OOS 24-9 - From prediction to action; the science of saving species from climate change

Wednesday, August 10, 2011: 10:50 AM
14, Austin Convention Center
Brendan A. Wintle, School of Botany, University of Melbourne, Australia, Sarah A. Bekessy, School of Global, Urban and Social Studies, RMIT University, Melbourne, Australia, David A. Keith, Department of Environment and Climate Change New South Wales, Sydney, Australia, Brian van Wilgen, CSIR South Africa, Stellenbosch, South Africa and Hugh P. Possingham, ARC Centre of Excellence for Environmental Decisions, University of Queensland, St. Lucia, Australia
Background/Question/Methods

Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity; the IPCC Fourth Assessment Report cites 28,586 studies demonstrating significant biological changes in terrestrial systems. Yet there is little advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity under realistic social and economic constraints. Given that there is an impending extinction crisis, we need to move urgently from predictive science to decision science in order to support difficult choices between climate adaptation options under severe uncertainty. Here we present a systematic ecological and economic analysis of a climate adaptation problem in one of the world's most species rich and threatened ecosystems; the South African Fynbos. Our approach integrates models of climatic and ecological change, population demographic models to predict plant abundance fluctuations in response to environmental stressors and management, and a decision theoretic approach to identifying optimal adaptation strategies.

Results/Conclusions

We discover a counter-intuitive optimal investment strategy that switches twice between fire management and habitat protection options as the available adaptation budgets increases. We demonstrate that optimal investment is non-linearly dependent on available resources, making the choice of how much to invest as important as determining what to invest in and where. Our study emphasizes the importance of a sound analytical framework for adaptation investment that integrates information and tools from ecology, economics, social science and decision science. Our method for prioritizing investment can be applied at any scale to minimize the loss of species under climate change. We anticipate that the approach illustrated here will form the basis of future climate adaptation investments.

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