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Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region
Cui, Erqian1,2; Huang, Kun1,2; Arain, Muhammad Altaf3,4; Fisher, Joshua B.5; Huntzinger, Deborah N.6; Ito, Akihiko7; Luo, Yiqi8; Jain, Atul K.9; Mao, Jiafu10,11; Michalak, Anna M.12; Niu, Shull13,14; Parazoo, Nicholas C.5; Peng, Changhui15,16; Peng, Shushi17; Poulter, Benjamin18; Ricciuto, Daniel M.10,11; Schaefer, Kevin M.19; Schwalm, Christopher R.6,20; Shi, Xiaoying10,11; Tian, Hanqin21,22; Wang, Weile23; Wang, Jinsong13; Wei, Yaxing10,11; Yan, Enrong1; Yan, Liming1; Zeng, Ning24; Zhu, Qiuan16; Xia, Jianyang1,2
2019-06-01
Source PublicationGLOBAL BIOGEOCHEMICAL CYCLES
ISSN0886-6236
Volume33Issue:6Pages:668-689
Corresponding AuthorXia, Jianyang(jyxia@des.ecnu.edu.cn)
AbstractGlobal and regional projections of climate change by Earth system models are limited by their uncertain estimates of terrestrial ecosystem productivity. At the middle to low latitudes, the East Asian monsoon region has higher productivity than forests in Europe-Africa and North America, but its estimate by current generation of terrestrial biosphere models (TBMs) has seldom been systematically evaluated. Here, we developed a traceability framework to evaluate the simulated gross primary productivity (GPP) by 15 TBMs in the East Asian monsoon region. The framework links GPP to net primary productivity, biomass, leaf area and back to GPP via incorporating multiple vegetation functional properties of carbon-use efficiency (CUE), vegetation C turnover time (tau(veg)), leaf C fraction (F-leaf), specific leaf area (SLA), and leaf area index (LAI)-level photosynthesis (P-LAI), respectively. We then applied a relative importance algorithm to attribute intermodel variation at each node. The results showed that large intermodel variation in GPP over 1901-2010 were mainly propagated from their different representation of vegetation functional properties. For example, SLA explained 77% of the intermodel difference in leaf area, which contributed 90% to the simulated GPP differences. In addition, the models simulated higher CUE (18.1 21.3%), tau(veg) (18.2 26.9%), and SLA (27.436.5%) than observations, leading to the overestimation of simulated GPP across the East Asian monsoon region. These results suggest the large uncertainty of current TBMs in simulating GPP is largely propagated from their poor representation of the vegetation functional properties and call for a better understanding of the covariations between plant functional properties in terrestrial ecosystems.
Keywordenvironmental drivers initial conditions model uncertainty MsTMIP relative importance vegetation functional property
DOI10.1029/2018GB005909
WOS KeywordCARBON-DIOXIDE EXCHANGE ; EARTH SYSTEM MODEL ; PROGRAM MULTISCALE SYNTHESIS ; GROSS PRIMARY PRODUCTIVITY ; CO2 EXCHANGE ; CLIMATE-CHANGE ; INTERCOMPARISON PROJECT ; BIOMASS ALLOCATION ; SEASONAL-VARIATION ; FOREST ECOSYSTEMS
Indexed BySCI
Language英语
Funding ProjectNational Key R&D Program of China[2017YFA0604603] ; National Natural Science Foundation of China[31722009] ; National Natural Science Foundation of China[41630528] ; Fok Ying-Tong Education Foundation for Young Teachers in the Higher Education Institutions of China[161016] ; National 1000 Young Talents Program of China ; NASA ROSES Grant[NNX10AG01A] ; NASA ROSES Grant[NNH10AN681] ; California Institute of Technology ; National Basic Research Program of China[2013CB956602] ; National Science and Engineering Research Council of Canada (NSERC) ; US Department of Energy (DOE), Office of Science, Biological and Environmental Research ; DOE[DE-AC05-00OR22725]
