Distribution modelling and statistical phylogeography: an integrative framework for generating and testing alternative biogeographical hypotheses

Biogeographical research seeks to identify the processes structuring organismal diversity at a variety of geographic and taxonomic scales, from community patterns of species richness to higher-order taxonomic study. Molecular data are featured prominently in contemporary biogeographical studies because patterns of genetic variation, when interpreted in the context of geography, can provide insights into the historical demographic and biogeographical history of species (Avise et al., 1987; Avise, 2000; Knowles & Maddison, 2002). However, whereas the relationship between geographic distribution and genetic variation is central to biogeography, as Kidd & Ritchie (2006) recently noted, phylogeographic research has to date placed most of its emphasis on the ‘phylo’ component, and much less on ‘geography’, despite the inherent information that the spatial-geographic component contains about the evolutionary past. These authors illustrate the potential of new GIS-based techniques to bring phylogeography back into balance, not only allowing a more powerful investigation of the geographic components of genetic variation, but also facilitating the formation of historical biogeographical hypotheses. We argue that GIS-based approaches to generating such alternative hypotheses, when coupled with genetic approaches to testing them, have the potential to increase profoundly the rigour of phylogeographic research. Herein we aim to provide readers with the necessary tools and conceptual background to take advantage of this powerful combination of distribution and coalescent-based modelling techniques in generating and testing biogeographical hypotheses. This approach has broad utility given that the required data can be readily generated for many taxa.