An introduction to decision science for conservation |
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| Authors: | Victoria Hemming Abbey E Camaclang Megan S Adams Mark Burgman Katherine Carbeck Josie Carwardine Iadine Chadès Lia Chalifour Sarah J Converse Lindsay N K Davidson Georgia E Garrard Riley Finn Jesse R Fleri Jacqueline Huard Helen J Mayfield Eve McDonald Madden Ilona Naujokaitis-Lewis Hugh P Possingham Libby Rumpff Michael C Runge Daniel Stewart Vivitskaia J D Tulloch Terry Walshe Tara G Martin |
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| Institution: | 1. Conservation Decisions Lab, Department of Forest and Conservation Sciences, University of British Columbia, Vancouver, British Columbia, Canada;2. Centre for Environmental Policy, Imperial College London, London, UK;3. Land and Water, CSIRO, Dutton Park, Queensland, Australia;4. Department of Biology, University of Victoria, Victoria, British Columbia, Canada;5. U.S. Geological Survey, Washington Cooperative Fish and Wildlife Research Unit, School of Environmental and Forest Sciences & School of Aquatic and Fishery Sciences, University of Washington, Seattle, Washington, USA;6. Biodiversity Research Center, University of British Columbia, Vancouver, British Columbia, Canada;7. School of Ecosystem and Forest Sciences, The University of Melbourne, Melbourne, Victoria, Australia;8. Department of Botany, University of Wyoming, Laramie, Wyoming, USA;9. School of Earth and Environmental Sciences, The University of Queensland, Brisbane, Queensland, Australia;10. National Wildlife Research Centre, Environment and Climate Change Canada, Carleton University, Ottawa, Ontario, Canada;11. Centre for Biodiversity and Conservation Science, The University of Queensland, Saint Lucia, Queensland, Australia;12. U.S. Geological Survey Eastern Ecological Science Center, Patuxent Research Refuge, Laurel, Maryland, USA |
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| Abstract: | Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems. |
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| Keywords: | conservation decision analysis decision science decision-making prioritization social science structured decision-making uncertainty values análisis de decisiones ciencias de la decisión ciencias sociales conservación incertidumbre priorización toma de decisiones toma estructurada de decisiones valores |
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