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Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
Authors:S G Vandamme  G E Maes  J A M Raeymaekers  K Cottenie  A K Imsland  B Hellemans  G Lacroix  E Mac Aoidh  J T Martinsohn  P Martínez  J Robbens  R Vilas  F A M Volckaert
Institution:1. Institute for Agricultural and Fisheries Research (ILVO), Animal Sciences Unit – Fisheries, , B‐8400 Ostend, Belgium;2. Laboratory of Biodiversity and Evolutionary Genomics, University of Leuven, , B‐3000 Leuven, Belgium;3. Centre for Sustainable Tropical Fisheries and Aquaculture, School of Marine and Tropical Biology, James Cook University, , Townsville, Qld, 4811 Australia;4. Zoological Institute, University of Basel, , CH‐4051 Basel, Switzerland;5. Laboratory of Aquatic Ecology, Evolution and Conservation, University of Leuven, , B‐3000 Leuven, Belgium;6. Department of Integrative Biology, University of Guelph, , Guelph, ON, Canada, N1G 2W1;7. Department of Biology, High Technology Centre, University of Bergen, , N‐5020 Bergen, Norway;8. Akvaplan‐niva, Iceland Office, , 201 Kopavogi, Iceland;9. Royal Belgian Institute of Natural Sciences, Operational Directorate Natural Environment, , B‐1200 Brussels, Belgium;10. Maritime Affairs Unit (G.04) – FISHREG Action, European Commission, Joint Research Centre, , I‐21027 Ispra, Italy;11. Departamento de Genética, Facultad de Veterinaria, Universidad de Santiago de Compostela, , 27002 Lugo, Spain
Abstract:Unravelling the factors shaping the genetic structure of mobile marine species is challenging due to the high potential for gene flow. However, genetic inference can be greatly enhanced by increasing the genomic, geographical or environmental resolution of population genetic studies. Here, we investigated the population structure of turbot (Scophthalmus maximus) by screening 17 random and gene‐linked markers in 999 individuals at 290 geographical locations throughout the northeast Atlantic Ocean. A seascape genetics approach with the inclusion of high‐resolution oceanographical data was used to quantify the association of genetic variation with spatial, temporal and environmental parameters. Neutral loci identified three subgroups: an Atlantic group, a Baltic Sea group and one on the Irish Shelf. The inclusion of loci putatively under selection suggested an additional break in the North Sea, subdividing southern from northern Atlantic individuals. Environmental and spatial seascape variables correlated marginally with neutral genetic variation, but explained significant proportions (respectively, 8.7% and 10.3%) of adaptive genetic variation. Environmental variables associated with outlier allele frequencies included salinity, temperature, bottom shear stress, dissolved oxygen concentration and depth of the pycnocline. Furthermore, levels of explained adaptive genetic variation differed markedly between basins (3% vs. 12% in the North and Baltic Sea, respectively). We suggest that stable environmental selection pressure contributes to relatively strong local adaptation in the Baltic Sea. Our seascape genetic approach using a large number of sampling locations and associated oceanographical data proved useful for the identification of population units as the basis of management decisions.
Keywords:adaptive genetic variation  microsatellite  oceanography  population structure     Scophthalmus maximus     seascape genetics
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