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Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus)
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.; Martinez, P.; Robbens, J.; Vilas, R.; Volckaert, F.A.M. (2014). Regional environmental pressure influences population differentiation in turbot (Scophthalmus maximus). Mol. Ecol. 23(3): 618-636. dx.doi.org/10.1111/mec.12628
In: Molecular Ecology. Blackwell: Oxford. ISSN 0962-1083; e-ISSN 1365-294X
Peer reviewed article  
Available in  Authors 
Keywords
    Scophthalmus maximus (Linnaeus, 1758) [WoRMS]
    Marine/Coastal
Author keywords
    adaptive genetic variation; microsatellite; oceanography; populationstructure; Scophthalmus maximus; seascape genetics
Authors  Top 
  • 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.
  • Martinez, P.
  • Robbens, J.
  • Vilas, R.
  • Volckaert, F.A.M.
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.
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