Analyzing the supply and demand of ecosystem services and the regional balance pattern is an important basis for improving the ecological management level. Taking the Yangtze River economic belt as the study area, the spatiotemporal characteristics and balance pattern of ecosystem service supply and demand are quantitatively revealed based on equivalent factors, supply and demand balance modeling and quantile regression. The results show that: (1) the ecosystem services value in the research area experienced a change process of “increase–decrease–increase” from 2000 to 2020. The ecological service value of cultivated land and grassland presented a continuous decline, with decreases of 20.446 billion and 4.53 billion yuan, respectively, in the past 20 years, with reduction rates of −4.82% and −3.98%, respectively. (2) The demand for ecosystem services showed an unbalanced and phased growth trend. The total demand for ecosystem services showed heterogeneity and agglomeration effects in space. High demand and higher demand areas are mainly distributed in the regions with relatively developed population and economy, including Yangtze River Delta urban agglomeration, “Changsha–Zhuzhou–Xiangtan” urban agglomeration, Poyang Lake Plain, Jianghan Plain and Chengdu Plain. (3) The overall pattern of the supply–demand balance of ecosystem services has changed little; however, there have also been significant changes in certain areas in individual years.

The carbon emission level and spatiotemporal characteristics in Hubei Province were estimated and studied using the Intergovernmental Panel on Climate Change (IPCC) carbon emission coefficient technique based on county data from Hubei Province from 2000 to 2020. The relationship between carbon emissions from cultivated land utilization and agricultural economic growth was examined using the Tapio decoupling index, and the factors influencing carbon emissions in Hubei Province were further examined using the Logarithmic Mean Divisia Index (LMDI model). The results demonstrate that: (1) Spatiotemporal variations in carbon emissions are evident. In terms of time, the volume of carbon emissions in Hubei Province is still substantial, and the transition to low-carbon land use is quite gradual. Geographically, the high-value region of the middle east coexists with the low-value zone of the west, with apparent regional contrasts. (2) The decoupling between carbon emissions and agricultural economic growth is becoming more and more obvious in Hubei Province. The number of counties and cities in a negative decoupling state has significantly decreased, and the majority of counties are now in a strong decoupling condition. (3) Agricultural production efficiency is the most significant driving factor for restricting carbon emission, according to the decomposition results of carbon emission driving factors based on the LMDI model. In addition, the results of sample decomposition based on topographic characteristics indicate that agricultural production efficiency is primarily responsible for the suppression of carbon emissions in flat regions. The increase in carbon emissions in hilly regions is primarily influenced by agricultural productivity. The increase in carbon emissions in mountainous regions is mostly influenced by agricultural labor intensity. This study′s finding has enlightening implications for the high-quality growth of agriculture.

The rapid conversion of cultivated land resources has posed a severe danger to national food security, where the primary concerns are the quantity as well as the quality of the land being cultivated. Cultivated land use efficiency (CLUE) reflects the rational allocation and utilization level of cultivated land, labor, capital, and other factors so as to maximize output and minimize cost. In this study, carbon emissions were included as an unexpected output into the measurement framework of CLUE. The super SBM undesirable model, Spatial analysis model, and Tobit model were comprehensively used to measure the difference pattern and influencing factors of CLUE in 72 counties of Hubei Province from 2005 to 2020. The results show the following: the CLUE in Hubei Province showed significant regional differences and temporal variation characteristics. During the observation period of 2005 to 2020, the overall CLUE in Hubei Province increased, reaching 0.7475 by 2020, but was still at a low level (less than 1). Due to the limitation of topographic factors, this does not show obvious spatial agglomeration characteristics on the whole. In general, the CLUE value formed after considering the carbon emission index in most counties decreased by different ranges compared to the value formed without considering the carbon emission index. From the perspective of transverse terrain comparison, the measured results of the super SBM undesirable model showed that the cultivated land utilization efficiency of the mountain and hill was higher than that of the plain. From the vertical time comparison, the CLUE of different regions showed an upward trend, indicating obvious regional differences in the study period. The results of the Tobit model show that farmers’ income level can actively promote the improvement of CLUE in Hubei Province. Urbanization level, rural power consumption, per capita cultivated land scale, and agricultural mechanization level have an impact on cultivated land use efficiency as a whole, but the impact has topographic heterogeneity. This study can provide theoretical and technical reference for the improvement of regional cultivated land efficiency and the formulation of cultivated land protection strategies and policies.

The crop spatial pattern (CSP) is the spatial expression of the planting structure, maturity and planting pattern of crops in a region or production unit. It reflects the situation of human agricultural production using agricultural production resources, and is very important for human survival and development. Based on 5356 publications collected from the Web of Science Core CollectionTM (WoS), this paper’s aim is to illustrate a comprehensive run-through and visualization of the subject of CSP. A time series evolution diagram of hot topics and the evolution of research hotspots are discussed in detail. Then, remote sensing monitoring methods of the crop planting area, multiple cropping, crop planting patterns and the mechanisms of crop spatial patterns are summarized, respectively. In the discussion, we focus on three important issues, namely, the remote sensing cloud platform, the changes in characteristics of the crop spatial pattern and the simulation of the crop spatial pattern. The main objective of the paper is to assist research workers interested in the area of CSP in determining potential research gaps and hotspots.

Background In the wake of the severe impact of COVID-19 on the food security of the vulnerable groups in rural areas, the issue of how to achieve the Sustainable Development Goals 2 aims to “Zero Hunger” (SDG 2) and ensure the food safety of farmers has drawn unprecedented attention. Nutritional intake is generally used as an important indicator to reflect family food security. Under the background that Chinese farmers have gradually changed from the traditional diversified production mode to the specialized production of crops, the main purpose of this article is to explore what are the impact of crop specialization on farmers’ nutritional intake? Could the specialization of crop production be taken as an important measure to ensure the food safety of farmers and achieve the SDG 2? Methods Based on the micro-survey data from 866 farmer households in China, this paper using Seemingly Unrelated Regressions model, Group Regression model and Mediating Effect model to analyze the average and heterogeneous effects of crop specialization on the nutritional intake of farmers, as well as the mediating effect of income. In addition, robustness test and endogenous treatment were performed by using alternative explanatory variables and IV-2SLS method was used to estimate the results. Results After correcting for endogenous bias, crop specialization had a significant negative impact on energy intake and fat intake of farmers at the statistical level of 5% and 1% respectively, especially for farmers in mountainous areas. Household income played a mediating effect on the effect of crop specialization on farmers’ energy and fat intake, and the proportion of the masking effect was 8.43% and 8.96% respectively. In addition, household financial capital and social capital have a significant positive impact on farmers’ nutritional intake. Conclusions Crop specialization cannot guarantee the food safety of farmers in terms of nutritional intake. However, when the development trend of crop specialization is irreversible, more attention should be paid to improving the level of various livelihood capital of farmers, especially those in mountainous areas, and to continuously increasing their income to ease and ultimately eliminate the negative impact of crop specialization on farmers’ nutritional intake, which finally make everyone realize the SDG 2.