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Using Expert Judgments to Explore Robust Alternatives for Forest Management under Climate Change

Authors

  • Timothy McDaniels,

    Corresponding author
    1. University of British Columbia
      Timothy McDaniels, School of Community and Regional Planning, University of British Columbia, 415-6333 Memorial Rd., Vancouver, BC, V6T 1Z2 Canada; tel: 604-822-9288; timmcd@exchange.ubc.ca
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  • Tamsin Mills,

    1. Climate Adaptation Planner, City of Vancouver, and Compass Resource Management Ltd., 200 – 1260 Hamilton St. Vancouver, B.C. V6B 2S8 Canada
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  • Robin Gregory,

    1. Senior Reseacher, Decision Research, Galiano BC Canada V0N1P0
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  • Dan Ohlson

    1. Partner, Compass Resource Management Ltd. 200 – 1260 Hamilton St. Vancouver, B.C. V6B 2S8 Canada
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Timothy McDaniels, School of Community and Regional Planning, University of British Columbia, 415-6333 Memorial Rd., Vancouver, BC, V6T 1Z2 Canada; tel: 604-822-9288; timmcd@exchange.ubc.ca.

Abstract

We develop and apply a judgment-based approach to selecting robust alternatives, which are defined here as reasonably likely to achieve objectives, over a range of uncertainties. The intent is to develop an approach that is more practical in terms of data and analysis requirements than current approaches, informed by the literature and experience with probability elicitation and judgmental forecasting. The context involves decisions about managing forest lands that have been severely affected by mountain pine beetles in British Columbia, a pest infestation that is climate-exacerbated. A forest management decision was developed as the basis for the context, objectives, and alternatives for land management actions, to frame and condition the judgments. A wide range of climate forecasts, taken to represent the 10–90% levels on cumulative distributions for future climate, were developed to condition judgments. An elicitation instrument was developed, tested, and revised to serve as the basis for eliciting probabilistic three-point distributions regarding the performance of selected alternatives, over a set of relevant objectives, in the short and long term. The elicitations were conducted in a workshop comprising 14 regional forest management specialists. We employed the concept of stochastic dominance to help identify robust alternatives. We used extensive sensitivity analysis to explore the patterns in the judgments, and also considered the preferred alternatives for each individual expert. The results show that two alternatives that are more flexible than the current policies are judged more likely to perform better than the current alternatives on average in terms of stochastic dominance. The results suggest judgmental approaches to robust decision making deserve greater attention and testing.

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