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Economic decision making under uncertainty for wildfire fuels mitigation Scorah, Hugh William


Increases in wildfire suppression cost expenditures, an upward trend in burned area, increasing damages and evacuations, along with research pointing to a worsening trend in all of these areas as a result of climate change is motivating research into methods to limit the consequences of wildfire. My research is chiefly concerned with the use of economic tools to identify the best use of resources when evaluating fuel mitigation efforts both from a project perspective and at the landscape level. Using tools from Extreme Value Theory, I show that the distribution of wildfire costs is not likely to follow a normal distribution and instead is more likely drawn from fat-tailed distributions. This distribution implies that conventional tools of economic analysis, in particular, cost-benefit and cost-effectiveness analysis are not applicable and, if economic tools are to be applied, alternative approaches need to be developed. I present an alternative approach for analyzing individual projects, modeled after banking stress-tests, and apply it to four fuel-treatment case studies in the interior of British Columbia. This approach, called the Defensibility Heuristic, makes use of frontline experience (tacit knowledge), has few data and modeling requirements, and has the potential to quickly rank projects within a government budget and planning cycle that are most likely to protect the most important values. Following the development of this approach for picking fuel treatments in the short run, a tool for making decisions about longer-term forest management concerned with wildfire management is considered. This tool is community-centric as opposed to taking a provincial or federal perspective. Different approaches to ranking outcomes from decision theory were considered in the face of wildfire events that were drawn from a Power Law distribution. The existing decision rules were found wanting and I developed a rule called a Trauma Exposure. This decision rule was applied to the problem of setting annual harvest volumes to show that setting the harvest volume slightly below maximum sustained yield and organizing forest stands into a patchwork is likely to result in a more stable harvest volume over the long run.

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