Arts and Sciences, Irving K. Barber School of (Okanagan)
Biology, Department of (Okanagan)
DSpace
UBCO
Elliott, Lucas Dane
Master of Science - MSc
University of British Columbia
Marine and freshwater fisheries have seen dramatic declines over the past century due largely to various direct and indirect anthropogenic factors. In tandem with addressing the initial causes leading to fish population decline, stocking initiatives have been increasingly employed for stock reintroduction and/or enhancement. One such program aimed at repatriating the anadromous sockeye salmon (Oncorhynchus nerka) in Skaha Lake, British Columbia has seen successful establishment over the past 15 years. However, substantial levels of hybridization with the freshwater resident ecotype of O. nerka, kokanee, have been detected in juvenile fish. While this hybridization could be a healthy source of genetic diversity, it could also lead towards the genetic swamping of either population, lowered reproductive success, and potentially even extirpation. Here, we aim to investigate the genetic and biological consequences of hybridization and introgression in this system. We examined a total of 786 individuals comprising both spawners and age-0 fish collected from 2008 – 2017. Each sample was genotyped at 32 single nucleotide polymorphisms and assigned to a sockeye, kokanee, or hybrid class. We selected individuals from all three classes to undergo otolith microchemistry analysis to determine their migratory life history. Across sampling years, we found a large majority of hybrids to be non-anadromous with a resident maternal parent and of an intermediate size in comparison with the purestocks. These results provide empirical support for the theorized mechanisms of hybridization and offer some prospective pathways for management in this system. Additionally, we have developed a generalized methodology to construct a panel of molecular markers to differentiate advanced introgression classes. Demonstrated with the test case of sockeye – kokanee hybridization, the resulting accuracy- and cost-optimized panel will assist in the continued time-series sampling of Skaha Lake to monitor this reintroduction program as it matures.
THERE AND BACK AGAIN: AN INVESTIGATION OF THE BIOLOGICAL AND GENETIC CONSEQUENCES OF A SOCKEYE STOCKING PROGRAM by Lucas Dane Elliott B.A., Colorado College, 2016 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE COLLEGE OF GRADUATE STUDIES (Biology) THE UNIVERSITY OF BRITISH COLUMBIA (Okanagan) March 2019 © Lucas Dane Elliott, 2019 ii The following individuals certify that they have read, and recommend to the College of Graduate Studies for acceptance, a thesis/dissertation entitled: THERE AND BACK AGAIN: AN INVESTIGATION OF THE BIOLOGICAL AND GENETIC CONSEQUENCES OF A SOCKEYE STOCKING PROGRAM submitted by Lucas Dane Elliott in partial fulfillment of the requirements of the degree of Master of Science Dr. Michael Russello, Department of Biology, Irving K. Barber School of Arts and Sciences Supervisor Dr. Hillary Ward, Ministry of Forests, Lands and Natural Resource Operations, Thompson – Okanagan Region Supervisory Committee Member Dr. Robert Lalonde, Department of Biology, Irving K. Barber School of Arts and Sciences Supervisory Committee Member Dr. Jeff Curtis, Department of Earth, Environmental and Geographic Studies, Irving K. Barber School of Arts and Sciences University Examiner iii Abstract Marine and freshwater fisheries have seen dramatic declines over the past century due largely to various direct and indirect anthropogenic factors. In tandem with addressing the initial causes leading to fish population decline, stocking initiatives have been increasingly employed for stock reintroduction and/or enhancement. One such program aimed at repatriating the anadromous sockeye salmon (Oncorhynchus nerka) in Skaha Lake, British Columbia has seen successful establishment over the past 15 years. However, substantial levels of hybridization with the freshwater resident ecotype of O. nerka, kokanee, have been detected in juvenile fish. While this hybridization could be a healthy source of genetic diversity, it could also lead towards the genetic swamping of either population, lowered reproductive success, and potentially even extirpation. Here, we aim to investigate the genetic and biological consequences of hybridization and introgression in this system. We examined a total of 786 individuals comprising both spawners and age-0 fish collected from 2008 – 2017. Each sample was genotyped at 32 single nucleotide polymorphisms and assigned to a sockeye, kokanee, or hybrid class. We selected individuals from all three classes to undergo otolith microchemistry analysis to determine their migratory life history. Across sampling years, we found a large majority of hybrids to be non-anadromous with a resident maternal parent and of an intermediate size in comparison with the purestocks. These results provide empirical support for the theorized mechanisms of hybridization and offer some prospective pathways for management in this system. Additionally, we have developed a generalized methodology to construct a panel of molecular markers to differentiate advanced introgression classes. Demonstrated with the test case of sockeye – kokanee hybridization, the resulting accuracy- and cost-optimized panel will assist in the continued time-series sampling of Skaha Lake to monitor this reintroduction program as it matures. iv Lay Summary Freshwater fisheries have seen dramatic declines over the past century due largely to various direct and indirect human factors. In tandem with addressing the initial causes leading to fish population decline, stocking initiatives have been increasingly employed. One such program aimed at returning sockeye salmon to Skaha Lake, British Columbia has seen successful establishment over the past 15 years. However, unexpectedly high levels of hybridization with another fish, kokanee, have been detected. While this hybridization could be beneficial, it could also lead towards the extinction of either population. Here, we investigate how sockeye - kokanee hybridization is affecting the salmon population of Skaha Lake and propose some management strategies for limiting its negative impacts. We additionally provide a generalizable framework for studying this hybridization that can be applied to the increasing number of stocking programs employed around the globe. v Preface Multiple individuals have contributed to Chapters 2 and 3 of this thesis. The study design was a collaborative effort between myself, Dr. Michael Russello, and Dr. Hillary Ward. I have been primarily responsible for sample processing, genetic data collection, data analysis, and manuscript preparation. Samples were provided by the Okanagan Nation Alliance and the Ministry of Forests, Lands and Natural Resource Operations who recorded all morphometric data. A manuscript containing the results from Chapter 2 has been completed with Dr. Michael Russello and Dr. Hillary Ward as co-authors. It has been submitted to the Canadian Journal of Fisheries and Aquatic Sciences for publication. The results and methodology contained in Chapter 3 have been published in Fisheries Research with Dr. Michael Russello as co-author. The title of the article is SNP panels for differentiating advanced-generation hybrid classes in recently diverged stocks: A sensitivity analysis to inform monitoring of sockeye salmon re-stocking programs. vi Table of Contents Abstract ................................................................................................................................... iii Lay Summary ......................................................................................................................... iv Preface ...................................................................................................................................... v Table of Contents ................................................................................................................... vi List of Tables ........................................................................................................................ viii List of Figures ......................................................................................................................... ix Acknowledgements ................................................................................................................. x Chapter 1: Introduction ......................................................................................................... 1 1.1 Freshwater fisheries and reintroductions......................................................................... 1 1.2 Oncorhynchus nerka ....................................................................................................... 2 1.3 Sockeye stocking in Skaha Lake ..................................................................................... 3 1.4 Genetic assignment of salmonids and their hybrids ........................................................ 5 1.5 Study objectives .............................................................................................................. 6 Chapter 2: Genetic monitoring of sockeye salmon and kokanee hybridization in Skaha Lake, BC .................................................................................................................................. 7 2.1 Background ..................................................................................................................... 7 2.2 Methods ......................................................................................................................... 10 2.2.1 Sample collection ................................................................................................... 10 2.2.2 Genetic analyses ..................................................................................................... 11 2.2.3 Age distribution and morphometric analyses ......................................................... 12 2.2.4 Microchemistry analyses ........................................................................................ 12 vii 2.3 Results ........................................................................................................................... 13 2.3.1 Genetic stock assignment ....................................................................................... 13 2.3.2. Age distributions and morphometric analyses ....................................................... 14 2.3.3 Microchemistry analyses ........................................................................................ 15 2.4 Discussion ..................................................................................................................... 15 Chapter 3: SNP panels for differentiating advanced-generation hybrid classes in recently diverged stocks: a sensitivity analysis to inform monitoring of sockeye salmon re-stocking programs ............................................................................................................ 19 3.1 Background ................................................................................................................... 19 3.2 Methods ......................................................................................................................... 21 3.3 Results ........................................................................................................................... 22 3.4 Discussion ..................................................................................................................... 23 Chapter 4: Conclusion .......................................................................................................... 26 4.1 Research findings and significance ............................................................................... 26 4.2 Limitations and future studies ....................................................................................... 27 References ............................................................................................................................ 400 viii List of Tables Table 1. Numbers of age-0 hatchery sockeye released into Skaha Lake between 2004 and 2017......................................................................................................................................... 30 Table 2. Stock composition of spawners and juvenile (age-0) fish by year........................... 30 Table 3. Observed number of female spawners compared to expected proportions based on whole sample year. Pearson’s chi-squared test results included. ............................................ 31 Table 4. Otolith microchemistry analysis results ................................................................... 31 Table 5. Number of fish assigned to each genetic category by sample year and spawning age determined by otolith analysis ................................................................................................ 31 Table 6. Average spawning age in years of all genetically assigned fish .............................. 31 Table 7. Confusion matrices of simulated individuals’ proportional assignment using LEA’s admixture coefficient. Rows show known introgression class and columns are the assigned class with highlighted values corresponding to correct assignment proportions. ................... 32 Table 8. Confusion matrices of simulated individuals’ proportional assignment using NEWHYBRIDS. Rows show known introgression class and columns are the assigned class with highlighted values corresponding to correct assignment proportions. ........................... 