Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs?
Type | Article |
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Date | 2021-08 |
Language | English |
Author(s) | Virgili Auriane1, Hedon Laura1, Authier Matthieu1, Calmettes Beatriz2, Claridge Diane3, Cole Tim4, Corkeron Peter4, Dorémus Ghislain1, Dunn Charlotte3, Dunn Tim E.5, Laran Sophie1, Lehodey Patrick2, Lewis Mark4, Louzao Maite6, Mannocci Laura7, Martínez-Cedeira José8, Monestiez Pascal9, Palka Debra4, Pettex Emeline10, Roberts Jason J.11, Ruiz Leire12, Saavedra Camilo13, Santos M. Begoña13, Van Canneyt Olivier1, Bonales José Antonio Vázquez14, Ridoux Vincent1, 15 |
Affiliation(s) | 1 : Observatoire PELAGIS, UMS 3462 CNRS—La Rochelle Université, La Rochelle, France 2 : Space Oceanography Division, CLS, Ramonville, France 3 : Bahamas Marine Mammal Research Organisation, Marsh Harbour, Abaco, Bahamas 4 : Protected Species Branch, NOAA Fisheries Northeast Fisheries Science, Woods Hole, Massachusetts, United States of America 5 : Joint Nature Conservation Committee, Inverdee House, Aberdeen, United Kingdom 6 : AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Pasaia, Spain 7 : MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Sète, France 8 : CEMMA, Pontevedra, Spain 9 : BioSP, INRA, Avignon, France, Centre d’Etudes Biologiques de Chizé - La Rochelle, UMR 7372 CNRS—La Rochelle Université, Villiers-en-Bois, France 10 : ADERA, Pessac Cedex, Pessac, France, Cohabys—ADERA, La Rochelle Université, La Rochelle, France 11 : Marine Geospatial Ecology Laboratory, Duke University, Durham, North Carolina, United States of America 12 : AMBAR Elkartea Organisation, Bizkaia, Spain 13 : Instituto Español de Oceanografía, Centro Oceanográfico de Vigo, Vigo, Spain 14 : Alnilam Research and Conservation, Madrid, Spain 15 : Centre d’Etudes Biologiques de Chizé - La Rochelle, UMR 7372 CNRS—La Rochelle Université, Villiers-en-Bois, France |
Source | Plos One (1932-6203) (Public Library of Science (PLoS)), 2021-08 , Vol. 16 , N. 8 , P. e0255667 (21p.) |
DOI | 10.1371/journal.pone.0255667 |
WOS© Times Cited | 8 |
Abstract | 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. |
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