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
Viewed
Total article views: 4,616 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
3,621
601
394
4,616
218
99
166
HTML: 3,621
PDF: 601
XML: 394
Total: 4,616
Supplement: 218
BibTeX: 99
EndNote: 166
Views and downloads (calculated since 15 Jul 2024)
Cumulative views and downloads
(calculated since 15 Jul 2024)
Total article views: 2,875 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
2,509
321
45
2,875
88
55
81
HTML: 2,509
PDF: 321
XML: 45
Total: 2,875
Supplement: 88
BibTeX: 55
EndNote: 81
Views and downloads (calculated since 14 Jul 2025)
Cumulative views and downloads
(calculated since 14 Jul 2025)
Total article views: 1,741 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
1,112
280
349
1,741
130
44
85
HTML: 1,112
PDF: 280
XML: 349
Total: 1,741
Supplement: 130
BibTeX: 44
EndNote: 85
Views and downloads (calculated since 15 Jul 2024)
Cumulative views and downloads
(calculated since 15 Jul 2024)
Viewed (geographical distribution)
Total article views: 4,616 (including HTML, PDF, and XML)
Thereof 4,476 with geography defined
and 140 with unknown origin.
Total article views: 2,875 (including HTML, PDF, and XML)
Thereof 2,806 with geography defined
and 69 with unknown origin.
Total article views: 1,741 (including HTML, PDF, and XML)
Thereof 1,670 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...