Collaborative Research: CMG: Mathematical Modeling and Bayesian Analysis of Paleocommunity Collapse during Mass Extinctions

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The PIs propose to study the role of the shutdown of primary production, during times of mass extinction, in propagating extinction and ecosystem collapse. The disruption of primary production has been suggested as a proximal mechanism of extinction during extreme ecological crises in the Earth's past, perhaps causing avalanches of secondary extinction throughout trophic systems. The complexity of ecological networks presents a distinct challenge to understanding the pathways by which such secondary extinctions are propagated. This project will use a combined approach of numerical simulation and Bayesian statistical modeling to partition extinction due to direct effects on species, versus extinction caused by the loss of trophic resources. Given that food web structure varies with organismal composition through the periods of interest, the PIs will use numerical simulations to evaluate the sensitivity of food webs to perturbations of primary production. They predict that sensitivity will decline during intervals of mass extinction and post-extinction recovery. They will use Bayesian statistical modeling to estimate primary and secondary extinction components using observed extinction data from the fossil record of specific paleobiogeographic communities from the Permian and late Neogene. They will estimate the maximum levels of primary production disruption that could yield observed levels of extinction. They predict such levels to increase dramatically during intervals of mass extinction, if disruption of photosynthesis and secondary extinction were indeed important drivers of ecosystem collapse.