Data from: Assessing among-lineage variability in phylogenetic imputation of functional trait datasets

We found that under a Brownian motion model of evolution (BM, Pagel s λ = 1), tip-level accuracy rapidly decreased with increasing tip branch-lengths, and only tips of approximately 10% or less of the total height of the trees showed consistently accurate predictions (i.e. cross-validation R-squared > 0.75). When phylogenetic signal was weak, the effect of tip branch-length was reduced, becoming negligible for traits simulated with λ < 0.7, where accuracy was in any case low.

Our study shows that variability in prediction accuracy among individual tips of the phylogeny should be considered when evaluating the reliability of phylogenetically imputed trait values. To address this challenge, we describe a Monte Carlo-based method that allows one to estimate the expected tip-level accuracy of phylogenetic predictions for continuous traits. Our approach identifies gaps in functional trait datasets for which phylogenetic imputation performs poorly, and will help ecologists to design more efficient trait collection campaigns by focusing resources on lineages whose trait values are more uncertain. | Phylogeny used for the empirical analysis Species-level time-calibrated molecular phylogeny of DNA including the 69 European and North American tree species used in the empirical analysis of the study (subset of a higher-rank phylogeny including 889 European and North American tree species, see Appendix 2 in Supplementary Material) Phylogeny.txt