Data from: Modeling the evolution of rates of continuous trait evolution

Rates of phenotypic evolution vary markedly across the tree of life, from
the accelerated evolution apparent in adaptive radiations to the
remarkable evolutionary stasis exhibited by so-called “living fossils”.
Such rate variation has important consequences for large-scale
evolutionary dynamics, generating vast disparities in phenotypic diversity
across space, time, and taxa. Despite this, most methods for estimating
trait evolution rates assume rates vary deterministically with respect to
some variable of interest or change infrequently during a clade’s history.
These assumptions may cause underfitting of trait evolution models and
mislead hypothesis testing. Here, we develop a new trait evolution model
that allows rates to vary gradually and stochastically across a clade.
Further, we extend this model to accommodate generally decreasing or
increasing rates over time, allowing for flexible modeling of “early/late
bursts” of trait evolution. We implement a Bayesian method, termed
“evolving rates” (evorates for short), to efficiently fit this model to
comparative data. Through simulation, we demonstrate that evorates can
reliably infer both how and in which lineages trait evolution rates varied
during a clade’s history. We apply this method to body size evolution in
cetaceans, recovering substantial support for an overall slowdown in body
size evolution over time with recent bursts among some oceanic dolphins
and relative stasis among beaked whales of the genus Mesoplodon. These
results unify and expand on previous research, demonstrating the empirical
utility of evorates.