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Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison
Hu, ZM (Hu, Zhongmin)1,2,3; Shi, H (Shi, Hao)4; Cheng, KL (Cheng, Kaili)2,3; Wang, YP (Wang, Ying-Ping)5,6; Piao, SL (Piao, Shilong)7,8; Li, Y (Li, Yue)7; Zhang, L (Zhang, Li)2,3; Xia, JY (Xia, Jianyang)9,10; Zhou, L (Zhou, Lei)11; Yuan, WP (Yuan, Wenping)12; Running, S (Running, Steve)13; Li, LH (Li, Longhui)14; Hao, YB (Hao, Yanbin)15; He, NP (He, Nianpeng)2,3; Yu, Q (Yu, Qiang)3,4,16; Yu, GR (Yu, Guirui)2,3
Source PublicationGLOBAL CHANGE BIOLOGY
2018-07-01
Volume24Issue:7Pages:2965-2979 
DOI10.1111/gcb.14274
AbstractGiven the important contributions of semiarid region to global land carbon cycle, accurate modeling of the interannual variability (IAV) of terrestrial gross primary productivity (GPP) is important but remains challenging. By decomposing GPP into leaf area index (LAI) and photosynthesis per leaf area (i.e., GPP_leaf), we investigated the IAV of GPP and the mechanisms responsible in a temperate grassland of northwestern China. We further assessed six ecosystem models for their capabilities in reproducing the observed IAV of GPP in a temperate grassland from 2004 to 2011 in China. We observed that the responses to LAI and GPP_leaf to soil water significantly contributed to IAV of GPP at the grassland ecosystem. Two of six models with prescribed LAI simulated of the observed IAV of GPP quite well, but still underestimated the variance of GPP_leaf, therefore the variance of GPP. In comparison, simulated pattern by the other four models with prognostic LAI differed significantly from the observed IAV of GPP. Only some models with prognostic LAI can capture the observed sharp decline of GPP in drought years. Further analysis indicated that accurately representing the responses of GPP_leaf and leaf stomatal conductance to soil moisture are critical for the models to reproduce the observed IAV of GPP_leaf. Our framework also identified that the contributions of LAI and GPP_leaf to the observed IAV of GPP were relatively independent. We conclude that our framework of decomposing GPP into LAI and GPP_leaf has a significant potential for facilitating future model intercomparison, benchmarking and optimization should be adopted for future data-model comparisons.
WOS IDWOS:000437281500020
Language英语
Indexed BySCIE
KeywordLAND-SURFACE MODELS GROSS PRIMARY PRODUCTIVITY WATER-USE EFFICIENCY STOMATAL CONDUCTANCE LEAF-AREA PHOTOSYNTHESIS MODEL CLIMATE VARIABILITY CYCLE MODELS CARBON CO2
WOS Research AreaBiodiversity & Conservation ; Environmental Sciences & Ecology
WOS SubjectBiodiversity Conservation ; Ecology ; Environmental Sciences
Cooperation Status国际
ISSN1354-1013
Department高寒生态重点实验室
PublisherWILEY
Citation statistics
Cited Times:5[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.itpcas.ac.cn/handle/131C11/8611
Collection图书馆
Affiliation1.South China Normal Univ, Sch Geog, Guangzhou, Guangdong, Peoples R China;
2.Chinese Acad Sci, Synth Res Ctr, Chinese Ecosyst Res Network,Inst Geog Sci & Nat R, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China;
3.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing, Peoples R China;
4.Northwest A&F Univ, State Key Lab Soil Eros & Dryland Farming Loess P, Yangling, Shaanxi, Peoples R China.;
5.CSIRO Oceans & Atmosphere, Aspendale, Vic, Australia;
6.Chinese Acad Sci, South China Bot Garden, Terr Biogeochem Grp, Guangzhou, Guangdong, Peoples R China;
7.Peking Univ, Coll Urban & Environm Sci, Sinofrench Inst Earth Syst Sci, Beijing, Peoples R China;
8.Chinese Acad Sci, Inst Tibetan Plateau Res, Beijing, Peoples R China;
9.East China Normal Univ, Sch Ecol & Environm Sci, Tiantong Natl Forest Ecosyst Observat & Res Stn, Shanghai, Peoples R China;
10.IEC, Shanghai, Peoples R China;
11.Zhejiang Normal Univ, Coll Geog & Environm Sci, Jinhua, Peoples R China;
12.Sun Yat Sen Univ, Sch Atmospher Sci, Guangzhou, Guangdong, Peoples R China;
13.Univ Montana, Coll Forestry & Conservat, NTSG, Missoula, MT 59812 USA;
14.Nanjing Normal Univ, Sch Geog Sci, Nanjing, Jiangsu, Peoples R China;
15.Univ Chinese Acad Sci, Coll Life Sci, Beijing, Peoples R China;
16.Univ Technol Sydney, Sch Life Sci, Sydney, NSW, Australia.
Recommended Citation
GB/T 7714
Hu, ZM ,Shi, H ,Cheng, KL ,et al. Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison[J]. GLOBAL CHANGE BIOLOGY,2018,24(7):2965-2979 .
APA Hu, ZM .,Shi, H .,Cheng, KL .,Wang, YP .,Piao, SL .,...&Yu, GR .(2018).Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison.GLOBAL CHANGE BIOLOGY,24(7),2965-2979 .
MLA Hu, ZM ,et al."Joint structural and physiological control on the interannual variation in productivity in a temperate grassland: A data-model comparison".GLOBAL CHANGE BIOLOGY 24.7(2018):2965-2979 .
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