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.