This study investigates the impact of rural digital economy development on agricultural carbon emission efficiency, aiming to elucidate the intrinsic mechanisms and pathways through which digital technology enables low-carbon transformation in agriculture, thereby contributing to the achievement of agricultural carbon neutrality goals. Based on provincial-level panel data from China spanning 2011 to 2022, this study examines the relationship between the rural digital economy and agricultural carbon emission efficiency, along with its underlying mechanisms, using bidirectional fixed effects models, mediation effect analysis, and Spatial Durbin Models. The results indicate the following: (1) A significant N-shaped-curve relationship exists between rural digital economy development and agricultural carbon emission efficiency. Specifically, agricultural carbon emission efficiency exhibits a three-phase trajectory of “increase, decrease, and renewed increase” as the rural digital economy advances, ultimately driving a sustained improvement in efficiency. (2) Industrial integration acts as a critical mediating mechanism. Rural digital economy development accelerates the formation of the N-shaped curve by promoting the integration between agriculture and other sectors. (3) Spatial spillover effects significantly influence agricultural carbon emission efficiency. Due to geographical proximity, regional diffusion, learning, and demonstration effects, local agricultural carbon emission efficiency fluctuates with changes in neighboring regions’ digital economy development levels. (4) The relationship between rural digital economy development and agricultural carbon emission efficiency exhibits a significant inverted N-shaped pattern in regions with higher marketization levels, planting-dominated areas of southeast China, and digital economy demonstration zones. Further analysis reveals that within rural digital economy development, production digitalization and circulation digitalization demonstrate a more pronounced inverted N-shaped relationship with agricultural carbon emission efficiency. This study proposes strategic recommendations to maximize the positive impact of the rural digital economy on agricultural carbon emission efficiency, unlock its spatially differentiated contribution potential, identify and leverage inflection points of the N-shaped relationship between digital economy development and emission efficiency, and implement tailored policy portfolios—ultimately facilitating agriculture’s green and low-carbon transition.

A path of green, low-carbon development in agriculture is to be explored in the face of global warming, which promotes sustainable development. Taking the policy of the main grain-producing area (MGPA) as a special background, this study shows the impact of the MGPA on reducing agricultural carbon emissions (ACEs). In the empirical analysis, a difference-in-differences (DID) model was constructed using panel data from 1999 to 2020 across 31 provinces in China to examine the impact of the MGPA on agricultural carbon emission reduction (ACER). The findings indicate the following: (1) The ACER is significantly promoted after the implementation of the MGPA policy. The results passed robustness and endogeneity tests. (2) The mechanism test reveals that the policy can achieve said reduction by advancing the level of planting specialization. (3) An analysis of the heterogeneity reveals that the implementation of this policy leads to a substantial decrease in ACE in regions characterized by lower economic development and imbalances in the structure of factors involved in agricultural production. Furthermore, in areas where small-scale farming prevails, the policy demonstrates enhanced effectiveness in ACER. The outcomes of this study not only elucidate the link between the MGPA and ACE but also serve as a valuable roadmap for achieving ACER and sustainable development. Additionally, they contribute to expanding the notion of environmentally friendly, low-carbon agriculture in the context of small-scale farming.

A major driving force behind China’s low-carbon, environmentally friendly development of agriculture and the accomplishment of the “dual-carbon” goal is the digital transformation of rural areas. In this study, on the basis of clarifying the degree of rural digitization and agricultural carbon emissions efficiency in China from 2010 to 2021, the degree of coupled coordination and the spatiotemporal pattern characteristics between the two are examined using the coupled coordination model. Then, the influencing factors are analyzed in depth using the spatial Durbin model. Our findings reveal that, first, in terms of the degree of rural digitization, the index increases overall and the spatial imbalance is obvious, with a spatial distribution pattern of “high in the east and low in the west”. Regarding the efficiency of agricultural carbon emissions, there is an overall “N-shaped” change, which is mainly influenced by technological progress in agricultural production, and the regional annual averages are, in descending order, the Western, Eastern, Northeastern, and Central regions, with obvious regional differences. Second, the coupling coordination index shows a fluctuating upward trend, from “extreme disorder” to “high-level coordination”. Furthermore, there are obvious regional characteristics. The regional growth rates are, in descending order, the Western, Eastern, Central, and Northeastern regions. Third, coupling coordination is jointly influenced by a variety of factors, including government input, educational level, industrial structure, energy use, urbanization rate, living standards, driving temporal patterns, and regional differences. This study not only helps to clarify the relationship between the two, offering a reference for the realization of the “dual-carbon” goal, but also broadens the concepts of the low-carbon and environmentally friendly development of agriculture.

