- 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 21 - 40 of 129
Informing proactive wildfire management that benefits vulnerable communities and ecological values
Year: 2024
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
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
Blending Indigenous and western science: Quantifying cultural burning impacts in Karuk Aboriginal Territory
Year: 2024
The combined effects of Indigenous fire stewardship and lightning ignitions shaped historical fire regimes, landscape patterns, and available resources in many ecosystems globally. The resulting fire regimes created complex fire–vegetation dynamics that were further influenced by biophysical setting, disturbance history, and climate. While there is increasing recognition of Indigenous fire stewardship among western scientists and managers, the extent and purpose of cultural burning is generally absent from the landscape–fire modeling literature and our understanding of ecosystem processes and…
Publication Type: Journal Article
A fire-use decision model to improve the United States’ wildfire management and support climate change adaptation
Year: 2024
The US faces multiple challenges in facilitating the safe, effective, and proactive use of fire as a landscape management tool. This intentional fire use exposes deeply ingrained communication challenges and distinct but overlapping strategies of prescribed fire, cultural burning, and managed wildfire. We argue for a new conceptual model that is organized around ecological conditions, capacity to act, and motivation to use fire and can integrate and expand intentional fire use as a tool. This result emerges from more considered collaboration and communication of values and needs to address…
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
Resource objective wildfire leveraged to restore old growth forest structure while stabilizing carbon stocks in the southwestern United States
Year: 2024
Wildfire futures and aboveground carbon (C) dynamics associated with forest restoration programs that integrate resource objective wildfire as part of a larger treatment strategy are not well understood. Using simulation modeling, we examined alternative forest and fuel management strategies on a 237,218-ha study area within a 778,000-ha landscape that is a high priority target for federal restoration programs. We simulated two wildfire management scenarios combined with three levels of conventional forest restoration treatments over 64 years using a detailed landscape disturbance and…
Publication Type: Journal Article
Using focus groups for knowledge sharing: Tracking emerging pandemic impacts on USFS wildland fire operations
Year: 2024
In early 2020 the US Forest Service (USFS) recognized the need to gather real-time information from its wildland fire management personnel about their challenges and adaptations during the unfolding COVID-19 pandemic. The USFS conducted 194 virtual focus groups to address these concerns, over 32 weeks from March 2020 to October 2020. This management effort provided an opportunity for an innovative practice-based research study. Here, we outline a novel methodological approach (weekly, iterative focus groups, with two-way communication between USFS staff and leadership), which culminated in a…
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
Avoided wildfire impact modeling with counterfactual probabilistic analysis
Year: 2023
Assessing the effectiveness and measuring the performance of fuel treatments and other wildfire risk mitigation efforts are challenging endeavors. Perhaps the most complicated is quantifying avoided impacts. In this study, we show how probabilistic counterfactual analysis can help with performance evaluation. We borrow insights from the disaster risk mitigation and climate event attribution literature to illustrate a counterfactual framework and provide examples using ensemble wildfire simulations. Specifically, we reanalyze previously published fire simulation data from fire-prone landscapes…
Publication Type: Journal Article
An aridity threshold model of fire sizes and annual area burned in extensively forested ecoregions of the western USA
Year: 2023
Wildfire occurrence varies among regions and through time due to the long-term impacts of climate on fuel structure and short-term impacts on fuel flammability. Identifying the climatic conditions that trigger extensive fire years at regional scales can enable development of area burned models that are both spatially and temporally robust, which is crucial for understanding the impacts of past and future climate change. We identified region-specific thresholds in fire-season aridity that distinguish years with limited, moderate, and extensive area burned for 11 extensively forested ecoregions…
Publication Type: Journal Article
Long-term mortality burden trends attributed to black carbon and PM2·5 from wildfire emissions across the continental USA from 2000 to 2020: a deep learning modelling study
Year: 2023
Background
Long-term improvements in air quality and public health in the continental USA were disrupted over the past decade by increased fire emissions that potentially offset the decrease in anthropogenic emissions. This study aims to estimate trends in black carbon and PM2·5 concentrations and their attributable mortality burden across the USA.
Methods
In this study, we derived daily concentrations of PM2·5 and its highly toxic black carbon component at a 1-km resolution in the USA from 2000 to 2020 via deep learning that integrated big data from satellites, models, and surface…
Publication Type: Journal Article
Exploring and Testing Wildfire Risk Decision-Making in the Face of Deep Uncertainty
Year: 2023
We integrated a mechanistic wildfire simulation system with an agent-based landscape change model to investigate the feedbacks among climate change, population growth, development, landowner decision-making, vegetative succession, and wildfire. Our goal was to develop an adaptable simulation platform for anticipating risk-mitigation tradeoffs in a fire-prone wildland–urban interface (WUI) facing conditions outside the bounds of experience. We describe how five social and ecological system (SES) submodels interact over time and space to generate highly variable alternative futures even within…
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
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
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
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
Incorporating pyrodiversity into wildlife habitat assessments for rapid post-fire management: A woodpecker case study
Year: 2023
Spatial and temporal variation in fire characteristics—termed pyrodiversity—areincreasingly recognized as important factors that structure wildlife communitiesin fire-prone ecosystems, yet there have been few attempts to incorporatepyrodiversity or post-fire habitat dynamics into predictive models of animaldistributionsandabundancetosupportpost-firemanagement.Weusetheblack-backed woodpecker—a species associated with burned forests—as a case study todemonstrate a pathway for incorporating pyrodiversity into wildlife habitatassessments for adaptive management. Employing monitoring data (2009–…
Publication Type: Journal Article
Using soil moisture information to better understand and predict wildfire danger: a review of recent developments and outstanding questions
Year: 2023
Soil moisture conditions are represented in fire danger rating systems mainly through simple drought indices based on meteorological variables, even though better sources of soil moisture information are increasingly available. This review summarises a growing body of evidence indicating that greater use of in situ, remotely sensed, and modelled soil moisture information in fire danger rating systems could lead to better estimates of dynamic live and dead herbaceous fuel loads, more accurate live and dead fuel moisture predictions, earlier warning of wildfire danger, and better forecasts of…
Publication Type: Journal Article