Genomic signatures and correlates of widespread population declines in salmon

Variable parallelism in the genomic basis of age at maturity across spatial scales in Atlantic Salmon

Complex traits often exhibit complex underlying genetic architectures resulting from a combination of evolution from standing variation, hard and soft sweeps, and alleles of varying effect size. Increasingly, studies implicate both large-effect loci and polygenic patterns underpinning adaptation, but the extent that common genetic architectures are utilized during repeated adaptation is not well understood. Sea age or age at maturation represents a significant life history trait in Atlantic Salmon (Salmo salar), the genetic basis of which has been studied extensively in European Atlantic populations, with repeated identification of large-effect loci. However, the genetic basis of sea age within North American Atlantic Salmon populations remains unclear, as does the potential for a parallel trans-Atlantic genomic basis to sea age. Here, we used a large single-nucleotide polymorphism (SNP) array and low-coverage whole-genome resequencing to explore the genomic basis of sea age variation in North American Atlantic Salmon. We found significant associations at the gene and SNP level with a large-effect locus (vgll3) previously identified in European populations, indicating genetic parallelism, but found that this pattern varied based on both sex and geographic region. We also identified nonrepeated sets of highly predictive loci associated with sea age among populations and sexes within North America, indicating polygenicity and low rates of genomic parallelism. Despite low genome-wide parallelism, we uncovered a set of conserved molecular pathways associated with sea age that were consistently enriched among comparisons, including calcium signaling, MapK signaling, focal adhesion, and phosphatidylinositol signaling. Together, our results indicate parallelism of the molecular basis of sea age in North American Atlantic Salmon across large-effect genes and molecular pathways despite population-specific patterns of polygenicity. These findings reveal roles for both contingency and repeated adaptation at the molecular level in the evolution of life history variation.

The Discovery and Characterization of Conserved and Novel miRNAs in the Different Developmental Stages and Organs of Pikeperch (Sander lucioperca)

Micro RNAs (miRNAs) are short non-coding RNAs that act as post-transcriptional gene expression regulators. Genes regulated in vertebrates include those affecting growth and development or stress and immune response. Pikeperch (Sander lucioperca) is a species that is increasingly being considered for farming in recirculation aquaculture systems. We characterized the pikeperch miRNA repertoire to increase the knowledge of the genomic mechanisms affecting performance and health traits by applying small RNA sequencing to different developmental stages and organs. There were 234 conserved and 8 novel miRNA genes belonging to 104 families. A total of 375 unique mature miRNAs were processed from these genes. Many mature miRNAs showed high relative abundances or were significantly more expressed at early developmental stages, like the miR-10 and miR-430 family, let-7, the miRNA clusters 106-25-93, and 17-19-92. Several miRNAs associated with immune responses (e.g., slu-mir-731-5p, slu-mir-2188-5p, and slu-mir-8159-5p) were enriched in the spleen. The mature miRNAs slu-mir-203a-3p and slu-mir-205-5p were enriched in gills. These miRNAs are similarly abundant in many vertebrates, indicating that they have shared regulatory functions. There was also a significantly increased expression of the disease-associated miR-462/miR-731 cluster in response to hypoxia stress. This first pikeperch miRNAome reference resource paves the way for future functional studies to identify miRNA-associated variations that can be utilized in marker-assisted breeding programs.

Multifaceted framework for defining conservation units: An example from Atlantic salmon (Salmo salar) in Canada

Conservation units represent important components of intraspecific diversity that can aid in prioritizing and protecting at-risk populations, while also safeguarding unique diversity that can contribute to species resilience. In Canada, identification and assessments of conservation units is done by the Committee on the Status of Endangered Wildlife in Canada (COSEWIC). COSEWIC can recognize conservation units below the species level (termed "designatable units"; DUs) if the unit has attributes that make it both discrete and evolutionarily significant. There are various ways in which a DU can meet criteria of discreteness and significance, and increasing access to "big data" is providing unprecedented information that can directly inform both criteria. Specifically, the incorporation of genomic data for an increasing number of non-model species is informing more COSEWIC assessments; thus, a repeatable, robust framework is needed for integrating these data into DU characterization. Here, we develop a framework that uses a multifaceted, weight of evidence approach to incorporate multiple data types, including genetic and genomic data, to inform COSEWIC DUs. We apply this framework to delineate DUs of Atlantic salmon (Salmo salar, L.), an economically, culturally, and ecologically significant species, that is also characterized by complex hierarchical population structure. Specifically, we focus on an in-depth example of how our approach was applied to a previously data limited region of northern Canada that was defined by a single large DU. Application of our framework with newly available genetic and genomic data led to subdividing this DU into three new DUs. Although our approach was developed to meet criteria of COSEWIC, it is widely applicable given similarities in the definitions of a conservation unit.

