期刊
INTERNATIONAL JOURNAL OF WILDLAND FIRE
卷 29, 期 2, 页码 104-119出版社
CSIRO PUBLISHING
DOI: 10.1071/WF19039
关键词
boosted regression trees; fire probability; MODIS; relative importance
类别
资金
- National Natural Science Foundation of China [31570462]
- Scientific and Technological Research Project of Jiangxi Provincial Department of Education [GJJ160275]
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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