Evidence for spatial coherence in time trends of marine life history traits of Atlantic salmon in the North Atlantic

Maxime Olmos; Félix Massiot-Granier; Etienne Prévost; Gérald Chaput; Ian R. Bradbury; Marie Nevoux; Etienne Rivot

doi:10.1111/faf.12345

Evidence for spatial coherence in time trends of marine life history traits of Atlantic salmon in the North Atlantic

Maxime Olmos, Félix Massiot-Granier, Etienne Prévost, Gérald Chaput, Ian R. Bradbury, Marie Nevoux, Etienne Rivot

Research output: Contribution to journal › Article › peer-review

44 Citations (Scopus)

Abstract

A hierarchical Bayesian life cycle model is presented that considers spatial covariation of marine life history traits of Atlantic salmon (Salmo salar) populations in the North Atlantic. The model is based on a collective analysis of the dynamics of 13 stock units (SUs) from two continental stock groups (CSGs) in North America and Southern Europe in a single hierarchical model over the period 1971–2014. The model sets up a new assessment framework for Atlantic salmon stocks. It also provides a framework to investigate the drivers of changes in Atlantic salmon population dynamics including disentangling the effects of fisheries from those of environmental factors in a hierarchy of spatial scales. It is used to test the hypothesis of a strong spatial synchrony in marine life history dynamics of Atlantic salmon populations. The trends in two key parameters associated with the early marine phase of the life cycle are estimated: (i) the marine survival during the first summer–autumn spent at sea and (ii) the proportion of fish maturing after the first winter at sea. The results provide evidence of a decline in the marine survival together with an increase in the proportion of fish that mature after the first winter at sea, common to all SUs. Our results show an increased coherence in the covariations of trends in these two marine life history traits related to geographic proximity of SUs which support the hypothesis of a coherent response of geographically proximate Atlantic salmon populations that likely share similar migration routes.

Original language	English
Pages (from-to)	322-342
Number of pages	21
Journal	Fish and Fisheries
Volume	20
Issue number	2
DOIs	https://doi.org/10.1111/faf.12345
Publication status	Published - Mar 1 2019
Externally published	Yes

Bibliographical note

Funding Information:
The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 244706/ECOKNOWS project, and from the Agence Française de la Biodiversité under grant agreement INRA-AFB SalmoGlob 2016-2018. This study was made possible by the work of the numerous people who collect and compile the data used by the ICES Working Group on North Atlantic Salmon. For North America: Dave Reddin, Martha Robertson and Geoff Veinott of Fisheries and Oceans Canada (DFO) Newfoundland and Labrador Region, Ross Jones and Alex Levy of DFO Maritimes Region, Cindy Breau, Michel Biron, Scott Douglas of DFO Gulf Region, Mélanie Dionne and Julien April from the provincial government of Quebec, and Tim Sheehan and Joan Trial of United States. For Southern NEAC: Dennis Ensing (UK Northern Ireland), Gudni Gudbergsson (Iceland), Michael Millane and Niall O Maoiléidigh (Ireland), Ted Potter and Ian Russel (UK England and Wales), Gordon Smith (UK Scotland) and the Pôle AFB-IRA Gest-Aqua lead by Laurent Beaulaton (France). We thank Jerome Guitton for his help in the map design and Maud Queroue for her help gathering the freshwater data. We further thank the two anonymous reviewers and the Chief Editor for their comments, which considerably improved the quality of the manuscript.

Publisher Copyright:
© 2018 John Wiley & Sons Ltd

ASJC Scopus Subject Areas

Oceanography
Ecology, Evolution, Behavior and Systematics
Aquatic Science
Management, Monitoring, Policy and Law

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1111/faf.12345

Cite this

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title = "Evidence for spatial coherence in time trends of marine life history traits of Atlantic salmon in the North Atlantic",

abstract = "A hierarchical Bayesian life cycle model is presented that considers spatial covariation of marine life history traits of Atlantic salmon (Salmo salar) populations in the North Atlantic. The model is based on a collective analysis of the dynamics of 13 stock units (SUs) from two continental stock groups (CSGs) in North America and Southern Europe in a single hierarchical model over the period 1971–2014. The model sets up a new assessment framework for Atlantic salmon stocks. It also provides a framework to investigate the drivers of changes in Atlantic salmon population dynamics including disentangling the effects of fisheries from those of environmental factors in a hierarchy of spatial scales. It is used to test the hypothesis of a strong spatial synchrony in marine life history dynamics of Atlantic salmon populations. The trends in two key parameters associated with the early marine phase of the life cycle are estimated: (i) the marine survival during the first summer–autumn spent at sea and (ii) the proportion of fish maturing after the first winter at sea. The results provide evidence of a decline in the marine survival together with an increase in the proportion of fish that mature after the first winter at sea, common to all SUs. Our results show an increased coherence in the covariations of trends in these two marine life history traits related to geographic proximity of SUs which support the hypothesis of a coherent response of geographically proximate Atlantic salmon populations that likely share similar migration routes.",

author = "Maxime Olmos and F{\'e}lix Massiot-Granier and Etienne Pr{\'e}vost and G{\'e}rald Chaput and Bradbury, {Ian R.} and Marie Nevoux and Etienne Rivot",

