. (2004). The Genetic Architecture of Parallel Armor Plate Reduction in Threespine Sticklebacks. PLoS Biology, 2(5), e109. https://doi.org/10.1371/journal.pbio.0020109 Conte, G. L., Arnegard, M. E., Best, J., Chan, Y. F., Jones, F. C., Kingsley, D. M., Schluter, D., & Peichel, C. L. (2015). Extent of QTL Reuse During Repeated Phenotypic Divergence of Sympatric Threespine Stickleback. Genetics, 201(3), 1189–1200. https://doi.org/10.1534/genetics.115.182550 Conte, G. L., & Schluter, D. (2013). Experimental confirmation that body size determines mate preference via phenotype matching in a stickleback species pair. Evolution, 67(5), 1477–1484. Coyne, J. A., & Orr, H. A. (2004). Speciation. Oxford University Press. Cui, R., Schumer, M., Kruesi, K., Walter, R., Andolfatto, P., & Rosenthal, G. G. (2013). PHYLOGENOMICS REVEALS EXTENSIVE RETICULATE EVOLUTION IN XIPHOPHORUS FISHES: PHYLOGENOMICS OF XIPHOPHORUS FISHES. Evolution, 67(8), 2166–2179. https://doi.org/10.1111/evo.12099 Dobzhansky, T. (1937). Genetic nature of species differences. The American Naturalist, 71(735), 404–420. Doering, P. H., Chamberlain, R. H., & Haunert, K. M. (n.d.). Chlorophyll a and Its Use as an Indicator of Eutrophication in the Caloosahatchee Estuary, Florida. FLORIDA SCIENTIST, 69. 127 Dumont, H. J., Van de Velde, I., & Dumont, S. (1975). The dry weight estimate of biomass in a selection of Cladocera, Copepoda and Rotifera from the plankton, periphyton and benthos of continental waters. Oecologia, 19(1), 75–97. https://doi.org/10.1007/BF00377592 Fisher, H. S., Wong, B. B. M., & Rosenthal, G. G. (2006). Alteration of the chemical environment disrupts communication in a freshwater fish. Proceedings of the Royal Society B: Biological Sciences, 273(1591), 1187–1193. https://doi.org/10.1098/rspb.2005.3406 Foster, S. A., Baker, J. A., & Bell, M. A. (2003). The case for conserving threespine stickleback populations: Protecting an adaptive radiation. Fisheries, 28(5), 10–18. Frare, C. F., Matocq, M. D., Feldman, C. R., White, A. M., Manley, P. N., Jermstad, K. D., & Hekkala, E. R. (2017). Landscape disturbance and sporadic hybridization complicate field identification of chipmunks. The Journal of Wildlife Management, 81(2), 248–258. https://doi.org/10.1002/jwmg.21193 Gagnaire, P.-A. (2020). Comparative genomics approach to evolutionary process connectivity. Evolutionary Applications, 13(6), 1320–1334. https://doi.org/10.1111/eva.12978 Geraldes, A., Basset, P., Smith, K. L., & Nachman, M. W. (2011). Higher differentiation among subspecies of the house mouse (Mus musculus) in genomic regions with low recombination. Molecular Ecology, 20(22), 4722–4736. https://doi.org/10.1111/j.1365-294X.2011.05285.x Gilman, R. T., & Behm, J. E. (2011). Hybridization, Species Collapse, and Species Reemergence After Disturbance to Premating Mechanisms of Reproductive Isolation: Hybridization, 128 Species Collapse, and Species Reemergence. Evolution, 65(9), 2592–2605. https://doi.org/10.1111/j.1558-5646.2011.01320.x Gow, J. L., Peichel, C. L., & Taylor, E. B. (2006). Contrasting hybridization rates between sympatric three-spined sticklebacks highlight the fragility of reproductive barriers between evolutionarily young species: HYBRIDIZATION IN STICKLEBACK SPECIES PAIRS. Molecular Ecology, 15(3), 739–752. https://doi.org/10.1111/j.1365-294X.2006.02825.x Grabenstein, K. C., Otter, K. A., Burg, T. M., & Taylor, S. A. (2023). Hybridization between closely related songbirds is related to human habitat disturbance. Global Change Biology, 29(4), 955–968. https://doi.org/10.1111/gcb.16476 Grabenstein, K. C., & Taylor, S. A. (2018). Breaking Barriers: Causes, Consequences, and Experimental Utility of Human-Mediated Hybridization. Trends in Ecology & Evolution, 33(3), 198–212. https://doi.org/10.1016/j.tree.2017.12.008 Grant, B. R., & Grant, P. R. (1996). High survival of Darwin’s finch hybrids: Effects of beak morphology and diets. Ecology, 77(2), 500–509. Grant, P. R., & Grant, B. R. (1992). Hybridization of Bird Species. Science, 256(5054), 193–197. https://doi.org/10.1126/science.256.5054.193 Grant, P. R., & Grant, B. R. (1996). Speciation and hybridization in island birds. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 351(1341), 765–772. Grant, P. R., & Grant, B. R. (2014). Speciation undone. Nature, 507(7491), 178–179. https://doi.org/10.1038/507178b 129 Gross, J. B., Borowsky, R., & Tabin, C. J. (2009). A Novel Role for Mc1r in the Parallel Evolution of Depigmentation in Independent Populations of the Cavefish Astyanax mexicanus. PLoS Genetics, 5(1), e1000326. https://doi.org/10.1371/journal.pgen.1000326 G.w, F. (1982). The Gulf Coast pitcher plant bogs [Mississippi, Alabama]. American Scientist. https://scholar.google.com/scholar_lookup?title=The+Gulf+Coast+pitcher+plant+bogs+%5BMississippi%2C+Alabama%5D.