Transforming the forestry development model and promoting the integrated development of the forestry industry has become an important way for forestry to break through development bottlenecks and achieve efficiency enhancement, prosperity of forest areas, and income increase for forest farmers. In this study, we have theoretically elaborated on the mechanism by which the integrated development of the forestry industry affects the income level of forest farmers. In terms of empirical research, we use the inter provincial panel data from 2005 to 2019 to empirically test the individual heterogeneity, regional heterogeneity, and spatial spillover effects of forestry industry integration on forest farmer income with the help of fixed effect model, quantile regression model and spatial panel model. Results showed that, firstly, the level of integration in the forestry industry is on the rise, with most provinces in the middle or high integration stage. Among them, the Northeast region has the highest level of integration. Secondly, there is a positive spatial correlation in the income of Chinese forest farmers, and the spatial correlation is gradually increasing. The income of forest farmers in coastal provinces is relatively high, as indicated by the presence of HH clusters. Thirdly, the integration of the forestry industry has significantly improved the income level of forest farmers, and there are group heterogeneity and regional differences. The heterogeneity of income is reflected in the increasing income effect of forestry industry integration, which continuously strengthens with the improvement of the income level of forest farmers. Regional heterogeneity is mainly manifested in the Northeastern, Eastern, and Central regions. The integration of forestry industries can significantly promote the growth of forest farmers’ income, while in the Western regions, the income increase effect of forestry industry integration has an inhibitory effect, but is not significant. Finally, the integration of the forestry industry has significant spatial spillover effect and the indirect effect is greater than the direct effect. However, the spillover effect coefficient is 0.007, which is still at a relatively low level, and the diffusion effect generated by factor flow still needs to be strengthened. Efforts to boost integrated forestry industry development will broaden the income channels of forest farmers by leveraging high productivity of the agglomeration effects, diffusion effect and demonstration effect, strengthening regional communication and cooperation, and promoting integrated forestry industry development with adjacent regions. This study helps to correctly grasp the relationship between forestry industry integration and farmers’ income, and provides decision-making reference for local governments to formulate policies for increasing farmers’ income in the development of forestry industry integration based on actual situations.

Given the increasing environmental pressures, it is essential that agriculture achieves the goal of sustainable and low-carbon development. In 2010, China, as the top carbon emitter, introduced a policy on agricultural land lease (ALL), which has been met with considerable approval from farmers and has resulted in a notable surge in the rate of ALL within the country. Nevertheless, the question of how the ALL policy affects agricultural carbon emissions (ACEs) remains unanswered. What are the transmission mechanisms? To answer these questions, this paper presents an equilibrium model that accounts for the heterogeneous production efficiency among farmers. It offers a theoretical analysis of the impact of ALL policy on agricultural carbon emission reduction (ACER) and presents an empirical test of this impact using a difference-in-differences (DID) model. Our research shows that the ALL policy gives impetus to ACER. This conclusion persists even after conducting the robustness and endogeneity tests. The mechanism posits that the policy achieves ACER through reducing the proportion of rural agricultural employees. Heterogeneity analysis indicates that the policy effect is significant in both the northern and southern regions of China. Nonetheless, the effect is only observable in economically developed areas, regions with high chemical fertilizer application rates, and areas with restricted agricultural progress. This study elucidates the connection between land transfer and agricultural carbon emissions, offering empirical evidence to support the advancement of green and low-carbon agricultural development.

Green talent development has become a central institutional priority for higher education systems that train graduates for the agricultural and forestry sectors, yet the performance-appraisal architecture that links practical education to business-innovation outcomes remains weakly specified. This study develops a four-dimensional performance-appraisal framework for practical education in agriculture and forestry programmes and applies it to a sample of 359 stakeholders (312 students and 47 faculty) drawn from three regional universities in Poland during the 2023–2024 academic year, supplemented by depth interviews with sixteen industry employers. The framework decomposes the appraisal goal into four primary dimensions—practical education system, education process, instructor capability, and learning environment—and sixteen sub-indicators weighted through an analytic hierarchy process. We combine survey responses with factor analysis and importance–performance gap analysis to identify the appraisal sub-indicators that most strongly constrain green talent readiness. Results indicate that the practical education process dimension carries the largest aggregate weight (0.308), that innovation capability and practice-base construction display the widest importance–performance gaps, and that triangulated student–faculty–employer evidence supports five mutually reinforcing optimisation paths: index-system reform, multi-stakeholder co-evaluation, industry–university co-supervision, digital appraisal platforms, and continuous incentive feedback. The study contributes a transferable measurement framework for green-talent appraisal in regulated education sectors and a set of design heuristics for embedding business-innovation outcomes in sustainability-oriented curricula.