33 ix List of Figures Figure 1. Map showing the northern extent of the Columbia River with inset map (right) showing Skaha Lake and nearby lakes, rivers and dams. ....................................................... 34 Figure 2. Graph of strontium and barium levels overlaid on a cross-section of the otolith they were taken from.. .................................................................................................................... 35 Figure 3. Stock proportions of age-0 juvenile fish including results from Veale and Russello 2016......................................................................................................................................... 36 Figure 4. Variation in fork length (mm) by sex and stock pooled across sample years. ....... 37 Figure 5. Fork length of spawners from each class by sample year. ..................................... 37 Figure 6. Fork length of spawners from each class by age. ................................................... 38 Figure 7. Distribution of admixture coefficients from LEA for 1000 simulated individuals from each introgression class. ................................................................................................. 39 x Acknowledgements Despite the single authorship on the title page, this thesis is really the culmination of many people’s work, input, advice, and encouragement. Primarily, I would like to thank my advisor, Dr. Michael Russello, for giving me the opportunity to pursue my ecological interests and his invaluable guidance throughout my degree. I am extremely grateful for the vital insight and feedback provided by Dr. Hillary Ward for this project. Additionally, I am thankful for the input of Dr. Bob Lalonde who has helped shaped my thesis. The support of past and present members of the Ecological Conservation Genomics Laboratory has kept me engaged throughout my degree. Thank you to Brett, Matt, and Evelyn for welcoming me into the lab, Bryson for showing me that even the wise cannot see all ends, and Yoamel for having an endlessly positive outlook. I’m very fortunate to have synced up my graduate studies with as wonderful of a person as Danielle and unfortunate enough to only catch the beginning of Farida, Brock, and Sarah’s. I am especially grateful to the incredible community of friends I’ve found in Kelowna. You have all made this the warmest and most comfortable two years of my life. Additionally, I am forever thankful to my parents for their unwavering support of my scientific pursuits even as it’s led me to faraway, distant places. Both of you have inspired and motivated me to become the person I am today. I would also like to thank all of the contributors to Stack Exchange and similar forums for being a light in many dark places, when all other lights had gone out. Nearly all aspects of my thesis have been helped along by openly-accessible online sources. This research was funded by the Freshwater Fisheries Society of BC (FFSBC) through a MITACS Accelerate Internship. Samples have been provided by the Okanagan Nation Alliance (ONA) and the British Columbia Ministry of Forests, Lands and Natural Resource Operations (FLNRO).1 Chapter 1: Introduction 1.1 Freshwater fisheries and reintroductions Freshwater fisheries are a priority for conservation due to their disproportionally high biodiversity and comparative vulnerability with marine and terrestrial ecosystems (Dudgeon et al. 2006). These fisheries are threatened worldwide due largely to anthropogenic factors such as exotic species introductions, dam operations, spawning habitat destruction, over-fishing, altered nutrient inputs, and climate change (Darwall & Freyhof 2015; Post et al. 2002). Among vertebrates in the 20th century, freshwater fishes have the highest rate of extinction which is predicted to remain constant or even increase towards the year 2050 (Burkhead 2012). In tandem with reducing the initial factors leading to fish population decline, stocking initiatives have been increasingly employed for stock reintroduction and/or enhancement (Cochran-Biederman et al. 2015). Dating back more than 100 years with artificially raised Oncorhynchus keta being released to bolster stock numbers in Japan as early as 1876 (Kitada 1999), these programs were often motivated by what was technologically feasible at the time rather than meeting pre-defined management goals (Molony et al. 2004). Stocking with the intent of returning an extirpated species to a historical range began in the 1980s (Monnerjahn 2011). Despite high failure rates for these programs throughout the mid to late 20th century, improved monitoring and an increase of reintroduction-related papers published in peer-reviewed journals have coincided with some spectacular success stories (Armstrong & Seddon 2008). While stocking initially increases the overall population numbers of the managed fish, hatchery reared “native invaders” can cause a decrease in foraging efficiency and growth rate of sympatric wild fish through competition while also altering the ecosystem they were stocked into (Hasegawa et al. 2018). Despite being the offspring of wild fish themselves, stocked hatchery fish have been recorded as having significantly lower survival than their wild counterparts (Saltveit 2006). Focusing on scales broader than basic population establishment has been identified as a priority for future reintroduction research (Taylor et al. 2017). 2 1.2 Oncorhynchus nerka Sockeye salmon (Oncorhynchus nerka) are found throughout the Northern Pacific Ocean with spawning areas in Japan, Russia, Alaska, British Columbia, and the northwestern US (Groot & Margolis 1991; McPhail 2007). The majority of sockeye salmon populations in British Columbia are distributed throughout the Fraser River and Skeena River drainages with a minority in the southeast of the province migrating through the Columbia River. The Committee on the Status of Endangered Wildlife in Canada (COSEWIC) recently recommended the listing of eight Fraser River sockeye salmon populations as endangered under Canada’s Species at Risk Act (SARA). Several anadromous populations in the United States are similarly listed under the Endangered Species Act due to dramatically reduced spawning populations (NOAA/NMFS 2015). Through a proposed model of recurrent evolution where separate lineages evolve similar traits, O. nerka has repeatedly diverged into three polyphyletic ecotypes: (1) the “lake-type” that spawn in lakes or nearby tributaries and rear in nursery lakes for at least one year before migrating to the ocean, (2) the “sea/river-type” that spawn in rivers or side channels and migrate out to the ocean after a comparatively shorter and more variable period of weeks or months spent in river or estuarine environments without over-wintering, and (3) “non-anadromous-type” (kokanee) whose entire life history is spent in freshwater (Beacham & Withler 2017; Wood et al. 2008). An additional group composed of sockeye that have recently forgone their anadromous life history in favor of residing solely in freshwater lakes has also been considered (Nichols et al. 2016). It is theorized that “sea/river-type” sockeye were able to persist during the 19 or 20 glaciations of the Pleistocene Epoch, while “lake-type” sockeye and subsequently kokanee repeatedly faced extinction and re-evolved through adaptive radiation from the ancestral “sea/river-type” during interglacial periods (Wood et al. 2008). Higher genetic diversity in “sea-type” sockeye supports the idea that modern “lake-type” sockeye and kokanee diverged from this lineage approximately 10 - 15,000 years ago in the wake of the last glaciation (Wood & Foote 1996). Size selective mating, differing spawning times, and countergradient variation of breeding color are all thought to contribute to the continued sympatric differentiation of “lake-type” sockeye and kokanee (Craig et al. 2005; Hamon & Foote 2005). Unlike kokanee, 3 sockeye have strong selective pressures to maintain fast growth rates and a large body size to increase smolt survival during their seaward migration (Henderson & Cass 1991). Observed spawning ages for kokanee and sockeye are often at age-3 (4 years after fertilization), however many environmental factors can influence the timing of this event (Wood & Foote 1996). Kokanee in particular are liable to spawn at earlier ages in response to conditions 10 to 16 months prior to their potential spawning date (Patterson et al. 2008). This predisposal for precocious maturation has been documented in sockeye – kokanee hybrids suggesting a genetic component to this ability (Wood & Foote 1996). Captively reared sockeye – kokanee hybrids have provided some information on the morphology and physiology of this group, but little is known about their life history or fitness in natural environments (Wood & Foote 1996). 1.3 Sockeye stocking in Skaha Lake The study case of Skaha Lake exemplifies the trials of many anadromous fish in western North America through the 20th century. Dam construction in British Columbia began with small-scale projects starting in the 1890s and culminated with the Columbia River Treaty of 1964 (Sandford et al. 2014). South of the US-Canada border, watershed alterations along the Columbia River began to peak much earlier with the passage of the Reclamation Act of 1902 and the expansion of the Army Corp of Engineers into civilian projects (Barber 2005; MacKendrick 1975). These constructions, along with numerous other anthropogenic factors, have significantly contributed to more freshwater fish species having gone extinct in North America (n = 57) in the 20th century than the rest of the world combined (n = 26) over this time period (Burkhead 2012). On a finer scale, anadromous salmonids have been especially impacted by watershed alterations along the Columbia River with nearly a quarter of historical evolutionarily significant units (distinct populations designated for conservation) being lost (Gustafson et al. 2007). Located in the Okanagan Valley of Southern British Columbia, Skaha Lake (Figure 1) drains through the Okanagan River into Vaseux and Osoyoos Lake ultimately joining with the Columbia River at Lake Pateros in Washington, USA. Prior to the 20th century, it is believed that anadromous sockeye salmon navigated these waterways to spawn in the Okanagan River Basin potentially as far north as Skaha and Okanagan Lake depending on 4 river flow conditions. The construction of a dam near McIntyre Bluff in 1916 blocked the return of these migrants, effectively extirpating anadromous O. nerka northwards (Alliance et al. 2000; Hewes 1998; Kennedy & Bouchard 1998). In the 1990s, the Okanagan Nation Alliance (ONA) partnered with the Chelan and Grant Counties Public Utilities in Washington State to advocate for sockeye reintroduction in the area (McQueen et al. 2017). Pending an investigative period, the Okanagan Basin Technical Working Group (composed of Fisheries and Oceans Canada (DFO), British Columbia Ministry of Forests Lands and Natural Resource Operations (FLNRO), and ONA) approved the experimental restocking of sockeye into Skaha Lake (Peters et al. 1998). Three annual reports were subsequently published to document the project design and risk assessment prior to reintroduction (Okanagan Nation Alliance 2001, 2002, 2003). Due to the possibility of exotic species and fish disease introduction (particularly the Parvicapsula parasite), the truck and transport method of reintroduction was initially favored over completely opening McIntyre and other Skaha Lake outlet dams to migrants (Wright & Smith 2004). This option additionally facilitated easier marking and number control of juvenile sockeye released into the lake. In 2003, sockeye were collected from the Okanagan River near Oliver, BC to serve as brood-stock for the reintroduction . After eggs and fry were reared in a DFO managed hatchery, 325,500 sockeye fry were released into Skaha Lake in May 2004 to gauge if any would manage to successfully leave the lake as smolts the following year (Lawrence et al. 2005; Wright & Smith 2004). Following the success of this trial, variable numbers of sockeye fry have been released into the lake each year since 2004, with the exception of 2014 which was designated a fallow year, totaling approximately 15 million fish over this period (Table 1). Through dam modifications, upstream passage was provided for returning anadromous migrants in 2011 (McQueen et al. 2017). 5 1.4 Genetic assignment of salmonids and their hybrids The groundwork for using genetics as a fishery stock identification tool has a long history with “races” of Oncorhynchus nerka being described in the 1950s through blood types (Ridgway & Klontz 1961). Allozyme studies linking O. nerka genetic variants to their geographic spawning areas appeared as early as 1980 (Grant et al. 1980). Since this time period, genetic methods began to gradually replace their predecessors largely due to their: (1) consistent expression independent of environmental factors, (2) discrete composition allowing for quantification, (3) temporal stability, and (4) cost effectiveness (Milner et al. 1985). Salmonids’ small breeding populations and high fidelity to native streams make them an ideal study taxa for genetic differentiation (Allendorf & Seeb 2000). Early attempts at the genetic identification of hybrids were limited by the small number of molecular markers that could be identified and their relative informativeness at discriminating the parent populations (Currat et al. 2008). Despite these challenges, introgression from a single escape of several hundred to several thousand Norwegian farmed Atlantic salmon (Salmo salar L.) was detected in Northern Ireland stocks in the early 1990s using diagnostic allozymes (Crozier 1993). However, few hybridizing events present these ideal conditions of a single introduction, fixed different alleles, and a rapid response (Glover et al. 2017). One of the first studies to examine long-term introgression from a mixed-origin stock used a suite of microsatellite loci to observe a change in genetic profiles over 21 years (Skaala et al. 2006). Currently, single nucleotide polymorphisms (SNPs) have become the hybrid identification tool of choice due to their abundance relative to other molecular markers, genome-wide distribution, and relative ease of genotyping (Glover et al. 2010; Twyford & Ennos 2012). 