The increasing scarcity of cultivated land resources necessitates the continuous change in cultivated land functions. Cultivated land has gradually changed from being used for a single function to multiple functions. The use of cultivated land for multiple functions has become an important way to achieve the sustainable use, management, and protection of cultivated land. In this, the development of different functions of cultivated land must be coordinated. Thus, clarifying the evolution trend of the use of cultivated land for various functions, calculating the coupling and coordination degrees of these multiple functions, and identifying the driving factors in these uses play important roles in realizing the orderly development of cultivated land multifunctionality. This paper defined multifunctioning cultivated land as containing a production function, a social function, and an ecological function. Based on the socioeconomic panel data and geospatial data of Heilongjiang, Jilin, and Liaoning, which are the major grain-producing areas of northeast China, in the years 2005, 2010, 2015, and 2020 we calculated the multiple function coupling coordination degree of cultivated land using the Coupling Coordination Degree Model and identified the driving forces in the evolution of the spatial-temporal pattern of cultivated land multifunctionality using Geodetector. The results show that from 2005 to 2020, there were significant regional differences in terms of the production, social, and ecological functions of cultivated land in the research areas. The multifunctional coupling coordination degree of cultivated land in the study areas was gradually improved. The spatial-temporal evolution of the multifunctional coupling coordination degree of cultivated land was found to mainly be influenced by the level of agricultural development, such as the level of per capita disposable income and the rate of effective irrigation of cultivated land. The government should attempt to guarantee the comparative benefits of agricultural production to increase the income level of farmers; increase investment in agricultural infrastructure construction to improve the level of agriculture development; and implement a strict farmland protection policy to achieve the continuous improvement of the productivity of cultivated land, realize the ordered development of coupling, and improve the coordination of the use of cultivated land for multiple functions. The results of this study are applicable not only to northeast China but also to other major grain-producing areas that are under pressure to protect their cultivated land and achieve the suitable use of cultivated land.

China’s rural land transfer market has been plagued by issues including poor information transmission, limited scale, and an incoherent structure. In this context, this study collected the data of 337 farmers in Qufu City, Shandong Province, and incorporated into the analysis the acquaintance-based nature of rural society that includes strong geographic ties. Taking the herd effect as the starting point, this paper it considers how farmers in the same geo-network affect the land transfer behavior of individual farmers, and adopts the Probit model to analyze the impact of geo-networks to verify the function of the herd effect in farmers’ land transfer behavior. Then, the IV-Probit model is applied to solve the endogenous problem of the herd effect. The results show that: (1) Farmers imitate the land transfer behavior of other farmers in the same geo-network. Geo-networks positively impact the land transfer behavior of farmers, and the herd effect is apparent in farmers’ land transfer behavior. (2) Farmers’ family background, resource endowment, and cognitive features are key factors that influencing farmers’ land transfer behavior. (3) Farmers’ land transfer behavior is more significantly influenced in groups with low and middle agricultural income than in groups with high agricultural income. This study aims to assist the government in giving full play to the positive role of the herd effect, promoting the leading role of village cadres as leader sheep, and smoothing the transmission of land transfer information. Governments should place more emphasis on developing land transfer platforms and invest more in the construction of farmland infrastructure. This paper may serve as a reference to achieve large-scale agriculture operation via land transfer and promote the prosperity of the land transfer market.

Research on land resource carrying capacity (LRCC) focuses on the population that regional land resources can support as well as the grain output they can deliver. China’s major grain-producing areas consist of 13 provinces, and the grain produced in these areas makes up 75% of the country’s gross grain output. To boost the land carrying capacity of major grain-producing areas and to ensure national food security, it is crucial to examine the spatial–temporal evolution patterns of LRCC and to devise optimal regulatory strategies. From the perspective of human–grain relationships, this paper looks into the evolutionary features of the spatial–temporal patterns of the LRCC of China’s major grain-producing areas based on a land resource carrying capacity model, a land resource carrying capacity index model, and a land resource limitation model. We obtain three main results: (1) On the temporal scale, the land resource carrying capacity index (LRCCI) of China’s major grain-producing areas as a whole tapered off over a period from 1980 to 2020, whereas the overall LRCC increased in this period, indicating that the human–grain relationship in China’s major grain-producing areas is improving. (2) On a spatial scale, China’s major grain-producing areas ranked by LRCC from the greatest to the lowest, in 2020, were North China, the middle and lower reaches of the Yangtze River, Northeast China, and other regions. In terms of the carrying state of land resources, provinces with grain surpluses significantly rose during 1980–2020, the growth of LRCC of the aforementioned four major regions markedly slowed down in 2015–2020, and a large gap exists in LRCCI between the 13 provinces, revealing an unbalanced, insufficient development of LRCC in each province. (3) From 2000 to 2020, the limit of land resources on population aggregation in most major grain-producing areas was negative, and its absolute value continued to increase; this suggests that the land resources of major grain-producing provinces set small limits on population aggregation, with great potential for increasing LRCC. Taking into account the research results, this paper gives strategies for regulating the LRCC of China’s major grain-producing areas in a bid to further augment the human–grain carrying capacity of land resources in China’s major grain-producing areas and to guarantee national food security.

Major grain-producing areas in Northeast China serve as a significant national commodity in their role as grain bases. In order to achieve sustainable land use in such areas and ensure national food security, it is critical to understand the spatial–temporal evolution features of the land comprehensive carrying capacity of such areas, ascertain major obstacle factors and propose regulatory policies for effectively improving the land comprehensive carrying capacity. In this paper, a TOPSIS model based on grey relational entropy weight is developed to analyze the spatial–temporal evolution features of the land comprehensive carrying capacity of major grain-producing areas in Northeast China from 2000 to 2020, and an obstacle degree model is employed to determine the main obstacles to improving the land comprehensive carrying capacity of major grain-producing areas in Northeast China. The study results show the following: (1) The land comprehensive carrying capacity of major grain-producing areas in Northeast China is at a low level, showing an N-shaped trendline, and its spatial–temporal evolution features are subject to changes in land food carrying capacity, land economic carrying capacity and land ecological carrying capacity.(2) The main obstacle factors for improving the land comprehensive carrying capacity of major grain-producing areas in Northeast China are urbanization rate, gross industrial output per hectare and industrial solid waste emission per hectare. Cultivated land area per capita, grain output per hectare and industrial wastewater discharge per hectare have recently become obstacle factors for the land comprehensive carrying capacity of the study areas. Based on these results, the paper proposes regulatory strategies for stabilizing agricultural population transfer to avoid its reversal, exploring the optimization and upgrading of secondary sector structures to promote a low-carbon transition to green industries, and implementing cultivated land protection policies to steadily boost cultivated land grain productivity, with a view to increasing the land comprehensive carrying capacity of major grain-producing areas in Northeast China. The findings of this study act as a scientific reference for enhancing the land comprehensive carrying capacity of major grain-producing areas in Northeast China, which is crucial for ensuring national food security.