Research and Publications
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Efforts to understand, assess, and address diversifying recovery needs have growing relevance as wildfires continue to impact communities. However, little is known about social experiences navigating gaps in assistance funding and support or “unmet needs” in post-fire spaces, particularly for indirect impacts like smoke damage. Determining how affected residents access available information and make decisions related to unmet needs can aid the development of resources and programs that support rapid identification of, and response to, emergent or undocumented impacts during recovery processes. This study explores household experiences with smoke damage as an unmet need during recovery following the 2021 Marshall Fire in Boulder County, Colorado, USA. Semi-structured interviews with residents and professionals who dealt with smoke damage revealed a wide spectrum of impacts. Decisions to act on smoke damage were influenced by risk perceptions and personal capacity to undertake self-guided recovery in the absence of a formalized process for navigating remediation. These experiences underscored a distinct absence of scientific and management expertise, legal protections or standards, and assistance related to smoke damage identification and remediation, catalyzing distrust in officials and ambiguity regarding whether smoke damaged homes could become safe again. Together, these conditions created cascading uncertainties for residents with smoke damaged homes that motivated long-term health concerns. Unmet needs after wildfire appeared to emerge because of misconceptions about impact severity, limited professional capacity, and adherence to rigid recovery structures that restrict professionals’ ability to identify and incorporate non-traditional impacts into existing processes. Findings informed suggestions for improving smoke damage recovery processes, inviting consideration of policy and more inclusive assistance to support recovery from indirect wildfire impacts.
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Since 2015, the Fishlake National Forest and partners have been restoring pre-colonial disturbance cycles, on a large-landscape scale.
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A new set of tools developed by the Rocky Mountain Research Station and partners can answer managers complex, spatially related questions in minutes. Raster Tools uses numerous lines of code and mathematical functions that empowers any analyst to model outcomes and create custom tools for natural resource planning and management. For example, managers can use it to determine the cost of specific wildfire treatments, transporting materials, or harvesting on their landscape.
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Seed pellets improved seedling emergence in both experiments, with 136% and 56% higher odds of emergence from seed pellets compared to broadcast seeding in the first and second experiments, respectively. Composition and activated carbon additions without herbicide treatment had limited effects. Following aminopyralid herbicide treatment, we found significantly higher emergence from seed pellets containing activated carbon. Seed pellets with activated carbon may be an effective seeding method in dryland ecosystems where herbicide treatment and reseeding are needed. Varying clay content and activated carbon additions had limited impacts without herbicide treatment.
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Seed coating designed to accelerate germination strongly increased emergence in species with high dormancy requirements, while seed coating designed to delay germination decreased emergence in species with low dormancy by about half and postponed emergence by up to 15 days. These coatings altered emergence timing regardless of watering regime, suggesting that seed coating could expand emergence windows under variable precipitation regimes. Seedling growth and total biomass were less dependent on seed coating and were more driven by the average amount of soil moisture provisioned to the developing plant. While seed coating designed to accelerate germination increased the emergence of two grass species, growth decreased during late periods of water availability, suggesting a trade-off in seedling performance.
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Researchers at UC Berkeley and the US Forest Service sought to evaluate the influence of forest structure and composition, topography, and weather on fire severity in a third successive fire. They investigated the structural conditions emerging after successive burns, whether these conditions contributed to fire severity, and how these conditions compared to historical estimates. Their study utilized a network of Forest Service field plots in the Plumas and Lassen National Forests that had been initially burned in the Storrie and Rich Fires in 2000 and 2008, reburned in the Chips Fire in 2012, and were then subject to a second reburn in the 2021 Dixie Fire. Plots were sampled in 2017 and 2018 following the Chips Fire and in 2023 following the Dixie Fire.
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From 1992 to 2024, in all 8 contiguous-US Forest Service regions combined, wildfire-ignition density was lowest in designated wilderness areas (1.75 fires/1000 hectares), followed closely by Inventoried Roadless Areas (1.97 fires/1000 ha). The highest wildfire-ignition density was in lands within 50 m of roads (7.99 fires/1000 ha), and the second highest wildfire-ignition density was in other national forest lands outside of the 50-m road buffers but not in wilderness or roadless areas (3.50 fires/1000 ha). For human-caused, natural, and undetermined fires, wildfire-ignition density decreased as distance to road increased, irrespective of designation categories such as “wilderness” or “roadless.” In lands between 0 and 250 m from roads, 6 fires ignited per 1000 ha, whereas fewer than 2 fires ignited per 1000 ha at a distance class of over 2000 m from roads. Mean fire size varied by where the fire started: it was greatest in wilderness areas (239 ha), followed by Inventoried Roadless Areas (135 ha), roaded national forest lands outside of Inventoried Roadless Areas, wilderness, and the 50-m buffer (62 ha), and lands within the 50-m road buffer (49 ha). We found, however, that the largest 2% of fires had similar mean sizes and ignition densities regardless of where they started.
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Using measurements of aeolian sediment flux and plant community development from seven sites following wildfire, we identified ordinal plant communities to develop a quantitative index of site stability post-wildfire. Using these plant communities, we modeled how management focusing on reducing a single plant functional group (e.g., fuel treatments) may impact wind erosion as plant communities redeveloped after wildfire. We found the outcome of management focused on a single functional group has different impacts on wind erosion based on its surrounding plant community and time since wildfire.
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Wildfires are increasingly impacting social and environmental systems in the United States (US). The ability to mitigate the adverse effects of wildfires increases with understanding of the social, physical, and biological conditions that co-occurred with or caused the wildfire ignitions and contributed to the wildfire impacts. To this end, we developed the FPA FOD-Attributes dataset, which augments the sixth version of the Fire Program Analysis Fire-Occurrence Database (FPA FOD v6) with nearly 270 attributes that coincide with the date and location of each wildfire ignition in the US. FPA FOD v6 contains information on location, jurisdiction, discovery time, cause, and final size of wildfires in the US between 1992 and 2020 . For each wildfire, we added physical (e.g., weather, climate, topography, and infrastructure), biological (e.g., land cover and normalized difference vegetation index), social (e.g., population density and social vulnerability index), and administrative (e.g., national and regional preparedness level and jurisdiction) attributes. This publicly available dataset can be used to answer numerous questions about the covariates associated with human- and lightning-caused wildfires. Furthermore, the FPA FOD-Attributes dataset can support descriptive, diagnostic, predictive, and prescriptive wildfire analytics, including the development of machine learning models.