Quantile regression models for fish recruitment environment relationships: four case studies
Understanding and modelling the environmental control of fish recruitment has been a 14 central question in fish population ecology for the last century. Most environment -recruitment models have primarily been developed to model mean recruitment using conventional regression techniques which assume...
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ftarchimer:oai:archimer.ifremer.fr:3985 2023-05-15T14:30:23+02:00 Quantile regression models for fish recruitment environment relationships: four case studies Planque, Benjamin Buffaz, Laure 2008-04 application/pdf https://archimer.ifremer.fr/doc/2008/publication-3985.pdf https://doi.org/10.3354/meps07274 https://archimer.ifremer.fr/doc/00000/3985/ eng eng Inter-Research https://archimer.ifremer.fr/doc/2008/publication-3985.pdf doi:10.3354/meps07274 https://archimer.ifremer.fr/doc/00000/3985/ 2008 Inter-Research info:eu-repo/semantics/openAccess restricted use Marine Ecology Progress Series (0171-8630) (Inter-Research), 2008-04 , Vol. 357 , P. 213-223 Autocorrelated time series Pacific sardine Bay of Biscay anchovy Atlanto scandian herring Northeast Arctic cod Quantile regression models Environment recruitment text Publication info:eu-repo/semantics/article 2008 ftarchimer https://doi.org/10.3354/meps07274 2021-09-23T20:15:45Z Understanding and modelling the environmental control of fish recruitment has been a 14 central question in fish population ecology for the last century. Most environment -recruitment models have primarily been developed to model mean recruitment using conventional regression techniques which assume that all environmental parameters are included and that the residual unexplained variability is unstructured. However, the complexity of environmental controls and the empirical evidence that many relationships have failed when retested suggest that these assumptions are generally not met. Most environmental controls may be considered as limiting factors to recruitment and act in interaction with other factors (often not measured or not known). We used quantile regression modelling, which is specifically designed to model limiting relationships, to reanalyse environment-recruitment relationships that have been published for 4 fish stocks: (1) Northeast Arctic cod (Barents Sea), (2) Atlanto-Scandian herring, (3) Bay of Biscay anchovy and (4) Pacific sardine. The method was adapted to the specific case of autocorrelated time series, a common feature of most environmental signals. The results from quantile regression were not straightforward extensions of conventional regressions. For Northeast Arctic cod and Pacific sardine, the original relationships with temperature were not statistically significant in the quantile model. For Atlanto-Scandian herring the relationship was confirmed and temperature clearly appeared as a limiting factor to recruitment, The published relationship for the Bay of Biscay anchovy with upwelling was not confirmed, but the previously undetected relationship with river runoff was established. In this specific case, it was only by using a quantile model that the relationship could be detected as statistically significant. These results confirm the ability of quantile regression models to provide robust interpretation of environment-recruitment relationships and to produce environmentally based advance warning when recruitment is expected to be low. Article in Journal/Newspaper Arctic cod Arctic Barents Sea Northeast Arctic cod Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) Arctic Barents Sea Pacific Marine Ecology Progress Series 357 213 223 |
institution |
Open Polar |
collection |
Archimer (Archive Institutionnelle de l'Ifremer - Institut français de recherche pour l'exploitation de la mer) |
op_collection_id |
ftarchimer |
language |
English |
topic |
Autocorrelated time series Pacific sardine Bay of Biscay anchovy Atlanto scandian herring Northeast Arctic cod Quantile regression models Environment recruitment |
spellingShingle |
Autocorrelated time series Pacific sardine Bay of Biscay anchovy Atlanto scandian herring Northeast Arctic cod Quantile regression models Environment recruitment Planque, Benjamin Buffaz, Laure Quantile regression models for fish recruitment environment relationships: four case studies |
topic_facet |
Autocorrelated time series Pacific sardine Bay of Biscay anchovy Atlanto scandian herring Northeast Arctic cod Quantile regression models Environment recruitment |
description |
Understanding and modelling the environmental control of fish recruitment has been a 14 central question in fish population ecology for the last century. Most environment -recruitment models have primarily been developed to model mean recruitment using conventional regression techniques which assume that all environmental parameters are included and that the residual unexplained variability is unstructured. However, the complexity of environmental controls and the empirical evidence that many relationships have failed when retested suggest that these assumptions are generally not met. Most environmental controls may be considered as limiting factors to recruitment and act in interaction with other factors (often not measured or not known). We used quantile regression modelling, which is specifically designed to model limiting relationships, to reanalyse environment-recruitment relationships that have been published for 4 fish stocks: (1) Northeast Arctic cod (Barents Sea), (2) Atlanto-Scandian herring, (3) Bay of Biscay anchovy and (4) Pacific sardine. The method was adapted to the specific case of autocorrelated time series, a common feature of most environmental signals. The results from quantile regression were not straightforward extensions of conventional regressions. For Northeast Arctic cod and Pacific sardine, the original relationships with temperature were not statistically significant in the quantile model. For Atlanto-Scandian herring the relationship was confirmed and temperature clearly appeared as a limiting factor to recruitment, The published relationship for the Bay of Biscay anchovy with upwelling was not confirmed, but the previously undetected relationship with river runoff was established. In this specific case, it was only by using a quantile model that the relationship could be detected as statistically significant. These results confirm the ability of quantile regression models to provide robust interpretation of environment-recruitment relationships and to produce environmentally based advance warning when recruitment is expected to be low. |
format |
Article in Journal/Newspaper |
author |
Planque, Benjamin Buffaz, Laure |
author_facet |
Planque, Benjamin Buffaz, Laure |
author_sort |
Planque, Benjamin |
title |
Quantile regression models for fish recruitment environment relationships: four case studies |
title_short |
Quantile regression models for fish recruitment environment relationships: four case studies |
title_full |
Quantile regression models for fish recruitment environment relationships: four case studies |
title_fullStr |
Quantile regression models for fish recruitment environment relationships: four case studies |
title_full_unstemmed |
Quantile regression models for fish recruitment environment relationships: four case studies |
title_sort |
quantile regression models for fish recruitment environment relationships: four case studies |
publisher |
Inter-Research |
publishDate |
2008 |
url |
https://archimer.ifremer.fr/doc/2008/publication-3985.pdf https://doi.org/10.3354/meps07274 https://archimer.ifremer.fr/doc/00000/3985/ |
geographic |
Arctic Barents Sea Pacific |
geographic_facet |
Arctic Barents Sea Pacific |
genre |
Arctic cod Arctic Barents Sea Northeast Arctic cod |
genre_facet |
Arctic cod Arctic Barents Sea Northeast Arctic cod |
op_source |
Marine Ecology Progress Series (0171-8630) (Inter-Research), 2008-04 , Vol. 357 , P. 213-223 |
op_relation |
https://archimer.ifremer.fr/doc/2008/publication-3985.pdf doi:10.3354/meps07274 https://archimer.ifremer.fr/doc/00000/3985/ |
op_rights |
2008 Inter-Research info:eu-repo/semantics/openAccess restricted use |
op_doi |
https://doi.org/10.3354/meps07274 |
container_title |
Marine Ecology Progress Series |
container_volume |
357 |
container_start_page |
213 |
op_container_end_page |
223 |
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1766304236295946240 |