Integrating Genomics, Collections, and Community Science to Delimit Species Clarifies the Taxonomy of a Variable Monitor Lizard (Varanus tristis).

Abstract

The accurate characterization of species diversity is a vital prerequisite for ecological and evolutionary research, as well as conservation. Thus, it is necessary to generate robust hypotheses of species limits based on the inference of evolutionary processes. Integrative species delimitation, the inference of species limits based on multiple sources of evidence, can provide unique insight into species diversity and the processes behind it. Here, we show how community observations can be integrated with standard molecular and phenotypic datasets under an integrative framework to identify the processes generating genetic and phenotypic variation. We implement this approach in Varanus tristis, a widespread and variable complex of Australian monitor lizards. Using genomic, phenotypic (linear and geometric morphometrics, coloration), spatial, and environmental data, we show that disparity in this complex is inconsistent with intraspecific variation and instead suggests that speciation has occurred. Based on our results, we provide an updated taxonomy for this complex and identify the processes that may have been responsible for the geographic sorting of variation. Our workflow provides a guideline for the integrative analysis of several types of data to identify the occurrence and causes of speciation. Furthermore, our study highlights the benefits and caveats associated with community science and machine learning-two tools used here-in taxonomic research.