skip to main content


This content will become publicly available on March 1, 2024

Title: Shifting social-ecological fire regimes explain increasing structure loss from Western wildfires
Abstract Structure loss is an acute, costly impact of the wildfire crisis in the western conterminous United States (“West”), motivating the need to understand recent trends and causes. We document a 246% rise in West-wide structure loss from wildfires between 1999–2009 and 2010–2020, driven strongly by events in 2017, 2018, and 2020. Increased structure loss was not due to increased area burned alone. Wildfires became significantly more destructive, with a 160% higher structure-loss rate (loss/kha burned) over the past decade. Structure loss was driven primarily by wildfires from unplanned human-related ignitions (e.g. backyard burning, power lines, etc.), which accounted for 76% of all structure loss and resulted in 10 times more structures destroyed per unit area burned compared with lightning-ignited fires. Annual structure loss was well explained by area burned from human-related ignitions, while decadal structure loss was explained by state-level structure abundance in flammable vegetation. Both predictors increased over recent decades and likely interacted with increased fuel aridity to drive structure-loss trends. While states are diverse in patterns and trends, nearly all experienced more burning from human-related ignitions and/or higher structure-loss rates, particularly California, Washington, and Oregon. Our findings highlight how fire regimes—characteristics of fire over space and time—are fundamentally social-ecological phenomena. By resolving the diversity of Western fire regimes, our work informs regionally appropriate mitigation and adaptation strategies. With millions of structures with high fire risk, reducing human-related ignitions and rethinking how we build are critical for preventing future wildfire disasters.  more » « less
Award ID(s):
1655121
NSF-PAR ID:
10442427
Author(s) / Creator(s):
; ; ; ; ;
Editor(s):
Liu, Junguo
Date Published:
Journal Name:
PNAS Nexus
Volume:
2
Issue:
3
ISSN:
2752-6542
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Downslope wind‐driven fires have resulted in many of the wildfire disasters in the western United States and represent a unique hazard to infrastructure and human life. We analyze the co‐occurrence of wildfires and downslope winds across the western United States (US) during 1992–2020. Downslope wind‐driven fires accounted for 13.4% of the wildfires and 11.9% of the burned area in the western US yet accounted for the majority of local burned area in portions of southern California, central Washington, and the front range of the Rockies. These fires were predominantly ignited by humans, occurred closer to population centers, and resulted in outsized impacts on human lives and infrastructure. Since 1999, downslope wind‐driven fires have accounted for 60.1% of structures and 52.4% of human lives lost in wildfires in the western US. Downslope wind‐driven fires occurred under anomalously dry fuels and exhibited a seasonality distinct from other fires—occurring primarily in the spring and fall. Over 1992–2020, we document a 25% increase in the annual number of downslope wind‐driven fires and a 140% increase in their respective annual burned area, which partially reflects trends toward drier fuels. These results advance our understanding of the importance of downslope winds in driving disastrous wildfires that threaten populated regions adjacent to mountain ranges in the western US. The unique characteristics of downslope wind‐driven fires require increased fire prevention and adaptation strategies to minimize losses and incorporation of changing human‐ignitions, fuel availability and dryness, and downslope wind occurrence to elucidate future fire risk.

