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Title: Temporal and spatial pattern analysis of escaped prescribed fires in California from 1991 to 2020
Abstract BackgroundPrescribed fires play a critical role in reducing the intensity and severity of future wildfires by systematically and widely consuming accumulated vegetation fuel. While the current probability of prescribed fire escape in the United States stands very low, their consequential impact, particularly the large wildfires they cause, raises substantial concerns. The most direct way of understanding this trade-off between wildfire risk reduction and prescribed fire escapes is to explore patterns in the historical prescribed fire records. This study investigates the spatiotemporal patterns of escaped prescribed fires in California from 1991 to 2020, offering insights for resource managers in developing effective forest management and fuel treatment strategies. ResultsThe results reveal that the months close to the beginning and end of the wildfire season, namely May, June, September, and November, have the highest frequency of escaped fires. Under similar environmental conditions, areas with more records of prescribed fire implementation tend to experience fewer escapes. The findings revealed the vegetation types most susceptible to escaped prescribed fires. Areas with tree cover ranging from 20 to 60% exhibited the highest incidence of escapes compared to shrubs and grasslands. Among all the environmental conditions analyzed, wind speed stands out as the predominant factor that affects the risk of prescribed fire escaping. ConclusionsThese findings mark an initial step in identifying high-risk areas and periods for prescribed fire escapes. Understanding these patterns and the challenges of quantifying escape rates can inform more effective landscape management practices.  more » « less
Award ID(s):
2318718 2335847 2209695 2146520 2114740
PAR ID:
10565544
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
Springer Science + Business Media
Date Published:
Journal Name:
Fire Ecology
Volume:
21
Issue:
1
ISSN:
1933-9747
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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