Fuels & Fuel Treatments
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This virtual- and field-based training was developed and hosted by the Oak Woodlands & Forests Fire Consortium, Lake States Fire Science Consortium, and the Huron-Manistee National Forests. The virtual event was held June 1-4, 2021, and introduced participants to:
- tools for selecting metrics that match management/restoration objectives;
- developing site-specific protocols for sampling;
- developing a monitoring handbook and monitoring protocols/program for your local ecosystems;
- how to establish long-term monitoring and quantitative/qualitative data for wildfire risk assessment;
- evaluating the need for prescribed burns and other fuels treatments.
Webinar recording.
The Center for Ecosystem Climate Solutions (CECS), with support from California’s Strategic Growth Council (SGC), built a data cube of California forest conditions for 1985 to 2023. These data include state-wide, 30-m information on ecosystem disturbance, carbon, water, and fire hazard. These data are being tested against field observations with support from CALFIRE, and an updated 2024 dataset is nearing release. This presentation will introduce the data cube and use it to quantify recent changes in California’s wildlands.
Mike Goulden is a Professor of Earth System Science (ESS) at UC Irvine. Goulden’s research focuses on Ecosystem ecology, and the Biological, physical, and chemical controls on terrestrial carbon and water cycling. Goulden has conducted extensive fieldwork on carbon exchange in tropical, boreal and temperate ecosystems. Goulden’s more recent work emphasizes satellite-based mapping of ecosystem conditions and function.
The Forest Health Research Program is part of California Climate Investments, a statewide initiative that puts billions of Cap-and-Trade dollars to work reducing greenhouse gas emissions, strengthening the economy, and improving public health and the environment — particularly in disadvantaged communities.
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We quantified active management and wildfire severity across yellow pine and mixed conifer (YPMC) forests in the Sierra Nevada of California over a 22-year period (2001–2022). We did not detect increases in the area treated through time, but the area of beneficial wildfire (low to moderate severity) increased substantially, exceeding active treatment area in 8 of 22 years. Overall, beneficial wildfire treated ~17% more area than all treatments combined, and roughly four times more area than fire-related treatments alone. We then used disturbance history to evaluate resistance to high-severity wildfire and forest loss across the YPMC range. Of the 2.3 million ha YPMC of forests in 2001, 20% lost mature forests due to high-severity fire by 2022, which is nearly half of all YPMC area burned. Most of the landscape (47%) remains at risk of high-severity fire because it had no restorative disturbances, but 33% of the study area has some level of resistance to high-severity wildfire. In these areas, resistance will need to be enhanced and maintained over time via active management or managed wildfire, but these treatment needs will likely outpace capacity even under optimistic implementation scenarios. Given limited resources for implementing active management and the likelihood of a more fiery future, incorporating beneficial wildfire into landscape-level treatment planning has the potential to amplify the impact of active management treatments.
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This paper does three things: (1) Identifies features correlated with structure loss. (2) Compares methods of characterizing structure susceptibility, including home assessments and emerging fire spread models. (3) Evaluates methods and open data sources used to measure these features. We find that relative feature importance varies widely among studies due to data limitations and scale issues. Built-environment fire spread models show limited inclusion of structure-level features. Additional research, model validation, improved data, and improved data collection methods are needed to bridge the gaps between primary research, susceptibility indices, and built-environment fire spread models. Advancing scalable methods for characterizing built-environment fuels and susceptibility will refine risk mitigation efforts globally.
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In a collaborative effort with Dixie National Forest, Sarah Barga, a research botanist with the Rocky Mountain Research Station, outlines a project focused on building ecosystem resilience and resistance in Utah’s Pine Valley Ranger District. A team of specialists from the National Forest system, Utah State University, and Rocky Mountain Research station are examining the roles of invasive species, local vegetation, and fire history in managing this key landscape. The project launched in 2024 with initial ground truthing surveys to build out localized strategies to support the recovery of native understory plants resistant to invasives like cheatgrass and resilient to wildfire. The work underscores the significance of adapting efforts at the local level and the role of partnerships in integrating knowledge into future planning for improved management outcomes.
