Research Database
Displaying 21 - 40 of 133
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
Future fire events are likely to be worse than climate projections indicate – these are some of the reasons why
Year: 2024
BackgroundClimate projections signal longer fire seasons and an increase in the number of dangerous fire weather days for much of the world including Australia.AimsHere we argue that heatwaves, dynamic fire–atmosphere interactions and increased fuel availability caused by drought will amplify potential fire behaviour well beyond projections based on calculations of afternoon forest fire danger derived from climate models.MethodsWe review meteorological dynamics contributing to enhanced fire behaviour during heatwaves, drawing on examples of…
Publication Type: Journal Article
Global rise in forest fire emissions linked to climate change in the extratropics
Year: 2024
Climate change increases fire-favorable weather in forests, but fire trends are also affected by multiple other controlling factors that are difficult to untangle. We use machine learning to systematically group forest ecoregions into 12 global forest pyromes, with each showing distinct sensitivities to climatic, human, and vegetation controls. This delineation revealed that rapidly increasing forest fire emissions in extratropical pyromes, linked to climate change, offset declining emissions in tropical pyromes during 2001 to 2023. Annual emissions tripled in one extratropical pyrome due to…
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
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
Wildfire management decisions outweigh mechanical treatment as the keystone to forest landscape adaptation
Year: 2024
BackgroundModern land management faces unprecedented uncertainty regarding future climates, novel disturbance regimes, and unanticipated ecological feedbacks. Mitigating this uncertainty requires a cohesive landscape management strategy that utilizes multiple methods to optimize benefits while hedging risks amidst uncertain futures. We used a process-based landscape simulation model (LANDIS-II) to forecast forest management, growth, climate effects, and future wildfire dynamics, and we distilled results using a decision support tool allowing us to examine tradeoffs between alternative…
Publication Type: Journal Article
Western larch regeneration more sensitive to wildfire-related factors than seasonal climate variability
Year: 2024
To understand the impacts of changing climate and wildfire activity on conifer forests, we studied how wildfire and post-fire seasonal climate conditions influence western larch (Larix occidentalis) regeneration across its range in the northwestern US. We destructively sampled 1651 seedlings from 57 sites across 32 fires that burned at moderate or high severity between 2000 and 2015; sites were within 100 m of reproductively mature western larch. Using dendrochronological methods, we estimated germination years of seedlings to calculate annual recruitment rates. We used boosted…
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…
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
A model for rapid PM2.5 exposure estimates in wildfire conditions using routinely available data: rapidfire v0.1.3
Year: 2024
Urban smoke exposure events from large wildfires have become increasingly common in California and throughout the western United States. The ability to study the impacts of high smoke aerosol exposures from these events on the public is limited by the availability of high-quality, spatially resolved estimates of aerosol concentrations. Methods for assigning aerosol exposure often employ multiple data sets that are time-consuming to create and difficult to reproduce. As these events have gone from occasional to nearly annual in frequency, the need for rapid smoke exposure assessments has…
Publication Type: Journal Article
Informing proactive wildfire management that benefits vulnerable communities and ecological values
Year: 2024
- 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…
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
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
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