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Learning, Adaptive Management and Wildfire Policy
Unformatted Document Text:  ii Learning, Adaptive Management and Wildfire Policy Abstract Wildfire disasters threaten numerous communities and ecosystems in America today. An effective policy strategy to counteract the threat of wildfire disasters would entail the reduction of accumulated fuels (flammable organic materials) found across large areas in many American ecosystems. Major uncertainties surround this policy endeavor, since fuel reduction has never been attempted on such large scales before. This study outlines an adaptive policy strategy designed to resolve these uncertainties through a systematic process of learning. An adaptive wildfire policy would employ fuel reduction experiments on large scales, with the goal of generating new knowledge to progressively improve the effectiveness of fuel reduction strategies over time. Keywords Wildfires, disasters, learning, adaptive management. Acknowledgments The author thanks William Ascher, Linda deLeon, Peter deLeon, Jody Fitzpatrick, Christine Martell, Richard Stillman II, Paul Teske, and the reviewers for their comments concerning this study.

Authors: Busenberg, George.
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ii
Learning, Adaptive Management and Wildfire Policy
Abstract
Wildfire disasters threaten numerous communities and ecosystems in America today. An
effective policy strategy to counteract the threat of wildfire disasters would entail the reduction
of accumulated fuels (flammable organic materials) found across large areas in many American
ecosystems. Major uncertainties surround this policy endeavor, since fuel reduction has never
been attempted on such large scales before. This study outlines an adaptive policy strategy
designed to resolve these uncertainties through a systematic process of learning. An adaptive
wildfire policy would employ fuel reduction experiments on large scales, with the goal of
generating new knowledge to progressively improve the effectiveness of fuel reduction strategies
over time.
Keywords
Wildfires, disasters, learning, adaptive management.
Acknowledgments
The author thanks William Ascher, Linda deLeon, Peter deLeon, Jody Fitzpatrick, Christine
Martell, Richard Stillman II, Paul Teske, and the reviewers for their comments concerning this
study.


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