Dataset - Gene flow and migration routes in Salmo trutta L

Understanding gene flow can help biodiversity to mitigate habitat changes by contributing to inform and design protected areas. The seascape is composed of heterogeneous landscapes where resources are unevenly distributed. The brown trout, Salmo trutta, displays a multitude of life-history strategies and represents an ideal model for applications in conservation genetics. Information on trout migrations at sea and the effects of abiotic factors on the species dispersal remains limited. Using a panel of 185 single nucleotide polymorphism markers, the present study aimed to explore the population structure of the brown trout and in the English Channel. The genotypes of 2,729 individual trout from 88 rivers were obtained across England and France. Population structure revealed the presence isolation by distance (R² = 0.464) and the presence of genetic clusters spatially located following an east/west gradient. The maximum threshold distance between genetic distance and geographic distance was 344 km. The measure appeared relative to the studied spatial environment and reflected Salmo trutta capacity to achieve long migration distances. A machine-learning framework derived from a gradient forest analysis was used to generate a resistance surface using changes in allelic frequencies and environmental predicators. The resulting surface identified areas limiting gene flow. On the British coast, a clear genetic break was observed along the Jurassic coast, whereas the Cotentin peninsula acted as a physical barrier to gene flow among French coastal populations. Salmo trutta populations appeared to be differently affected by environmental factors which might reflect demes preference to specific breeding ground. Using our resistance map, we extended from an IBD model to an isolation by resistance approach and computed the distance of maximum correlation (DMC) using cost distance which allowed the pruning of our genetic graph. The resulting least cost path connections were mapped to reveal the main dispersal routes. Finally, a prioritization analysis using connectivity surface was implemented to design potential MPAs.