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

The influence of incident management teams on the deployment of wildfire suppression resources

Michael Hand A C , Hari Katuwal B , David E. Calkin A and Matthew P. Thompson A
+ Author Affiliations
- Author Affiliations

A US Department of Agriculture Forest Service,Rocky Mountain Research Station, 800 East Beckwith Avenue, Missoula, MT 59801, USA.

B University of Montana, 32 Campus Drive, Missoula, MT 59812, USA.

C Corresponding author. Email: mshand@fs.fed.us

International Journal of Wildland Fire 26(7) 615-629 https://doi.org/10.1071/WF16126
Submitted: 14 July 2016  Accepted: 24 February 2017   Published: 26 April 2017

Abstract

Despite large commitments of personnel and equipment to wildfire suppression, relatively little is known about the factors that affect how many resources are ordered and assigned to wildfire incidents and the variation in resources across incident management teams (IMTs). Using detailed data on suppression resource assignments for IMTs managing the highest complexity wildfire incidents (Type 1 and Type 2), this paper examines daily suppression resource use and estimates the variation in resource use between IMTs. Results suggest that after controlling for fire and landscape characteristics, and for higher average resource use on fires in California, differences between IMTs account for ~14% of variation in resource use. Of the 89 IMTs that managed fires from 2007 to 2011, 17 teams exhibited daily resource capacity that was significantly higher than resource use for the median team.

Additional keywords: fixed effects, resource demand, suppression effort.


References

Broyles G (2011) Fireline production rate. USDA Forest Service, National Technology and Development Program, Fire Management Report 1151–1805. (San Dimas, CA).

Butry DT, Gumpertz M, Genton MG (2008) The production of large and small wildfires. In ‘The economics of forest disturbances: wildfires, storms, and invasive species’. (Eds TP Holmes, JP Prestemon, KL Abt) pp. 79–106. (Springer: Dordrecht, Netherlands)

Calkin DE, Venn T, Wibbenmeyer M, Thompson MP (2013) Estimating US federal wildland fire managers’ preferences toward competing strategic suppression objectives. International Journal of Wildland Fire 22, 212–222.
Estimating US federal wildland fire managers’ preferences toward competing strategic suppression objectives.CrossRef | open url image1

Canton-Thompson J, Gebert KM, Thompson B, Jones G, Calkin D, Donovan G (2008) External human factors in incident management team decision-making and their effect on large fire suppression expenditures. Journal of Forestry 106, 416–424.

Donovan GH, Brown TC (2005) An alternative incentive structure for wildfire management on national forest land. Forest Science 51, 387–395.

Donovan GH, Noordijk P, Radeloff V (2004) Estimating the impact of proximity of houses on wildfire suppression costs in Oregon and Washington. In ‘2nd symposium on fire economics and policy: a global view’, 19–22 April 2004, Cordoba, Spain. (Ed. A González-Cabán) USDA Forest Service, Pacific Southwest Research Station, General Technical Report PSW-GTR-208, pp. 19–22. (Albany, CA)

Donovan GH, Prestemon JP, Gebert K (2011) The effect of newspaper coverage and political pressure on wildfire suppression costs. Society & Natural Resources 24, 785–798.
The effect of newspaper coverage and political pressure on wildfire suppression costs.CrossRef | open url image1

Finney M, Grenfell IC, McHugh CW (2009) Modeling containment of large wildfires using generalized linear mixed-model analysis. Forest Science 55, 249–255.

Gebert KM, Black AE (2012) Effect of suppression strategies on federal wildland fire expenditures. Journal of Forestry 110, 65–73.
Effect of suppression strategies on federal wildland fire expenditures.CrossRef | open url image1

Gebert KM, Calkin DE, Yoder J (2007) Estimating suppression expenditures for individual large wildland fires. Western Journal of Applied Forestry 22, 188–196.

González-Cabán A (1997) Managerial and institutional factors affect prescribed burning costs. Forest Science 43, 535–543.

