What affects power to estimate speciation rate shifts?

Area of Science:

• Evolutionary Biology
• Phylogenetics
• Diversification Analysis

Background:

• Estimating speciation and extinction rates from phylogenies aids in understanding diversification drivers.
• Researchers frequently test trait evolution's impact on speciation rates using methods like BiSSE, MEDUSA, and BAMM.
• Evaluating the performance of these diversification modeling methods is crucial for reliable evolutionary inference.

Purpose of the Study:

• To assess the power of BiSSE, MEDUSA, and BAMM in detecting single speciation rate shifts.
• To investigate how factors like rate asymmetry, lineage size, and tip-ratio bias affect shift detection.
• To provide practical recommendations for users of these diversification modeling techniques.

Main Methods:

• Simulated time-calibrated phylogenies, each with a single speciation rate shift.
• Varied parameters including speciation rate asymmetry, number of tips, tip-ratio bias, and timing of the rate shift.
• Compared the power of BiSSE, MEDUSA, and BAMM to detect these simulated shifts.

Main Results:

• All three methods demonstrated good power to detect rate shifts when speciation rate asymmetry was high and lineage sizes were large.
• High rate asymmetry maintained good detection power even with smaller lineage sizes.
• BAMM performance was most affected by small lineage sizes, while tip-ratio bias impacted rate estimation accuracy more than detection power.

Conclusions:

• BiSSE, MEDUSA, and BAMM are generally effective for detecting speciation rate shifts, particularly under strong asymmetry and large lineages.
• Users should be mindful of lineage size, especially when employing BAMM.
• The study offers guidance for optimizing the application of these diversification modeling tools in evolutionary research.