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Large-scale soil organic carbon mapping based on multivariate modelling: The case of grasslands on the Loess Plateau
Wang, Yinyin1,2,3; Deng, Lei4; Wu, Gaolin4; Wang, Kaibo5; Shangguan, Zhouping1,2,3
2018
Source PublicationLAND DEGRADATION & DEVELOPMENT
Volume29Issue:1Pages:26-37
SubtypeArticle
AbstractThe Loess Plateau is considered one of the world's regions with severe soil erosion. Grasslands are widely distributed on the Loess Plateau, accounting for approximately 40% of the total area. Soil organic carbon (SOC) plays an important role in the terrestrial carbon cycle in this region. We compiled more than 1,000 measurements of plant biomass and SOC content derived from 223 field studies of grasslands on the Loess Plateau. Combined with meteorological factors (precipitation and air temperature) and the photosynthetically active radiation factor, the topsoil SOC contents of grasslands were predicted using the random forest (RF) regression algorithm. Predicted grassland SOC content (1.70-40.34gkg(-1)) decreased from the southeast to the northwest of the Loess Plateau, with approximately 1/5 of the grassland exhibiting values lower than 4gkg(-1). Observed SOC content was positively correlated with observed plant biomass, and for predicted values, this correlation was strong in the desert steppe and the steppe desert of rocky mountains. Air temperature was the most important factor affecting SOC contents in the RF model. Moreover, the residual error of observations and predictions increased as the grazing intensity varied from none to very severe in the temperate desert steppe, and this RF model may not perform well in plains. The use of the RF model for SOC prediction in Loess Plateau grasslands provides a reference for C storage studies in arid and semi-arid regions, and aboveground biomass and temperature should receive more attention due to increasing C sequestration.
KeywordAboveground Biomass Belowground Biomass Grassland Loess Plateau Soil Organic Carbon
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine
DOI10.1002/ldr.2833
WOS KeywordLONG-TERM FERTILIZATION ; FINE-ROOT DISTRIBUTION ; FOR-GREEN PROGRAM ; LAND-USE ; TEMPERATURE SENSITIVITY ; CLIMATE-CHANGE ; TOTAL NITROGEN ; VEGETATION RESTORATION ; SPATIAL VARIABILITY ; NORTHWESTERN CHINA
Indexed BySCI
Language英语
WOS Research AreaEnvironmental Sciences & Ecology ; Agriculture
WOS SubjectEnvironmental Sciences ; Soil Science
WOS IDWOS:000423123700003
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ieecas.cn/handle/361006/5244
Collection生态环境研究室
Affiliation1.Chinese Acad Sci, Inst Soil & Water Conservat, State Key Lab Soil Eros & Dryland Farming Loess P, Xinong Rd 26, Yangling 712100, Shaanxi, Peoples R China
2.Minist Water Resources, Xinong Rd 26, Yangling 712100, Shaanxi, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling 712100, Shaanxi, Peoples R China
5.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Wang, Yinyin,Deng, Lei,Wu, Gaolin,et al. Large-scale soil organic carbon mapping based on multivariate modelling: The case of grasslands on the Loess Plateau[J]. LAND DEGRADATION & DEVELOPMENT,2018,29(1):26-37.
APA Wang, Yinyin,Deng, Lei,Wu, Gaolin,Wang, Kaibo,&Shangguan, Zhouping.(2018).Large-scale soil organic carbon mapping based on multivariate modelling: The case of grasslands on the Loess Plateau.LAND DEGRADATION & DEVELOPMENT,29(1),26-37.
MLA Wang, Yinyin,et al."Large-scale soil organic carbon mapping based on multivariate modelling: The case of grasslands on the Loess Plateau".LAND DEGRADATION & DEVELOPMENT 29.1(2018):26-37.
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