6 1.5 Study objectives Considerable knowledge gaps are present regarding the origin and life history of sockeye – kokanee hybrids. This fundamental information is critical to effectively manage and evaluate stocks of Oncorhynchus nerka where these ecotypes co-occur. Our findings will allow managers to assess the risks that sockeye reintroductions could pose to native kokanee in three ways: First, we will investigate the biological mechanisms of sockeye - kokanee hybridization and its consequent genetic, morphological and behavioral implications. Second, we will document hybridization trends in both the spawning and juvenile populations related to the Skaha Lake sockeye reintroduction program Finally, we will evaluate and optimize a single nucleotide polymorphism panel in silico for differentiating advanced-generation hybrid classes that will allow for effective monitoring to continue into the future. 7 Chapter 2: Genetic monitoring of sockeye salmon and kokanee hybridization in Skaha Lake, BC 2.1 Background The predicted collapse of marine fisheries has garnered wide attention (Costello et al. 2016; Worm et al. 2006). Although less publicized, freshwater fisheries worldwide are threatened with a similar fate due largely to anthropogenic factors such as exotic species introductions, dam operations, spawning habitat destruction, altered nutrient inputs, and climate change (Darwall & Freyhof 2015; Post et al. 2002). Among vertebrates in the 20th century, freshwater fishes have the highest rate of extinction which is predicted to remain constant or even increase towards the year 2050 (Burkhead 2012). In tandem with reducing the impacts leading to decline, stocking initiatives have been increasingly employed for stock reintroduction and/or reinforcement (Cochran-Biederman et al. 2015). Dating back more than 100 years with artificially raised Oncorhynchus keta being released to bolster stock numbers in Japan as early as 1876 (Kitada 1999), these stocking programs were often motivated by what was technologically feasible at the time rather than meeting pre-defined management goals (Molony et al. 2004). Stocking with the intent of returning an extirpated species to a historical range has become increasingly more prevalent since the 1980s (Monnerjahn 2011). While stocking bolsters the abundance numbers of the managed fish, hatchery reared “native invaders” can cause a decrease in foraging efficiency and growth rate of sympatric wild fish through competition while also altering the ecosystem they were stocked into (Hasegawa et al. 2018). Despite being the offspring of wild fish themselves, stocked hatchery fish have been recorded as having significantly lower returns than their wild counterparts (Saltveit 2006). In cases where reproductively compatible native stocks exist, hybridization has been reported between hatchery fish and native stocks and there is a need to monitor the genetic outcomes of hybridization and introgression (Cordes et al. 2006; Savary et al. 2017). Hybridization has been identified as a central force in the evolution and speciation of organisms by providing the raw material needed for adaptive divergence (Abbott et al. 2013). However, high rates of anthropogenically facilitated hybridization have been linked to 8 lowered reproductive success, genetic swamping of historical populations, and outright extinction (Allendorf et al. 2001; Todesco et al. 2016). Even if hybrids suffer from outbreeding depression and a lowered overall fitness, maladaptive introgression can still proliferate through spatial sorting to the detriment of one or both parent taxa (Lowe et al. 2015). Introgression is of particular concern for North American freshwater fishes due to large-scale watershed alterations and the introduction of nonindigenous species primarily from other regions of the continent (Perry et al. 2002). Populations of several salmonids have faced detrimental hybridization with congeners that have been intentionally or unintentionally stocked outside their historical range. One notable case is that of cutthroat trout (Oncorhynchus clarki), with two extinct subspecies and a number of others threatened by rainbow trout (O. mykiss) introductions (Allendorf & Leary 1988; Muhlfeld et al. 2009). Genomic extinction of the entire cutthroat species through introgression is thought to be imminent without the management of hybrid source populations (Muhlfeld et al. 2014). Through a proposed model of recurrent evolution where separate lineages evolve similar traits, O. nerka has diverged into two main polyphyletic ecotypes: (1) anadromous sockeye salmon who spawn in lakes or rivers and rear in freshwater for a period of time before migrating out to the ocean and (2) resident kokanee whose entire life history is spent in freshwater (Beacham & Withler 2017; Wood et al. 2008). Size selective mating, differing spawning times, and countergradient variation of breeding color are all thought to contribute to the continued sympatric differentiation of sockeye and kokanee (Craig et al. 2005; Hamon & Foote 2005). Despite the extensive assortative mating of the two stocks, reproductive isolation is not complete between ecotypes with hybridization reported in the wild through a theorized model of kokanee jacks that forgo the typical size-assortative territorial competition in favor of a strategy of “sneaking in” on sockeye spawners (Foote et al. 1992). However, no studies have sought to verify this mechanism of hybridization while few have examined hybrids themselves outside of laboratory and hatchery settings largely due to the lack of appropriate identifying techniques (Wood et al. 1999). Non-anadromous hybrids have been identified by their pallid mating color caused by an inefficiency at acquiring and storing carotenoid pigments (Craig et al. 2005). However, mature anadromous hybrids do not possess a similar diagnostic characteristic, but are thought to be significantly rarer since their 9 minimum length at maturation may not allow them to take full advantage of the favorable growth conditions provided by the marine environment (Wood & Foote 1996). Investigations of hybridization within the genus Oncorhynchus have supported the broader historical findings by ichthyologists on the inheritance of behavioral and morphological traits (Hubbs1955). While this hybrid intermediacy is widely reported, notable exceptions have also been documented. Kunimasu (O. kawamurae) and himemasu (O. nerka) offspring are morphologically intermediate in regards to their number of gill rakers and pyloric caeca (Nakamaya et al. 2018). Hybridized individuals of coastal cutthroat trout (O. c. clarki) and steelhead trout (O. mykiss) show intermediate values of important migration parameters such as time spent in estuaries and the extent to which their migration tracks meandered (Moore et al. 2010). The introgression in this system has been shown to be largely reciprocal with the notable exception of post-F1 hybrids that mate with the species that match their mtDNA type (Bettles et al. 2005). Within O. mykiss, lab-reared F2 progeny of anadromous steelhead trout and resident rainbow trout overwhelmingly developed in accordance with one life-history category while only 4% showed a mixed phenotype (Hecht et al. 2012). A quantitative trait locus (QTL) analysis performed in this study suggests a complex polygenic architecture controlling migration that is partially conserved between populations. Two of their main identified regions associated with migration-based traits differed from those located in a previous QTL analysis (Nichols et al. 2008) suggesting a more complicated picture where local adaptation could play a role. In order to investigate the migratory behavior of diadromous fishes, trace element analysis of the otolith, an inner ear bone, is commonly used to retrospectively determine at which points the fish resided in a freshwater or saltwater environment. The incorporation of strontium and barium into the calcium carbonate matrix of otoliths throughout an individual’s lifespan has been shown to be significantly correlated to environmental salinity (Miller 2011; Rieman et al. 1994). These elements persist transgenerationally, from mother to offspring in the otolith cores, allowing for the additional identification of maternal migratory behavior (Hegg et al. 2018; Huelga-Suarez et al. 2013). The introduction of Okanagan River anadromous sockeye salmon into Skaha Lake, British Columbia, provides an ideal case study to examine the effects of intraspecific 10 hybridization. Historically, anadromous sockeye salmon may have co-occurred in Skaha Lake with kokanee, the freshwater resident form of O. nerka, until the construction of a dam near McIntyre Bluff in 1916 (Alliance et al. 2000; Hewes 1998; Kennedy & Bouchard 1998). A planning process was initiated in 1997 to explore the possibility of establishing a sockeye salmon population in Skaha Lake (Peters et al. 1998). Following a risk assessment period, over 15 million hatchery produced anadromous sockeye salmon fry have been released into Skaha Lake since 2004 (Table 1), with the ultimate goal of creating a self-sustaining population (McQueen et al. 2017). Beginning in 2011, structural improvements were made to migration barriers to permit upstream fish passage for sockeye salmon spawners (McQueen et al. 2017). Since this modification, the previously absent age-0 sockeye salmon began to comprise a significant proportion of juvenile O. nerka in Skaha Lake (Veale & Russello 2016). Additionally, they documented a concurrent rise in sockeye – kokanee hybrids in the age-0 population over this same time period. However, the study design did not allow for comment on the biological and fitness consequences of this introgression. In this study, we use genetic and biological data collected from the Skaha Lake system to (1) quantify trends in hybridization in both the spawning and juvenile populations related to the sockeye introduction program, and (2) investigate the mating strategies resulting in hybridization and their consequent genetic, morphological and behavioral outcomes. These findings will not only assist in the continued monitoring of this stocking program, but also inform management strategies for this and related systems. 2.2 Methods 2.2.1 Sample collection Both age-0 and spawning-aged O. nerka individuals were sampled in Skaha Lake between 2013-2017. Age-0 juveniles were collected during annual trawl surveys in 2013 (n = 96) and 2015 (n = 96). The trawl survey consisted of a towing a 3 m x 7 m mid-water trawl net at various depth strata between four and eight times per sampling year. Detailed specifications of the trawl survey methods used are given in Enzenhofer & Hume (1989). The trawl survey occurred during September and October of the sampling year to ensure that both native and stocked O. nerka age-0 individuals were fully vulnerable to the sampling gear. O. nerka 11 spawners were sampled in the Okanagan River, upstream of Skaha Lake, in the fall of 2014 (n = 102), 2016 (n = 96), and 2017 (n = 222). All individuals were sampled post-mortem. Individuals were visually identified as deceased, collected, and removed from the river system during multiple sampling sessions conducted throughout the three-week duration of the spawning run in October and November in the sample year. This sampling design ensured that collected fish were representative of the entire spawning cohort for that year. All fish were measured from snout to the middle of their caudal ray fins (fork length) and had their lapilli otoliths collected for age analysis; a subset of otoliths were also used for microchemistry analysis. Age of spawning fish was defined from the time of hatch to the time of capture. Deadpitch samples were sexed based on a visual examination of the gonads. Tissue samples were collected from all individuals and stored in absolute ethanol for subsequent genetic analysis. Newly obtained morphological and genetic data were combined with previously published data from Veale & Russello (2016) for reference kokanee (n = 130) that were sampled from Skaha Lake in 2003 before hatchery sockeye were released into the system, and reference sockeye (n = 148) that originated from the brood-stock collected in 2012 and used in the stocking program. 2.2.2 Genetic analyses DNA extraction, genotyping, and assignment protocols followed Veale & Russello (2016). Using a standard Chelex-based protocol, DNA extractions were conducted in 96-well plates containing 195 µl 10% Chelex solution, 5 µl proteinase K (10 mg/ml), and an approximately 0.25 cm3 piece of tissue (Walsh et al. 1991). Plates were incubated for 4 hrs at 55°C and then 95°C for 15 min in an Applied Biosystems Veriti™ thermal cycler (Applied Biosystems, Foster City, CA, USA). All samples were genotyped at 32 single nucleotide polymorphism (SNP) loci previously used in Veale & Russello (2016) for accurately discriminating purestocks and F1 hybrids. Genotyping was performed using TaqMan™ assays in 6 µl reaction volumes: 2.5 µl TaqMan™ Universal PCR Master Mix (Life Technologies, Carlsbad, CA, USA). 