Testing spatial heterogeneity with stock assessment models

This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between s...

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Published in:PLOS ONE
Main Authors: Jardim, Ernesto, Eero, Margit, Silva, Alexandra, Ulrich, Clara, Pawlowski, Lionel, Holmes, Steven J., Ibaibarriaga, Leire, De Oliveira, José A. A., Riveiro, Isabel, Alzorriz, Nekane, Citores, Leire, Scott, Finlay, Uriarte, Andres, Carrera, Pablo, Duhamel, Erwan, Mosqueira, Iago
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
Online Access:https://orbit.dtu.dk/en/publications/051409d8-d85f-4b22-81f9-25d37574e506
https://doi.org/10.1371/journal.pone.0190791
https://backend.orbit.dtu.dk/ws/files/142937194/Publishers_version.pdf
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spelling ftdtupubl:oai:pure.atira.dk:publications/051409d8-d85f-4b22-81f9-25d37574e506 2023-12-10T09:52:02+01:00 Testing spatial heterogeneity with stock assessment models Jardim, Ernesto Eero, Margit Silva, Alexandra Ulrich, Clara Pawlowski, Lionel Holmes, Steven J. Ibaibarriaga, Leire De Oliveira, José A. A. Riveiro, Isabel Alzorriz, Nekane Citores, Leire Scott, Finlay Uriarte, Andres Carrera, Pablo Duhamel, Erwan Mosqueira, Iago 2018 application/pdf https://orbit.dtu.dk/en/publications/051409d8-d85f-4b22-81f9-25d37574e506 https://doi.org/10.1371/journal.pone.0190791 https://backend.orbit.dtu.dk/ws/files/142937194/Publishers_version.pdf eng eng info:eu-repo/semantics/openAccess Jardim , E , Eero , M , Silva , A , Ulrich , C , Pawlowski , L , Holmes , S J , Ibaibarriaga , L , De Oliveira , J A A , Riveiro , I , Alzorriz , N , Citores , L , Scott , F , Uriarte , A , Carrera , P , Duhamel , E & Mosqueira , I 2018 , ' Testing spatial heterogeneity with stock assessment models ' , P L o S One , vol. 13 , no. 1 , e0190791 . https://doi.org/10.1371/journal.pone.0190791 article 2018 ftdtupubl https://doi.org/10.1371/journal.pone.0190791 2023-11-15T23:57:41Z This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub-population abundances. If the additivity results hold true for putative sub-populations, then assessment results based on sub-populations will provide information to develop and monitor the implementation of finer scale/local management. The simulation study confirmed that when sub-populations are independent and not too heterogeneous with regards to productivity, the sum of stock assessment model estimates of sub-populations' SSB is similar to the SSB estimates of the meta-population. It also showed that a strong diffusion process can be detected and that the stronger the connection between SSB and recruitment, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis. Article in Journal/Newspaper Northeast Atlantic Technical University of Denmark: DTU Orbit PLOS ONE 13 1 e0190791
institution Open Polar
collection Technical University of Denmark: DTU Orbit
op_collection_id ftdtupubl
language English
description This paper describes a methodology that combines meta-population theory and stock assessment models to gain insights about spatial heterogeneity of the meta-population in an operational time frame. The methodology was tested with stochastic simulations for different degrees of connectivity between sub-populations and applied to two case studies, North Sea cod (Gadus morua) and Northeast Atlantic sardine (Sardina pilchardus). Considering that the biological components of a population can be partitioned into discrete spatial units, we extended this idea into a property of additivity of sub-population abundances. If the additivity results hold true for putative sub-populations, then assessment results based on sub-populations will provide information to develop and monitor the implementation of finer scale/local management. The simulation study confirmed that when sub-populations are independent and not too heterogeneous with regards to productivity, the sum of stock assessment model estimates of sub-populations' SSB is similar to the SSB estimates of the meta-population. It also showed that a strong diffusion process can be detected and that the stronger the connection between SSB and recruitment, the better the diffusion process will be detected. On the other hand it showed that weak to moderate diffusion processes are not easy to identify and large differences between sub-populations productivities may be confounded with weak diffusion processes. The application to North Sea cod and Atlantic sardine exemplified how much insight can be gained. In both cases the results obtained were sufficiently robust to support the regional analysis.
format Article in Journal/Newspaper
author Jardim, Ernesto
Eero, Margit
Silva, Alexandra
Ulrich, Clara
Pawlowski, Lionel
Holmes, Steven J.
Ibaibarriaga, Leire
De Oliveira, José A. A.
Riveiro, Isabel
Alzorriz, Nekane
Citores, Leire
Scott, Finlay
Uriarte, Andres
Carrera, Pablo
Duhamel, Erwan
Mosqueira, Iago
spellingShingle Jardim, Ernesto
Eero, Margit
Silva, Alexandra
Ulrich, Clara
Pawlowski, Lionel
Holmes, Steven J.
Ibaibarriaga, Leire
De Oliveira, José A. A.
Riveiro, Isabel
Alzorriz, Nekane
Citores, Leire
Scott, Finlay
Uriarte, Andres
Carrera, Pablo
Duhamel, Erwan
Mosqueira, Iago
Testing spatial heterogeneity with stock assessment models
author_facet Jardim, Ernesto
Eero, Margit
Silva, Alexandra
Ulrich, Clara
Pawlowski, Lionel
Holmes, Steven J.
Ibaibarriaga, Leire
De Oliveira, José A. A.
Riveiro, Isabel
Alzorriz, Nekane
Citores, Leire
Scott, Finlay
Uriarte, Andres
Carrera, Pablo
Duhamel, Erwan
Mosqueira, Iago
author_sort Jardim, Ernesto
title Testing spatial heterogeneity with stock assessment models
title_short Testing spatial heterogeneity with stock assessment models
title_full Testing spatial heterogeneity with stock assessment models
title_fullStr Testing spatial heterogeneity with stock assessment models
title_full_unstemmed Testing spatial heterogeneity with stock assessment models
title_sort testing spatial heterogeneity with stock assessment models
publishDate 2018
url https://orbit.dtu.dk/en/publications/051409d8-d85f-4b22-81f9-25d37574e506
https://doi.org/10.1371/journal.pone.0190791
https://backend.orbit.dtu.dk/ws/files/142937194/Publishers_version.pdf
genre Northeast Atlantic
genre_facet Northeast Atlantic
op_source Jardim , E , Eero , M , Silva , A , Ulrich , C , Pawlowski , L , Holmes , S J , Ibaibarriaga , L , De Oliveira , J A A , Riveiro , I , Alzorriz , N , Citores , L , Scott , F , Uriarte , A , Carrera , P , Duhamel , E & Mosqueira , I 2018 , ' Testing spatial heterogeneity with stock assessment models ' , P L o S One , vol. 13 , no. 1 , e0190791 . https://doi.org/10.1371/journal.pone.0190791
op_rights info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.1371/journal.pone.0190791
container_title PLOS ONE
container_volume 13
container_issue 1
container_start_page e0190791
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