Cropland plays a crucial role in agricultural production, significantly impacting crop yield, quality, and the sustainable development of agricultural ecosystems. This study establishes an evaluation index system to assess cropland quality using panel data from 30 Chinese provinces. The research employs the entropy method to quantify cropland quality, the Dagum Gini coefficient to investigate the sources of disparities in cropland quality and the development quality of its subsystems, and various analytical techniques including Kernel density estimation, Markov chains, and spatial convergence to examine the distribution dynamics and evolutionary trends of cropland quality. The findings reveal a consistent upward trend in overall cropland quality in China over the years, with a relatively low Gini coefficient, indicating minor quality fluctuations. Notably, the inter-regional Gini coefficient is highest between China’s eastern and western regions and lowest between the western and northeastern regions. Moreover, the Gini coefficients show an increasing trend among the eastern-central, eastern-western, eastern- northeastern, and central-western regions. Regarding distribution dynamics, the absolute disparities in cropland quality among the eastern, central, and northeastern regions are decreasing but widening in the western region, suggesting a polarization effect among the four major regions, albeit with a tendency towards reduction. The findings from the Markov chain analysis indicate that cropland quality in China tends to be stable, making leapfrog development challenging. From a spatial convergence perspective, the σ coefficient is relatively high for the entire country; however, the western region exhibits a lower σ coefficient. The consistently significant negative β value indicates the presence of absolute β convergence, conditional β convergence, spatial absolute β convergence, and spatial conditional β convergence in the cropland quality index across China and its two major regions, with variations in convergence rates and cycles observed at both national and regional levels.

Under small-scale farming operations, cultivated land protection behaviors (CLPBs) are a feasible path to achieve food security, ecological security, and sustainable agricultural development in China. However, farmers may face operational difficulties because of their lack of motivation or “freeriding” behavior. This study uses survey data from 265 micro farmers in Xingning City, Guangdong Province, to examine the theoretical framework of the impact of social capital and policy cognition on CLPBs. This study uses a partial least squares model to explore the path relationship between the three factors and verify the intermediary mechanism. Results show that (1) social networks, social norms, and social trust have a significant direct impact on CLPBs, with social trust as the leading factor, followed by social norms; (2) different types of social capital will have varying influence on the CLPBs of the farmers; and (3) the influence path of social capital on CLPBs is through the indirect positive influence of policy cognition. Moreover, social networks are the social capital most affected by policy cognition. Therefore, the promotion of the CLPBs of farmers should start from two aspects, that is, the increase of farmers’ social capital and the enhancement of their policy cognition, to improve the pertinence of cultivated land protection policy formulation.

Unbalanced regional development remains a major obstacle to sustainable development. In recent years, China has experienced slower GDP growth, shifting population trends, rural revitalization, and nationwide poverty reduction. It is unclear if China’s core pattern of uneven regional development has changed as a result. This study analyzes county-level data from 2010 to 2020 using five regional categories: poverty-stricken vs. non-poverty- stricken counties, urban-dominant vs. rural-dominant areas, population growth vs. population decline, GDP growth vs. decline, and Eastern, Central, Western, and Northeast China regions. Using the Sustainable Development Index and Theil Index, we calculated 21 county-level sustainability indicators to measure regional gaps across economy, environment, and social services. Results show that as of 2020, the overall sustainable development in China steadily improved. While the disparity between poverty- and non-poverty-stricken counties has largely narrowed, disparities between urban-rural-dominant areas and between Eastern and Western China remain the main challenges. Differences linked to population or GDP changes were not significant. However, many Northeast China regions pose sustainability concerns due to simultaneous population and GDP decline.