Research and Publications
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Beginning in the 2010s, structured wildfire risk assessment tools were developed to provide a framework for prioritizing management actions based on wildfire hazard, ecological response, and decision-maker values. Yet, more than a decade later, operationalizing risk assessments remains challenging and limited by disconnected tooling, static data, and workflows that are difficult to scale or adapt for collaborative decision-making. Here, we present the Vibrant Planet Platform (VPP), a modular, cloud-based decision-support system that integrates fire simulation, ecological response functions, multi-objective optimization, and user input into a unified planning environment. The platform enables risk-based scenario planning across landscapes up to millions of hectares by linking validated modeling tools (e.g., FSim, FVS, ForSys) with high-resolution, up-to-date vegetation and infrastructure data. We describe the challenges inherent to operationalizing risk assessments, demonstrate how VPP addresses them through architectural and methodological design, and highlight real-world deployments in U.S. risk-exposed landscapes and communities. We outline a multi-tiered validation framework for assessing model relevance, internal coherence, predictive performance, and field alignment. VPP illustrates how structured decision-making can be operationalized at broad scales, offering a model for ecological planning tools that are rigorous, transparent, and participatory.
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Widespread impacts of landscape fire on ecosystems, societies, and the climate system itself have heightened the need to understand the potential future trajectory of fire under continued climate change. However, the complexity of fire makes climate change impact assessment challenging. The climate system influences fire in many ways, including through vegetation, fuel dryness, fire weather, and ignition. Furthermore, fire’s impacts are highly diverse, spanning threats to human and ecological values and beneficial ecosystem and cultural services. Here, we discuss the art and science of projecting climate change impacts on landscape fire. This not only includes how fire, its drivers, and its impacts are modeled, but critically it also includes how projections of the climate system are developed. By raising and discussing these issues, we aim to foster the development of more robust and useful fire projections, help interpret existing assessments, and support society in charting a course toward a sustainable fire future.
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In historically frequent fire forests, wildfires are burning larger areas and driving forest loss across western North America, yet they also produce extensive low- to moderate-severity effects that can be leveraged to harden landscapes against future high-severity fire. Here, we operationalize prior conceptual calls by presenting a framework that identifies opportunities to leverage recent wildfire footprints via three management pathways to increasing resistance to high-severity fire: create (use burned edges as containment lines to treat adjacent unburned forest), enhance (apply mechanical treatment and prescribed fire or wildfire managed for resource objectives to areas with one prior beneficial disturbance), and maintain (sustain high-resistance stands with recurring fire). We quantify the extent of these opportunities across California’s Sierra Nevada yellow pine-mixed conifer forests at the Potential Operational Delineations (PODs) scale and outline policy options to act within limited post-fire windows. This work can support increasing resistance to high-severity fire across the landscape, highlighting how leveraging wildfire has the potential to save time and money, lower operational risk under suitable conditions, and promote pyrodiversity and biodiversity.
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When wildland firefighters head into the field, they know the work is dangerous; but until now, agencies lacked detailed data on exactly which activities and hazards posed the greatest threats. A recent analysis of five years of serious firefighter injuries offers new insights.
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Study detailed 25 unique potential benefits of fuel treatments and multiple costs. Complexity in benefit-cost analysis of fuel treatments stems from limited data and reference studies, various beneficiaries and accounting stances, spatial and temporal dispersion of benefits and costs, and aggregating multiple benefits with differing outputs and units.
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Land managers and fire professionals use predictions of wildfire behavior and probability to prepare for
the fire season.
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We generated burn severity spectral index values for a dataset of Composite Burn Index (CBI) field plots across the conterminous US. The effectiveness of offset corrections was tested across image selection techniques, spectral indices, offset generation methods and burn perimeter sources. We assessed the influence of offset corrections on the modeled relationship with CBI, agreement between burn severity thresholds and potential bias. Applying offset corrections consistently improved the modeled relationship with CBI by addressing extreme outlier severity values. However, automated offset corrections had the potential to introduce bias, systematically lowering severity values and reducing correspondence with observed burn severity categories. Offset corrections offer benefits but also present trade-offs to accurately representing remotely sensed burn severity.
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To assess the role of current and source environments in explaining variation in flowering phenology of Bromus tectorum, an invasive annual grass, we conducted a replicated common garden experiment using 92 genotypes collected across western North America. Replicates of each genotype were planted in two densities (low = 100 seeds/1 m², high = 100 seeds/0.04 m²) under two different temperature treatments (low = white gravel; high = black gravel; 2.1°C average difference) in a factorial design, replicated across four common garden locations in Idaho and Wyoming, USA. We tested for the effect of current environment (i.e., density treatment, temperature treatment, and common garden location), source environment (i.e., genotype source climate), and their interaction on each plant’s flowering phenology. Flowering timing was strongly influenced by a plant’s current environment, with plants that experienced warmer current climates and higher densities flowering earlier than those that experienced cooler current climates and lower densities. Genotypes from hot and dry source climates flowered consistently earlier than those from cool and wet source climates, even after accounting for genotype relatedness, suggesting that this genetically based climate cline is a product of natural selection. We found minimal evidence of interactions between current and source environments or genotype-by-environment interactions. Phenology was more sensitive to variation in the current climate than to variation in source climate. These results indicate that cheatgrass phenology reflects high levels of plasticity as well as rapid local adaptation. Both processes likely contribute to its current success as a biological invader and its capacity to respond to future environmental change.
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Local adaptation may facilitate range expansion during invasions, but the mechanisms underlying successful invasions remain unclear. Cheatgrass (Bromus tectorum), native to Eurasia and Africa, has invaded globally, with severe impacts in western North America. We aim to identify mechanisms and consequences of local adaptation in the North American cheatgrass invasion. We sequence 307 range-wide genotypes and conduct controlled experiments. We find that diverse lineages invaded North America, where long-distance gene flow is common. Nearly half of North American cheatgrass comprises a mosaic of ~19 locally adapted, near-clonal genotypes, each seemingly very successful in a different part of North America. Additionally, ancestry, phenotype, and allele frequency-environment clines in the native range predict those in the invaded range, indicating pre-adapted genotypes colonized different regions. Common gardens show directional selection on flowering time that reverse between warm and cold sites, potentially maintaining clines. In the USA Great Basin, genomic predictions of strong local adaptation identify sites where cheatgrass is most dominant. Our results indicate that multiple introductions and migration within the invaded range fuel local adaptation and success of cheatgrass in western North America. Understanding how environment and gene flow shape adaptation and invasion is critical for managing ongoing invasions.
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Forest growth, fire behavior, fire spread and emissions models were used to simulate fuel treatments and their potential impacts. The ‘underburn only’ and ‘thin from below + pile burn’ treatments had a minimum annual fire probability (AFP) 5–35% lower than other treatment types to achieve reduced GHG emissions. When AFP was high, the ‘stand density index (SDI) thin + underburn’ treatment reduced GHG emissions 13–54% more than the next best treatment. AFP, forest type and initial hazard level should be primary considerations when selecting a fuel treatment type for reducing future GHG emissions.