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Data from: Comparing the rates of speciation and extinction between phylogenetic trees

Citation

Revell, Liam J. (2019), Data from: Comparing the rates of speciation and extinction between phylogenetic trees, Dryad, Dataset, https://doi.org/10.5061/dryad.f8c9165

Abstract

Over the past decade or so it has become increasingly popular to use reconstructed evolutionary trees to investigate questions about the rates of speciation and extinction. Although the methodology of this field has grown substantially in its sophistication in recent years, here I’ll take a step back to present a very simple model that is designed to investigate the relatively straightforward question of whether the tempo of diversification (speciation and extinction) differs between two or more phylogenetic trees, without attempting to attribute a causal basis to this difference. It is a likelihood method, and I demonstrate that it generally shows type I error that is close to the nominal level. I also demonstrate that parameter estimates obtained with this approach are largely unbiased. Since this method can be used to compare trees of unknown relationship, it will be particularly well-suited to problems in which a difference in diversification rate between clades is suspected, but in which these clades are not particularly closely related. Since diversification methods can easily take into account an incomplete sampling fraction, but missing lineages are assumed to be missing at random, this method is also appropriate for cases in which we’ve hypothesized a difference in the process of diversification between two or more focal clades, but in which many un-sampled groups separate the few of interest. The method of this study is by no means an attempt to replace more sophisticated models in which, for instance, diversification depends on the state of an observed or unobserved discrete or continuous trait. Rather, my intention is to provide a complementary approach for circumstances in which a simpler hypothesis is warranted and of biological interest.

Usage Notes

Funding

National Science Foundation, Award: DEB-1350474