The million-year wait for macroevolutionary bursts.

Area of Science:

• Evolutionary biology
• Paleontology
• Comparative genomics

Background:

• Understanding evolutionary patterns requires integrating short-term and long-term data, which is rarely done.
• Phenotypic evolution models often focus on single timescales, limiting comprehensive analysis.

Purpose of the Study:

• To test alternative models of phenotypic evolution using a large, multi-timescale dataset.
• To identify evolutionary processes that explain patterns across both short and long geological timescales.

Main Methods:

• Analysis of a large dataset (>8,000 data points) including historical studies, fossil records, and comparative data.
• Body-size measurements from mammals, squamates, and birds were used to model evolutionary patterns.
• Testing of stochastic models to explain phenotypic evolution across different time scales.

Main Results:

• A consistent pattern of divergence timing was observed across taxonomic groups.
• Short-term evolution (<1 Myr) is rapid but constrained, not accumulating over time.
• Long-term evolution (1-360 Myr) shows increasing divergence with time, best explained by rare bursts of change and shorter-term bounded fluctuations.

Conclusions:

• A combined model of rare adaptive zone shifts and bounded fluctuations best explains evolutionary patterns.
• Rare bursts likely represent permanent adaptive zone changes, while short-term fluctuations indicate niche optima variations.
• This integrated framework advances our understanding of evolutionary pattern and process across diverse timescales.