&author=Folkerts+G.W.&publication_year=1982 Harper, D. M. (1992). Eutrophication of freshwaters. Springer. Hatfield, T., & Schluter, D. (1999). Ecological Speciation in Sticklebacks: Environment‐Dependent Hybrid Fitness. Evolution, 53(3), 866–873. https://doi.org/10.1111/j.1558-5646.1999.tb05380.x Hedrick, P. W. (2013). Adaptive introgression in animals: Examples and comparison to new mutation and standing variation as sources of adaptive variation. Molecular Ecology, 22(18), 4606–4618. Hedrick, P. W., & Garcia-Dorado, A. (2016). Understanding inbreeding depression, purging, and genetic rescue. Trends in Ecology & Evolution, 31(12), 940–952. Hendry, A. P., Gotanda, K. M., & Svensson, E. I. (2017). Human influences on evolution, and the ecological and societal consequences. In Philosophical Transactions of the Royal Society B: Biological Sciences (Vol. 372, Issue 1712, p. 20160028). The Royal Society. Heuschele, J., Mannerla, M., Gienapp, P., & Candolin, U. (2009). Environment-dependent use of mate choice cues in sticklebacks. Behavioral Ecology, 20(6), 1223–1227. https://doi.org/10.1093/beheco/arp123 130 Ingram, T., Svanbäck, R., Kraft, N. J., Kratina, P., Southcott, L., & Schluter, D. (2012). Intraguild predation drives evolutionary niche shift in threespine stickleback. Evolution, 66(6), 1819–1832. Irwin, D. E. (2020). Assortative Mating in Hybrid Zones Is Remarkably Ineffective in Promoting Speciation. The American Naturalist, 195(6), E150–E167. https://doi.org/10.1086/708529 Irwin, D., & Schluter, D. (2022). Hybridization and the Coexistence of Species. The American Naturalist, 200(3), E93–E109. Jones, F. C., Chan, Y. F., Schmutz, J., Grimwood, J., Brady, S. D., Southwick, A. M., Absher, D. M., Myers, R. M., Reimchen, T. E., & Deagle, B. E. (2012). A genome-wide SNP genotyping array reveals patterns of global and repeated species-pair divergence in sticklebacks. Current Biology, 22(1), 83–90. Jones, F. C., Grabherr, M. G., Chan, Y. F., Russell, P., Mauceli, E., Johnson, J., Swofford, R., Pirun, M., Zody, M. C., White, S., Birney, E., Searle, S., Schmutz, J., Grimwood, J., Dickson, M. C., Myers, R. M., Miller, C. T., Summers, B. R., Knecht, A. K., … Kingsley, D. M. (2012). The genomic basis of adaptive evolution in threespine sticklebacks. Nature, 484(7392), 55–61. https://doi.org/10.1038/nature10944 Karjalainen, J., Ruokonen, T. J., MarjomäKi, T. J., Martikainen, A., Pursiainen, M., Sarvala, J., Tarvainen, M., & Ventelä, A.-M. (2015). Predation by signal crayfish Pacifastacus leniusculus on fish eggs and its consequences for coregonid recruitment. Journal of Fish Biology, 86(2), 651–667. https://doi.org/10.1111/jfb.12588 Kleindorfer, S., O’Connor, J. A., Dudaniec, R. Y., Myers, S. A., Robertson, J., & Sulloway, F. J. (2014). Species collapse via hybridization in Darwin’s tree finches. The American Naturalist, 183(3), 325–341. 131 Kraak, S. B. M., Mundwiler, B., & Hart, P. J. B. (2001). Increased number of hybrids between benthic and limnetic three‐spined sticklebacks in Enos Lake, Canada; the collapse of a species pair? Journal of Fish Biology, 58(5), 1458–1464. Kulmuni, J., Wiley, B., & Otto, S. P. (2023). On the fast track: Hybrids adapt more rapidly than parental populations in a novel environment. Evolution Letters, qrad002. Lackey, A. C., & Boughman, J. W. (2013). Loss of sexual isolation in a hybridizing stickleback species pair. Current Zoology, 59(5), 591–603. Lamont, B. B., He, T., Enright, N. J., Krauss, S. L., & Miller, B. P. (2003). Anthropogenic disturbance promotes hybridization between Banksia species by altering their biology. Journal of Evolutionary Biology, 16(4), 551–557. Latch, E. K., Kierepka, E. M., Heffelfinger, J. R., & Rhodes Jr, O. E. (2011). Hybrid swarm between divergent lineages of mule deer (Odocoileus hemionus). Molecular Ecology, 20(24), 5265–5279. Lewontin, R. C., & Birch, L. C. (1966). Hybridization as a Source of Variation for Adaptation to New Environments. Evolution, 20(3), 315–336. https://doi.org/10.1111/j.1558-5646.1966.tb03369.x Li, H., & Durbin, R. (2009). Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics, 25(14), 1754–1760. https://doi.org/10.1093/bioinformatics/btp324 Liu, J. Y., Sheng, Z. W., Hu, Y. Q., Liu, Q., Qiang, S., Song, X. L., & Liu, B. (2021). Fitness of F1 hybrids between 10 maternal wild soybean populations and transgenic soybean. Transgenic Research, 30(1), 105–119. https://doi.org/10.1007/s11248-020-00230-x 132 Mallet, J. (2005). Hybridization as an invasion of the genome. Trends in Ecology & Evolution, 20(5), 229–237. https://doi.org/10.1016/j.tree.2005.02.010 Massardo, D., VanKuren, N. W., Nallu, S., Ramos, R. R., Ribeiro, P. G., Silva-Brandão, K. L., Brandão, M. M., Lion, M. B., Freitas, A. V. L., Cardoso, M. Z., & Kronforst, M. R. (2020). The roles of hybridization and habitat fragmentation in the evolution of Brazil’s enigmatic longwing butterflies, Heliconius nattereri and H. hermathena. BMC Biology, 18(1), 84. https://doi.org/10.1186/s12915-020-00797-1 Mathur, S., & DeWoody, J. A. (2021). Genetic load has potential in large populations but is realized in small inbred populations. Evolutionary Applications, 14(6), 1540–1557. https://doi.org/10.1111/eva.13216 Matute, D. R., Butler, I. A., Turissini, D. A., & Coyne, J. A. (2010). A test of the snowball theory for the rate of evolution of hybrid incompatibilities. Science, 329(5998), 1518–1521. Mayr, E. (1942a). Birds collected during the Whitney South Sea Expedition. 48, Notes on the Polynesian species of Aplonis. American Museum novitates; no. 1166. Mayr, E. (1942b). Systematics and the origin of species, from the viewpoint of a zoologist. Columbia University Press. Mayr, E. (1963). Animal species and evolution. Harvard University Press. McKinney, R. A., Glatt, S. M., & Williams, S. R. (2004). Allometric length-weight relationships for benthic prey of aquatic wildlife in coastal marine habitats. Wildlife Biology, 10(4), 241–249. https://doi.org/10.2981/wlb.2004.029 133 McKinnon, J. S., & Rundle, H. D. (2002). Speciation in nature: The threespine stickleback model systems. Trends in Ecology & Evolution, 17(10), 480–488. https://doi.org/10.1016/S0169-5347(02)02579-X McPhail, J. D. (1993). Ecology and evolution of sympatric sticklebacks ( Gasterosteus ): Origin of the species pairs. Canadian Journal of Zoology, 71(3), 515–523. https://doi.org/10.1139/z93-072 Mecham, J. S. (1960). Introgressive hybridization between two southeastern treefrogs. Evolution, 445–457. Meier, J. I., Marques, D. A., Mwaiko, S., Wagner, C. E., Excoffier, L., & Seehausen, O. (2017). Ancient hybridization fuels rapid cichlid fish adaptive radiations. Nature Communications, 8(1), Article 1. https://doi.org/10.1038/ncomms14363 Miyasaka, H., Genkai-Kato, M., Miyake, Y., Kishi, D., Katano, I., Doi, H., Ohba, S., & Kuhara, N. (2008). Relationships between length and weight of freshwater macroinvertebrates in Japan. Limnology, 9(1), 75–80. https://doi.org/10.1007/s10201-008-0238-4 Moran, B. M., Payne, C., Langdon, Q., Powell, D. L., Brandvain, Y., & Schumer, M. (2021). The genomic consequences of hybridization. ELife, 10, e69016. https://doi.org/10.7554/eLife.69016 Moyle, L. C., & Nakazato, T. (2010). Hybrid incompatibility “snowballs” between Solanum species. Science, 329(5998), 1521–1523. Mullen, S. P., Little, K., Draud, M., Brozek, J., & Itzkowitz, M. (2012). Hybridization among Caribbean damselfish species correlates with habitat degradation. Journal of Experimental Marine Biology and Ecology, 416, 221–229. 134 Nagel, L., & Schluter, D. (1998). Body Size, Natural Selection, and Speciation in Sticklebacks. Evolution, 52(1), 209–218. https://doi.org/10.1111/j.1558-5646.1998.tb05154.x Nath, S., Shaw, D. E., & White, M. A. (2021). Improved contiguity of the threespine stickleback genome using long-read sequencing. G3 Genes|Genomes|Genetics, 11(2), jkab007. https://doi.org/10.1093/g3journal/jkab007 Nosil, P. (2012). Ecological Speciation. OUP Oxford. Obenchain, V., Lawrence, M., Carey, V., Gogarten, S., Shannon, P., & Morgan, M. (2014). VariantAnnotation: A Bioconductor package for exploration and annotation of genetic variants. Bioinformatics, 30(14), 2076–2078. https://doi.org/10.1093/bioinformatics/btu168 Peichel, C. L., & Marques, D. A. (2017). The genetic and molecular architecture of phenotypic diversity in sticklebacks. Philosophical Transactions of the Royal Society B: Biological Sciences, 372(1713), 20150486. https://doi.org/10.1098/rstb.2015.0486 Peichel, C. L., Nereng, K. S., Ohgi, K. A., Cole, B. L. E., Colosimo, P. F., Buerkle, C. A., Schluter, D., & Kingsley, D. M. (2001). The genetic architecture of divergence between threespine stickleback species. Nature, 414(6866), 901–905. https://doi.org/10.1038/414901a Pfennig, K. S., Chunco, A. J., & Lackey, A. C. R. (2007). Ecological selection and hybrid fitness: Hybrids succeed on parental resources. Poore, H. A., Stuart, Y. E., Rennison, D. J., Roesti, M., Hendry, A. P., Bolnick, D. I., & Peichel, C. L. (2023). Repeated genetic divergence plays a minor role in repeated phenotypic divergence of lake-stream stickleback. Evolution, 77(1), 110–122. https://doi.org/10.1093/evolut/qpac025 135 