Adaptive photoperiod interpretation modulates phenological timing in Atlantic salmon

Photoperiod, the portion of 24-h cycle during which an organism is exposed to illumination, is an important phenological cue in many animals. However, despite its influence on critical biological processes, there remain many unknowns regarding how variations in light intensity translate into perceived photoperiod. This experiment examined how light intensity variations affect perceived photoperiod in Atlantic salmon (Salmo salar) to determine whether photoperiod interpretation is, a) fixed such that anything above a minimum detection threshold is regarded as 'illumination', or b) adaptive and varies with recent light exposure. To do this we compared the frequency of smoltification and sexual maturation between groups of male parr which were exposed to one of eight light regimes on a 12:12 cycling regime (12-hour day/12-hour night). The eight regimes were divided into two treatments, four with 'High' daytime light intensity and four with 'Low' daytime light intensity. The 'High' and 'Low' intensity treatments were each sub-divided into four groups for which the subjective 'night' light intensity was 100%, 10%, 1% and 0% of the daytime light intensity, with four replicate tanks of each treatment. The results show that above a minimum detection threshold, Atlantic salmon have adaptive photoperiod interpretation which varies with recent light exposure, and that adaptive photoperiod interpretation modulates the timing of the parr-smolt transformation and sexual maturation. Further, we show that photoperiod interpretation varies between closely related families. Given the influence of phenological timing on species survival, our results reveal a critical role for integration of photoperiod interpretation in attempts to understand how geographically shifting thermal niches due to climate change will affect future populations.

Bird community structure is driven by urbanization level, blue-green infrastructure configuration and precision farming in Taizhou, China

Land use/land cover (LULC) changes and high urbanization rates are the main drivers of avian habitat loss in developing countries. However, few studies have examined the effects of urbanization intensity on avian diversity distribution and its importance in guiding eco-friendly urban planning. We surveyed bird distribution (n = 67 species) in different seasons using local ecological knowledge (LEK) and transect line methods in Jiangyan District from July 2018 to May 2019. One-way analysis of variance (ANOVA) was used to assess the effects of urbanization levels on birds relative density and richness during spring-summer (breeding season) and autumn-winter seasons (non-breeding season). Generalized linear models (GLM) were identified for the landscape composition and configuration that drive relative density and richness in native bird communities. Using redundancy analysis (RDA), we identified the landscape composition and configuration factors affecting bird foraging and roosting at urbanization levels. The results showed high dependency of waders and granivores on paddy fields and dry arable land respectively during the breeding season. During non-breeding season, wetland abundance, land cover, connectivity and total area of BGI were important habitat factors in attracting birds. Moreover, the landscape composition and configuration factors of BGI: wetlands as well as farmland habitats, are the main environmental cues that influence bird foraging. Therefore, to increase habitat suitability over landscape matrix, we propose creation of multiple waterbodies and green corridors of variable types and sizes on natural patches to improve the connectivity of ecological network. We also recommend land management interventions in farmland ecosystems, which could contribute to natural habitat restoration and improve bird biodiversity in urban areas.

Simulation-Based Evaluation of Methods, Data Types, and Temporal Sampling Schemes for Detecting Recent Population Declines

Understanding recent population trends is critical to quantifying species vulnerability and implementing effective management strategies. To evaluate the accuracy of genomic methods for quantifying recent declines (beginning <120 generations ago), we simulated genomic data using forward-time methods (SLiM) coupled with coalescent simulations (msprime) under a number of demographic scenarios. We evaluated both site frequency spectrum (SFS)-based methods (momi2, Stairway Plot) and methods that employ linkage disequilibrium information (NeEstimator, GONE) with a range of sampling schemes (contemporary-only samples, sampling two time points, and serial sampling) and data types (RAD-like data and whole-genome sequencing). GONE and momi2 performed best overall, with >80% power to detect severe declines with large sample sizes. Two-sample and serial sampling schemes could accurately reconstruct changes in population size, and serial sampling was particularly valuable for making accurate inferences when genotyping errors or minor allele frequency cutoffs distort the SFS or under model mis-specification. However, sampling only contemporary individuals provided reliable inferences about contemporary size and size change using either site frequency or linkage-based methods, especially when large sample sizes or whole genomes from contemporary populations were available. These findings provide a guide for researchers designing genomics studies to evaluate recent demographic declines.

