| Abstract: | With the continued adoption of genome‐scale data in evolutionary biology comes the challenge of adequately harnessing the information to make accurate phylogenetic inferences. Coalescent‐based methods of species tree inference have become common, and concatenation has been shown in simulation to perform well, particularly when levels of incomplete lineage sorting are low. However, simulation conditions are often overly simplistic, leaving empiricists with uncertainty regarding analytical tools. We use a large ultraconserved element data set (>3,000 loci) from rattlesnakes of the Crotalus triseriatus group to delimit lineages and estimate species trees using concatenation and several coalescent‐based methods. Unpartitioned and partitioned maximum likelihood and Bayesian analysis of the concatenated matrix yield a topology identical to coalescent analysis of a subset of the data in bpp . ASTRAL analysis on a subset of the more variable loci also results in a tree consistent with concatenation and bpp , whereas the SVDquartets phylogeny differs at additional nodes. The size of the concatenated matrix has a strong effect on species tree inference using SVDquartets , warranting additional investigation on optimal data characteristics for this method. Species delimitation analyses suggest up to 16 unique lineages may be present within the C. triseriatus group, with divergences occurring during the Neogene and Quaternary. Network analyses suggest hybridization within the group is relatively rare. Altogether, our results reaffirm the Mexican highlands as a biodiversity hotspot and suggest that coalescent‐based species tree inference on data subsets can provide a strongly supported species tree consistent with concatenation of all loci with a large amount of missing data. |
