Data from: A new method for testing evolutionary rate variation and shifts in phenotypic evolution

1.Quantifying phenotypic evolutionary rates and their variation across
phylogenetic trees is a major issue in evolutionary biology. A number of
phylogenetic comparative methods (PCMs) currently perform such task.
However, available PCMs can locate rate shifts pertaining to entire
portions of the phylogeny, but not those expected to occur at the level of
individual species and lineages, such as with the idea that body size
changes more rapidly in insular vertebrates. Still, most PCMs cannot deal
with fossil phylogenies, albeit fossils provide highly desirable
information when it comes to understand trait variation and evolution.
2.We developed a PCM based on phylogenetic ridge regression, which we
named RRphylo, which assigns an evolutionary rate to each branch of the
phylogeny, and is designed to locate rate shifts relating to entire
clades, as well as to unrelated tree tips. We tested RRphylo on simulated
trees and data to assess its performance under different conditions. Then,
we repeated its application with two real case scenarios, the evolution of
flight in ornithodirans and mammals, and body size evolution in insular
mammals, which are usually subsumed to evolve under different range
regimes than terrestrial and continental species, respectively. 3.RRphylo
performs well across all different conditions. The simulation experiments
demonstrated it has low Type I and Type II error rate. We found
significant evidence that flight accelerates the rate of body size
evolution in vertebrates, and that the acquisition of very large body size
slows down the rate. Still, insular mammals body size evolution is not
faster than in continental species. 4.RRphylo is a new PCM ideal to
estimate variation and shift in the rate of phenotypic evolution with
fossil data. In addition to testing evolutionary rate variation, it is
open to a variety of further questions, such as the evolution of rates in
time, the estimation of ancestral states, and the estimation of phenotypic
trends over time.