Research Database
Displaying 1 - 20 of 98
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
Prescribed fire placement matters more than increasing frequency and extent in a simulated Pacific Northwest landscape
Year: 2024
Prescribed fire has been increasingly promoted to reduce wildfire risk and restore fire-adapted ecosystems. Yet, the complexities of forest ecosystem dynamics in response to disturbances, climate change, and drought stress, combined with myriad social and policy barriers, have inhibited widespread implementation. Using the forest succession model LANDIS-II, we investigated the likely impacts of increasing prescribed fire frequency and extent on wildfire severity and forest carbon storage at local and landscape scales. Specifically, we ask how much prescribed fire is required to maintain…
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
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
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
Tribal stewardship for resilient forest socio-ecosystems
Year: 2024
The Yurok Tribe, along with other tribal communities in northwest California, non-profit organizations, universities, and governmental agencies are working to restore forests and woodlands to be more resilient to wildfires, drought, pests and diseases. Our current work within ancestral Yurok territory is designing and evaluating effects of forest treatments including fuels reduction, tree harvesting, and intentional burning based upon indigenous knowledge and associated traditional stewardship practices. Central to these evaluations are the potential availability, quantity, and quality of…
ecocultural, modeling, silviculture and forest management, Indigenous land management, ecocultural resources
Publication Type: Journal Article
Five social and ethical considerations for using wildfire visualizations as a communication tool
Year: 2024
BackgroundIncreased use of visualizations as wildfire communication tools with public and professional audiences—particularly 3D videos and virtual or augmented reality—invites discussion of their ethical use in varied social and temporal contexts. Existing studies focus on the use of such visualizations prior to fire events and commonly use hypothetical scenarios intended to motivate proactive mitigation or explore decision-making, overlooking the insights that those who have already experienced fire events can provide to improve user engagement and understanding of wildfire…
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
Fire branding: Why do new residents make a burn scar their home?
Year: 2024
Researchers have sought to understand why wildland urban interface areas continue to expand in the United States despite increasing riskand loss to those areas. Using the case of the Camp Fire in northern California, which destroyed the town of Paradise and surrounding communities in the fall of 2018, this article explores how new arrivals to this area interact with rebuild institutions to evaluate their risk of future wildfires. The paper builds off of concepts of “disaster machine” (Pais and Elliott in Soc Forces 86(4):1415–1453, 2008) and “resilience gentrification” (Gould and Lewis, 2021…
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
Projecting live fuel moisture content via deep learning
Year: 2023
Background: Live fuel moisture content (LFMC) is a key environmental indicator used to monitor for high wildfire risk conditions. Many statistical models have been proposed to predict LFMC from remotely sensed data; however, almost all these estimate current LFMC (nowcasting models). Accurate modelling of LFMC in advance (projection models) would provide wildfire managers with more timely information for assessing and preparing for wildfire risk. Aims: The aim of this study was to investigate the potential for deep learning models to predict LFMC across the continental United States 3 months…
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
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
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