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Journal Article

Citation

Coen JL, Stavros EN, Fites-Kaufman JA. Ecol. Appl. 2018; 28(6): 1565-1580.

Affiliation

Pacific Southwest Region, USDA Forest Service, 1323 Club Drive Vallejo, CA, 94592.

Copyright

(Copyright © 2018, Ecological Society of America)

DOI

10.1002/eap.1752

PMID

29797684

Abstract

Hypotheses that megafires - very large, high impact fires - are caused by either climate effects such as drought or fuel accumulation due to fire exclusion with accompanying changes to forest structure have long been alleged and guided policy but their physical basis remains untested. Here, unique airborne observations and microscale simulations using a coupled weather - wildland fire behavior model allowed a recent megafire, the King Fire, to be deconstructed and the relative impacts of forest structure, fuel load, weather, and drought on fire size, behavior, and duration to be separated. Simulations reproduced observed details including the arrival at an inclined canyon, a 25-km run, and later slower growth and features. Analysis revealed that fire-induced winds that equaled or exceeded ambient winds and fine-scale airflow undetected by surface weather networks were primarily responsible for the fire's rapid growth and size. Sensitivity tests varied fuel moisture and amount across wide ranges and showed that both drought and fuel accumulation effects were secondary, limited to sloped terrain where they compounded each other, and, in this case, unable to significantly impact the final extent. Compared to standard data, fuel models derived solely from remote sensing of vegetation type and forest structure improved simulated fire progression, notably in disturbed areas, and the distribution of burn severity. These results point to self-reinforcing internal dynamics rather than external forces as a means of generating this and possibly other outlier fire events. Hence, extreme fires need not arise from extreme fire environment conditions. Kinematic models used in operations do not capture fire-induced winds and dynamic feedbacks so can underestimate megafire events. The outcomes provided a nuanced view of weather, forest structure, fuel accumulation, and drought impacts on landscape-scale fire behavior - roles that can be misconstrued using correlational analyses between area burned and macroscale climate data or other exogenous factors. A practical outcome is that fuel treatments should be focused on sloped terrain, where factors multiply, for highest impact. This article is protected by copyright. All rights reserved.

This article is protected by copyright. All rights reserved.


Language: en

Keywords

LiDAR; coupled atmosphere - fire model; fire behavior; fire model; multiple plumes; numerical weather prediction; pyrocumulus; wildfire; wildland fire

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