Genetic stock identification of Atlantic salmon and its evaluation in a large population complex

Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate among distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the...

Full description

Bibliographic Details
Published in:Canadian Journal of Fisheries and Aquatic Sciences
Main Authors: Vähä, Juha-Pekka, Erkinaro, Jaakko, Falkegård, Morten, Orell, Panu, Niemelä, Eero
Format: Article in Journal/Newspaper
Language:English
Published: Canadian Science Publishing 2017
Subjects:
Online Access:http://dx.doi.org/10.1139/cjfas-2015-0606
http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2015-0606
http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2015-0606
id crcansciencepubl:10.1139/cjfas-2015-0606
record_format openpolar
spelling crcansciencepubl:10.1139/cjfas-2015-0606 2024-09-15T17:56:07+00:00 Genetic stock identification of Atlantic salmon and its evaluation in a large population complex Vähä, Juha-Pekka Erkinaro, Jaakko Falkegård, Morten Orell, Panu Niemelä, Eero 2017 http://dx.doi.org/10.1139/cjfas-2015-0606 http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2015-0606 http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2015-0606 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Canadian Journal of Fisheries and Aquatic Sciences volume 74, issue 3, page 327-338 ISSN 0706-652X 1205-7533 journal-article 2017 crcansciencepubl https://doi.org/10.1139/cjfas-2015-0606 2024-08-29T04:08:48Z Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate among distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon (Salmo salar) population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (global F ST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed-stock fisheries. Article in Journal/Newspaper Atlantic salmon Salmo salar Canadian Science Publishing Canadian Journal of Fisheries and Aquatic Sciences 74 3 327 338
institution Open Polar
collection Canadian Science Publishing
op_collection_id crcansciencepubl
language English
description Addressing biocomplexity in fisheries management is a challenge requiring an ability to differentiate among distinct populations contributing to fisheries. We produced extensive genetic baseline data involving 36 sampling locations and 33 microsatellite markers, which allowed characterization of the genetic structure and diversity in a large Atlantic salmon (Salmo salar) population complex of the River Teno system, northernmost Europe. Altogether, we identified 28 hierarchically structured and genetically distinct population segments (global F ST = 0.065) corresponding exceptionally well with their geographical locations. An assessment of factors affecting the stock identification accuracy indicated that the identification success is largely defined by the interaction of genetic divergence and the baseline sample sizes. The choice between the two statistical methods tested for performance in genetic stock identification, ONCOR and cBAYES, was not critical, albeit the latter demonstrated slightly higher identification accuracy and lower sensitivity to population composition of the mixture sample. The strong genetic structuring among populations together with a powerful marker system allowed for accurate stock identification of individuals and enabled assessment of stock compositions contributing to mixed-stock fisheries.
format Article in Journal/Newspaper
author Vähä, Juha-Pekka
Erkinaro, Jaakko
Falkegård, Morten
Orell, Panu
Niemelä, Eero
spellingShingle Vähä, Juha-Pekka
Erkinaro, Jaakko
Falkegård, Morten
Orell, Panu
Niemelä, Eero
Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
author_facet Vähä, Juha-Pekka
Erkinaro, Jaakko
Falkegård, Morten
Orell, Panu
Niemelä, Eero
author_sort Vähä, Juha-Pekka
title Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_short Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_full Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_fullStr Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_full_unstemmed Genetic stock identification of Atlantic salmon and its evaluation in a large population complex
title_sort genetic stock identification of atlantic salmon and its evaluation in a large population complex
publisher Canadian Science Publishing
publishDate 2017
url http://dx.doi.org/10.1139/cjfas-2015-0606
http://www.nrcresearchpress.com/doi/full-xml/10.1139/cjfas-2015-0606
http://www.nrcresearchpress.com/doi/pdf/10.1139/cjfas-2015-0606
genre Atlantic salmon
Salmo salar
genre_facet Atlantic salmon
Salmo salar
op_source Canadian Journal of Fisheries and Aquatic Sciences
volume 74, issue 3, page 327-338
ISSN 0706-652X 1205-7533
op_rights http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining
op_doi https://doi.org/10.1139/cjfas-2015-0606
container_title Canadian Journal of Fisheries and Aquatic Sciences
container_volume 74
container_issue 3
container_start_page 327
op_container_end_page 338
_version_ 1810432330006790144