Exploring the eco-efficiency of cultivated land utilization and its influencing factors in China's Yangtze River Economic Belt, 2001-2018

Systematic coupling and multistage interactive response of the urban land use efficiency and ecological environment quality

Rapid urbanization and industrialization have greatly contributed to boosting regional economic growth and mitigating the problem of poverty, but blind expansion of cities and towns has not only caused the inefficient use of urban land resources but also caused the deterioration in the urban ecological environment. Within the current context of emphasizing high-quality development, achieving synergy between the efficient use of urban land and ecological environmental protection is an urgent task for promoting new urbanization construction. In this study, cities in the upper reaches of the Yangtze River (URYR) were adopted as the research object, a theoretical analysis framework for the urban land use efficiency (ULUE) and ecological environment quality (EEQ) was established, the ULUE was measured by using the Slacks-Based Measure (SBM) model, the coupling coordination and interactive corresponding response relationship between the ULUE and EEQ were analyzed, and the influencing factors of the coupling coordination between these two systems were explored by using the random forest model. The following conclusions can be obtained: in 2020, compared with those in 2006, both the ULUE and EEQ were improved, and the two systems exhibited interactions and significant spatiotemporal heterogeneity. The coupling coordination degree (CCD) between the ULUE and EEQ could facilitate maintaining the original state, and the transfer of the CCD exhibited a significant spatial correlation with the state of neighbouring cities. The effect of the ULUE on the EEQ indicated nonlinear characteristics, while the effect of the EEQ on the ULUE was manifested as inhibition initially and then promotion. The random forest regression results showed that the population density, landscape agglomeration and connectivity, market conditions, government intervention, and industrial institutions are the key influencing factors of the CCD. Finally, this study provides policy implications for innovative urban land use modelling, environmental regulation, and industrial transformation and upgrading.

Mapping sustainability: A comparative analysis proposal across EU countries and regions

This paper addresses the need to understand the structure of sustainability change in the face of the unpredictability of modern civilization. The aim of the paper is to examine the structure of sustainability change in relation to smaller spatial units such as the regions of the European Union and to compare these results with those achieved at the country level. For this purpose, the sustainable development indicators available in the Eurostat database were analyzed. Studies published to date have tended to focus on the performance of national economies or selected regions. In this article, the available data on regions are also analyzed. The study aims to compare the level of sustainable development achieved at the level of EU countries and regions located within them. Methodologically, the study uses advanced methods of comparative analysis, and the synthesis of the data enables the construction of a synthetic measure using taxonomic methods, facilitating the classification of EU countries and regions into clusters. The results highlight significant divergences in sustainability achievements between EU countries and regions. The study reveals the importance of studying sustainable development in smaller geographical cross-sections. The results highlight the need to expand access to data at the regional level (sustainability indicators) to facilitate more comprehensive analyses and inform targeted policy interventions. Looking to the future, the study recommends further research into the inter-linkages between sustainability and other critical areas in EU regions, such as innovation and competitiveness.

How does regional economic integration affect carbon emission efficiency? Evidence from the Yangtze River Delta, China

Rapid urbanization and industrialization promote economic growth as well as bring carbon emissions, which seriously threaten the eco-environment and socioeconomic sustainable development. Facing increasing resource constraints, improving carbon emissions efficiency (CEE) is conducive to promote coordinated development of economy and environmental protection. In recent years, regional economic integration (REI) has rapidly developed. It can not only promote factors flow between regions but also achieve industrial and economic agglomeration. However, few studies have been reported in the literature about the relationship between the REI and CEE. In this study, we first illustrate how the REI influences CEE in theory, then take the Yangtze River Delta (YRD) as a case study to conduct empirical research. The results show that (1) the overall CEE value in the YRD has exhibited an upward trend from 2000 to 2020, and its spatial distribution has revealed a significant auto-correlation pattern. (2) On the whole, the REI act a noteworthy positive impact on CEE. When considering types of cities, it is found to have significant positive impacts for the CEE in economically developed cities, while it exhibits a negative impact in the less-developed ones. (3) Upgrading industrial structure and increasing per capita GDP can promote the CEE, but hinder its growth in surrounding areas. Our findings suggest that the government should formulate a unified overall plan to facilitate REI development and establish a modern industrial system of clean and low-carbon to promote regional sustainable development.

