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Genetic population structure of marine fish: mismatch between biological and fisheries management units
Author(s) -
Reiss Henning,
Hoarau Galice,
DickeyCollas Mark,
Wolff Wim J.
Publication year - 2009
Publication title -
fish and fisheries
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.747
H-Index - 109
eISSN - 1467-2979
pISSN - 1467-2960
DOI - 10.1111/j.1467-2979.2008.00324.x
Subject(s) - fisheries management , clupea , fishery , population , biology , genetic structure , context (archaeology) , merluccius merluccius , hake , herring , fishing , genetic diversity , fish <actinopterygii> , paleontology , demography , sociology
Abstract An essential prerequisite of a sustainable fisheries management is the matching of biologically relevant processes and management action. In fisheries management and assessment, fish stocks are the fundamental biological unit, but the reasoning for the operational management unit is often indistinct and mismatches between the biology and the management action frequently occur. Despite the plethora of population genetic data on marine fishes, to date little or no use is made of the information, despite the fact that the detection of genetic differentiation may indicate reproductively distinct populations. Here, we discuss key aspects of genetic population differentiation in the context of their importance for fisheries management. Furthermore, we evaluate the population structure of all 32 managed marine fish species in the north‐east Atlantic and relate this structure to current management units and practice. Although a large number of studies on genetic population structure have been published in the last decades, data are still rare for most exploited species. The mismatch between genetic population structure and the current management units found for six species ( Gadus morhua , Melanogrammus aeglefinus , Merlangius merlangus, Micromesistius poutassou, Merluccius merluccius and Clupea harengus ), emphasizes the need for a revision of these units and questions the appropriateness of current management measures. The implementation of complex and dynamic population structures into novel and less static management procedures should be a primary task for future fisheries management approaches.

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