Accounting for spatial sampling patterns in Bayesian phylogeography

Statistical phylogeography provides useful tools to characterize and quantify the spread of organisms during the course of evolution. Analyzing georeferenced genetic data often relies on the assumption that samples are preferentially collected in densely populated areas of the habitat. Deviation from this assumption negatively impacts the inference of the spatial and demographic dynamics. This issue is pervasive in phylogeography. It affects analyses that approximate the habitat as a set of discrete demes as well as those that treat it as a continuum. The present study introduces a Bayesian modeling approach that explicitly accommodates for spatial sampling strategies. An original inference technique, based on recent advances in statistical computing, is then described that is most suited to modeling data where sequences are preferentially collected at certain locations, independently of the outcome of the evolutionary process. The analysis of georeferenced genetic sequences from the West Nile virus in North America along with simulated data shows how assumptions about spatial sampling may impact our understanding of the forces shaping biodiversity across time and space.

Genetic hubs: a phylogeographer’s widget for pinpointing of ancestral populations

Statistical phylogeography benefits from the development of increasingly realistic models of spatially structured genetic variation. Their fitting, however, is computationally demanding and requires population and/or genomic sampling that is not available for many species of interest. ‘Genetic hubs’ is a method that can be used for exploratory analyses of various kinds of genetic data, including those as typical in mitochondrial phylogeography, i.e. many small samples of single locus genotypes scattered throughout the species distributional range. ‘Genetic hubs’ allows to quantify and visualize gradients of genetic variation with the aim to pinpoint possible origin of expansion. It estimates local genetic variability as an accessibility of all genetic variation from the site in question and it allows to take dissimilarity of genotypes into account. The method represents fast and versatile tool that can be used whenever history of range expansion is assumed to shape the observed distribution of genetic variation and it is useful especially for preliminary analyses whose purpose is to provide sound basis for formulation of testable hypotheses and design of follow-up studies.