| Summary: | Abstract Background Net primary productivity (NPP) in forests plays an important role in the global carbon cycle. However, it is not well known about the increase rate of China’s forest NPP, and there are different opinions about the key factors controlling the variability of forest NPP. Methods This paper established a statistics-based multiple regression model to estimate forest NPP, using the observed NPP, meteorological and remote sensing data in five major forest ecosystems. The fluctuation values of NPP and environment variables were extracted to identify the key variables influencing the variation of forest NPP by correlation analysis. Results The long-term trends and annual fluctuations of forest NPP between 2000 and 2018 were examined. The results showed a significant increase in forest NPP for all five forest ecosystems, with an average rise of 5.2 gC·m− 2·year− 1 over China. Over 90% of the forest area had an increasing NPP range of 0–161 gC·m− 2·year− 1. Forest NPP had an interannual fluctuation of 50–269 gC·m− 2·year− 1 for the five major forest ecosystems. The evergreen broadleaf forest had the largest fluctuation. The variability in forest NPP was caused mainly by variations in precipitation, then by temperature fluctuations. Conclusions All five forest ecosystems in China exhibited a significant increasing NPP along with annual fluctuations evidently during 2000–2018. The variations in China’s forest NPP were controlled mainly by changes in precipitation.
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