Modeling Wildfire Incident Complexity Dynamics

Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of...

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Bibliographic Details
Published in:PloS one Vol. 8; no. 5; p. e63297
Main Author: Thompson, Matthew P.
Format: Journal Article
Language:English
Published: United States Public Library of Science 14.05.2013
Public Library of Science (PLoS)
Subjects:
Agriculture
Analysis
Chain dynamics
Complexity
Conservation of Natural Resources
Containment
Cost analysis
Costs
Decision Making
Decisions
Dynamics
Earth Sciences
Ecological effects
Economic analysis
Engineering
Environment
Environmental conditions
Expenditures
Fires
Forest management
Forests
Growth models
Likelihood Functions
Management
Markov analysis
Markov Chains
Markov processes
Modelling
Models, Statistical
Probabilistic analysis
Regional analysis
Statistical analysis
Stochasticity
Temporal variations
Web applications
Wildfires
United States > US
ISSN:1932-6203, 1932-6203
Online Access:Get full text
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Description
Summary:Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.
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Competing Interests: The author has declared that no competing interests exist.
Conceived and designed the experiments: MPT. Analyzed the data: MPT. Wrote the paper: MPT.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0063297