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1. Fire lines adjacent to aspen are unlikely to hold during extreme burning conditions in southern Rocky Mountain forests

   https://doi.org/10.1002/eap.70249  

   Carter, Trevor A; Balch, Jennifer K; Cook, Maxwell C; Hart, Sarah J (April 2026, Ecological Applications)

   Abstract Increases in area of extent, severity, and frequency of wildfires across the western United States are presenting challenges to socio‐ecological systems, including shifts to alternative ecological states, loss of homes, and compromising human health. Wildfire suppression operations, such as constructing hand lines to limit the spread of fire, are an important part of wildland fire management, particularly in the wildland urban interface. Like other attributes of wildland fire activity and effects, suppression strategies and their effectiveness vary with ecological, topographic, climatological, and sociopolitical factors. However, there has been little research that examines the efficacy of suppression operations, specifically as they relate to forest composition. Here, we ask about the effectiveness of fire line construction based on adjacent stand composition. Specifically, we ask: (1) Are wildfire suppression lines preferentially constructed in stands with specific tree species? (2) How does species identity influence the probability that suppression lines hold when also considering differences in topography, climate, and extreme fire weather? We anticipated that suppression operations will be biased towards—and more effective in—stands with quaking aspen because they are often associated with less extreme fire behavior than many conifer species. We conducted our study in the southern Rocky Mountain ecoregion using fires (n = 36) that burned during 2019–2023 and included records of fire suppression operations (n = 4295). We used nonparametric statistical models to elucidate biases in the construction of fire lines and the effects of stand composition. We found quaking aspen was the least common tree species to be within fire footprints, yet fire lines were placed near quaking aspen 1.68–5.30 times more than commonly co‐occurring tree species. Fire growth, independent of stand composition, was the most important predictor for whether fire suppression lines were likely to hold but the percentage of fire lines that held differed between fires >40,500 ha and smaller events (65% vs. 82%, respectively). This research suggests that wildland firefighters preferentially located fire lines near aspen stands, perhaps due to the long‐held notion that aspen stands are less flammable. However, during extreme burning conditions fire lines are unlikely to hold regardless of stand composition. 

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2. Conceptualizing a probabilistic risk and loss assessment framework for wildfires

   https://doi.org/10.1007/s11069-022-05472-y  

   Elhami-Khorasani, Negar; Ebrahimian, Hamed; Buja, Lawrence; Cutter, Susan L.; Kosovic, Branko; Lareau, Neil; Meacham, Brian J.; Rowell, Eric; Taciroglu, Ertugrul; Thompson, Matthew P.; et al (July 2022, Natural Hazards)

   Wildfires are an essential part of a healthy ecosystem, yet the expansion of the wildland-urban interface, combined with climatic changes and other anthropogenic activities, have led to the rise of wildfire hazards in the past few decades. Managing future wildfires and their multi-dimensional impacts requires moving from traditional reactive response to deploying proactive policies, strategies, and interventional programs to reduce wildfire risk to wildland-urban interface communities. Existing risk assessment frameworks lack a unified analytical method that properly captures uncertainties and the impact of decisions across social, ecological, and technical systems, hindering effective decision-making related to risk reduction investments. In this paper, a conceptual probabilistic wildfire risk assessment framework that propagates modeling uncertainties is presented. The framework characterizes the dynamic risk through spatial probability density functions of loss, where loss can include different decision variables, such as physical, social, economic, environmental, and health impacts, depending on the stakeholder needs and jurisdiction. The proposed approach consists of a computational framework to propagate and integrate uncertainties in the fire scenarios, propagation of fire in the wildland and urban areas, damage, and loss analyses. Elements of this framework that require further research are identified, and the complexity in characterizing wildfire losses and the need for an analytical-deliberative process to include the perspectives of the spectrum of stakeholders are discussed. 

