Unifying the study of biodiversity across timescales: What a MESS!
Abstract: Biodiversity in ecological communities can accumulate via colonization from a regional source pool, in situ speciation, or some combination of these. Reconciling the relative importance of these processes is hindered because current theory tends to focus only one timescale (i.e. macro-ecology, phylogeography, and/or macro-evolution). I will introduce a mechanistic model of community assembly, rooted in classic island biogeography theory (MacArthur and Wilson 1967; Hubbell 2006), which makes historically dynamic joint predictions of species richness and abundances; genetic diversities and divergences; and trait evolution within the context of phylogenetic diversification. Using simulations and empirical data I demonstrate that each data axis captures information at different timescales of assembly, and that combining all these axes results in much finer resolution inference. Finally, I demonstrate our simulation-based inferential framework (massive eco-evolutionary synthesis simulation; MESS), which uses supervised machine learning to test competing models of community assembly and evolution (niche vs neutral and evolved vs assembled) and to estimate an array of model parameters relevant to a complex history of island assembly and evolution.
Those unable to attend can stream the lecture from our YouTube channel.