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PyRate requires Python v.3.8 or higher. To install or upgrade Python visit: python.org. To ensure all the dependencies are installed, you can setup a virtual environment as shown here. Older versions of PyRate for Python v.2 are available here (PyRate_for_Python2 directory).

PyRate is licensed under a AGPLv3 License.

The program's documentation is available in PyRate Tutorials

For questions, suggestions or bugs contact us

• Silvestro D., Salamin N., Antonelli A., Meyer X. (2019) Improved estimation of macroevolutionary rates from fossil data using a Bayesian framework. Paleobiology, doi:10.1017/pab.2019.23

• Silvestro D., Schnitzler J., Liow L.H., Antonelli A., Salamin N. (2014) Bayesian Estimation of Speciation and Extinction from Incomplete Fossil Occurrence Data. Systematic Biology, 63, 349-367.

• Silvestro D., Salamin N., Schnitzler J. (2014) PyRate: A new program to estimate speciation and extinction rates from incomplete fossil record. Methods in Ecology and Evolution, 5, 1126-1131.

• See tutorials 1, 2, and 3

• Silvestro D., Antonelli A., Salamin N., Quental T. B. (2015) The role of clade competition in the diversification of North American canids. PNAS, 112, 8684-8689.

• Silvestro D., Pires M. M., Quental T., Salamin N. (2017) Bayesian estimation of multiple clade competition from fossil data. Evolutionary Ecology Research, 18:41-59.

• Lehtonen S., Silvestro D., Karger D. N., Scotese C., Tuomisto H., Kessler M., Peña C., Wahlberg N., Antonelli A. (2017) Environmentally driven extinction and opportunistic origination explain fern diversification patterns. Scientific Reports, 7:4831.

• See tutorial 4

• Silvestro D., Zizka A., Bacon C. D., Cascales-Minana B., Salamin N., Antonelli, A. (2016) Fossil Biogeography: A new model to infer dispersal, extinction and sampling from paleontological data. Philosophical Transactions of the Royal Society B 371:20150225.

• Hauffe T., Pires M.M., Quental T.B., Wilke T., Silvestro, D. (2022) A quantitative framework to infer the effect of traits, diversity and environment on dispersal and extinction rates from fossils. Methods in Ecology and Evolution doi:10.1111/2041-210X.13845

• See tutorial 5

• Silvestro et al. (2019) A 450 million years long latitudinal gradient in age‐dependent extinction. Ecology Letters, doi: 10.1111/ele.13441.

• Hagen O., Andermann T., Quental T. B., Antonelli A., Silvestro D. (2017) Estimating Age-dependent Extinction: Contrasting Evidence from Fossils and Phylogenies. Systematic Biology, doi: 10.1093/sysbio/syx082.

• For the Bayesian implementation see tutorial 4. The ADE-NN model (using neural networks) is available here

• Silvestro D., Warnock R., Gavryushkina A., Stadler T. (2018) Closing the gap between palaeontological and neontological speciation and extinction rate estimates. Nature Communications, doi: 10.1038/s41467-018-07622-y.

• See tutorial 4

• Warnock R., Heath T. A., Stadler T. (2020) Assessing the impact of incomplete species sampling on estimates of speciation and extinction rates. Paleobiology, doi: 10.1017/pab.2020.12.

• Stadler T., Gavryushkina A., Warnock R. C., Drummond A. J., Heath T. A. (2018). The fossilized birth-death model for the analysis of stratigraphic range data under different speciation modes. Journal of Theoretical Biology doi: 10.1016/j.jtbi.2018.03.0.

• Tutorial in prep.

• Pimiento C., Bacon C. D., Silvestro D., Handy A., Jaramillo C., Zizka A., Meyer X., Antonelli A. (2020) Selective extinction against redundant species buffers functional diversity. Proceedings of the Royal Society B doi: 10.1098/rspb.2020.1162.

• Tutorial in prep., example file here.