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    Author(s): David Calkin; Kevin Hyde; Krista GebertGreg Jones
    Date: 2005
    Source: Res. Note RMRS-RN-24. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 8 p.
    Publication Series: Research Note (RN)
    Station: Rocky Mountain Research Station
    PDF: View PDF  (678.0 KB)

    Description

    Determining the economic effectiveness of wildfire suppression activities is complicated by difficulties in identifying the area that would have burned and the associated resource value changes had suppression resources not been employed. We developed a case study using break-even analysis for two large wildfires from the 2003 fire season in western Montana -- the Black Mountain and Crazy Horse Fires. We used GIS to identify the location and taxable value of private residences within perimeters expanding in a likely direction of fire spread for both fires. We identified the size of an expanded perimeter where the market values of private property equaled the amount of money spent suppressing a fire (the break even point). This analysis showed that suppression expenditures on the Black Mountain Fire were economically justified if these efforts reduced the potential fire perimeter a modest amount. However, the potential fire perimeter for the Crazy Horse Fire would have had to be considerably larger than the actual fire perimeter to economically justify the associated suppression expenditures. We also demonstrated the ability to use this methodology to examine nonmarket resource values at risk on the Crazy Horse Fire.

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    Citation

    Calkin, David; Hyde, Kevin; Gebert, Krista; Jones, Greg. 2005. Comparing resource values at risk from wildfires with Forest Service fire suppression expenditures: Examples from 2003 western Montana wildfire season. Res. Note RMRS-RN-24. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 8 p.

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    Keywords

    wildfire suppression costs, break-even analysis, cost containment, cadastral data

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