Evaluating the monthly and interannual variation of net primary production in response to climate in Wuhan during 2001 to 2010

Abstract

As the difference between photosynthesis, or gross primary productivity (GPP), and autotrophic respiration (RA), net primary productivity (NPP) is a key component of the terrestrial carbon cycle. The temporal and spatial response of NPP to climate change is thus one of the most important aspects in the study of climate-vegetation relationship. In this study, we developed a new method to estimate NPP accurately by finding a linear relationship between solar radiation and photosynthetically active radiation (PAR) and improving maximum light use efficiency (LUE) of vegetation, which could be adopted and used in other regions of the world. We utilize normalized difference vegetation index (NDVI) datasets of Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2010 and geographic information system (GIS) techniques to reveal the monthly and interannual change of NPP in Wuhan, China. We also applied the lagged cross-correlation analysis method to study the delayed and continuous effects on monthly and interannual variations of NPP to climatic factors (air temperature, precipitation, total radiation and sunshine percentage). The result showed that precipitation and total radiation were the major climatic factors influencing monthly variation of NPP, and sunshine percentage mostly determined the interannual variation of NPP for different vegetation. Monthly NPP showed significant positive correlation with total radiation of that month, and the effect could persist for one month; significant positive one month lagged correlation was also observed between monthly variation of NPP and precipitation, and the influences of changing climate on NPP would last for two months.