Unraveling the drivers and synergistic mechanisms of selenium distribution in cultivated soils across China: A quantitative analysis using explainable machine learning
文献类型：期刊论文
| 作者 | Wang, Jing2,5; Zhong, Chuanliang2; Shang, Cailing2; Wei, Binggan1; Wu, Ye3; Li, Hairong1,4; Yang, Linsheng1,4 |
| 刊名 | JOURNAL OF HAZARDOUS MATERIALS
 |
| 出版日期 | 2026-04-01 |
| 卷号 | 507页码:141790 |
| 关键词 | Selenium Cultivated soil Spatial distribution Environmental drivers Explainable machine learning |
| ISSN号 | 0304-3894 |
| DOI | 10.1016/j.jhazmat.2026.141790 |
| 产权排序 | 3 |
| 文献子类 | Article |
| 英文摘要 | Selenium (Se) is an essential yet potentially toxic micronutrient for human health, and its distribution in cultivated soils is fundamentally linked to ecosystem safety. This study evaluated the spatial distribution of Se in China's surface cultivated soils by integrating a reviewed database with field surveys. Using random forestShapley additive explanations and structural equation modeling, we analyzed 22 environmental factors to identify the dominant drivers and their interactive mechanisms. The results showed that the mean Se content of cultivated soil in China was 0.283 mg & sdot;kg-1, with a coefficient of variation of 51.6%. Although the classic spatial pattern persists, Se-sufficient and Se-rich soils have expanded markedly, covering 55.6% and 19.8% of the total area, respectively. Mean annual precipitation (MAP), aridity index (AI), net primary productivity (NPP), and evapotranspiration (ET) emerged as the primary determinants, confirming the predominant role of climate at the national scale. Notably, substantial interaction effects were observed between >= 0 degrees C accumulative temperature (ATT0) and MAP, and between ATT0 and AI, highlighting that hydrothermal interactions exert primary control on soil Se distribution. Additional climate-soil couplings, specifically AI with pH, and AI with cation exchange capacity (CEC), further reinforced this spatial differentiation. Furthermore, NPP served as a key biogeochemical intermediary, with its biologically driven pathway exerting a greater total effect on soil Se than that mediated by soil properties. This work provides quantitative evidence of the key drivers shaping Se distribution in cultivated topsoils across China and offers practical guidance for the sustainable soil Se management and public nutritional health protection. |
| URL标识 | 查看原文 |
| WOS关键词 | BIOAVAILABILITY ; ACCUMULATION ; HEALTH |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:001722337900001 |
| 出版者 | ELSEVIER |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/221279]  |
| 专题 | 陆地表层格局与模拟院重点实验室_外文论文 |
| 通讯作者 | Wang, Jing; Wei, Binggan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China; 2.Cent China Normal Univ, Res Inst Sustainable Dev, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China; 3.Minist Ecol & Environm Peoples Republ China, South China Inst Environm Sci, Guangzhou 510665, Peoples R China 4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China; 5.Cent China Normal Univ, Hubei Jianghan Plain Sci Observat & Res Stn Farmla, Wuhan 430079, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Wang, Jing,Zhong, Chuanliang,Shang, Cailing,et al. Unraveling the drivers and synergistic mechanisms of selenium distribution in cultivated soils across China: A quantitative analysis using explainable machine learning[J]. JOURNAL OF HAZARDOUS MATERIALS,2026,507:141790. |
| APA | Wang, Jing.,Zhong, Chuanliang.,Shang, Cailing.,Wei, Binggan.,Wu, Ye.,...&Yang, Linsheng.(2026).Unraveling the drivers and synergistic mechanisms of selenium distribution in cultivated soils across China: A quantitative analysis using explainable machine learning.JOURNAL OF HAZARDOUS MATERIALS,507,141790. |
| MLA | Wang, Jing,et al."Unraveling the drivers and synergistic mechanisms of selenium distribution in cultivated soils across China: A quantitative analysis using explainable machine learning".JOURNAL OF HAZARDOUS MATERIALS 507(2026):141790. |
入库方式： OAI收割
来源：地理科学与资源研究所
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