Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the La Thuile database

被引:265
作者
Yuan, Wenping [1 ,2 ]
Cai, Wenwen [1 ]
Xia, Jiangzhou [1 ]
Chen, Jiquan [3 ,4 ]
Liu, Shuguang [5 ]
Dong, Wenjie [1 ]
Merbold, Lutz [6 ]
Law, Beverly [7 ]
Arain, Altaf [8 ,9 ]
Beringer, Jason [10 ]
Bernhofer, Christian [11 ]
Black, Andy [12 ]
Blanken, Peter D. [13 ]
Cescatti, Alessandro [14 ]
Chen, Yang [1 ]
Francois, Louis [15 ]
Gianelle, Damiano [16 ]
Janssens, Ivan A. [17 ]
Jung, Martin [18 ]
Kato, Tomomichi [19 ]
Kiely, Gerard [20 ]
Liu, Dan [1 ]
Marcolla, Barbara [16 ]
Montagnani, Leonardo [21 ,22 ]
Raschi, Antonio [23 ]
Roupsard, Olivier [24 ,25 ]
Varlagin, Andrej [26 ]
Wohlfahrt, Georg [27 ]
机构
[1] Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China
[2] Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, State Key Lab Cryospher Sci, Lanzhou 730000, Gansu, Peoples R China
[3] Nanjing Univ Informat Sci & Technol, Int Ctr Ecol Meteorol & Environm, Nanjing 210044, Jiangsu, Peoples R China
[4] Univ Toledo, Dept Environm Sci, Toledo, OH 43606 USA
[5] Cent South Univ Forestry & Technol, State Engn Lab Southern Forestry Appl Ecol & Tech, Changsha 410004, Hunan, Peoples R China
[6] Swiss Fed Inst Technol, Dept Environm Syst Sci, CH-8092 Zurich, Switzerland
[7] Oregon State Univ, Coll Forestry, Corvallis, OR 97331 USA
[8] McMaster Univ, McMaster Ctr Climate Change, Hamilton, ON, Canada
[9] McMaster Univ, Sch Geog & Earth Sci, Hamilton, ON, Canada
[10] Monash Univ, Sch Geog & Environm Sci, Clayton, Vic 3800, Australia
[11] Tech Univ Dresden, Inst Hydrol & Meteorol, D-01062 Dresden, Germany
[12] Univ British Columbia, Fac Land & Food Syst, Vancouver, BC V5Z 1M9, Canada
[13] Univ Colorado, Dept Geog, Boulder, CO 80309 USA
[14] European Commiss, Joint Res Ctr, Inst Environm & Sustainabil, Ispra, Italy
[15] Univ Liege, Inst Astrophys & Geophys, B-4000 Liege, Belgium
[16] Fdn Edmund Mach, IASMA Res & Innovat Ctr, Sustainable Agroecosyst & Bioresources Dept, I-38010 San Michele All Adige, TN, Italy
[17] Univ Antwerp, Dept Biol, B-2610 Antwerp, Belgium
[18] Max Planck Inst Biogeochem, D-07745 Jena, Germany
[19] CEA CNRS UVSQ Orme Merisiers, IPSL, Lab Sci CLimat & Environm, F-91191 Gif Sur Yvette, France
[20] Univ Coll Cork, Environm Res Inst, Dept Civil & Environm Engn, Cork, Ireland
[21] Autonomous Prov Bolzano, Forest Serv, I-39100 Bolzano, Italy
[22] Free Univ Bolzano, Fac Sci & Technol, I-39100 Bolzano, Italy
[23] CNR, Inst Biometeorol, I-50145 Florence, Italy
[24] CIRAD, UMR Eco & Sols Ecol Fonct & Biogeochim Sols & Agr, F-34060 Montpellier, France
[25] CATIE Trop Agr Ctr Res & Higher Educ, Turrialba 7170, Costa Rica
[26] Russian Acad Sci, AN Severtsov Inst Ecol & Evolut, Moscow 119071, Russia
[27] Univ Innsbruck, Inst Ecol, A-6020 Innsbruck, Austria
基金
湖南省自然科学基金; 美国国家科学基金会; 国家高技术研究发展计划(863计划);
关键词
Gross primary production; Light use efficiency; Seven LUE models; NET ECOSYSTEM EXCHANGE; PHOTOSYNTHETICALLY ACTIVE RADIATION; WATER-VAPOR EXCHANGE; CARBON-DIOXIDE; INTERANNUAL VARIABILITY; LEAF-AREA; PONDEROSA PINE; FOREST; MODIS; SATELLITE;
D O I
10.1016/j.agrformet.2014.03.007
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Simulating gross primary productivity (GPP) of terrestrial ecosystems has been a major challenge in quantifying the global carbon cycle. Many different light use efficiency (LUE) models have been developed recently, but our understanding of the relative merits of different models remains limited. Using CO2 flux measurements from multiple eddy covariance sites, we here compared and assessed major algorithms and performance of seven LUE models (CASA, CFix, CFlux, EC-LUE, MODIS, VPM and VPRM). Comparison between simulated GPP and estimated GPP from flux measurements showed that model performance differed substantially among ecosystem types. In general, most models performed better in capturing the temporal changes and magnitude of GPP in deciduous broadleaf forests and mixed forests than in evergreen broadleaf forests and shrublands. Six of the seven LUE models significantly underestimated GPP during cloudy days because the impacts of diffuse radiation on light use efficiency were ignored in the models. CFlux and EC-LUE exhibited the lowest root mean square error among all models at 80% and 75% of the sites, respectively. Moreover, these two models showed better performance than others in simulating interannual variability of GPP. Two pairwise comparisons revealed that the seven models differed substantially in algorithms describing the environmental regulations, particularly water stress, on GPP. This analysis highlights the need to improve representation of the impacts of diffuse radiation and water stress in the LUE models. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:108 / 120
页数:13
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