Webinar recording.
Learn about new geospatial data products to support wildfire planning and response including national fuel treatments, fire response districts and communities mapping.
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Using random forest modeling and Shapley local importance measures, we found that weather and fuels were both dominant drivers of fire severity, and past fuel treatments were successful at reducing severity—even during extreme fire progression days. First-entry fires were more typically driven by top-down climate and weather variables, while for reburns (i.e., overlapping fire footprints within the period of record), severity was largely mitigated by reduced fuels and a positive influence of topography (e.g., burning downslope). Likewise, reburns overall exhibited lower fire severity than first entry fires, suggesting strong negative feedbacks associated with past fire footprints. The normalized difference moisture index (NDMI)—an indicator of live fuel loading and moisture levels—was a leading predictor of fire severity for both first-entry fires and reburns. NDMI values < 0 (i.e., low biomass) were associated with reduced fire severity, while values > 0.25 (i.e., high biomass) were associated with increased severity. Forest management was effective across a variety of conditions, especially under low to moderate wind speeds (< 17 m·s−1), and where canopy base heights were ≥ 1.3 m.
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Data-driven decision support can help guide sustainable grazing management by providing an accurate estimate of grazing capacity, in coproduction with managers. Here, we described the development of a decision support model to estimate grazing capacity and illustrated its application on two sites in the western United States. For the Montgomery PassWild Horse Territory in California and Nevada, the upper limit estimated in the capacity assessment was 398 horses and the current population was 654 horses. For the Eagle Creek watershed of the Apache-Sitgreaves National Forest of eastern Arizona, the lower end of capacity was estimated at 1560 cattle annually, compared to the current average of 1090 cattle annually. In addition to being spatio-temporally comprehensive, the model provides a repeatable, cost-effective, and transparent process for establishing and adjusting capacity estimates and associated grazing plans that are supported by scientific information, in order to support livestock numbers at levels that are sustainable over time, including levels that are below average forage production during drought conditions. This modeling process acts as a decision support tool because it enables different assumptions to be used and explored to accommodate multiple viewpoints during the planning process.
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Through interviews with wildland fire and forest managers (e.g., Incident Commanders, Agency Administrators, Fire Management Officers, and Fuels Planners) on seven western wildfire incidents during 2020 and 2021, we investigated how forest fuel treatments were utilized during firefighting. We found that treatments were considered and used during incidents in various ways, including to conduct burnouts, for direct modification of fire behavior, as access points for firefighters or equipment, or as components of contingency plans. Most interviewees said treatments provided additional options and flexibility in decision-making, enhancing both firefighter and community safety. For instance, treatments were used to reduce overhead hazards to firefighters and, in some cases, were prepared to serve as safety zones.
Reliability of satellite-based vegetation maps for planning wildfire-fuel treatments in shrub steppe
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We compared commonly used, publicly available vegetation cover and fuels maps, specifically the Rangeland Analysis Platform (RAP) and LANDFIRE, with field-based assessments at two U.S. National Parks dominated by sagebrush steppe: City of Rocks National Reserve and Craters of the Moon National Monument and Preserve. Plant-community composition and fuels measured at ∼1700 field locations spanning ∼300,000 ha revealed that 1) RAP generally underestimated each vegetation cover type where the cover was actually abundant, and conversely overestimated cover types where they were actually scarce, and 2) there was considerable disagreement in fuel-bed maps derived from LANDFIRE compared to field observations. As a result, there were substantial discrepancies in the spatial patterning of wildfire behavior estimated from the fire-spread model FLAMMAP when parameterized with LANDFIRE compared to field-based fuel-bed maps created from Random Forests models. Reliable maps of vegetation cover and fuel conditions are needed to help guide fuels and invasive species management, especially given recent increases in pre- and post-fire treatments in arid and semiarid landscapes. The costs associated with poorly informed fuel reduction may greatly exceed the costs of field-based vegetation and fuels inventory to inform effective design of vegetative fuels treatments.