Anthropogenic controls over soil organic carbon distribution from the cultivated lands in Northeast China
文献类型:期刊论文
作者 | Wang, Shuai1,2; Zhou, Mingyi1; Adhikari, Kabindra5; Zhuang, Qianlai4; Bian, Zhenxing1; Wang, Yan3; Jin, Xinxin1 |
刊名 | CATENA
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出版日期 | 2022-03-01 |
卷号 | 210页码:11 |
关键词 | Agroecosystem Anthropogenic variable Digital soil mapping Soil organic carbon Spatial variation |
ISSN号 | 0341-8162 |
DOI | 10.1016/j.catena.2021.105897 |
通讯作者 | Jin, Xinxin(jinxinxin0218@syau.edu.cn) |
英文摘要 | Both natural and anthropogenic variables affect soil C distribution and its pool, however studies about anthropogenic influence on soil C distribution are very limited in the literature. This study investigated anthropogenic effects on soil organic carbon (SOC) changes in the cultivated lands of Northeast China. A total of 196 topsoil samples (0-30 cm) were collected, and analyzed for SOC content, and 12 environmental variables (natural and anthropogenic) were selected as SOC predictors. Natural factors included elevation, slope gradient, slope aspect (SA), topographic wetness index (TWI), mean annual temperature, mean annual precipitation, and normalized difference vegetation index, while population (POP), gross domestic product (GDP), distance to the socioeconomic center, distance to roads, and reclamation period (PER) represented anthropogenic variables. Three different boosted-regression trees models with different combination of SOC predictors were constructed, and the model performance was evaluated with 10-fold cross-validation. We found that the model that included all predictors had the best performance, followed by the model with topography and climate variables, and the model with only anthropogenic variables. However, adding the anthropogenic variables in the model greatly improved its performance. Results showed that PER, POP and GDP were the key environmental variables affecting SOC content in the topsoil agroecosystems in Northeast China. This study suggests that anthropogenic variables should be selected as the main environmental variable in predicting of SOC content in agroecosystem with a higher human influence. We believe that the accurate prediction and mapping of SOC content in the topsoil agroecosystem will help formulate farmland soil management policies and promote soil carbon sequestration. |
WOS关键词 | CLIMATE-CHANGE ; STOCKS ; REGRESSION ; DYNAMICS ; IMPACTS |
资助项目 | China Postdoctoral Science Foundation[2019M660782] ; National Science and Technology Basic Resources Survey Program of China[2019FY101300] ; Young Scientific and Technological Talents Project of Liaoning Province[LSNQN201910] ; Young Scientific and Technological Talents Project of Liaoning Province[LSNQN201914] |
WOS研究方向 | Geology ; Agriculture ; Water Resources |
语种 | 英语 |
WOS记录号 | WOS:000790439200002 |
出版者 | ELSEVIER |
资助机构 | China Postdoctoral Science Foundation ; National Science and Technology Basic Resources Survey Program of China ; Young Scientific and Technological Talents Project of Liaoning Province |
源URL | [http://ir.igsnrr.ac.cn/handle/311030/176226] ![]() |
专题 | 中国科学院地理科学与资源研究所 |
通讯作者 | Jin, Xinxin |
作者单位 | 1.Shenyang Agr Univ, Coll Land & Environm, 120 Dongling Rd, Shenyang 110866, Liaoning, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 3.Jiujiang Univ, Coll Tourism & Geog, Jiujiang 332005, Peoples R China 4.Purdue Univ, Dept Earth Atmospher & Planetary Sci, W Lafayette, IN 47907 USA 5.USDA ARS, Soil & Water Res Lab, Temple, TX 76502 USA |
推荐引用方式 GB/T 7714 | Wang, Shuai,Zhou, Mingyi,Adhikari, Kabindra,et al. Anthropogenic controls over soil organic carbon distribution from the cultivated lands in Northeast China[J]. CATENA,2022,210:11. |
APA | Wang, Shuai.,Zhou, Mingyi.,Adhikari, Kabindra.,Zhuang, Qianlai.,Bian, Zhenxing.,...&Jin, Xinxin.(2022).Anthropogenic controls over soil organic carbon distribution from the cultivated lands in Northeast China.CATENA,210,11. |
MLA | Wang, Shuai,et al."Anthropogenic controls over soil organic carbon distribution from the cultivated lands in Northeast China".CATENA 210(2022):11. |
入库方式: OAI收割
来源:地理科学与资源研究所
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