Shuai Wang

Dr. Shuai Wang

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

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

Representative Publications

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1 November 2017 in Geoderma
Verified
Journal Article
Closed access
Shuai WangShuai Wang
Shuai Wang
QZQianlai Zhuang
Qianlai Zhuang
QWQiubing Wang
Qiubing Wang
XJXinxin Jin
Xinxin Jin
CHChunlan Han
Chunlan Han

1 January 2018 in Ecological Indicators
Verified
Journal Article
Closed access
Shuai WangShuai Wang
Shuai Wang
Kabindra AdhikariKabindra Adhikari
Kabindra Adhikari
QWQiubing Wang
Qiubing Wang
XJXinxin Jin
Xinxin Jin
HLHongdan Li
Hongdan Li

1 March 2018 in Geoderma
Verified
Journal Article
Closed access
Shuai WangShuai Wang
Shuai Wang
QZQianlai Zhuang
Qianlai Zhuang
SJShuhai Jia
Shuhai Jia
XJXinxin Jin
Xinxin Jin
QWQiubing Wang
Qiubing Wang

10 November 2016 in Sustainability
Verified
Journal Article
Open access
PDF file
Shuai WangShuai Wang
Shuai Wang
QWQiu-Bing Wang
Qiu-Bing Wang
Kabindra AdhikariKabindra Adhikari
Kabindra Adhikari
SJShuhai Jia
Shuhai Jia
XJXinxin Jin
Xinxin Jin
HLHongbin Liu
Hongbin Liu
Soil organic carbon (SOC) plays an important role in soil fertility and the global carbon cycle. A better understanding of spatial-temporal changes of SOC content is essential for soil resource management, emission studies, and carbon accounting. In this study, we used a boosted regression trees (BRT) model to map distributions of SOC content in the topsoil (0–20 cm) and evaluated its temporal dynamics from 1990–2010 in Wafangdian City, northeast of China. A set of 110 (1990) and 127 (2010) soil samples were collected and nine environment variables (including topography and vegetation) were used. A 10-fold cross-validation was used to evaluate model performance as well as predictive uncertainty. Accuracy assessments showed that R2 of 0.53 and RMSE (Root-mean-square error) of 9.7 g∙kg−1 for 1990, and 0.55, and 5.2 g∙kg−1 for 2010. Elevation and NDVI (Normalized Difference Vegetation Index) were the two important variables affecting SOC distribution. Results showed that mean SOC content decreased from 19 ± 14 to 18 ± 8 g∙kg−1 over a 20 year period. The maps of SOC represented a decreasing trend from south to north across the study area in both periods. Rapid urbanization and land-use changes were accountable for declining SOC levels. We believe predicted maps of SOC can help local land managers and government agencies to evaluate soil quality and assess carbon sequestration potential and carbon credits.

1 July 2018 in CATENA
Verified
Journal Article
Closed access
Shuai WangShuai Wang
Shuai Wang
XJXinxin Jin
Xinxin Jin
Kabindra AdhikariKabindra Adhikari
Kabindra Adhikari
Wenwen LiWenwen Li
Wenwen Li
MYMiao Yu
Miao Yu
QWQiubing Wang
Qiubing Wang

1 May 2019 in Geoderma
Verified
Journal Article
Closed access
YWYan Wang
Yan Wang
Shuai WangShuai Wang
Shuai Wang
Kabindra AdhikariKabindra Adhikari
Kabindra Adhikari
QWQiubing Wang
Qiubing Wang
YSYueyu Sui
Yueyu Sui
GXGang Xin
Gang Xin