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Featured researches published by James K. Brown.


Gen. Tech. Rep. INT-GTR-344. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station. 65 p. | 1997

First Order Fire Effects Model: FOFEM 4.0, user's guide

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

A First Order Fire Effects Model (FOFEM) was developed to predict the direct consequences of prescribed fire and wildfire. FOFEM computes duff and woody fuel consumption, smoke production, and fire-caused tree mortality for most forest and rangeland types in the United States. The model is available as a computer program for PC or Data General computer.Current information on FOFEM


International Journal of Wildland Fire | 2001

Modeling fire effects

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

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.


Gen. Tech. Rep. INT-16. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 24 p. | 1974

Handbook for inventorying downed woody material

James K. Brown


Res. Pap. INT-RP-197. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 56 p. | 1978

Weight and density of crowns of Rocky Mountain conifers

James K. Brown


Canadian Journal of Forest Research | 1987

Fire damage, mortality, and suckering in aspen

James K. Brown; Norbert V. DeByle


Canadian Journal of Forest Research | 1976

Estimating shrub biomass from basal stem diameters

James K. Brown


Forest Science | 1971

A Planar Intersect Method for Sampling Fuel Volume and Surface Area

James K. Brown


Forest Science | 1970

Ratios of surface area to volume for common fine fuels.

James K. Brown


International Journal of Wildland Fire | 1995

Calibration of a Large Fuel Burnout Model

Fa Albini; James K. Brown; Elizabeth D. Reinhardt; Rd Ottmar


Res. Pap. INT-RP-290. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 10 p. | 1982

Fuel and fire behavior prediction in big sagebrush

James K. Brown

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Robert E. Keane

Commonwealth Scientific and Industrial Research Organisation

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Robert E. Keane

Commonwealth Scientific and Industrial Research Organisation

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