Ecological controls of biodiversity in deep time

Abstract

Temporal, spatial and among lineage differences in biodiversity are trademarks in the history of life. Documenting how the number of species varies is a first order description, but to fully understand biodiversity we also need to understand how speciation and extinction rates vary over time or among lineages, and what factors control the dynamics of such rates. The last decade has seen an unprecedented development of new statistical tools to infer diversification dynamics from the fossil record and molecular data, but only very recently have we seen an effort to more directly incorporate ecology into macroevolutionary models. A deep time (here defined as a multi-million year time frame) perspective on biodiversity dynamics have typically polarized views of abiotic and biotic controls, attributing drastic diversity changes to abiotic factors, and relegating a secondary role for biotic interactions. This might not be surprising given how difficult it is to document biotic interactions in deep time. The current project aims to use and develop new statistical tools that will allow a better understanding of the roles of biotic and abiotic factors, and their likely interaction, in driving changes in speciation and extinction dynamics. Data on the fossil record, molecular phylogenies, ecology and morphology will be used to investigate the diversification dynamics using state-of-the-art tools from both analytical paleontology and phylogenetic comparative methods. As model system, we will use different vertebrate groups, with special attention to mammals and birds. More specifically, we will investigate the effect of interspecific interactions and of gradual changes in environmental area on speciation and extinction dynamics. The empirical results will help develop a new theory on how equilibrium and non-equilibrium processes operate to regulate biodiversity in deep time, help us understand the role of species interaction and environmental changes in deep time, and help us better understand how short time processes scale up to macroevolutionary time scales. (AU)