Protecting and improving the quality of cultivated land is important to agricultural modernization. Based on data from a survey of 706 rice-growing households in Hunan, Jiangxi and Jiangsu, this paper uses the Probit model, CMP method and Biprobit model to systematically analyze the impact of agricultural socialized services on farmers’ cultivated land quality protection behaviors. This study finds that agricultural socialized services have a significantly positive impact on the adoption of soil testing formulas and straw returning technology among farmers, which can improve both the probability and the degree of cultivated land quality protection. The heterogeneity test results suggest that agricultural socialized services provide a higher incentive for the older generation of farmers to adopt arable land quality protection. In addition, we found that agricultural socialized services are more conducive to the protection of contracted land than transferred land. Therefore, we recommend that policies on agricultural socialized services be further implemented, the supply of agricultural socialized services be optimized, and the role of service organizations in publicizing and promoting cultivated land protection techniques be brought into play. We also posit that the simultaneous encouragement of farmers in using agricultural socialized services would protect the quality of cultivated land. During this process, additional attention should be paid to the response differentiation of peasants with different characteristics.
Agriculture has the dual effect of contributing to both carbon emissions and sequestration, and thus plays a critical role in mitigating global climate change and achieving carbon neutrality. Agricultural eco-efficiency (AEE) is an important measurement through which we can assess the efforts toward reduced emissions and increased sequestration. The purpose of this study was to understand the relationship between China’s target of carbon neutrality and AEE through an evaluative model, so as to improve AEE and ultimately achieve sustainable agricultural development. The Super-SBM model scientifically measures the AEE based on provincial panel data collected between 2000 and 2020. We selected kernel density function and spatial distribution to explore the spatial and temporal evolutionary trends, and used a Tobit model to identify the drivers of AEE. The research shows that (1) China’s agricultural system functions as a net carbon sink, with all provinces’ agricultural carbon sequestration levels recorded as higher than their carbon emissions from 2000 to 2020. (2) Despite sequestration levels, the level of AEE in China is not high enough, and the average efficiency level from 2000 to 2020 is 0.7726, showing an overall trend where AEE decreased at first and then increased. (3) The AEE of each province is clearly polarized; there are obvious core–periphery characteristics and spatial distribution of clustered contiguous areas. Central provinces generally have lower efficiency, eastern and northeastern provinces have higher efficiency, and northeastern provinces always remain in the high-efficiency group. (4) Influencing factors show that urbanization, upgrading of industrial structure, financial support for agriculture, and mechanization have a significant positive impact on AEE. These findings have important implications for the promotion of the low-carbon green development of Chinese agriculture.
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