Inferring Diversification Rate Variation From Phylogenies With Fossils

Area of Science:

• Evolutionary Biology
• Paleontology
• Computational Biology

Background:

• Time-calibrated phylogenies of extant species are common for studying diversification.
• However, extinction rate inferences can be unreliable without fossil data.
• The fossilized birth-death process offers a framework for integrating fossil data.

Purpose of the Study:

• To introduce a general framework for studying speciation-extinction dynamics using phylogenies of extant and extinct species.
• To implement this model in BAMM (Bayesian Analysis of Macroevolutionary Mixtures).
• To assess the impact of fossil data on diversification rate estimation.

Main Methods:

• Developed a general framework based on the fossilized birth-death process.
• Modeled phylogenies as mixtures of rate regimes governed by a hierarchical Poisson process.
• Implemented the model in BAMM using reversible jump Markov chain Monte Carlo.

Main Results:

• Speciation rates are reliably inferred even without paleontological data.
• Including fossil observations significantly enhances the accuracy of extinction rate estimates.
• The model shows robustness to violations in preservation rates and fossil occurrence data.

Conclusions:

• Integrating fossil data is crucial for accurate estimation of extinction rates in macroevolutionary studies.
• The BAMM implementation provides a robust tool for analyzing phylogenies with both extant and extinct taxa.
• This framework advances our understanding of speciation-extinction dynamics across evolutionary history.