Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment

Farmed Atlantic salmon escapees represent a significant threat to the genetic integrity of natural populations. Not all escapement events are reported, and consequently, there is a need to develop an effective tool for the identification of escapees. In this study, > 2200 salmon were collected fr...

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Published in:Aquaculture
Main Authors: Glover, Kevin A., Hansen, Michael Møller, Skaala, Oystein
Format: Article in Journal/Newspaper
Language:English
Published: 2009
Subjects:
Online Access:https://orbit.dtu.dk/en/publications/e388e7a2-9ac4-48f3-a166-0748ab802f4a
https://doi.org/10.1016/j.aquaculture.2009.01.034
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spelling ftdtupubl:oai:pure.atira.dk:publications/e388e7a2-9ac4-48f3-a166-0748ab802f4a 2024-09-15T17:56:18+00:00 Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment Glover, Kevin A. Hansen, Michael Møller Skaala, Oystein 2009 https://orbit.dtu.dk/en/publications/e388e7a2-9ac4-48f3-a166-0748ab802f4a https://doi.org/10.1016/j.aquaculture.2009.01.034 eng eng https://orbit.dtu.dk/en/publications/e388e7a2-9ac4-48f3-a166-0748ab802f4a info:eu-repo/semantics/restrictedAccess Glover , K A , Hansen , M M & Skaala , O 2009 , ' Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment ' , Aquaculture , vol. 290 , no. 1-2 , pp. 37-46 . https://doi.org/10.1016/j.aquaculture.2009.01.034 article 2009 ftdtupubl https://doi.org/10.1016/j.aquaculture.2009.01.034 2024-08-05T23:48:28Z Farmed Atlantic salmon escapees represent a significant threat to the genetic integrity of natural populations. Not all escapement events are reported, and consequently, there is a need to develop an effective tool for the identification of escapees. In this study, > 2200 salmon were collected from 44 cages located on 26 farms in the Hardangerfjord, western Norway. This fjord represents one of the major salmon farming areas in Norway, with a production of 57,000 t in 2007. Based upon genetic data from 17 microsatellite markers, significant but highly variable differentiation was observed among the 44 samples (cages), with pair-wise FST values ranging between 0.000 and 0.185. Bayesian clustering of the samples revealed five major genetic groups, into which the 44 samples were re-organised. Bayesian clustering also identified two samples consisting of fish with mixed genetic background. Performing self-assignment simulations with the data divided into different sub-sets, overall accuracy of assignment was 44% within the entire material (44 samples), 44% for the 28 spring samples, 59% for the 16 autumn samples, and 70% for 8 autumn samples collected from a geographically restricted area. Accuracy of assignment varied greatly among the individual samples. For the Bayesian clustered data set consisting of five genetic groups, overall accuracy of self-assignment was 99%, demonstrating the effectiveness of this strategy to significantly increase accuracy of assignment, albeit at the expense of precision. This study demonstrates the potential to identify the farm of origin for escapees in a region with a large number of salmon farms. The approaches described here will be of relevance to a range of other species reared in culture where identification of escapees may be required. Article in Journal/Newspaper Atlantic salmon Salmo salar Technical University of Denmark: DTU Orbit Aquaculture 290 1-2 37 46
institution Open Polar
collection Technical University of Denmark: DTU Orbit
op_collection_id ftdtupubl
language English
description Farmed Atlantic salmon escapees represent a significant threat to the genetic integrity of natural populations. Not all escapement events are reported, and consequently, there is a need to develop an effective tool for the identification of escapees. In this study, > 2200 salmon were collected from 44 cages located on 26 farms in the Hardangerfjord, western Norway. This fjord represents one of the major salmon farming areas in Norway, with a production of 57,000 t in 2007. Based upon genetic data from 17 microsatellite markers, significant but highly variable differentiation was observed among the 44 samples (cages), with pair-wise FST values ranging between 0.000 and 0.185. Bayesian clustering of the samples revealed five major genetic groups, into which the 44 samples were re-organised. Bayesian clustering also identified two samples consisting of fish with mixed genetic background. Performing self-assignment simulations with the data divided into different sub-sets, overall accuracy of assignment was 44% within the entire material (44 samples), 44% for the 28 spring samples, 59% for the 16 autumn samples, and 70% for 8 autumn samples collected from a geographically restricted area. Accuracy of assignment varied greatly among the individual samples. For the Bayesian clustered data set consisting of five genetic groups, overall accuracy of self-assignment was 99%, demonstrating the effectiveness of this strategy to significantly increase accuracy of assignment, albeit at the expense of precision. This study demonstrates the potential to identify the farm of origin for escapees in a region with a large number of salmon farms. The approaches described here will be of relevance to a range of other species reared in culture where identification of escapees may be required.
format Article in Journal/Newspaper
author Glover, Kevin A.
Hansen, Michael Møller
Skaala, Oystein
spellingShingle Glover, Kevin A.
Hansen, Michael Møller
Skaala, Oystein
Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment
author_facet Glover, Kevin A.
Hansen, Michael Møller
Skaala, Oystein
author_sort Glover, Kevin A.
title Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment
title_short Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment
title_full Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment
title_fullStr Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment
title_full_unstemmed Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment
title_sort identifying the source of farmed escaped atlantic salmon (salmo salar): bayesian clustering analysis increases accuracy of assignment
publishDate 2009
url https://orbit.dtu.dk/en/publications/e388e7a2-9ac4-48f3-a166-0748ab802f4a
https://doi.org/10.1016/j.aquaculture.2009.01.034
genre Atlantic salmon
Salmo salar
genre_facet Atlantic salmon
Salmo salar
op_source Glover , K A , Hansen , M M & Skaala , O 2009 , ' Identifying the source of farmed escaped Atlantic salmon (Salmo salar): Bayesian clustering analysis increases accuracy of assignment ' , Aquaculture , vol. 290 , no. 1-2 , pp. 37-46 . https://doi.org/10.1016/j.aquaculture.2009.01.034
op_relation https://orbit.dtu.dk/en/publications/e388e7a2-9ac4-48f3-a166-0748ab802f4a
op_rights info:eu-repo/semantics/restrictedAccess
op_doi https://doi.org/10.1016/j.aquaculture.2009.01.034
container_title Aquaculture
container_volume 290
container_issue 1-2
container_start_page 37
op_container_end_page 46
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