Uncertainty, priors, autocorrelation and disparate data in downscaling of species distributions

Abstract

We provide a step-by-step demonstration of how a map of species' detections at continental extent can be downscaled to a fine-grain map of occurrence probabilities using a two-scale hierarchical Bayesian modelling (HBM). The method requires fine-grain environmental data, but it does not require fine-grain data on species detections.

We demonstrate how it can incorporate spatial autocorrelation (SAC) and informative priors based on known habitat preferences, and how it can provide maps of uncertainty about the downscaled predictions.

Keywords

• Cross-scale
• dispersal limitation
• maps of uncertainty
• multigrain
• niche modelling
• small area estimation
• species distribution modelling