Research Database
Displaying 1 - 20 of 182
Governance of Indigenous data in open earth systems science
Year: 2025
In the age of big data and open science, what processes are needed to follow open science protocols while upholding Indigenous Peoples’ rights? The Earth Data Relations Working Group (EDRWG), convened to address this question and envision a research landscape that acknowledges the legacy of extractive practices and embraces new norms across Earth science institutions and open science research. Using the National Ecological Observatory Network (NEON) as an example, the EDRWG recommends actions, applicable across all phases of the data lifecycle, that recognize the sovereign rights of…
Publication Type: Journal Article
Modeling the probability of bark beetle-caused tree mortality as a function of watershed-scale host species presence and basal area
Year: 2025
In recent decades, bark beetle outbreaks have caused mass tree mortality in western US forests, which has led to altered wildfire characteristics, hydrological processes, and forest carbon dynamics. Understanding spatial variability in forest susceptibility to bark beetle outbreaks in the western US could inform strategic forest management to reduce wildfire risk, manage forest carbon, and plan for altered hydrology. The susceptibility of a forest stand to mortality by bark beetles depends on the availability and characteristics of trees of the host tree species. For multiple bark beetle…
Publication Type: Journal Article
Comparing modeled soil temperature and moisture dynamics during prescribed fires, slash-pile burns and wildfires
Year: 2025
Background: Wildfires, prescribed fires and slash-pile burns are disturbances that occur in many terrestrial ecosystems. Such fires produce variable surface heat fluxes causing a spectrum of effects on soil, such as seed mortality, nutrient loss, changes in microbial activity and water repellency. Accurately modeling soil heating is vital to predicting these second-order fire effects. The process-based Massman HMV (Heat–Moisture–Vapor) model incorporates soil water evaporation, heat transport and water vapor movement, and captures the observed rapid evaporation of soil moisture. Aims:…
Publication Type: Journal Article
Enhancing fire emissions inventories for acute health effects studies: integrating high spatial and temporal resolution data
Year: 2025
Background: Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies.Aims: This paper provides a method for improving an FEI dataset with readily available information to create a more robust dataset with daily fire progression.Methods: High temporal and spatial resolution burned area information from two FEI…
Publication Type: Journal Article
Can ‘‘Fire Safe’’ Cigarettes (FSCs) Start Wildfires?
Year: 2025
Over the last 20 years, all states within the US have required all cigarettes sold to be ‘‘fire safe’’ or ‘‘fire standards compliant’’ meaning that they must pass ASTM standard E2187. Though these cigarettes are designed to self-extinguish, there have been recent studies suggesting that these ‘‘fire safe’’ cigarettes (FSCs) can still ignite mattresses and other furnishings, but there has been no guidance for fire investigators whether FSCs can ignite natural fuels, such as duff and needles, that can be the source of a wildland fire. This work sets out to investigate whether FSCs can indeed be…
Publication Type: Journal Article
Extreme Fire Spread Events Burn More Severely and Homogenize Postfire Landscapes in the Southwestern United States
Year: 2025
Extreme fire spread events rapidly burn large areas with disproportionate impacts on people and ecosystems. Such events are associated with warmer and drier fire seasons and are expected to increase in the future. Our understanding of the landscape outcomes of extreme events is limited, particularly regarding whether they burn more severely or produce spatial patterns less conducive to ecosystem recovery. To assess relationships between fire spread rates and landscape burn severity patterns, we used satellite fire detections to create day‐of‐burning maps for 623 fires comprising 4267 single‐…
Publication Type: Journal Article
Evaluating a simulation-based wildfire burn probability map for the conterminous US
Year: 2025
Background: Wildfire simulation models are used to derive maps of burn probability (BP) based on fuels, weather, topography and ignition locations, and BP maps are key components of wildfire risk assessments.Aims: Few studies have compared BP maps with real-world fires to evaluate their suitability for near-future risk assessment. Here, we evaluated a BP map for the conterminous US based on the large fire simulation model FSim.Methods: We compared BP with observed wildfires from 2016 to 2022 across 128 regions representing similar fire regimes (‘pyromes’). We…
Publication Type: Journal Article
Wildland fire entrainment: The missing link between wildland fire and its environment
Year: 2025
Wildfires are growing in destructive power, and accurately predicting the spread and intensity of wildland fire is essential for managing ecological and societal impacts. No current operational models used for fire behavior prediction resolve critical fire-atmospheric coupling or nonlocal influences of the fire environment, rendering them inadequate in accounting for the range of wildland fire behavior scenarios under increasingly novel fuel and climate conditions. Here, we present a new perspective on a dominant fire-atmospheric feedback mechanism, which we term wildland fire entrainment (…
