干旱区生态环境知识资源中心(Arid): Improved global estimations of gross primary productivity of natural vegetation types by incorporating plant functional type

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DOI	10.1016/j.jag.2021.102328
	Improved global estimations of gross primary productivity of natural vegetation types by incorporating plant functional type
	Lin, Shangrong; Li, Jing; Liu, Qinhuo; Gioli, Beniamino; Paul-Limoges, Eugenie; Buchmann, Nina; Gharun, Mana; Hortnagl, Lukas; Foltynova, Lenka; Dusek, Jiri; Li, Longhui; Yuan, Wenping
通讯作者	Li, J (corresponding author), Chinese Acad Sci, Jointly Sponsored Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China. ; Li, J (corresponding author), Beijing Normal Univ, Beijing 100101, Peoples R China.
来源期刊	INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
ISSN	1569-8432
EISSN	1872-826X
出版年	2021
卷号	100
英文摘要	Satellite-based light use efficiency (LUE) models are important tools for estimating regional and global vegetation gross primary productivity (GPP). However, all LUE models assume a constant value of maximum LUE at canopy scale (LUEmaxcanopy) over a given vegetation type. This assumption is not supported by observed plant traits regulating LUEmaxcanopy, which varies greatly even within the same ecosystem type. In this study, we developed an improved satellite data driven GPP model by identifying the potential maximal GPP (GPPPOT) and their dominant climate control factor in various plant functional types (PFT), which takes into account both plant trait and climatic control inter-dependence. We selected 161 sites from the FLUXNET2015 dataset with eddy covariance CO2 flux data and continuous meteorology to derive GPPPOT and their dominant climate control factor of vegetation growth for 42 natural PFTs. Results showed that (1) under the same phenology and incident photosynthetic active radiation, the maximal variance of GPPPOT is found in different PFTs of forests (10.9 g C m- 2 day-1) and in different climatic zones of grasslands (>10 g C m- 2 day-1); (2) intra-annual change of GPP in tropical and arid climate zones is mostly driven by vapor pressure deficit (VPD) changes, while temperature is the dominant climate control factor in temperate, boreal and polar climate zones; even under the same climate condition, physiological stress in photosynthesis is different across PFTs; (3) the model that takes into account the plant trait difference across PFTs had a higher agreement with flux tower-based GPP data (GPPflux) than the GPP products that omit PFT differences. Such agreement was highest for natural vegetation cover sites (R2 = 0.77, RMSE = 1.79 g C m- 2 day- 1). These results suggest that global scale GPP models should incorporate both plant traits and their dominant climate control factor variance in various PFT to reduce the uncertainties in terrestrial carbon assessments.
英文关键词	Terrestrial carbon cycle Carbon flux Plant trait Climatic zones
类型	Article
语种	英语
开放获取类型	gold, Green Accepted, Green Published
收录类别	SCI-E
WOS记录号	WOS:000647797000002
WOS关键词	LIGHT-USE EFFICIENCY ; NET PRIMARY PRODUCTION ; PHOTOSYNTHETIC CAPACITY ; TERRESTRIAL CARBON ; WATER-STRESS ; MODEL ; TEMPERATURE ; GPP ; CLIMATE ; FOREST
WOS类目	Remote Sensing
WOS研究方向	Remote Sensing
来源机构	北京师范大学
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/368608
作者单位	[Lin, Shangrong; Li, Jing; Liu, Qinhuo] Chinese Acad Sci, Jointly Sponsored Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China; [Lin, Shangrong; Li, Jing; Liu, Qinhuo] Beijing Normal Univ, Beijing 100101, Peoples R China; [Lin, Shangrong; Yuan, Wenping] Sun Yat Sen Univ, Sch Atmospher Sci, Southern Marine Sci & Engn Guangdong Lab Zhuhai, Zhuhai 519082, Guangdong, Peoples R China; [Gioli, Beniamino] Inst Bioecon, CNR IBE, Via Caproni 8, Florence, Italy; [Paul-Limoges, Eugenie] Univ Zurich, Dept Geog, CH-8057 Zurich, Switzerland; [Buchmann, Nina; Gharun, Mana; Hortnagl, Lukas] Swiss Fed Inst Technol, Dept Environm Syst Sci, Inst Agr Sci, Univ Str 2, CH-8092 Zurich, Switzerland; [Foltynova, Lenka; Dusek, Jiri] Czech Acad Sci, Global Change Res Inst, Belidla 4a, Brno 60300, Czech Republic; [Li, Longhui] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing 210023, Peoples R China; [Li, Longhui] Minist Educ, Key Lab Geog Environm Evolut, Nanjing 210023, Peoples R China
推荐引用方式 GB/T 7714	Lin, Shangrong,Li, Jing,Liu, Qinhuo,et al. Improved global estimations of gross primary productivity of natural vegetation types by incorporating plant functional type[J]. 北京师范大学,2021,100.
APA	Lin, Shangrong.,Li, Jing.,Liu, Qinhuo.,Gioli, Beniamino.,Paul-Limoges, Eugenie.,...&Yuan, Wenping.(2021).Improved global estimations of gross primary productivity of natural vegetation types by incorporating plant functional type.INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION,100.
MLA	Lin, Shangrong,et al."Improved global estimations of gross primary productivity of natural vegetation types by incorporating plant functional type".INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 100(2021).