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The performance of wildfire suppression is often monitored using statistics related to area burned and time to contain a fire. Potential factors affecting the probability of initial attack (IA) success and the probability of large fires were examined in a data set composed of 334 Australian
wildfires that burned in forest and shrubland vegetation and used aerial- and tanker-based suppression during the IA phase. Logistic regression analysis was used to determine the most significant predictor variables for a range of area- and time-based definitions for these measures. The variables
that were found to be the best predictors of IA success were fire area at IA, fuel hazard, and aircraft response time. The probability of large fires was related to fuel hazard, area at IA, and the Forest Fire Danger Index. Fire area at IA was strongly linked with aerial suppression time delay
and was also influenced by weather and fuel hazard score. Fire management practices can influence IA area, response timing, and fuel hazard. IA area and response times can be minimized through efficient fire detection and by deploying appropriate suppression resources rapidly from bases in
locations that provide optimized geographical coverage. Fuel hazard can be moderated through management actions such as fuel reduction burning.
Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.