Grant: Discovery Grants Program - Individual

Long-term patterns of evolution have captured the imagination of biologists for centuries, and understanding the “tree of life” is a fundamental problem in science. Macroevolutionary patterns such as stasis and adaptive radiations have been extensively analyzed, and it is generally thought that ecological adaptations play an important role for long-term evolution. However, ecological explanations for macroevolutionary patters are still mostly based on verbal theories. Macroevolutionary patterns ultimately result from microevolutionary processes. With the research proposed here, I intend to develop a mathematical theory for macroevolutionary dynamics and phylogenetic analysis that is derived from ecological birth-death processes. I propose to use this theory as a testing ground for existing comparative phylogenetic methods. Finally, I propose to apply novel computational tools to study macroevolution of ecologically important traits on large phylogenetic trees. Specifically: 1) I propose to use adaptive dynamics models incorporating diversification and extinction to classify salient patterns of macroevolutionary dynamics generated by different types of ecological interactions, for varying dimensions of phenotype space, and for different assumptions about the biogeography of the evolving communities. This will yield a general classification of the types of macroevolutionary patterns generated by mechanistic models for long-term evolution. In particular, it will enable a critical evaluation of salient verbal theories for macroevolution. 2) The adaptive dynamics models yield artificial phylogenetic trees that I propose to analyze using a variety of comparative phylogenetic methods in order to test which of these can best explain the phylogenies. This will allow for a comparison of inferences made from comparative methods with the actual ecological processes that generated the phylogenies. This work will also give important insights into the statistical properties of mechanistic models for macroevolution. 3) Microorganisms have shaped the chemistry of Earth's ecosystems, and determining the macroevolutionary patterns of metabolic functions in the prokaryotic tree of life is an important problem. Prokaryotic phylogenies can be extremely large, and their analysis requires novel computational tools. I propose to apply such tools to the problem of the evolution of protein superfamilies along the microbial tree of life.