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Attribute parameter characterized the seasonal variation of gross primary productivity (alpha(GPP)): Spatiotemporal variation and influencing factors
Zhang, Weikang1,2; Yu, Guirui1,2; Chen, Zhi1,2; Zhang, Leiming1,2; Wang, Qiufeng1,2; Zhang, Yangjian1,2; He, Honglin1,2; Han, Lang1,2; Chen, Shiping3; Han, Shijie4; Li, Yingnian5; Sha, Liqing6; Shi, Peili1; Wang, Huimin1; Wang, Yanfen7; Xiang, Wenhua8; Yan, Junhua9; Zhang, Yiping6; Zona, Donatella10; Arain, M. Altaf11,12; Maximov, Trofim13; Oechel, Walter10; Kosugi, Yoshiko14
2020-01-15
Source PublicationAGRICULTURAL AND FOREST METEOROLOGY
ISSN0168-1923
Volume280Pages:23
Corresponding AuthorYu, Guirui(yugr@igsnrr.ac.cn) ; Chen, Zhi(chenz@igsnrr.ac.cn)
AbstractThe seasonal dynamic of gross primary productivity (GPP) has influences on the annual GPP (AGPP) of the terrestrial ecosystem. However, the spatiotemporal variation of the seasonal dynamic of GPP and its effects on spatial and temporal variations of AGPP are still poorly addressed. In this study, we developed a parameter, alpha(GPP), defined as the ratio of mean daily GPP (GPP(mean)) to the maximum daily GPP (GPP(max)) during the growing season, to analyze the seasonal dynamic of GPP based on Weibull function. The alpha(GPP) was a comprehensive parameter characterizing the shape, scale, and location of the seasonal dynamic curve of GPP. We calculated aGPP based on the data of GPP for 942 site-years from 115 flux sites in the Northern Hemisphere, and analyzed the spatiotemporal variation and influencing factors of the aGPP. We found that the aGPP of terrestrial ecosystems in the Northern Hemisphere ranged from 0.47 to 0.85, with an average of 0.62 +/- 0.06. The aGPP varied significantly both among different climatic zones and different ecosystem types. The alpha(GPP) was stable on the interannual scale, while decreased as latitude increased, which was consistent across different ecosystem types. The spatial pattern of the seasonal dynamic of astronomical radiation was the dominating factor of the spatial pattern of alpha(GPP), that was, the spatial pattern of the seasonal dynamic of astronomical radiation determined that of the seasonal dynamic of GPP by controlling that of seasonal dynamics of total radiation and temperature. In addition, we assessed the spatial variation of AGPP preliminarily based on alpha(GPP) and other seasonal dynamic parameters of GPP, indicating that the understanding of the spatiotemporal variation of alpha(GPP) could provide a new approach for studying the spatial and temporal variations of AGPP and estimating AGPP based on the seasonal dynamic of GPP.
KeywordAnnual gross primary productivity Attribute parameter of seasonal dynamic Maximum daily gross primary productivity Mean daily gross primary productivity Spatiotemporal variation
DOI10.1016/j.agrformet.2019.107774
WOS KeywordCARBON-DIOXIDE EXCHANGE ; NET ECOSYSTEM EXCHANGE ; ENERGY FLUX MEASUREMENTS ; GREENHOUSE-GAS BALANCE ; BLACK SPRUCE FOREST ; EDDY-COVARIANCE ; INTERANNUAL VARIABILITY ; CO2 EXCHANGE ; WATER-VAPOR ; DECIDUOUS FOREST
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[41671045] ; National Natural Science Foundation of China[31600347] ; National Key Research and Development Program of China[2016YFA0600104] ; National Key Research and Development Program of China[2016YFA0600103] ; CDIAC and ICOS Ecosystem Thematic Center ; OzFlux office ; ChinaFlux office ; AsiaFlux office
Funding OrganizationNational Natural Science Foundation of China ; National Key Research and Development Program of China ; CDIAC and ICOS Ecosystem Thematic Center ; OzFlux office ; ChinaFlux office ; AsiaFlux office
WOS Research AreaAgriculture ; Forestry ; Meteorology & Atmospheric Sciences
WOS SubjectAgronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS IDWOS:000525807000011
PublisherELSEVIER
Citation statistics
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/134003
Collection中国科学院地理科学与资源研究所
Corresponding AuthorYu, Guirui; Chen, Zhi
Affiliation1.Chinese Acad Sci, Key Lab Ecosyst Network Observat & Modeling, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China
2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China
4.Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Peoples R China
5.Chinese Acad Sci, Northwest Inst Plateau Biol, Key Lab Adaptat & Evolut Plateau Biota, Xining 810001, Qinghai, Peoples R China
6.Chinese Acad Sci, CAS Key Lab Trop Forest Ecol, Xishuangbcmna Trop Bot Garden, Menglun 666303, Peoples R China
7.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
8.Cent South Univ Forestry & Technol, Fac Life Sci & Technol, Changsha 410004, Hunan, Peoples R China
9.Chinese Acad Sci, Key Lab Vegetat Restorat & Management Degraded Ec, South China Bot Garden, Guangzhou 510650, Peoples R China
10.San Diego State Univ, Global Change Res Grp, San Diego, CA 92182 USA
11.McMaster Univ, Sch Geog & Earth Sci, 1280 Main St West, Hamilton, ON L8S 4K1, Canada
12.McMaster Ctr Climate Change, 1280 Main St West, Hamilton, ON L8S 4K1, Canada
13.Russian Acad Sci, Inst Biol Problems Cryolithozone, Siberian Branch, 41 Lenin Ave, Yakutsk 677980, Russia
14.Kyoto Univ, Grad Sch Agr, Lab Forest Hydrol, Kyoto, Kyoto 6068502, Japan
Recommended Citation
GB/T 7714
Zhang, Weikang,Yu, Guirui,Chen, Zhi,et al. Attribute parameter characterized the seasonal variation of gross primary productivity (alpha(GPP)): Spatiotemporal variation and influencing factors[J]. AGRICULTURAL AND FOREST METEOROLOGY,2020,280:23.
APA Zhang, Weikang.,Yu, Guirui.,Chen, Zhi.,Zhang, Leiming.,Wang, Qiufeng.,...&Kosugi, Yoshiko.(2020).Attribute parameter characterized the seasonal variation of gross primary productivity (alpha(GPP)): Spatiotemporal variation and influencing factors.AGRICULTURAL AND FOREST METEOROLOGY,280,23.
MLA Zhang, Weikang,et al."Attribute parameter characterized the seasonal variation of gross primary productivity (alpha(GPP)): Spatiotemporal variation and influencing factors".AGRICULTURAL AND FOREST METEOROLOGY 280(2020):23.
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