The utility of genetics in marine fisheries management: a simulation study based on Pacific cod off Alaska

Information on genetic population structure has been documented in many marine fish species, but it is not always incorporated into management plans. This study examines how conservation status and yield change when management units are established using genetic data versus treating the entire area...

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Bibliographic Details
Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Spies, Ingrid, Punt, André E.
Other Authors: Wilberg, Michael
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2015
Subjects:
Online Access:http://dx.doi.org/10.1139/cjfas-2014-0050
http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2014-0050
http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2014-0050
Description
Summary:Information on genetic population structure has been documented in many marine fish species, but it is not always incorporated into management plans. This study examines how conservation status and yield change when management units are established using genetic data versus treating the entire area as a single management unit. Simulations use a spatially structured, individual-based model that combines multilocus microsatellite genotypes and a traditional fish population dynamics model that establishes abundance-at-age by cohort. Results are considered in terms of marine fish species in general, and parameters in the model are based on Pacific cod (Gadus macrocephalus) in the Bering Sea and Aleutian Islands region of Alaska. Population dynamics are projected under several management strategies, some of which establish management units based on the results of genetic testing and some that do not. Simulations incorporate annual stock assessments and fishing for 100 years. Results show that managed fishing can result in a reduction in stock sizes below target reference points when distinct populations are not managed based on the results of genetic testing. However, stock size is maintained at target levels and catches may increase when stocks identified using genetics are managed separately, even given error rates inherent to genetic testing.