中国
土壤碳
环境科学
空间分布
分布(数学)
自然地理学
碳纤维
土壤科学
地理
土壤水分
遥感
数学
考古
算法
复合数
数学分析
作者
Shihang Zhang,Yusen Chen,Shihang Zhang,Zhu Bo
摘要
Abstract Soil organic carbon (SOC) pool of cropland is one of the most active parts of the global C pool. Hence, it is important to estimate cropland SOC stock, drivers, and future evolutionary trends in order to improve the C sequestration and emission reduction capacity of cropland soil and stability of food production. In this study, we utilized 856 samples for SOC density (SOCD) at a depth of 0–20 cm and 544 samples for SCOD at 0–100 cm. Using five machine learning models combined with environmental factors data, we predicted the spatial distribution, key drivers, and future trends of SOC in China's croplands. The results were as follows: (1) The mean values of SOCD 0–20 cm and SOCD 0–100 cm were 2.98 and 7.88 kg m −2 , respectively, and the stocks were 5.64 and 14.91 Pg, which accounted for 15.78% and 17.25% of the SOC stocks in terrestrial ecosystems, respectively. (2) Soil physicochemical properties consistently explained more of the spatial variation in SOCD uniquely than other factors, explaining 50% and 43% of the spatial variation in SOCD 0–20 cm and SOCD 0–100 cm , respectively. SOCD 0–20 cm was mainly driven by nitrogen deposition and human impacts; SOCD 0–100 cm was mainly driven by pH, normalized difference vegetation index, mean annual precipitation, and mean annual temperature. (3) Under Shared Socioeconomic Pathway 5–8.5 (high‐C emissions), the greatest decline trend of cropland two‐depth SOC stock. Our study is important for understanding global changes in cropland soil C stocks and in enhancing human capacity to implement mitigation and adaptation strategies.
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