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Cited by 795

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Testing macro–evolutionary models using incomplete molecular phylogenies

Open access
Pybus, Oliver G., Harvey, Paul H.·2000·Proceedings of the Royal Society of London. Series B: Biological Sciences

Abstract

Phylogenies reconstructed from gene sequences can be used to investigate the tempo and mode of species diversification. Here we develop and use new statistical methods to infer past patterns of speciation and extinction from molecular phylogenies. Specifically, we test the null hypothesis that per-lineage speciation and extinction rates have remained constant through time. Rejection of this hypothesis may provide evidence for evolutionary events such as adaptive radiations or key adaptations. In contrast to previous approaches, our methods are robust to incomplete taxon sampling and are conservative with respect to extinction. Using simulation we investigate, first, the adverse effects of failing to take incomplete sampling into account and, second, the power and reliability of our tests. When applied to published phylogenies our tests suggest that, in some cases, speciation rates have decreased through time.

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Metadata

Authors
Pybus, O. G., & Harvey, P. H.
Venue
Proceedings of the Royal Society of London. Series B: Biological Sciences
Published
2000-11-22
Volume
267
Issue
1459
Pages
2267-2272
ISSN
  • 0080-4649 (ISSN-L)
  • 0962-8452
  • 1471-2954
OpenAlex
W2118610143
Cited by
795
References
3
FWCI
9.01
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Testing macro–evolutionary models using incomplete molecular phylogenies. https://app.cochat.ai/papers/10.1098/rspb.2000.1278
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Pybus, O. G., & Harvey, P. H. (2000). Testing macro–evolutionary models using incomplete molecular phylogenies. Proceedings of the Royal Society of London. Series B: Biological Sciences. https://doi.org/10.1098/rspb.2000.1278

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.