bioRxiv preprint doi: https://doi.org/10.1101/774604; this version posted December 26, 2019. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. 1 embarcadero: 2 Species distribution modelling with Bayesian additive 3 regression trees in R 1,y 4 Colin J. Carlson 1 5 Department of Biology, Georgetown University, Washington, D.C. 20057, USA. y 6 Correspondence should be directed to
[email protected]. 7 Submitted to Methods in Ecology and Evolution on December 26, 2019 8 Abstract 9 1. embarcadero is an R package of convenience tools for species distribution mod- 10 elling with Bayesian additive regression trees (BART), a powerful machine learning 11 approach that has been rarely applied to ecological problems. 12 13 2. Like other classification and regression tree methods, BART estimates the prob- 14 ability of a binary outcome based on a set of decision trees. Unlike other methods, 15 BART iteratively generates sets of trees based on a set of priors about tree structure 16 and nodes, and builds a posterior distribution of estimated classification probabili- 17 ties. So far, BARTs have yet to be applied to species distribution modelling. 18 19 3. embarcadero is a workflow wrapper for BART species distribution models, and 20 includes functionality for easy spatial prediction, an automated variable selection 21 procedure, several types of partial dependence visualization, and other tools for eco- 22 logical application.