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International Journal of Wildland Fire International Journal of Wildland Fire Society
Journal of the International Association of Wildland Fire
RESEARCH ARTICLE

Effect of fire prevention programs on accidental and incendiary wildfires on tribal lands in the United States

Karen L. Abt A D , David T. Butry B , Jeffrey P. Prestemon A and Samuel Scranton C
+ Author Affiliations
- Author Affiliations

A USDA Forest Service, Southern Research Station, PO Box 12254, Research Triangle Park, NC 27709, USA.

B National Institute of Standards and Technology, 100 Bureau Drive, Gaithersburg, MD 20899, USA.

C Bureau of Indian Affairs – National Interagency Fire Center, 3833 South Development Avenue, Boise, ID 83705, USA.

D Corresponding author. Email: kabt@fs.fed.us

International Journal of Wildland Fire 24(6) 749-762 https://doi.org/10.1071/WF14168
Submitted: 16 September 2014  Accepted: 16 March 2015   Published: 4 June 2015

Abstract

Humans cause more than 55% of wildfires on lands managed by the USDA Forest Service and US Department of the Interior, contributing to both suppression expenditures and damages. One means to reduce the expenditures and damages associated with these wildfires is through fire prevention activities, which can include burn permits, public service programs or announcements, outreach efforts to schools, youth groups and equipment operators, and law enforcement. Using data from 17 US Bureau of Indian Affairs tribal units, we modelled the effect of prevention programs and law enforcement on the number of human-caused ignitions. We also included weather and lagged burned area in our estimation of fixed-effects count models. The results show that prevention activities led to significant reductions in wildfires caused by escaped campfires, juveniles, fire-use (e.g. escaped debris burns) and equipment. Increased law enforcement resulted in fewer incendiary- and equipment-caused wildfires. Using average suppression expenditures by wildfire and our estimate of avoided wildfires per additional year of prevention, we estimate partial benefit–cost ratios of greater than 4.5 for all Bureau of Indian Affairs regions for the continuation of the prevention program.

Additional keywords: arson wildfires, instrumental variables methods, intervention analysis, law enforcement, wildfire suppression.


References

Butry DT, Prestemon JP (2005) Spatiotemporal wildland arson crime functions. Paper presented at the Annual Meeting of the American Agricultural Economics Association, 24–27 July 2005, Providence, RI. Available at http://purl.umn.edu/19197 [Verified 29 May 2014].

Butry DT, Prestemon JP, Abt KL, Sutphen R (2010) Economic optimisation of wildfire intervention activities. International Journal of Wildland Fire 19, 659–672.
Economic optimisation of wildfire intervention activities.Crossref | GoogleScholarGoogle Scholar |

Calef MP, McGuire AD, Chapin FS (2008) Human influences on wildfire in Alaska from 1988 through 2005: an analysis of the spatial patterns of human impacts. Earth Interactions 12, 1–17.
Human influences on wildfire in Alaska from 1988 through 2005: an analysis of the spatial patterns of human impacts.Crossref | GoogleScholarGoogle Scholar |

Cardille JA, Ventura SJ, Turner MG (2001) Environmental and social factors influencing wildfires in the upper Midwest, United States. Ecological Applications 11, 111–127.
Environmental and social factors influencing wildfires in the upper Midwest, United States.Crossref | GoogleScholarGoogle Scholar |

Donoghue LR, Main WA (1985) Some factors influencing wildfire occurrence and measurement of fire prevention effectiveness. Journal of Environmental Management 20, 87–96.

Garcia CV, Woodard PM, Titus SJ, Adamowicz WL, Lee BS (1995) A logit model for predicting daily occurrence of human caused forest fires. International Journal of Wildland Fire 5, 101–111.
A logit model for predicting daily occurrence of human caused forest fires.Crossref | GoogleScholarGoogle Scholar |

Goodrick SL (2002) Modification of the Fosberg fire weather index to include drought. International Journal of Wildland Fire 11, 205–221.
Modification of the Fosberg fire weather index to include drought.Crossref | GoogleScholarGoogle Scholar |

Haines DA, Main WA, Frost JS, Simard AJ (1983) Fire-danger rating and wildfire occurrence in the north-eastern United States. Forest Science 29, 679–696.