0.25 µl TaqMan™ Genotyping Assay (20x), 1.25 µl ddH2O and 2 µl of 1:100 diluted extracted DNA. Reactions were performed in 384-well plates using an Applied Biosystems ViiA7™ Real-Time PCR system (Life Technologies). 12 Individuals were genetically assigned to pure stock kokanee, pure stock sockeye or hybrid using consensus results from STRUCTURE 2.3.4 (Pritchard et al. 2000) and NEWHYBRIDS (Anderson & Thompson 2002), both of which relied on reference baseline data from 2003 spawning kokanee and 2012 spawning sockeye originally collected in Veale & Russello (2016). STRUCTURE was run using the correlated allele frequency model allowing admixture, fixing the number of clusters (K) to 2, without location prior, and with a burn-in period of 1,000,000 followed by 1,000,000 iterations for the Markov Chain Monte Carlo algorithm to converge to a solution. Individuals were assigned to pure-stock or hybrid based on membership coefficients (sockeye < 0.21, hybrid 0.21–0.81, kokanee > 0.81) empirically derived in Veale & Russello (2016). For NEWHYBRIDS, three genotype frequency classes (kokanee, sockeye, and hybrid) were specified with a burn-in period of 10,000 and 50,000 iterations postburn-in. The z and s flags for individuals with known genotypes that were sampled separately were used for our reference kokanee and sockeye groups. Individuals were assigned to the class with the highest probability of assignment. 2.2.3 Age distribution and morphometric analyses One-way ANOVAs and post-hoc Tukey Tests were used to determine if the mean spawning age and mean fork length differed between stocks within sample years. To address any confounding age-related factors that could arise by looking solely at sample year, we also examined any size differences with the spawners grouped by age. 2.2.4 Microchemistry analyses Otoliths collected from O. nerka spawners were also used to determine the migratory behavior of individuals and their maternal parent. After individual spawners from 2016 and 2017 were genetically assigned to either purestock or hybrid classes, the otoliths of 104 individuals underwent microchemical analysis for signatures that indicate time spent in a marine or freshwater environment. Samples were selected to be representative of all three classes while prioritizing hybrids and individuals with high-confidence assignments (Table 4). While the focus of this analysis was to determine the migratory behavior of sockeye-kokanee hybrids and the biological mechanism of their hybridization, the cross-referencing 13 of migratory data from the purestocks to their assigned class was used to provide additional support of genetic assignments. For the microchemistry analysis, otoliths were stabilized in Buehler Epoxy-Cure 2 Resin and polished with varying grit sizes of adhesive-backed lapping papers to expose the core. Elemental analysis was conducted using Thermo X-Series 2 Quadrupole ICP-MS (Thermo Electron Corporation) coupled to a New Wave UP-213 UV laser ablation system. Migratory life history was determined based on the relative concentrations of barium and strontium across the time-series of the otolith (Miller 2011). Anadromous fish were identified as having a higher strontium concentration (generally Sr > 1500 ppm; Figure 2) at the outer edge of the otolith in comparison with barium concentration; whereas resident fish were identified with stable strontium concentrations and relatively high barium concentrations (Ba > 5 ppm; Figure 2). Similarly, maternal origin was assigned using an analysis of relative strontium and barium concentrations at the core of the otolith. 2.3 Results 2.3.1 Genetic stock assignment Individuals missing data at more than 6 SNPs (>20%) were excluded from our sample due to the uncertainty of genetically assigning individuals with so few molecular markers. These samples’ low DNA yields and inability to amplify during qPCR are likely due to tissue degradation during storage. The retained samples genotyped in this study (n = 543) had an average missing data value of 2.15% (σ = 3.81) across the 32 SNPs, with no data systematically missing (i.e. no assays failed to amplify for an entire sample year or age cohort). Genetic assignments from NEWHYBRIDS and STRUCTURE were largely consistent, with disagreement on only 23 individuals (4.2%). In these cases, STRUCTURE’s membership coefficients were close to the 0.20 or 0.80 cutoff with NEWHYBRID’s posterior probability of membership evenly split between two or more genotype frequency classes. For each of these conflicts, the sample was considered to be of an unknown class and removed from subsequent analyses. 14 Stock proportions of spawners and age-0 fish fluctuated over the sampling period (Table 2). Hybrids were identified in every sample year for both age-0 fish and spawners. In a single sample year, the composition of hybrids in the spawning cohort varied from 5% to 20% while kokanee ranged from 34% - 66% and sockeye 14% - 55% over the same time period. Age-0 fish from 2013 and 2015 showed similar trends as those reported in Veale & Russello (2016) of increasing numbers of sockeye and hybrids compared to pre-2012 levels (Figure 3).No significant deviation from expected sex ratios for each sampling year was detected within a stock based on chi-squared tests (Table 3). 2.3.2. Age distributions and morphometric analyses Unlike 2016 and 2017, we did not identify any age-2 fish among the 2014 spawners (Table 5). For this year, all stocks displayed a roughly homogenous mean spawning age of approximately 3.4 years old (Table 6). For 2016 and 2017, a wider distribution of ages were present, with purestock kokanee and sockeye exhibiting significantly different mean spawning ages (p < 0.05). In contrast, the mean spawning age of hybrids in 2016 and 2017 were similar (2.48 and 2.58 respectively), occupying an intermediate range between purestock sockeye and kokanee. Relative to the purestocks, this difference in hybrid spawner age is statistically significant for 2016 (p < 0.05), but not for 2017. The 2016 and 2017 samples appeared to be dominated by two main demographic groups: age-2 kokanee and age-3 sockeye (Table 5). The age-2 kokanee comprised 58.2% of the 2016 sample, while the age-2 kokanee (23%) and age-3 sockeye (40.4%) were the large majority of the 2017 sample. Sockeye males were found to have a much wider distribution of spawner lengths than females, while kokanee and hybrid lengths were similar between sexes (Figure 4). Across sampling years, sockeye have consistently larger mean lengths compared with kokanee (p < 0.05; Figure 5). Hybrids generally occupy a statistically significant intermediate range between the two purestocks with the exception of 2014 (hybrid-kokanee; p = 0.811, hybrid-sockeye; p = 0.175) and 2017 in regards to kokanee (p = 0.073). The size distributions of each sample year are largely consistent with the data subdivided by age across the three sampling years (Figure 6). Comparisons of sockeye and hybrid mean length at age-2 and age-3 showed highly significant differences (p < 0.05), while age-4 showed somewhat more overlap (p = 0.086). Despite having similar size 15 distributions at age-2, the mean size of hybrids and kokanee begins to differentiate at age-3 and age-4 (p = 0.031 and p = 0.009 respectively). 2.3.3 Microchemistry analyses For the microchemistry analysis, we selected individuals from all three stocks in 2016 and 2017 for a total of 104 fish (Table 4). The migration behavior and maternal ancestry inferred from microchemistry analyses were highly congruent with genetic assignment of purestocks (>97%), with only two instances of conflict. One sockeye in 2016 was found to be non-anadromous with a resident maternal parent, while another sockeye in 2017 had a resident maternal parent, but was anadromous. All genetically assigned kokanee samples were non-anadromous with resident maternal parents. Interestingly, the vast majority of hybrids were found to be non-anadromous (92%), with most having a resident maternal parent (76%) (Table 4). 2.4 Discussion Our results show that sockeye - kokanee hybrids comprise a considerable proportion (5 – 20%) of age-0 fish in Skaha Lake and survive to a reproductive age in significant numbers. These hybrids spawn at an intermediate age in comparison with the purestocks and have a roughly average fork length. Spawning hybrids are almost entirely non-anadromous with largely resident maternal parents. Additionally, the migratory behavior of identified purestocks determined by otolith microchemistry analysis is consistent with our genetic assignments. The proportions of all stocks of spawners varied significantly throughout the sampling period, particularly for purestocks. Beginning in 2013, age-0 sockeye either equaled or substantially exceeded the proportion of kokanee in the lake for the first time since records have been compiled in this system. The increase in proportions of age-0 sockeye starting in 2012 does not strongly correspond with the number of fry released into the lakes earlier those same years, but does coincide with fish passage for anadromous migrants. With almost no fish stocked in the lake from 2012 – 2014, age-0 sockeye varied from 28% to 67% of the population. The one exception was 2015, when the largest release of 16 fry at the time (1.7 million fish) was followed by the highest recorded composition of age-0 sockeye (78%). The impacts of 4.5 million fry released into Skaha Lake in 2017 on stock proportions remain to be assessed. The composition of age-0 hybrids in Skaha Lake has remained fairly stable (approximately 12% of population) since their first detection in 2012. However, with a sampling period of less than two generations of hybrids, it remains unclear if this stability will continue. Overall, given the numerous factors influencing returns of spawning fish, it is difficult to resolve any trends from the limited period of time examined in this study underscoring the need for continued monitoring in this system. There are numerous environmental, individual-, and population-level factors that influence O. nerka’s variable size and age of maturation (Braun et al. 2014; Freshwater et al. 2016). However, the separate energy investments of smolting and maturation are thought to contribute towards a generally later spawning age of anadromous individuals (Thorpe & Kingdom 1987). Additionally, the nutrient-rich ocean environment allows anadromous individuals to reach a significantly larger size than their resident counterparts (Wood & Foote 1996). Despite sharing kokanee’s resident behavior and habitat, hybrids were found to spawn at a later age and have a significantly larger size for age-3 and age-4 individuals. The intermediacy of these traits suggests a genetic component to maturation age and growth that is inherited from both parents. Interestingly, the three anadromous hybrid individuals in our sample were all age-4 and placed in the longer end of the length distribution (467 – 501 mm). While this is ultimately too small of a cohort to make any overarching conclusions from, it is consistent with environmental factors contributing towards growth and maturation alongside genetics. Alternatively, mortality associated with migration could be acting as a filter where smaller and younger individuals are unable to complete the journey to and from the ocean and are therefore absent from our sample. Of the 37 hybrids sampled in 2016 and 2017, 92% were determined to be non-anadromous. The significant imbalance of anadromous and non-anadromous fish could be due to a number of reasons. One possibility is that anadromous hybrids who undertake the long migration out to the marine environment may exhibit high mortality of due to their smaller size as previously hypothesized by Wood & Foote (1996). Another is that hybrids simply have a predisposition towards a non-anadromous life history. This biased inheritance 17 of migratory strategies is not unprecedented in salmonids. While displaying the inverse of our findings, approximately three quarters of steelhead and rainbow F2 hybrids reared in the lab developed quantitative traits associated with migration during smoltification (Hecht et al. 2012). However, it is unknown whether the development of these traits definitively results in migratory behavior. As is often the case in natural systems, these two processes could also be working in tandem to produce the observed imbalance of migrants. It is worth noting that hybrids were not fully prevented from migrating to and returning from the ocean, with approximately 8% of our sample showing time spent in a marine environment. We found that hybrids were largely the result of a resident mother mating with a presumably anadromous male fish. Previously, two biological mechanisms of hybridization for O. nerka have been proposed: 1) size selective mating, where smaller male sockeye would overlap with larger female kokanee (Craig et al. 2005); or 2) “sneaker” mating of smaller kokanee males with sockeye females (Wood & Foote 1996). Our results are consistent with the hypothesis of size selective mating with less frequent occurrences of kokanee males “sneaking” on sockeye spawners. With male sockeye having a particularly wide distribution of lengths, the smaller individuals are likely to seek out hybrids or kokanee as mates. This mechanism of hybridization implicates hybrids’ intermediate size at maturation as a possible contributor towards continued inter-breeding. Acting as bridge between the two differentiated phenotypes of sockeye and kokanee, hybrids could facilitate and perpetuate introgression. The two genetically assigned sockeye with non-anadromous maternal parents also raise the possibility of residualization in this system. This phenomenon has been documented in other populations of sockeye salmon in British Columbia, including in Cultus Lake, where residualized fish make up ~5% of the sockeye population, consistent with the proportions we observed in Skaha Lake (Vinebrooke et al. 2009). The congruence of genetic purestocks and migratory life history determined by otolith microchemistry lends a degree of confidence to our assignments. The use of genetic markers and microchemistry data in tandem has been previously applied to the characterization and monitoring of fish stocks (see Barnett-Johnson et al. 2010; Martin et al. 2015). Our work underscores the utility of this combination; not only as independent streams of data, but as a means of assessing the accuracy of each source. 