Soil carbon sequestration potential of cultivated lands and its controlling factors in China

被引:3
|
作者
Wang, Shuai [1 ,2 ,4 ]
Xu, Li [1 ,3 ,4 ,6 ]
Adhikari, Kabindra [5 ]
He, Nianpeng [1 ,3 ,4 ]
机构
[1] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China
[2] Shenyang Agr Univ, Coll Land & Environm, Shenyang 110866, Liaoning, Peoples R China
[3] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
[4] Chinese Acad Sci, Earth Crit Zone & Flux Res Stn Xingan Mt, Daxinganling 165200, Peoples R China
[5] USDA ARS, Grassland Soil & Water Res Lab, Temple, TX 76502 USA
[6] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China
基金
中国国家自然科学基金;
关键词
Carbon sequestration; Machine learning; Cultivated lands; Environmental variable; Spatial variation; Anthropogenic factors; ORGANIC-MATTER CONTENT; CLIMATE-CHANGE; STOCKS; PRODUCTIVITY; TOPOGRAPHY; MANAGEMENT; PATTERNS; MODEL; CROPLAND; IMPACTS;
D O I
10.1016/j.scitotenv.2023.167292
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Understanding soil organic carbon (SOC) stocks and carbon sequestration potential in cultivated lands can have significant benefit for mitigating climate change and emission reduction. However, there is currently a lack of spatially explicit information on this topic in China, and our understanding of the factors that influence both saturated SOC level (SOCS) and soil organic carbon density (SOCD) remains limited. This study predicted SOCS and SOCD of cultivated lands across mainland China based on point SOC measurements, and mapped its spatial distribution using environmental variables as predictors. Based on the differentiation between SOCS and SOCD, the soil organic carbon sequestration potentials (SOCP) of cultivated land were calculated. Boosted regression trees (BRT), random forest (RF), and support vector machine (SVM) were evaluated as prediction models, and the RF model presented the best performance in predicting SOCS and SOCD based on 10-fold cross-validation. A total of 991 topsoil (0-20 cm) SOC measurements and 12 environmental variables explaining topography, climate, organism, soil properties, and human activity were used as predictors in the model. Both SOCS and SOCD suggested higher SOC levels in northeast China and lower levels in central China. The cultivated lands in China had the potential to sequester about 2.13 +/- 0.96 kg m- 2 (3.25 Pg) SOC in the top 20 cm soil depth. Northeastern China had the largest SOCP followed by Northern China, and Southwestern China had the lowest SOCP. The primary environmental variables that affected the spatial variation of SOCS were mean annual temperature, followed by clay content and normalized difference vegetation index (NDVI). The assessment and mapping of SOCP in China's cultivated lands holds significance importance as it can provide valuable insights to policy makers and researchers about SOCP, and aid in formulating climate change mitigation strategies.
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收藏
页数:11
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