Genomic vulnerability of a freshwater salmonid under climate change.

Understanding the adaptive potential of populations and species is pivotal for minimizing the loss of biodiversity in this era of rapid climate change. Adaptive potential has been estimated in various ways, including based on levels of standing genetic variation, presence of potentially beneficial alleles, and/or the severity of environmental change. Kokanee salmon, the non-migratory ecotype of sockeye salmon (Oncorhynchus nerka), is culturally and economically important and has already been impacted by the effects of climate change. To assess its climate vulnerability moving forward, we integrated analyses of standing genetic variation, genotype-environment associations, and climate modeling based on sequence and structural genomic variation from 224 whole genomes sampled from 22 lakes in British Columbia and Yukon (Canada). We found that variables for extreme temperatures, particularly warmer temperatures, had the most pervasive signature of selection in the genome and were the strongest predictors of levels of standing variation and of putatively adaptive genomic variation, both sequence and structural. Genomic offset estimates, a measure of climate vulnerability, were significantly correlated with higher increases in extreme warm temperatures, further highlighting the risk of summer heat waves that are predicted to increase in frequency in the future. Levels of standing genetic variation, an important metric for population viability and resilience, were not correlated with genomic offset. Nonetheless, our combined approach highlights the importance of integrating different sources of information and genomic data to formulate more comprehensive and accurate predictions on the vulnerability of populations and species to future climate change.

Genotyping-in-Thousands by sequencing panel development and application for high-resolution monitoring of introgressive hybridization within sockeye salmon.

Stocking programs have been widely implemented to re-establish extirpated fish species to their historical ranges; when employed in species with complex life histories, such management activities should include careful consideration of resulting hybridization dynamics with resident stocks and corresponding outcomes on recovery initiatives. Genetic monitoring can be instrumental for quantifying the extent of introgression over time, however conventional markers typically have limited power for the identification of advanced hybrid classes, especially at the intra-specific level. Here, we demonstrate a workflow for developing, evaluating and deploying a Genotyping-in-Thousands by Sequencing (GT-seq) SNP panel with the power to detect advanced hybrid classes to assess the extent and trajectory of intra-specific hybridization, using the sockeye salmon (Oncorhynchus nerka) stocking program in Skaha Lake, British Columbia as a case study. Previous analyses detected significant levels of hybridization between the anadromous (sockeye) and freshwater resident (kokanee) forms of O. nerka, but were restricted to assigning individuals to pure-stock or "hybrid". Simulation analyses indicated our GT-seq panel had high accuracy, efficiency and power (> 94.5%) of assignment to pure-stock sockeye salmon/kokanee, F1, F2, and B2 backcross-sockeye/kokanee. Re-analysis of 2016/2017 spawners previously analyzed using TaqMan® assays and otolith microchemistry revealed shifts in assignment of some hybrids to adjacent pure-stock or B2 backcross classes, while new assignment of 2019 spawners revealed hybrids comprised 31% of the population, ~ 74% of which were B2 backcross or F2. Overall, the GT-seq panel development workflow presented here could be applied to virtually any system where genetic stock identification and intra-specific hybridization are important management parameters.

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout.

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.

El uso de datos extensivos, pero de baja resolución, de la abundancia es una práctica común en la evaluación del estado de riesgo de una especie con base en los criterios cuantitativos de declinación establecidos por la Unión Internacional para la Conservación de la Naturaleza (UICN) y la legislación nacional sobre especies en peligro extinción. Dicha información puede ser problemática por tres razones: primero, el poder estadístico para rechazar la hipótesis nula de ningún cambio es frecuentemente bajo debido a un tamaño pequeño de la muestra y a la elevada incertidumbre del muestreo, lo que resulta en una frecuencia elevada de errores de tipo II; segundo, las evaluaciones de amplia variedad compuestas de varias observaciones específicas de sitio no sopesan efectivamente las tendencias específicas de sitio dentro de las tendencias globales; y tercero, la incertidumbre en las tendencias temporales específicas de sitio y en la abundancia relativa no se propagan a la escala espacial apropiada. Un resultado común del uso de esta información es la propensión a subestimar la magnitud de las declinaciones, y por lo tanto equivocarse en la identificación del estado de riesgo apropiado para la especie. Usamos tres estrategias estadísticas, de simples a más complejas, para estimar las tasas de declinación temporal para una unidad designable (UD) de trucha arcoíris en la cuenca del río Athabasca al oeste de Canadá. Esta UD es considerada una especie nativa por razones de listado debido a su composición genética, caracterizada como >0-95 de origen nativo de frente a la continua hibridación introgresiva con poblaciones introducidas a la cuenca. El análisis de las tendencias de abundancia de 57 series de tiempo con un modelo de efectos fijos identificó 33 sitios con tendencias negativas, pero sólo dos fueron estadísticamente significativas. En contraste, un modelo lineal mixto de jerarquías sopesado por abundancia específica de sitio proporcionó una estimación de declinación en toda la UD de 16.4% año−1 y una declinación a tres generaciones de 93.2%. Un modelo bayesiano de jerarquías produjo una tendencia de declinación a tres generaciones de 91.3% y la distribución posterior mostró que el estimado tuvo una probabilidad >99% de exceder los umbrales para la categorización como especie en peligro. Concluimos que la estrategia bayesiana fue la más útil porque proporcionó una afirmación probabilística de la superación del umbral a favor de una recomendación de categorizar el estado como en riesgo.

