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spelling ftunivpau:oai:HAL:hal-01860018v1 2023-11-12T04:14:28+01:00 A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean Olmos, Maxime Prévost, Etienne Chaput, Gérald Nevoux, Marie Rivot, Etienne Écologie et santé des écosystèmes (ESE) Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST Ecologie Comportementale et Biologie des Populations de Poissons (ECOBIOP) Institut National de la Recherche Agronomique (INRA)-Université de Pau et des Pays de l'Adour (UPPA) Department of Fisheries and Oceans St Andrews, United Kingdom 2018-07-02 https://hal.science/hal-01860018 https://hal.science/hal-01860018/document https://hal.science/hal-01860018/file/2018_Olmos_ISEC2018Com_1.pdf en eng HAL CCSD hal-01860018 https://hal.science/hal-01860018 https://hal.science/hal-01860018/document https://hal.science/hal-01860018/file/2018_Olmos_ISEC2018Com_1.pdf PRODINRA: 440823 info:eu-repo/semantics/OpenAccess International Statistical Ecology Conference (ISEC 2018) https://hal.science/hal-01860018 International Statistical Ecology Conference (ISEC 2018), Jul 2018, St Andrews, United Kingdom. 328 p marine survival maturation probability atlantic salmon environmentally driven change bottom-up sst salmon survival global change north atlantic atlantic population dynamics spatial covariation hierarchical bayesian model stage-based life cycle model changement climatique atlantique nord dynamique des populations modèle bayésien survie température de surface salmo salar [SDE.BE]Environmental Sciences/Biodiversity and Ecology [SDE.MCG]Environmental Sciences/Global Changes info:eu-repo/semantics/conferenceObject Conference papers 2018 ftunivpau 2023-10-15T20:41:30Z Résumé Résumé International audience Conference Object Atlantic salmon North Atlantic Salmo salar HAL e2s UPPA (Université de Pau et des Pays de l'Adour)
institution Open Polar
collection HAL e2s UPPA (Université de Pau et des Pays de l'Adour)
op_collection_id ftunivpau
language English
topic marine survival
maturation probability
atlantic salmon
environmentally driven change
bottom-up
sst
salmon
survival
global change
north atlantic
atlantic
population dynamics
spatial covariation
hierarchical bayesian model
stage-based life cycle model
changement climatique
atlantique nord
dynamique des populations
modèle bayésien
survie
température de surface
salmo salar
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SDE.MCG]Environmental Sciences/Global Changes
spellingShingle marine survival
maturation probability
atlantic salmon
environmentally driven change
bottom-up
sst
salmon
survival
global change
north atlantic
atlantic
population dynamics
spatial covariation
hierarchical bayesian model
stage-based life cycle model
changement climatique
atlantique nord
dynamique des populations
modèle bayésien
survie
température de surface
salmo salar
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SDE.MCG]Environmental Sciences/Global Changes
Olmos, Maxime
Prévost, Etienne
Chaput, Gérald
Nevoux, Marie
Rivot, Etienne
A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean
topic_facet marine survival
maturation probability
atlantic salmon
environmentally driven change
bottom-up
sst
salmon
survival
global change
north atlantic
atlantic
population dynamics
spatial covariation
hierarchical bayesian model
stage-based life cycle model
changement climatique
atlantique nord
dynamique des populations
modèle bayésien
survie
température de surface
salmo salar
[SDE.BE]Environmental Sciences/Biodiversity and Ecology
[SDE.MCG]Environmental Sciences/Global Changes
description Résumé Résumé International audience
author2 Écologie et santé des écosystèmes (ESE)
Institut National de la Recherche Agronomique (INRA)-AGROCAMPUS OUEST
Ecologie Comportementale et Biologie des Populations de Poissons (ECOBIOP)
Institut National de la Recherche Agronomique (INRA)-Université de Pau et des Pays de l'Adour (UPPA)
Department of Fisheries and Oceans
format Conference Object
author Olmos, Maxime
Prévost, Etienne
Chaput, Gérald
Nevoux, Marie
Rivot, Etienne
author_facet Olmos, Maxime
Prévost, Etienne
Chaput, Gérald
Nevoux, Marie
Rivot, Etienne
author_sort Olmos, Maxime
title A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean
title_short A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean
title_full A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean
title_fullStr A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean
title_full_unstemmed A Bayesian hierarchical model to unravel the spatial covariations in the response of Atlantic salmon populations to climate change in the North Atlantic Ocean
title_sort bayesian hierarchical model to unravel the spatial covariations in the response of atlantic salmon populations to climate change in the north atlantic ocean
publisher HAL CCSD
publishDate 2018
url https://hal.science/hal-01860018
https://hal.science/hal-01860018/document
https://hal.science/hal-01860018/file/2018_Olmos_ISEC2018Com_1.pdf
op_coverage St Andrews, United Kingdom
genre Atlantic salmon
North Atlantic
Salmo salar
genre_facet Atlantic salmon
North Atlantic
Salmo salar
op_source International Statistical Ecology Conference (ISEC 2018)
https://hal.science/hal-01860018
International Statistical Ecology Conference (ISEC 2018), Jul 2018, St Andrews, United Kingdom. 328 p
op_relation hal-01860018
https://hal.science/hal-01860018
https://hal.science/hal-01860018/document
https://hal.science/hal-01860018/file/2018_Olmos_ISEC2018Com_1.pdf
PRODINRA: 440823
op_rights info:eu-repo/semantics/OpenAccess
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