Estimation of gross primary production over the terrestrial ecosystems in China

Estimation of gross primary production over the terrestrial ecosystems in China

Ecological Modelling

Abstract 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 C3 and C4 vegetation, respectively. Regional patterns of GPP at a spatial resolution of 10 km × 10 km from 2000 to 2009 were determined using the MERRA (Modern Era Retrospective-analysis for Research and Applications) reanalysis dataset and MODIS (MODerate 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 (R2 = 0.66, P < 0.05), precipitation (R2 = 0.71, P < 0.05), and normalized difference vegetation index (NDVI) (R2 = 0.83, P < 0.05), respectively.