Dynamic Changes in and Driving Factors of Soil Organic Carbon in China from 2001 to 2020

Authors:
Open Access
Publisher website
Google Scholar
Abstract
It remains unclear what changes have occurred in the distribution pattern of and trend in soil organic carbon (SOC) in China against the background of climate and land use change. Clarifying the dynamic changes in SOC and their driving factors in different regions of China is therefore crucial for assessing the global carbon cycle. In this study, we collected and supplemented a large amount of soil organic carbon density (SOCD) data in China from 2001 to 2020 and extracted data on environmental covariates (ECs) for the corresponding years. A random forest model was used to estimate the SOCD at a depth of 0–20 cm and 0–100 cm in China for the years 2001, 2005, 2010, 2015, and 2020, and we explored the trend of SOCD changes and their key driving factors. The results showed the following: (1) Compared with previous studies, the predictive ability of the 0–100 cm depth model was greatly improved; the coefficient of determination (R2) was 0.61 and Lin’s concordance correlation coefficient (LCCC) was =0.76. (2) From 2001 to 2020, China’s soil organic carbon stocks (SOCS) were 38.11, 39.11, 39.88, 40.16, and 41.12 Pg C for the 0–20 cm depth and 110.49, 112.67, 112.80, 113.06, and 114.96 Pg C for the 0–100 cm depth, respectively. (3) The effects of temperature and precipitation on SOCD in China showed obvious regional variability, and land use changes had mainly positive effects on SOCD in all regions of China, which was related to the large-scale implementation of ecological protection and restoration and the policy of returning farmland to forests and grasslands in China. This study provides strong scientific support for addressing climate change and rationalizing the use of land resources.
Funding Information
  • China Geological Survey Project, the Ministry of Natural Resources (DD20220877(ZD20220133), DD20220879, AD20297090, [2023]10-2302-05)
  • Guangxi Science and Technology Base and Talent Project (DD20220877(ZD20220133), DD20220879, AD20297090, [2023]10-2302-05)
  • Science and Technology Innovation Project of Kunming General Survey of Natural Resources Center China Geological Survey (DD20220877(ZD20220133), DD20220879, AD20297090, [2023]10-2302-05)

This publication has 86 references indexed in Scilit: