Presentation on theme: "Using expert judgments to explore robust alternatives for forest management under climate change By Tim McDaniels University of British Columbia and CEDM."— Presentation transcript:
Using expert judgments to explore robust alternatives for forest management under climate change By Tim McDaniels University of British Columbia and CEDM Using expert judgments to explore robust alternatives for forest management under climate change By Tim McDaniels University of British Columbia and CEDM
Acknowledgements Thanks to the CEDM and National Science Foundation for support Thanks to co-authors Tamsin Mills, Robin Gregory and Dan Ohlson Thanks to participants, and to Bruce Blackwell and Cindy Pearce for forestry advice and insights
Highlights First paper on RDM using expert judgments (forthcoming, Risk Analysis) Develops a framework for elicitation based on DA concepts: objectives, alts, Likert scales for performance measures of consequences, given different climate scenarios Results show two alternatives consistently outperform the current status quo Results are broadly consistent, and indicate promise for this approach
80% Volume of Pine killed on the Timber Harvesting Land Base by 2014 Maps: Government of BC
MPB Drivers “significant increase in infestations occurring in areas that were historically climatically unsuitable for the beetle.” (CFS) Infestations are climate exacerbated (along with previous management choices) Photo: watersecretsblog.com
Concepts and objectives Robust DM has great appeal as a response to irreducible uncertainty The analytical and information demands are enormous The intent here is to explore the feasibility of judgmental approaches to identifying robust alternatives in a specific climate adaptation decision context: how to manage land after the infestation
Robust DM criteria An array of definitions, used in various contexts Here: “..reasonably likely to achieve objectives, over a range of uncertainties” Here the uncertainty addressed is climate uncertainties, with three scenarios: low to high
Structured Decision Making Source: Ohlson et al 2005
Elicitation concepts Group elicitation of three point probabilities over the consequences of alternatives in terms of selected objectives Informed by concepts for improving judgmental forecasting: graphical communication, combining forecasts, specify scenarios, avoid bias and overconfidence etc (Stewart and Lusk)
Workbook /Workshop Elicit expert judgements Purposive Sampling Pilot test Workshop (n=14 after one rejection) Workbook: Defining the problem: study area Defining the problem: study area Management Objectives Management Objectives Climate Change scenarios Climate Change scenarios Introducing alternatives Introducing alternatives Evaluate the strategies; judgements Evaluate the strategies; judgements
Analysis approaches Examine the patterns for each person (one rejected) Examine the distributions (none bimodal) Combined forecasts (averaging at first) Conducted extensive sensitivity analysis (varying weights on each objective) Examined individual preferred alternatives (consistent with averaged results)
Findings Two closely related alts widely seen as most robust over the climate uncertainty The current status quo policy performs worst The more robust alts have higher performance in part due to more flexibility and diversity on the ground (like findings of analytical RDM) This is an encouraging method that deserves further work
How were judgements affected by time period, objectives and climate change scenarios?
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