Regional environmental pressure influences population differentiation in turbot ( <scp>S</scp>cophthalmus maximus )

• Published in: Molecular Ecology
• Main Authors: Vandamme, S. G., Maes, G. E., Raeymaekers, J. A. M., Cottenie, K., Imsland, A. K., Hellemans, B., Lacroix, G., Mac Aoidh, E., Martinsohn, J. T., Martínez, P., Robbens, J., Vilas, R., Volckaert, F. A. M.
• Other Authors: ILVO
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2014
• Subjects: Genetics; Ecology, Evolution, Behavior and Systematics; Turbot
• Online Access: http://dx.doi.org/10.1111/mec.12628; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1111%2Fmec.12628; https://onlinelibrary.wiley.com/doi/pdf/10.1111/mec.12628

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 ( S cophthalmus maximus ) by screening 17 random and gene‐linked markers in 999 individuals at 290 geographical locations throughout the n ortheast A tlantic O cean. 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 A tlantic group, a B altic S ea group and one on the I rish S helf. The inclusion of loci putatively under selection suggested an additional break in the N orth S ea, subdividing southern from northern A tlantic 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.