Powell, D. L., García-Olazábal, M., Keegan, M., Reilly, P., Du, K., Díaz-Loyo, A. P., Banerjee, S., Blakkan, D., Reich, D., Andolfatto, P., Rosenthal, G. G., Schartl, M., & Schumer, M. (2020). Natural hybridization reveals incompatible alleles that cause melanoma in swordtail fish. Science, 368(6492), 731–736. https://doi.org/10.1126/science.aba5216 Rafferty, N. E., & Boughman, J. W. (2006). Olfactory mate recognition in a sympatric species pair of three-spined sticklebacks. Behavioral Ecology, 17(6), 965–970. https://doi.org/10.1093/beheco/arl030 Rhymer, J. M., & Simberloff, D. (1996). Extinction by Hybridization and Introgression. Annual Review of Ecology and Systematics, 27(1), 83–109. https://doi.org/10.1146/annurev.ecolsys.27.1.83 Ribeiro, F., & Caticha, N. (2009). Emergence and loss of assortative mating in sympatric speciation. Journal of Theoretical Biology, 258(3), 465–477. Rieseberg, L. H. (1997). Hybrid Origins of Plant Species. Annual Review of Ecology and Systematics, 28(1), 359–389. https://doi.org/10.1146/annurev.ecolsys.28.1.359 Rieseberg, L. H., Kim, S.-C., Randell, R. A., Whitney, K. D., Gross, B. L., Lexer, C., & Clay, K. (2007). Hybridization and the colonization of novel habitats by annual sunflowers. Genetica, 129, 149–165. Roberts Kingman, G. A., Vyas, D. N., Jones, F. C., Brady, S. D., Chen, H. I., Reid, K., Milhaven, M., Bertino, T. S., Aguirre, W. E., & Heins, D. C. (2021). Predicting future from past: The genomic basis of recurrent and rapid stickleback evolution. Science Advances, 7(25), eabg5285. Rodgers, T. (2022). FW Enterprises Ltd. C/o Seacliff Properties 305-1788 West 5th Avenue Vancouver, BC V6J 1P2. 136 Roesti, M., Moser, D., & Berner, D. (2013). Recombination in the threespine stickleback genome—Patterns and consequences. Molecular Ecology, 22(11), 3014–3027. https://doi.org/10.1111/mec.12322 Rundle, H. D., Nagel, L., Boughman, J. W., & Schluter, D. (2000). Natural Selection and Parallel Speciation in Sympatric Sticklebacks. Science, 287(5451), 306–308. https://doi.org/10.1126/science.287.5451.306 Rundle, H. D., & Schluter, D. (2004). Natural selection and ecological speciation in sticklebacks. Adaptive Speciation, 19(3), 192–209. Rundle, H. D., & Whitlock, M. C. (2001). A genetic interpretation of ecologically dependent isolation. Evolution, 55(1), 198–201. Schlefer, E. K., Romano, M. A., Guttman, S. I., & Ruth, S. B. (1986). Effects of Twenty Years of Hybridization in a Disturbed Habitat on Hyla cinerea and Hyla gratiosa. Journal of Herpetology, 20(2), 210–221. https://doi.org/10.2307/1563946 Schley, R. J., Twyford, A. D., & Pennington, R. T. (2022). Hybridization: A ‘double-edged sword’ for Neotropical plant diversity. Botanical Journal of the Linnean Society, 199(1), 331–356. https://doi.org/10.1093/botlinnean/boab070 Schluter, D. (1995a). Adaptive radiation in sticklebacks: Trade‐offs in feeding performance and growth. Ecology, 76(1), 82–90. Schluter, D. (1995b). Adaptive Radiation in Sticklebacks: Trade-Offs in Feeding Performance and Growth. Ecology, 76(1), 82–90. https://doi.org/10.2307/1940633 Schluter, D. (1996). Ecological Causes of Adaptive Radiation. Am. Nat., 148, S40–S64. https://doi.org/10.1086/285901 137 Schluter, D., & McPhail, J. (1992). Ecological Character Displacement and Speciation in Sticklebacks. The American Naturalist, 140, 85–108. https://doi.org/10.1086/285404 Schluter, D., & Nagel, L. M. (1995). Parallel Speciation by Natural Selection. The American Naturalist, 146(2), 292–301. Schluter, D., Roesti, M., & Veen, T. (2017). Mark-recapture estimates of stickleback population sizes in Paxton and Priest Lakes in 2016. Schoener, T. W. (1969). Size Patterns in West Indian Anolis Lizards: I. Size and Species Diversity. Systematic Zoology, 18(4), 386–401. https://doi.org/10.2307/2412183 Schumer, M., Cui, R., Rosenthal, G. G., & Andolfatto, P. (2015). Reproductive Isolation of Hybrid Populations Driven by Genetic Incompatibilities. PLOS Genetics, 11(3), e1005041. https://doi.org/10.1371/journal.pgen.1005041 Schumer, M., Xu, C., Powell, D. L., Durvasula, A., Skov, L., Holland, C., Blazier, J. C., Sankararaman, S., Andolfatto, P., Rosenthal, G. G., & Przeworski, M. (2018). Natural selection interacts with recombination to shape the evolution of hybrid genomes. Science, 360(6389), 656–660. https://doi.org/10.1126/science.aar3684 Seber, G. A. F. (1982). The Estimation of Animal Abundance and Related Parameters. Charles Griffin. Seehausen, O. (2006). Conservation: Losing biodiversity by reverse speciation. Current Biology, 16(9), R334–R337. Seehausen, O., Alphen, J. J. M. V., & Witte, F. (1997). Cichlid Fish Diversity Threatened by Eutrophication That Curbs Sexual Selection. Science, 277(5333), 