Can the digitalization level of agriculture improve its ecological efficiency under carbon constraints: Evidence from China

The interplay between digitalization and economic development constitutes a pivotal global issue, yet empirical research on agricultural ecological efficiency in developing countries remains limited. This study initially establishes a measurement system and a comprehensive index for the level of agricultural digitalization. Subsequently, it delineates the relationship between agricultural digitalization level and agroecological efficiency using the spatial Durbin model, and ultimately explores the enhancing effect of agricultural digitalization level on agroecological efficiency using China as a case study. Research reveals that the agricultural ecological efficiency across the 31 mainland Chinese provinces demonstrates a generally linear upward trajectory, embodying both agglomeration and heterogeneity. The level of agricultural digitization exerts a significant, positive direct impact and facilitates a spatial spillover effect on agricultural ecological efficiency. Other control variables, such as financial support for agriculture and local economic development, impart a positive direct impact on regional agricultural ecological efficiency, while rural household operating income propels a positive spatial spillover effect on adjacent areas. The findings furnish guidance for developing countries to adeptly execute digital rural construction, aiming to enhance agricultural ecological efficiency amidst carbon constraints.

Spatiotemporal differences, dynamic evolution and trend of cultivated land use efficiency: Based on three food functional areas

China's agricultural development has entered a period of transition, and improving the cultivated land use efficiency (CLUE) is of great significance for guaranteeing national food security. Based on the province panel data in China from 2000 to 2021, this research calculates the cultivated land use efficiency, and uses the Dagum-Gini coefficient, Kernel density estimation, and Markov chain to conduct an in-depth analysis of CLUE's regional variations and distribution dynamics in three food functional areas (TFA) of China. The study results showed that the trend of CLUE was characterized by "increasing levels and decreasing absolute differences," not only in the whole country but also in the TFA. The inter-regional variation among TFA is gradually narrowing, and the cross-group degree of inter-regional variation is on the rise. The upward probability of CLUE was more effective than the probability of a transitionary change, and the mutual influence of CLUE between neighboring cities would lead to spatial convergence in the level of CLUE in the long term. Therefore, improving CLUE in China's TFA should not only grasp the regional differences in CLUE but also actively utilize the spatial spillover effects among functional regions to realize the cross-regional synergistic development of cropland utilization efficiency in China.

Future land use simulation model-based landscape ecological risk prediction under the localized shared socioeconomic pathways in the Xiangjiang River Basin, China

Landscape ecological risk (LER) is an effective index to identify regional ecological risk and measure regional ecological security. The localized shared socioeconomic pathways (LSSPs) can provide multi-scenario parameters of social and economic development for LER research. The research of LER under LSSPs is of scientific significance and practical value in curbing the breeding and spread of LER risk areas. In this study, land-cover raster files from 2010 to 2020 were used as the foundational data. Future land use simulation (FLUS), regression, and Markov chain models were used to predict the land cover patterns under the five LSSP scenarios in the Xiangjiang River Basin (XJRB) in 2030. Thus, an evaluation model was established, and the LER of the watershed was evaluated. We found that the rate of land cover change (LCC) in the XJRB between 2010 and 2020 had a higher intensity (increasing at an average of 18.89% per decade) than that projected under the LSSPs for 2020-2030 (averaging an increase of 8.58% per decade). Among the growth rates of all land use types in the XJRB, that of urban land was the highest (33.3%). From 2010 to 2030, the LER in the XJRB was classified as lower risk (33.73%), lowest risk (33.11%), and moderate risk (24.13%) for each decade. Finally, the LER exhibited significant heterogeneity among different scenarios. Specifically, the percentages of regions characterized by the highest (9.77%) and higher LER (9.75%) were notably higher than those in the remaining scenarios. The higher-level risk area under the localized SSP1 demonstrated a clear spatial reduction compared to those of the other four scenarios. In addition, in order to facilitate the differential management and control of LER by relevant departments, risk zoning was carried out at the county level according to the prediction results of LER. And we got three types of risk management regions for the XJRB under the LSSPs.

