Natural and anthropogenic influences on short-term forest growth status: Evidence and mechanisms from China.

Journal: Journal of environmental management
Published Date: Jun 4, 2025

Abstract

The relationship between forest growth and natural-anthropogenic drivers remains controversial, and the relative importance of these factors on short-term forest growth at large scales still unclear. This uncertainty hinders the development of effective forest sustainable protection and management strategies. We constructed a new Forest Growth Status Index (FGSI) and used an interpretable machine learning model to reveal the spatial distribution pattern of forest growth in China to analyze the influence of natural and anthropogenic factors on short-term forest growth. We found the forest growth status in China showed increasing trend over approximately 1.17 million km (44 %) and a decreasing trend over about 1.49 million km (56 %) between 2017 and 2020. The decrease area of FGSI followed a spatially clustered pattern, whereas the increase area exhibited a more dispersed pattern. The three factors with the strongest explanatory power for the decreasing FGSI in China were: mean precipitation (SHAP = 0.14), population density (SHAP = 0.11), and evapotranspiration change (SHAP = 0.10). Conversely, the factors with the strongest explanatory power for the increasing FGSI were: human footprint (SHAP = 0.12), mean precipitation (SHAP = 0.08), and elevation (SHAP = 0.08). FGSI cold spots areas were primarily influenced by anthropogenic factors, such as population density and human footprint, hot spots areas were mainly influenced by natural factors, such as mean precipitation. We call for further research into the monitoring of short-term forest growth and its drivers, to provide a scientific basis for the conservation and sustainable development of forest ecosystems.

Authors

  • Zhenglin Tian
    Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education, Edmond Fischer Cell Signaling Laboratory, School of Life Sciences, Jilin University, Changchun 130012, China.
  • Chengyuan Wang
    School of Forestry, Northeast Forestry University, Harbin, 150040, China; Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, 150040, China.
  • Tongpeng Wang
    School of Forestry, Northeast Forestry University, Harbin, 150040, China; Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, 150040, China.
  • Zian Liu
    School of Forestry, Northeast Forestry University, Harbin, 150040, China; Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, 150040, China; School of Future Technology, Northeast Forestry University, Harbin, 150040, China.
  • Longxin Ding
    School of Forestry, Northeast Forestry University, Harbin, 150040, China; Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, 150040, China.
  • Xuegang Mao
    School of Forestry, Northeast Forestry University, Harbin, 150040, China; Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, Northeast Forestry University, Harbin, 150040, China; Research and Development Center of Big Data for Ecosystem, Northeast Forestry University, Harbin, 150040, China. Electronic address: maoxuegang@nefu.edu.cn.

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