Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat

Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of dem...

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Published in:Frontiers in Ecology and Evolution
Main Authors: Woodward, Guy, Morris, Olivia, Barquín, José, Belgrano, Andrea, Bull, Colin, de Eyto, Elvira, Friberg, Nikolai, Guðbergsson, Guðni, Layer-Dobra, Katrin, Lauridsen, Rasmus B., Lewis, Hannah M., McGinnity, Philip, Pawar, Samraat, Rosindell, James, O'Gorman, Eoin J.
Format: Article in Journal/Newspaper
Language:English
Published: Frontiers 2021
Subjects:
Online Access:https://hdl.handle.net/11250/2984501
https://doi.org/10.3389/fevo.2021.675261
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spelling ftnorskinstvf:oai:niva.brage.unit.no:11250/2984501 2023-05-15T15:30:21+02:00 Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat Woodward, Guy Morris, Olivia Barquín, José Belgrano, Andrea Bull, Colin de Eyto, Elvira Friberg, Nikolai Guðbergsson, Guðni Layer-Dobra, Katrin Lauridsen, Rasmus B. Lewis, Hannah M. McGinnity, Philip Pawar, Samraat Rosindell, James O'Gorman, Eoin J. 2021 application/pdf https://hdl.handle.net/11250/2984501 https://doi.org/10.3389/fevo.2021.675261 eng eng Frontiers Frontiers in Ecology and Evolution. 2021, 9, 675261. urn:issn:2296-701X https://hdl.handle.net/11250/2984501 https://doi.org/10.3389/fevo.2021.675261 cristin:2003045 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no Copyright © 2021 Woodward, Morris, Barquín, Belgrano, Bull, de Eyto, Friberg, Guðbergsson, Layer-Dobra, Lauridsen, Lewis, McGinnity, Pawar, Rosindell and O’Gorman CC-BY 10 9 Frontiers in Ecology and Evolution 675261 Peer reviewed Journal article 2021 ftnorskinstvf https://doi.org/10.3389/fevo.2021.675261 2023-02-21T08:45:47Z Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon—given the huge data resources that already exist for this species—the general principles developed here could be applied and extended to many other species and ecosystems. publishedVersion Article in Journal/Newspaper Atlantic salmon Norwegian Institute for Water research: NIVA Open Access Archive (Brage) Frontiers in Ecology and Evolution 9
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collection Norwegian Institute for Water research: NIVA Open Access Archive (Brage)
op_collection_id ftnorskinstvf
language English
description Populations of Atlantic salmon are crashing across most of its natural range: understanding the underlying causes and predicting these collapses in time to intervene effectively are urgent ecological and socioeconomic priorities. Current management techniques rely on phenomenological analyses of demographic population time-series and thus lack a mechanistic understanding of how and why populations may be declining. New multidisciplinary approaches are thus needed to capitalize on the long-term, large-scale population data that are currently scattered across various repositories in multiple countries, as well as marshaling additional data to understand the constraints on the life cycle and how salmon operate within the wider food web. Here, we explore how we might combine data and theory to develop the mechanistic models that we need to predict and manage responses to future change. Although we focus on Atlantic salmon—given the huge data resources that already exist for this species—the general principles developed here could be applied and extended to many other species and ecosystems. publishedVersion
format Article in Journal/Newspaper
author Woodward, Guy
Morris, Olivia
Barquín, José
Belgrano, Andrea
Bull, Colin
de Eyto, Elvira
Friberg, Nikolai
Guðbergsson, Guðni
Layer-Dobra, Katrin
Lauridsen, Rasmus B.
Lewis, Hannah M.
McGinnity, Philip
Pawar, Samraat
Rosindell, James
O'Gorman, Eoin J.
spellingShingle Woodward, Guy
Morris, Olivia
Barquín, José
Belgrano, Andrea
Bull, Colin
de Eyto, Elvira
Friberg, Nikolai
Guðbergsson, Guðni
Layer-Dobra, Katrin
Lauridsen, Rasmus B.
Lewis, Hannah M.
McGinnity, Philip
Pawar, Samraat
Rosindell, James
O'Gorman, Eoin J.
Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat
author_facet Woodward, Guy
Morris, Olivia
Barquín, José
Belgrano, Andrea
Bull, Colin
de Eyto, Elvira
Friberg, Nikolai
Guðbergsson, Guðni
Layer-Dobra, Katrin
Lauridsen, Rasmus B.
Lewis, Hannah M.
McGinnity, Philip
Pawar, Samraat
Rosindell, James
O'Gorman, Eoin J.
author_sort Woodward, Guy
title Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat
title_short Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat
title_full Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat
title_fullStr Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat
title_full_unstemmed Using Food Webs and Metabolic Theory to Monitor, Model, and Manage Atlantic Salmon—A Keystone Species Under Threat
title_sort using food webs and metabolic theory to monitor, model, and manage atlantic salmon—a keystone species under threat
publisher Frontiers
publishDate 2021
url https://hdl.handle.net/11250/2984501
https://doi.org/10.3389/fevo.2021.675261
genre Atlantic salmon
genre_facet Atlantic salmon
op_source 10
9
Frontiers in Ecology and Evolution
675261
op_relation Frontiers in Ecology and Evolution. 2021, 9, 675261.
urn:issn:2296-701X
https://hdl.handle.net/11250/2984501
https://doi.org/10.3389/fevo.2021.675261
cristin:2003045
op_rights Navngivelse 4.0 Internasjonal
http://creativecommons.org/licenses/by/4.0/deed.no
Copyright © 2021 Woodward, Morris, Barquín, Belgrano, Bull, de Eyto, Friberg, Guðbergsson, Layer-Dobra, Lauridsen, Lewis, McGinnity, Pawar, Rosindell and O’Gorman
op_rightsnorm CC-BY
op_doi https://doi.org/10.3389/fevo.2021.675261
container_title Frontiers in Ecology and Evolution
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