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: Ernesto Jardim, Margit Eero, Alexandra Silva, Clara Ulrich, Lionel Pawlowski, Steven J Holmes, Leire Ibaibarriaga, José A A De Oliveira, Isabel Riveiro, Nekane Alzorriz, Leire Citores, Finlay Scott, Andres Uriarte, Pablo Carrera, Erwan Duhamel, Iago Mosqueira
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2018
Subjects:
R
Q
Online Access:https://doi.org/10.1371/journal.pone.0190791
https://doaj.org/article/596eda56cde84ea0a82ea1738a219a4a
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spelling ftdoajarticles:oai:doaj.org/article:596eda56cde84ea0a82ea1738a219a4a 2023-05-15T17:41:32+02:00 Testing spatial heterogeneity with stock assessment models. Ernesto Jardim Margit Eero Alexandra Silva Clara Ulrich Lionel Pawlowski Steven J Holmes Leire Ibaibarriaga José A A De Oliveira Isabel Riveiro Nekane Alzorriz Leire Citores Finlay Scott Andres Uriarte Pablo Carrera Erwan Duhamel Iago Mosqueira 2018-01-01T00:00:00Z https://doi.org/10.1371/journal.pone.0190791 https://doaj.org/article/596eda56cde84ea0a82ea1738a219a4a EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC5783371?pdf=render https://doaj.org/toc/1932-6203 1932-6203 doi:10.1371/journal.pone.0190791 https://doaj.org/article/596eda56cde84ea0a82ea1738a219a4a PLoS ONE, Vol 13, Iss 1, p e0190791 (2018) Medicine R Science Q article 2018 ftdoajarticles https://doi.org/10.1371/journal.pone.0190791 2022-12-31T04:40:31Z 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 Directory of Open Access Journals: DOAJ Articles PLOS ONE 13 1 e0190791
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Ernesto Jardim
Margit Eero
Alexandra Silva
Clara Ulrich
Lionel Pawlowski
Steven J Holmes
Leire Ibaibarriaga
José A A De Oliveira
Isabel Riveiro
Nekane Alzorriz
Leire Citores
Finlay Scott
Andres Uriarte
Pablo Carrera
Erwan Duhamel
Iago Mosqueira
Testing spatial heterogeneity with stock assessment models.
topic_facet Medicine
R
Science
Q
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 Ernesto Jardim
Margit Eero
Alexandra Silva
Clara Ulrich
Lionel Pawlowski
Steven J Holmes
Leire Ibaibarriaga
José A A De Oliveira
Isabel Riveiro
Nekane Alzorriz
Leire Citores
Finlay Scott
Andres Uriarte
Pablo Carrera
Erwan Duhamel
Iago Mosqueira
author_facet Ernesto Jardim
Margit Eero
Alexandra Silva
Clara Ulrich
Lionel Pawlowski
Steven J Holmes
Leire Ibaibarriaga
José A A De Oliveira
Isabel Riveiro
Nekane Alzorriz
Leire Citores
Finlay Scott
Andres Uriarte
Pablo Carrera
Erwan Duhamel
Iago Mosqueira
author_sort Ernesto Jardim
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 (PLoS)
publishDate 2018
url https://doi.org/10.1371/journal.pone.0190791
https://doaj.org/article/596eda56cde84ea0a82ea1738a219a4a
genre Northeast Atlantic
genre_facet Northeast Atlantic
op_source PLoS ONE, Vol 13, Iss 1, p e0190791 (2018)
op_relation http://europepmc.org/articles/PMC5783371?pdf=render
https://doaj.org/toc/1932-6203
1932-6203
doi:10.1371/journal.pone.0190791
https://doaj.org/article/596eda56cde84ea0a82ea1738a219a4a
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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