干旱区生态环境知识资源中心(Arid): Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels

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DOI	10.1016/j.agrformet.2020.108017
	Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels
	Alton, Paul B.
通讯作者	Alton, PB
来源期刊	AGRICULTURAL AND FOREST METEOROLOGY
ISSN	0168-1923
EISSN	1873-2240
出版年	2020
卷号	290
英文摘要	One of the major uncertainties in estimating global Net Primary Productivity (NPP) and Gross Primary Productivity (GPP) is the ability of carbon-monitoring sites to represent the climate and canopy-density of global vegetation ("representativeness"). These sites are used for empirical upscaling and calibration of global landsurface models. The current study determines the representativeness of two important carbon-monitoring networks - FLUXNET2015 and the Ecosystem Model-Data Intercomparison (EMDI) - by calculating the euclidian distance in climate-canopy space between each global 0.5 degrees cell and all carbon-monitoring sites of the same biome or Plant Functional Type (PFT). Reliance on the single (most similar) site has been adopted in the past. A straightforward weighted upscaling, using inverse euclidian distance, identifies which PFTs contribute most to global primary productivity in the context of how well they are represented in carbon-monitoring networks. Some vegetation types, which are numerically well-represented within the network, are sampled at the 'wrong' latitude and in more temperate climes than their global distribution. This includes non-mediterranean needleleaf forest which is one of the main vegetation types contributing to global GPP and NPP. (Semi-)arid regions (mean annual precipitation < 400 mm yr(-1)) are undersampled as well as the sparse vegetation that tends to characterise them. These regions include the tundra and the northern half of the boreal forest where growth is disproportionately affected by climate change. We find a large spread in NPP and GPP recorded at sites of the same PFT (standard deviation is 56% mean). Consequently, our bootstrap error analysis indicates that a minimum of 50 climate-representative sites per PFT is required to quantify adequately (2% precision) the primary productivity of each global vegetation type. Selecting unchartered climate-canopy space for new sites appears to be more important than a simple increase in site numbers.
英文关键词	Gross primary productivity (GPP) Net primary productivity (NPP) Representativeness MODIS Land-surface modelling Plant functional types
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000540172000014
WOS关键词	LIGHT-USE EFFICIENCY ; AREA INDEX PRODUCTS ; TERRESTRIAL GROSS ; PHOTOSYNTHETIC CAPACITY ; ATMOSPHERE EXCHANGE ; ECOSYSTEM EXCHANGE ; CONSTANT FRACTION ; IGBP DISCOVER ; WATER FLUXES ; CO2
WOS类目	Agronomy ; Forestry ; Meteorology & Atmospheric Sciences
WOS研究方向	Agriculture ; Forestry ; Meteorology & Atmospheric Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/324734
作者单位	[Alton, Paul B.] Swansea Univ, Geog Dept, Swansea SA2 8PP, W Glam, Wales
推荐引用方式 GB/T 7714	Alton, Paul B.. Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels[J],2020,290.
APA	Alton, Paul B..(2020).Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels.AGRICULTURAL AND FOREST METEOROLOGY,290.
MLA	Alton, Paul B.."Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels".AGRICULTURAL AND FOREST METEOROLOGY 290(2020).

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