Application of Omics Tools in Designing and Monitoring Marine Protected Areas For a Sustainable Blue Economy

A key component of the global blue economy strategy is the sustainable extraction of marine resources and conservation of marine environments through networks of marine protected areas (MPAs). Connectivity and representativity are essential factors that underlie successful implementation of MPA networks, which can safeguard biological diversity and ecosystem function, and ultimately support the blue economy strategy by balancing ocean use with conservation. New “big data” omics approaches, including genomics and transcriptomics, are becoming essential tools for the development and maintenance of MPA networks. Current molecular omics techniques, including population-scale genome sequencing, have direct applications for assessing population connectivity and for evaluating how genetic variation is represented within and among MPAs. Effective baseline characterization and long-term, scalable, and comprehensive monitoring are essential for successful MPA management, and omics approaches hold great promise to characterize the full range of marine life, spanning the microbiome to megafauna across a range of environmental conditions (shallow sea to the deep ocean). Omics tools, such as eDNA metabarcoding can provide a cost-effective basis for biodiversity monitoring in large and remote conservation areas. Here we provide an overview of current omics applications for conservation planning and monitoring, with a focus on metabarcoding, metagenomics, and population genomics. Emerging approaches, including whole-genome sequencing, characterization of genomic architecture, epigenomics, and genomic vulnerability to climate change are also reviewed. We demonstrate that the operationalization of omics tools can enhance the design, monitoring, and management of MPAs and thus will play an important role in a modern and comprehensive blue economy strategy.

Genetic approaches for increasing fitness in endangered species

The global rate of wildlife extinctions is accelerating, and the persistence of many species requires conservation breeding programs. A central paradigm of these programs is to preserve the genetic diversity of the founder populations. However, this may preserve original characteristics that make them vulnerable to extinction. We introduce targeted genetic intervention (TGI) as an alternative approach that promotes traits that enable species to persist in the face of threats by changing the incidence of alleles that impact on fitness. The TGI toolkit includes methods with established efficacy in model organisms and agriculture but are largely untried for conservation, such as synthetic biology and artificial selection. We explore TGI approaches as a species-restoration tool for intractable threats including infectious disease and climate change.

Conservation genetics as a management tool: The five best-supported paradigms to assist the management of threatened species

About 50 y ago, Crow and Kimura [An Introduction to Population Genetics Theory (1970)] and Ohta and Kimura [Genet. Res. 22, 201-204 (1973)] laid the foundations of conservation genetics by predicting the relationship between population size and genetic marker diversity. This work sparked an enormous research effort investigating the importance of population dynamics, in particular small population size, for population mean performance, population viability, and evolutionary potential. In light of a recent perspective [J. C. Teixeira, C. D. Huber, Proc. Natl. Acad. Sci. U.S.A. 118, 10 (2021)] that challenges some fundamental assumptions in conservation genetics, it is timely to summarize what the field has achieved, what robust patterns have emerged, and worthwhile future research directions. We consider theory and methodological breakthroughs that have helped management, and we outline some fundamental and applied challenges for conservation genetics.

Environmentally associated chromosomal structural variation influences fine-scale population structure of Atlantic Salmon (Salmo salar)

Chromosomal rearrangements (e.g., inversions, fusions, and translocations) have long been associated with environmental variation in wild populations. New genomic tools provide the opportunity to examine the role of these structural variants in shaping adaptive differences within and among wild populations of non-model organisms. In Atlantic Salmon (Salmo salar), variations in chromosomal rearrangements exist across the species natural range, yet the role and importance of these structural variants in maintaining adaptive differences among wild populations remains poorly understood. We genotyped Atlantic Salmon (n = 1429) from 26 populations within a highly genetically structured region of southern Newfoundland, Canada with a 220K SNP array. Multivariate analysis, across two independent years, consistently identified variation in a structural variant (translocation between chromosomes Ssa01 and Ssa23), previously associated with evidence of trans-Atlantic secondary contact, as the dominant factor influencing population structure in the region. Redundancy analysis suggested that variation in the Ssa01/Ssa23 chromosomal translocation is strongly correlated with temperature. Our analyses suggest environmentally mediated selection acting on standing genetic variation in genomic architecture introduced through secondary contact may underpin fine-scale local adaptation in Placentia Bay, Newfoundland, Canada, a large and deep embayment, highlighting the importance of chromosomal structural variation as a driver of contemporary adaptive divergence.

