Research and Publications
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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.
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Study used over 500,000 wildfire ignition records from 2000 to 2020 to develop machine learning models that predict daily ignition probability across the WUS and incorporate a wide range of physical, biological, social, and administrative variables. A key innovation of this work is development of novel sampling techniques for representing ignition absence. Unlike traditional purely random sampling or hyper-sampling, which does not account for temporally autocorrelated factors (such as droughts, insect outbreaks, and heatwaves) and spatially autocorrelated factors (such as proximity to human settlements, infrastructure presence, and fuel type), we introduce spatially and temporally stratified sampling of ignition absence. By drawing absence samples near the location and time of historical ignitions, we better captured the complex environmental and anthropogenic conditions associated with fire occurrence or lack thereof. Models trained without stratified sampling produced ignition probability maps that consistently overestimated fire risk during high fire danger periods, whereas models incorporating stratified fire absence samples more accurately captured the spatial and temporal variability of fire potential and achieved predictive accuracies exceeding 95%. In addition to operational utility for fire prevention and resource allocation, our approach offers insights into the drivers of wildfire ignitions and highlights the value of incorporating spatial and temporal structure in absence sampling for wildfire modeling.
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Wildfire induced large declines in the live overstory biomass for control (47%) and prescribed fire plots (32%) though remotely sensed burn severity was lower in treated plots relative to the control. Downed woody fuels and duff were consumed equivalently in both control and treated plots, ranging from 24 to 99% consumption. Grass loading increased 78-fold in control plots and 22-fold in prescribed fire plots after wildfire, largely driven by invasive cheatgrass, which comprised 79% to 99% of grass cover. However, overstory canopy cover was negatively correlated with cheatgrass loadings (R2 = 0.81) and cover (R2 = 0.84).
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Spring warming treatment effects varied with yearly weather and species emergence timing relative to the rest of the seeded species. Later-emergence timing was associated with lower emergence rates, particularly with late spring warming, and lower survival with early spring warming, but higher survival without warming or with late spring warming. Seed mix scenarios tuned to warming treatment and yearly weather outperformed early- or late-emergence timing and even proportion mixes. Early spring warming increased invasive annual grass abundance, which was associated with lower survival of seeded species.