Keetch JJ, Byram GM (1968) A drought index for forest fire control. USDA Forest Service, Southeastern Forest Experiment Station, Research Paper SE-38. (Asheville, NC)

Martell DL, Otukol S, Stocks BJ (1987) A logistic model for predicting daily people-caused forest fire occurrence in Ontario. Canadian Journal of Forest Research 17, 394–401.
A logistic model for predicting daily people-caused forest fire occurrence in Ontario.Crossref | GoogleScholarGoogle Scholar |

Mercer DE, Prestemon JP, Butry DT, Pye JM (2007) Evaluating alternative prescribed burning policies to reduce net economic damages from wildfire. American Journal of Agricultural Economics 89, 63–77.
Evaluating alternative prescribed burning policies to reduce net economic damages from wildfire.Crossref | GoogleScholarGoogle Scholar |

National Wildfire Coordinating Group (2012) National fire and aviation management web applications: fire and weather data. Available at http://fam.nwcg.gov/fam-web/weatherfirecd/ [Verified 23 July 2014]

Preisler HK, Brillinger DR, Burgan RE, Benoit JW (2004) Probability based models for estimation of wildfire risk. International Journal of Wildland Fire 13, 133–142.
Probability based models for estimation of wildfire risk.Crossref | GoogleScholarGoogle Scholar |

Preisler HK, Chen SC, Fujioka F, Benoit JW, Westerling AL (2008) Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices. International Journal of Wildland Fire 17, 305–316.
Wildland fire probabilities estimated from weather model-deduced monthly mean fire danger indices.Crossref | GoogleScholarGoogle Scholar |

Prestemon JP, Butry DT (2005) Time to burn: modeling wildland arson as an autoregressive crime function. American Journal of Agricultural Economics 87, 756–770.
Time to burn: modeling wildland arson as an autoregressive crime function.Crossref | GoogleScholarGoogle Scholar |

Prestemon JP, Pye JM, Butry DT, Holmes TP, Mercer DE (2002) Understanding broad-scale wildfire risks in a human-dominated landscape. Forest Science 48, 685–693.

Prestemon JP, Butry DT, Abt KL, Sutphen R (2010) Net benefits of wildfire prevention education efforts. Forest Science 56, 181–192.

Prestemon JP, Chas-Amil ML, Touza JM, Goodrick SL (2012) Forecasting intentional wildfires using temporal and spatiotemporal autocorrelations. International Journal of Wildland Fire 21, 743–754.
Forecasting intentional wildfires using temporal and spatiotemporal autocorrelations.Crossref | GoogleScholarGoogle Scholar |

Prestemon JP, Hawbaker TJ, Bowden M, Carpenter J, Brooks MT, Abt KL, Sutphen R, Scranton S (2013) Wildfire ignitions: a review of the science and recommendations for empirical modeling. USDA Forest Service, Southern Research Station, General Technical Report SRS-171. (Asheville, NC)

Syphard AD, Radeloff VC, Keeley JE, Hawbaker TJ, Clayton MK, Stewart SI, Hammer RB (2007) Human influence on California fire regimes. Ecological Applications 17, 1388–1402.
Human influence on California fire regimes.Crossref | GoogleScholarGoogle Scholar | 17708216PubMed |

Thomas DS, Butry DT, Prestemon JP (2011) Enticing arsonists with broken windows and social disorder. Fire Technology 47, 255–273.
Enticing arsonists with broken windows and social disorder.Crossref | GoogleScholarGoogle Scholar |

Thomas DS, Butry DT, Prestemon JP (2012) Social disorder, accidents, and municipal wildfires. In ‘Proceedings of the 3rd Human Dimensions of Wildland Fire’, 17–19 April 2012, Seattle, WA. Available at http://www.iawfonline.org/pdf/3rd%20Human%20Dimensions%20Conference%20Proceedings%20-%20FINAL.pdf [Verified 23 July 2014]

US Department of Justice (1998) Directory of law enforcement agencies, 1996. (US Department of Commerce, Bureau of the Census. Interuniversity Consortium for Political and Social Research: Ann Arbor, MI)10.3886/ICPSR02260.V1

US Department of Justice (2009) Census of state and local law enforcement agencies, 2000. ICPSR03484-v4. Bureau of Justice Statistics (Interuniversity Consortium for Political and Social Research: Ann Arbor, MI) Released 8 July 200910.3886/ICPSR03484.V4

US Department of Justice (2011a) Census of state and local law enforcement agencies, 2004. ICPSR28001-v1. Office of Justice Programs, Bureau of Justice Statistics. (Interuniversity Consortium for Political and Social Research: Ann Arbor, MI) Released 23 May 201110.3886/ICPSR28001.V1

US Department of Justice (2011b) Census of state and local law enforcement agencies, 2008. ICPSR27681-v1. Office of Justice Programs, Bureau of Justice Statistics. (Interuniversity Consortium for Political and Social Research: Ann Arbor, MI) Released 3 August 201110.3886/ICPSR27681.V1

Vilar L, Woolford DG, Martell DL, Martin MP (2010) A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain. International Journal of Wildland Fire 19, 325–337.
A model for predicting human-caused wildfire occurrence in the region of Madrid, Spain.Crossref | GoogleScholarGoogle Scholar |

Yakama Nation (2015) Yakama nation fire prevention. Available at http://www.yakamanationfire.com/prevention-yakama-nation-fire-management.php [Verified 15 January 2015]

Yang J, He HS, Shifley SR, Gustafson EJ (2007) Spatial patterns of modern period human-caused fire occurrence in the Missouri Ozark Highlands. Forest Science 53, 1–15.