Summer Is Coming! Tackling Ocean Warming in Atlantic Salmon Cage Farming

Atlantic salmon (Salmo salar) cage farming has traditionally been located at higher latitudes where cold seawater temperatures favor this practice. However, these regions can be impacted by ocean warming and heat waves that push seawater temperature beyond the thermo-tolerance limits of this species. As more mass mortality events are reported every year due to abnormal sea temperatures, the Atlantic salmon cage aquaculture industry acknowledges the need to adapt to a changing ocean. This paper reviews adult Atlantic salmon thermal tolerance limits, as well as the deleterious eco-physiological consequences of heat stress, with emphasis on how it negatively affects sea cage aquaculture production cycles. Biotechnological solutions targeting the phenotypic plasticity of Atlantic salmon and its genetic diversity, particularly that of its southernmost populations at the limit of its natural zoogeographic distribution, are discussed. Some of these solutions include selective breeding programs, which may play a key role in this quest for a more thermo-tolerant strain of Atlantic salmon that may help the cage aquaculture industry to adapt to climate uncertainties more rapidly, without compromising profitability. Omics technologies and precision breeding, along with cryopreservation breakthroughs, are also part of the available toolbox that includes other solutions that can allow cage farmers to continue to produce Atlantic salmon in the warmer waters of the oceans of tomorrow.

Climate change threatens Chinook salmon throughout their life cycle

Widespread declines in Atlantic and Pacific salmon (Salmo salar and Oncorhynchus spp.) have tracked recent climate changes, but managers still lack quantitative projections of the viability of any individual population in response to future climate change. To address this gap, we assembled a vast database of survival and other data for eight wild populations of threatened Chinook salmon (O. tshawytscha). For each population, we evaluated climate impacts at all life stages and modeled future trajectories forced by global climate model projections. Populations rapidly declined in response to increasing sea surface temperatures and other factors across diverse model assumptions and climate scenarios. Strong density dependence limited the number of salmon that survived early life stages, suggesting a potentially efficacious target for conservation effort. Other solutions require a better understanding of the factors that limit survival at sea. We conclude that dramatic increases in smolt survival are needed to overcome the negative impacts of climate change for this threatened species.

Detecting population declines via monitoring the effective number of breeders (Nb )

Estimating the effective population size and effective number of breeders per year (N_b ) can facilitate early detection of population declines. We used computer simulations to quantify bias and precision of the one-sample LDNe estimator of N_b in age-structured populations using a range of published species life history types, sample sizes, and DNA markers. N_b estimates were biased by ~5%-10% when using SNPs or microsatellites in species ranging from fishes to mosquitoes, frogs, and seaweed. The bias (high or low) was similar for different life history types within a species suggesting that life history variation in populations will not influence N_b estimation. Precision was higher for 100 SNPs (H ≈ 0.30) than for 15 microsatellites (H ≈ 0.70). Confidence intervals (CIs) were occasionally too narrow, and biased high when N_b was small (N_b  < 50); however, the magnitude of bias would unlikely influence management decisions. The CIs (from LDNe) were sufficiently narrow to achieve high statistical power (≥0.80) to reject the null hypothesis that N_b  = 50 when the true N_b  = 30 and when sampling 50 individuals and 200 SNPs. Similarly, CIs were sufficiently narrow to reject N_b  = 500 when the true N_b  = 400 and when sampling 200 individuals and 5,000 loci. Finally, we present a linear regression method that provides high power to detect a decline in N_b when sampling at least five consecutive cohorts. This study provides guidelines and tools to simulate and estimate N_b for age structured populations (https://github.com/popgengui/agestrucnb/), which should help biologists develop sensitive monitoring programmes for early detection of changes in N_b and population declines.

