A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study
International audience Considering spatial processes in population dynamics models can be difficult because of data limitations and computational costs. We adapted a high-resolution spatiotemporal assessment framework to better address fine scale spatial heterogeneities based on theories of fish pop...
Published in: | Ecological Modelling |
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Main Authors: | , , , , , , |
Other Authors: | , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
HAL CCSD
2023
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Subjects: | |
Online Access: | https://hal.inrae.fr/hal-04489873 https://doi.org/10.1016/j.ecolmodel.2023.110484 |
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ftofficefbiodive:oai:HAL:hal-04489873v1 |
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institution |
Open Polar |
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Portail HAL OFB (Office français de la biodiversité) |
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ftofficefbiodive |
language |
English |
topic |
Chionoecetes opilio Size-structured spatiotemporal model Spatial management State-space model [SDE]Environmental Sciences |
spellingShingle |
Chionoecetes opilio Size-structured spatiotemporal model Spatial management State-space model [SDE]Environmental Sciences Olmos, Maxime Cao, Jie Thorson, James T. Punt, André E. Monnahan, Cole Alglave, Baptiste Szuwalski, Cody A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study |
topic_facet |
Chionoecetes opilio Size-structured spatiotemporal model Spatial management State-space model [SDE]Environmental Sciences |
description |
International audience Considering spatial processes in population dynamics models can be difficult because of data limitations and computational costs. We adapted a high-resolution spatiotemporal assessment framework to better address fine scale spatial heterogeneities based on theories of fish population dynamics and spatiotemporal statistics. Specifically, we developed a size-based state-space model for the snow crab (Chionoecetes opilio) population in the Eastern Bering Sea (EBS) to refine the representation of spatial processes in integrated population models, facilitate understanding of the drivers of spatiotemporal population dynamics, and provide new insights for management advice. The model fits to spatial survey and fishery-dependent catch data. It implicitly accounts for seasonal movement between the time of the survey and that of fishery to estimate fine-scale spatial population dynamic and fishing impacts, including potential environmental drivers. We quantify, for the first time, spatiotemporal variation in exploitable abundance, fishing mortality, recruitment, and mature and immature abundance. The model estimated declines in exploitable abundance and in fishing mortality with variable spatial distributions, and sporadic recruitment, spatially concentrated in the northeast EBS. Few spatial assessments have been used as the basis for management advice and we consider this study as a step towards the integration of spatial dynamics in stock assessment. |
author2 |
Pôle OFB-INRAE-Institut Agro-UPPA pour la gestion des migrateurs amphihalins dans leur environnement (MIAME) Université de Pau et des Pays de l'Adour (UPPA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Office français de la biodiversité (OFB)-Institut Agro Rennes Angers Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) Dynamique et durabilité des écosystèmes : de la source à l’océan (DECOD) Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut Agro Rennes Angers Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) School of Aquatic Fishery Sciences University of Washington Seattle National Oceanic and Atmospheric Administration (NOAA) Nanjing University of Finance and Economics (NUFE) Northwest Fisheries Science Center (NWFSC) NOAA National Marine Fisheries Service (NMFS) National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA) School of Aquatic and Fishery Sciences (University of Washington) |
format |
Article in Journal/Newspaper |
author |
Olmos, Maxime Cao, Jie Thorson, James T. Punt, André E. Monnahan, Cole Alglave, Baptiste Szuwalski, Cody |
author_facet |
Olmos, Maxime Cao, Jie Thorson, James T. Punt, André E. Monnahan, Cole Alglave, Baptiste Szuwalski, Cody |
author_sort |
Olmos, Maxime |
title |
A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study |
title_short |
A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study |
title_full |
A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study |
title_fullStr |
A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study |
title_full_unstemmed |
A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study |
