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• Both GPP and GPP max in Chinese grasslands showed increases at different space–time scales. • Trend analysis and breakpoint tests were used for the first time to monitor GPP change simultaneously in Chinese grasslands. • GPP max × CUP is a robust indicator to explain annual-scale variation in GPP. At the ecosystem level, Gross Primary Productivity (GPP) was defined as the organic compounds formed by plants that absorb atmospheric CO 2 through photosynthesis and sequester carbon in plant bodies. How to accurately assess the spatiotemporal evolution of ecosystem carbon indicators has become a critical issue to be addressed. Chinese grasslands are located in a typical arid and semi-arid climate zone and are sensitive to global changes, which will inevitably have serious impacts on the function and structure of Chinese grasslands. Based on this, our paper takes Chinese grassland ecosystems as the research area, and used multi-source GPP dataset from terrestrial ecosystem model simulations and remote sensing satellite observations to quantitatively analyze the spatiotemporal evolution patterns of GPP in Chinese grasslands over the past 40 years. We combined trend analysis and breakpoint test, and then to analyze the mechanism components of GPP space–time variability. The main results are as follows: (1) The model and remote sensing estimated GPP results showed that more than 80% of Chinese grasslands show a significant increasing trend over the past 40 years, with growth rates ranging from 0.68 to 3.13 g C/m−2 year−1. (2) GPP max also shows that more than 80% of Chinese grasslands are growing rapidly, with an overall growth rate of more than 0.1 g C/m−2 year−1 in each region. The overall long-term trends and interannual variability of multi-source GPP and GPP max are generally consistent, yet vegetation dynamics in local areas are still uncertain. (3) The breakpoint test showed that 'monotonically increasing' was the largest breakpoint type of GPP in Chinese grasslands (33.09%), and the direction of change of GPP in Chinese grasslands before and after the breakpoint was also increasing. (4) GPP max × CUP explained 91% of the temporal variability of annual-scale GPP in Chinese grasslands from a mechanistic view, and we found that the peak photosynthetic growth and the length of the phenological period synergistically controlled the interannual variability of GPP in Chinese grasslands. Under the scenario of rapid global change, our study accurately assessed the long-term dynamics of GPP and its mechanism-driven of grassland ecosystems in China, which is helpful for estimating and predicting the carbon budget of grassland ecosystems in China, and has important guiding significance for policy formulation to mitigate climate change. [ABSTRACT FROM AUTHOR]

[Display omitted] • As compared to precipitation, soil moisture greatly influences GPP. • There is a solid spatial agreement among PUE and SWUE with a step-wise gradient from southwest to northeast. • PUE and SWUE are relatively low in extremely arid and humid regions. • In relatively moderate areas, PUE and SWUE increase with the abundance of moisture conditions. • Meadow grassland has the highest PUE and SWUE, followed by typical grassland and desert steppe. Grassland ecosystem dominates in the Mongolian Plateau, mostly located in its arid and semi-arid regions. Although the ecosystem is an important source for agriculture, it is also a fragile system ecologically. This system is one of the most sensitive areas to global climate change. Precipitation (PPT) and soil moisture (SM) are important water sources in the grassland ecosystem, and their changes would greatly affect vegetation growth. This paper generates the precipitation use efficiency (PUE) and soil water use efficiency (SWUE) of Mongolian Plateau grassland based on multi-source remote sensing data to investigate the spatio-temporal distribution pattern and identify the driving factors. Results showed four main findings. Firstly, two water use efficiency (WUE) indicators show a generally increasing trend from 2000 to 2018, with average PUE and SWUE 1.07 gC·m−2·mm−1 and 1.03 gC/kg·H 2 O, respectively. They have similar spatial distribution patterns, consistent with the available water resources, decreasing from northeast to southwest. However, grassland vegetation growth is more sensitive to soil moisture than precipitation, and the dynamic change of SWUE is smoother and more significant than PUE. Secondly, due to the higher species richness, better vegetation biological characteristics and less severe growth environment, meadow grassland has the highest PUE and SWUE, followed by typical grassland and desert steppe. Thirdly, PUE and SWUE are relatively low in extremely arid and humid regions. In areas with relatively moderate water conditions (PPT in 148–360 mm, SM in 0.14–0.35 cm3/cm3), two indicators increase with the abundance of moisture conditions and reach the maximum. Fourthly, there is a positive linear relationship between PUE (SWUE) with precipitation and a unimodal correlation between PUE (SWUE) with temperature across the entire grassland. However, a varying correlation exists in different grassland ecosystems, especially meadow grassland. Together with analyzing past and future trends, this study provides strong evidence to reflect the impact of global climate change and the management and protection of the grassland ecosystems in arid and semi-arid regions. [ABSTRACT FROM AUTHOR]