Data from: The million-year wait for macroevolutionary bursts

We lack a comprehensive understanding of evolutionary pattern and process
because short-term and long-term data have rarely been combined into a
single analytical framework. Here we test alternative models of phenotypic
evolution using a dataset of unprecedented size and temporal span (nearly
8,000 data points). The data are body-size measurements taken from
historical studies, the fossil record, and among-species comparative data
representing mammals, squamates, and birds. By analyzing this unusually
large dataset, we identify stochastic models that can explain evolutionary
patterns on both short and long timescales and reveal a remarkably
consistent pattern in the timing of divergence across taxonomic groups.
Even though rapid, short-term evolution often occurs in intervals shorter
than 1 Myr, the changes are constrained and do not accumulate over time.
Over longer intervals (1–360 Myr), this pattern of bounded evolution
yields to a pattern of increasing divergence with time. The bestfitting
model to explain this pattern is a model that combines rare but
substantial bursts of phenotypic change with bounded fluctuations on
shorter timescales. We suggest that these rare bursts reflect permanent
changes in adaptive zones, whereas the short-term fluctuations represent
local variations in niche optima due to restricted environmental variation
within a stable adaptive zone.