RT Journal Article
SR Electronic
T1 Model Adequacy and the Macroevolution of Angiosperm Functional Traits
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 004002
DO 10.1101/004002
A1 Matthew W. Pennell
A1 Richard G. FitzJohn
A1 William K. Cornwell
A1 Luke J. Harmon
YR 2014
UL http://biorxiv.org/content/early/2014/10/31/004002.abstract
AB Making meaningful inferences from phylogenetic comparative data requires a meaningful model of trait evolution. It is thus important to determine whether the model is appropriate for the data and the question being addressed. One way to assess this is to ask whether the model provides a good statistical explanation for the variation in the data. To date, researchers have focused primarily on the explanatory power of a model relative to alternative models. Methods have been developed to assess the adequacy, or absolute explanatory power, of phylogenetic trait models but these have been restricted to specific models or questions. Here we present a general statistical framework for assessing the adequacy of phylogenetic trait models. We use our approach to evaluate the statistical performance of commonly used trait models on 337 comparative datasets covering three key Angiosperm functional traits. In general, the models we tested often provided poor statistical explanations for the evolution of these traits. This was true for many different groups and at many different scales. Whether such statistical inadequacy will qualitatively alter inferences draw from comparative datasets will depend on the context. Regardless, assessing model adequacy can provide interesting biological insights — how and why a model fails to describe variation in a dataset gives us clues about what evolutionary processes may have driven trait evolution across time.