Extreme Fire Spread Events Burn More Severely and Homogenize Postfire Landscapes in the Southwestern United States

Abstract

Extreme fire spread events rapidly burn large areas with disproportionate impacts on people and ecosystems. Such events are associated with warmer and drier fire seasons and are expected to increase in the future. Our understanding of the landscape outcomes of extreme events is limited, particularly regarding whether they burn more severely or produce spatial patterns less conducive to ecosystem recovery. To assess relationships between fire spread rates and landscape burn severity patterns, we used satellite fire detections to create day-of-burning maps for 623 fires comprising 4267 single-day events within forested ecoregions of the southwestern United States. We related satellite-measured burn severity and a suite of high-severity patch metrics to daily area burned. Extreme fire spread events (defined here as burning > 4900 ha/day) exhibited higher mean burn severity, a greater proportion of area burned severely, and increased like adjacencies between high-severity pixels. Furthermore, increasing daily area burned also resulted in greater distances within high-severity patches to live tree seed sources. High-severity patch size and total high-severity core area were substantially higher for fires containing one or more extreme spread events than for fires without an extreme event. Larger and more homogenous high-severity patches produced during extreme events can limit tree regeneration and set the stage for protracted forest conversion. These landscape outcomes are expected to be magnified under future climate scenarios, accelerating fire-driven forest loss and long-term ecological change.

Keywords: area burned; burn severity; daily fire progression; extreme fire spread events; fast fires; forest resilience; landscape metrics.

FIGURE 1

Map of the southwestern US study area, large (> 400 ha) fire perimeters (2002–2020), and the forested ecoregions included in this analysis (EPA 2023). Map lines delineate study areas and do not necessarily depict accepted national boundaries.

FIGURE 2

Example shows the East Troublesome fire, depicting (a) daily fire progression, (b) categorical fire spread event types, (c) high‐severity burn patches (red), and (d) prefire vegetation with topographic relief. The East Troublesome fire burned 78,000 ha in Colorado in October 2020.

FIGURE 3

Boxplots and scatterplots showing relationships of burn severity and high‐severity patch metrics with daily fire spread event size. We illustrate relationships between either fire spread event types (boxplots in left column) or daily area burned (scatterplots and LME trendlines in right column) with burn severity (A and B; 0.01% subsample), proportion of area burned at high severity (C and D), percentage of like adjacencies of high‐severity areas burned (E and F), and distance to nearest live tree seed source (G and H; 0.01% subsample). Fire spread event categories are defined as common (yellow; ≤ 1285 ha), large (orange; 1286–4900 ha), and extreme (red; > 4900 ha/day) fire spread events based on statistical thresholds across all fires. In boxplots, black diamonds represent mean values. Scatterplots illustrate metrics plotted against daily area burned (ha), with the x‐axis on a log₁₀ scale. Trendlines on scatterplots include 95% confidence intervals.

FIGURE 4

Boxplots and scatterplots showing relationships between fire type, fire spread event size, and landscape metrics of high‐severity patches at the fire level. We illustrate relationships between area‐weighted mean high‐severity patch size (A‐B) and total high‐severity core area (C‐D) with fire spread event types (boxplots in left column) and daily area burned (scatterplots and linear trendlines in right column). Fire type is categorically represented by the boxplots as fires with one or more extreme fire spread events (dark blue; “Extreme Day(s)”) or fires without an extreme fire spread event (light blue; “No Extreme Days”). Central horizontal lines within the boxplots depict median values, black diamonds represent means, and points represent outliers. Geometric means were plotted instead of arithmetic means to account for log₁₀‐transformed Y axes. Scatterplots illustrate metrics plotted against log₁₀‐transformed mean daily area burned (ha). Trendlines on scatterplots include 95% confidence intervals.