18 While hybridization is often documented in cases of introduced species, the Skaha Lake system is relatively unique as it involves the reintroduction of a formerly native stock and dissolution of natural reproductive barriers separating ecotypes. The rates of sockeye and kokanee hybridization have not previously been recorded in “natural” systems, but the sympatric divergence of these ecotypes implies some level of restricted gene flow. Although hybridization can lead to an increase in genetic diversity, there have been no studies investigating whether Skaha Lake kokanee are impacted by inbreeding depression or require genetic rescue. One particular concern for these fish is the loss or fragmentation of genes adapted to a migratory or resident life history that could impair fitness. The fitness of hybridized individuals is an important factor to consider for the future management of the Skaha Lake system. By incorporating abundance counts of age-0 juveniles and spawners collected annually, a stage-structured assessment model could be constructed to estimate hybrid survival while factoring in spawning at different ages (e.g. Cunningham et al. 2018). While maladapted introgression can still spread throughout populations, the temporal response window and success of management intervention are more favorable when hybrids are not outcompeting purestocks (Lowe et al. 2015). If hybrids continue to self-perpetuate, the creation of spawning habitats tailored towards purestocks could be useful in introducing some reproductive isolation. Kokanee generally spawn in gravel with finer particles and a narrower range of variation since they produce uniformly smaller and less variable eggs than sockeye (McGurk 2000; Wood & Foote 1996). As reintroduction programs are increasingly implemented, genetic monitoring and investigations into the multifaceted implications of hybridization allow managers to assess the possible impacts on native stocks. With less than a decade of genetic data, continued monitoring is necessary to determine management strategies going forward. 19 Chapter 3: SNP panels for differentiating advanced-generation hybrid classes in recently diverged stocks: a sensitivity analysis to inform monitoring of sockeye salmon re-stocking programs 3.1 Background The predicted collapse of marine fisheries has garnered wide attention (Costello et al. 2016; Worm et al. 2006). Although less publicized, freshwater fisheries worldwide are threatened with a similar fate due largely to anthropogenic factors such as exotic species introductions, dam operations, spawning habitat destruction, altered nutrient inputs, and climate change (Darwall & Freyhof 2015; Post et al. 2002). In tandem with reducing the impacts leading to decline, re-stocking initiatives have been increasingly employed for stock reintroduction and/or reinforcement (Cochran-Biederman et al. 2015). In cases where reproductively compatible native stocks exist, there is a need to monitor the impacts of genetic consequences such as hybridization and introgression (Cordes et al. 2006; Savary et al. 2017). Such assessments can be particularly challenging in cases where populations are genetically similar, but ecologically divergent (Veale & Russello 2016). Genetic tools, primarily microsatellites, have been employed for monitoring re-stocking programs for decades (Ward 2000). These approaches can be effective in systems in the early stages of introgression, providing management relevant accuracy for distinguishing pure stocks and F1 hybrids. However, as re-stocking programs mature, limited numbers of traditional genetic markers may be ineffective at distinguishing more advanced introgression classes, such as in the case of backcrosses and F2 hybrids (Vaha & Primmer 2004). The detection of these classes is important for evaluating the fitness of hybridized individuals as well as the direction of introgression in the population. Genome-wide single nucleotide polymorphisms (SNPs) can allow for more accurate assessment of introgressive hybridization than traditional molecular markers (Twyford & Ennos 2012). However, there remains a need to evaluate the number of markers relative to their information content to sufficiently and cost-effectively assign individuals to advanced introgression classes, especially in cases where native and re-introduced stocks have only recently diverged. The reintroduction of Okanagan River anadromous sockeye salmon into Skaha Lake, British Columbia, provides such a case study (Figure 1). Historically, anadromous sockeye 20 salmon co-occurred in Skaha Lake with kokanee, the freshwater resident form of O. nerka, until the construction of a dam near McIntyre Bluff in 1916 (Figure 1; Alliance et al. 2000; Hewes 1998; Kennedy & Bouchard 1998). A planning process was initiated in 1997 to explore the possibility of bringing anadromous sockeye salmon to Skaha Lake. Following a risk assessment period, over 15 million hatchery produced anadromous sockeye salmon fry have been released into Skaha Lake from 2004 to 2017 (Table 1), with the ultimate goal of creating a self-sustaining population (McQueen et al. 2017). Beginning in 2011, structural improvements were made to migration barriers to permit upstream fish passage for sockeye salmon spawners (McQueen et al. 2017). Genetic monitoring throughout the reintroduction has shown a sharply rising number of returning anadromous sockeye and F1 age-0 hybrids beginning in 2012 (Figure 3; Veale & Russello 2016). The custom 32 SNP panel used in Veale & Russello (2016) was sufficient for distinguishing F1 hybrids from pure anadromous sockeye and resident kokanee, but rapidly lost resolution with more advanced introgression classes. As the program matures, the ability to genetically identify first- and second-generation backcrosses is essential to the on-going monitoring of these populations, particularly for obtaining a fuller understanding of any fitness implications to resident kokanee. Here, we conducted a simulation-based study using SNP genotypic data collected from Okanagan River sockeye salmon and Skaha Lake kokanee sampled pre-sockeye reintroduction to evaluate the accuracy and power of varying subsets of the data to assign individuals to advanced-generation hybrid classes. Using empirical data at 7,347 SNPs previously collected from the reference populations (Veale & Russello 2017), we simulated six introgression classes (F1, F2, B2-anadromous backcross, B2-kokanee backcross, B3-anadromous backcross, B3-kokanee backcross) using eight different SNP datasets that varied in marker number and information content [100 random, 100 highest Fst, 300 random, 300 highest Fst, 1000 random, 1000 highest Fst, outliers, all non-outliers]. We further evaluated the performance of two independent assignment methods for distinguishing individuals from each of the introgression classes using the various SNP panels. We discuss the implications of the results for monitoring the Skaha Lake anadromous sockeye stocking program into the future, as well as for other such initiatives involving recently diverged stocks of management concern. 21 3.2 Methods We used previously published genotypic data at 7,347 SNPs for Okanagan River sockeye salmon (n = 35) and Skaha Lake kokanee (n = 20), collected as part of a landscape genomic study of anadromous sockeye and kokanee across multiple catchment areas in British Columbia (Veale & Russello 2017). Skaha Lake kokanee were originally sampled in 2003, prior to the commencement of the anadromous sockeye restocking program, while Okanagan River anadromous sockeye were collected in 2012 (Veale & Russello 2016). Outlier loci, which exhibit locus-specific behavior or patterns of variation that are extremely divergent from the rest of the genome (Luikart et al. 2003), were detected between Skaha Lake kokanee and Okanagan River anadromous sockeye using the Fst-based approach implemented in BAYESCAN (Foll & Gaggiotti 2008). Significance levels were adjusted for multiple comparisons using a 5% false discovery rate and the method of Benjamini & Yekutieli (2001). Genotypic disequilibrium was tested for all pairs of loci using GENEPOP 4.5 (Raymond & Rousset 1995). Loci that significantly deviated from linkage equilibrium in both populations were removed. Due to the recent salmonid whole genome duplication event, homeologs were filtered out by Hobs and Fis (Hohenlohe et al. 2011). Any locus with a negative Fis or Hobs > 0.5 occurring in both reference populations was also removed. From this cleaned dataset, locus-specific Fst between parental stocks was calculated using VCFTOOLS (Danecek et al. 2011). Based on these results, eight datasets were partitioned including: 1) 100 random SNPs; 2) 100 highest Fst SNPs; 3) 300 random SNPs; 4) 300 highest Fst SNPs; 5) 1000 random SNPs; 6) 1000 highest Fst SNPs; 7) outlier loci only; 8) all non-outlier SNPs. Outlier SNPs were only included in panel 7. Offspring (n = 1000) from each of six introgression classes (F1, F2, B2 backcross-sockeye, B2 backcross-kokanee, B3 backcross-sockeye, B3 backcross-kokanee) were simulated independently for each of the six datasets using a custom Python script (accessible at https://github.com/salanova-elliott/recom-sim) based on HYBRIDLAB 1.0 (Nielsen et al. 2006). Assignment of simulated individuals to parental or various hybrid stocks was assessed using two different measures. First, we estimated admixture coefficients using the non-negative matrix factorization (sNMF) algorithm implemented in Landscape and Ecological Association studies R package (LEA), fixing the number of putative populations (K) at 2 (Frichot & François 2015). Admixture cut-off points were determined separately for each 22 panel by calculating the intersections of their density plots (Figure 8). Second, we calculated the posterior probabilities of hybrid category membership using NEWHYBRIDS. As NEWHYBRIDS was experiencing underflow errors with larger datasets, the full non-outlier SNP dataset was not examined with this method. The other seven panels were tested with 80 individuals per run: 20 of each reference population (indicated as known genotypes with the “z” option) and 10 of each introgression class. This process was repeated 100 times with unique simulated individuals for each run. From these analyses, we constructed confusion matrices for each panel size to investigate the level of correct self-assignment to ancestry class as well as the rates of misassignment. Confusion matrices display the accuracy of a classification model by measuring how many samples of known origin were correctly or incorrectly assigned. Individuals were placed into the ancestry class with the highest probability of membership according to a strict maximum likelihood criterion. 3.3 Results After filtering for suspected homeologs, linkage, and monomorphic loci, a total of 6,339 SNPs were retained. Twenty-three outliers were detected between Skaha Lake kokanee and Okanagan River anadromous sockeye using BAYESCAN, consistent with the findings of Veale & Russello (2017). The final SNP panels included: 1) 100 random (mean Fst = 0.073); 2) 100 highest Fst (mean Fst = 0.395); 3) 300 random (mean Fst = 0.074); 4) 300 highest Fst (mean Fst = 0.328); 5) 1000 random (mean Fst = 0.076); 6) 1000 highest Fst (mean Fst = 0.205); 7) 23 outlier loci (mean Fst = 0.625); 8) 6,326 non-outlier SNPs (mean Fst = 0.077). The different SNP panels provided variable accuracy and power to assign individuals to different introgression classes, with results improving with marker number, level of differentiation, and choice of algorithm. For LEA, the plotted distributions of admixture coefficients revealed little to no overlap across all introgression classes for the 6,326 non-outlier SNP panel (Figure 7A). Regarding panels that included only a subset of SNPs (Figure 7B-H), the 300 highest Fst and 1000 highest Fst panels performed best, discriminating all introgression classes through B2 backcross with high accuracy (>0.99), and only beginning to lose resolution when differentiating B2 from B3 backcrosses, and B3 backcrosses from corresponding parental stock (data not shown). In contrast, the 100 random SNP and 23 outlier loci panels revealed poor assignment accuracy, unable to even reliably discriminate 23 F1’s from pure stock. Consistent patterns were reconstructed when examining self-assignment using the confusion matrices, with >0.99 accuracy achieved for the 300 highest Fst and 1000 highest Fst panels for parental, F1 and B2-backcrosses (Table 7). All other SNP panels revealed deficiencies, even for F1 assignment. For example, the 1000 random SNP panel failed to achieve high assignment accuracy to F1 (0.944), while the 100 highest Fst SNP panel only managed moderate accuracy at this level (0.897; Table 7). These patterns were generally reflected in the posterior probabilities of correct assignment for each simulated individual as estimated in NEWHYBRIDS (Table 8). Based on the 300 highest Fst and 1000 highest Fst datasets, near perfect assignments for every introgression class, including F2, were achieved (>0.99; Table 8A & 8C). This was the case even for discriminating B2 from B3 backcrosses, with NEWHYBRIDS outperforming LEA in most scenarios (data not shown). Assignment accuracies also substantially improved when examining the 100 highest Fst panel over those generated from LEA, assigning individuals with >0.96 at the F1 and B2-backcross levels (Table 8). 