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Managing Wildfire Events: Risk‐Based Decision Making Among a Group of Federal Fire Managers

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  • Robyn S. Wilson
  • Patricia L. Winter
  • Lynn A. Maguire
  • Timothy Ascher

Abstract

Managing wildfire events to achieve multiple management objectives involves a high degree of decision complexity and uncertainty, increasing the likelihood that decisions will be informed by experience‐based heuristics triggered by available cues at the time of the decision. The research reported here tests the prevalence of three risk‐based biases among 206 individuals in the USDA Forest Service with authority to choose how to manage a wildfire event (i.e., line officers and incident command personnel). The results indicate that the subjects exhibited loss aversion, choosing the safe option more often when the consequences of the choice were framed as potential gains, but this tendency was less pronounced among those with risk seeking attitudes. The subjects also exhibited discounting, choosing to minimize short‐term over long‐term risk due to a belief that future risk could be controlled, but this tendency was less pronounced among those with more experience. Finally, the subjects, in particular those with more experience, demonstrated a status quo bias, choosing suppression more often when their reported status quo was suppression. The results of this study point to a need to carefully construct the decision process to ensure that the uncertainty and conflicting objectives inherent in wildfire management do not result in the overuse of common heuristics. Individual attitudes toward risk or an agency culture of risk aversion may counterbalance such heuristics, whereas increased experience may lead to overconfident intuitive judgments and a failure to incorporate new and relevant information into the decision.

Suggested Citation

  • Robyn S. Wilson & Patricia L. Winter & Lynn A. Maguire & Timothy Ascher, 2011. "Managing Wildfire Events: Risk‐Based Decision Making Among a Group of Federal Fire Managers," Risk Analysis, John Wiley & Sons, vol. 31(5), pages 805-818, May.
  • Handle: RePEc:wly:riskan:v:31:y:2011:i:5:p:805-818
    DOI: 10.1111/j.1539-6924.2010.01534.x
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    References listed on IDEAS

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    Cited by:

    1. Matthew P Thompson, 2013. "Modeling Wildfire Incident Complexity Dynamics," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-10, May.
    2. Michael Greenberg & Charles Haas & Anthony Cox & Karen Lowrie & Katherine McComas & Warner North, 2012. "Ten Most Important Accomplishments in Risk Analysis, 1980–2010," Risk Analysis, John Wiley & Sons, vol. 32(5), pages 771-781, May.
    3. Michael S. Hand & Matthew J. Wibbenmeyer & David E. Calkin & Matthew P. Thompson, 2015. "Risk Preferences, Probability Weighting, and Strategy Tradeoffs in Wildfire Management," Risk Analysis, John Wiley & Sons, vol. 35(10), pages 1876-1891, October.
    4. Karin L. Riley & Matthew P. Thompson & Joe H. Scott & Julie W. Gilbertson-Day, 2018. "A Model-Based Framework to Evaluate Alternative Wildfire Suppression Strategies," Resources, MDPI, vol. 7(1), pages 1-26, January.
    5. Katuwal, Hari & Hand, Michael S. & Thompson, Matthew & Stonesifer, Crystal & Calkin, David, 2018. "Predict and Attack (or Don’t): An Econometric Approach to Large Wildfire Early Detection and Suppression Effectiveness," 2018 Annual Meeting, August 5-7, Washington, D.C. 274304, Agricultural and Applied Economics Association.
    6. Rossi, David & Kuusela, Olli-Pekka, 2020. "The influence of risk attitudes on suppression spending and on wildland fire program budgeting," Forest Policy and Economics, Elsevier, vol. 113(C).
    7. L. Robin Keller & Yitong Wang, 2017. "Information Presentation in Decision and Risk Analysis: Answered, Partly Answered, and Unanswered Questions," Risk Analysis, John Wiley & Sons, vol. 37(6), pages 1132-1145, June.

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