Modeling the Evolution of Rates of Continuous Trait Evolution

Area of Science:

• Evolutionary biology
• Macroevolutionary dynamics
• Comparative genomics

Background:

• Phenotypic evolution rates vary significantly across taxa, from rapid adaptive radiations to stasis in "living fossils."
• Existing models often assume deterministic or infrequent rate changes, potentially leading to underfitting and misleading conclusions.
• Understanding rate variation is crucial for explaining phenotypic diversity across space, time, and taxa.

Purpose of the Study:

• To develop a novel trait evolution model allowing gradual, stochastic rate variation across clades.
• To extend the model for decreasing or increasing rates over time, accommodating "early/late burst" scenarios.
• To implement an efficient Bayesian method (evorates) for fitting this flexible model to comparative data.

Main Methods:

• Development of a new trait evolution model with gradually and stochastically varying rates.
• Extension to model time-dependent rate changes (decreasing/increasing).
• Implementation of a Bayesian inference framework named "evolving rates" (evorates).

Main Results:

• Simulations confirm evorates reliably infers lineage-specific and time-varying evolutionary rates.
• Application to cetacean body size evolution shows an overall slowdown over time.
• Identified recent bursts in oceanic dolphins and stasis in Mesoplodon beaked whales.

Conclusions:

• The evorates method provides a powerful tool for analyzing complex patterns of phenotypic evolution.
• Demonstrates empirical utility by revealing nuanced body size evolution in cetaceans.
• Offers a more flexible and accurate approach to modeling macroevolutionary rate variation.