Population genomics for wildlife conservation and management

Biodiversity is under threat worldwide. Over the past decade, the field of population genomics has developed across nonmodel organisms, and the results of this research have begun to be applied in conservation and management of wildlife species. Genomics tools can provide precise estimates of basic features of wildlife populations, such as effective population size, inbreeding, demographic history and population structure, that are critical for conservation efforts. Moreover, population genomics studies can identify particular genetic loci and variants responsible for inbreeding depression or adaptation to changing environments, allowing for conservation efforts to estimate the capacity of populations to evolve and adapt in response to environmental change and to manage for adaptive variation. While connections from basic research to applied wildlife conservation have been slow to develop, these connections are increasingly strengthening. Here we review the primary areas in which population genomics approaches can be applied to wildlife conservation and management, highlight examples of how they have been used, and provide recommendations for building on the progress that has been made in this field.

Genome-wide genetic diversity yields insights into genomic responses of candidate climate-selected loci in an Andean wetland plant

Assessing population evolutionary potential has become a central tenet of conservation biology. Since adaptive responses require allelic variation at functional genes, consensus has grown that genetic variation at genes under selection is a better surrogate for adaptive evolutionary potential than neutral genetic diversity. Although consistent with prevailing theory, this argument lacks empirical support and ignores recent theoretical advances questioning the very concept of neutral genetic diversity. In this study, we quantified genome-wide responses of single nucleotide polymorphism loci linked to climatic factors over a strong latitudinal gradient in natural populations of the high Andean wetland plant, Carex gayana, and then assessed whether genetic variation of candidate climate-selected loci better predicted their genome-wide responses than genetic variation of non-candidate loci. Contrary to this expectation, genomic responses of climate-linked loci only related significantly to environmental variables and genetic diversity of non-candidate loci. The effects of genome-wide genetic diversity detected in this study may be a result of either the combined influence of small effect variants or neutral and demographic factors altering the adaptive evolutionary potential of C. gayana populations. Regardless of the processes involved, our results redeem genome-wide genetic diversity as a potentially useful indicator of population adaptive evolutionary potential.

Snake River sockeye and Chinook salmon in a changing climate: Implications for upstream migration survival during recent extreme and future climates

In 2015, the Pacific marine heat wave, low river flows, and record high water temperatures in the Columbia River Basin contributed to a near-complete failure of the adult migration of endangered Snake River sockeye salmon (Oncorhynchus nerka, NOAA Fisheries 2016). These extreme weather events may become the new normal due to anthropogenic climate change, with catastrophic consequences for endangered species. Existing anthropogenic pressures may amplify vulnerability to climate change, but these potential synergies have rarely been quantified. We examined factors affecting survival of endangered sockeye (Oncorhynchus nerka) and threatened Chinook salmon (O. tshawytscha) as they migrated upstream through eight dams and reservoirs to spawning areas in the Snake River Basin. Our extensive database included histories of 17,279 individual fish that migrated since 2004. A comparison between conditions in 2015 and daily temperatures and flows in a regulated basin forced by output from global climate models showed that 2015 did have many characteristics of projected future mean conditions. To evaluate potential salmon responses, we modeled migration timing and apparent survival under historical and future climate scenarios (2040s). For Chinook salmon, adult survival from the first dam encountered to spawning grounds dropped by 4-15%, depending on the climate scenario. For sockeye, survival dropped by ~80% from their already low levels. Through sensitivity analyses, we observed that the adult sockeye migration would need to shift more than 2 weeks earlier than predicted to maintain survival rates typical of those seen during 2008-2017. Overall, the greater impacts of climate change on adult sockeye compared with adult Chinook salmon reflected differences in life history and environmental sensitivities, which were compounded for sockeye by larger effect sizes from other anthropogenic factors. Compared with Chinook, sockeye was more negatively affected by a history of juvenile transportation and by similar temperatures and flows. The largest changes in temperature and flow were projected to be upstream from the hydrosystem, where direct mitigation through hydrosystem management is not an option. Unfortunately, Snake River sockeye have likely lost much of their adaptive capacity with the loss of the wild population. Further work exploring habitat restoration or additional mitigation actions is urgently needed.