1808–1811. https://doi.org/10.1126/science.277.5333.1808 138 Seehausen, O., Takimoto, G., Roy, D., & Jokela, J. (2008). Speciation reversal and biodiversity dynamics with hybridization in changing environments. Molecular Ecology, 17(1), 30–44. https://doi.org/10.1111/j.1365-294X.2007.03529.x Smith, J. M., & Haigh, J. (1974). The hitch-hiking effect of a favourable gene. Genetics Research, 23(1), 23–35. Stacklies, W., Redestig, H., Scholz, M., Walther, D., & Selbig, J. (2007). pcaMethods—A bioconductor package providing PCA methods for incomplete data. Bioinformatics, 23(9), 1164–1167. https://doi.org/10.1093/bioinformatics/btm069 Stuart, Y. E., Veen, T., Weber, J. N., Hanson, D., Ravinet, M., Lohman, B. K., Thompson, C. J., Tasneem, T., Doggett, A., Izen, R., Ahmed, N., Barrett, R. D. H., Hendry, A. P., Peichel, C. L., & Bolnick, D. I. (2017). Contrasting effects of environment and genetics generate a continuum of parallel evolution. Nature Ecology & Evolution, 1(6), Article 6. https://doi.org/10.1038/s41559-017-0158 Taylor, E. B., Boughman, J. W., Groenenboom, M., Sniatynski, M., Schluter, D., & Gow, J. L. (2005). Speciation in reverse: Morphological and genetic evidence of the collapse of a three-spined stickleback (Gasterosteus aculeatus) species pair: COLLAPSE OF A STICKLEBACK SPECIES PAIR. Molecular Ecology, 15(2), 343–355. https://doi.org/10.1111/j.1365-294X.2005.02794.x Taylor, E. B., & McPhail, J. D. (2000). Historical contingency and ecological determinism interact to prime speciation in sticklebacks, Gasterosteus. Proceedings of the Royal Society B: Biological Sciences, 267(1460), 2375–2384. Taylor, E. B., & Piercey, R. S. (2018). Going, going, gone: Evidence for loss of an endemic species pair of threespine sticklebacks (Gasterosteus aculeatus) with implications for 139 protection under species-at-risk legislation. Conservation Genetics, 19(2), 297–308. https://doi.org/10.1007/s10592-017-1000-4 Taylor, S. A., & Larson, E. L. (2019). Insights from genomes into the evolutionary importance and prevalence of hybridization in nature. Nature Ecology & Evolution, 3(2), 170–177. https://doi.org/10.1038/s41559-018-0777-y Thompson, K. A., Peichel, C. L., Rennison, D. J., McGee, M. D., Albert, A. Y. K., Vines, T. H., Greenwood, A. K., Wark, A. R., Brandvain, Y., Schumer, M., & Schluter, D. (2022). Analysis of ancestry heterozygosity suggests that hybrid incompatibilities in threespine stickleback are environment dependent. PLOS Biology, 20(1), e3001469. https://doi.org/10.1371/journal.pbio.3001469 Todesco, M., Pascual, M. A., Owens, G. L., Ostevik, K. L., Moyers, B. T., Hübner, S., Heredia, S. M., Hahn, M. A., Caseys, C., Bock, D. G., & Rieseberg, L. H. (2016). Hybridization and extinction. Evolutionary Applications, 9(7), 892–908. https://doi.org/10.1111/eva.12367 Vaeßen, S., & Hollert, H. (2015). Impacts of the North American signal crayfish (Pacifastacus leniusculus) on European ecosystems. Environmental Sciences Europe, 27(1), 33. https://doi.org/10.1186/s12302-015-0065-2 Valenzuela, C. A., Zuloaga, R., Mercado, L., Einarsdottir, I. E., Björnsson, B. T., Valdés, J. A., & Molina, A. (2018). Chronic stress inhibits growth and induces proteolytic mechanisms through two different nonoverlapping pathways in the skeletal muscle of a teleost fish. American Journal of Physiology. Regulatory, Integrative and Comparative Physiology, 314(1), R102–R113. https://doi.org/10.1152/ajpregu.00009.2017 140 Vamosi, S. M., Hatfield, T., & Schluter, D. (2000). A test of ecological selection against young-of-the-year hybrids of sympatric sticklebacks. Journal of Fish Biology, 57(1), 109–121. https://doi.org/10.1111/j.1095-8649.2000.tb00779.x Vamosi, S. M., & Schluter, D. (2002). Impacts of trout predation on fitness of sympatric sticklebacks and their hybrids. Proceedings of the Royal Society of London. Series B: Biological Sciences, 269(1494), 923–930. https://doi.org/10.1098/rspb.2001.1946 Vaz Pinto, P., Beja, P., Ferrand, N., & Godinho, R. (2016). Hybridization following population collapse in a critically endangered antelope. Scientific Reports, 6(1), 1–9. Velema, G. J., Rosenfeld, J. S., & Taylor, E. B. (2012). Effects of invasive American signal crayfish ( Pacifastacus leniusculus ) on the reproductive behaviour of threespine stickleback ( Gasterosteus aculeatus ) sympatric species pairs. Canadian Journal of Zoology, 90(11), 1328–1338. https://doi.org/10.1139/z2012-102 Veller, C., Edelman, N. B., Muralidhar, P., & Nowak, M. A. (2021). Recombination and selection against introgressed DNA (p. 846147). bioRxiv. https://doi.org/10.1101/846147 Vonlanthen, P., Bittner, D., Hudson, A. G., Young, K. A., Müller, R., Lundsgaard-Hansen, B., Roy, D., Di Piazza, S., Largiader, C. R., & Seehausen, O. (2012). Eutrophication causes speciation reversal in whitefish adaptive radiations. Nature, 482(7385), Article 7385. https://doi.org/10.1038/nature10824 Whitehead, A., Clark, B. W., Reid, N. M., Hahn, M. E., & Nacci, D. (2017). When evolution is the solution to pollution: Key principles, and lessons from rapid repeated adaptation of killifish (Fundulus heteroclitus) populations. Evolutionary Applications, 10(8), 762–783. 