Data from: The impact of rate heterogeneity on inference of phylogenetic models of trait evolution

Rates of trait evolution are known to vary across phylogenies; however,
standard evolutionary models assume a homogeneous process of trait change.
These simple methods are widely applied in small-scale phylogenetic
studies, whereas models of rate heterogeneity are not, so the prevalence
and patterns of potential rate variation in groups up to hundreds of
species remain unclear. The extent to which trait evolution is modelled
accurately on a given phylogeny is also largely unknown because studies
typically lack absolute model fit tests. We investigated these issues by
applying both rate-static and variable-rates methods on (i) body mass data
for 88 avian clades of 10–318 species, and (ii) data simulated under a
range of rate-heterogeneity scenarios. Our results show that rate
heterogeneity is present across small-scaled avian clades, and
consequently applying only standard single-process models prompts
inaccurate inferences about the generating evolutionary process.
Specifically, these approaches underestimate rate variation, and
systematically mislabel temporal trends in trait evolution. Conversely,
variable-rates approaches have superior relative fit (they are the best
model) and absolute fit (they describe the data well). We show that rate
changes such as single internal branch variations, rate decreases and
early bursts are hard to detect, even by variable-rates models. We also
use recently developed absolute adequacy tests to highlight misleading
conclusions based on relative fit alone (e.g. a consistent preference for
constrained evolution when isolated terminal branch rate increases are
present). This work highlights the potential for robust inferences about
trait evolution when fitting flexible models in conjunction with tests for
absolute model fit.