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Ecological–economic optimization of biodiversity conservation under climate change

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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References

  1. Rosenzweig, C. et al. in IPCC Climate Change 2007: Impacts, Adaptation, and Vulnerability (eds Parry, M. L. et al.) 79–131 (Cambridge Univ. Press, 2007).

    Google Scholar 

  2. Richardson, A. J. & Poloczanska, E. S. Under resourced, under threat. Science 320, 1294–1295 (2008).

    Article  CAS  Google Scholar 

  3. Thomas, C. D. et al. Extinction risk from climate change. Nature 427, 145–148 (2004).

    Article  CAS  Google Scholar 

  4. Dawson, T. P., Jackson, S. T., House, J. I., Prentice, I. C. & Mace, G. M. Beyond predictions: Biodiversity conservation in a changing climate. Science 332, 53–58 (2011).

    Article  CAS  Google Scholar 

  5. Hoegh-Guldberg, O. et al. Coral reefs under rapid climate change and ocean acidification. Science 318, 1737–1742 (2007).

    Article  CAS  Google Scholar 

  6. Parmesan, C. Ecological and evolutionary responses to recent climate change. Annu. Rev. Ecol. Syst. 37, 637–669 (2006).

    Article  Google Scholar 

  7. Heller, N. E. & Zavaleta, E. S. Biodiversity management in the face of climate change: A review of 22 years of recommendations. Biol. Conserv. 142, 14–32 (2009).

    Article  Google Scholar 

  8. Polasky, S., Carpenter, S. R., Folke, C. & Keeler, B. Decision-making under great uncertainty: Environmental management in an era of global change. Trends Ecol. Evol. 26, 398–494 (2011).

    Article  Google Scholar 

  9. Wald, A. Statistical decision functions which minimize the maximum risk. Ann. Math. 46, 265–280 (1945).

    Article  Google Scholar 

  10. Goldblatt, P. & Manning, J. Plant diversity of the Cape region of South Africa. Ann. Missouri Bot. Garden 89, 281–302 (2002).

    Article  Google Scholar 

  11. Keith, D. A. et al. Predicting extinction risks under climate change: Coupling stochastic population models with dynamic bioclimatic habitat models. Biol. Lett. 4, 560–563 (2008).

    Article  Google Scholar 

  12. Wilson, K. A. et al. Conserving biodiversity efficiently: What to do, where, and when. PloS Biol. 5, 1850–1861 (2007).

    Article  CAS  Google Scholar 

  13. van Wilgen, B. W. The evolution of fire and invasive alien plant management practices in fynbos. South Afr. J. Sci. 105, 335–342 (2009).

    Google Scholar 

  14. Hoegh-Guldberg, O. et al. Assisted colonization and rapid climate change. Science 321, 345–346 (2008).

    Article  CAS  Google Scholar 

  15. van Wilgen, B. W. et al. Fire management in Mediterranean-climate shrublands: A case study from the Cape fynbos, South Africa. J. Appl. Ecol. 47, 631–638 (2010).

    Article  Google Scholar 

  16. Pitman, A. J., Narisma, G. T. & McAneney, J. The impact of climate change on the risk of forest and grassland fires in Australia. Climatic Change 84, 383–401 (2007).

    Article  Google Scholar 

  17. Osano, M. O., Rouget, M., Turpie, J., Thuiller, W. & Balmford, A. in Estimating Land Prices and Opportunity Costs of Conservation in a Megadiversity Country (ATPS Working Paper Series No. 58, African Technology Policy Studies Network, 2011).

    Google Scholar 

  18. McCarthy, M. A. & Thompson, C. Expected minimum population size as a measure of threat. Animal Conserv. 4, 351–355 (2001).

    Article  Google Scholar 

  19. Burgman, M. A., Akcakaya, H. R. & Loew, S. S. The use of extinction models for species conservation. Biol. Conserv. 43, 9–25 (1988).

    Article  Google Scholar 

  20. Joseph, L. N., Maloney, R. F. & Possingham, H. P. Optimal allocation of resources among threatened species: A project prioritization protocol. Conserv. Biol. 23, 328–338 (2009).

    Article  Google Scholar 

  21. Ben-Haim, Y. Info-gap Decision Theory 2nd edn (Elsevier, 2006).

    Google Scholar 

  22. Gold, M. R., Siegel, J. E., Russell, L. B. & Weinstein, M. C. Cost-effectiveness in Health and Medicine (Oxford Univ. Press, 1996).

    Google Scholar 

  23. National Action Plan for Energy Efficiency Understanding Cost-effectiveness of Energy Efficiency Programs: Best Practices, Technical Methods, and Emerging Issues for Policy-makers (US Environment Protection Agency, Energy and Environmental Economics, 2008).

  24. Fowler, R. A. et al. Cost effectiveness of defending against bioterrorism: A comparison of vaccination and antibiotic prophylaxis against anthrax. Ann. Intern. Med. 142, 601–610 (2005).

    Article  Google Scholar 

  25. Kremen, C. et al. Aligning conservation priorities across taxa in Madagascar with high-resolution planning tools. Science 320, 222–225 (2008).

    Article  CAS  Google Scholar 

  26. Moilanen, A. et al. Planning for robust reserve networks using uncertainty analysis. Ecol. Model. 199, 115–124 (2007).

    Article  Google Scholar 

  27. Ferraro, P. J. & Pattanayak, S. K. Money for nothing? A call for empirical evaluation of biodiversity conservation investments. PLoS Biol. 4, 482–488 (2006).

    Article  CAS  Google Scholar 

  28. McDonald-Madden, E. et al. Active adaptive conservation of threatened species in the face of uncertainty. Ecol. Appl. 20, 1476–1489 (2010).

    Article  Google Scholar 

  29. Walters, C. & Holling, C. S. Large-scale management experiments and learning by doing. Ecology 71, 2060–2068 (1990).

    Article  Google Scholar 

  30. Stankey, G. H. et al. Adaptive management and the Northwest Forest Plan; rhetoric and reality. J. For. 101, 40–46 (2003).

    Google Scholar 

  31. RAMAS GIS: linking spatial data with population viability analysis v.5.0 (Applied Biomathematics, 2005).

  32. Lucas, C., Hennessy, K., Mills, G. & Bathols, J. Bushfire Weather in Southeast Australia: Recent Trends and Projected Climate Change Impacts: Consultancy Report Prepared for The Climate Institute of Australia (CSIRO, Bushfire CRC, 2007).

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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.

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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.

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Correspondence to Brendan A. Wintle.

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The authors declare no competing financial interests.

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Wintle, B., Bekessy, S., Keith, D. et al. Ecological–economic optimization of biodiversity conservation under climate change. Nature Clim Change 1, 355–359 (2011). https://doi.org/10.1038/nclimate1227

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