Economic optimisation of wildfire intervention activities
David T. Butry A D , Jeffrey P. Prestemon B , Karen L. Abt B and Ronda Sutphen CA Office of Applied Economics, Building and Fire Research Laboratory, National Institute of Standards and Technology, 100 Bureau Drive, Mail Stop 8603, Gaithersburg, MD 20899-8603, USA.
B Southern Research Station, Forestry Sciences Laboratory, PO Box 12254, Research Triangle Park, NC 27709, USA. Email: jprestemon@fs.fed.us; kabt@fs.fed.us
C Florida Division of Forestry, Department of Agriculture and Consumer Services, 3125 Conner Boulevard, Tallahassee, FL 32399-1650, USA. Email: sutpher@doacs.state.fl.us
D Corresponding author. Email: david.butry@nist.gov
International Journal of Wildland Fire 19(5) 659-672 https://doi.org/10.1071/WF09090
Submitted: 19 August 2009 Accepted: 7 April 2010 Published: 9 August 2010
Abstract
We describe how two important tools of wildfire management, wildfire prevention education and prescribed fire for fuels management, can be coordinated to minimise the combination of management costs and expected societal losses resulting from wildland fire. We present a long-run model that accounts for the dynamics of wildfire, the effects of fuels management on wildfire ignition risk and area burned, and the effects of wildfire prevention education on the ignition risk of human-caused, unintentional wildfires. Based on wildfire management activities in Florida from 2002 to 2007, we find that although wildfire prevention education and prescribed fire have different effects on timing and types of fires, the optimal solution is to increase both interventions. Prescribed fire affects whole landscapes and therefore reduces losses from all wildfire types (including lightning), whereas wildfire prevention education reduces only human-caused ignitions. However, prescribed fire offers a longer-term solution with little short-term flexibility. Wildfire prevention education programs, by comparison, are more flexible, both in time and space, and can respond to unexpected outbreaks, but with limited mitigation longevity. Only when used together in a coordinated effort do we find the costs and losses from unintentional wildfires are minimised.
Additional keywords: fire economics, hazard mitigation, wildland–urban interface, wildland fire.
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A Prevention success may affect fuels, and thereby, indirectly affect wildfire size. We address this negative feedback below.
B These include debris fire escapes, campfire escapes, and fires caused by discarded cigarettes and by children. We ignore other kinds of unintentional fire starts (such as equipment and railroad fires) because they are not the focus of wildfire prevention education, and we ignore arson because its occurrence is affected by a different combination of managerial (and law enforcement) actions (e.g. Prestemon and Butry 2005).
C This figure assumes a constant cost plus loss per hectare of wildfire. An alternative assumption, allowing costs plus losses to have a fixed cost per fire and a variable cost per hectare burned, was not testable with the available data.
D A program focussing on private lands would require a prescribed fire incentive program, which we did not evaluate in this study.