Predicting Thermal Adaptation by Looking Into Populations' Genomic Past

Molecular evolution offers an insightful theory to interpret the genomic consequences of thermal adaptation to previous events of climate change beyond range shifts. However, disentangling often mixed footprints of selective and demographic processes from those due to lineage sorting, recombination rate variation, and genomic constrains is not trivial. Therefore, here we condense current and historical population genomic tools to study thermal adaptation and outline key developments (genomic prediction, machine learning) that might assist their utilization for improving forecasts of populations' responses to thermal variation. We start by summarizing how recent thermal-driven selective and demographic responses can be inferred by coalescent methods and in turn how quantitative genetic theory offers suitable multi-trait predictions over a few generations via the breeder's equation. We later assume that enough generations have passed as to display genomic signatures of divergent selection to thermal variation and describe how these footprints can be reconstructed using genome-wide association and selection scans or, alternatively, may be used for forward prediction over multiple generations under an infinitesimal genomic prediction model. Finally, we move deeper in time to comprehend the genomic consequences of thermal shifts at an evolutionary time scale by relying on phylogeographic approaches that allow for reticulate evolution and ecological parapatric speciation, and end by envisioning the potential of modern machine learning techniques to better inform long-term predictions. We conclude that foreseeing future thermal adaptive responses requires bridging the multiple spatial scales of historical and predictive environmental change research under modern cohesive approaches such as genomic prediction and machine learning frameworks.

Effects of global warming on sex ratios in fishes

In fishes, sex is determined by genetics, the environment or an interaction of both. Temperature is among the most important environmental factors that can affect sex determination. As a consequence, changes in temperature at critical developmental stages can induce biases in primary sex ratios in some species. However, early sex ratios can also be biased by sex-specific tolerances to environmental stresses that may, in some cases, be amplified by changes in water temperature. Sex-specific reactions to environmental stress have been observed at early larval stages before gonad formation starts. It is therefore necessary to distinguish between temperature effects on sex determination, generally acting through the stress axis or epigenetic mechanisms, and temperature effects on sex-specific mortality. Both are likely to affect sex ratios and hence population dynamics. Moreover, in cases where temperature effects on sex determination lead to genotype-phenotype mismatches, long-term effects on population dynamics are possible, for example temperature-induced masculinization potentially leading to the loss of Y chromosomes or feminization to male-biased operational sex ratios in future generations. To date, most studies under controlled conditions conclude that if temperature affects sex ratios, elevated temperatures mostly lead to a male bias. The few studies that have been performed on wild populations seem to confirm this general trend. Recent findings suggest that transgenerational plasticity could mitigate the effects of warming on sex ratios in some populations.

aTBP: A versatile tool for fish genotyping

Animal Tubulin-Based-Polymorphism (aTBP), an intron length polymorphism method recently developed for vertebrate genotyping, has been successfully applied to the identification of several fish species. Here, we report data that demonstrate the ability of the aTBP method to assign a specific profile to fish species, each characterized by the presence of commonly shared amplicons together with additional intraspecific polymorphisms. Within each aTBP profile, some fragments are also recognized that can be attributed to taxonomic ranks higher than species, e.g. genus and family. Versatility of application across different taxonomic ranks combined with the presence of a significant number of DNA polymorphisms, makes the aTBP method an additional and useful tool for fish genotyping, suitable for different purposes such as species authentication, parental recognition and detection of allele variations in response to environmental changes.

Multiple decades of stocking has resulted in limited hatchery introgression in wild brook trout (Salvelinus fontinalis) populations of Nova Scotia

Many populations of freshwater fishes are threatened with losses, and increasingly, the release of hatchery individuals is one strategy being implemented to support wild populations. However, stocking of hatchery individuals may pose long-term threats to wild populations, particularly if genetic interactions occur between wild and hatchery individuals. One highly prized sport fish that has been heavily stocked throughout its range is the brook trout (Salvelinus fontinalis). In Nova Scotia, Canada, hatchery brook trout have been stocked since the early 1900s, and despite continued stocking efforts, populations have suffered declines in recent decades. Before this study, the genetic structure of brook trout populations in the province was unknown; however, given the potential negative consequences associated with hatchery stocking, it is possible that hatchery programs have adversely affected the genetic integrity of wild populations. To assess the influence of hatchery supplementation on wild populations, we genotyped wild brook trout from 12 river systems and hatchery brook trout from two major hatcheries using 100 microsatellite loci. Genetic analyses of wild trout revealed extensive population genetic structure among and within river systems and significant isolation-by-distance. Hatchery stocks were genetically distinct from wild populations, and most populations showed limited to no evidence of hatchery introgression (<5% hatchery ancestry). Only a single location had a substantial number of hatchery-derived trout and was located in the only river where a local strain is used for supplementation. The amount of hatchery stocking within a watershed did not influence the level of hatchery introgression. Neutral genetic structure of wild populations was influenced by geography with some influence of climate and stocking indices. Overall, our study suggests that long-term stocking has not significantly affected the genetic integrity of wild trout populations, highlighting the variable outcomes of stocking and the need to evaluate the consequences on a case-by-case basis.

