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Type: Journal Article
Author(s): Zhiwei Wu; Hong S. He; Robert E. Keane II; Zhiliang Zhu; Yeqiao Wang; Yanlong Shan
Publication Date: 2020

Forest fire patterns are likely to be altered by climate change. We used boosted regression trees modelling and the MODIS Global Fire Atlas dataset (2003-15) to characterise relative influences of nine natural and human variables on fire patterns across five forest zones in China. The same modelling approach was used to project fire patterns for 2041-60 and 2061-80 based on two general circulation models for two representative concentration pathways scenarios. The results showed that, for the baseline period (2003-15) and across the five forest zones, climate variables explained 37.4-43.5% of the variability in fire occurrence and human activities were responsible for explaining an additional 27.0-36.5% of variability. The fire frequency was highest in the subtropical evergreen broadleaf forests zone in southern China, and lowest in the warm temperate deciduous broadleaved mixed-forests zone in northern China. Projection results showed an increasing trend in fire occurrence probability ranging from 43.3 to 99.9% and 41.4 to 99.3% across forest zones under the two climate models and two representative concentration pathways scenarios relative to the current climate (2003–15). Increased fire occurrence is projected to shift from southern to central-northern China for both 2041-60 and 2061-80.

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Citation: Wu, Zhiwei; He, Hong S.; Keane, Robert E.; Zhu, Zhiliang; Wang, Yeqiao; Shan, Yanlong. 2020. Current and future patterns of forest fire occurrence in China. International Journal of Wildland Fire 29(2):104-119.

Cataloging Information

Topics:
Regions:
Keywords:
  • boosted regression trees
  • China
  • fire frequency
  • fire patterns
  • fire probability
  • human impact
  • MODIS - Moderate Resolution Imaging Spectroradiometer
  • relative importance
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Record Maintained By: FRAMES Staff (https://www.frames.gov/contact)
FRAMES Record Number: 60748