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Severity & Spread

Threat of fire severity and spread is better understood by using prediction models and other risk assessment tools. One of the initial attempts to implement a more generic assessment of fire risk was the National Fire Danger Rating System (Burgan 1988, Deeming and others 1972 ). This system relied on expert judgment to evaluate the risk from a set of explanatory variables, principally fuels, topography, and weather. Prediction of fire occurrence is just the first part of a complete analysis of fire risk. Fire occurrence risk must be combined with models that determine the risk of the effects of fire.

The severity and spread of wildland fire is key in understanding its threat to forest health. This section reviews many of the models created to help us better manage fire through biophysical principles, probability-based predictions, as well as the effects of vegetation changes on fire behavior. Modeling fire proves to have great promise predicting and managing fire risks. Further, goals to assess ecological risks in the context of fuel loading, which can lead to uncharacteristically severe wildlfire, has shifted fire management to being a proactive rather than reactive practice. Risk management decisions rely on a mix of science and policy; the most important role for science is providing information to be used in environmental decision making (Power and McCarty 1997). Studying fire severity and spread has led to several policy changes recently, including the Healthy Forests Initiative, and may someday shift the scales from fire as a threat to fire a tool in forest management in many ecosystems.


To further review fire severity and spread, consider reading the following Environmental Threats Case Studies:

Digital Aerial Sketchmapping and Downlink Communications: A New Tool for Fire Managers

Assessing Risks to Multiple Resources Affected by Wildfire and Forest Management Using an Integrated Probabilistic Framework

Evaluating Wildland Fire Danger and Prioritizing Vegetation and Fuels Treatments


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Encyclopedia ID: p3280



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