Exploring patterns of interspecific variation in quantitative traits using sequential phylogenetic eigenvector regressions.

摘要: A number of metrics have been developed for estimating phylogenetic signal in data and to evaluate correlated evolution, inferring broad-scale evolutionary ecological processes. Here, we proposed an approach called signal-representation (PSR) curve, built upon eigenvector regression (PVR). In PVR, selected eigenvectors extracted from a distance matrix are used model interspecific variation. the PSR sequential PVR models fitted after successively increasing plotting their R(2) against accumulated eigenvalues. We simulations show that linear curve is expected under Brownian motion its shape changes alternative models. The area, expressing deviations motion, strongly (r= 0.873; P < 0.01) with Blomberg's K-statistics, so nonlinear curves reveal if traits evolving at slower or higher rate than by motion. area also half-life Ornstein-Uhlenbeck process, suggesting how both methods describe relationship between variation time since divergence among species. provides elegant exploratory method understand terms acceleration deceleration rates occurring large small distances.