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Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years
Yao, YT (Yao, Yitong)1; Wang, XH (Wang, Xuhui)1; Li, Y (Li, Yue)1; Wang, T (Wang, Tao)2,3; Shen, MG (Shen, Miaogen)2,3; Du, MY (Du, Mingyuan)4; He, HL (He, Honglin)5; Li, YN (Li, Yingnian)6; Luo, WJ (Luo, Weijun)7; Ma, MG (Ma, Mingguo)8; Ma, YM (Ma, Yaoming)2,3; Tang, YH (Tang, Yanhong)1; Wang, HM (Wang, Huimin)5; Zhang, XZ (Zhang, Xianzhou)5; Zhang, YP (Zhang, Yiping)9; Zhao, L (Zhao, Liang)10; Zhou, GS (Zhou, Guangsheng)11; Piao, SL (Piao, Shilong)1,2,3
Source PublicationGLOBAL CHANGE BIOLOGY
2018
Volume24Issue:1Pages:184-196
DOI10.1111/gcb.13830
Abstract

The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm developing a new GPP dataset for China with 0.1 degrees spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets. According to our estimates, mean annual GPP over China is 6.62 +/- 0.23 PgC/year during 1982-2015 with a clear gradient from southeast to northwest. The trend of GPP estimated by this study (0.020 +/- 0.002 PgC/year(2) from 1982 to 2015) is almost two times of that estimated by the previous global dataset. The GPP increment is widely spread with 60% area showing significant increasing trend (p <.05), except for Inner Mongolia. Most ecosystem models overestimated the GPP magnitudes but underestimated the temporal trend of GPP. The monsoon affected eastern China, in particular the area surrounding Qinling Mountain, seems having larger contribution to interannual variability (IAV) of China's GPP than the semiarid northwestern China and Tibetan Plateau. At country scale, temperature is the dominant climatic driver for IAV of GPP. The area where IAV of GPP dominated by temperature is about 42%, while precipitation and solar radiation dominate 31% and 27% respectively over semiarid area and cold-wet area. Such spatial pattern was generally consistent with global GPP dataset, except over the Tibetan Plateau and northeastern forests, but not captured by most ecosystem models, highlighting future research needs to improve the modeling of ecosystem response to climate variations.

Subject Area生态学
WOS IDWOS:000426506100044
Language英语
Indexed BySCIE
KeywordNet Primary Production Photosynthetically Active Radiation Terrestrial Carbon-cycle Global Vegetation Model Interannual Variability Ecosystem Exchange Biosphere Model Plant Geography Dynamics Dioxide
WOS Research AreaBiodiversity & Conservation ; Environmental Sciences & Ecology
WOS SubjectBiodiversity Conservation ; Ecology ; Environmental Sciences
Cooperation Status国际
ISSN1354-1013
Department高寒生态重点实验室
PublisherWILEY
Citation statistics
Cited Times:32[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itpcas.ac.cn/handle/131C11/8776
Collection图书馆
Corresponding AuthorPiao, SL (Piao, Shilong)
Affiliation1.Peking Univ, Coll Urban & Environm Sci, Sinofrench Inst Earth Syst Sci, Beijing, Peoples R China;
2.Chinese Acad Sci, Inst Tibetan Plateau Res, Key Lab Alpine Ecol & Biodivers, Beijing, Peoples R China;
3.Chinese Acad Sci, Ctr Excellence Tibetan Earth Sci, Beijing, Peoples R China;
4.Natl Agr & Food Res Org, Inst Agroenvironm Sci, Tsukuba, Ibaraki, Japan;
5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China;
6.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining, Qinghai, Peoples R China;
7.Chinese Acad Sci, Inst Geochem, State Key Lab Environm Geochem, Guiyang, Guizhou, Peoples R China;
8.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Cold & Arid Reg Remote Sensing Observat Syst Expt, Lanzhou, Gansu, Peoples R China;
9.Chinese Acad Sci, Xishuangbanna Trop Bot Garden, Key Lab Trop Forest Ecol, Mengla, Yunnan, Peoples R China;
10.Chinese Acad Sci, Northwest Inst Plateau Biol, Haibei Alpine Meadow Ecosyst Res Stn, Key Lab Adaptat & Evolut Plateau Biota, Xining, Qinghai, Peoples R China;
11.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing, Peoples R China.
Recommended Citation
GB/T 7714
Yao, YT ,Wang, XH ,Li, Y ,et al. Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years[J]. GLOBAL CHANGE BIOLOGY,2018,24(1):184-196.
APA Yao, YT .,Wang, XH .,Li, Y .,Wang, T .,Shen, MG .,...&Piao, SL .(2018).Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years.GLOBAL CHANGE BIOLOGY,24(1),184-196.
MLA Yao, YT ,et al."Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years".GLOBAL CHANGE BIOLOGY 24.1(2018):184-196.
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