title: Delimiting species without monophyletic gene trees.
abstract: Genetic data are frequently used to delimit species, where species status is determined on the basis of an exclusivity criterium, such as reciprocal monophyly. Not only are there numerous empirical examples of incongruence between the boundaries inferred from such data compared to other sources like morphology -- especially with recently derived species, but population genetic theory also clearly shows that an inevitable bias in species status results because genetic thresholds do not explicitly take into account how the timing of speciation influences patterns of genetic differentiation. This study represents a fundamental shift in how genetic data might be used to delimit species. Rather than equating gene trees with a species tree or basing species status on some genetic threshold, the relationship between the gene trees and the species history is modeled probabilistically. Here we show that the same theory that is used to calculate the probability of reciprocal monophyly can also be used to delimit species despite widespread incomplete lineage sorting. The results from a preliminary simulation study suggest that very recently derived species can be accurately identified long before the requisite time for reciprocal monophyly to be achieved following speciation. The study also indicates the importance of sampling, both with regards to loci and individuals. Withstanding a thorough investigation into the conditions under which the coalescent-based approach will be effective, namely how the timing of divergence relative to the effective population size of species affects accurate species delimitation, the results are nevertheless consistent with other recent studies (aimed at inferring species relationships), showing that despite the lack of monophyletic gene trees, a signal of species divergence persists and can be extracted. Using an explicit model-based approach also avoids two primary problems with species delimitation that result when genetic thresholds are applied with genetic data -- the inherent biases in species detection arising from when and how speciation occurred, and failure to take into account the high stochastic variance of genetic processes. Both the utility and sensitivities of the coalescent-based approach outlined here are discussed; most notably, a model-based approach is essential for determining whether incompletely sorted gene lineages are (or are not) consistent with separate species lineages, and such inferences require accurate model parameterization (i.e., a range of realistic effective population sizes relative to potential times of divergence for the purported species). It is the goal (and motivation of this study) that genetic data might be used effectively as a source of complementation to other sources of data for diagnosing species, as opposed to the exclusion of other evidence for species delimitation, which will require an explicit consideration of the effects of the temporal dynamic of lineage splitting on genetic data.
authors.affiliation: Department of Ecology and Evolutionary Biology, Museum of Zoology, University of Michigan, Ann Arbor, MI 48109-1079, USA. knowlesl@umich.edu
authors.forename: L Lacey
authors.initials: LL
authors.lastname: Knowles
authors.forename: Bryan C
authors.initials: BC
authors.lastname: Carstens
mesh_terms: D000818:Animals; D002965:Classification / Q000379:methods*; D049810:Genetic Speciation; D005828:Genetics, Population; D008954:Models, Biological; D010802:Phylogeny