Funding OrganizationNational Key R&D Program of China ; National Natural Science Foundation of China ; Fok Ying-Tong Education Foundation for Young Teachers in the Higher Education Institutions of China ; National 1000 Young Talents Program of China ; NASA ROSES Grant ; California Institute of Technology ; National Basic Research Program of China ; National Science and Engineering Research Council of Canada (NSERC) ; US Department of Energy (DOE), Office of Science, Biological and Environmental Research ; DOE
WOS Research AreaEnvironmental Sciences & Ecology ; Geology ; Meteorology & Atmospheric Sciences
WOS SubjectEnvironmental Sciences ; Geosciences, Multidisciplinary ; Meteorology & Atmospheric Sciences
WOS IDWOS:000474839000003
PublisherAMER GEOPHYSICAL UNION
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/58352
Collection中国科学院地理科学与资源研究所
Corresponding AuthorXia, Jianyang
Affiliation1.East China Normal Univ, Zhejiang Tiantong Natl Forest Ecosyst Observat &, Shanghai Key Lab Urban Ecol Proc & Ecorestorat, Sch Ecol & Environm Sci,Ctr Global Change & Ecol, Shanghai, Peoples R China
2.Inst Ecochongming, Shanghai, Peoples R China
3.McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON, Canada
4.McMaster Univ, McMaster Ctr Climate Change, Hamilton, ON, Canada
5.CALTECH, Jet Prop Lab, Pasadena, CA USA
6.No Arizona Univ, Sch Earth Sci & Environm Sustainabil, Flagstaff, AZ 86011 USA
7.Natl Inst Environm Studies, Tsukuba, Ibaraki, Japan
8.No Arizona Univ, Dept Biol Sci, Ctr Ecosyst Sci & Soc, Flagstaff, AZ 86011 USA
9.Univ Illinois, Dept Atmospher Sci, Urbana, IL USA
10.Oak Ridge Natl Lab, Div Environm Sci, POB 2008, Oak Ridge, TN 37831 USA
11.Oak Ridge Natl Lab, Climate Change Sci Inst, Oak Ridge, TN USA
12.Carnegie Inst Sci, Dept Global Ecol, Stanford, CA USA
13.Univ Chinese Acad Sci, Dept Resources & Environm, Beijing, Peoples R China
14.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China
15.Univ Quebec Montreal, Inst Environm Sci, Dept Biol Sci, Montreal, PQ, Canada
16.Northwest A&F Univ, Ctr Ecol Forecasting & Global Change, Coll Forestry, Yangling, Shaanxi, Peoples R China
17.Peking Univ, Coll Urban & Environm Sci, Sino French Inst Earth Syst Sci, Beijing, Peoples R China
18.Montana State Univ, Dept Ecol, Bozeman, MT 59717 USA
19.Univ Colorado, Cooperat Inst Res Environm Sci, Natl Snow & Ice Data Ctr, Boulder, CO 80309 USA
20.Woods Hole Res Ctr, Falmouth, MA USA
21.Auburn Univ, Int Ctr Climate & Global Change Res, Auburn, AL 36849 USA
22.Auburn Univ, Sch Forestry & Wildlife Sci, Auburn, AL 36849 USA
23.NASA, Ames Res Ctr, Moffett Field, CA 94035 USA
24.Univ Maryland, Dept Atmospher & Ocean Sci, College Pk, MD 20742 USA
Recommended Citation
GB/T 7714
Cui, Erqian,Huang, Kun,Arain, Muhammad Altaf,et al. Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region[J]. GLOBAL BIOGEOCHEMICAL CYCLES,2019,33(6):668-689.
APA Cui, Erqian.,Huang, Kun.,Arain, Muhammad Altaf.,Fisher, Joshua B..,Huntzinger, Deborah N..,...&Xia, Jianyang.(2019).Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region.GLOBAL BIOGEOCHEMICAL CYCLES,33(6),668-689.
MLA Cui, Erqian,et al."Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region".GLOBAL BIOGEOCHEMICAL CYCLES 33.6(2019):668-689.
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