New Heuristic Methods for Joint Species Delimitation and Species Tree Inference

被引:209
作者
O'Meara, Brian C. [1 ]
机构
[1] Univ Tennessee, Dept Ecol & Evolutionary Biol, Knoxville, TN 37996 USA
基金
美国国家科学基金会;
关键词
Brownie; gene tree parsimony; gene tree species tree; speciation; species delimitation; MAXIMUM-LIKELIHOOD-ESTIMATION; ANCESTRAL POPULATION SIZES; GENE TREES; DNA-SEQUENCES; DROSOPHILA-PSEUDOOBSCURA; PHYLOGENETIC INFERENCE; GENEALOGICAL APPROACH; DIVERGENCE TIMES; BAYES ESTIMATION; MODEL;
D O I
10.1093/sysbio/syp077
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页码:59 / 73
页数:15
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