文献类型：期刊文献

英文题名：Estimation of gross primary production over the terrestrial ecosystems in China

作者：Li, Xianglan[1,2,3] Liang, Shunlin[1,2,3,4] Yu, Guirui[5] Yuan, Wenping[1,2,3] Cheng, Xiao[1,2,3] Xia, Jiangzhou[1,2,3] Zhao, Tianbao[6] Feng, Jinming[3,6] Ma, Zhuguo[6] Ma, Mingguo[7] Liu, Shaomin[8] Chen, Jiquan[9,10] Shao, Changliang[11] Li, Shenggong[12] Zhang, Xudong[13] Zhang, Zhiqiang[14] Chen, Shiping[11] Ohta, Takeshi[15] Varlagin, Andrej[16] Miyata, Akira[17] Takagi, Kentaro[18] Saiqusa, Nobuko[19] Kato, Tomomichi[20]

第一作者：Li, Xianglan

通信作者：Liang, SL[1];Liang, SL[2]

机构：[1]Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China;[2]Chinese Acad Sci, State Key Lab Remote Sensing Sci, Inst Remote Sensing & Digital Earth, Beijing 100875, Peoples R China;[3]Beijing Normal Univ, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China;[4]Univ Maryland, Dept Geog, College Pk, MD 20742 USA;[5]Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Synth Res Ctr, Key Lab Ecosyst Network Observat & Modeling,Chine, Beijing 100101, Peoples R China;[6]Chinese Acad Sci, Inst Atmospher Phys, Key Lab Reg Climate Environm Res Temperate East A, Beijing 100029, Peoples R China;[7]Chinese Acad Sci, Cold & Arid Regions Environm & Engn Res Inst, Lanzhou 730000, Gansu, Peoples R China;[8]Beijing Normal Univ, Sch Geog, Sate Key Lab Remote Sensing Sci, Beijing 100875, Peoples R China;[9]Nanjing Univ Informat Sci & Technol, Int Ctr Ecol, Meteorol & Environm IceMe, Nanjing 210044, Jiangsu, Peoples R China;[10]Univ Toledo, Dept Environm Sci, Toledo, OH 43606 USA;[11]Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China;[12]Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;[13]Chinese Acad Forestry, Inst Forestry Res, Beijing 100091, Peoples R China;[14]Beijing Forestry Univ, Coll Soil Water Conservat, Beijing 100083, Peoples R China;[15]Nagoya Univ, Grad Sch Bioagricultural Sci, Chikusa Ku, Nagoya, Aichi 4648601, Japan;[16]Russian Acad Sci, AN Severtsov Inst Ecol & Evolut, Moscow 119071, Russia;[17]Natl Inst Agroenvironm Sci, Tsukuba, Ibaraki 3058604, Japan;[18]Hokkaido Univ, Ctr Northern Biosphere, Field Sci Ctr No Biosphere, Horonobe, Teshio 0982943, Japan;[19]Natl Inst Environm Studies, Ctr Global Environm Res, Tsukuba, Ibaraki 3058506, Japan;[20]Natl Inst Environm Studies, Tsukuba, Ibaraki 3058569, Japan

年份：2013

卷号：261

起止页码：80-92

外文期刊名：ECOLOGICAL MODELLING

收录：;EI(收录号：20132116364746);Scopus(收录号：2-s2.0-84877918056);WOS:【SCI-EXPANDED(收录号:WOS:000320494800008)】；

基金：We acknowledge the financial support from National High Technology Research and Development Program of China (863 Program) (2013AA122003), and National Key Basic Research and Development Plan of China (2011CB952001) and the Fundamental Research Funds for the Central Universities. We also acknowledge the Coordinated Observations and Integrated Research over Arid and Semi-arid China (COIRAS) (lead by Key Laboratory of Regional Climate-Environment Research for the Temperate East Asia (REC-TEA)).

语种：英文

外文关键词：EC-LUE model; Gross primary production; Eddy covariance; MODIS; MERRA

摘要：Gross primary production (GPP) is of significant importance for the terrestrial carbon budget and climate change, but large uncertainties in the regional estimation of GPP still remain over the terrestrial ecosystems in China. Eddy covariance (EC) flux towers measure continuous ecosystem-level exchange of carbon dioxide (CO2) and provide a promising way to estimate GPP. We used the measurements from 32 EC sites to examine the performance of a light use efficiency model (i.e., EC-LUE) at various ecosystem types, including 23 sites in China and 9 sites in adjacent areas with the similar climate environments. No significant systematic error was found in the EC-LUE model predictions, which explained 79% and 62% of the GPP variation at the validation sites with C-3 and C-4 vegetation, respectively. Regional patterns of GPP at a spatial resolution of 10 km x 10 km from 2000 to 2009 were determined using the MERRA (Modern Era Retrospective-analysis for Research and Applications) reanalysis dataset and MODIS (MOD-erate resolution Imaging Spectroradiometer). China's terrestrial GPP decreased from southeast toward the northwest, with the highest values occurring over tropical forests areas, and the lowest values in dry regions. The annual GPP of land in China varied between 5.63 Pg C and 6.39 Pg C, with a mean value of 6.04 Pg C, which accounted for 4.90-6.29% of the world's total terrestrial GPP. The GPP densities of most vegetation types in China such as evergreen needleleaf forests, deciduous needleleaf forests, mixed forests, woody savannas, and permanent wetlands were much higher than the respective global GPP densities. However, a high proportion of sparsely vegetated area in China resulted in the overall low GPP. The inter-annual variability in GPP was significantly influenced by air temperature (R-2 = 0.66, P < 0.05), precipitation (R-2 = 0.71, P < 0.05), and normalized difference vegetation index (NDVI) (R-2 = 0.83, P < 0.05), respectively. Published by Elsevier B.V.