Publication Type: Journal Article
Enhancing fire emissions inventories for acute health effects studies: integrating high spatial and temporal resolution data
Year: 2025
Background: Daily fire progression information is crucial for public health studies that examine the relationship between population-level smoke exposures and subsequent health events. Issues with remote sensing used in fire emissions inventories (FEI) lead to the possibility of missed exposures that impact the results of acute health effects studies.Aims: This paper provides a method for improving an FEI dataset with readily available information to create a more robust dataset with daily fire progression.Methods: High temporal and spatial…
Publication Type: Journal Article
Short-term impacts of operational fuel treatments on modelled fire behaviour and effects in seasonally dry forests of British Columbia, Canada
Year: 2025
Background: In response to increasing risk of extreme wildfire across western North America, forest managers are proactively implementing fuel treatments.Aims: We assessed the efficacy of alternative combinations of thinning, pruning and residue fuel management to mitigate potential fire behaviour and effects in seasonally dry forests of interior British Columbia, Canada.Methods: Across five community forests, we measured stand attributes before and after fuel treatments in 2021 and 2022, then modelled fire behaviour and effects using the…
Publication Type: Journal Article
Assessing wildland fire suppression effectiveness with infrared imaging on experimental fires
Year: 2025
Background: Suppression effectiveness is often evaluated by measuring the extent to which it slows fire spread and reduces fireline intensity. Although studies have used infrared (IR) imaging methods to explore suppression effectiveness, most do not measure or assess the influence of water application on energy release.Aims: This preliminary analysis uses IR imagery to quantify the impact of suppression on fire behaviour and the reduction in energy released from a flaming fire.Methods: We conducted a series of small-scale experimental burns…
Publication Type: Journal Article
Fire Intensity and spRead forecAst (FIRA): A Machine Learning Based Fire Spread Prediction Model for Air Quality Forecasting Application
Year: 2025
Fire activities introduce hazardous impacts on the environment and public health by emitting various chemical species into the atmosphere. Most operational air quality forecast (AQF) models estimate smoke emissions based on the latest available satellite fire products, which may not represent real-time fire behaviors without considering fire spread. Hence, a novel machine learning (ML) based fire spread forecast model, the Fire Intensity and spRead forecAst (FIRA), is developed for AQF model applications. FIRA aims to improve the performance of AQF models by providing realistic, dynamic fire…
Publication Type: Journal Article
Visibility-informed mapping of potential firefighter lookout locations using maximum entropy modelling
Year: 2024
BackgroundSituational awareness is an essential component of wildland firefighter safety. In the US, crew lookouts provide situational awareness by proxy from ground-level locations with visibility of both fire and crew members.AimsTo use machine learning to predict potential lookout locations based on incident data, mapped visibility, topography, vegetation, and roads.MethodsLidar-derived topographic and fuel structural variables were used to generate maps of visibility across 30 study areas that possessed lookout location data. Visibility…
Publication Type: Journal Article
Estimating the influence of field inventory sampling intensity on forest landscape model performance for determining high-severity wildfire risk
Year: 2024
Historically, fire has been essential in Southwestern US forests. However, a century of fire-exclusion and changing climate created forests which are more susceptible to uncharacteristically severe wildfires. Forest managers use a combination of thinning and prescribed burning to reduce forest density to help mitigate the risk of high-severity fires. These treatments are laborious and expensive, therefore optimizing their impact is crucial. Landscape simulation models can be useful in identifying high risk areas and assessing treatment effects, but uncertainties in these models can limit…
Publication Type: Journal Article
Restoring frequent fire to dry conifer forests delays the decline of subalpine forests in the southwest United States under projected climate
Year: 2024
- In southwestern US forests, the combined impact of climate change and increased fuel loads due to more than a century of human-caused fire exclusion is leading to larger and more severe wildfires. Restoring frequent fire to dry conifer forests can mitigate high-severity fire risk, but the effects of these treatments on the vegetation composition and structure under projected climate change remain uncertain.
