Spatial variability characteristics and drivers of surface soil nitrogen fractions in the drylands of northern China
文献类型:期刊论文
| 作者 | Zhang, Shihang2,3; Chen, Yusen1,2; Zhou, Xiaobing1; Zhang, Yuanming1 |
| 刊名 | JOURNAL OF ARID LAND
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| 出版日期 | 2025-11-01 |
| 卷号 | 17期号:11页码:1558-1575 |
| 关键词 | soil nitrogen fractions total nitrogen (TN) inorganic nitrogen (IN) microbial biomass nitrogen (MBN) machine learning model eXtreme Gradient Boosting (XGBoost) model dryland ecosystems |
| ISSN号 | 1674-6767 |
| DOI | 10.1007/s40333-025-0065-z |
| 英文摘要 | In dryland ecosystems, nitrogen (N) is the primary limiting factor after water availability, constraining both plant productivity and organic matter decomposition while also regulating ecosystem function and service provision. However, the distributions of different soil N fraction stocks in drylands and the factors that influence them remain poorly understood. In this study, we collected 2076 soil samples from 173 sites across the drylands of northern China during the summers of 2021 and 2022. Using the best-performing eXtreme Gradient Boosting (XGBoost) model, we mapped the spatial distributions of the soil N fraction stocks and identified the key drivers of their variability. Our findings revealed that the stocks of total nitrogen (TN), inorganic nitrogen (IN), and microbial biomass nitrogen (MBN) in the top 30 cm soil layer were 1020.4, 92.2, and 40.8 Tg, respectively, with corresponding mean densities of 164.6, 14.9, and 6.6 g/m2. Climate variables-particularly mean annual temperature and aridity-along with human impacts emerged as the dominant drivers of soil N stock distribution. Notably, increased aridity and intensified human impacts exerted mutually counteracting effects on soil N fractions: aridity-driven moisture limitation generally suppressed N accumulation, whereas anthropogenic activities (e.g., fertilization and grazing) promoted N enrichment. By identifying the key environmental and anthropogenic factors shaping the soil N distribution, this study improves the accuracy of regional and global N stock estimates. These insights provide a scientific foundation for developing more effective soil N management strategies in dryland ecosystems, contributing to sustainable land use and long-term ecosystem resilience in drylands. |
| WOS关键词 | LOESS PLATEAU REGION ; ORGANIC-CARBON ; LAND-USE ; TEMPERATURE SENSITIVITY ; ECOSYSTEM SERVICES ; MINERALIZATION ; STORAGE ; BIOMASS ; GRASSLAND ; PATTERNS |
| 资助项目 | Xinjiang Outstanding Youth Fund[2021D01E03] ; Natural Science Foundation of Xinjiang Uygur Autonomous Region[2022D01D083] ; National Natural Science Foundation of China[U2003214] ; National Natural Science Foundation of China[41977099] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001619216900005 |
| 出版者 | SPRINGER HEIDELBERG |
| 资助机构 | Xinjiang Outstanding Youth Fund ; Natural Science Foundation of Xinjiang Uygur Autonomous Region ; National Natural Science Foundation of China |
| 源URL | [http://ir.imde.ac.cn/handle/131551/59331] ![]() |
| 专题 | 中国科学院水利部成都山地灾害与环境研究所 |
| 通讯作者 | Zhou, Xiaobing |
| 作者单位 | 1.Chinese Acad Sci, Xinjiang Inst Ecol & Geog, State Key Lab Ecol Safety & Sustainable Dev Arid, Urumqi 830011, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Key Lab Mt Surface Proc & Ecol Regulat, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Shihang,Chen, Yusen,Zhou, Xiaobing,et al. Spatial variability characteristics and drivers of surface soil nitrogen fractions in the drylands of northern China[J]. JOURNAL OF ARID LAND,2025,17(11):1558-1575. |
| APA | Zhang, Shihang,Chen, Yusen,Zhou, Xiaobing,&Zhang, Yuanming.(2025).Spatial variability characteristics and drivers of surface soil nitrogen fractions in the drylands of northern China.JOURNAL OF ARID LAND,17(11),1558-1575. |
| MLA | Zhang, Shihang,et al."Spatial variability characteristics and drivers of surface soil nitrogen fractions in the drylands of northern China".JOURNAL OF ARID LAND 17.11(2025):1558-1575. |
入库方式: OAI收割
来源:成都山地灾害与环境研究所
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