Inferring macro-evolutionary patterns using an adaptive peak model of evolution

Background: Currently available methods of ancestral reconstruction are built either on Brownian Motion (BM) or Ornstein-Uhlenbeck (OU) models of evolution. Results from these methods sometimes do not agree with the fossil record. Aim: Develop a new method, the method of Independent Evolution (IE), built on an adaptive peak model of evolution. Key assumptions: In evolution, population phenotypes are affected by the wandering adaptive peaks of adaptive surfaces. Branch-specific rates of evolution depend on weighted, relative distances between an ancestral adaptive peak and a new adaptive surface that descendant populations attempt to climb. Methods: We defined an eight-step algorithm to incorporate the assumptions, and then applied it recursively for each node in the tree to produce the phylogenetic histories. We performed two studies: a simulation study of directional selection on particular branches in a model primate phylogeny, and a case study of primate brain and body size in which we reconstructed the ancestral states of primate brain sizes and body sizes and compared them with 28 fossil data points. In each study, we used strong inference - that is, we employed six different methods of ancestral reconstruction to determine how well each succeeds. Four of the methods of ancestral reconstruction are based on BM, one on the OU, and one is IE. Results: The method based on an adaptive peak model of evolution (IE) significantly outperformed both BM-based and OU-based methods of ancestral reconstruction in the simulation study. Independent Evolution also yielded much more accurate estimates of ancestral (i.e. fossil) primate brain and body sizes than the other methods of ancestral reconstruction.