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Wu, WX, Wang, SQ, Xiao, XM, Yu, GR, Fu, YL, Hao, YB (2008). "Modeling gross primary production of a temperate grassland ecosystem in Inner Mongolia, China, using MODIS imagery and climate data". SCIENCE IN CHINA SERIES D-EARTH SCIENCES, 51(10), 1501-1512.

Abstract
Carbon fluxes in temperate grassland ecosystems are characterized by large inter-annual variations due to fluctuations in precipitation and land water availability. Since an eddy flux tower has been in operation in the Xilin Gol grassland, which belongs to typical temperate grassland in North China, in this study, observed eddy covariance flux data were used to critically evaluate the biophysical performance of different remote sensing vegetation indices in relation to carbon fluxes. Furthermore, vegetation photosynthesis model (VPM) was introduced to estimate gross primary production (GPP) of the grassland ecosystem for assessing its dependability. As defined by the input variables of VPM, Moderate Resolution Imaging Spectroradimeter (MODIS) and standard data product MOD09A1 were downloaded for calculating enhanced vegetation index (EVI) and land surface water index (LSWI). Measured air temperature (Ta) and photosynthetically active radiation (PAR) data were also included for model simulating. Field CO2 flux data, during the period from May, 2003 to September, 2005, were used to estimate the observed GPP (GPP(obs)) for validation. The seasonal dynamics of GPP predicted from VPM (GPP(VPM)) was compared quite well (R-2=0.903, N=111, p<0.0001) with the observed GPP. The aggregate GPP(VPM) for the study period was 641.5 g C.m(-2), representing a similar to 6% over-estimation, compared with GPP(obs). Additionally, GPP predicted from other two typical production efficiency model (PEM) represents either higher overestimation or lower underestimation to GPP(obs). Results of this study demonstrate that VPM has potential for estimating site-level or regional grassland GPP, and might be an effective tool for scaling-up carbon fluxes.

DOI:
10.1007/s11430-008-0113-5

ISSN:
1006-9313

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