Data from: A test for rate-coupling of trophic and cranial evolutionary dynamics in New World bats
Shi, Jeff; Westeen, Erin; Rabosky, Daniel (2021), Data from: A test for rate-coupling of trophic and cranial evolutionary dynamics in New World bats, Dryad, Dataset, https://doi.org/10.5061/dryad.ghx3ffbn3
Data supporting article Shi et al. 2021, Evolution: https://doi.org/10.1111/evo.14188
Morphological evolution is often assumed to be causally related to underlying patterns of ecological trait evolution. However, few studies have directly tested whether evolutionary dynamics of and major shifts in ecological resource use are coupled with morphological shifts that may facilitate trophic innovation. Using diet and multivariate cranial (microCT) data, we tested whether rates of trophic and cranial evolution are coupled in the radiation of New World bats. We developed a generalizable information-theoretic method for describing evolutionary rate heterogeneity across large candidate sets of multi-rate models of evolution, without relying on a single best-fitting model. We found considerable variation in trophic evolutionary dynamics, in sharp contrast to a largely homogeneous cranial evolutionary process. This dichotomy is surprising given documented functional associations between overall skull morphology and trophic ecology. We suggest that assigning discrete trophic states may underestimate trophic generalism, and that this radiation could be characterized by generally labile crania that result in a homogeneous dynamic of overall high morphological rates. Overall, we discuss how trophic classification could substantively impact our interpretation of how these dynamics covary in adaptive radiations.
These shape data were collected from specimens archived in a repository described by these authors (Shi et al. 2018, PLOS ONE). They were processed using the program Stratovan Checkpoint (Stratovan, Davis, USA). All subsequent analyses were performed in R using a combination of packages described in the published paper.
Please read the README.txt for notes on each subdirectory and the analyses contained within.
National Science Foundation, Award: DEB 1501304