Factors influencing large wildland fire suppression expenditures
Jingjing Liang A E , Dave E. Calkin B , Krista M. Gebert B , Tyron J. Venn C and Robin P. Silverstein DA Department of Forest Sciences, PO Box 757200, University of Alaska, Fairbanks, AK 99775, USA.
B USDA Rocky Mountain Research Station, Forestry Sciences Laboratory, 800 East Beckwith Ave., Missoula, MT 59801, USA.
C College of Forestry and Conservation, University of Montana, Missoula, MT 59812, USA.
D Wildlife Biology Program, University of Montana, Missoula, MT 59812, USA.
E Corresponding author. Email: j.liang@uaf.edu
International Journal of Wildland Fire 17(5) 650-659 https://doi.org/10.1071/WF07010
Submitted: 11 January 2007 Accepted: 24 December 2007 Published: 3 October 2008
Abstract
There is an urgent and immediate need to address the excessive cost of large fires. Here, we studied large wildland fire suppression expenditures by the US Department of Agriculture Forest Service. Among 16 potential non-managerial factors, which represented fire size and shape, private properties, public land attributes, forest and fuel conditions, and geographic settings, we found only fire size and private land had a strong effect on suppression expenditures. When both were accounted for, all the other variables had no significant effect. A parsimonious model to predict suppression expenditures was suggested, in which fire size and private land explained 58% of variation in expenditures. Other things being equal, suppression expenditures monotonically increased with fire size. For the average fire size, expenditures first increased with the percentage of private land within burned area, but as the percentage exceeded 20%, expenditures slowly declined until they stabilised when private land reached 50% of burned area. The results suggested that efforts to contain federal suppression expenditures need to focus on the highly complex, politically sensitive topic of wildfires on private land.
Additional keywords: cost containment, fire economics, geostatistics, hierarchical partitioning, hypothesis test.
A See http://nris.mt.gov (accessed 22 May 2006).
B See http://www.idwr.idaho.gov (accessed 22 May 2006).
C See http://www.census.gov/ (accessed 29 June 2006).
D Available at http://nris.state.mt.us/nsdi/cadastral/ for Montana and http://gis.idl.state.id.us/website/idl for Idaho (accessed 15 August 2006).
E See http://seamless.usgs.gov (accessed 6 June 2006).
F P. Garbutt is the USDA Forest Service Region One Assistant Director of Fire management.
G See Headwater Economics at http://www.headwaterseconomics.org/wildfire/ (accessed 12 February 2008).
Acknowledgements
We thank Amy Steinke, Kevin D. Hyde, and Judy M. Troutwine for assistance with data and mapping. We are greatly obliged to Mo Zhou for insights and review.
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