Development of customized fire behavior fuel models for boreal forests of northeastern China

Environ Manage. 2011 Dec;48(6):1148-57. doi: 10.1007/s00267-011-9707-3. Epub 2011 Jun 21.

Abstract

Knowledge of forest fuels and their potential fire behavior across a landscape is essential in fire management. Four customized fire behavior fuel models that differed significantly in fuels characteristics and environmental conditions were identified using hierarchical cluster analysis based on fuels data collected across a boreal forest landscape in northeastern China. Fuel model I represented the dense and heavily branched Pinus pumila shrubland which has significant fine live woody fuels. These forests occur mainly at higher mountain elevations. Fuel model II is applicable to forests dominated by Betula platyphylla and Populus davidiana occurring in native forests on hill slopes or at low mountain elevations. This fuel model was differentiated from other fuel models by higher herbaceous cover and lower fine live woody loading. The primary coniferous forests dominated by Larix gmelini and Pinus sylvestris L. var. mongolica were classified as fuel model III and fuel model IV. Those fuel models differed from one another in average cover and height of understory shrub and herbaceous layers as well as in aspect. The potential fire behavior for each fuel model was simulated with the BehavePlus5.0 fire behavior prediction system. The simulation results indicated that the Pinus pumila shrubland fuels had the most severe fire behavior for the 97th percentile weather condition, and had the least severe fire behavior under 90th percentile weather condition. Fuel model II presented the least severe fire potential across weather conditions. Fuel model IV resulted in greater fire severity than Fuel model III across the two weather scenarios that were examined.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China
  • Conservation of Natural Resources
  • Disasters / prevention & control
  • Fires / prevention & control*
  • Forestry / methods
  • Models, Theoretical
  • Trees*
  • Weather