Current and future patterns of forest fire occurrence in China
Zhiwei Wu A B C J , Hong S. He D E , Robert E. Keane F , Zhiliang Zhu G , Yeqiao Wang H and Yanlong Shan I J
+ Author Affiliations
- Author Affiliations
A Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China.
B School of Geography and Environment, Jiangxi Normal University, Nanchang 330022, China.
C Jiangxi Provincial Key Laboratory of Poyang Lake Comprehensive Management and Resource Development, Jiangxi Normal University, Nanchang 330022, China.
D School of Natural Resources, University of Missouri–Columbia, Columbia, MO 65211-7270, USA.
E School of Geographic Sciences, Northeast Normal University, Changchun 130024, China.
F USDA Forest Service, Rocky Mountain Research Station, Missoula Fire Sciences Laboratory, Missoula, MT 59808, USA.
G US Geological Survey, Reston, VA 20192, USA.
H Department of Natural Resources Science, University of Rhode Island, Kingston, RI 02881, USA.
I Forestry College, Beihua University, Jilin 132013, China.
J Corresponding authors. Email: wuzhiwei@jxnu.edu.cn; shanyl@163.com
International Journal of Wildland Fire 29(2) 104-119 https://doi.org/10.1071/WF19039
Submitted: 23 March 2019 Accepted: 27 October 2019 Published: 26 November 2019
Abstract
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.
Additional keywords: boosted regression trees, fire probability, MODIS, relative importance.
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