ArticleEvolutionary bioinformatics online2016
Notes on the Statistical Power of the Binary State Speciation and Extinction (BiSSE) Model.
Article in Evolutionary bioinformatics online, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 1 of them a synthesis that pooled it.
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11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Speciation through chromosomal fusion and fission in Lepidoptera.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020Pooled it
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- Macroevolutionary Analyses Suggest That Environmental Factors, Not Venom Apparatus, Play Key Role in Terebridae Marine Snail Diversification.Systematic biology · 2020Article
- Geo-Climatic Changes and Apomixis as Major Drivers of Diversification in the Mediterranean Sea Lavenders (Frontiers in plant science · 2020Article
- Evolutionary diversification of the African achyranthoid clade (Amaranthaceae) in the context of sterile flower evolution and epizoochory.Annals of botany · 2018Article
- Repeated evolution and reversibility of self-fertilization in the volvocine green algae.Evolution; international journal of organic evolution · 2018Article
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- Phylogenetic evidence from freshwater crayfishes that cave adaptation is not an evolutionary dead-end.Evolution; international journal of organic evolution · 2017Article
- Disentangling geographical, biotic, and abiotic drivers of plant diversity in neotropical Ruellia (Acanthaceae).PloS one · 2017Article
Corrections and comments
- Erratum issued
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1 author.
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No grant is acknowledged in the PubMed record.
Abstract
The Binary State Speciation and Extinction (BiSSE) method is one of the most popular tools for investigating the rates of diversification and character evolution. Yet, based on previous simulation studies, it is commonly held that the BiSSE method requires phylogenetic trees of fairly large sample sizes (>300 taxa) in order to distinguish between the different models of speciation, extinction, or transition rate asymmetry. Here, the power of the BiSSE method is reevaluated by simulating trees of both small and large sample sizes (30, 60, 90, and 300 taxa) under various asymmetry models and root state assumptions. Results show that the power of the BiSSE method can be much higher, also in trees of small sample size, for detecting differences in speciation rate asymmetry than anticipated earlier. This, however, is not a consequence of any conceptual or mathematical flaw in the method per se but rather of assumptions about the character state at the root of the simulated trees and thus the underlying macroevolutionary model, which led to biased results and conclusions in earlier power assessments. As such, these earlier simulation studies used to determine the power of BiSSE were not incorrect but biased, leading to an overestimation of type-II statistical error for detecting differences in speciation rate but not for extinction and transition rates.
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