First-Order Fire Effects Models for Land Management: Overview and Issues
Open accessAbstract
We give an overview of the science application process at work in supporting fire management. First-order fire effects models, such as those discussed in accompanying papers, are the building blocks of software systems designed for application to landscapes over time scales from days to centuries. Fire effects may be modeled using empirical, rule based, or process approaches. Fire effects software systems can be used to conduct risk assessments, develop prescriptions for fuel treatments or prescribed fire, or support long-term planning. A brief review of the software systems available and the fire effects models on which they are based is presented. We consider the future of software systems for fire management and, given gaps in fire effects modeling capabilities, how to strengthen their foundation.
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In California, statewide wildfire estimates of CO2 and PM are based on FOFEM, though reports of CH4 estimates from wildfires are lacking.
“In California, statewide wildfire estimates of CO 2 and PM are based on the USA Forest Service's First Order Fire Effects Model (FOFEM; Reinhardt and Dickinson, 2010), though reports of CH 4 estimates from wildfires are lacking, despite the importance of CH 4 for meeting the state's ambitious climate goals.”
From Ground solar absorption observations of total column CO, CO <sub>2</sub> , CH <sub>4</sub> , and aerosol optical depth from California's Sequoia Lightning Complex Fire: emission factors and modified combustion efficiency at regional scales (2023) · cites this paper as Reinhardt and Dickinson, 2010
The Conclusions table identifies FOFEM as a system used for smoke-production modeling, supporting the identification of the model. The paper does not say that California’s statewide CO2 and PM wildfire estimates are based on FOFEM, or that reports of wildfire CH4 estimates are lacking (searched: California statewide estimates, CO2, PM, and CH4). (LLM, conf=0.82)
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Research works printed but not linked: 20
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- Campbell, G.S., J.D. Jungbauer Jr., K.L. Bristow, and R.D. Hungerford. 1995. Soil tempera- ture and water content beneath a surface fire. Soil Science 159: 363-374. doi: 10.1097/00010694-199506000-00001 · DOI
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- Jones, J.L., B.W. Webb, B.W. Butler, M.B. Dickinson, D. Jimenez, J. Reardon, and A.S. Bova. 2006. Prediction and measurement of thermally induced cambial tissue necrosis in tree stems. International Journal of Wildland Fire 15: 3-17. doi: 10.1071/WF05017 · DOI
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Cited by
Sorted by citations
Probabilistic assessment of wildfire hazard and municipal watershed exposure
Scott, J., Helmbrecht, D., Thompson, M. P., Calkin, D. E., & Marcille, K. (2012) · Natural Hazards · doi:10.1007/s11069-012-0265-7 · Cited by 66 · see citing works
Frausto-Vicencio, I., Heerah, S., Meyer, A. G., Parker, H. A., Dubey, M., & Hopkins, F. M. (2023) · Atmospheric Chemistry and Physics · doi:10.5194/acp-23-4521-2023 · Cited by 10 · see citing works
“In California, statewide wildfire estimates of CO2 and PM are based on the USA Forest Service’s First Order Fire Effects Model (FOFEM; Reinhardt and Dickinson, 2010), though reports of CH4 estimates from wildfires are lacking, despite the importance of CH4 for meeting the state’s ambitious climate goals.”
- Authors
- Reinhardt, E. D., & Dickinson, M. B.
- Affiliations
- US Forest Service (US)
- Corresponding author
- Reinhardt, Elizabeth D.
- Venue
- Fire Ecology
- Published
- 2010-04
- Volume
- 6
- Issue
- 1
- Pages
- 131-142
- ISSN
- 1933-9747 (ISSN-L)
- OpenAlex
- W2166976519
- Cited by
- 62
- References
- 0
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2023: 4 · 2022: 5 · 2021: 1 · 2020: 5 · 2019: 4 · 2018: 5 · 2017: 4 · 2016: 3 · 2015: 1 · 2014: 5 · 2013: 5 · 2012: 9
- FWCI
- 5.48
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Fire Ecology (publishedVersion, cc-by)
- Topics
- Physical Sciences › Environmental Science › Global and Planetary Change › Fire effects on ecosystems
- Physical Sciences › Environmental Science › Ecology › Rangeland and Wildlife Management
- Physical Sciences › Environmental Science › Global and Planetary Change › Forest Management and Policy
- Keywords
- fire management, land management, prescribed burning, fuel treatment, risk assessment, long-term planning, empirical model, rule-based models, mechanistic model
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