Arid
DOI10.1007/s12665-016-6158-4
Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors
Gao, Tian1,2,3; Xu, Bin2; Yang, Xiuchun2; Deng, Songqiu4; Liu, Yuechen5; Jin, Yunxiang6; Ma, Hailong2; Li, Jinya7; Yu, Haida2; Zheng, Xiao1; Yu, Qiangyi2
通讯作者Xu, Bin
来源期刊ENVIRONMENTAL EARTH SCIENCES
ISSN1866-6280
EISSN1866-6299
出版年2017
卷号76期号:1
英文摘要

Accurate assessments of spatiotemporal patterns in net primary productivity and their links to climate are important to obtain a deeper understanding of the function, stability and sustainability of grassland ecosystems. We combined a satellite-derived NDVI time-series dataset and field-based samples to investigate spatiotemporal patterns in aboveground net primary productivity (ANPP), and we examined the effect of growing season air temperate (GST) and precipitation (GSP) on these patterns along a climaterelated gradient in an eastern Eurasian grassland. Our results indicated that the ANPP fluctuated with no significant trend during 2001-2012. The spatial distribution of ANPP was heterogeneous and decreased from northeast to southwest. The interannual changes in ANPP were mainly controlled by year-to-year GSP; a strong correlation of interannual variability between ANPP and GSP was observed. Similarly, GSP strongly influenced spatial variations in ANPP, and the slopes of fitted linear functions of the GSP-ANPP relationship increased from arid temperate desert grassland to humid meadow grassland. An exponential function could be used to fit the GSP-ANPP relationship for the entire region. An improved moisture index that combines the effects of GST and GSP better explained the variations in ANPP compared with GSP alone. In comparisons with the previous studies, we found that the relationships between spatiotemporal variations in ANPP and climate factors were probably scale dependent. We imply that the quantity and spatial range of analyzed samples contribute to these different results. Multi-scale studies are necessary to improve our knowledge of the response of grassland ANPP to climate change.


英文关键词Temperate steppe Aboveground net primary productivity Remote sensing Spatiotemporal patterns Growing season air temperature Growing season precipitation
类型Article
语种英语
国家Peoples R China ; Japan
收录类别SCI-E
WOS记录号WOS:000392286300055
WOS关键词PRECIPITATION-USE EFFICIENCY ; INNER-MONGOLIA GRASSLAND ; TIME-SERIES DATA ; NORTHERN CHINA ; CARBON STOCKS ; WATER-USE ; BIOMASS ; ECOSYSTEM ; DYNAMICS ; FOREST
WOS类目Environmental Sciences ; Geosciences, Multidisciplinary ; Water Resources
WOS研究方向Environmental Sciences & Ecology ; Geology ; Water Resources
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/198641
作者单位1.Chinese Acad Sci, CAS Key Lab Forest Ecol & Management, Inst Appl Ecol, Shenyang, Peoples R China;
2.Chinese Acad Agr Sci, Key Lab Agri Informat, Minist Agr, Inst Agr Resources & Reg Planning, 12 Zhongguancun South St, Beijing, Peoples R China;
3.Chinese Acad Sci, Qingyuan Forest CERN, Shenyang, Peoples R China;
4.Shinshu Univ, Inst Mt Sci, Nagano, Japan;
5.Chinese Acad Agr Engn, Beijing, Peoples R China;
6.Chinese Acad Agr Sci, Agr Informat Inst, Beijing, Peoples R China;
7.Chinese Acad Sci, State Key Lab Urban & Reg Ecol, Ecoenvironm Sci Res Ctr, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Gao, Tian,Xu, Bin,Yang, Xiuchun,et al. Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors[J],2017,76(1).
APA Gao, Tian.,Xu, Bin.,Yang, Xiuchun.,Deng, Songqiu.,Liu, Yuechen.,...&Yu, Qiangyi.(2017).Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors.ENVIRONMENTAL EARTH SCIENCES,76(1).
MLA Gao, Tian,et al."Aboveground net primary productivity of vegetation along a climate-related gradient in a Eurasian temperate grassland: spatiotemporal patterns and their relationships with climate factors".ENVIRONMENTAL EARTH SCIENCES 76.1(2017).
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