Phylogeographic analyses are a common approach in molecular ecology, connecting historical processes in evolution with spatial distributions that traditionally scale over millions of years [6] . Many popular phylogeographic approaches [7, 8] can be remiss in ignoring the interaction between evolutionary processes and spatial-temporal domains. One first reconstructs a phylogeny omitting spatial information and then conditions the phylogeo-graphic inferences on this reconstruction [1, 9] , exploiting nonparametric tests to evaluate the significance of this conditional structure, e.g. [7, 10, 11] . To draw conclusions about the epidemic origin or epidemiological linkage between locations, however, we require a reconstruction of the dispersal patterns and process throughout the evolutionary history. Considering locations as discrete states, this boils down to the well-known problem of ancestral state inference [7] . Parsimony is a popular heuristic approach to map characters onto a single phylogenetic tree [12] . Unfortunately, parsimony reconstructions ignore important sources of model uncertainty, including both uncertainty in the dispersal process as well as in the unknown phylogeny [13] . In addition, minimizing the number of state exchanges over a phylogeny is misleading when rates of evolution are rapid and when the state exchange probabilities are unequal [14] .