Effects of ecosystem types on the spatial variations in annual gross primary productivity over terrestrial ecosystems of China

Annual gross primary productivity (AGPP) serves as the basis for forming biomass and carbon sinks. Analysing the effects of ecosystem types on AGPP spatial variations would be beneficial for clarifying the spatial variability in AGPP, which would serve ecological management practices such as ensuring regional food security. Based on published eddy covariance measurements in China, we collected AGPP data from 128 ecosystems and analysed the effects of ecosystem types on the spatial variations in AGPP to reveal the AGPP spatial variability and its influencing factors over terrestrial ecosystems of China. The results showed that AGPP significantly differed among ecosystem types and vegetation regions, with the lowest AGPP appearing in grasslands, while different ecosystem types had comparable AGPP within the same vegetation region. The AGPP of all ecosystem types showed a decreasing latitudinal trend but slight longitudinal and altitudinal trends. Mean annual air temperature (MAT) and mean annual precipitation (MAP) were found to affect the spatial variations in AGPP over most ecosystem types, while other factors played little role. The mean annual leaf area index (LAI) and the maximum leaf area index (MLAI) were also found to affect the spatial variations in AGPP over most ecosystem types. Factors influencing the AGPP spatial variations differed among ecosystem types, but all included climatic and biotic factors. Therefore, climate inducing spatial distribution of ecosystem types and the non-zonal water supply made AGPP values and factors affecting the spatial variations in AGPP differ among ecosystem types, while different ecosystem types within the same vegetation region had comparable AGPP values. The spatial variation in AGPP over terrestrial ecosystems of China resulted from the integrated effects of climatic and biotic factors. Our study provided data support for improving the understanding of global AGPP spatial variability.