3.4 Discussion Genetic monitoring is fundamental for critically evaluating the performance of re-stocking initiatives, especially in terms of meeting program goals of stock re-establishment and/or reinforcement while minimizing impacts to native stocks. The identification of hybridized individuals is often not possible without the use of molecular markers. Genomic tools now provide opportunities for extending the feasibility of such monitoring as programs mature and in systems where stocks have recently diverged and hybridization is on-going. Here, we have demonstrated the importance of marker number, information content and assignment algorithm in designing an efficient and cost-effective SNP panel for assigning individuals to advanced introgression classes, using as a case study the anadromous sockeye salmon restocking program in Skaha Lake, British Columbia that has spanned over a decade. Regarding SNP panel composition, it was not entirely surprising that the largest marker panel (6,326 non-outlier SNPs) provided the greatest assignment accuracy across all introgression classes. As the costs of developing and screening such a large number of SNPs is not presently feasible for the vast majority of fisheries management programs, research 24 continues to focus on maximizing information content while minimizing marker number in the development of cost-effective marker panels (Lemay & Russello 2015; Pritchard e et al. 2016). For example, the use of outlier loci has become well-established for providing accurate and cost-effective molecular markers for informing genetics-based fisheries management (Freamo et al. 2011; Pritchard et al. 2016; Russello et al. 2012). However, although high Fst outliers have been useful for assigning individuals to divergent stocks, they may be less effective over time for detecting hybridization and quantifying introgression depending upon the mode and strength of selection. In our case, the outlier-only panel was not effective for discriminating pure stocks from any introgression class, likely due to the small number of biallelic markers (n = 23 SNPs) that were less than half of what has been previously recommended for distinguishing hybrids (Fitzpatrick 2012). For the other panels that included only a subset of SNPs, as marker number increased, so did assignment accuracies as would be expected (Figure 7; Table 7). Yet, only when preferentially using the highest Fst SNPs were management relevant assignment accuracies achieved, the number of which varied by assignment algorithm. In this system, the 100 highest Fst panel was able to assign F1 and B2-backcrosses with moderate to high accuracy, while the 300 highest Fst and 1000 highest Fst panels achieved up to >0.99 across all introgression classes tested regardless of algorithm used (Table 7 & 8). In addition to marker number and information content, we found a high degree of variation in assignment accuracies achieved by the two algorithms tested. Specifically, the more conventionally used NEWHYBRIDS substantially outperformed LEA, similar to the findings of Marie et al. (2011) when comparing the performance of the former relative to STRUCTURE for assigning individuals to different introgression classes. The main advantage of LEA lies in the number of loci and individuals it can efficiently process at one time, both important considerations as our ability to cost-effectively genotype large numbers of SNPs increases. In fact, LEA was able to complete analyses of the 6,326 non-outlier SNP dataset 1500X faster than NEWHYBRIDS processed the 100 SNP datasets (data not shown). However, this gain in analytical capacity and efficiency comes with the tradeoff of less predictive power across all panels that used only a subset of the markers, with accuracy falling dramatically with SNP number (Table 7). The only exception was for the full non-outlier dataset (6,326 SNPs), which NEWHYBRIDS and another conventionally used 25 assignment software, ONCOR (Kalinowski et al. 2007), were unable to process (data not shown). This finding is perhaps moot, given that the underlying model in NEWHBRIDS is not appropriate when using a large number of physically linked loci (Anderson, E. personal communication 2017). Despite the dataset size limitations of NEWHYBRIDS, the resulting assignments were considerably more accurate than the corresponding results from LEA, using even as few as 100 SNPs to accurately assign individuals through the B2 generation (>0.98; Table 7). Another advantage of NEWHYBRIDS is the ability to distinguish F2 hybrids (F1 x F1) by factoring in proportions of homozygous and heterozygous loci, which is not possible using LEA. In our case, accurate F2 assignment was achieved (>0.94) using as few as the 100 highest Fst panel (Table 8). In summary, development of cost-effective SNP panels for monitoring introgressive hybridization associated with re-stocking programs and other fisheries management applications requires a balance between marker number and information content, in tandem with careful consideration of appropriate assignment algorithm. Panel size and composition will vary according to the characteristics of the system of interest, including but not limited to the level of divergence of parental stocks and duration of the program since inception. Given the need for case-by-case assessments when it comes to detecting hybridization and the extent of introgression (Allendorf et al. 2001), we recommend conducting simulation-based analyses as shown here for optimizing SNP panels and analytical workflow for a given system and management question prior to commencing genetic monitoring. Based on our results, the 300 highest Fst SNP panel should provide sufficient resolution for monitoring of introgressive hybridization trends between anadromous sockeye and resident kokanee in Skaha Lake over the coming decade. This panel size is further optimal for analyzing management-relevant numbers of individuals accurately and cost-effectively using genotyping-in-thousands by sequencing (GT-Seq: Campbell et al. 2015) and other such approaches that make use of high-throughput DNA sequencing platforms. 26 Chapter 4: Conclusion 4.1 Research findings and significance As management programs enacted with the intent of introducing or re-introducing extirpated stocks are increasingly employed, there is a need to monitor their implementation along with any unintended impacts on the ecosystem and co-occurring native taxa. Here, we focused on an anadromous sockeye salmon stocking program in Skaha Lake and the subsequent hybridization with native kokanee. By using genetic markers to identify hybrid and purestock individuals, we were able to describe some of the morphological, behavioral, and genetic consequences of sockeye – kokanee hybridization and introgression. One possible outcome of the reported hybridization of these two ecotypes is the potential for genetic or demographic swamping adversely impacting the native kokanee population. The possibility of extinction through one of these processes is largely context dependent and needs to be evaluated on a case-by-case basis, however heightened propagule pressure and habitat disturbance have been generally identified as two significant risk factors (Todesco et al. 2016). The continued stocking of sockeye fry into Skaha Lake along with the channelization of their historic spawning stream place the Skaha Lake system at an increased risk of increased hybridization in the future. Alternatively, hybridization may lead towards positive demographic outcomes. Resident O. nerka in Skaha Lake support a regionally-significant recreational fishery which values large fish sizes. Due to hybrids’ resident life history and intermediate size, hybridization may lead to an overall increase in the size of resident O. nerka subsequently improving angling quality and survivability (Henderson & Cass 1991; Parkinson et al. 2004). Additionally, the mixing of these stocks could result in an increase of genetic diversity improving fitness. However, there is no existing data suggesting that Skaha Lake kokanee are impacted by inbreeding depression or require genetic rescue through hybridization with sockeye. Through the three years of spawner sampling, sockeye composed a significant proportion of the population in Penticton Channel signaling progress towards re-establishment. Additionally, these proportions showed that hybrids have been surviving to a 27 reproductive age in appreciable numbers. Whether these fish are producing viable offspring remains to be documented, but the detection of constant proportions of age-0 hybrids suggest these fish will continue to be present in this system into the future. Consistent with morphological intermediacy previously reported (Wood & Foote 1996; Veale & Russello 2016), hybrids showed an average spawning age and length at maturation. In assessing the risk of directional introgression and continued hybridization, hybrid length at maturation is of particular interest since sockeye and kokanee mate assortatively by size (Foote 1987). Previous to this study, the migratory behavior of sockeye – kokanee hybrids in the wild had not been documented. Otolith microchemistry analysis revealed spawning-aged hybrids are almost entirely non-anadromous with largely resident maternal parents. Previously, two biological mechanisms of hybridization for O. nerka have been proposed: 1) size selective mating, where smaller male sockeye would overlap with larger female kokanee (Craig et al. 2005); or 2) “sneaker” mating of smaller kokanee males with sockeye females (Wood & Foote 1996). Our results are consistent with the hypothesis of size selective mating with less frequent occurrences of kokanee males “sneaking” on sockeye spawners. With male sockeye having a particularly wide distribution of lengths, the smaller individuals are likely to seek out hybrids or kokanee as mates. This mechanism of hybridization implicates the intermediate size of hybrids at maturation as a possible contributor towards continued inter-breeding. Acting as bridge between the two differentiated phenotypes of sockeye and kokanee, hybrids could facilitate and perpetuate introgression. 4.2 Limitations and future studies One aspect of this study that separates it from many others is the taxonomic level of hybridizing populations (ecotypes in this case rather than congeners). Some previous authors have called into question the detrimental possibilities of intraspecific hybridization since populations of the same species generally share most alleles (Cuenco et al. 1993). Indeed, non-anadromous kokanee show similar seawater adaptability cycles to that of sockeye salmon suggesting more genetic similarity than their divergent life histories would otherwise imply (Foote et al. 1994). However, the mixing of these stocks could still result in the loss of adapted traits through many small allele frequency shifts throughout the genome (Allendorf 28 et al. 2001). Similar precautionary action should be taken in cases of intraspecific hybridization, particularly those featuring populations with highly divergent life histories, as with their interspecific counterparts. The fitness of hybridized individuals is an important factor to consider for the future management of the Skaha Lake system. By incorporating abundance counts of age-0 juveniles and spawners collected annually, a stage-structured assessment model could be constructed to estimate hybrid survival while factoring in spawning at different ages (e.g. Cunningham et al. 2018). Ideally this model would include the complete spawning cohorts across multiple years (i.e. age-2, age-3, and age-4 spawners from the same brood year) to provide a comprehensive picture of O. nerka spawning trends, data which is not fully present in our study. The absence of these data highlights the need for continued monitoring of the Skaha Lake system into the future. The predominance of non-anadromous individuals detected in spawning-aged hybrids could be due to a number of reasons. One possibility is that anadromous hybrids who undertake the long migration out to the marine environment may exhibit high mortality due to their smaller size as previously hypothesized by Wood & Foote (1996). Another is that hybrids simply have a predisposition towards one life history as previously documented in the case of O. mykiss (Hecht et al. 2012). Future studies could address these theories in multiple ways. One possibility is the tagging of age-0 fish with passive-integrated transponders (PIT-tags) and collecting corresponding tissue samples. Migrants could later be identified as they are leaving the lake system with stationary receivers and cross-referenced against their genetic assignments to detect the presence of ocean-bound hybrids (see Fukuwaka & Kaeriyama 1997; Warren & Morbey 2012 for examples of PIT-tag use in O. nerka). A small number of migrating hybrids would be anticipated since a minority of spawning-aged hybrids were found to be anadromous, but any significant numbers would support the seaward migrant mortality hypothesis. The 32 single nucleotide polymorphism panel used in our study for genetic assignment was sufficient for distinguishing F1 hybrids from pure anadromous sockeye and resident kokanee, but rapidly lost resolution with more advanced introgression classes. As the program matures, the ability to genetically identify first- and second-generation backcrosses 29 is essential to the on-going monitoring of these populations, particularly for obtaining a fuller understanding of any fitness implications to resident kokanee. Without the ability to identify these fish, assessing the reproductive viability of hybrids or any directional introgression would be very challenging. The 300 highest Fst SNP panel we developed should provide sufficient resolution for monitoring of introgressive hybridization trends between anadromous sockeye and resident kokanee in Skaha Lake over the coming decade. The detection of these classes would help address the reproductive viability of these hybrids in a natural setting. While the absence of backcrosses and F2 hybrids would preclude genetic swamping from occurring in this system, the wasted reproductive effort of kokanee could still result in below replacement levels and the shrinking of the population. 