Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands | |
Zhou, Huimin; Shao, Junjiong; Liu, Huiying; Du, Zhenggang; Zhou, Lingyan; Liu, Ruiqiang; Bernhofer, Christian1; Gruenwald, Thomas1; Dusek, Jiri2; Montagnani, Leonardo3,4; Tagesson, Torbern5,6; Black, Thomas Andrew7; Jassal, Rachhpal7; Woodgate, William8,9; Biraud, Sebastien10; Varlagin, Andrej11; Mammarella, Ivan12; Gharun, Mana13; Shekhar, Ankit13; Buchmann, Nina13; Manco, Antonio14; Magliulo, Enzo14; Billesbach, Dave15; Silberstein, Richard P.; Ohta, Takeshi18; Yu, Guirui19,20; Chen, Zhi19,20; Zhang, Yiping21![]() | |
2021 | |
Source Publication | AGRICULTURAL AND FOREST METEOROLOGY
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ISSN | 0168-1923 |
Volume | 307Issue:xPages:- |
Abstract | Compared to the well-known drivers of spatial variability in gross primary productivity (GPP), the relative importance of climatic variables, soil properties and plant traits to the spatial variability in net ecosystem exchange of CO2 between terrestrial ecosystem and atmosphere (NEE) is poorly understood. We used principal component regression to analyze data from 147 eddy flux sites to disentangle effects of climatic variables, soil properties and plant traits on the spatial variation in annual NEE and its components (GPP and ecosystem respiration (RE)) across global forests and grasslands. Our results showed that the largest unique contribution (proportion of variance only explained by one class of variables) to NEE variance came from climatic variables for forests (24%-30%) and soil properties for grasslands (41%-54%). Specifically, mean annual precipitation and potential evapotranspiration were the most important climatic variables driving forest NEE, whereas available soil water capacity, clay content and cation exchange capacity mainly influenced grassland NEE. Plant traits showed a small unique contribution to NEE in both forests and grasslands. However, leaf phosphorus content strongly interacted with soil total nitrogen density and clay content, and these combined factors represented a major contribution for grassland NEE. For GPP and RE, the majority of spatial variance was attributed to the common contribution of climate, soil and plant traits (50% - 62%, proportion of variance explained by more than one class of variables), rather than their unique contributions. Interestingly, those factors with only minor influences on GPP and RE variability (e.g., soil properties) have significant contributions to the spatial variability in NEE. Such emerging factors and the interactions between climatic variables, soil properties and plant traits are not well represented in current terrestrial biosphere models, which should be considered in future model improvement to accurately predict the spatial pattern of carbon cycling across forests and grasslands globally. |
Keyword | Carbon Climatic variables Net ecosystem exchange Plant traits Soil properties Spatial variability |
Subject Area | Agriculture ; Forestry ; Meteorology & Atmospheric Sciences |
DOI | 10.1016/j.agrformet.2021.108506 |
Indexed By | SCI |
Language | 英语 |
WOS ID | WOS:000682515100024 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | https://ir.xtbg.ac.cn/handle/353005/12352 |
Collection | 全球变化研究组 |
Affiliation | 1.East China Normal Univ, Ctr Global Change & Ecol Forecasting, Sch Ecol & Environm Sci, Shanghai Key Lab Urban Ecol Proc & Ecorestorat,Ti, Shanghai 200241, Peoples R China 2.Tech Univ Dresden, Fac Environm Sci, Inst Hydrol & Meteorol, D-01062 Dresden, Germany 3.Acad Sci Czech Republ, Global Change Res Inst, Belidla 986-4a, Brno, Czech Republic 4.Free Univ Bolzano, Fac Sci & Technol, Bolzano, Italy 5.Forest Serv, Bolzano, Italy 6.Lund Univ, Dept Phys Geog & Ecosyst Sci, Solvegatan 12, SE-22362 Lund, Sweden 7.Univ Copenhagen, Dept Geosci & Nat Resource Management, Oster Voldgade 10, DK-1350 Copenhagen, Denmark 8.Univ British Columbia, Fac Land & Food Syst, 2357 Main Mall, Vancouver, BC V6T 1Z4, Canada 9.Univ Queensland, Sch Earth & Environm Sci, Brisbane, Qld, Australia 10.CSIRO, Land & Water, Brisbane, Qld, Australia 11.Lawrence Berkeley Natl Lab, 1 Cyclotron Rd, Berkeley, CA 94720 USA 12.Russian Acad Sci, AN Severtsov Inst Ecol & Evolut, Leninsky Pr 33, Moscow 119071, Russia 13.Univ Helsinki, Inst Atmospher & Earth Syst Res Phys, Helsinki, Finland 14.Swiss Fed Inst Technol, Dept Environm Syst Sci, Univ Str 2, CH-8092 Zurich, Switzerland 15.Natl Res Council Italy CNR ISAFOM, Inst Agr & Forestry Syst Mediterranean, Piazzale Enrico Fermi 1, Portici, NA, Italy 16.Univ Nebraska, Dept Biol Syst Engn, Lincoln, NE 68588 USA 17.Silberstein, Richard P.] Edith Cowan Univ, Joondalup, WA, Australia 18.Silberstein, Richard P.] Univ Western Australia, Nedlands, WA, Australia 19.Nagoya Univ, Chikua Ku, Furo Cho, Nagoya, Aichi 4648601, Japan 20.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Simulat, Beijing 100101, Peoples R China 21.Univ Chinese Acad Sci, Sch Resources & Environm, Beijing 100049, Peoples R China 22.Chinese Acad Sci, CAS Key Lab Trop Forest Ecol, Xishuangbanna Trop Bot Garden, Menglun 666303, Peoples R China 23.Shanghai Inst Pollut Control & Ecol Secur, 1515 North Zhongshan Rd, Shanghai 200437, Peoples R China |
Recommended Citation GB/T 7714 | Zhou, Huimin,Shao, Junjiong,Liu, Huiying,et al. Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands[J]. AGRICULTURAL AND FOREST METEOROLOGY,2021,307(x):-. |
APA | Zhou, Huimin.,Shao, Junjiong.,Liu, Huiying.,Du, Zhenggang.,Zhou, Lingyan.,...&Zhou, Xuhui.(2021).Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands.AGRICULTURAL AND FOREST METEOROLOGY,307(x),-. |
MLA | Zhou, Huimin,et al."Relative importance of climatic variables, soil properties and plant traits to spatial variability in net CO2 exchange across global forests and grasslands".AGRICULTURAL AND FOREST METEOROLOGY 307.x(2021):-. |
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