FN Archimer Export Format
PT J
TI Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs?
BT 
AF 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
AS 1:1;2:1;3:1;4:2;5:3;6:4;7:4;8:1;9:3;10:5;11:1;12:2;13:4;14:6;15:7;16:8;17:9;18:4;19:10;20:11;21:12;22:13;23:13;24:1;25:14;26:1,15;
FF 1:;2:;3:;4:;5:;6:;7:;8:;9:;10:;11:;12:;13:;14:;15:;16:;17:;18:;19:;20:;21:;22:;23:;24:;25:;26:;
C1 Observatoire PELAGIS, UMS 3462 CNRS—La Rochelle Université, La Rochelle, France
   Space Oceanography Division, CLS, Ramonville, France
   Bahamas Marine Mammal Research Organisation, Marsh Harbour, Abaco, Bahamas
   Protected Species Branch, NOAA Fisheries Northeast Fisheries Science, Woods Hole, Massachusetts, United States of America
   Joint Nature Conservation Committee, Inverdee House, Aberdeen, United Kingdom
   AZTI, Marine Research, Basque Research and Technology Alliance (BRTA), Pasaia, Spain
   MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Sète, France
   CEMMA, Pontevedra, Spain
   BioSP, INRA, Avignon, France, Centre d’Etudes Biologiques de Chizé - La Rochelle, UMR 7372 CNRS—La Rochelle Université, Villiers-en-Bois, France
   ADERA, Pessac Cedex, Pessac, France, Cohabys—ADERA, La Rochelle Université, La Rochelle, France
   Marine Geospatial Ecology Laboratory, Duke University, Durham, North Carolina, United States of America
   AMBAR Elkartea Organisation, Bizkaia, Spain
   Instituto Español de Oceanografía, Centro Oceanográfico de Vigo, Vigo, Spain
   Alnilam Research and Conservation, Madrid, Spain
   Centre d’Etudes Biologiques de Chizé - La Rochelle, UMR 7372 CNRS—La Rochelle Université, Villiers-en-Bois, France
C2 UNIV LA ROCHELLE, FRANCE
   CLS, FRANCE
   BMMRO, BAHAMAS
   NOAA, USA
   JNCC, UK
   AZTI, SPAIN
   UNIV MONTPELLIER, FRANCE
   CEMMA, SPAIN
   INRA, FRANCE
   ADERA, FRANCE
   UNIV DUKE, USA
   AMBAR ELKARTEA ORGANISATION, SPAIN
   IEO, SPAIN
   ALNILAM RESEARCH AND CONSERVATION, SPAIN
   CNRS, FRANCE
UM MARBEC
IN WOS Cotutelle UMR
   DOAJ
   copubli-france
   copubli-europe
   copubli-univ-france
   copubli-int-hors-europe
IF 3.752
TC 8
UR https://archimer.ifremer.fr/doc/00710/82202/87006.pdf
   https://archimer.ifremer.fr/doc/00710/82202/87007.pdf
   https://archimer.ifremer.fr/doc/00710/82202/87008.pdf
   https://archimer.ifremer.fr/doc/00710/82202/87009.pdf
   https://archimer.ifremer.fr/doc/00710/82202/87010.tif
LA English
DT Article
AB 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. 
PY 2021
PD AUG
SO Plos One
SN 1932-6203
PU Public Library of Science (PLoS)
VL 16
IS 8
UT 000685264900069
DI 10.1371/journal.pone.0255667
ID 82202
ER

EF