Computational molecular species delimitation and taxonomic revision of the gecko genus Ebenavia Boettger, 1878

The taxonomic challenge posed by cryptic species (two or more distinct species classified as a single species) has been recognized for nearly 300 years, but the advent of relatively inexpensive and rapid DNA sequencing has given biologists a new tool for detecting and differentiating morphologically similar species. Here, we synthesize the literature on cryptic and sibling species and discuss trends in their discovery. However, a lack of systematic studies leaves many questions open, such as whether cryptic species are more common in particular habitats, latitudes or taxonomic groups. The discovery of cryptic species is likely to be non-random with regard to taxon and biome and, hence, could have profound implications for evolutionary theory, biogeography and conservation planning.

Background Taxonomy is the biological discipline that identifies, describes, classifies and names extant and extinct species and other taxa. Nowadays, species taxonomy is confronted with the challenge to fully incorporate new theory, methods and data from disciplines that study the origin, limits and evolution of species. Results Integrative taxonomy has been proposed as a framework to bring together these conceptual and methodological developments. Here we review perspectives for an integrative taxonomy that directly bear on what species are, how they can be discovered, and how much diversity is on Earth. Conclusions We conclude that taxonomy needs to be pluralistic to improve species discovery and description, and to develop novel protocols to produce the much-needed inventory of life in a reasonable time. To cope with the large number of candidate species revealed by molecular studies of eukaryotes, we propose a classification scheme for those units that will facilitate the subsequent assembly of data sets for the formal description of new species under the Linnaean system, and will ultimately integrate the activities of taxonomists and molecular biologists.

In the absence of recent admixture between species, bipartitions of individuals in gene trees that are shared across loci can potentially be used to infer the presence of two or more species. This approach to species delimitation via molecular sequence data has been constrained by the fact that genealogies for individual loci are often poorly resolved and that ancestral lineage sorting, hybridization, and other population genetic processes can lead to discordant gene trees. Here we use a Bayesian modeling approach to generate the posterior probabilities of species assignments taking account of uncertainties due to unknown gene trees and the ancestral coalescent process. For tractability, we rely on a user-specified guide tree to avoid integrating over all possible species delimitations. The statistical performance of the method is examined using simulations, and the method is illustrated by analyzing sequence data from rotifers, fence lizards, and human populations.