Estimating visitor preferences for recreation sites in wildfire prone areas
Sophia Tanner A * , Frank Lupi B and Cloé Garnache C
+ Author Affiliations
- Author Affiliations
A U.S. Department of Agriculture, 805 Pennsylvania Avenue, Kansas City, MO, USA.
B Department of Agricultural, Food, and Resource Economics, Michigan State University, 446 W. Circle Drive Rm. 202, East Lansing, MI, USA.
C Department of Economics, University of Oslo, Postboks 1095 Blindern N-0317, Oslo, Norway.
* Correspondence to: sophia.tanner@usda.gov
International Journal of Wildland Fire 31(9) 871-885 https://doi.org/10.1071/WF21133
Submitted: 2 October 2021 Accepted: 20 July 2022 Published: 30 August 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Development into the wildland–urban interface, combined with heat and drought, contribute to increasing wildfires in the U.S. West and a range of damages including recreation site closures and longer-term effects on recreation areas. A choice experiment survey is used to estimate visitor preferences for vegetation and the effects of past fire at recreation sites. Intercept interviews are used to randomly select visitors at national forest sites near Los Angeles. The choice model results reveal that recreation sites with waterbodies and sites with tree cover, instead of shrubs or barren areas, are highly desirable, while evidence of past fires decreases the value of a site. We find the effects of past fire depend on vegetation type, fire intensity and time since the fire ended. Older forest fires and shrub fires are undesirable, but forest fires that reach the crowns of trees are least desirable. The findings add to evidence that fire damage to recreation areas extends beyond closures and depends on vegetation, which can inform the allocation of firefighting and prevention resources.
Keywords: choice experiment, random parameter logit model, stated preference, survey.
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