Forest disturbance decreased in China from 1986 to 2020 despite regional variations - INSU - Institut national des sciences de l'Univers Access content directly
Journal Articles Communications Earth & Environment Year : 2023

Forest disturbance decreased in China from 1986 to 2020 despite regional variations

Zhihua Liu
  • Function : Author
Wen J. Wang
  • Function : Author
Hong S. He
  • Function : Author
Xugao Wang
  • Function : Author
Shuguang Liu
  • Function : Author
Michael C. Wimberly
  • Function : Author
Shilong Piao
  • Function : Author
Qichao Yao
  • Function : Author
Yu Liang
  • Function : Author
Zhiwei Wu
  • Function : Author
Yunting Fang
  • Function : Author
Anping Chen
  • Function : Author
Wenru Xu
  • Function : Author
Jiaojun Zhu
  • Function : Author

Abstract

Human activities have altered disturbance patterns in many parts of world, but there is no quantitative information on patterns and trends of forest disturbance regimes in China. We applied a spectral-temporal segmentation approach over all available Landsat data to map individual disturbance patches and characterize the patterns and trends in disturbance rate, size, frequency, and severity across China's forests. From 1986 to 2020, about 39.7% of China's forests were disturbed with an annual rate of 1.16 ± 0.41% yr−1. The disturbance decreased at a rate of −390 ± 142 km2 yr−1, primarily driven by the effective implementation of forest protection policy since 2000s. The rate, frequency, and size of disturbance generally intensified in Southeast, but weakened in Northeast China. Our high-quality, spatially explicit disturbance map provides an essential data layer to understand the landscape-scale drivers of forest dynamics and functions for important but less understood pan-temperate forest regions.
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Dates and versions

insu-03993148 , version 1 (16-02-2023)

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Zhihua Liu, Wen J. Wang, Ashley Ballantyne, Hong S. He, Xugao Wang, et al.. Forest disturbance decreased in China from 1986 to 2020 despite regional variations. Communications Earth & Environment, 2023, 4, ⟨10.1038/s43247-023-00676-x⟩. ⟨insu-03993148⟩
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