Global parameterization and validation of a two-leaf light use efficiency model for predicting gross primary production across FLUXNET sites

被引:118
|
作者
Zhou, Yanlian [1 ,2 ]
Wu, Xiaocui [2 ,3 ]
Ju, Weimin [3 ,4 ]
Chen, Jing M. [2 ,3 ]
Wang, Shaoqiang [5 ]
Wang, Huimin [5 ]
Yuan, Wenping [6 ]
Black, T. Andrew [7 ]
Jassal, Rachhpal [7 ]
Ibrom, Andreas [8 ]
Han, Shijie [9 ]
Yan, Junhua [10 ]
Margolis, Hank [11 ]
Roupsard, Olivier [12 ,13 ]
Li, Yingnian [14 ]
Zhao, Fenghua [5 ]
Kiely, Gerard [15 ]
Starr, Gregory [16 ]
Pavelka, Marian [17 ]
Montagnani, Leonardo [18 ,19 ]
Wohlfahrt, Georg [20 ,21 ]
D'Odorico, Petra [22 ]
Cook, David [23 ]
Arain, M. Altaf [24 ,25 ]
Bonal, Damien [26 ]
Beringer, Jason [27 ]
Blanken, Peter D. [28 ]
Loubet, Benjamin [29 ]
Leclerc, Monique Y. [30 ]
Matteucci, Giorgio [31 ]
Nagy, Zoltan [32 ]
Olejnik, Janusz [33 ,34 ]
U, Kyaw Tha Paw [35 ,36 ]
Varlagin, Andrej [37 ]
机构
[1] Nanjing Univ, Sch Geog & Oceanog Sci, Jiangsu Prov Key Lab Geog Informat Sci & Technol, Nanjing 210008, Jiangsu, Peoples R China
[2] Joint Ctr Global Change Studies, Beijing, Peoples R China
[3] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210008, Jiangsu, Peoples R China
[4] Jiangsu Ctr Collaborat Innovat Geog Informat Res, Nanjing, Jiangsu, Peoples R China
[5] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing, Peoples R China
[6] Beijing Normal Univ, Future Earth Res Inst, State Key Lab Earth Surface Proc & Resource, Beijing 100875, Peoples R China
[7] Univ British Columbia, Fac Land & Food Syst, Vancouver, BC V5Z 1M9, Canada
[8] Tech Univ Denmark DTU, Dept Environm Engn, Lyngby, Denmark
[9] Chinese Acad Sci, Inst Appl Ecol, Shenyang 110016, Peoples R China
[10] Chinese Acad Sci, South China Bot Garden, Guangzhou, Guangdong, Peoples R China
[11] Univ Laval, Fac Forestry Geog & Geomat, Ctr Forest Studies, Quebec City, PQ, Canada
[12] SupAgro CIRAD INRA IRD, UMR Ecol Fonctionnelle & Biogeochim Sols & Agroec, CIRAD Persyst, Montpellier, France
[13] CATIE Trop Agr Ctr Res & Higher Educ, Turrialba, Costa Rica
[14] Chinese Acad Sci, Northwest Inst Plateau Biol, Xining, Peoples R China
[15] Univ Coll Cork, Civil & Environm Engn Dept, Environm ntal Res Inst, Cork, Ireland
[16] Univ Alabama, Dept Biol Sci, Tuscaloosa, AL USA
[17] Inst Syst Biol & Ecol AS CR, Lab Plants Ecol Physiol, Prague, Czech Republic
[18] Forest Serv, Autonomous Prov Bolzano, Bolzano, Italy
[19] Free Univ Bolzano, Fac Sci & Technol, Bolzano, Italy
[20] Univ Innsbruck, Inst Ecol, A-6020 Innsbruck, Austria
[21] European Acad Bolzano, Bolzano, Italy
[22] Swiss Fed Inst Technol, Inst Agr Sci, Grassland Sci Grp, Zurich, Switzerland
[23] Argonne Natl Lab, Div Environm Sci, Atmospher & Climate Res Program, 9700 S Cass Ave, Argonne, IL 60439 USA
[24] McMaster Univ, McMaster Ctr Climate Change, Hamilton, ON, Canada
[25] McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON, Canada
[26] INRA Nancy, UMR EEF, Nancy, France
[27] Univ Western Australia, Sch Earth & Environm, Crawley, Australia
[28] Univ Colorado, Dept Geog, Boulder, CO 80309 USA
[29] Univ Paris Saclay, AgroParisTech, INRA, UMR ECOSYS, Thiverval Grignon, France
[30] Univ Georgia, Coll Agr & Environm Sci, Dept Crop & Soil Sci, Athens, GA 30602 USA
[31] Univ Tuscia, Viea San Camillo Ed LellisViterbo, Viterbo, Italy
[32] Szent Istvan Univ, MTA SZIE Plant Ecol Res Grp, Godollo, Hungary
[33] Poznan Univ Life Sci, Meteorol Dept, Poznan, Poland
[34] Global Change Res Ctr, Dept Matter & Energy Fluxes, Brno, Czech Republic
[35] Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA
[36] MIT, Joint Program Sci & Policy Global Change, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[37] Russian Acad Sci, AN Severtsov Inst Ecol & Evolut, Moscow, Russia
基金
加拿大自然科学与工程研究理事会; 美国国家科学基金会; 中国国家自然科学基金;
关键词
NET ECOSYSTEM EXCHANGE; PHOTOSYNTHETICALLY ACTIVE RADIATION; CARBON-DIOXIDE EXCHANGE; EDDY COVARIANCE TECHNIQUE; WATER-VAPOR EXCHANGE; NCEP-NCAR REANALYSIS; LAND-SURFACE MODEL; DECIDUOUS FOREST; TERRESTRIAL GROSS; SOLAR-RADIATION;
D O I
10.1002/2014JG002876
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Light use efficiency (LUE) models are widely used to simulate gross primary production (GPP). However, the treatment of the plant canopy as a big leaf by these models can introduce large uncertainties in simulated GPP. Recently, a two-leaf light use efficiency (TL-LUE) model was developed to simulate GPP separately for sunlit and shaded leaves and has been shown to outperform the big-leaf MOD17 model at six FLUX sites in China. In this study we investigated the performance of the TL-LUE model for a wider range of biomes. For this we optimized the parameters and tested the TL-LUE model using data from 98 FLUXNET sites which are distributed across the globe. The results showed that the TL-LUE model performed in general better than the MOD17 model in simulating 8 day GPP. Optimized maximum light use efficiency of shaded leaves (epsilon(msh)) was 2.63 to 4.59 times that of sunlit leaves (epsilon(msu)). Generally, the relationships of epsilon(msh) and epsilon(msu) with epsilon(max) were well described by linear equations, indicating the existence of general patterns across biomes. GPP simulated by the TL-LUE model was much less sensitive to biases in the photosynthetically active radiation (PAR) input than the MOD17 model. The results of this study suggest that the proposed TL-LUE model has the potential for simulating regional and global GPP of terrestrial ecosystems, and it is more robust with regard to usual biases in input data than existing approaches which neglect the bimodal within-canopy distribution of PAR.
引用
收藏
页码:1045 / 1072
页数:28
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