Long-term stocking practices threaten the original genetic diversity of the southernmost European populations of Atlantic salmon Salmo salar

Many Atlantic salmon Salmo salar populations in Europe are threatened by previous stocking with foreign hatchery strains. Temporal patterns of genetic characteristics of salmon from northern Spain, the southernmost European populations, were compared before and after species decline and heavy stocking with specimens from northern Europe. Eleven microsatellite loci were analysed in archival (scales from 1958-1960) and contemporary (2007-2008) samples from the River Sella. Temporal analyses revealed a similar heterozygosity between archival and contemporary samples, despite a drastic decrease in population abundance, while the contemporary sample showed a higher allelic richness due to the occurrence of foreign alleles. Considering only the alleles with at least 4% frequency in the archival sample, 2 alleles exclusive to the River Sella were absent in the contemporary sample, and 14 alleles showed a decrease of at least 4% frequency. Four alleles common in Scotland showed a high occurrence in the contemporary sample, so they are good candidates as markers of introgression of foreign genes. The heavy stocking with non-native Scottish broodstocks between 1970 and 1990 caused the introgression found in the contemporary sample when compared with the pristine population. An abrupt decrease was evident when the estimates of effective number of breeders were adjusted to take into account overlapping generations (NbAdj), effective population size (NeAdj) estimated from NbAdj, and number of breeders estimated using the sibship assignment method (NbSIB). The very low effective size values found in the contemporary sample, together with the detrimental synergy between genetic drift and high rates of introgression, represent a severe risk for the conservation of native salmon.

Northern European Salmo trutta (L.) populations are genetically divergent across geographical regions and environmental gradients

The salmonid fish Brown trout is iconic as a model for the application of conservation genetics to understand and manage local interspecific variation. However, there is still scant information about relationships between local and large-scale population structure, and to what extent geographical and environmental variables are associated with barriers to gene flow. We used information from 3,782 mapped SNPs developed for the present study and conducted outlier tests and gene-environment association (GEA) analyses in order to examine drivers of population structure. Analyses comprised >2,600 fish from 72 riverine populations spanning a central part of the species' distribution in northern Europe. We report hitherto unidentified genetic breaks in population structure, indicating strong barriers to gene flow. GEA loci were widely spread across genomic regions and showed correlations with climatic, abiotic and geographical parameters. In some cases, individual loci showed consistent GEA across the geographical regions Britain, Europe and Scandinavia. In other cases, correlations were observed only within a sub-set of regions, suggesting that locus-specific variation was associated with local processes. A paired-population sampling design allowed us to evaluate sampling effects on detection of outlier loci and GEA. Two widely applied methods for outlier detection (pcadapt and bayescan) showed low overlap in loci identified as statistical outliers across sub-sets of data. Two GEA analytical approaches (LFMM and RDA) showed good correspondence concerning loci associated with specific variables, but LFMM identified five times more statistically significant associations than RDA. Our results emphasize the importance of carefully considering the statistical methods applied for the hypotheses being tested in outlier analysis. Sampling design may have lower impact on results if the objective is to identify GEA loci and their population distribution. Our study provides new insights into trout populations, and results have direct management implications in serving as a tool for identification of conservation units.

Conservation and Management of Salmon in the Age of Genomics

Salmon were among the first nonmodel species for which systematic population genetic studies of natural populations were conducted, often to support management and conservation. The genomics revolution has improved our understanding of the evolutionary ecology of salmon in two major ways: (a) Large increases in the numbers of genetic markers (from dozens to 10⁴-10⁶) provide greater power for traditional analyses, such as the delineation of population structure, hybridization, and population assignment, and (b) qualitatively new insights that were not possible with traditional genetic methods can be achieved by leveraging detailed information about the structure and function of the genome. Studies of the first type have been more common to date, largely because it has taken time for the necessary tools to be developed to fully understand the complex salmon genome. We expect that the next decade will witness many new studies that take full advantage of salmonid genomic resources.