Evaluation of a Single Nucleotide Polymorphism Baseline for Genetic Stock Identification of Chinook Salmon (Oncorhynchus tshawytscha) in the California Current Large Marine Ecosystem

Chinook Salmon (Oncorhynchus tshawytscha) is an economically and ecologically important species, and populations from the west coast of North America are a major component of fisheries in the North Pacific Ocean. The anadromous life history strategy of this species generates populations (or stocks) that typically are differentiated from neighboring populations. In many cases, it is desirable to discern the stock of origin of an individual fish or the stock composition of a mixed sample to monitor the stock-specific effects of anthropogenic impacts and alter management strategies accordingly. Genetic stock identification (GSI) provides such discrimination, and we describe here a novel GSI baseline composed of genotypes from more than 8000 individual fish from 69 distinct populations at 96 single nucleotide polymorphism (SNP) loci. The populations included in this baseline represent the likely sources for more than 99% of the salmon encountered in ocean fisheries of California and Oregon. This new genetic baseline permits GSI with the use of rapid and cost-effective SNP genotyping, and power analyses indicate that it provides very accurate identification of important stocks of Chinook Salmon. In an ocean fishery sample, GSI assignments of more than 1000 fish, with our baseline, were highly concordant (98.95%) at the reporting unit level with information from the physical tags recovered from the same fish. This SNP baseline represents an important advance in the technologies available to managers and researchers of this species

Heterogeneous genetic basis of age at maturity in salmonid fishes

Understanding the genetic basis of repeated evolution of the same phenotype across taxa is a fundamental aim in evolutionary biology and has applications in conservation and management. However, the extent to which interspecific life-history trait polymorphisms share evolutionary pathways remains underexplored. Here, we address this gap by studying the genetic basis of a key life-history trait, age at maturity, in four species of Pacific salmonids (genus Oncorhynchus) that exhibit intra- and interspecific variation in this trait-Chinook Salmon, Coho Salmon, Sockeye Salmon, and Steelhead Trout. We tested for associations in all four species between age at maturity and two genome regions, six6 and vgll3, that are strongly associated with the same trait in Atlantic Salmon (Salmo salar). We also conducted a genome-wide association analysis in Steelhead to assess whether additional regions were associated with this trait. We found the genetic basis of age at maturity to be heterogeneous across salmonid species. Significant associations between six6 and age at maturity were observed in two of the four species, Sockeye and Steelhead, with the association in Steelhead being particularly strong in both sexes (p = 4.46 x 10(-9) after adjusting for genomic inflation). However, no significant associations were detected between age at maturity and the vgll3 genome region in any of the species, despite its strong association with the same trait in Atlantic Salmon. We discuss possible explanations for the heterogeneous nature of the genetic architecture of this key life-history trait, as well as the implications of our findings for conservation and management.Peer reviewe

Geo-Referenced, Abundance Calibrated Ocean Distribution of Chinook Salmon (Oncorhynchus tshawytscha) Stocks across the West Coast of North America

Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus Oncorhynchus) forecasting models predict stock composition, abundance, and distribution during annual assessments of proposed fisheries impacts. Most models, however, fail to account for the influence of biophysical factors on year-to-year fluctuations in migratory distributions and stock-specific survival. In this study, the ocean distribution and relative abundance of Chinook salmon (O. tshawytscha) stocks encountered in the California Current large marine ecosystem, U.S.A were inferred using catch-per-unit effort (CPUE) fisheries and genetic stock identification data. In contrast to stock distributions estimated through coded-wire-tag recoveries (typically limited to hatchery salmon), stock-specific CPUE provides information for both wild and hatchery fish. Furthermore, in contrast to stock composition results, the stock-specific CPUE metric is independent of other stocks and is easily interpreted over multiple temporal or spatial scales. Tests for correlations between stock-specific CPUE and stock composition estimates revealed these measures diverged once proportional contributions of locally rare stocks were excluded from data sets. A novel aspect of this study was collection of data both in areas closed to commercial fisheries and during normal, open commercial fisheries. Because fishing fleet efficiency influences catch rates, we tested whether CPUE differed between closed area (non-retention) and open area (retention) data sets. A weak effect was indicated for some, but not all, analyzed cases. Novel visualizations produced from stock-specific CPUE-based ocean abundance facilitates consideration of how highly refined, spatial and genetic information could be incorporated in ocean fisheries management systems and for investigations of biogeographic factors that influence migratory distributions of fish

