Spatial pattern of grassland aboveground biomass and its environmental controls in the Eurasian steppe
Jiao, CC; Yu, GR; He, NP; Ma, AN; Ge, JP; Hu, ZM
2017
Source PublicationJOURNAL OF GEOGRAPHICAL SCIENCES
ISSN1009-637X
Volume27Issue:1Pages:3-22
AbstractVegetation biomass is an important component of terrestrial ecosystem carbon stocks. Grasslands are one of the most widespread biomes worldwide, playing an important role in global carbon cycling. Therefore, studying spatial patterns of biomass and their correlations to environment in grasslands is fundamental to quantifying terrestrial carbon budgets. The Eurasian steppe, an important part of global grasslands, is the largest and relatively well preserved grassland in the world. In this study, we analyzed the spatial pattern of aboveground biomass (AGB), and correlations of AGB to its environment in the Eurasian steppe by meta-analysis. AGB data used in this study were derived from the harvesting method and were obtained from three data sources (literature, global NPP database at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL), some data provided by other researchers). Our results demonstrated that: (1) as for the Eurasian steppe overall, the spatial variation in AGB exhibited significant horizontal and vertical zonality. In detail, AGB showed an inverted parabola curve with the latitude and with the elevation, while a parabola curve with the longitude. In addition, the spatial pattern of AGB had marked horizontal zonality in the Black Sea-Kazakhstan steppe subregion and the Mongolian Plateau steppe subregion, while horizontal and vertical zonality in the Tibetan Plateau alpine steppe subregion. (2) Of the examined environmental variables, the spatial variation of AGB was related to mean annual precipitation (MAP), mean annual temperature (MAT), mean annual solar radiation (MAR), soil Gravel content, soil pH and soil organic content (SOC) at the depth of 0-30 cm. Nevertheless, MAP dominated spatial patterns of AGB in the Eurasian steppe and its three subregions. (3) A Gaussian function was found between AGB and MAP in the Eurasian steppe overall, which was primarily determined by unique patterns of grasslands and environment in the Tibetan Plateau. AGB was significantly positively related to MAP in the Black Sea-Kazakhstan steppe subregion (elevation < 3000 m), the Mongolian Plateau steppe subregion (elevation < 3000 m) and the surface (elevation ae 4800 m) of the Tibetan Plateau. Nevertheless, the spatial variation in AGB exhibited a Gaussian function curve with the increasing MAP in the east and southeast margins (elevation < 4800 m) of the Tibetan Plateau. This study provided more knowledge of spatial patterns of AGB and their environmental controls in grasslands than previous studies only conducted in local regions like the Inner Mongolian temperate grassland, the Tibetan Plateau alpine grassland, etc.
SubtypeJournal
Keywordthe Eurasian steppe aboveground biomass spatial pattern parabola curve Gaussian function
Subject AreaPhysical Geography
WOS Subject ExtendedGeography, Physical
WOS KeywordNET PRIMARY PRODUCTIVITY ; INNER-MONGOLIA GRASSLAND ; SPACE-TIME CLIMATE ; TIBETAN PLATEAU ; PRECIPITATION GRADIENT ; TEMPERATE GRASSLAND ; CHINA GRASSLANDS ; USE EFFICIENCY ; CARBON STOCKS ; UNITED-STATES
Indexed BySCI
Language英语
WOS IDWOS:000388979600001
PublisherSCIENCE PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/44139
Collection生态系统网络观测与模拟院重点实验室_生态网络实验室
Recommended Citation
GB/T 7714
Jiao, CC,Yu, GR,He, NP,et al. Spatial pattern of grassland aboveground biomass and its environmental controls in the Eurasian steppe[J]. JOURNAL OF GEOGRAPHICAL SCIENCES,2017,27(1):3-22.
APA Jiao, CC,Yu, GR,He, NP,Ma, AN,Ge, JP,&Hu, ZM.(2017).Spatial pattern of grassland aboveground biomass and its environmental controls in the Eurasian steppe.JOURNAL OF GEOGRAPHICAL SCIENCES,27(1),3-22.
MLA Jiao, CC,et al."Spatial pattern of grassland aboveground biomass and its environmental controls in the Eurasian steppe".JOURNAL OF GEOGRAPHICAL SCIENCES 27.1(2017):3-22.
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