title_sort |
step towards the integration of spatial dynamics in population dynamics models: eastern bering sea snow crab as a case study |
publisher |
HAL CCSD |
publishDate |
2023 |
url |
https://hal.inrae.fr/hal-04489873 https://doi.org/10.1016/j.ecolmodel.2023.110484 |
geographic |
Bering Sea |
geographic_facet |
Bering Sea |
genre |
Bering Sea Chionoecetes opilio Snow crab |
genre_facet |
Bering Sea Chionoecetes opilio Snow crab |
op_source |
ISSN: 0304-3800 EISSN: 1872-7026 Ecological Modelling https://hal.inrae.fr/hal-04489873 Ecological Modelling, 2023, 485, pp.110484. ⟨10.1016/j.ecolmodel.2023.110484⟩ |
op_relation |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolmodel.2023.110484 hal-04489873 https://hal.inrae.fr/hal-04489873 doi:10.1016/j.ecolmodel.2023.110484 WOS: 001076537000001 |
op_rights |
http://hal.archives-ouvertes.fr/licences/copyright/ |
op_doi |
https://doi.org/10.1016/j.ecolmodel.2023.110484 |
container_title |
Ecological Modelling |
container_volume |
485 |
container_start_page |
110484 |
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1801374043883962368 |
spelling |
ftofficefbiodive:oai:HAL:hal-04489873v1 2024-06-09T07:45:06+00:00 A step towards the integration of spatial dynamics in population dynamics models: Eastern Bering Sea snow crab as a case study Olmos, Maxime Cao, Jie Thorson, James T. Punt, André E. Monnahan, Cole Alglave, Baptiste Szuwalski, Cody Pôle OFB-INRAE-Institut Agro-UPPA pour la gestion des migrateurs amphihalins dans leur environnement (MIAME) Université de Pau et des Pays de l'Adour (UPPA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Office français de la biodiversité (OFB)-Institut Agro Rennes Angers Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) Dynamique et durabilité des écosystèmes : de la source à l’océan (DECOD) Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut Agro Rennes Angers Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro) School of Aquatic Fishery Sciences University of Washington Seattle National Oceanic and Atmospheric Administration (NOAA) Nanjing University of Finance and Economics (NUFE) Northwest Fisheries Science Center (NWFSC) NOAA National Marine Fisheries Service (NMFS) National Oceanic and Atmospheric Administration (NOAA)-National Oceanic and Atmospheric Administration (NOAA) School of Aquatic and Fishery Sciences (University of Washington) 2023-11 https://hal.inrae.fr/hal-04489873 https://doi.org/10.1016/j.ecolmodel.2023.110484 en eng HAL CCSD Elsevier info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolmodel.2023.110484 hal-04489873 https://hal.inrae.fr/hal-04489873 doi:10.1016/j.ecolmodel.2023.110484 WOS: 001076537000001 http://hal.archives-ouvertes.fr/licences/copyright/ ISSN: 0304-3800 EISSN: 1872-7026 Ecological Modelling https://hal.inrae.fr/hal-04489873 Ecological Modelling, 2023, 485, pp.110484. ⟨10.1016/j.ecolmodel.2023.110484⟩ Chionoecetes opilio Size-structured spatiotemporal model Spatial management State-space model [SDE]Environmental Sciences info:eu-repo/semantics/article Journal articles 2023 ftofficefbiodive https://doi.org/10.1016/j.ecolmodel.2023.110484 2024-05-16T14:04:36Z International audience Considering spatial processes in population dynamics models can be difficult because of data limitations and computational costs. We adapted a high-resolution spatiotemporal assessment framework to better address fine scale spatial heterogeneities based on theories of fish population dynamics and spatiotemporal statistics. Specifically, we developed a size-based state-space model for the snow crab (Chionoecetes opilio) population in the Eastern Bering Sea (EBS) to refine the representation of spatial processes in integrated population models, facilitate understanding of the drivers of spatiotemporal population dynamics, and provide new insights for management advice. The model fits to spatial survey and fishery-dependent catch data. It implicitly accounts for seasonal movement between the time of the survey and that of fishery to estimate fine-scale spatial population dynamic and fishing impacts, including potential environmental drivers. We quantify, for the first time, spatiotemporal variation in exploitable abundance, fishing mortality, recruitment, and mature and immature abundance. The model estimated declines in exploitable abundance and in fishing mortality with variable spatial distributions, and sporadic recruitment, spatially concentrated in the northeast EBS. Few spatial assessments have been used as the basis for management advice and we consider this study as a step towards the integration of spatial dynamics in stock assessment. Article in Journal/Newspaper Bering Sea Chionoecetes opilio Snow crab Portail HAL OFB (Office français de la biodiversité) Bering Sea Ecological Modelling 485 110484 |