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Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs?
In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environ...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336804/ https://www.ncbi.nlm.nih.gov/pubmed/34347854 http://dx.doi.org/10.1371/journal.pone.0255667 |
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author | Virgili, Auriane Hedon, Laura Authier, Matthieu Calmettes, Beatriz Claridge, Diane Cole, Tim Corkeron, Peter Dorémus, Ghislain Dunn, Charlotte Dunn, Tim E. Laran, Sophie Lehodey, Patrick Lewis, Mark Louzao, Maite Mannocci, Laura Martínez-Cedeira, José Monestiez, Pascal Palka, Debra Pettex, Emeline Roberts, Jason J. Ruiz, Leire Saavedra, Camilo Santos, M. Begoña Van Canneyt, Olivier Bonales, José Antonio Vázquez Ridoux, Vincent |
author_facet | Virgili, Auriane Hedon, Laura Authier, Matthieu Calmettes, Beatriz Claridge, Diane Cole, Tim Corkeron, Peter Dorémus, Ghislain Dunn, Charlotte Dunn, Tim E. Laran, Sophie Lehodey, Patrick Lewis, Mark Louzao, Maite Mannocci, Laura Martínez-Cedeira, José Monestiez, Pascal Palka, Debra Pettex, Emeline Roberts, Jason J. Ruiz, Leire Saavedra, Camilo Santos, M. Begoña Van Canneyt, Olivier Bonales, José Antonio Vázquez Ridoux, Vincent |
author_sort | Virgili, Auriane |
collection | PubMed |
description | In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans. |
format | Online Article Text |
id | pubmed-8336804 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-83368042021-08-05 Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? Virgili, Auriane Hedon, Laura Authier, Matthieu Calmettes, Beatriz Claridge, Diane Cole, Tim Corkeron, Peter Dorémus, Ghislain Dunn, Charlotte Dunn, Tim E. Laran, Sophie Lehodey, Patrick Lewis, Mark Louzao, Maite Mannocci, Laura Martínez-Cedeira, José Monestiez, Pascal Palka, Debra Pettex, Emeline Roberts, Jason J. Ruiz, Leire Saavedra, Camilo Santos, M. Begoña Van Canneyt, Olivier Bonales, José Antonio Vázquez Ridoux, Vincent PLoS One Research Article In habitat modelling, environmental variables are assumed to be proxies of lower trophic levels distribution and by extension, of marine top predator distributions. More proximal variables, such as potential prey fields, could refine relationships between top predator distributions and their environment. In situ data on prey distributions are not available over large spatial scales but, a numerical model, the Spatial Ecosystem And POpulation DYnamics Model (SEAPODYM), provides simulations of the biomass and production of zooplankton and six functional groups of micronekton at the global scale. Here, we explored whether generalised additive models fitted to simulated prey distribution data better predicted deep-diver densities (here beaked whales Ziphiidae and sperm whales Physeter macrocephalus) than models fitted to environmental variables. We assessed whether the combination of environmental and prey distribution data would further improve model fit by comparing their explanatory power. For both taxa, results were suggestive of a preference for habitats associated with topographic features and thermal fronts but also for habitats with an extended euphotic zone and with large prey of the lower mesopelagic layer. For beaked whales, no SEAPODYM variable was selected in the best model that combined the two types of variables, possibly because SEAPODYM does not accurately simulate the organisms on which beaked whales feed on. For sperm whales, the increase model performance was only marginal. SEAPODYM outputs were at best weakly correlated with sightings of deep-diving cetaceans, suggesting SEAPODYM may not accurately predict the prey fields of these taxa. This study was a first investigation and mostly highlighted the importance of the physiographic variables to understand mechanisms that influence the distribution of deep-diving cetaceans. A more systematic use of SEAPODYM could allow to better define the limits of its use and a development of the model that would simulate larger prey beyond 1,000 m would probably better characterise the prey of deep-diving cetaceans. Public Library of Science 2021-08-04 /pmc/articles/PMC8336804/ /pubmed/34347854 http://dx.doi.org/10.1371/journal.pone.0255667 Text en © 2021 Virgili et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Virgili, Auriane Hedon, Laura Authier, Matthieu Calmettes, Beatriz Claridge, Diane Cole, Tim Corkeron, Peter Dorémus, Ghislain Dunn, Charlotte Dunn, Tim E. Laran, Sophie Lehodey, Patrick Lewis, Mark Louzao, Maite Mannocci, Laura Martínez-Cedeira, José Monestiez, Pascal Palka, Debra Pettex, Emeline Roberts, Jason J. Ruiz, Leire Saavedra, Camilo Santos, M. Begoña Van Canneyt, Olivier Bonales, José Antonio Vázquez Ridoux, Vincent Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
title | Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
title_full | Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
title_fullStr | Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
title_full_unstemmed | Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
title_short | Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
title_sort | towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8336804/ https://www.ncbi.nlm.nih.gov/pubmed/34347854 http://dx.doi.org/10.1371/journal.pone.0255667 |
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