- In response to mounting wildfire risks, land managers across the country will need to dramatically increase proactive wildfire management (e.g. fuel and forest health treatments). While human communities vary widely in their vulnerability to the impacts of fire, these discrepancies have rarely informed prioritizations for wildfire mitigation treatments. The ecological values and ecosystem services provided by forests have also typically been secondary considerations.
- To identify locations across the conterminous US where proactive wildfire management is likely to be effective…
Research Database
Displaying 41 - 60 of 182
Informing proactive wildfire management that benefits vulnerable communities and ecological values
Year: 2024
Publication Type: Journal Article
Snow-cover remote sensing of conifer tree recovery in high-severity burn patches
Year: 2024
The number of large, high-severity wildfires has been increasing across the western United States over the last several decades. It is not fully understood how changes in the frequency of large, severe wildfires may impact the resilience of conifer forests, due to alterations in regeneration success or failure. Our research investigates 30 years of conifer recovery patterns within 34 high-severity wildfire complexes (1988–1991) of the Northern Rocky Mountains. We evaluate the capability of snow-cover Landsat to characterize conifer tree recolonization of high-severity burn patches. Snow-…
Publication Type: Journal Article
Before the fire: predicting burn severity and potential post-fire debris-flow hazards to conservation populations of the Colorado River Cutthroat Trout (Oncorhynchus clarkii pleuriticus)
Year: 2024
Background: Colorado River Cutthroat Trout (CRCT; Oncorhynchus clarkii pleuriticus) conservation populations may be at risk from wildfire and post-fire debris flows hazards. Aim: To predict burn severity and potential post-fire debris flow hazard classifications to CRCT conservation populations before wildfires occur. Methods: We used remote sensing, spatial analyses, and machine learning to model 28 wildfire incidents (2016–2020) and spatially predict burn severity from pre-wildfire environmental factors to evaluate the likelihood…
Publication Type: Journal Article
Wildfire probability estimated from recent climate and fine fuels across the big sagebrush region
Year: 2024
BackgroundWildfire is a major proximate cause of historical and ongoing losses of intact big sagebrush (Artemisia tridentata Nutt.) plant communities and declines in sagebrush obligate wildlife species. In recent decades, fire return intervals have shortened and area burned has increased in some areas, and habitat degradation is occurring where post-fire re-establishment of sagebrush is hindered by invasive annual grasses. In coming decades, the changing climate may accelerate these wildfire and invasive feedbacks, although projecting future wildfire dynamics requires a better…
Publication Type: Journal Article
Landsat assessment of variable spectral recovery linked to post-fire forest structure in dry sub-boreal forests
Year: 2024
Forest disturbances such as wildfires can dramatically alter forest structure and composition, increasing the likelihood of ecosystem changes. Up-to-date and accurate measures of post-disturbance forest recovery in managed forests are critical, particularly for silvicultural planning. Measuring the live and dead vegetation post-fire is challenging because areas impacted by wildfire may be remote, difficult to access, and/or dangerous to survey. The difficulties of post-fire monitoring are compounded by the global increase in the frequency and severity of disturbances, as expansion of…
Publication Type: Journal Article
Probabilistic Forecasting of Lightning Strikes over the Continental USA and Alaska: Model Development and Verification
Year: 2024
Lightning is responsible for the most area annually burned by wildfires in the extratropical region of the Northern Hemisphere. Hence, predicting the occurrence of wildfires requires reliable forecasting of the chance of cloud-to-ground lightning strikes during storms. Here, we describe the development and verification of a probabilistic lightning-strike algorithm running on a uniform 20 km grid over the continental USA and Alaska. This is the first and only high-resolution lightning forecasting model for North America derived from 29-year-long data records. The algorithm consists of a large…
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
Performance of Fire Danger Indices and Their Utility in Predicting Future Wildfire Danger Over the Conterminous United States
Year: 2023
Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale-dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high-resolution (4 km) climate and fuel data sets for the 1984–2019…
Publication Type: Journal Article
Satellite-derived prefire vegetation predicts variation in field-based invasive annual grass cover after fir
Year: 2023
