All models are wrong.

As the field of phylogeography has continued to move in the model-based direction, researchers continue struggling to construct useful models for inference. These models must be both simple enough to be tractable yet contain enough of the complexity of the natural world to make meaningful inference. Beyond constructing such models for inference, researchers explore model space and test competing models with the data on hand, with the goal of improving the understanding of the natural world and the processes underlying natural biological communities. Approximate Bayesian computation (ABC) has increased in recent popularity as a tool for evaluating alternative historical demographic models given population genetic samples. As a thorough demonstration, Pelletier & Carstens (2014) use ABC to test 143 phylogeographic submodels given geographically widespread genetic samples from the salamander species Plethodon idahoensis (Carstens et al. 2014) and, in so doing, demonstrate how the results of the ABC model choice procedure are dependent on the model set one chooses to evaluate.