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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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 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
topic |
Medicine R Science Q |
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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 |
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13 |
container_issue |
1 |
container_start_page |
e0190791 |
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1766143133502930944 |