###### Abstract  
As the country with the highest food consumption in the world, China's food security has been drawing global attention. The inter-annual variability of agricultural productivity and its predominant driving factors play important roles in food security and sustainable agricultural development. Here, we used gross primary productivity (GPP), which was simulated using the vegetation photosynthesis model (VPM), to quantify the spatial-temporal heterogeneity of cropland productivity from 2000 to 2015. The results showed that the cropland GPP significantly increased in northern China and markedly decreased in southern China. Socioeconomic and climatic factors jointly promoted a rise in GPP in the Northeast region, Inner Mongolia and Great Wall region, Huang-Huai-Hai region, and Loess Plateau region, with contribution rates of 93.6%, 67.9%, 73.8%, and 78.1%, respectively. The negative GPP trend in southern China was mainly attributed to the decreasing cropping intensity, with direct contributions of 54.1%, 53.9%, and 48.7% for the Yangtze River region, Southwest region, and South China region, respectively. Despite the decline in cropping intensity, the policies of Cang-liang-yu-di and Cang-liang-yu-ji can help in ensuring food security in China. cropland productivity; gross primary productivity; cropping intensity; vegetation photosynthesis model; China +
Footnote †: journal: Journal of the Royal Society B: Biological and Physical Sciences  
1202  
inputs have significantly improved crop yield [12; 13; 14]. Additionally, harvested area is another important factor that affects total cropland productivity [8]. The unprecedented growth of the population and economy has led to a decrease in the area of cropland over the past decades [15; 16]. Fortunately, cropping intensity, which refers to the cropping frequency in a given cropland area per year, provides another promising opportunity to boost crop production [17], and multiple cropping is an important component of Chinese farming practices, especially in southern China, where intensive cropping has been widely deployed [18]. In the past decades, multiple cropping has played an especially important role in ensuring the food security of China [19]. Research has shown that part of south China experienced a marked decrease in cropping intensity [20], although these regions have the largest potential to increase their harvested area and have a strong irrigation infrastructure [8]. The socioeconomic factors that affect cropland productivity vary at field, regional, and global scales [21]. The amount of change in cropland productivity due to socioeconomic factors is still unknown, especially on large scales. Additionally, cropland productivity has also been affected by climatic change [14; 22]. To ensure the sustainable promotion of grain yield and achieve food security, it is necessary to evaluate the productivity of Chinese cropland and the factors that influence Chinese cropland. Understanding the influences of recent policies and changes in climatic factors is important for sustainable development not only in China but also in the rest of the world. Gross primary productivity (GPP) quantifies the total amount of CO\({}_{2}\) fixed by plants through photosynthesis and is an important indicator for monitoring the productivity of vegetation [23; 24]. Terrestrial ecosystem productivity cannot be directly measured at the regional scale [25]. Therefore, with the rapid development of satellite technology in the past decades, remote sensing-driven models have been widely used to estimate terrestrial productivity [26; 27; 28; 29; 30; 31]. Among these models, the vegetation photosynthesis model (VPM), a typical light use model [32; 33], has been extensively used. Recent studies have indicated that the VPM has a superior performance in site-level validations of agricultural ecosystems [34; 35; 36] and a satisfactory performance at regional and global scales [37; 38; 39].