AimsInvasion by annual grasses (IAGs) and concomitant increases in wildfire are impacting many drylands globally, and an understanding of factors that contribute to or detract from community resistance to IAGs is needed to inform postfire restoration interventions. Prefire vegetation condition is often unknown in rangelands but it likely affects variation in postfire invasion resistance across large burned scars. Whether satellite-derived products like the Rangeland Analysis Platform (RAP) can fulfill prefire information needs and be used to parametrize models of fire recovery to inform…
Publication Type: Journal Article
DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure
Year: 2023
Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. We present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and…
Publication Type: Journal Article
Atmospheric turbulence and wildland fires: a review
Year: 2023
The behaviour of wildland fires and the dispersion of smoke from those fires can be strongly influenced by atmospheric turbulent flow. The science to support that assertion has developed and evolved over the past 100+ years, with contributions from laboratory and field observations, as well as modelling experiments. This paper provides a synthesis of the key laboratory- and field-based observational studies focused on wildland fire and atmospheric turbulence connections that have been conducted from the early 1900s through 2021. Included in the synthesis are reports of anecdotal…
Publication Type: Journal Article
Quantifying burned area of wildfires in the western United States from polar-orbiting and geostationary satellite active-fire detections
Year: 2023
Background: Accurately estimating burned area from satellites is key to improving biomass burning emission models, studying fire evolution and assessing environmental impacts. Previous studies have found that current methods for estimating burned area of fires from satellite active-fire data do not always provide an accurate estimate. Aims and methods: In this work, we develop a novel algorithm to estimate hourly accumulated burned area based on the area from boundaries of non-convex polygons containing the accumulated Visible Infrared Imaging Radiometer Suite (VIIRS) active-fire detections.…
Publication Type: Journal Article
The Power Grid/Wildfire Nexus: Using GIS and Satellite Remote Sensing to Identify Vulnerabilities
Year: 2023
The effects of wildfire on the power grid are a recurring concern for utility companies who need reliable information about where to prioritize infrastructure hardening. Though there are existing data layers that provide measures of burn probability, these models predominately consider long-term climate variables, which are not helpful when analyzing current season trends. Utility companies need data that are temporally and locally relevant. To determine the primary drivers of burn probability relative to power grid vulnerability, this study assessed potential wildfire drivers that are both…
Publication Type: Journal Article
Modeling Wildland Firefighters’ Assessments of Structure Defensibility
Year: 2023
In wildland–urban interface areas, firefighters balance wildfire suppression and structure protection. These tasks are often performed under resource limitations, especially when many structures are at risk. To address this problem, wildland firefighters employ a process called “structure triage” to prioritize structure protection based on perceived defensibility. Using a dataset containing triage assessments of thousands of structures within the Western US, we developed a machine learning model that can improve the understanding of factors contributing to assessed structure defensibility.…
Publication Type: Journal Article
Deterioration of air quality associated with the 2020 US wildfires
Year: 2023
The wildfires of August and September 2020 in the western part of the United States were characterized by an unparalleled duration and wide geographical coverage. A particular consequence of massive wildfires includes serious health effects due to short and long-term exposure to poor air quality. Using a variety of data sources including aerosol optical depth (AOD) and ultraviolet aerosol index (UVAI), obtained with the Moderate-Resolution Imaging Spectroradiometer (MODIS), Multi-Angle Implementation of Atmospheric Correction (MAIAC) and Tropospheric Monitoring Instrument (TROPOMI), combined…
Publication Type: Journal Article
A comparison of smoke modelling tools used to mitigate air quality impacts from prescribed burning
Year: 2023
Background. Prescribed fire is a land management tool used extensively across the United States. Owing to health and safety risks, smoke emitted by burns requires appropriate manage- ment. Smoke modelling tools are often used to mitigate air pollution impacts. However, direct comparisons of tools’ predictions are lacking. Aims. We compared three tools commonly used to plan prescribed burning projects: the Simple Smoke Screening Tool, VSmoke and HYSPLIT. Methods. We used each tool to model smoke dispersion from prescribed burns conducted by the North Carolina Division of Parks and Recreation…
Publication Type: Journal Article