A simple hierarchical model for heterogeneity in the evolutionary correlation on a phylogenetic tree

Area of Science:

• Phylogenetic comparative biology
• Evolutionary biology
• Quantitative genetics

Background:

• Understanding correlated trait evolution is crucial in phylogenetic comparative biology.
• Evolutionary correlations between traits can be constant or vary across different parts of a phylogeny.

Purpose of the Study:

• To develop and present a method for fitting hierarchical models of heterogeneous evolutionary rates and correlations for two quantitative traits on a phylogeny.
• To assess the performance of the proposed method in parameter estimation and model selection.

Main Methods:

• Developed a hierarchical modeling framework to analyze trait evolution.
• Applied the method to empirical datasets (sunfish buccal morphology, lizard body dimensions).
• Utilized numerical simulations to evaluate parameter estimation and model selection accuracy.

Main Results:

• The method allows for fitting models where evolutionary rates and correlations vary across phylogenetic clades and branches.
• Demonstrated application to real-world datasets, providing insights into trait evolution in sunfishes and lizards.
• Simulations confirmed the method's utility for parameter estimation and model selection.

Conclusions:

• The presented method offers a flexible approach to model heterogeneity in trait evolutionary rates and correlations.
• This framework enhances the analysis of complex evolutionary patterns in phylogenetic comparative studies.
• The study provides a valuable tool for investigating how trait relationships evolve over time.