Distribution and Seasonal Change of Net Primary Productivity in China from April, 1992 to March, 1993
SUN Rui, Zhu Qi jiang (Department of Resource and Environment Sciences, Beijing Normal University, Beijing\ 100875)
It is significant to estimate terrestrial net primary productivity (NPP) accurately not only for global change research, but also for natural resources management to achieve sustainable development. The estimation of NPP by climate data is only a potential NPP rather than true NPP. But remote sensing data can describe large scale distribution of plant resources better. So, 1 km AVHRR NDVI data was used adopted here to estimate the distribution of NPP in China. First, the fraction of absorbed photosynthetically active radiation (FPAR) by vegetation is derived from NDVI data using the linear relationship between FPAR and vegetation index. The incident PAR was estimated by climate data. Then NPP was calculated with absorbed PAR and energy efficiency ε * g . In order to estimate NPP more accurate, the effects of temperaturely, soil water content and plant respiration were also considered in the model. The model can be described as below:NPP=ε g×f 1(T)×f 2(β)×FPAR×PAR-Rin which f 1(T) and f 2(β) mean the temperature and soil water content effects on photosynthesis, R means plant respiration including maintenance respiration and growth respiration. Monthly and annual net primary productivity in China was computed by monthly 1km AVHRR NDVI data, climate data between April, 1992 and March, 1993, vegetation type map and soil texture map. The results gained were compared with ground-observation and Miami model results. It shows that the results using remote sensing data are closer to truth. Total annual NPP in China is 2 645×10 9tC. The distribution of NPP in China is mainly effected by precipitation and has the trend of decreasing from south east to north west. Finally, the seasonal change of NPP was investigated on the basis of monthly NPP.