30 Table 1. Numbers of age-0 hatchery sockeye released into Skaha Lake between 2004 and 2017. In-Lake Year Number of Hatchery Sockeye Released 2004 352,500 2005 1,205,500 2006 1,384,000 2007 1,479,000 2008 885,500 2009 1,614,300 2010 448,300 2011 900,000 2012 6,000 2013 6,000 2014 0 2015 1,761,798 2016 362,000 2017 4,493,577 Table 2. Stock composition of spawners and juvenile (age-0) fish by year. Sample Year Kokanee (%) Hybrid (%) Sockeye (%) Spawners 2017 34 11 55 2016 66 20 14 2014 48 5 47 Juveniles 2015 12 10 78 2014 44 15 41 2013 24 9 67 2012 61 11 28 2010 98 2 0 2008 97 3 1 31 Table 3. Observed proportions of female spawners compared to expected proportions based on whole sample year. Pearson’s chi-squared test results included. Sample year Expected proportion of females Kokanee Hybrid Sockeye 2017 0.538 0.516 0.500 0.564 Χ2 = 0.119, p = 0.730 Χ2 = 0.116, p = 0.733 Χ2 = 0.282, p = 0.595 2016 0.505 0.533 0.44 0.461 Χ2 = 0.193, p = 0.661 Χ2 = 0.264, p = 0.607 Χ2 = 0.098, p = 0.754 2014 0.564 0.500 1.000 0.586 Χ2 = 0.499, p = 0.480 Χ2 = 2.357, p = 0.125 Χ2 = 0.058, p = 0.809 Table 4. Otolith microchemistry analysis results. Sample year Assignment Sample size Proportion anadromous Proportion maternal anadromous 2017 Kokanee 20 0.00 (n = 0) 0.00 (n = 0) 2017 Hybrid 19 0.05 (n = 1) 0.26 (n = 5) 2017 Sockeye 20 1.00 (n = 20) 0.95 (n = 19) 2016 Kokanee 16 0.00 (n = 0) 0.00 (n = 0) 2016 Hybrid 18 0.11 (n = 2) 0.22 (n = 4) 2016 Sockeye 11 0.91 (n = 10) 0.91 (n = 10) Table 5. Number of fish assigned to each genetic category by sample year and their age determined by otolith analysis. Genetic 2014 2016 2017 Assignment Age 2 Age 3 Age 4 Age 2 Age 3 Age 4 Age 2 Age 3 Age 4 Kokanee 0 18 12 52 6 2 42 17 3 Hybrid 0 2 1 11 3 4 10 7 3 Sockeye 0 17 12 2 5 6 22 74 5 Table 6. Average spawning age in years of all genetically assigned fish. Genetic assignment 2014 2016 2017 Kokanee 3.40 2.17 2.37 Hybrid 3.33 2.48 2.58 Sockeye 3.41 3.31 2.83 32 Table 7. Confusion matrices of simulated individuals’ proportional assignment using LEA’s admixture coefficient. Rows show known introgression class and columns are the assigned class with highlighted values corresponding to correct assignment proportions. A. All 6,326 Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 1.000 0.000 0.000 0.000 0.000 Sockeye 0.000 1.000 0.000 0.000 0.000 F1 Hybrid 0.000 0.000 1.000 0.000 0.000 B2 Kokanee 0.000 0.000 0.000 1.000 0.000 B2 Sockeye 0.000 0.000 0.000 0.000 1.000 B. 1000 Fst Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 1.000 0.000 0.000 0.000 0.000 Sockeye 0.000 1.000 0.000 0.000 0.000 F1 Hybrid 0.000 0.000 1.000 0.000 0.000 B2 Kokanee 0.000 0.000 0.000 1.000 0.000 B2 Sockeye 0.000 0.000 0.000 0.000 1.000 C. 1000 Random Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.990 0.000 0.000 0.010 0.000 Sockeye 0.000 0.993 0.000 0.000 0.008 F1 Hybrid 0.000 0.000 0.944 0.037 0.019 B2 Kokanee 0.016 0.000 0.002 0.982 0.000 B2 Sockeye 0.000 0.012 0.016 0.000 0.972 D. 300 Fst Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 1.000 0.000 0.000 0.000 0.000 Sockeye 0.000 1.000 0.000 0.000 0.000 F1 Hybrid 0.000 0.000 1.000 0.000 0.000 B2 Kokanee 0.000 0.000 0.003 0.997 0.000 B2 Sockeye 0.000 0.000 0.001 0.000 0.999 E. 300 Random Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.896 0.000 0.000 0.104 0.000 Sockeye 0.000 0.889 0.000 0.000 0.111 F1 Hybrid 0.000 0.000 0.714 0.127 0.159 B2 Kokanee 0.100 0.000 0.096 0.802 0.002 B2 Sockeye 0.000 0.141 0.157 0.000 0.702 F. 100 Fst Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.991 0.000 0.000 0.009 0.000 Sockeye 0.000 1.000 0.000 0.000 0.000 F1 Hybrid 0.000 0.000 0.897 0.065 0.038 B2 Kokanee 0.069 0.000 0.031 0.900 0.000 B2 Sockeye 0.000 0.145 0.014 0.000 0.841 G. 100 Random Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.868 0.000 0.012 0.120 0.000 Sockeye 0.000 0.795 0.009 0.000 0.196 F1 Hybrid 0.025 0.015 0.533 0.163 0.264 B2 Kokanee 0.312 0.000 0.266 0.414 0.008 B2 Sockeye 0.000 0.233 0.191 0.010 0.566 H. 23 Outliers Kokanee Sockeye F1 Hybrid B2 Kokanee B2 Sockeye Kokanee 1.000 0.000 0.000 0.000 0.000 Sockeye 0.000 0.996 0.000 0.000 0.004 F1 Hybrid 0.015 0.090 0.609 0.120 0.166 B2 Kokanee 0.682 0.000 0.089 0.229 0.000 B2 Sockeye 0.000 0.679 0.129 0.002 0.190 33 Table 8. Confusion matrices of simulated individuals’ proportional assignment using NEWHYBRIDS. Rows show known introgression class and columns are the assigned class with highlighted values corresponding to correct assignment proportions. A. 1000 Fst Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 1.000 0.000 0.000 0.000 0.000 0.000 Sockeye 0.000 1.000 0.000 0.000 0.000 0.000 F1 Hybrid 0.000 0.000 0.992 0.008 0.000 0.000 F2 Hybrid 0.000 0.000 0.003 0.997 0.000 0.000 B2 Kokanee 0.000 0.000 0.000 0.000 1.000 0.000 B2 Sockeye 0.000 0.000 0.000 0.000 0.000 1.000 B. 1000 Random Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.984 0.000 0.000 0.000 0.016 0.000 Sockeye 0.000 0.977 0.000 0.000 0.000 0.023 F1 Hybrid 0.000 0.000 0.890 0.076 0.025 0.009 F2 Hybrid 0.000 0.000 0.068 0.900 0.026 0.006 B2 Kokanee 0.000 0.000 0.004 0.039 0.957 0.000 B2 Sockeye 0.000 0.000 0.010 0.044 0.000 0.946 C. 300 Fst Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 1.000 0.000 0.000 0.000 0.000 0.000 Sockeye 0.000 1.000 0.000 0.000 0.000 0.000 F1 Hybrid 0.000 0.000 0.995 0.005 0.000 0.000 F2 Hybrid 0.000 0.000 0.002 0.998 0.000 0.000 B2 Kokanee 0.000 0.000 0.000 0.000 1.000 0.000 B2 Sockeye 0.000 0.000 0.000 0.001 0.000 0.999 D. 300 Random Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.860 0.000 0.000 0.000 0.140 0.000 Sockeye 0.000 0.819 0.000 0.000 0.000 0.181 F1 Hybrid 0.000 0.000 0.564 0.264 0.145 0.027 F2 Hybrid 0.000 0.000 0.144 0.646 0.157 0.053 B2 Kokanee 0.010 0.000 0.020 0.373 0.597 0.002 B2 Sockeye 0.000 0.007 0.075 0.424 0.000 0.494 E. 100 Fst Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.913 0.000 0.000 0.000 0.087 0.000 Sockeye 0.000 0.935 0.000 0.000 0.000 0.065 F1 Hybrid 0.000 0.000 0.960 0.036 0.004 0.038 F2 Hybrid 0.000 0.000 0.030 0.946 0.009 0.015 B2 Kokanee 0.000 0.000 0.000 0.012 0.988 0.000 B2 Sockeye 0.000 0.000 0.002 0.008 0.000 0.990 F. 100 Random Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.731 0.000 0.003 0.037 0.229 0.000 Sockeye 0.000 0.635 0.037 0.190 0.138 0.196 F1 Hybrid 0.000 0.000 0.384 0.302 0.199 0.115 F2 Hybrid 0.002 0.000 0.216 0.408 0.254 0.120 B2 Kokanee 0.057 0.000 0.127 0.262 0.544 0.010 B2 Sockeye 0.000 0.018 0.161 0.403 0.035 0.383 G. 23 Outliers Kokanee Sockeye F1 Hybrid F2 Hybrid B2 Kokanee B2 Sockeye Kokanee 0.994 0.000 0.000 0.000 0.006 0.000 Sockeye 0.000 0.998 0.000 0.000 0.000 0.002 F1 Hybrid 0.000 0.000 0.861 0.104 0.018 0.017 F2 Hybrid 0.000 0.000 0.096 0.858 0.033 0.013 B2 Kokanee 0.109 0.000 0.043 0.092 0.756 0.000 B2 Sockeye 0.000 0.187 0.030 0.040 0.000 0.743 34 Figure 1. Map showing the northern extent of the Columbia River with inset map (right) showing Skaha Lake and nearby lakes, rivers and dams. A size comparison between an average sockeye jack and an average kokanee jack also shown. Reproduced from Veale AJ, Russello MA (2016) Sockeye salmon repatriation leads to population re-establishment and rapid introgression with native kokanee. Evolutionary Applications 9, 1301-1311. Used under Creative Commons Attribution 4.0 International (https://creativecommons.org/licenses/by/4.0/). 35 Figure 2. Graph of strontium and barium levels overlaid on a cross-section of the otolith they were taken from. The peak of strontium in the core suggests an anadromous maternal parent while the raised levels of strontium near the edges indicate the examined fish is also ocean migrating. 36 Figure 3. Stock proportions of age-0 juvenile fish including results from Veale and Russello 2016. 37 Figure 4. Fork length (mm) by sex and stock pooled across sample years. Figure 5. Fork length of spawners from each class by sample year. 38 Figure 6. Fork length of spawners from each class by age. 39 Figure 7. Distribution of admixture coefficients from LEA for 1000 simulated individuals from each introgression class. Panel size and composition is noted at the top of each graph. 40 References Abbott R, Albach D, Ansell S, et al. (2013) Hybridization and speciation. Journal of Evolutionary Biology 26, 229–246. Allendorf FW, Leary RF (1988) Conservation and Distribution of Genetic Variation in a Polytypic Species, the Cutthroat Trout. Conservation Biology 2, 170–184 Allendorf FW, Leary RF, Spruell P, Wenburg JK (2001) The problems with hybrids: Setting conservation guidelines. Trends in Ecology and Evolution 16, 613-622. Allendorf FW, Seeb LW (2000) Concordance of genetic divergence among sockeye salmon populations at allozyme, nuclear DNA, and mitochondrial DNA markers. Evolution 54, 640–651. Alliance ON, Ernst A, Allison N, et al. (2000) Aboriginal Fisheries Information within the Okanagan Basin. Okanagan Nation Fisheries Commission, Westbank. Anderson EC, Thompson EA (2002) A model-based method for identifying species hybrids using multilocus genetic data. Genetics 160, 1217–1229. Armstrong DP, Seddon PJ (2008) Directions in reintroduction biology. Trends in Ecology and Evolution 23, 20–25. Barber, K (2005) Death of Celilo Falls. Center for the Study of the Pacific Northwest in association with University of Washington Press, Seattle. Barnett-Johnson R, Teel DJ, Casillas E (2010) Genetic and otolith isotopic markers identify salmon populations in the Columbia River at broad and fine geographic scales. Environmental Biology of Fishes 89, 533–546. Beacham TD, Withler RE (2017) Population structure of sea-type and lake-type sockeye salmon and kokanee in the Fraser River and Columbia River drainages. PLoS ONE 12. Benjamini Y, Yekutieli D (2001) The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165–1188. Bettles CM, Docker MF, Dufour B, Heath DD (2005) Hybridization dynamics between sympatric species of trout: Loss of reproductive isolation. Journal of Evolutionary Biology 18, 1220–1233. 41 Braun DC, Reynolds JD, Fleming I (2014) Life history and environmental influences on population dynamics in sockeye salmon. Canadian Journal of Fisheries and Aquatic Sciences 71, 1198–1208. Burkhead N (2012) Extinction Rates in North American Freshwater Fishes, 1900–2010. BioScience 62, 798–808. Campbell NR, Harmon SA, Narum SR (2015) Genotyping-in-Thousands by sequencing (GT-seq): A cost effective SNP genotyping method based on custom amplicon sequencing. Molecular Ecology Resources 15, 855–867. Cochran-Biederman JL, Wyman KE, French WE, Loppnow GL (2015) Identifying correlates of success and failure of native freshwater fish reintroductions. Conservation Biology 29, 175–186. Cordes JF, Stephens MR, Blumberg MA, May B (2006) Identifying Introgressive Hybridization in Native Populations of California Golden Trout Based on Molecular Markers. Transactions of the American Fisheries Society 135, 110–128. Costello C, Ovando D, Clavelle T, et al. (2016) Global fishery prospects under contrasting management regimes. Proceedings of the National Academy of Sciences 113, 5125–5129. Craig JK, Foote CJ, Wood CC (2005) Countergradient variation in carotenoid use between sympatric morphs of sockeye salmon (Oncorhynchus nerka) exposes nonanadromous hybrids in the wild by their mismatched spawning colour. Biological Journal of the Linnean Society 84, 287–305. Crozier WW (1993) Evidence of genetic interaction between escaped farmed salmon and wild Atlantic salmon (Salmo salar L.) in a Northern Irish river. Aquaculture 113, 19–29. Cuenco ML, Backman WH, Mundy PR (1993) The use of supplementation to aid in natural stock restoration. In: Genetic conservation of salmonid fishes, pp. 269–293. Springer, Boston, MA. Cunningham CJ, Westley PAH, Adkison MD (2018) Signals of large scale climate drivers, hatchery enhancement, and marine factors in Yukon River Chinook salmon survival revealed with a Bayesian life history model. Global Change Biology 24, 4399–4416. Currat M, Ruedi M, Petit RJ, Excoffier L (2008) The hidden side of invasions: Massive introgression by local genes. Evolution 62, 1908–1920. Danecek P, Auton A, Abecasis G, et al. (2011) The variant call format and VCFtools. Bioinformatics 27, 2156–2158. 