Reconciling seascape genetics and fisheries science in three codistributed flatfishes.

Autor: Vandamme S; Laboratory of Biodiversity and Evolutionary Genomics KU Leuven Leuven Belgium.; Animal Sciences Unit - Fisheries and Aquatic Production Flanders Research Institute for Agriculture, Fisheries and Food (ILVO) Oostende Belgium.; Department of Animal Sciences and Aquatic Ecology Ghent University Oostende Belgium., Raeymaekers JAM; Laboratory of Biodiversity and Evolutionary Genomics KU Leuven Leuven Belgium.; Faculty of Biosciences and Aquaculture Nord University Bodø Norway., Maes GE; Laboratory of Biodiversity and Evolutionary Genomics KU Leuven Leuven Belgium.; Centre for Sustainable Tropical Fisheries and Aquaculture Comparative Genomics Centre College of Sciences and Engineering James Cook University Townsville QLD Australia.; Center for Human Genetics Genomics Core KU Leuven Leuven Belgium., Cottenie K; Department of Integrative Biology University of Guelph Guelph ON Canada., Calboli FCF; Laboratory of Biodiversity and Evolutionary Genomics KU Leuven Leuven Belgium., Diopere E; Laboratory of Biodiversity and Evolutionary Genomics KU Leuven Leuven Belgium., Volckaert FAM; Laboratory of Biodiversity and Evolutionary Genomics KU Leuven Leuven Belgium.; CeMEB Department of Marine Sciences University of Gothenburg Gothenburg Sweden.
Jazyk: angličtina
Zdroj: Evolutionary applications [Evol Appl] 2020 Nov 02; Vol. 14 (2), pp. 536-552. Date of Electronic Publication: 2020 Nov 02 (Print Publication: 2021).
DOI: 10.1111/eva.13139
Abstrakt: Uncertainty hampers innovative mixed-fisheries management by the scales at which connectivity dynamics are relevant to management objectives. The spatial scale of sustainable stock management is species-specific and depends on ecology, life history and population connectivity. One valuable approach to understand these spatial scales is to determine to what extent population genetic structure correlates with the oceanographic environment. Here, we compare the level of genetic connectivity in three codistributed and commercially exploited demersal flatfish species living in the North East Atlantic Ocean. Population genetic structure was analysed based on 14, 14 and 10 neutral DNA microsatellite markers for turbot, brill and sole, respectively. We then used redundancy analysis (RDA) to attribute the genetic variation to spatial (geographical location), temporal (sampling year) and oceanographic (water column characteristics) components. The genetic structure of turbot was composed of three clusters and correlated with variation in the depth of the pycnocline, in addition to spatial factors. The genetic structure of brill was homogenous, but correlated with average annual stratification and spatial factors. In sole, the genetic structure was composed of three clusters, but was only linked to a temporal factor. We explored whether the management of data poor commercial fisheries, such as in brill and turbot, might benefit from population-specific information. We conclude that the management of fish stocks has to consider species-specific genetic structures and may benefit from the documentation of the genetic seascape and life-history traits.
Competing Interests: None declared.
(© 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)
Databáze: MEDLINE
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