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Integration of social and ecological sciences for natural resource decision making: challenges and opportunities

  • Kelly F. RobinsonEmail author
  • Angela K. Fuller
  • Richard C. Stedman
  • William F. Siemer
  • Daniel J. Decker
Article

Abstract

The last 25 years have witnessed growing recognition that natural resource management decisions depend as much on understanding humans and their social interactions as on understanding the interactions between non-human organisms and their environment. Decision science provides a framework for integrating ecological and social factors into a decision, but challenges to integration remain. The decision-analytic framework elicits values and preferences to help articulate objectives, and then evaluates the outcomes of alternative management actions to achieve these objectives. Integrating social science into these steps can be hindered by failing to include social scientists as more than stakeholder-process facilitators, assuming that specific decision-analytic skills are commonplace for social scientists, misperceptions of social data as inherently qualitative, timescale mismatches for iterating through decision analysis and collecting relevant social data, difficulties in predicting human behavior, and failures of institutions to recognize the importance of this integration. We engage these challenges, and suggest solutions to them, helping move forward the integration of social and biological/ecological knowledge and considerations in decision-making.

Keywords

Adaptive management Multi-objective decision analysis Decision science Natural resources Social science Structured decision making 

Notes

Acknowledgements

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. We thank M. Mitchell, C. Moore, and one anonymous reviewer for helpful comments on drafts of this manuscript. Ideas in this paper were generated by working on a collaborative structured decision-making process for white-tailed deer management in New York State, supported by New York Federal Aid in Wildlife Restoration Grant WE – 173 – G. This is publication no. 2019−03 from the Quantitative Fisheries Center.

Compliance with ethical standards

Conflict of Interest

The authors declare that they have no conflicts of interest.

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Copyright information

© This is a U.S. government work and its text is not subject to copyright protection in the United States; however, its text may be subject to foreign copyright protection 2019

Authors and Affiliations

  1. 1.Department of Natural Resources, New York Cooperative Fish and Wildlife Research UnitCornell UniversityIthacaUSA
  2. 2.Department of Natural Resources, U.S. Geological Survey, New York Cooperative Fish and Wildlife Research UnitCornell UniversityIthacaUSA
  3. 3.Department of Natural Resources, Cornell Center for Conservation Social SciencesCornell UniversityIthacaUSA
  4. 4.Department of Fisheries and Wildlife, Quantitative Fisheries CenterMichigan State UniversityEast LansingUSA

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