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

Cite this dataset

Castiglione, Silvia et al. (2017). Data from: A new method for testing evolutionary rate variation and shifts in phenotypic evolution [Dataset]. Dryad.


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.

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