Evolutionary Sample Size and Consilience in Phylogenetic Comparative Analysis.

Area of Science:

• Evolutionary biology
• Comparative genomics

Background:

• Phylogenetic comparative methods (PCMs) are vital for studying evolution and adaptation.
• Common PCMs for discrete traits often misinterpret single evolutionary transitions as correlated evolution.

Purpose of the Study:

• To identify limitations in current PCMs for discrete traits, particularly concerning single evolutionary transitions.
• To propose solutions for accurately assessing correlated evolution in phylogenetic studies.

Main Methods:

• Simulations were used to evaluate the performance of PCMs, specifically Pagel's Discrete model, under scenarios with small evolutionary sample sizes.
• Analysis focused on rate parameter estimation and model selection biases.
• Introduced the phylogenetic imbalance ratio for assessing discrete trait models.

Main Results:

• Pagel's Discrete model frequently detects spurious correlated evolution when traits evolve only once.
• Poor rate parameter estimation occurs due to small effective evolutionary sample sizes.
• Models with continuous data distributions are less prone to bias but still affected by small sample sizes.

Conclusions:

• Researchers should design studies to maximize evolutionary sample sizes and test a priori hypotheses.
• Assessing model suitability using metrics like the phylogenetic imbalance ratio is crucial.
• A consilience of evidence from multiple fields (e.g., biogeography, developmental biology) strengthens evolutionary hypotheses.