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First Order Fire Effects Model (FOFEM)

Overview & Applicability

First order fire effects are the immediate consequences of a fire, whether direct or indirect. The FOFEM tool is designed to calculate these consequences for prescribed fire or wildfire using four separate metrics: tree mortality, fuel consumption, emissions or smoke production, and soil heating. This tool is intended for direct use in assessing fire impacts and severity, planning prescribed fires that accomplish resource needs, and other applications. The model can be run in either 'prediction' or 'planning' mode; the first computes expected fire effects, the second generates a range of conditions that may lead to a specified set of desired effects. The tool is national in scope, dividing the U.S. into four separate regions.


FOFEM can help determine tree mortality as a result of fire.FOFEM: FOFEM can help determine tree mortality as a result of fire.

History

The first version of FOFEM was developed in the late 1980's for use on the Forest Service Data General computer platform. Since then it has gone through several update cycles. FOFEM 4.0 was the first version developed for the PC Windows environment and was released in the mid 1990's. The most recent version of this tool, FOFEM 6, was released in 2013, and contains an improved user interface compared to previous versions.

Inputs and outputs

The specific inputs needed vary according to which of the four outputs the user wishes to generate. Default values are provided for most of the necessary parameters, although users are free to customize values using their own data.

To determine fuel consumption, emissions, and soil heating, the inputs required and the outputs generated are similar. These include:

Inputs

  • geographical region cover classification
  • system and cover type, season of burn and general burning conditions
  • fuel type, fuel loading by size class, fuel moisture for some size classes, duff depth and type of duff moisture
  • percentage of crown burned
  • soil heating only: soil texture and soil moisture percentage

Outputs

  • preburn loading, consumed loading, postburn loading
  • percentage reduction, duff depth consumed, and percentage of mineral soil exposure
  • emissions only: CO2, CO, CH4, SO2, NOx, PM2.5 and PM10 from flaming and smoldering combustion , total consumption in flaming and smoldering combustion and duration of flaming and smoldering combustion
  • soil heating only: soil layer maximum temperatures and duration of heating at at 0 to 13 cm depth by 1cm increments, maximum depth reaching 60°C, and maximum depth reaching 275°C.

To examine tree mortality, the input parameters include:

  • geographical region
  • general burning conditions
  • density, d.b.h., tree height, crown ratio and flame length or scorch height for each species and d.b.h. class species

Tree mortality outputs are generated as the percentage of tree mortality by species and size class, and pre- and postfire canopy cover.

Restrictions and limitations

FOFEM is a point model which means that it predicts fuel consumption and smoke emissions for a point on the landscape/stand (about 1-5 m2). The extrapolation of that point measurement upwards in scale is at the discretion of the user. Fuel and moisture conditions across a stand and landscape are notoriously variable so one point estimate for large areas can introduce bias into the predictions. The appropriate scaling up of FOFEM predictions is the most important consideration in using the model. Another important consideration is the accurate measurement of the inputs that go into FOFEM, namely fuel loadings and fuel moistures. The more accurate the measurements are, the more realistic the predictions. Users should also keep in mind that the default values provided in FOFEM are based on literature but may not accurately reflect local conditions. Areas where fire effects research is limited or where fires are infrequent may be particularly subject to error.

Accessing the tool and additional information.

The model itself, plus a tool overview and self-guided tutorials are available at the following website: www.firelab.org/project/fofem

A published overview of First Order Fire Effects models, including FOFEM: http://www.treesearch.fs.fed.us/pubs/35017

A User's Guide for FOFEM 4.0, written as a General Technical Report
http://www.treesearch.fs.fed.us/pubs/25257

* Part of this information has been modified from:
Peterson, David L.; Evers, Louisa; Gravenmier, Rebecca A.; Eberhardt, Ellen. 2007. A consumer guide: tools to manage vegetation and fuels. Gen. Tech. Rep. PNW-GTR-690. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 151 p.

Fast Facts

Website

www.firelab.org/project/fofem

Purpose

FOFEM is a model that predicts first-order fire effects including tree mortality, fuel consumption, emissions (smoke) production, and soil heating caused by prescribed burning or wildfire. Estimated emissions are included for CO2, CO, CH4, SO2, NOx, PM2.5 and PM10.

Output

Graphs and tabular reports describing the four parameters listed above (tree mortality, consumption, emissions, and soil heating).

Developed by

USDA Forest Service, R&D and Rocky Mountain Research Station with support from the Joint Fire Science Program. For a full list of credits see the project page.

Format

Downloadable software that will run on most Windows platforms.

Geography

United States

Scale (range)

Forest stands to small watersheds

Training Requirement

2 (on a scale of 1-3). Moderate time investment (<1 week).

Status

Development is ongoing; improvements are released in new versions of the tool.

Potential Applications

Wildfire impact assessments, design of fire prescriptions, fire management planning.

Caveats, Restrictions

The appropriate scaling up of FOFEM predictions is the most important consideration in using the model. Extrapolating one point estimate to a large area can introduce significant bias into the predictions. Another important consideration is the accurate measurement of the inputs that go into FOFEM, namely fuel loadings and fuel moistures. The more accurate the measurements the more realistic the predictions.