Poor transferability of species distribution models for a pelagic predator, the Grey Petrel, indicates contrasting habitat preferences across Ocean Basins

• Published in: PLOS ONE
• Main Authors: Torres, Leigh G., Sutton, Philip J. H., Thompson, David R., Delord, Karine, Weimerskirch, Henri, Sagar, Paul M., Sommer, Erica, Dilley, Ben J., Ryan, Peter G., Phillips, Richard A.
• Other Authors: National Institute of Water and Atmospheric Research Wellington (NIWA), Centre d'Études Biologiques de Chizé - UMR 7372 (CEBC), Université de La Rochelle (ULR)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), National Institute of Water and Atmospheric Research Christchurch (NIWA), Percy FitzPatrick Institute of African Ornithology, University of Cape Town, DST/NRF Centre of Excellence, University of Cape Town-Percy FitzPatrick Institute of African Ornithology, British Antarctic Survey (BAS), Natural Environment Research Council (NERC)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2015
• Subjects: [SDE]Environmental Sciences; Antarctic; Kerguelen; Antarc*; Marion Island
• Online Access: https://hal.archives-ouvertes.fr/hal-01138142; https://doi.org/10.1371/journal.pone.0120014

International audience Species distribution models (SDMs) are increasingly applied in conservation management to predict suitable habitat for poorly known populations. High predictive performance of SDMs is evident in validations performed within the model calibration area (interpolation), but few studies have assessed SDM transferability to novel areas (extrapolation), particularly across large spatial scales or pelagic ecosystems. We performed rigorous SDM validation tests on distribution data from three populations of a long-ranging marine predator, the grey petrel Procellaria cinerea, to assess model transferability across the Southern Hemisphere (25-65°S). Oceanographic data were combined with tracks of grey petrels from two remote sub-Antarctic islands (Antipodes and Kerguelen) using boosted regression trees to generate three SDMs: one for each island population, and a combined model. The predictive performance of these models was assessed using withheld tracking data from within the model calibration areas (interpolation), and from a third population, Marion Island (extrapolation). Predictive performance was assessed using k-fold cross validation and point biserial correlation. The two population-specific SDMs included the same predictor variables and suggested birds responded to the same broad-scale oceanographic influences. However, all model validation tests, including of the combined model, determined strong interpolation but weak extrapolation capabilities. These results indicate that habitat use reflects both its availability and bird preferences, such that the realized distribution patterns differ for each population. The spatial predictions by the three SDMs were compared with tracking data and fishing effort to demonstrate the conservation pitfalls of extrapolating SDMs outside calibration regions. This exercise revealed that SDM predictions would have led to an underestimate of overlap with fishing effort and potentially misinformed bycatch mitigation efforts. Although SDMs can elucidate ...