Climate based multi-year predictions of the Barents Sea cod stock.
Predicting fish stock variations on interannual to decadal time scales is one of the major issues in fisheries science and management. Although the field of marine ecological predictions is still in its infancy, it is understood that a major source of multi-year predictability resides in the ocean....
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Online Access: | https://hdl.handle.net/1956/19208 https://doi.org/10.1371/journal.pone.0206319 |
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ftunivbergen:oai:bora.uib.no:1956/19208 2023-05-15T15:38:29+02:00 Climate based multi-year predictions of the Barents Sea cod stock. Årthun, Marius Bogstad, Bjarte Daewel, Ute Keenlyside, Noel Sandø, Anne Britt Schrum, Corinna Ottersen, Geir 2018-10-30T08:44:49Z application/pdf https://hdl.handle.net/1956/19208 https://doi.org/10.1371/journal.pone.0206319 eng eng Public Library of Science EC/H2020: 727852 Norges forskningsråd: 263223 urn:issn:1932-6203 https://hdl.handle.net/1956/19208 https://doi.org/10.1371/journal.pone.0206319 cristin:1624410 Attribution CC BY http://creativecommons.org/licenses/by/4.0/ Copyright 2018 The Authors PLoS ONE Peer reviewed Journal article 2018 ftunivbergen https://doi.org/10.1371/journal.pone.0206319 2023-03-14T17:42:24Z Predicting fish stock variations on interannual to decadal time scales is one of the major issues in fisheries science and management. Although the field of marine ecological predictions is still in its infancy, it is understood that a major source of multi-year predictability resides in the ocean. Here we show the first highly skilful long-term predictions of the commercially valuable Barents Sea cod stock. The 7-year predictions are based on the propagation of ocean temperature anomalies from the subpolar North Atlantic toward the Barents Sea, and the strong co-variability between these temperature anomalies and the cod stock. Retrospective predictions for the period 1957–2017 capture well multi-year to decadal variations in cod stock biomass, with cross-validated explained variance of over 60%. For lead times longer than one year the statistical long-term predictions show more skill than operational short-term predictions used in fisheries management and lagged persistence forecasts. Our results thus demonstrate the potential for ecosystem-based fisheries management, which could enable strategic planning on longer time scales. Future predictions show a gradual decline in the cod stock towards 2024. publishedVersion Article in Journal/Newspaper Barents Sea North Atlantic University of Bergen: Bergen Open Research Archive (BORA-UiB) Barents Sea PLOS ONE 13 10 e0206319 |
institution |
Open Polar |
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University of Bergen: Bergen Open Research Archive (BORA-UiB) |
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ftunivbergen |
language |
English |
description |
Predicting fish stock variations on interannual to decadal time scales is one of the major issues in fisheries science and management. Although the field of marine ecological predictions is still in its infancy, it is understood that a major source of multi-year predictability resides in the ocean. Here we show the first highly skilful long-term predictions of the commercially valuable Barents Sea cod stock. The 7-year predictions are based on the propagation of ocean temperature anomalies from the subpolar North Atlantic toward the Barents Sea, and the strong co-variability between these temperature anomalies and the cod stock. Retrospective predictions for the period 1957–2017 capture well multi-year to decadal variations in cod stock biomass, with cross-validated explained variance of over 60%. For lead times longer than one year the statistical long-term predictions show more skill than operational short-term predictions used in fisheries management and lagged persistence forecasts. Our results thus demonstrate the potential for ecosystem-based fisheries management, which could enable strategic planning on longer time scales. Future predictions show a gradual decline in the cod stock towards 2024. publishedVersion |
format |
Article in Journal/Newspaper |
author |
Årthun, Marius Bogstad, Bjarte Daewel, Ute Keenlyside, Noel Sandø, Anne Britt Schrum, Corinna Ottersen, Geir |
spellingShingle |
Årthun, Marius Bogstad, Bjarte Daewel, Ute Keenlyside, Noel Sandø, Anne Britt Schrum, Corinna Ottersen, Geir Climate based multi-year predictions of the Barents Sea cod stock. |
author_facet |
Årthun, Marius Bogstad, Bjarte Daewel, Ute Keenlyside, Noel Sandø, Anne Britt Schrum, Corinna Ottersen, Geir |
author_sort |
Årthun, Marius |
title |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_short |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_full |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_fullStr |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_full_unstemmed |
Climate based multi-year predictions of the Barents Sea cod stock. |
title_sort |
climate based multi-year predictions of the barents sea cod stock. |
publisher |
Public Library of Science |
publishDate |
2018 |
url |
https://hdl.handle.net/1956/19208 https://doi.org/10.1371/journal.pone.0206319 |
geographic |
Barents Sea |
geographic_facet |
Barents Sea |
genre |
Barents Sea North Atlantic |
genre_facet |
Barents Sea North Atlantic |
op_source |
PLoS ONE |
op_relation |
EC/H2020: 727852 Norges forskningsråd: 263223 urn:issn:1932-6203 https://hdl.handle.net/1956/19208 https://doi.org/10.1371/journal.pone.0206319 cristin:1624410 |
op_rights |
Attribution CC BY http://creativecommons.org/licenses/by/4.0/ Copyright 2018 The Authors |
op_doi |
https://doi.org/10.1371/journal.pone.0206319 |
container_title |
PLOS ONE |
container_volume |
13 |
container_issue |
10 |
container_start_page |
e0206319 |
_version_ |
1766369429451440128 |