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Modeling fire effects

Authors: Elizabeth D. Reinhardt; Robert E. Keane; James K. Brown;

Modeling fire effects

Abstract

This paper was presented at the conference ‘Integrating spatial technologies and ecological principles for a new age in fire management’, Boise, Idaho, USA, June 1999 Fire effects are modeled for a variety of reasons including: to evaluate risk, to develop treatment prescriptions, to compare management options, and to understand ecosystems. Fire effects modeling may be conducted at a range of temporal and spatial scales. First-order fire effects are those that are the direct result of the combustion process such as plant injury and death, fuel consumption and smoke production. Modeling these effects provides an important cornerstone for models that operate at larger spatial and temporal scales. Detailed physical models of heat transfer and the combustion process under development should provide a vehicle for quantifying fire treatment and predicting fire effects. Second-order fire effects are indirect consequences of fire and other post-fire interactions such as weather. They may take place a few hours to many decades after a fire. Some important second-order fire effects are smoke dispersion, erosion, and vegetation succession. Many approaches have been used to model fire effects including empirical, mechanistic, stochastic, and combinations of all three. Selection of the appropriate model approach and scale depends on the objectives of the modeler, as well as the quality and quantity of available data. This paper is not meant to provide an exhaustive review of fire effects models. Instead, it presents a background in approaches to modeling fire effects to provide managers a basis for selecting and interpreting simulation tools.

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    influence
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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
63
Top 10%
Top 10%
Top 10%
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