Coastal migration patterns of the four largest Barents Sea Atlantic salmon stocks inferred using genetic stock identification methods

Abstract Combining detailed temporal and spatial catch data, including catch per unit effort, with a high-resolution microsatellite genetic baseline facilitated the development of stock-specific coastal migration models for the four largest Atlantic salmon (Salmo salar) populations, Målselv, Alta, T...

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Bibliographic Details
Published in:ICES Journal of Marine Science
Main Authors: Svenning, Martin-A, Falkegård, Morten, Niemelä, Eero, Vähä, Juha-Pekka, Wennevik, Vidar, Ozerov, Mikhail, Prusov, Sergey, Dempson, J Brian, Power, Michael, Fauchald, Per
Other Authors: Gomez-Uchida, Daniel, Norwegian Research Council
Format: Article in Journal/Newspaper
Language:English
Published: Oxford University Press (OUP) 2019
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Online Access:http://dx.doi.org/10.1093/icesjms/fsz114
http://academic.oup.com/icesjms/article-pdf/76/6/1379/31247409/fsz114.pdf
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Summary:Abstract Combining detailed temporal and spatial catch data, including catch per unit effort, with a high-resolution microsatellite genetic baseline facilitated the development of stock-specific coastal migration models for the four largest Atlantic salmon (Salmo salar) populations, Målselv, Alta, Tana and Kola rivers, contributing to the Barents Sea mixed-stock fishery. Målselv salmon displayed a restricted coastal movement with 85% of the fish captured within 20 km of their natal river. Kola salmon also demonstrated limited coastal movements in Norwegian waters, with most (> 90%) caught in eastern Finnmark. Multi-sea-winter (MSW) Alta salmon were caught west of Alta fjord across a broader stretch of coast while one-sea-winter (1SW) fish migrated more extensively along the coast prior to river entry. Tana salmon, however, were detected over a broad expanse (600 km) of the North-Norwegian coast. For all populations MSW salmon dominating catches earlier in the season (May–June) while 1SW fish were more common from July to August. This study provides an example of how traditional catch and effort information may be combined with genetic methods to obtain insights into spatial and temporal changes in Atlantic salmon catch composition and their associated migration patterns in a mixed-stock coastal fishery.