A unifying framework for understanding ecological and evolutionary population connectivity

Although the concept of connectivity is ubiquitous in ecology and evolution, its definition is often inconsistent, particularly in interdisciplinary research. In an ecological context, population connectivity refers to the movement of individuals or species across a landscape. It is measured by locating organisms and tracking their occurrence across space and time. In an evolutionary context, connectivity is typically used to describe levels of current and past gene flow, calculated from the degree of genetic similarity between populations. Both connectivity definitions are useful in their specific contexts, but rarely are these two perspectives combined. Different definitions of connectivity could result in misunderstandings across subdisciplines. Here, we unite ecological and evolutionary perspectives into a single unifying framework by advocating for connectivity to be conceptualized as a generational continuum. Within this framework, connectivity can be subdivided into three timescales: (1) within a generation (e.g., movement), (2) across one parent-offspring generation (e.g., dispersal), and (3) across two or more generations (e.g., gene flow), with each timescale determining the relevant context and dictating whether the connectivity has ecological or evolutionary consequences. Applying our framework to real-world connectivity questions can help to identify sampling limitations associated with a particular methodology, further develop research questions and hypotheses, and investigate eco-evolutionary feedback interactions that span the connectivity continuum. We hope this framework will serve as a foundation for conducting and communicating research across subdisciplines, resulting in a more holistic understanding of connectivity in natural systems

Early Ocean Distribution of Juvenile Chinook Salmon in an Upwelling Ecosystem

Extreme variability in abundance of California salmon populations is often ascribed to ocean conditions, yet relatively little is known about their marine life-history. To investigate which ocean conditions influence their distribution and abundance, we surveyed juvenile Chinook salmon (Oncorhynchus tshawytscha) within the California Current (central California (37o 30’ N) to Newport, Oregon (44o 00’ N)) for a two-week period over three summers (2010-2012). At each station, we measured chlorophyll a as an indicator of primary productivity, acoustic-based metrics of zooplankton density as an indicator of potential prey availability, and physical characteristics such as bottom depth, temperature, and salinity. We also measured fork lengths and collected genetic samples from each salmon that was caught. Genetic stock identification revealed that the majority of juvenile salmon were from the Central Valley and the Klamath Basin (91-98%). We constructed generalized logistic-linear negative binomial hurdle models and chose the best model(s) using AIC to determine which covariates influenced salmon presence and, at locations where salmon were present, determined the variables that influenced their abundance. The probability of salmon presence was highest in shallower waters with high chlorophyll a concentration and close to an individual’s natal river. Catch abundance was primarily influenced by year, mean fork length, and proximity to natal rivers. At the scale of sampling stations, presence and abundance was not related to acoustic indices of zooplankton density. In the weeks to months following ocean entry, California’s juvenile Chinook salmon population appears to be primarily constrained to coastal waters near natal river outlets

Use of Genetic Stock Identification Data for Comparison of the Ocean Spatial Distribution, Size at Age, and Fishery Exposure of an Untagged Stock and Its Indicator: California Coastal versus Klamath River Chinook Salmon

