State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Department of Plant Nutrition, Sanya Institute of China Agricultural University, 572025 Sanya, China
Tingyao Cai
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Xingshuai Tian
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Zhong Chen
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Kai He
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Zihan Wang
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Haiqing Gong
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Qi Miao
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Yingcheng Wang
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Yiyan Chu
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
Minghao Zhuang
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
State Key Laboratory of Nutrient Use and Management, College of Resources and Environmental Sciences, China Agricultural University, 100193 Beijing, China
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4,562
1,114
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6,137
425
132
210
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PDF: 1,114
XML: 461
Total: 6,137
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BibTeX: 132
EndNote: 210
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Cumulative views and downloads
(calculated since 15 Jul 2024)
Total article views: 4,248 (including HTML, PDF, and XML)
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EndNote
3,369
772
107
4,248
245
84
120
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PDF: 772
XML: 107
Total: 4,248
Supplement: 245
BibTeX: 84
EndNote: 120
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Cumulative views and downloads
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Total article views: 1,889 (including HTML, PDF, and XML)
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1,193
342
354
1,889
180
48
90
HTML: 1,193
PDF: 342
XML: 354
Total: 1,889
Supplement: 180
BibTeX: 48
EndNote: 90
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Total article views: 6,137 (including HTML, PDF, and XML)
Thereof 6,036 with geography defined
and 101 with unknown origin.
Total article views: 4,248 (including HTML, PDF, and XML)
Thereof 4,218 with geography defined
and 30 with unknown origin.
Total article views: 1,889 (including HTML, PDF, and XML)
Thereof 1,818 with geography defined
and 71 with unknown origin.
Accurately quantifying the distribution of soil profile SOC (soil organic carbon) stocks is crucial for carbon sequestration and mitigation. The detailed spatial subsoil SOC data are the scientific basis for environmental protection, as well as for the development of Earth system models. Based on multiple environmental variables and soil profile data, this study used machine learning approaches to evaluate the SOC stocks and their spatial distribution at a depth interval of 20–100 cm in various ecosystems.
Accurately quantifying the distribution of soil profile SOC (soil organic carbon) stocks is...
