College of Land and Environment, Shenyang Agricultural University, Shenyang, Liaoning Province 110866, China; Key Laboratory Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China.
Key Laboratory Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China.
Sci Total Environ. 2021 Mar 1;758:143644. doi: 10.1016/j.scitotenv.2020.143644. Epub 2020 Nov 20.
Soil organic carbon (SOC) significantly influences soil fertility, soil water holding capacity, and plant productivity. In this study, we applied two boosted regression tree (BRT) models to map SOC stocks across China in the 1980s and the 2010s. The models incorporated nine environmental variables (climate, topography, and biology) and 8897 (in the 1980s) and 4534 (in the 2010s) topsoil (0-20 cm) samples. During the two study periods, 20% of the soil samples were randomly selected for model testing, and the remaining samples were used as a training set to construct the models. The verification results showed that incorporating climate environment variables significantly improved the model prediction in both study periods. Mean annual temperature, mean annual precipitation, elevation, and the normalized difference vegetation index were the dominant environmental factors affecting the spatial distribution of SOC stocks. The full-variable model predicted similar spatial distributions of SOC stocks for the 1980s and the 2010s. SOC stocks in China showed an increasing trend over the past 30 years, from 3.9 kg m in the 1980s to 4.6 kg m in the 2010s. In both periods, topsoil SOC stocks were mainly stored in agroecosystems, forests, and grasslands in the 1980s, with values of 9.5, 12.0, and 11.4 Pg C, respectively. Our study provides reliable information on Chain's carbon distribution, which can be used by land managers and the national government to formulate relevant land use and carbon sequestration policies.
土壤有机碳（SOC）对土壤肥力、土壤持水能力和植物生产力有显著影响。本研究应用两种提升回归树（BRT）模型，对中国 20 世纪 80 年代和 2010 年代的 SOC 储量进行制图。模型纳入了九个环境变量（气候、地形和生物）和 8897 个（20 世纪 80 年代）和 4534 个（2010 年代）表土（0-20cm）样本。在两个研究期间，20%的土壤样本被随机选择用于模型测试，其余样本被用作训练集来构建模型。验证结果表明，在两个研究期间纳入气候环境变量显著提高了模型预测能力。年均温、年均降水量、海拔和归一化差异植被指数是影响 SOC 储量空间分布的主要环境因素。全变量模型预测了 20 世纪 80 年代和 2010 年代 SOC 储量的相似空间分布。过去 30 年来，中国的 SOC 储量呈上升趋势，从 20 世纪 80 年代的 3.9kg·m-2 增加到 2010 年代的 4.6kg·m-2。在这两个时期，表土 SOC 储量主要储存在农业生态系统、森林和草地中，分别为 9.5、12.0 和 11.4Pg·C。本研究提供了可靠的 Chain 碳分布信息，可被土地管理者和国家政府用于制定相关土地利用和碳固存政策。
