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: Text
Language:English
Published: Public Library of Science 2018
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Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783371/
http://www.ncbi.nlm.nih.gov/pubmed/29364901
https://doi.org/10.1371/journal.pone.0190791
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spelling ftpubmed:oai:pubmedcentral.nih.gov:5783371 2023-05-15T17:41:32+02:00 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 2018-01-24 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783371/ http://www.ncbi.nlm.nih.gov/pubmed/29364901 https://doi.org/10.1371/journal.pone.0190791 en eng Public Library of Science http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783371/ http://www.ncbi.nlm.nih.gov/pubmed/29364901 http://dx.doi.org/10.1371/journal.pone.0190791 © 2018 Jardim et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. CC-BY Research Article Text 2018 ftpubmed https://doi.org/10.1371/journal.pone.0190791 2018-02-11T01:13:39Z 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. Text Northeast Atlantic PubMed Central (PMC) PLOS ONE 13 1 e0190791
institution Open Polar
collection PubMed Central (PMC)
op_collection_id ftpubmed
language English
topic Research Article
spellingShingle Research Article
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
topic_facet Research Article
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 Text
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
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
publisher Public Library of Science
publishDate 2018
url http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783371/
http://www.ncbi.nlm.nih.gov/pubmed/29364901
https://doi.org/10.1371/journal.pone.0190791
genre Northeast Atlantic
genre_facet Northeast Atlantic
op_relation http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5783371/
http://www.ncbi.nlm.nih.gov/pubmed/29364901
http://dx.doi.org/10.1371/journal.pone.0190791
op_rights © 2018 Jardim et al
http://creativecommons.org/licenses/by/4.0/
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
op_rightsnorm CC-BY
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