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Estimates speciation, extinction, and preservation rates from fossil occurrence data using a Bayesian framework. Pyrate includes several methods to understand how rates vary through time and whether they correlate with traits (e.g. body size) or respond to continuous variables (e.g. climate proxies) or competitive effects (through diversity dependence). Macro evolutionary rates are jointly estimated with preservation rates, describing processes of fossilization, sampling and identification of organisms.

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PyRate classification

PyRate specifications

Software type:
Framework
Restrictions to use:
None
Programming languages:
Python
Stability:
Stable
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
Computer skills:
Advanced
Requirements:
Python, Argparse Numpy, Scipy libraries

Publications

  • (Silvestro et al., 2014) Bayesian estimation of speciation and extinction from incomplete fossil occurrence data. Systematic Biology.
    PMID: 24510972
  • (Silvestro et al., 2014) PyRate: A new program to estimate speciation and extinction rates from incomplete fossil record. Methods in Ecology and Evolution.
    DOI: 10.1111/2041-210X.12263

PyRate support

Documentation

Maintainer

Credits

Institution(s)

Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; Department of Plant and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden; Biodiversity and Climate Research Centre & Senckenberg Research Institute, Frankfurt am Main, Germany; Department of Biological Sciences, Goethe University, Frankfurt am Main, Germany; Centre for Ecological and Evolutionary Synthesis, Department of Biosciences, University of Oslo, Oslo, Norway; Gothenburg Botanical Garden, Gothenburg, Sweden

Funding source(s)

This project was funded from the German Academic Exchange Service, the University of Lausanne, the Wenner-Gren Foundation, the LOEWE program of Hesse’s Ministry of Higher Education Research and the Arts, the Swedish Research Council (B0569601), the European Research Council under the European Unions Seventh Framework Programme (FP/2007-2013, ERC Grant Agreement No. 331024), the grants PDFMP3_134931 and 3100A0_138282 from the Swiss National Science Foundation.

Link to literature

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