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3. Multimodal Wildland Fire Smoke Detection

   https://doi.org/10.3390/rs15112790  

   Bhamra, Jaspreet Kaur; Anantha_Ramaprasad, Shreyas; Baldota, Siddhant; Luna, Shane; Zen, Eugene; Ramachandra, Ravi; Kim, Harrison; Schmidt, Chris; Arends, Chris; Block, Jessica; et al (June 2023, Remote Sensing)

   Research has shown that climate change creates warmer temperatures and drier conditions, leading to longer wildfire seasons and increased wildfire risks in the United States. These factors have, in turn, led to increases in the frequency, extent, and severity of wildfires in recent years. Given the danger posed by wildland fires to people, property, wildlife, and the environment, there is an urgent need to provide tools for effective wildfire management. Early detection of wildfires is essential to minimizing potentially catastrophic destruction. To that end, in this paper, we present our work on integrating multiple data sources into SmokeyNet, a deep learning model using spatiotemporal information to detect smoke from wildland fires. We present Multimodal SmokeyNet and SmokeyNet Ensemble for multimodal wildland fire smoke detection using satellite-based fire detections, weather sensor measurements, and optical camera images. An analysis is provided to compare these multimodal approaches to the baseline SmokeyNet in terms of accuracy metrics, as well as time-to-detect, which is important for the early detection of wildfires. Our results show that incorporating weather data in SmokeyNet improves performance numerically in terms of both F1 and time-to-detect over the baseline with a single data source. With a time-to-detect of only a few minutes, SmokeyNet can be used for automated early notification of wildfires, providing a useful tool in the fight against destructive wildfires. 

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4. Wildfire Risk: Anchorage and Fairbanks, Alaska and Whitehorse, Yukon 2024

   https://doi.org/10.18739/a2js9h98k  

   Schmidt, Jennifer (January 2025, NSF Arctic Data Center)

   While wildfires can be beneficial and part of a natural process, there have been numerous instances around the world, particularly in recent years, where wildfires have had devastating consequences for society. Weather conditions have created extreme wildfire behavior, resulting in speeds and intensities that can overpower suppression resources. It is ever more critical that communities and agencies take actions to mitigate and prevent wildfire disasters. We have developed a tool that enables wildfire practitioners to assess the risk of wildfire to structures in a straightforward, rapid, and affordable manner. The approach leverages information often collected by communities (e.g., building footprints, zoning) and available vegetation datasets. In conjunction with local wildfire management regulations, our project also used wildfire exposure to help identify wildland-urban interface boundaries. We used this approach on three communities in the Arctic (Anchorage and Fairbanks, Alaska, and Whitehorse, Yukon) to assess wildfire risk. We determined that there is considerable wildfire risk in urban Arctic communities, with a greater percentage of structures at high or very high risk in Fairbanks (26 percent (%)) and Whitehorse (22%) compared to Anchorage (14%). Combining local wildfire management practices with wildfire exposure is a successful way to identify meaningful Wildland Urban Interface (WUI) boundaries, which are essential for obtaining mitigation funds and planning. The key to producing updatable wildfire risk and vulnerability maps is accurate, up-to-date information on vegetation, building footprints, and zoning. With this information and the tool outlined here, communities and agencies have a way to inform community wildfire protection plans and identify impactful mitigation actions. 

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5. Compound atmospheric drivers of the catastrophic 2025 Los Angeles urban firestorm

   https://doi.org/10.1038/s44304-025-00155-7  

   Guirguis, Kristen; Hatchett, Benjamin; Clemesha, Rachel; Aguilera, Rosana; Gershunov, Alexander; Campbell, Ian; Cayan, Daniel; Merrifield, Mark (December 2025, npj Natural Hazards)

   Abstract Urban firestorms are a growing hazard in fire-prone regions worldwide due to increasingly dry vegetation and expanding populations at the wildland-urban interface. In January 2025, the city of Los Angeles, California (USA), experienced an unprecedented fire disaster that destroyed over 16,000 structures and caused 31 fatalities. The event was driven by a rare “jet-forced Santa Ana” wind subtype featuring an amplified upper-level ridge over the West Coast and retrograding trough over the central/eastern U.S., producing extreme northerly flow, large-scale subsidence, and mountain wave activity that impeded aerial fire suppression. While the extreme surface winds were not unprecedented, their occurrence ahead of the first winter rain was uncommon. Despite accurate multi-day forecasts, response systems were overwhelmed. Our analysis shows how upper-level atmospheric support can drive surface fire weather, compounding hazard in even well-developed areas. This underscores the importance of aligning long-range prediction with operational preparedness and communication strategies in California’s variable hydroclimate. 

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