141 Yang, X., Wu, X., Hao, H., & He, Z. (2008). Mechanisms and assessment of water eutrophication. Journal of Zhejiang University. Science. B, 9(3), 197–209. https://doi.org/10.1631/jzus.B0710626 142 Appendices Appendix A - Supplementary Material for Chapter 2 A.1 Phenol-Chlorofom Based DNA Isolation for Stickleback DNA Written by Mackenzie Kinney, modified from protocol by Katie Peichel Day 1: Tissue Digestion 1. Preparation: a. Turn on incubator, make sure it is set to 55ºC. b. Aliquot 500 μl of tissue digestion buffer into 1.5 ml tubes (1 tube per specimen). c. Make specimen labels if specimens are to be preserved. 2. Cut off caudal fin near base. Right pectoral fin may also be used. Allow fin to dry so that all ethanol from preservation is removed. 3. Place the fin clips into tube with 500 μl of tissue digestion buffer. 4. Add 15 μl of proteinase K. 5. Vortex briefly and place tubes in 55ºC incubator overnight. Day 2: DNA Isolation 1. Vortex samples briefly once tissue is fully digested. 2. Take samples to fumehood. Add 200uL of tissue lysis buffer for a new total of 700uL. Add 600 μl of 25:24:1 phenol:chloroform:isoamyl alcohol solution. Note: Be careful, this solution is highly toxic and tends to drip from the pipette. It must also be kept in the dark and in the fridge when not in use. Do not use is solution is pink-ish. It should be pale yellow in colour. 3. Vortex in hood a few seconds until completely mixed. Solution should look milky white. You can also shake vigorously by hand. 4. If possible, put centrifuge in fumehood. a. Spin 10 minutes at room temperature at 12,100 rpm. b. Aliquot 1 ml of 100% ethanol into new (labeled) 1.5 ml tubes with SafeLock lids. c. When spin is complete, remove tubes from centrifuge carefully so as to not distrupt distinct layers of solution. 5. In hood, carefully remove the top layer into fresh tube with 1ml 100% EtOH. By holding tubes on a slant as you pipette, you can get closer to the interface. Do not pipette up any of the interface or phenol below. Discard phenol tube. 143 6. Mix by inverting several times. 7. Spin 15 minutes at room temperature at 14,000 rpm. By keeping all tube hinges to the outside, DNA pellet will be in the same, predictable place in each tube. 8. After centrifugation you should see a gray/white pellet at the bottom of the tube. Remove ethanol (by pouring carefully) without disturbing the pellet. 9. Add 500 μl of ice cold 100% ethanol (stored in -20C freezer). Mix by shaking. 10. Place tubes into -20C freezer for 10 minutes. 11. Spin 10 minutes at room temperature at 14,000 rpm. 12. After centrifugation you should see a gray/white pellet at the bottom of the tube again. Remove (by pouring) ethanol without disturbing the pellet. 13. Add 500 μl of ice cold 70% ethanol (stored in -20C freezer). 14. Spin 10 minutes at room temperature at 14,000 rpm. 15. Remove 70% ethanol initially by quickly pouring the majority off. Then carefully remove the remaining ethanol with p200 pipette. 16. Dry pellet for 10-20 minutes at room temperature. Be sure to let dry so that all ethanol has evaporated (otherwise ethanol may interfere with PCR). 17. Resuspend in 50 μl of AE buffer. Troubleshooting after Nanodrop If 260/280 ratio is too high, (2.0 or above), suspect RNA contamination. RNA Removal 1. Add 2uL of RNAse A (10mg/mL concentration) to each tube. 2. Incubate at 55C for 1 hour (or overnight if timing works best). 3. Nanodrop to see if ratio has improved. If 260/230 ratio is too low (below 2.0), suspect phenol contamination. Ethanol Purification (see Barrick Protocol) 144 A.2 PCA cluster for stickleback classification. PCA plot used to cluster genomes of experimental stickleback for cross classification, where PC1 is the benthic to limnetic axis and PC2 is family. A) Seven distinct clusters identified which are reduced B) to three clusters that identify stickleback cross type. Cluster identity is based on location of known benthic and limnetic individuals within clusters. Green cluster is limnetic, black cluster is benthic and red cluster is hybrid individuals. -10 -5 0 5-6-4-20246PC1PC2-10 -5 0 5-6-4-20246PC1PC2ß Limnetic Benthic à ß Limnetic Benthic àA B 145 A.3 Chlorophyll A concentration at 4m depth. Day of the year corresponds to the number of days that have passed since January 1, with the x-axis displaying dates between April 20 and August 21st. Yellow lines are the eutrophic ponds and green lines are control ponds, with thin lines showing measurements from each individual pond over time, and thick lines representing linear regressions for each treatment type. Dashed horizontal lines indicate the chlorophyll A concentration threshold for water to be considered mesotrophic (2.5 ug/L) or eutrophic (>7ug/L) 012340.