42 Darwall WRT, Freyhof J (2015) Lost fishes, who is counting? The extent of the threat to freshwater fish biodiversity. In: Conservation of Freshwater Fishes, pp. 1-36. Cambridge University Press. Dudgeon D, Arthington AH, Gessner MO, et al. (2006). Freshwater biodiversity: Importance, threats, status and conservation challenges. Biological Reviews of the Cambridge Philosophical Society 81, 163-182. Enzenhofer HJ, Hume JMB (1989) Simple closing midwater trawl for small boats. North American Journal of Fisheries Management 9, 372–377. Fitzpatrick BM (2012) Estimating ancestry and heterozygosity of hybrids using molecular markers. BMC Evolutionary Biology 12, 131. Foll M, Gaggiotti O (2008) A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: A Bayesian perspective. Genetics 180, 977-993. Foote CJ (1987) An experiemental examination of behavioural isolation between sockeye salmon and kokanee, the anadromous and non-anadromous forms of Oncorhynchus nerka (Doctoral dissertation). University of British Columbia. Foote CJ, Mayer I, Wood CC, Clark WC, Blackburn J (1994) On the developmental pathway to nonanadromy in sockeye salmon,. Canadian Journal of Zoology 72, 397-405. Foote CJ, Wood CC, Clarke WC, Blackburn J (1992) Circannual Cycle of Seawater Adaptability in Oncorhynchus nerka: Genetic Differences between Sympatric Sockeye Salmon and Kokanee. Canadian Journal of Fisheries and Aquatic Sciences 49, 99-109. Freamo H, O’Reilly P, Berg PR, Lien S, Boulding EG (2011) Outlier SNPs show more genetic structure between two Bay of Fundy metapopulations of Atlantic salmon than do neutral SNPs. Molecular Ecology Resources 11, 254-267. Freshwater C, Trudel M, Beacham TD, et al. (2016) Disentangling individual- and population-scale processes within a latitudinal size gradient in sockeye salmon. Canadian Journal of Fisheries and Aquatic Sciences 73, 1190-1201. Frichot E, François O (2015) LEA: An R package for landscape and ecological association studies. Methods in Ecology and Evolution 6, 925-929. Fukuwaka M, Kaeriyama M (1997) Scale analyses to estimate somatic growth in sockeye salmon, Oncorhynchus nerka. Canadian Journal of Fisheries and Aquatic Sciences 54, 631-636. 43 Glover KA, Hansen MM, Lien S, et al. (2010) A comparison of SNP and STR loci for delineating population structure and performing individual genetic assignment. BMC Genetics 11, 2. Glover KA, Solberg MF, McGinnity P, et al. (2017). Half a century of genetic interaction between farmed and wild Atlantic salmon: Status of knowledge and unanswered questions. Fish and Fisheries 18, 890-927. Grant WS, Milner GB, Krasnowski P, Utter FM (1980) Use of Biochemical Genetic Variants for Identification of Sockeye Salmon (Oncorhynchus nerka) Stocks in Cook Inlet, Alaska. Canadian Journal of Fisheries and Aquatic Sciences 37, 1236-1247. Groot C, Margolis L (1991) Pacific salmon life histories. Vancouver: UBC Press. Gustafson RG, Waples RS, Myers JM, et al. (2007). Pacific salmon extinctions: Quantifying lost and remaining diversity. Conservation Biology 21, 1009-1020. Hamon TR, Foote CJ (2005) Concurrent natural and sexual selection in wild male sockeye salmon, Oncorhynchus nerka. Evolution 59, 1104-1118. Hasegawa K, Ohta T, Takahashi S (2018) Are hatchery chum salmon fry a native invader? Direct and indirect effects of stocking salmon fry on stream organisms. Hydrobiologia 806, 111-121. Hecht BC, Thrower FP, Hale MC, Miller MR, Nichols KM (2012) Genetic Architecture of Migration-Related Traits in Rainbow and Steelhead Trout, Oncorhynchus mykis s. Genes, Genomes, Genetics 2, 1113-1127. Hegg JC, Kennedy BP, Chittaro PM (2018) What did you say about my mother? The complexities of maternally derived chemical signatures in otoliths. Canadian Journal of Fisheries and Aquatic Sciences 76, 81-94. Henderson MA, Cass AJ (1991) Effect of smolt size on smolt-to-adult survival for Chilko Lake sockeye salmon (Oncorhynchus nerka). Canadian Journal of Fisheries and Aquatic Sciences 48, 988-994. Hewes G (1998) Fishing. In: Handbook of North American Indians (ed Walker D), pp. 620–640. Smithsonian Institute, Washington. Hohenlohe PA, Amish SJ, Catchen JM, Allendorf FW, Luikart G (2011) Next-generation RAD sequencing identifies thousands of SNPs for assessing hybridization between rainbow and westslope cutthroat trout. Molecular Ecology Resources 11, 117-122. 44 Hubbs CL (1955) Hybridization between fish species in nature. Systematic Zoology 4, 1-20. Huelga-Suarez G, Fernández B, Moldovan M, Alonso JIG (2013) Detection of transgenerational barium dual-isotope marks in salmon otoliths by means of LA-ICP-MS. Analytical and Bioanalytical Chemistry 405, 2901-2909. Kalinowski S, Manlove K, Taper M (2007) ONCOR: A computer program for genetic stock identification. Department of Ecology, Montana State University. Bozeman, MT. Retrieved from http://www.montana.edu/kalinowski/kalinowski_software.html. Kennedy D, Bouchard R (1998) Northern Okanagan, Lakes and Colville. In: Handbook of North American Indians (ed. Walker D), pp. 238–252. Smithsonian Institute, Washington. Kitada S (1999) Effectiveness of Japan’s stock enhancement programmes: Current perspectives. In: Stock Enhancement and Sea Ranching. Lawrence S, Wright R, Rankin D (2005) Sockeye reintroduction into Skaha Lake: 2004/2005 monitoring program, 2003 broodyear. Westbank, BC. Lemay MA, Russello MA (2015) Genetic evidence for ecological divergence in kokanee salmon. Molecular Ecology 24, 798-811. Lowe WH, Muhlfeld CC, Allendorf FW (2015) Spatial sorting promotes the spread of maladaptive hybridization. Trends in Ecology and Evolution 30, 456-462. Luikart G, England PR, Tallmon D, Jordan S, Taberlet P (2003) The power and promise of population genomics: From genotyping to genome typing. Nature Reviews Genetics 4, 981. MacKendrick D (1975) Before the Newlands Act: state sponsored reclamations projects in Colorado, 1888-1903. The Colorado Magazine 52, 1–21. Marie AD, Bernatchez L, Garant D (2011) Empirical assessment of software efficiency and accuracy to detect introgression under variable stocking scenarios in brook charr (Salvelinus fontinalis). Conservation Genetics 12, 1215. Martin J, Rougemont Q, Drouineau H, et al. (2015) Dispersal capacities of anadromous Allis shad population inferred from a coupled genetic and otolith approach. Canadian Journal of Fisheries and Aquatic Sciences 72, 991-1003. 45 McGurk MD (2000) Comparison of fecundity-length-latitude relationships between nonanadromous (kokanee) and anadromous sockeye salmon (Oncorhynchus nerka). Canadian Journal of Zoology 78, 1791-1805. McPhail JD (2007) The Freshwater Fishes of British Columbia. University of Alberta. McQueen D, Hyatt K, Stockwell M, et al. (2017) Evaluation of the experimental reintroduction of Sockeye Salmon (Oncorhynchus nerka) into Skaha Lake and assesment of Sockeye rearing in Osoyoos Lake. Westbank, BC. Miller JA (2011) Effects of water temperature and barium concentration on otolith composition along a salinity gradient: Implications for migratory reconstructions. Journal of Experimental Marine Biology and Ecology 405, 42-52. Milner GB, Teel DJ, Utter FM, Winans GA (1985) A Genetic Method of Stock Identification in Mixed Populations of Pacific Salmon, Oncorhynchus spp. Marine Fisheries Review 47, 1–8. Molony BW, Lenanton R, Jackson G, Norriss J (2004) Stock enhancement as a fisheries management tool. Reviews in Fish Biology and Fisheries 13, 409-432. Monnerjahn U (2011) Atlantic Salmon (Salmo salar L.) re-introduction in Germany: A status report on national programmes and activities. Journal of Applied Ichthyology 27, 33-40. Moore ME, Goetz FA, van Doornik DM, et al. (2010) Early marine migration patterns of wild coastal cutthroat trout (Oncorhynchus clarki clarki), steelhead trout (Oncorhynchus mykiss), and their hybrids. PLoS ONE 5, 1371. Muhlfeld CC, Kalinowski ST, McMahon TE, et al. (2009). Hybridization rapidly reduces fitness of a native trout in the wild. Biology Letters 5, 328-331. Muhlfeld CC, Kovach RP, Jones LA, et al. (2014). Invasive hybridization in a threatened species is accelerated by climate change. Nature Climate Change 4, 620. Nakamaya K, Tohkairin A, Yoshikawa A, Nakabo T (2018) Detection and morphological characteristics of “Kunimasu” (Oncorhynchus kawamurae)/"Himemasu" (O. nerka) hybrids in Lake Motusu, Yamanashi Prefecture, Japan. Ichthyological Research 65, 270–275. Nichols KM, Edo AF, Wheeler PA, Thorgaard GH (2008) The genetic basis of smoltification-related traits in Oncorhynchus mykiss. Genetics 179, 1559-1575. 46 Nichols KM, Kozfkay CC, Narum SR (2016) Genomic signatures among Oncorhynchus nerka ecotypes to inform conservation and management of endangered Sockeye Salmon. Evolutionary Applications 9, 1285-1300. Nielsen EE, Bach LA, Kotlicki P (2006) HYBRIDLAB (version 1.0): A program for generating simulated hybrids from population samples. Molecular Ecology Notes 6, 971-973. NOAA/NMFS (2015) Proposed ESA Recovery Plan for Snake River Fall Chinook Salmon (Oncorhynchus tshawytscha). Parkinson EA, Post JR, Cox SP (2004) Linking the dynamics of harvest effort to recruitment dynamics in a multistock, spatially structured fishery. Canadian Journal of Fisheries and Aquatic Sciences 61, 1658-1670. Patterson SD, Scarnecchia DL, Congleton JL (2008) Sexual Maturation in Kokanee Oncorhynchus nerka. Northwest Science 80, 32-48. Perry WL, Lodge DM, Feder JL (2002) Importance of hybridization between indigenous and nonindigenous freshwater species: An overlooked threat to North American biodiversity. Systematic Biology 51, 255-275. Peters C, Bernard D, Marmorek D (1998) Should Sockeye be reintroduced into Okangan Lake? An exploration of potential benefits, impacts and uncertainties. Post JR, Sullivan M, Cox S, et al. (2002) Canada’s Recreational Fisheries: The Invisible Collapse? Fisheries 27, 6-17. Pritchard JK, Stephens M, Donnelly P (2000) Inference of population structure using multilocus genotype data. Genetics 155, 945-959. Pritchard VL, Erkinaro J, Kent MP, et al. (2016) Single nucleotide polymorphisms to discriminate different classes of hybrid between wild Atlantic salmon and aquaculture escapees. Evolutionary Applications 9, 1017-1031. Raymond M, Rousset F (1995) GENEPOP (Version 1.2): Population Genetics Software for Exact Tests and Ecumenicism. Journal of Heredity 86, 248-249. Ridgway GJ, Klontz GW (1961) Blood types in Pacific salmon. In: International North Pacific Fisheries Commission. Vancouver, Washtington. 47 Rieman BE, Myers DL, Nielsen RL (1994) Use of Otolith Microchemistry to Discriminate Oncorhynchus nerka of Resident and Anadromous Origin. Canadian Journal of Fisheries and Aquatic Sciences 51, 68-77. Russello MA, Kirk SL, Frazer KK, Askey PJ (2012) Detection of outlier loci and their utility for fisheries management. Evolutionary Applications 5, 39-52. Saltveit SJ (2006) The effects of stocking Atlantic salmon, Salmo salar, in a Norwegian regulated river. Fisheries Management and Ecology 13, 197-205. Sandford RW, Harford D, O’Riordan J (2014) The Columbia River Treaty: A Primer. Rocky Mountain Books, Ltd. Savary R, Dufresnes C, Champigneulle A, et al. (2017) Stocking activities for the Arctic charr in Lake Geneva: Genetic effects in space and time. Ecology and Evolution 7, 5201-5211. Skaala Ø, Wennevik V, Glover KA (2006) Evidence of temporal genetic change in wild Atlantic salmon, Salmo salar L., populations affected by farm escapees. ICES Journal of Marine Science 63, 1224-1233. Taylor G, Canessa S, Clarke RH, et al. (2017). Is Reintroduction Biology an Effective Applied Science? Trends in Ecology and Evolution 32, 873-880. Thorpe JE, Kingdom U (1987) Smolting versus Residency: Developmental Conflict in Salmonids. American Fisheries Society Symposium 1, 244-252. Todesco M, Pascual MA, Owens GL, et al. (2016) Hybridization and extinction. Evolutionary Applications 9, 892-908. Twyford AD, Ennos RA (2012) Next-generation hybridization and introgression. Heredity 108, 179. Vaha JK, Primmer CR (2004) Efficiency of allele frequency-based bayesian programmes for detecting hybridization between farmed and wild salmon. Journal of Fish Biology 65, 324. Veale AJ, Russello MA (2016) Sockeye salmon repatriation leads to population re-establishment and rapid introgression with native kokanee. Evolutionary Applications 9, 1301-1311. Veale AJ, Russello MA (2017) Genomic changes associated with reproductive and migratory ecotypes in sockeye salmon (oncorhynchus nerka). Genome Biology and Evolution 9, 2921-2939. 48 Vinebrooke R, Welch DW, Melnychuk MC, et al. (2009) Freshwater and marine migration and survival of endangered Cultus Lake sockeye salmon (Oncorhynchus nerka) smolts using POST, a large-scale acoustic telemetry array. Canadian Journal of Fisheries and Aquatic Sciences 66, 736-750. Walsh PS, Metzger DA, Higuchi R (1991) Chelex-100 as a Medium for Simple Extraction of DNA for PCR- Based Typing from Forensic Material. BioTechniques 10, 506-513. Ward RD (2000) Genetics in fisheries management. Hydrobiologia 420, 191–201. Warren MA, Morbey YE (2012) Migration timing of female kokanee salmon Oncorhynchus nerka: Diel patterns and effects of maturation state. Journal of Fish Biology 81, 1234-1247. Wood CC, Bickham JW, Nelson RJ, Foote CJ, Patton JC (2008) Recurrent evolution of life history ecotypes in sockeye salmon: implications for conservation and future evolution. Evolutionary Applications 1, 207-221. Wood CC, Foote CJ (1996) Evidence for sympatric genetic divergence of anadromous and nonanadromous morphs of sockeye salmon (Oncorhynchus nerka). Evolution 50, 1265-1279. Wood CC, Foote CJ, Rutherford DT (1999) Ecological interactions between juveniles of reproductively isolated anadromous and non-anadromous morphs of sockeye salmon, Oncorhynchus nerka, sharing the same nursery lake. Environmental Biology of Fishes 54, 161-173. Worm B, Barbier EB, Beaumont N, et al. (2006) Impacts of biodiversity loss on ocean ecosystem services. Science 314, 787-790. Wright H, Smith H (2004) Management plan for the experimental reintroduction of Sockeye into Skaha Lake. Portland, OR.
Thesis/Dissertation
eng
Biology
Vancouver : University of British Columbia Library
Attribution-NonCommercial 4.0 International
Graduate
There and back again : an investigation of the biological and genetic consequences of a sockeye stocking program
Text