Estimation and influencing factors analysis of vegetation net primary productivity (NPP) in Northeast China

摘要

The Northeast China as the sensitive area of global climate change, there was important significance for regional and even global terrestrial ecosystem carbon cycle analyzing vegetation net primary productivity (NPP) and the relationship with temperature and precipitation. We used MODIS NDVI data, along with synchronous meteorological data to estimate vegetation NPP based on improved CASA model, through comparing estimation to others'' research results and real-test data collected from papers to validate simulation precision. Analyzing spatial distribution pattern, seasonal variation characteristics and main influencing factors of vegetation NPP we found that: The model estimate of annual mean NPP of Northeast China in 2008 was 451.61 gC·m−2·a−1 with total NPP 0.56 Pg C (1Pg=1015g). For different vegetation, annual average NPP from high to low was alpine vegetation >forest>swamp>cropland>grassland. For seasonal variation, vegetation NPP presented increasing first and then decreasing, what''s more, spring and winter NPP was lowest, highest NPP showed in summer, almost the maximum value for all vegetation were appeared in July. Correlation analysis showed that temperature and precipitation correlated significantly with estimated NPP, especially precipitation, with more obvious promotion for vegetation NPP increasing.