Remotely sensed temperature and precipitation data improve species distribution modelling in the tropics

Abstract : Species distribution modelling typically relies completely or partially on climatic variables as predictors, overlooking the fact that these are themselves predictions with associated uncertainties. This is particularly critical when such predictors are interpolated between sparse station data, such as in the tropics. The goal of this study is to provide a new set of satellite-based climatic predictor data and to evaluate its potential to improve modelled species–climate associations and transferability to novel geographical regions.
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Submitted on : Monday, August 29, 2016 - 11:22:37 AM
Last modification on : Monday, August 26, 2019 - 3:42:02 PM

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V. Deblauwe, V. Droissart, R. Bose, B. Sonké, A. Blach-Overgaard, et al.. Remotely sensed temperature and precipitation data improve species distribution modelling in the tropics. Global Ecology and Biogeography Letters, JSTOR, 2016, 25 (4), pp.443-454. ⟨10.1111/geb.12426⟩. ⟨hal-01357119⟩

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