Species tree discordance traces to phylogeographic clade boundaries in North American fence lizards (Sceloporus).

I investigated the impacts of phylogeographic sampling decisions on species tree estimation in the Sceloporus undulatus species group, a recent radiation of small, insectivorous lizards connected by parapatric and peripatric distribution across North America, using a variety of species tree inference methods (Bayesian estimation of species trees, Bayesian untangling of concordance knots, and minimize deep coalescences). Phylogenetic analyses of 16 specimens representing 4 putative species within S. "undulatus" using complete (8 loci, >5.5 kb) and incomplete (29 loci, >23.6 kb) nuclear data sets result in species trees that share features with the mitochondrial DNA (mtDNA) genealogy at the phylogeographic level but provide new insights into the evolutionary history of the species group. The concatenated nuclear data and mtDNA data both recover 4 major clades connecting populations across North America; however, instances of discordance are localized at the contact zones between adjacent phylogeographic groups. A random sub-sampling experiment designed to vary the phylogeographic samples included across hundreds of replicate species tree inferences suggests that inaccurate species assignments can result in inferred phylogenetic relationships that are dependent upon which particular populations are used as exemplars to represent species and can lead to increased estimates of effective population size. For the phylogeographic data presented here, reassigning specimens with introgressed mtDNA genomes to their prospective species, or excluding them from the analysis altogether, produces species tree topologies that are distinctly different from analyses that utilize mtDNA-based species assignments. Evolutionary biologists working at the interface of phylogeography and phylogenetics are likely to encounter multiple processes influencing gene trees congruence, which increases the relevance of estimating species trees with multilocus nuclear data and models that accommodate deep coalescence.