Impacts of extreme climate change on terrestrial ecosystem carbon storage in China

Junjie Jin; Haoqi Liu; Junjie Jiang; Hao Huang; Chen Dong; Feng Yu; Chao Zhu; Junguo Hu

doi:10.1016/j.scitotenv.2025.180890

Impacts of extreme climate change on terrestrial ecosystem carbon storage in China

Sci Total Environ. 2025 Nov 20:1005:180890. doi: 10.1016/j.scitotenv.2025.180890. Epub 2025 Nov 8.

Authors

Junjie Jin¹, Haoqi Liu¹, Junjie Jiang¹, Hao Huang¹, Chen Dong¹, Feng Yu², Chao Zhu¹, Junguo Hu³

Affiliations

¹ College of Mathematics and Computer Science, Zhejiang A&F University, 666 Wusu Street, Lin'an District, 311300, Hangzhou, Zhejiang, China; State Forestry Administration Key Laboratory of Forestry Sensing Technology and Intelligent Equipment, Zhejiang A&F University, Hangzhou, Zhejiang, 311300, China; Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology Research, Zhejiang A&F University, Hangzhou, Zhejiang, 311300, China.
² Zhejiang Sifang Group Co., Ltd., Yongkang, Jinhua, Zhejiang, 321300, China.
³ College of Mathematics and Computer Science, Zhejiang A&F University, 666 Wusu Street, Lin'an District, 311300, Hangzhou, Zhejiang, China; State Forestry Administration Key Laboratory of Forestry Sensing Technology and Intelligent Equipment, Zhejiang A&F University, Hangzhou, Zhejiang, 311300, China; Zhejiang Provincial Key Laboratory of Forestry Intelligent Monitoring and Information Technology Research, Zhejiang A&F University, Hangzhou, Zhejiang, 311300, China. Electronic address: hujunguo@zafu.edu.cn.

PMID: 41205264
DOI: 10.1016/j.scitotenv.2025.180890

Abstract

Extreme climatic events are occurring with increasing frequency, posing significant challenges in assessing their impact on terrestrial carbon storage. Based on daily meteorological observations from 1990 to 2019 across China, the trends and abrupt changes in 26 extreme climate indices were systematically analysed using the Theil-Sen estimator and Mann-Kendall test. A random forest regression model was constructed by integrating high-resolution remote sensing, meteorological, and topographic data to predict the spatial distribution of aboveground biomass carbon (AGBC). Furthermore, the XGBoost algorithm combined with Shapley additive explanations (SHAP) was employed to quantify the driving effects of extreme climate indices on AGBC and their spatial heterogeneity. The results reveal that over the past three decades, warm and extreme precipitation events have significantly intensified, whereas cold events have markedly declined. A notable shift in climate occurred between 1998 and 2005. During this period, the AGBC increased steadily, with forests, grasslands, and wetlands exhibiting significant growth. The SHAP analysis identified very wet days (R95pTOT), diurnal temperature range (DTR), annual maximum value of daily minimum temperature (TNx), and annual total precipitation on wet days (PRCPTOT) as the dominant climatic drivers of AGBC variation. Their ecological impacts demonstrated strong nonlinear responses and spatial differentiation. In humid eastern regions, these factors generally enhanced carbon sequestration, whereas in arid and high-altitude western regions, they may exert inhibitory effects. This study provides robust quantitative evidence for understanding the complex, nonlinear interactions between extreme climate events and ecosystem carbon dynamics and offers scientific guidance for regional carbon sink management and climate adaptation strategies to support the dual carbon goals of China.

Keywords: Aboveground biomass carbon; Extreme climate events; Random forest; Shapley additive explanations; XGBoost.