     
    more » « less
  2. In recent decades, wildfires in many areas of the United States (U.S.) have become larger and more frequent with increasing anthropogenic pressure, including interactions between climate, land-use change, and human ignitions. We aimed to characterize the spatiotemporal patterns of contemporary fire characteristics across the contiguous United States (CONUS). We derived fire variables based on frequency, fire radiative power (FRP), event size, burned area, and season length from satellite-derived fire products and a government records database on a 50 km grid (1984–2020). We used k-means clustering to create a hierarchical classification scheme of areas with relatively homogeneous fire characteristics, or modern ‘pyromes,’ and report on the model with eight major pyromes. Human ignition pressure provides a key explanation for the East-West patterns of fire characteristics. Human-dominated pyromes (85% mean anthropogenic ignitions), with moderate fire size, area burned, and intensity, covered 59% of CONUS, primarily in the East and East Central. Physically dominated pyromes (47% mean anthropogenic ignitions) characterized by relatively large (average 439 mean annual ha per 50 km pixel) and intense (average 75 mean annual megawatts/pixel) fires occurred in 14% of CONUS, primarily in the West and West Central. The percent of anthropogenic ignitions increased over time in all pyromes (0.5–1.7% annually). Higher fire frequency was related to smaller events and lower FRP, and these relationships were moderated by vegetation, climate, and ignition type. Notably, a spatial mismatch between our derived modern pyromes and both ecoregions and historical fire regimes suggests other major drivers for modern U.S. fire patterns than vegetation-based classification systems. This effort to delineate modern U.S. pyromes based on fire observations provides a national-scale framework of contemporary fire regions and may help elucidate patterns of change in an uncertain future. 
    more » « less
  3. Abstract. The annual area burned due to wildfires in the western United States (WUS) increased bymore than 300 % between 1984 and 2020. However, accounting for the nonlinear, spatially heterogeneous interactions between climate, vegetation, and human predictors driving the trends in fire frequency and sizes at different spatial scales remains a challenging problem for statistical fire models. Here we introduce a novel stochastic machine learning (SML) framework, SMLFire1.0, to model observed fire frequencies and sizes in 12 km × 12 km grid cells across the WUS. This framework is implemented using mixture density networks trained on a wide suite of input predictors. The modeled WUS fire frequency matches observations at both monthly (r=0.94) and annual (r=0.85) timescales, as do the monthly (r=0.90) and annual (r=0.88) area burned. Moreover, the modeled annual time series of both fire variables exhibit strong correlations (r≥0.6) with observations in 16 out of 18 ecoregions. Our ML model captures the interannual variability and the distinct multidecade increases in annual area burned for both forested and non-forested ecoregions. Evaluating predictor importance with Shapley additive explanations, we find that fire-month vapor pressure deficit (VPD) is the dominant driver of fire frequencies and sizes across the WUS, followed by 1000 h dead fuel moisture (FM1000), total monthly precipitation (Prec), mean daily maximum temperature (Tmax), and fraction of grassland cover in a grid cell. Our findings serve as a promising use case of ML techniques for wildfire prediction in particular and extreme event modeling more broadly. They also highlight the power of ML-driven parameterizations for potential implementation in fire modules of dynamic global vegetation models (DGVMs) and earth system models (ESMs). 
    more » « less
  4. Abstract

    Wildfire frequency has increased in the Western US over recent decades, driven by climate change and a legacy of forest management practices. Consequently, human structures, health, and life are increasingly at risk due to wildfires. Furthermore, wildfire smoke presents a growing hazard for regional and national air quality. In response, many scientific tools have been developed to study and forecast wildfire behavior, or test interventions that may mitigate risk. In this study, we present a retrospective analysis of 1 month of the 2020 Northern California wildfire season, when many wildfires with varying environments and behavior impacted regional air quality. We simulated this period using a coupled numerical weather prediction model with online atmospheric chemistry, and compare two approaches to representing smoke emissions: an online fire spread model driven by remotely sensed fire arrival times and a biomass burning emissions inventory. First, we quantify the differences in smoke emissions and timing of fire activity, and characterize the subsequent impact on estimates of smoke emissions. Next, we compare the simulated smoke to surface observations and remotely sensed smoke; we find that despite differences in the simulated smoke surface concentrations, the two models achieve similar levels of accuracy. We present a detailed comparison between the performance and relative strengths of both approaches, and discuss potential refinements that could further improve future simulations of wildfire smoke. Finally, we characterize the interactions between smoke and meteorology during this event, and discuss the implications that increases in regional smoke may have on future meteorological conditions.

     
    more » « less
  5. Abstract

    In the Western US, area burned and fire size have increased due to the influences of climate change, long-term fire suppression leading to higher fuel loads, and increased ignitions. However, evidence is less conclusive about increases in fire severity within these growing wildfire extents. Fires burn unevenly across landscapes, leaving islands of unburned or less impacted areas, known as fire refugia. Fire refugia may enhance post-fire ecosystem function and biodiversity by providing refuge to species and functioning as seed sources after fires. In this study, we evaluated whether the proportion and pattern of fire refugia within fire events have changed over time and across ecoregions. To do so, we processed all available Landsat 4–9 satellite imagery to identify fire refugia within the boundaries of large wildfires (405 ha+) in 16 forested ecoregions of the Western US. We found a significant change in % refugia from 1986–2021 only in one ecoregion—% refugia increased within fires in the Arizona/New Mexico Mountain ecoregion (AZ/NM). Excluding AZ/NM, we found no significant change in % refugia across the study area. Furthermore, we found no significant change in mean refugia patch size, patch density, or mean distance to refugia. As fire size increased, the amount of refugia increased proportionally. Evidence suggests that fires in AZ/NM had a higher proportion of reburns and, unlike the 15 other ecoregions, fires did not occur at higher elevation or within greener areas. We suggest several possibilities for why, with the exception of AZ/NM, ecoregions did not experience a significant change in the proportion and pattern of refugia. In summary, while area burned has increased over the past four decades, there are substantial and consistent patterns of refugia that could support post-fire recovery dependent on their spatial patterns and ability to function as seeds sources for neighboring burned patches.

     
    more » « less