Re-measurement and influencing factors of agricultural eco-efficiency under the 'dual carbon' target in China

Given that agriculture is both a carbon source and sink, the sustainability goals of carbon peaking and neutrality place high demands on the green and low-carbon agricultural development in China, and the exploration of a realistic path for a sustainable agricultural development is urgently needed. Under the above 'dual carbon' target, this study focused on the key issue of how to improve China's agricultural eco-efficiency (AEE) and constructed an innovative AEE indicator system that can reflect carbon constraint and coordinated agricultural economic development, resource use and ecological environment. The super-efficient slack-based measured Data Envelopment Analysis (SBM-DEA) method, which considers undesirable outputs, was applied to re-measure the AEE of 30 provinces and cities in China from 2001 to 2020, and its spatial and temporal evolution was analysed in conjunction with kernel density estimation. The Tobit regression model was used to explore various influencing factors by region. The results show that the AEE re-measurements, which take into account the 'dual carbon' requirement, are significantly better than the traditional AEE. From 2001 to 2020, China had an overall V-shaped fluctuation curve AEE, with a small decline and several inter-annual fluctuations, and exhibited a large potential to rise. China's AEE showed a spatially uneven regional development at different stages of distribution and evident multi-polar differentiation. Inter-provincial differences were observed in China's AEE, and the vicious circle of low-level green and low-carbon agricultural development was difficult to break. Urbanisation had a significant positive effect on national and eastern AEE but a significant negative effect on central AEE. The agricultural carbon offset rate had a significant effect on AEE nationally and in the three regions. Thus, the introduction of 'dual carbon' target effectively drove the development of AEE. Agricultural industry structure inhibited the improvement of AEE nationally and in the western region. Agricultural economic development hindered the national AEE improvement but promoted that of the central region, where China showed an environment Kuznets curve. Hopefully, this study can provide data support and theoretical reference for the green and low-carbon agricultural development and help achieve the 'dual carbon' target.

Evaluation of the efficiency and drivers of complemented cropland in Southwest China over the past 30 years from the perspective of cropland abandonment

Complemented croplands are a crucial component of cropland resources and play a significant role in ensuring national food security. In recent decades, to counter the loss of prime farmland caused by urban construction, the Chinese government introduced a requisition-compensation balance policy, leading to the substantial expansion of new croplands. Therefore, there is an urgent need to determine whether these complemented croplands can be effectively used. Taking Southwest China as a case study, we used high-precision long-term land-use data from 1990 to 2020 to reveal the dynamics of complemented cropland utilization, evaluate the efficiency of complemented cropland utilization from the perspective of abandoned farmland, and identify the factors driving complemented cropland use efficiency based on more than 13 million land parcels. The results showed that: (1) From 1990 to 2020, complemented cropland amounted to approximately 1170.07 × 104 hm2, accounting for 32.67% of the total arable land area in 1990. The potential grain production capacity of these complemented croplands was significantly lower than that of base croplands. (2) The abandonment of complemented croplands was more serious than that of base croplands, and 47.03% of the complemented croplands experienced abandonment at least once during the study period, and the average efficiency of the complemented croplands was 75.61%. (3) The labor population ratio, elevation, and land parcel size played pivotal roles in influencing the complemented cropland utilization efficiency; however, there was substantial variation among the different provinces. Labor replacement, overcoming farming difficulties brought by mountainous terrain, and improving farmers' income are the keys to alleviating cropland abandonment in mountainous areas and improving cropland utilization efficiency. This study provides novel insights into the efficiency assessment and exploration of the mechanisms driving complemented croplands and can provide references for cropland management.

