Yuanyuan Tang

Dr. Yuanyuan Tang

orcid

Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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8 March 2024 in Land
Verified
Journal Article
Open access
PDF file
JGJinwei Guo
Jinwei Guo
Yanbing QiYanbing Qi
Yanbing Qi
LZLuhao Zhang
Luhao Zhang
JZJiale Zheng
Jiale Zheng
JSJingyan Sun
Jingyan Sun
XYXiangyun Yang
Xiangyun Yang
The Yellow River Basin has been considered to have the most serious soil erosion in the world, and identifying and mapping the spatial controlling factors would be of great help in adopting targeting strategies for soil erosion prevention. This study used the Universal Soil Loss Equation (USLE) to estimate the spatial and temporal changes in soil erosion from 1985 to 2020 and analyzed the controlling factors. The results indicated that from 1985 to 2020, the average erosion modulus in the Yellow River Basin was 1160.97 t∙km−2∙yr−1, and the erosion modulus in the middle reach was significantly greater than in the lower and upper reaches. Changes in vegetation coverage, rainfall and land use controlled 38.95%, 40.87% and 9.21% of soil erosion changes, respectively. Among them, the area in which soil erosion was decreased due to increased vegetation coverage accounted for 70.77% of the area controlled by vegetation coverage, while the area in which soil erosion was increased due to increased rainfall accounted for 86.62% of the area controlled by rainfall. These results prove the effectiveness of vegetation restoration projects in controlling soil erosion in the Yellow River Basin, but more attention needs to be paid to the impact of rainfall on soil erosion in the future.

18 June 2024 in Land Degradation & Development
Verified
Journal Article
Closed access
YTYuanyuan Tang
Yuanyuan Tang
YYYuchun Yang
Yuchun Yang
YSYanyan Shen
Yanyan Shen
BLBingzhen Liao
Bingzhen Liao
Yanbing QiYanbing Qi
Yanbing Qi

8 August 2025 in Land
Verified
Journal Article
Open access
PDF file
YTYuanyuan Tang
Yuanyuan Tang
XYXiangyun Yang
Xiangyun Yang
XWXinru Wang
Xinru Wang
GDGuohong Du
Guohong Du
MKMukesh Kumar
Mukesh Kumar
Yanbing QiYanbing Qi
Yanbing Qi
Finding out the dynamics of soil organic carbon and inorganic carbon is paramount for sustaining terrestrial carbon cycling and climate change mitigation. From the 1980s to 2010s, substantial changes in land use, climate, and agricultural practices have occurred across North China. This study systematically quantified the stratified dynamics of soil carbon stocks (0–100 cm with 20 cm intervals) and their compositional shifts by using the geographically weighted regression kriging model. The model integrated soil sample data from provincial surveys across North China with key environmental covariates (e.g., elevation, precipitation, air temperature, and the vegetation index) to spatially predict and analyze vertical carbon stock changes. The results indicated that soil carbon stocks decreased considerably by 5.86 Gt in the one-meter soil profile from the 1980s to the 2010s. Significant losses in soil inorganic carbon stocks directly contributed to net soil carbon sources. These significant soil inorganic carbon losses of 7.03 Gt, originating primarily from losses of 7.35 Gt in deeper soil layers (20–100 cm), effectively offset increases of 1.17 Gt in soil organic carbon. About two-thirds of regions in North China have been categorized as carbon source regions. These are distributed for the most part in arid and semi-arid areas and the Qinghai–Tibet Plateau. The remaining one-third of regions have been classified as carbon sink regions which are primarily found in the Loess Plateau, the Huang–Huai–Hai Plain, the Middle-lower Yangtze Plain, and the Northeast China Plain. Significant losses in soil inorganic carbon stocks caused by strong carbon sources may undermine global measures aimed at enhancing terrestrial ecosystem carbon sequestration and fixation. Our results highlight the urgent need to account for vulnerable subsurface inorganic carbon pools in regional carbon sequestration strategies and climate models.