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...

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Published in:PLOS ONE
Main Authors: Virgili, Auriane, Hedon, Laura, Authier, Matthieu, Calmettes, Beatriz, Claridge, Diane, Cole, Tim, Corkeron, Peter, Doremus, Ghislain, Dunn, Charlotte, Dunn, Tim E, Laran, Sophie, Lehodey, Patrick, Lewis, Mark, Louzao, Maite, Mannocci, Laura
Format: Article in Journal/Newspaper
Language:English
Published: Public Library Science 2021
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Online Access:https://hdl.handle.net/10072/431118
https://doi.org/10.1371/journal.pone.0255667
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spelling ftgriffithuniv:oai:research-repository.griffith.edu.au:10072/431118 2024-06-23T07:56:13+00:00 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 Doremus, Ghislain Dunn, Charlotte Dunn, Tim E Laran, Sophie Lehodey, Patrick Lewis, Mark Louzao, Maite Mannocci, Laura 2021 https://hdl.handle.net/10072/431118 https://doi.org/10.1371/journal.pone.0255667 English eng Public Library Science PLoS ONE Virgili, A; Hedon, L; Authier, M; Calmettes, B; Claridge, D; Cole, T; Corkeron, P; Doremus, G; Dunn, C; Dunn, TE; Laran, S; Lehodey, P; Lewis, M; Louzao, M; Mannocci, L; et al., Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?, PLoS ONE, 2021, 16 (8) https://hdl.handle.net/10072/431118 1932-6203 doi:10.1371/journal.pone.0255667 https://creativecommons.org/licenses/by/4.0/ © 2021 Virgili et al. 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. open access Journal article 2021 ftgriffithuniv https://doi.org/10.1371/journal.pone.0255667 2024-05-29T00:05:25Z 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 ... Article in Journal/Newspaper Physeter macrocephalus Griffith University: Griffith Research Online PLOS ONE 16 8 e0255667
institution Open Polar
collection Griffith University: Griffith Research Online
op_collection_id ftgriffithuniv
language English
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 ...
format Article in Journal/Newspaper
author Virgili, Auriane
Hedon, Laura
Authier, Matthieu
Calmettes, Beatriz
Claridge, Diane
Cole, Tim
Corkeron, Peter
Doremus, Ghislain
Dunn, Charlotte
Dunn, Tim E
Laran, Sophie
Lehodey, Patrick
Lewis, Mark
Louzao, Maite
Mannocci, Laura
spellingShingle Virgili, Auriane
Hedon, Laura
Authier, Matthieu
Calmettes, Beatriz
Claridge, Diane
Cole, Tim
Corkeron, Peter
Doremus, Ghislain
Dunn, Charlotte
Dunn, Tim E
Laran, Sophie
Lehodey, Patrick
Lewis, Mark
Louzao, Maite
Mannocci, Laura
Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?
author_facet Virgili, Auriane
Hedon, Laura
Authier, Matthieu
Calmettes, Beatriz
Claridge, Diane
Cole, Tim
Corkeron, Peter
Doremus, Ghislain
Dunn, Charlotte
Dunn, Tim E
Laran, Sophie
Lehodey, Patrick
Lewis, Mark
Louzao, Maite
Mannocci, Laura
author_sort Virgili, Auriane
title 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_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_sort towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?
publisher Public Library Science
publishDate 2021
url https://hdl.handle.net/10072/431118
https://doi.org/10.1371/journal.pone.0255667
genre Physeter macrocephalus
genre_facet Physeter macrocephalus
op_relation PLoS ONE
Virgili, A; Hedon, L; Authier, M; Calmettes, B; Claridge, D; Cole, T; Corkeron, P; Doremus, G; Dunn, C; Dunn, TE; Laran, S; Lehodey, P; Lewis, M; Louzao, M; Mannocci, L; et al., Towards a better characterisation of deep-diving whales' distributions by using prey distribution model outputs?, PLoS ONE, 2021, 16 (8)
https://hdl.handle.net/10072/431118
1932-6203
doi:10.1371/journal.pone.0255667
op_rights https://creativecommons.org/licenses/by/4.0/
© 2021 Virgili et al. 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.
open access
op_doi https://doi.org/10.1371/journal.pone.0255667
container_title PLOS ONE
container_volume 16
container_issue 8
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