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No need for disease: testing extinction hypotheses for the thylacine using multi-species metamodels
Thomas A A Prowse1, Christopher N Johnson, Robert C Lacy
1Environment Institute and School of Earth and Environmental Science, University of Adelaide, Adelaide, SA, 5005, Australia.
Abstract:
Population viability analysis (PVA) is widely used to assess the extinction risk of threatened species and to evaluate different management strategies. However, conventional PVA neglects important biotic interactions and therefore can fail to identify important threatening processes. We designed a new PVA approach that includes species interactions explicitly by networking species models within a single 'metamodel'. We demonstrate the utility of PVA metamodels by employing them to reinterpret the extinction of the carnivorous, marsupial thylacine Thylacinus cynocephalus in Tasmania. In particular, we test the claim that well-documented impacts of European settlement cannot account for this extinction and that an unknown disease must have been an additional and necessary cause. We first constructed a classical, single-species PVA model for thylacines, which was then extended by incorporation within a dynamic predator-herbivore-vegetation metamodel that accounted for the influence of Europeans on the thylacine's prey base. Given obvious parameter uncertainties, we explored both modelling approaches with rigorous sensitivity analyses. Single-species PVA models were unable to recreate the thylacine's extinction unless a high human harvest, small starting population size or low maximum population growth rate was assumed, even if disease effects were included from 1906 to 1909. In contrast, we readily recreated the thylacine's demise using disease-free multi-species metamodels that simulated declines in native prey populations (particularly due to competition with introduced sheep). Dynamic, multi-species metamodels provide a simple, flexible framework for studying current species declines and historical extinctions caused by complex, interacting factors.
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