note = "Funding Information: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 244706/ECOKNOWS project, and from the Agence Fran{\c c}aise de la Biodiversit{\'e} under grant agreement INRA-AFB SalmoGlob 2016-2018. This study was made possible by the work of the numerous people who collect and compile the data used by the ICES Working Group on North Atlantic Salmon. For North America: Dave Reddin, Martha Robertson and Geoff Veinott of Fisheries and Oceans Canada (DFO) Newfoundland and Labrador Region, Ross Jones and Alex Levy of DFO Maritimes Region, Cindy Breau, Michel Biron, Scott Douglas of DFO Gulf Region, M{\'e}lanie Dionne and Julien April from the provincial government of Quebec, and Tim Sheehan and Joan Trial of United States. For Southern NEAC: Dennis Ensing (UK Northern Ireland), Gudni Gudbergsson (Iceland), Michael Millane and Niall O Maoil{\'e}idigh (Ireland), Ted Potter and Ian Russel (UK England and Wales), Gordon Smith (UK Scotland) and the P{\^o}le AFB-IRA Gest-Aqua lead by Laurent Beaulaton (France). We thank Jerome Guitton for his help in the map design and Maud Queroue for her help gathering the freshwater data. We further thank the two anonymous reviewers and the Chief Editor for their comments, which considerably improved the quality of the manuscript. Publisher Copyright: {\textcopyright} 2018 John Wiley & Sons Ltd",

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AU - Olmos, Maxime

AU - Massiot-Granier, Félix

AU - Prévost, Etienne

AU - Chaput, Gérald

AU - Bradbury, Ian R.

AU - Nevoux, Marie

AU - Rivot, Etienne

N1 - Funding Information: The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007–2013) under grant agreement No. 244706/ECOKNOWS project, and from the Agence Française de la Biodiversité under grant agreement INRA-AFB SalmoGlob 2016-2018. This study was made possible by the work of the numerous people who collect and compile the data used by the ICES Working Group on North Atlantic Salmon. For North America: Dave Reddin, Martha Robertson and Geoff Veinott of Fisheries and Oceans Canada (DFO) Newfoundland and Labrador Region, Ross Jones and Alex Levy of DFO Maritimes Region, Cindy Breau, Michel Biron, Scott Douglas of DFO Gulf Region, Mélanie Dionne and Julien April from the provincial government of Quebec, and Tim Sheehan and Joan Trial of United States. For Southern NEAC: Dennis Ensing (UK Northern Ireland), Gudni Gudbergsson (Iceland), Michael Millane and Niall O Maoiléidigh (Ireland), Ted Potter and Ian Russel (UK England and Wales), Gordon Smith (UK Scotland) and the Pôle AFB-IRA Gest-Aqua lead by Laurent Beaulaton (France). We thank Jerome Guitton for his help in the map design and Maud Queroue for her help gathering the freshwater data. We further thank the two anonymous reviewers and the Chief Editor for their comments, which considerably improved the quality of the manuscript. Publisher Copyright: © 2018 John Wiley & Sons Ltd

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N2 - A hierarchical Bayesian life cycle model is presented that considers spatial covariation of marine life history traits of Atlantic salmon (Salmo salar) populations in the North Atlantic. The model is based on a collective analysis of the dynamics of 13 stock units (SUs) from two continental stock groups (CSGs) in North America and Southern Europe in a single hierarchical model over the period 1971–2014. The model sets up a new assessment framework for Atlantic salmon stocks. It also provides a framework to investigate the drivers of changes in Atlantic salmon population dynamics including disentangling the effects of fisheries from those of environmental factors in a hierarchy of spatial scales. It is used to test the hypothesis of a strong spatial synchrony in marine life history dynamics of Atlantic salmon populations. The trends in two key parameters associated with the early marine phase of the life cycle are estimated: (i) the marine survival during the first summer–autumn spent at sea and (ii) the proportion of fish maturing after the first winter at sea. The results provide evidence of a decline in the marine survival together with an increase in the proportion of fish that mature after the first winter at sea, common to all SUs. Our results show an increased coherence in the covariations of trends in these two marine life history traits related to geographic proximity of SUs which support the hypothesis of a coherent response of geographically proximate Atlantic salmon populations that likely share similar migration routes.

AB - A hierarchical Bayesian life cycle model is presented that considers spatial covariation of marine life history traits of Atlantic salmon (Salmo salar) populations in the North Atlantic. The model is based on a collective analysis of the dynamics of 13 stock units (SUs) from two continental stock groups (CSGs) in North America and Southern Europe in a single hierarchical model over the period 1971–2014. The model sets up a new assessment framework for Atlantic salmon stocks. It also provides a framework to investigate the drivers of changes in Atlantic salmon population dynamics including disentangling the effects of fisheries from those of environmental factors in a hierarchy of spatial scales. It is used to test the hypothesis of a strong spatial synchrony in marine life history dynamics of Atlantic salmon populations. The trends in two key parameters associated with the early marine phase of the life cycle are estimated: (i) the marine survival during the first summer–autumn spent at sea and (ii) the proportion of fish maturing after the first winter at sea. The results provide evidence of a decline in the marine survival together with an increase in the proportion of fish that mature after the first winter at sea, common to all SUs. Our results show an increased coherence in the covariations of trends in these two marine life history traits related to geographic proximity of SUs which support the hypothesis of a coherent response of geographically proximate Atlantic salmon populations that likely share similar migration routes.

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Evidence for spatial coherence in time trends of marine life history traits of Atlantic salmon in the North Atlantic

Abstract

Bibliographical note

ASJC Scopus Subject Areas

UN SDGs

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