Recent large-scale prescribed fire treatments reduced Carr Fire severity at Whiskeytown National Recreation Area

  • Jill J. Beckmann
  • , Phillip J. van Mantgem
  • , Micah Wright
  • , Eamon Engber

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Severe fire weather is becoming more common throughout the western United States. Changing conditions demand a better understanding of how prescribed fire treatments perform under extreme burning conditions, including the interactive influence of the age of treatments, vegetation, and fire weather. The Carr Fire of July 2018 burned nearly the entire land area of Whiskeytown National Recreation Area (NRA) under extreme fuel moisture and temperature conditions. Prior to the Carr Fire and since 1997, staff at Whiskeytown NRA treated 23% of the 15,756-ha NRA using large-scale prescribed fire (underburn) treatments ranging in size from 40 to 400 hectares. Methods: We used simultaneous autoregressive (SAR) models to describe the effects of landscape-scale fuel treatments on wildfire severity under extreme burning conditions and across diverse biophysical settings at Whiskeytown NRA. Because vegetation type and structure are known drivers of fire severity in diverse ecosystems such as at Whiskeytown NRA, we also considered three different sources of vegetation structure data, including a 2006 physiognomic-floristic classification, a 2011 lidar-based forest structure classification, and a 2016 Landfire map of existing vegetation physiognomy-subclass. Results: The greatest effect on 2018 Carr Fire severity was time since treatment of underburn treatments, but treatment effectiveness on fire severity dissipated rapidly—showing notable effectiveness within 5 years of underburning but virtually no effectiveness beyond 10 years post-treatment. Additional factors related to severity included vegetation structure type, topographic position index, aspect, slope, temperature, and wind gust speed. Model variance explained and model parameters, including the effect of underburn treatments, were similar regardless of the source of vegetation structure data. Conclusions: Our results show that large-scale underburning treatments can reduce wildfire severity even under extreme fire weather conditions but suggest that frequent maintenance intervals are required to maintain treatment effectiveness ahead of severe wildfire events.
Original languageEnglish (US)
JournalFire Ecology
Volume21
Issue number1
DOIs
StatePublished - Jan 2025

Keywords

  • Coniferous forests
  • Extreme fire weather
  • Fire severity
  • Fuel treatments
  • Klamath Mountains
  • Lidar
  • Simultaneous autoregressive model
  • Underburning
  • Vegetation
  • Wildland fire

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