Hand MS, Gebert KM, Liang J, Calkin DE, Thompson MP, Zhou M (2014a) Modeling fire expenditures with spatially descriptive data. In ‘Economics of wildfire management’. (Eds MS Hand, KM Gebert, J Liang, DE Calkin, MP Thompson, M Zhou) pp. 37–48. (Springer: New York)

Hand MS, Gebert KM, Liang J, Calkin DE, Thompson MP, Zhou M (2014b) Regional and temporal trends in wildfire suppression expenditures. In ‘Economics of wildfire management’. (Eds MS Hand, KM Gebert, J Liang, DE Calkin, MP Thompson, M Zhou) pp. 19–35. (Springer)

Hand MS, Wibbenmeyer MJ, Calkin DE, Thompson MP (2015) Risk preferences, probability weighting, and strategy trade-offs in wildfire management. Risk Analysis 35, 1876–1891.
Risk preferences, probability weighting, and strategy trade-offs in wildfire management.CrossRef | open url image1

Holmes TP, Calkin DE (2013) Econometric analysis of fire suppression production functions for large wildland fires. International Journal of Wildland Fire 22, 246–255.
Econometric analysis of fire suppression production functions for large wildland fires.CrossRef | open url image1

Hsiao C (2014) ‘Analysis of panel data.’ (Cambridge University Press: Cambridge, UK)

Katuwal H, Calkin DE, Hand MS (2016) Production and efficiency of large wildland fire suppression effort: a stochastic frontier analysis. Journal of Environmental Management 166, 227–236.
Production and efficiency of large wildland fire suppression effort: a stochastic frontier analysis.CrossRef | open url image1

Liang J, Calkin DE, Gebert KM, Venn TJ, Silverstein RP (2008) Factors influencing large wildland fire suppression expenditures. International Journal of Wildland Fire 17, 650–659.
Factors influencing large wildland fire suppression expenditures.CrossRef | open url image1

MacGregor DG, González-Cabán A (2008) Decision modeling for analyzing fire action outcomes. USDA Forest Service, Southwest Pacific Research Station, Research Paper PSW-RP-258. (Albany, CA)

Maguire LA, Albright EA (2005) Can behavioral decision theory explain risk-averse fire management decisions? Forest Ecology and Management 211, 47–58.
Can behavioral decision theory explain risk-averse fire management decisions?CrossRef | open url image1

Thompson MP (2014) Social, institutional, and psychological factors affecting wildfire incident decision making. Society & Natural Resources 27, 636–644.
Social, institutional, and psychological factors affecting wildfire incident decision making.CrossRef | open url image1

Thompson MP, Freeborn P, Rieck JD, Calkin DE, Gilbertson-Day JW, Cochrane MA, Hand MS (2016) Quantifying the influence of previously burned areas on suppression effectiveness and avoided exposure: a case study of the Las Conchas Fire. International Journal of Wildland Fire 25, 167–181.
Quantifying the influence of previously burned areas on suppression effectiveness and avoided exposure: a case study of the Las Conchas Fire.CrossRef | open url image1

US Census Bureau (2011) 2010 census demographic profile summary file. Machine-readable data files. (US Department of Commerce: Washington, DC)

Wibbenmeyer MJ, Hand MS, Calkin DE, Venn TJ, Thompson MP (2013) Risk preferences in strategic wildfire decision-making: a choice experiment with US wildfire managers. Risk Analysis 33, 1021–1037.
Risk preferences in strategic wildfire decision-making: a choice experiment with US wildfire managers.CrossRef | open url image1

Wilson RS, Winter PL, Maguire LA, Ascher T (2011) Managing wildfire events: risk-based decision-making among a group of federal fire managers. Risk Analysis 31, 805–818.
Managing wildfire events: risk-based decision-making among a group of federal fire managers.CrossRef | open url image1

Wooldridge JM (2010) ‘Econometric analysis of cross section and panel data.’ (MIT Press: Cambridge, MA)

Yoder J, Gebert K (2012) An econometric model for ex ante prediction of wildfire suppression costs. Journal of Forest Economics 18, 76–89.
An econometric model for ex ante prediction of wildfire suppression costs.CrossRef | open url image1



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