Abstract
The nature and extent of climate and soil nutrient controls in Chinese forests remain poorly resolved. Here, we synthesized the data on carbon–climate–soil in eastern China, and litter N was firstly taken into consideration, to examine the variation of net primary productivity (NPP) and its driving forces. Results showed that NPP had significant latitude pattern and varied substantially across climate zones. Bivariate analyses indicated that mean annual temperature (MAT), mean annual precipitation (MAP), soil N content (Nsoil), and annual litter N (Nre) were the main controlling factors in spatial pattern of forest NPP. Notably, partial general linear model analysis revealed that MAT, MAP, and Nre jointly explained 84.8% of the spatial variation of NPP. Among the three major factors, Nre explained more variation of forest NPP than the other two factors, and MAT and MAP affected NPP mainly through the change of litter N rather than via themselves, highlighting the importance of litter N in estimating forest NPP. However, to accurately describe the pattern of forest NPP in China, more detailed field measurements and methodologies on NPP and relevant confounding factors should be addressed in future studies.
Highlights
Net primary productivity (NPP) is a key ecosystem variable and a critical component of the regional and global carbon cycle [1,2]
To confirm the effects of climate and soil on net primary productivity (NPP), partial general linear model (GLM) was conducted, and the results showed that the overall model including mean annual temperature (MAT), mean annual precipitation (MAP), and Nre, could account for 84.8% of the spatial variation in NPP (Figure 5)
Based on published data from Chinese literature and reports, we concluded that NPP increased from north to south within the North–South Transect of Eastern China (NSTEC), and high spatial variation of NPP was found among climate zones
Summary
Net primary productivity (NPP) is a key ecosystem variable and a critical component of the regional and global carbon cycle [1,2]. Accurate estimation of NPP and its driving forces is essential to understanding terrestrial carbon pools and responses of forest functions to future climate change [6,7]. Based on global NPP data, Lieth (1975) [8] developed the climate-driven theory, and described the relationship between climatic factors (annual mean temperature, annual precipitation, and annual evapotranspiration) and NPP in logistic functions. It is still unclear whether regional NPP across biomes follows the same pattern [12,13], since the driving factors vary among regions [14,15,16]. An international coordination for compilation of global NPP data for model validation and development, the Global
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