Species distribution modeling (SDM) enables conservation scientists to make range estimates for species of concern, as well as predictions of potential range in unsampled areas and for different time periods. With colleagues, we recently (Kass et al., Ecography 2023) developed the application Wallace EcoMod (https://wallaceecomod.github.io/), which offers access to the latest SDM tools through [...]
Understanding paleoclimatic variations is crucial for deciphering the historical shifts in global ecosystems, which have shaped today's biodiversity. The Temporal Altitudinal Biogeographical Shifts (TABS) R package is a powerful tool designed to model these shifts, providing spatially detailed reconstructions over continuous time series. This workshop aims to equip participants with the knowledge and skills [...]
Species distribution models (SDMs) are widely used as a tool for understanding species spatial ecology. They link species occurrence or abundance with environmental features of the location, via statistical modelling. According to ecological niche theory, species response curves are unimodal with respect to environmental gradients. A general problem with most habitat modelling approaches is [...]
sdm is a comprehensive modelling and simulation framework that enables fitting of individual and community-based species distribution models, while supporting markedly different modelling methods including correlative, process-based (mechanistic), agent-based, and cellular automata. It generates ensembles of models, and several options for evaluation of model results and projection of species potential distributions in space and [...]
Bayesian Additive Regression Trees (BART) are a powerful machine learning technique with very promising applications in ecology and biogeography in general, and in species distribution modelling (SDM) in particular. BART can produce highly accurate predictions without overfitting to noise or to particular cases in the data. Notably, unlike most SDM methods, BART generally shows [...]