Biogeography has been dominated by a "dispersal versus vicariance" debate. Users of computational methods, which included assumptions with respect to this debate, were often unaware of embedded assumptions. "BioGeoBEARS" (BioGeography with Bayesian (and likelihood) Evolutionary Analysis in R Scripts) is a new approach. Rather than choosing one model a priori, BioGeoBEARS uses multiple models, allowing researchers to perform model testing and model choice of the many different possible models of how current distributions come into being. This book explains the theory and practices of statistical model choice in general, and then explains how these can be applied in biogeography.
Key selling features:
Introduces principles of statistical historical biogeography
Promotes the practical skills needed to run historical biogeography inference in R
Distinguishes theory and the assumptions behind methods
Provides guidance to the creation of publication-quality graphics
Reveals pitfalls and caveats associated with all biogeographic analysis