Managing weak stocks in mixed-stock fisheries often relies on proxies derived from data-rich indicator stocks. For example, full cohort reconstruction of tagged Klamath River fall run Chinook salmon (Oncorhynchus tshawytscha) of northern California, USA, enables the use of detailed models to inform management. Information gained from this stock is also used in the management of the untagged, threatened California Coastal Chinook (CCC) salmon stock, by capping Klamath harvest rates. To evaluate use of this proxy, we used genetic stock identification (GSI) data to compare the two stocks\u27 size-at-age and ocean distribution, two key factors influencing fishery exposure. We developed methods to account for both sampling and genetic assignment uncertainty in catch estimates. We found that, in 2010, the stocks were similar in size-at-age early in the year (age-3 and age-4), but CCC fish were larger later in the year. The stocks appeared similarly distributed early in the year (2010), but more concentrated near their respective source rivers later in the year (2010 and 2011). If these results are representative, relative fishery impacts on the two stocks might scale similarly early in the year but management changes later in the year might have differing impacts on the two stocks

Geo-Referenced, Abundance Calibrated Ocean Distribution of Chinook Salmon (Oncorhynchus tshawytscha) Stocks across the West Coast of North America

Understanding seasonal migration and localized persistence of populations is critical for effective species harvest and conservation management. Pacific salmon (genus Oncorhynchus) forecasting models predict stock composition, abundance, and distribution during annual assessments of proposed fisheries impacts. Most models, however, fail to account for the influence of biophysical factors on year-to-year fluctuations in migratory distributions and stock-specific survival. In this study, the ocean distribution and relative abundance of Chinook salmon (O. tshawytscha) stocks encountered in the California Current large marine ecosystem, U.S.A were inferred using catch-per-unit effort (CPUE) fisheries and genetic stock identification data. In contrast to stock distributions estimated through coded-wire-tag recoveries (typically limited to hatchery salmon), stock-specific CPUE provides information for both wild and hatchery fish. Furthermore, in contrast to stock composition results, the stock-specific CPUE metric is independent of other stocks and is easily interpreted over multiple temporal or spatial scales. Tests for correlations between stock-specific CPUE and stock composition estimates revealed these measures diverged once proportional contributions of locally rare stocks were excluded from data sets. A novel aspect of this study was collection of data both in areas closed to commercial fisheries and during normal, open commercial fisheries. Because fishing fleet efficiency influences catch rates, we tested whether CPUE differed between closed area (non-retention) and open area (retention) data sets. A weak effect was indicated for some, but not all, analyzed cases. Novel visualizations produced from stock-specific CPUE-based ocean abundance facilitates consideration of how highly refined, spatial and genetic information could be incorporated in ocean fisheries management systems and for investigations of biogeographic factors that influence migratory distributions of fish

Leveraging natural history biorepositories as a global, decentralized, pathogen surveillance network

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic reveals a major gap in global biosecurity infrastructure: a lack of publicly available biological samples representative across space, time, and taxonomic diversity. The shortfall, in this case for vertebrates, prevents accurate and rapid identification and monitoring of emerging pathogens and their reservoir host(s) and precludes extended investigation of ecological, evolutionary, and environmental associations that lead to human infection or spillover. Natural history museum biorepositories form the backbone of a critically needed, decentralized, global network for zoonotic pathogen surveillance, yet this infrastructure remains marginally developed, underutilized, underfunded, and disconnected from public health initiatives. Proactive detection and mitigation for emerging infectious diseases (EIDs) requires expanded biodiversity infrastructure and training (particularly in biodiverse and lower income countries) and new communication pipelines that connect biorepositories and biomedical communities. To this end, we highlight a novel adaptation of Project ECHO’s virtual community of practice model: Museums and Emerging Pathogens in the Americas (MEPA). MEPA is a virtual network aimed at fostering communication, coordination, and collaborative problem-solving among pathogen researchers, public health officials, and biorepositories in the Americas. MEPA now acts as a model of effective international, interdisciplinary collaboration that can and should be replicated in other biodiversity hotspots. We encourage deposition of wildlife specimens and associated data with public biorepositories, regardless of original collection purpose, and urge biorepositories to embrace new specimen sources, types, and uses to maximize strategic growth and utility for EID research. Taxonomically, geographically, and temporally deep biorepository archives serve as the foundation of a proactive and increasingly predictive approach to zoonotic spillover, risk assessment, and threat mitigation