Towards a better characterisation of deep-diving whales’ distributions by using prey distribution model outputs?
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AuthorsVirgili, A. (Auriane); Authier, M. (Matthieu); Boisseau, O. (Oliver); Cañadas, A. (Ana); Claridge, D. (Diane); Cole, T. (Tim); Corkeron, P. (Peter); Dorémus, G. (Ghislain); David, L. (Léa); Di-Méglio, Nathalie; Dunn, C.(Charlotte); Dunn, T.E. (Tim E.); García-Barón, I. (Isabel); Laran, S. (Sophie); Lewis, M. (Mark); Louzao-Arsuaga, M. (Maite); Mannocci, L. (Laura); Martínez-Cedeira, J.A. (José Antonio); Palka, D. (Debra); Panigada, S. (Simone); Pettex, E.; Roberts, J.; Ruiz-Sancho, L.; Santos, M.B. (María Begoña); Saavedra, C. (Camilo); Van-Canneyt, O. (Olivier); Vázquez-Bonales, J.A. (José Antonio); Monastiez, P.; Ridoux, V. (Vincent)
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 deepdiver 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 expla ...
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