Macroevolutionary Drivers of Trait Evolution

• Applicant: Professor Dr. Sebastian Höhna
• Subject Area: Evolution, Anthropology
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 582613743

Darwinian evolution through natural selection is fundamentally acting on traits. Specifically, the actual trait value, such as beak size, and its deviation from the optimum defines the fitness of an individual. On a macroevolutionary scale, i.e., over millions of years and across hundreds of closely related species, we can study adaptation by how the mean trait value per species evolves around a trait optimum. Over macroevolutionary timescales, this trait optimum will not be stable but instead vary over time, e.g., due to changes in the global environment, and across species, e.g., specialization on different diets. Surprisingly, only very simplistic statistical approaches exist to study adaptation on a macroevolutionary scale. The currently most sophisticated approach uses the Ornstein-Uhlenbeck process, which contains three parameters: the rate of adaption, the rate of drift, and the trait optimum. This approach has been extended to allow for varying optima across species, although utilizing several shortcuts and inefficient theory prohibiting application on study groups of more than 500 species. In this project we will develop a novel approach to study trait adaptation over macroevolutionary timescales by extending the basic theory of Ornstein-Uhlenbeck processes. Specifically, we will develop a model where all three parameters (the rate of adaption, the rate of drift, and the trait optimum) can vary among species and/or vary over time, and we will develop and efficient algorithm to compute likelihoods extremely fast under this complex new model. We will implement this new model and likelihood computation in our popular Bayesian phylogenetics software RevBayes and explore the approach extensively by means of simulations. Furthermore, we will apply this novel approach to phylogenies of mammals, birds, fishes and crocodylomorphs to test if variation in optimal body size is correlated to habitat, diet and slow vs fast life history as well as global temperature and oxygen levels. With this project, we provide a fundamental advancement to study and understand trait adaption on a macroevolutionary scale. We will have, for the first time, a proper statistical framework to study macroevolutionary drivers of trait evolution.

• DFG Programme: Research Grants