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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Published in:PLOS ONE
Main Authors: Årthun, Marius, Bogstad, Bjarte, Daewel, Ute, Keenlyside, Noel, Sandø, Anne Britt, Schrum, Corinna, Ottersen, Geir
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science 2018
Subjects:
Online Access:https://hdl.handle.net/1956/19208
https://doi.org/10.1371/journal.pone.0206319
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spelling 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
collection University of Bergen: Bergen Open Research Archive (BORA-UiB)
op_collection_id 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
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