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Proportion of HybridsNumber of PondsTreatmentControlEutrophicFall TimepointBAMesotrophicEutrophic01234567891011121314110 130 150 170 190 210 230Day of the YearChlorophyll A Conc. (ug/L)TreatmentControlEutrophic 146 A.4 Light extinction changes during active nutrient addition. Light extinction/cm is calculated as the change in photosynthetically active radiation between two depths, divided by the depth total. This was done for differences between A) the surface and 1m B) the surface and 2m and C) the surface and 4 m. Measurements were taken at three timepoints; once in April, June and August. Concentrations for each timepoint has treatment (in yellow) and control(in green) paired. In all plots, points are individual ponds and thick horizontal lines are the treatment means. _ __ ___468April June AugustMonthLight Extinctioncm (mmoles light energy per m2 )Treatment__ControlEutrophicPAR Light Extinction from 0−1m Depth_ __ ___34567April June AugustMonthLight Extinctioncm (mmoles light energy per m2 )Treatment__ControlEutrophicPAR Light Extinction from 0−2m Depth_ __ ___2.53.03.54.0April June AugustMonthLight Extinctioncm (mmoles light energy per m2 )Treatment__ControlEutrophicPAR Light Extinction from 0−4m Depth012340.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Proportion of HybridsNumber of PondsTreatmentControlEutrophicFall TimepointA BC 147 A.5 Oxygen concentration during active nutrient addition. Absolute oxygen concentration was calculated at A) 1m B) 2m and C) 4 m depths in the water column. Measurements were taken at three timepoints; once in April, June and August. Concentrations for each timepoint has treatment (in yellow) and control(in green) paired. In all plots, points are individual ponds and thick horizontal lines are the treatment means. _ __ __ _910111213April June AugustMonthOxygen Concentration (mg/L) Treatment__ControlEutrophicOxygen Saturation at 1m_ __ __ _81012April June AugustMonthOxygen Concentration (mg/L) Treatment__ControlEutrophicOxygen Concentration at 2m_ __ __ _89101112April June AugustMonthOxygen Concentration (mg/L) Treatment__ControlEutrophicOxygen Concentration at 4m012340.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0Proportion of HybridsNumber of PondsTreatmentControlEutrophicFall TimepointA BC 148 A.6 Relationship of population estimate with treatment and hybrid proportion. A) Population estimate within ponds, where points are individual pond estimates and thick horizontal bar are treatment averages. Control ponds are shown in green and treatment ponds are shown in yellow. B) Hybrid proportion as a function of population estimate. Each black dot corresponds to a particular pond, and the green line is a linear regression. There is a slight positive, but insignificant relationship. _ _40080012001600Control EutrophicTreatmentPopulation EstimateTreatment__ControlEutrophicA0.000.250.500.751.00400 800 1200 1600Population EstimateHybrid ProportionB 149 A.7 Proportion of hybrids remaining after overwinter survival Proportion of hybrids remaining after overwinter survival, determined using samples collected during our summer sampling period. Hybrid proportion within a pond is binned in increments of 0.1, and the y axis shows the number of ponds with a proportion within that binned category. Each pond is treated separately, with treatment ponds in yellow and control ponds in green. 01230.