Ecological–economic optimization of biodiversity conservation under climate change

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Abstract

Substantial investment in climate change research has led to dire predictions of the impacts and risks to biodiversity. The Intergovernmental Panel on Climate Change fourth assessment report1 cites 28,586 studies demonstrating significant biological changes in terrestrial systems2. Already high extinction rates, driven primarily by habitat loss, are predicted to increase under climate change3,4,5,6. Yet there is little specific advice or precedent in the literature to guide climate adaptation investment for conserving biodiversity within realistic economic constraints7. 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. We discover a counterintuitive optimal investment strategy that switches twice between options as the available adaptation budget increases. We demonstrate that optimal investment is nonlinearly dependent on available resources, making the choice of how much to invest as important as determining where to invest and what actions to take. Our study emphasizes the importance of a sound analytical framework for prioritizing adaptation investments4. Integrating ecological predictions in an economic decision framework will help support complex choices between adaptation options under severe uncertainty. Our prioritization method can be applied at any scale to minimize species loss and to evaluate the robustness of decisions to uncertainty about key assumptions.

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Figure 1: A framework for climate adaptation investment decision-making.
Figure 2: Optimal allocation of management effort under varying budget constraints.
Figure 3: The robustness of fynbos climate adaptation investment options to uncertainty about fire management and habitat protection effectiveness.

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Acknowledgements

This work was funded by the Commonwealth Environment Research Facility; Applied Environmental Decision Analysis and by the Australian Research Council (LP0989537, FF0668778). M.C. was supported by the EU project RESPONSES. We thank M. Bode and W. Morris for assistance in modelling the fire management efficiency curves, G. Forsyth for evaluation of the fire, habitat and weed management cost estimates, and L. Rumpff for help with Fig. 1.

Author information

B.A.W., S.A.B., D.A.K., and H.P.P. designed the research. B.A.W., D.A.K., and B.W.v.W. performed the analysis. B.A.W., S.A.B, M.C., B.S., S.B.C., L.B., A.F., L.M., C.R., T.J.R., and H.P.P. wrote the paper. All authors discussed the results and edited the manuscript.

Correspondence to Brendan A. Wintle.

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The authors declare no competing financial interests.

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