The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Automatic Detection of Key Innovations, Rate Shifts, and Diversity-Dependence on Phylogenetic Trees
Open accessAbstract
A number of methods have been developed to infer differential rates of species diversification through time and among clades using time-calibrated phylogenetic trees. However, we lack a general framework that can delineate and quantify heterogeneous mixtures of dynamic processes within single phylogenies. I developed a method that can identify arbitrary numbers of time-varying diversification processes on phylogenies without specifying their locations in advance. The method uses reversible-jump Markov Chain Monte Carlo to move between model subspaces that vary in the number of distinct diversification regimes. The model assumes that changes in evolutionary regimes occur across the branches of phylogenetic trees under a compound Poisson process and explicitly accounts for rate variation through time and among lineages. Using simulated datasets, I demonstrate that the method can be used to quantify complex mixtures of time-dependent, diversity-dependent, and constant-rate diversification processes. I compared the performance of the method to the MEDUSA model of rate variation among lineages. As an empirical example, I analyzed the history of speciation and extinction during the radiation of modern whales. The method described here will greatly facilitate the exploration of macroevolutionary dynamics across large phylogenetic trees, which may have been shaped by heterogeneous mixtures of distinct evolutionary processes.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Equation of State Calculations by Fast Computing Machines
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., & Teller, E. (1953) · The Journal of Chemical Physics · doi:10.1063/1.1699114 · Cited by 37,192
Monte Carlo sampling methods using Markov chains and their applications.
Hastings, W. K. (1970) · Biometrika · doi:10.1093/biomet/57.1.97 · Cited by 15,195
The global diversity of birds in space and time
Jetz, W., Thomas, G. H., Joy, J. B., Hartmann, K., & Mooers, A. O. (2012) · Nature · doi:10.1038/nature11631 · Cited by 3,934
The delayed rise of present-day mammals
Bininda-Emonds, O. R. P., Cardillo, M., Jones, K. E., MacPhee, R. D. E., Beck, R. M. D., Grenyer, R., Price, S. A., Vos, R. A., Gittleman, J. L., & Purvis, A. (2007) · Nature · doi:10.1038/nature05634 · Cited by 2,082
Diversity versus disparity and the radiation of modern cetaceans
Slater, G. J., Price, S. A., Santini, F., & Alfaro, M. E. (2010) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2010.0408 · Cited by 312
Eastman, J. M., Alfaro, M. E., Joyce, P., Hipp, A. L., & Harmon, L. J. (2011) · Evolution · doi:10.1111/j.1558-5646.2011.01401.x · Cited by 240
Inferring speciation and extinction rates under different sampling schemes
Hohna, S., Stadler, T., Ronquist, F., & Britton, T. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr095 · Cited by 160
Etienne, R. S., & Haegeman, B. (2012) · The American Naturalist · doi:10.1086/667574 · Cited by 138
Cited by
Phytools 2.0: an updated R ecosystem for phylogenetic comparative methods (and other things)
Revell, L. J. (2024) · PeerJ · doi:10.7717/peerj.16505 · Cited by 1,244
Upham, N. S., Esselstyn, J. A., & Jetz, W. (2019) · PLOS Biology · doi:10.1371/journal.pbio.3000494 · Cited by 1,201
An inverse latitudinal gradient in speciation rate for marine fishes
Rabosky, D. L., Chang, J., Title, P. O., Cowman, P. F., Sallan, L., Friedman, M., Kaschner, K., Garilao, C., Near, T. J., Coll, M., et al. (2018) · Nature · doi:10.1038/s41586-018-0273-1 · Cited by 933
Self-citationDetecting hidden diversification shifts in models of trait-dependent speciation and extinction
Beaulieu, J. M., & O’Meara, B. C. (2016) · Systematic Biology · doi:10.1093/sysbio/syw022 · Cited by 579
Phylogenomics and the rise of the angiosperms
Zuntini, A. R., Carruthers, T., Maurin, O., Bailey, P. C., Leempoel, K., Brewer, G. E., Epitawalage, N., Françoso, E., Gallego-Paramo, B., McGinnie, C., et al. (2024) · Nature · doi:10.1038/s41586-024-07324-0 · Cited by 429
Metadata
- Authors
- Rabosky, D. L.
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2014-02-26
- Volume
- 9
- Issue
- 2
- Pages
- e89543
- ISSN
- 1932-6203 (ISSN-L)
- OpenAlex
- W2042449834
- Cited by
- 1,090
- References
- 8
- FWCI
- 74.40
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Automatic Detection of Key Innovations, Rate Shifts, and Diversity-Dependence on Phylogenetic Trees. https://app.cochat.ai/papers/10.1371/journal.pone.0089543
- The paper
- Rabosky, D. L. (2014). Automatic Detection of Key Innovations, Rate Shifts, and Diversity-Dependence on Phylogenetic Trees. PLoS ONE. https://doi.org/10.1371/journal.pone.0089543
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.
