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

Abstract

Statistical phylogeographic studies contribute to our understanding of the factors that influence population divergence and speciation, and that ultimately generate biogeographical patterns. The use of coalescent modelling for analyses of genetic data provides a framework for statistically testing alternative hypotheses about the timing and pattern of divergence. However, the extent to which such approaches contribute to our understanding of biogeography depends on how well the alternative hypotheses chosen capture relevant aspects of species histories. New modelling techniques, which explicitly incorporate spatio‐geographic data external to the gene trees themselves, provide a means for generating realistic phylogeographic hypotheses, even for taxa without a detailed fossil record. Here we illustrate how two such techniques – species distribution modelling and its historical extension, palaeodistribution modelling – in conjunction with coalescent simulations can be used to generate and test alternative hypotheses. In doing so, we highlight a few key studies that have creatively integrated both historical geographic and genetic data and argue for the wider incorporation of such explicit integrations in biogeographical studies.

Phylogeographic Patterns of mtDNA Variation Revealed Multiple Glacial Refugia for the Frog Species Feirana taihangnica Endemic to the Qinling Mountains

“…Subsequently, many populations have experienced contractions or expansions of population size and distribution range Knowles 2001;Maddison and McMahon 2000). Furthermore, the levels of genetic differentiation as well as other biological features may influence the lineage sorting, and determine whether different populations would merge into one gene pool within their secondary contact zone (Knowles 2000(Knowles , 2001Smith and Farrell 2005;Richards et al 2007).…”

When east meets west: population structure of a high-latitude resident species, the boreal chickadee (Poecile hudsonicus)

“…The model estimates the potential distribution of a species by assuming that the species is found in its preferred environmental conditions and that the current niche requirements are reflective of those in the past and/or future (that is, niche fidelity; Phillips et al, 2006;Richards et al, 2007).…”

Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty

“…One solution is to model the likelihood of occurrence as a function of the local environment, using the available distribution data and environmental variables as predictors of habitat suitability. Species distribution models have been used previously for biodiversity analysis (Austin, 1999;Ferrier et al, 2002b), improved sampling of rare and endangered species (Engler et al, 2004;Guisan et al, 2006), determination of reserve boundaries (Ferrier et al, 2002a;Araújo et al, 2004), historical reconstruction (Richards et al, 2007) and assessment of climate change impacts (Thomas et al, 2004;McClean et al, 2005). All of these applications could prove extremely useful for the Eastern Arc Mountains of Tanzania and Kenya (EAMs; Lovett, 1985), one of the most important regions for conservation in the world (Olson and Dinerstein, 1998;Stattersfield et al, 1998;Myers et al, 2000), yet to our knowledge no regional-scale predictive model for tree distributions in this area has been published.…”