Quantifying genetic effects of escaped farmed salmon on wild salmon

The QuantEscape knowledge platform combines expertise from four central research institutions that study interactions between escaped farmed and wild Atlantic salmon Salmo salar from different perspectives: population genetics, ecology, genomics, and quantitative genetics. The proposal was designed to meet all of the ambitions of the knowledge platform announced by the RCN Havbruk programme. We made use of a set of Single Nucleotide Polymorphisms (SNPs) that collectively are diagnostic for farmed and wild Atlantic salmon, and developed a statistical method to estimate farmed to wild introgression in individuals and populations. This tool was used to quantify gene flow from farmed to wild salmon in 147 populations, of which one half showed significant genetic introgression. There was a significant correlation between the average proportions of escaped farmed salmon in the rivers and introgression, and a higher coefficient of determination for aggregate county data than river data. Further analyses will identify factors that facilitate or limit gene flow from farmed to wild fish by including characteristics of the rivers and their salmon populations in the analyses. Analyses are also underway that investigate how genetic introgression affects the life history of wild individuals from large- and small-sized salmon populations. In controlled (ongoing) experiments, we quantify how farmed salmon change in response to natural selection, and investigate how their offspring perform in competition with wild juveniles with and without potential threats from larger trout. Detailed genomic studies of the breeding lines of farmed salmon have been explored to establish genetic signatures of artificial selection in farmed salmon, and also to study to what extent these signatures are evident among their offspring in the wild. Genomic analyses have been used to identify a large-effect locus controlling sea age at maturity in Atlantic salmon, with potential applications to management of both farmed and wild salmon, as well as their interactions. Genomic analyses are also employed to identify more powerful sets of genetic markers for future studies of genetic interactions between farmed and wild salmon. The combined genetic knowledge gained by the platform are being used to parameterize and refine models to predict the current and future fitness of wild salmon populations receiving escaped farmed salmon. Knowledge acquired through the QuantEscape knowledge platform has been used to inform national (Environment Agency, Fisheries Directorate) and international (ICES, NASCO) advice and management bodies and will contribute to the sustainable management of farmed and wild Atlantic salmon. Finally, QuantEscape will benefit the aquaculture industry and wild salmon fisheries and tourism by providing guidelines for sustainable development of aquaculture.

This proposal combines expertise from four central research institutions that study interactions between escaped farmed and wild Atlantic salmon Salmo salar from different perspectives: population genetics, ecology, genomics, and quantitative genetics. Th e proposal is designed to meet all of the ambitions of the knowledge platform announced by the RCN Havbruk programme. Our proposal will make use of recently developed molecular genetic tools to identify farmed and wild salmon. The tool (single nucleotide polymorphisms) will be used to quantify gene flow from farmed to wild salmon in a large set of populations. Moreover, we will combine this information with data on the proportions of escaped farmed salmon in the rivers, and with characteristics of the riv ers and their salmon populations, to identify factors that facilitate or limit gene flow from farmed to wild fish. In controlled experiments, we will quantify how farmed salmon change in response to natural selection. Detailed genomic studies of the breed ing lines of farmed salmon will be explored to establish genetic signatures of artificial selection in farmed salmon, and also to study to what extent these signatures are evident among their offspring in the wild. Genomic analyses will also be employed t o identify more powerful sets of genetic markers for future studies of genetic interactions between farmed and wild salmon. The combined genetic knowledge gained by the platform will be used to parameterize and refine models to predict the future of wild salmon populations receiving escaped farmed salmon. The knowledge platform will contribute to the sustainable management of farmed and wild Atlantic salmon, and also benefit the aquaculture industry and wild salmon fisheries and tourism by providing guide lines for sustainable development of aquaculture.