%0 Journal Article %A Colin J. Carlson %T embarcadero: Species distribution modelling with Bayesian additive regression trees in R %D 2019 %R 10.1101/774604 %J bioRxiv %P 774604 %X Classification and regression tree methods, like random forests (RF) or boosted regression trees (BRT), are one of the most popular methods of mapping species distributions.Bayesian additive regression trees (BARTs) are a relatively new alternative to other popular regression tree approaches. Whereas BRT iteratively fits an ensemble of trees each explaining smaller fractions of the total variance, BART starts by fitting a sum-of-trees model and then uses Bayesian backfitting with an MCMC algorithm to create a posterior draw. So far, BARTs have yet to be applied to species distribution modeling.embarcadero is an R package of convenience tools for researchers interested in species distribution modeling with BARTs. It includes functionality for spatial prediction, an automated variable selection and importance procedure, and other functionality for rapid implementation and data visualization.To show how embarcadero can be used by ecologists, we re-map the distribution of Crimean-Congo haemorrhagic fever and a likely vector, Hyalomma truncatum, in Africa. %U https://www.biorxiv.org/content/biorxiv/early/2019/09/19/774604.full.pdf