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9Proportion of HybridsNumber of PondsTreatmentControlEutrophicSummer Timepoint 150 A.8 Hybrid proportion predicted by chlorophyll A concentration. The relationship between the proportion of hybrids during the fall collection point and the chlorophyll A concentration at various points in time during active nutrient addition. Each colour corresponds to a different date, where the points are different ponds and lines are linear regressions showing the relationship between chlorophyll A concentration at a particular point in time and the final hybrid proportion in the fall, after the breeding period is over. Each date is used separately to determine if a particular point in time was more significant in predicting hybrid proportion. The was done for chlorophyll A concentration at A) 1m and B) 4m depths. C) shows the same information as figure A, with the exception that chlorophyll A concentration is used to predict the change in hybrid proportion over winter rather than absolute hybrid proportion in the fall. 0.000.250.500.751.003 6 9Chlorophyll A Conc. (ug/L)Hybrid Proportion Date2013−05−052013−05−082013−06−042013−06−292013−08−210.000.250.500.751.003 6 9Chlorophyll A Conc. (ug/L)Hybrid Proportion Date2013−05−052013−05−082013−06−042013−06−292013−08−21−0.3−0.2−0.10.00.10.23 6 9Chlorophyll A Conc. (ug/L)Hybrid Proportion ChangeDate2013−05−052013−05−082013−06−042013−06−292013−08−21A B−0.3−0.2−0.10.00.10.23 6 9Chlorophyll A Conc. (ug/L)Hybrid Proportion ChangeDate2013−05−052013−05−082013−06−042013−06−292013−08−21C1 m Depth 4 m Depth1 m Depth 151 A.9 Hybrid proportion predicted by light availability The relationship between the proportion of hybrids during the fall collection point and A) photosynthetically active radiation at a 1m depth and B) light extinction per cm between the surface and 1m depth. Each colour corresponds to a different date, where the points are different ponds and lines are linear regressions showing the relationship between light availability at a particular point in time and the final hybrid proportion in the fall, after the breeding period is over. Each date is used separately to determine if a particular point in time was more significant in predicting hybrid proportion. 0.000.250.500.751.00800 1000 1200PAR (mmoles light energy per m2)Hybrid Proportion ChangeDate2013−05−082013−06−042013−06−290.000.250.500.751.004 6 8Light Extinction cm (mmoles light energy per m2)Hybrid Proportion ChangeDate2013−05−082013−06−042013−06−29BA 152 A.10 Hybrid proportion predicted by oxygen availability. The relationship between the proportion of hybrids during the fall collection point and A) oxygen concentration at a 1m depth and B) oxygen reduction between the surface and 4m. Each colour corresponds to a different date, where the points are different ponds and lines are linear regressions showing the relationship between light availability at a particular point in time and the final hybrid proportion in the fall, after the breeding period is over. Each date is used separately to determine if a particular point in time was more significant in predicting hybrid proportion. All measurements are taken at a 1m depth. 0.000.250.500.751.009 10 11 12 13Oxygen Concentration (mg/L)Hybrid Proportion ChangeDate2013−05−082013−06−042013−06−290.000.250.500.751.000 10 20 30Oxygen Reduction (mg/L)Hybrid Proportion ChangeDate2013−05−082013−06−042013−06−29A B 153 Appendix B Supplementary Material for Chapter 3 B.1 Density dependant fish growth Natural log-transformed fish growth (length) in relation to the number of fish within each tank present at the end of the experiment. Each plot represent a single cross type. Dots represent individual tanks, lines are simple linear regression and grey regions are the 95% confidence intervals for each regression. 154 Appendix C Supplementary Material for Chapter 4 C.1 Changes in hybrid index across individual chromosomes 0.0 0.2 0.4 0.6 0.8 1.0024681012141618202224262830Chromosome 1 Position (Mbp)Hybrid IndexEnos Lake Chromosome 1−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618202224262830Chromosome 1 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 1−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618202224262830Chromosome 1 Position (Mbp)Hybrid IndexSecond Lake Chromosome 1−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618Chromosome 2 Position (Mbp)Hybrid IndexEnos Lake Chromosome 2−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618Chromosome 2 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 2−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618Chromosome 2 Position (Mbp)Hybrid IndexSecond Lake Chromosome 20.0 0.2 0.4 0.6 0.8 1.0024681012141618Chromosome 3 Position (Mbp)Hybrid IndexEnos Lake Chromosome 3−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618Chromosome 3 Position (Mbp)Hybrid IndexMurdo Frazer Pond Chromosome 3−0.2 0.0 0.2 0.4 0.6 0.8 1.0024681012141618Chromosome 3 Position (Mbp)Hybrid IndexSecond Lake Chromosome 3 155 156 157 158 159 160 161 Changes in hybrid index across individual chromosomes (1-21) based on SNP allele frequencies. Priest Lake was used as the reference when calculating hybrid index for each hybrid population. From left to right, columns are Enos Lake, Murdo Frazer Pond and Second Lake.
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