- We used a forest landscape model to assess the impact of thinning and prescribed burns in dry conifer forests across an elevation gradient, encompassing low-elevation…
Fire Effects and Fire Ecology, Fire History, Mixed-Conifer Management, Prescribed Burning, Restoration and Hazardous Fuel Reduction
Publication Type: Journal Article
Human driven climate change increased the likelihood of the 2023 record area burned in Canada
Year: 2024
In 2023, wildfires burned 15 million hectares in Canada, more than doubling the previous record. These wildfires caused a record number of evacuations, unprecedented air quality impacts across Canada and the northeastern United States, and substantial strain on fire management resources. Using climate models, we show that human-induced climate change significantly increased the likelihood of area burned at least as large as in 2023 across most of Canada, with more than two-fold increases in the east and southwest. The long fire season was more than five times as likely and the large areas…
Publication Type: Journal Article
A fast spectral recovery does not necessarily indicate post-fire forest recovery
Year: 2024
BackgroundClimate change has increased wildfire activity in the western USA and limited the capacity for forests to recover post-fire, especially in areas burned at high severity. Land managers urgently need a better understanding of the spatiotemporal variability in natural post-fire forest recovery to plan and implement active recovery projects. In burned areas, post-fire “spectral recovery”, determined by examining the trajectory of multispectral indices (e.g., normalized burn ratio) over time, generally corresponds with recovery of multiple post-fire vegetation types, including trees and…
Publication Type: Journal Article
Pixels to pyrometrics: UAS-derived infrared imagery to evaluate and monitor prescribed fire behaviour and effects
Year: 2024
Background: Prescribed fire is vital for fuel reduction and ecological restoration, but the effectiveness and fine-scale interactions are poorly understood. Aims: We developed methods for processing uncrewed aircraft systems (UAS) imagery into spatially explicit pyrometrics, including measurements of fuel consumption, rate of spread, and residence time to quantitatively measure three prescribed fires. Methods: We collected infrared (IR) imagery continuously (0.2 Hz) over prescribed burns and one experimental calibration burn, capturing…
Publication Type: Journal Article
Near-term fire weather forecasting in the Pacific Northwest using 500-hPa map types
Year: 2024
BackgroundNear-term forecasts of fire danger based on predicted surface weather and fuel dryness are widely used to support the decisions of wildfire managers. The incorporation of synoptic-scale upper-air patterns into predictive models may provide additional value in operational forecasting.AimsIn this study, we assess the impact of synoptic-scale upper-air patterns on the occurrence of large wildfires and widespread fire outbreaks in the US Pacific Northwest. Additionally, we examine how discrete upper-air map types can augment subregional models of…
Publication Type: Journal Article
Predicting daily firefighting personnel deployment trends in the western United States
Year: 2024
Projected increases in wildfire frequency, size, and severity may further stress already scarce firefighting resources in the western United States that are in high demand. Machine learning is a promising field with the ability to model firefighting resource usage without compromising dataset size or complexity. In this study, the Categorical Boosting (CatBoost) model was used with historical (2012-2020) wildfire data to train three models that calculate predicted daily counts of 1) total assigned personnel (total personnel), 2) assigned personnel that are at the fire (ground personnel), and…
Publication Type: Journal Article