Dataset Information

New heuristic methods for joint species delimitation and species tree inference.

ABSTRACT: Species delimitation and species tree inference are difficult problems in cases of recent divergence, especially when different loci have different histories. This paper quantifies the difficulty of jointly finding the division of samples to species and estimating a species tree without constraining the possible assignments a priori. It introduces a parametric and a nonparametric method, including new heuristic search strategies, to do this delimitation and tree inference using individual gene trees as input. The new methods were evaluated using thousands of simulations and 4 empirical data sets. These analyses suggest that the new methods, especially the nonparametric one, may provide useful insights for systematists working at the species level with molecular data. However, they still often return incorrect results.

SUBMITTER: O'Meara BC

PROVIDER: S-EPMC5841455 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

New heuristic methods for joint species delimitation and species tree inference.

O'Meara Brian C BC

Systematic biology 20091110 1

Species delimitation and species tree inference are difficult problems in cases of recent divergence, especially when different loci have different histories. This paper quantifies the difficulty of jointly finding the division of samples to species and estimating a species tree without constraining the possible assignments a priori. It introduces a parametric and a nonparametric method, including new heuristic search strategies, to do this delimitation and tree inference using individual gene t ...[more]

PMID: 20525620

Similar Datasets

Project description:Delimiting and describing species is fundamental to numerous biological disciplines such as evolution, macroecology, and conservation. Delimiting species as independent evolutionary lineages may and often does yield different outcomes depending on the species criteria applied, but methods should be chosen that minimize the inference of objectively erroneous species limits. Several protocols exploit single-gene or multi-gene coalescence statistics, assignment tests or other rationales related to nuclear DNA (nDNA) allele sharing to automatically delimit species. We apply seven different species delimitation protocols to a taxonomically confusing group of Malagasy lizards (Madascincus), and compare the resulting taxonomies with two newly developed metrics: the Taxonomic index of congruence C tax which quantifies the congruence between two taxonomies, and the Relative taxonomic resolving power index R tax which quantifies the potential of an approach to capture a high number of species boundaries. The protocols differed in the total number of species proposed, between 9 and 34, and were also highly incongruent in placing species boundaries. The Generalized Mixed Yule-Coalescent approach captured the highest number of potential species boundaries but many of these were clearly contradicted by extensive nDNA admixture between sympatric mitochondrial DNA (mtDNA) haplotype lineages. Delimiting species as phenotypically diagnosable mtDNA clades failed to detect two cryptic species that are unambiguous due to a lack of nDNA gene flow despite sympatry. We also consider the high number of species boundaries and their placement by multi-gene Bayesian species delimitation as poorly reliable whereas the Bayesian assignment test approach provided a species delimitation highly congruent with integrative taxonomic practice. The present study illustrates the trade-off in taxonomy between reliability (favored by conservative approaches) and resolving power (favored by inflationist approaches). Quantifying excessive splitting is more difficult than quantifying excessive lumping, suggesting a priority for conservative taxonomies in which errors are more liable to be detected and corrected by subsequent studies.

Dataset Information

New heuristic methods for joint species delimitation and species tree inference.

Publications

New heuristic methods for joint species delimitation and species tree inference.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets