Statistical phylogeography

Abstract

While studies of phylogeography and speciation in the past have largely focused on the documentation or detection of significant patterns of population genetic structure, the emerging field of statistical phylogeography aims to infer the history and processes underlying that structure, and to provide objective, rather than ad hoc explanations. Methods for parameter estimation are now commonly used to make inferences about demographic past. Although these approaches are well developed statistically, they typically pay little attention to geographical history. In contrast, methods that seek to reconstruct phylogeographic history are able to consider many alternative geographical scenarios, but are primarily nonstatistical, making inferences about particular biological processes without explicit reference to stochastically derived expectations. We advocate the merging of these two traditions so that statistical phylogeographic methods can provide an accurate representation of the past, consider a diverse array of processes, and yet yield a statistical estimate of that history. We discuss various conceptual issues associated with statistical phylogeographic inferences, considering especially the stochasticity of population genetic processes and assessing the confidence of phylogeographic conclusions. To this end, we present some empirical examples that utilize a statistical phylogeographic approach, and then by contrasting results from a coalescent-based approach to those from Templeton's nested cladistic analysis (NCA), we illustrate the importance of assessing error. Because NCA does not assess error in its inferences about historical processes or contemporary gene flow, we performed a small-scale study using simulated data to examine how our conclusions might be affected by such unconsidered errors. NCA did not identify the processes used to simulate the data, confusing among deterministic processes and the stochastic sorting of gene lineages. There is as yet insufficient justification of NCA's ability to accurately infer or distinguish among alternative processes. We close with a discussion of some unresolved problems of current statistical phylogeographic methods to propose areas in need of future development.

Phylogeny, phylogeography, phylobetadiversity and the molecular analysis of biological communities

“…[14,15]). The field has subsequently developed with a greater emphasis on approaches that consider both mutational and coalescent variance, referred to as statistical phylogeography [16]. The availability of tools for statistical hypothesis testing, combined with the use of multiple loci for phylogeographic inference, means that one can undertake rigorous phylogeographic analyses either within or among species (see [12,17] for recent reviews).…”

“…Thus, one can potentially undertake comparative phylogeographic analyses, with each focal species being sampled for multiple genetic loci, although this comprises a large task that has not been realized to date; so far studies have focused on one species and several genes (e.g. [14][15][16][17]18,19]) or several species and one gene (e.g. [20][21][22][23]).…”

Phylogeography: its development and impact in Australo-Papuan ornithology with special reference to paraphyly in Australian birds

“…These guesses may or may not accurately capture the biogeographical and temporal features of a species' history (Knowles and Maddison 2002). For example, a simple underlying population history is often assumed, such as simple divergence of two undivided populations of constant size.…”

“…It integrated geographical and genetic data from specimens in a study to determine, for example, where vicariance could be supported or rejected, where dispersal was needed to explain the data, and so on. Although widely seized upon by phylogeographers, NCA is controversial (Knowles and Maddison 2002;Templeton 2004). Petit (2008a) argued that NCA is fatally flawed in generating false-positive results at unacceptable rates and more debate predictably ensued (Garrick et al 2008a;Knowles 2008;Petit 2008b;Templeton 2008).…”

“…Joseph and Wilke (2007) used it as a minor, complementary analysis in examining diversity in three species widespread across the Australian arid zone. Statistical phylogeography was advocated in response to perceived problems with NCA (Knowles and Maddison 2002). Its basic tenet is that phylogeographic data should only be interpreted against a priori models.…”