Predictors of phylogeographic structure among codistributed taxa across the complex Australian monsoonal tropics

The Phylogenomic and Biogeographic History of the Gartersnakes, Watersnakes, and Allies (Natricidae: Thamnophiini)

North American Thamnophiini (gartersnakes, watersnakes, brownsnakes, and swampsnakes) are an ecologically and phenotypically diverse temperate clade of snakes representing 61 species across 10 genera. In this study, we estimate phylogenetic trees using ∼3,700 ultraconserved elements (UCEs) for 76 specimens representing 75% of all Thamnophiini species. We infer phylogenies using multispecies coalescent methods and time calibrate them using the fossil record. We also conducted ancestral area estimation to identify how major biogeographic boundaries in North America affect broadscale diversification in the group. While most nodes exhibited strong statistical support, analysis of concordant data across gene trees reveals substantial heterogeneity. Ancestral area estimation demonstrated that the genus Thamnophis was the only taxon in this subfamily to cross the Western Continental Divide, even as other taxa dispersed southward toward the tropics. Additionally, levels of gene tree discordance are overall higher in transition zones between bioregions, including the Rocky Mountains. Therefore, the Western Continental Divide may be a significant transition zone structuring the diversification of Thamnophiini during the Neogene and Pleistocene. Here we show that despite high levels of discordance across gene trees, we were able to infer a highly resolved and well-supported phylogeny for Thamnophiini, which allows us to understand broadscale patterns of diversity and biogeography.

Initiation of speciation across multiple dimensions in a rock-restricted, tropical lizard

Population isolation and concomitant genetic divergence, resulting in strong phylogeographical structure, is a core aspect of speciation initiation. If and how speciation then proceeds and ultimately completes depends on multiple factors that mediate reproductive isolation, including divergence in genomes, ecology and mating traits. Here we explored these multiple dimensions in two young (Plio-Pleistocene) species complexes of gekkonid lizards (Heteronotia) from the Kimberley-Victoria River regions of tropical Australia. Using mitochondrial DNA screening and exon capture phylogenomics, we show that the rock-restricted Heteronotia planiceps exhibits exceptional fine-scale phylogeographical structure compared to the codistributed habitat generalist Heteronotia binoei. This indicates pervasive population isolation and persistence in the rock-specialist, and thus a high rate of speciation initiation across this geographically complex region, with levels of genomic divergence spanning the "grey zone" of speciation. Proximal lineages of H. planiceps were often separated by different rock substrates, suggesting a potential role for ecological isolation; however, phylogenetic incongruence and historical introgression were inferred between one such pair. Ecomorphological divergence among lineages within both H. planiceps and H. binoei was limited, except that limestone-restricted lineages of H. planiceps tended to be larger than rock-generalists. By contrast, among-lineage divergence in the chemical composition of epidermal pore secretions (putative mating trait) exceeded ecomorphology in both complexes, but with less trait overlap among lineages in H. planiceps. This system-particularly the rock-specialist H. planiceps-highlights the role of multidimensional divergence during incipient speciation, with divergence in genomes, ecomorphology and chemical signals all at play at very fine spatial scales.

Using natural history to guide supervised machine learning for cryptic species delimitation with genetic data

The diversity of biological and ecological characteristics of organisms, and the underlying genetic patterns and processes of speciation, makes the development of universally applicable genetic species delimitation methods challenging. Many approaches, like those incorporating the multispecies coalescent, sometimes delimit populations and overestimate species numbers. This issue is exacerbated in taxa with inherently high population structure due to low dispersal ability, and in cryptic species resulting from nonecological speciation. These taxa present a conundrum when delimiting species: analyses rely heavily, if not entirely, on genetic data which over split species, while other lines of evidence lump. We showcase this conundrum in the harvester Theromaster brunneus, a low dispersal taxon with a wide geographic distribution and high potential for cryptic species. Integrating morphology, mitochondrial, and sub-genomic (double-digest RADSeq and ultraconserved elements) data, we find high discordance across analyses and data types in the number of inferred species, with further evidence that multispecies coalescent approaches over split. We demonstrate the power of a supervised machine learning approach in effectively delimiting cryptic species by creating a "custom" training data set derived from a well-studied lineage with similar biological characteristics as Theromaster. This novel approach uses known taxa with particular biological characteristics to inform unknown taxa with similar characteristics, using modern computational tools ideally suited for species delimitation. The approach also considers the natural history of organisms to make more biologically informed species delimitation decisions, and in principle is broadly applicable for taxa across the tree of life.