Genotyping-in-Thousands by sequencing panel development and application to inform kokanee salmon (Oncorhynchus nerka) fisheries management at multiple scales.

The ability to differentiate life history variants is vital for estimating fisheries management parameters, yet traditional survey methods can be inaccurate in mixed-stock fisheries. Such is the case for kokanee, the freshwater resident form of sockeye salmon (Oncorhynchus nerka), which exhibits various reproductive ecotypes (stream-, shore-, deep-spawning) that co-occur with each other and/or anadromous O. nerka in some systems across their pan-Pacific distribution. Here, we developed a multi-purpose Genotyping-in-Thousands by sequencing (GT-seq) panel of 288 targeted single nucleotide polymorphisms (SNPs) to enable accurate kokanee stock identification by geographic basin, migratory form, and reproductive ecotype across British Columbia, Canada. The GT-seq panel exhibited high self-assignment accuracy (93.3%) and perfect assignment of individuals not included in the baseline to their geographic basin, migratory form, and reproductive ecotype of origin. The GT-seq panel was subsequently applied to Wood Lake, a valuable mixed-stock fishery, revealing high concordance (>98%) with previous assignments to ecotype using microsatellites and TaqMan® SNP genotyping assays, while improving resolution, extending a long-term time-series, and demonstrating the scalability of this approach for this system and others.

Supply-demand equilibria and the size-number trade-off in spatially structured recreational fisheries.

Recreational fishing effort varies across complex inland landscapes (e.g., lake-districts) and appears influenced by both angler preferences and qualities of the fishery resource, like fish size and abundance. However, fish size and abundance have an ecological trade-off within a population, thereby structuring equal-quality isopleths expressing this trade-off across the fishing landscape. Since expressed preferences of recreational anglers (i.e., site-selection of high-quality fishing opportunities among many lakes) can be analogous to optimal foraging strategies of natural predators, adopting such concepts can aid in understanding scale-dependence in fish-angler interactions and impacts of fishing across broad landscapes. Here, we assumed a fish supply-angler demand equilibria and adapted a novel bivariate measure of fishing quality based on fish size and catch rates to assess how recreational anglers influence fishing quality among a complex inland landscape. We then applied this metric to evaluate (1) angler preferences for caught and released fish compared to harvested fish, (2) the nonlinear size-numbers trade-off with uncertainty in both traits, and (3) the spatial-scale of the equilibria across 62 lakes and four independent management regions in British Columbia's (BC) rainbow trout Oncorhynchus mykiss fishery. We found anglers had low preference for caught and released fish (~10% of the value compared to harvested fish), which modified anglers' perception of fishing quality. Hence, fishing quality and angler effort was not influenced simply by total fish caught, but largely by harvested fish catch rates. Fishing quality varied from BC's northern regions (larger fish and more abundant) compared to southern regions (smaller fish and less abundant) directly associated with a 2.5 times increase in annual fishing effort in southern regions, suggesting that latent fishing pressure can structure the size-numbers trade-off in rainbow trout populations. The presence of two different equal-quality isopleths suggests at least two effective landscapes support co-occurring ideal free distributions of recreational fishing effort in BC's rainbow fishery. Anglers' expressed preferences among lakes interacted with density dependent growth and survival within lakes to structure a size-numbers trade-off influencing how anglers perceive fishing quality and, ultimately, distribute across complex inland landscapes.