Spillover effects of urban form on urban land use efficiency: evidence from a comparison between the Yangtze and Yellow Rivers of China

The contradiction between the basin's economic importance and its role as an ecological barrier impedes efficient urban land use. This study aims to propose an integrated approach to compare the urban land use of two representative basin areas of the Yangtze River Economic Belt and the Yellow River Basin and to investigate the impact of urban form on urban land use efficiency. Urban form was characterized by landscape indexes including Patch Density, Largest Patch Index, Edge Density, Patch Cohesion Index, and Agglomeration Index based on FRAGSTATS 4.0 software, and urban land use efficiency was measured by using Slack-Based Model-Undesirable, considering urban land becomes an emission source. Furthermore, spatial econometric models were adopted to explore direct effects and spatial spillover effects of urban form on urban land use efficiency. From 2000 to 2018, changes in urban form in both Yangtze River Economic Belt and Yellow River Basin showed increased fragmentation, enhanced heterogeneity, and more complex patch shapes. The high values of urban land use efficiency were concentrated in lower reaches of the Yangtze and Yellow Rivers. Spatial econometric models suggested that between different basins and various sized cities, the impact of urban form on urban land use efficiency had a spatial spillover effect and regional heterogeneity. Results indicated that input factors such as capital and labor should be more concentrated in metropolitan areas and urban agglomerations, thus promoting higher land use efficiency.

Research on the coupling coordination and driving role of urbanization and ecological resilience in the middle and lower reaches of the Yangtze River

Background

The growth of urbanization in the 20th and 21st centuries has resulted in unprecedented ecological security issues. The imbalance between urban development and internal ecological security is a growing concern.

Methods

Based on the urban development process and the characteristics of ecosystem resilience, the corresponding urbanization evaluation system ("scale-structure-benefit") and ecosystem resilience assessment model ("resistance-adaptability-restoring") were constructed to explore the changes in each dimension as well as to analyze the spatial and temporal changes and driving effects of the coupled coordination level of urbanization and ecological resilience using the coupled coordination degree (CCD) model and geographically and temporally weighted regression (GTWR).

Results

(1) From 2005 to 2020, urbanization levels increased (from 0.204 to 0.264, respectively), whereas the level of ecological resilience gradually decreased (from 0.435 to 0.421, respectively). The spatial distribution of urbanization is rather steady, with a "high-northeast low-southwest" pattern of regional distribution; however, the spatial distribution pattern of ecological resilience is essentially the reverse. (2) During the study period, there was an improvement in the level of coordination between urbanization and ecological resilience, with an increase from 0.524 to 0.540. However, the main coordination type remained the same, with over 46% being at the basic coordination stage. The relative development type was dominated by the lagging urbanization stage, with the lagging ecological resilience and synchronous development stages accounting for a smaller proportion, and the space was distributed in a block-like cluster. (3) The running results of the GTWR show that the core dimensions of the whole region are scale, benefit, and structure, and the impact of each dimension shows obvious spatial heterogeneity. Cities with different levels of relative development also have different central dimensions. This research will provide support for the coordination of urban development in areas where economic construction and ecological resilience are not coordinated, and will contribute to the sustainable development of urban areas.

Modeling and exploring the coordination relationship between green infrastructure and land use eco-efficiency: an urban agglomeration perspective

In limited land space, improving the construction of infrastructure with ecological services can help to achieve the goal of promoting land use eco-efficiency (LUEE). In view of this, this study constructed interactive coordination relationship model of green infrastructure (GI) and LUEE that involves entropy method model, super-efficiency slack-based measure (SBM) model with undesirable outputs, and coupling coordination degree model. The interactive coordination relationship model can help to study and reveal the mechanisms of interaction and the coordination relationship between GI and LUEE from a land benefit and ecological perspective. We took the Beijing-Tianjin-Hebei urban agglomeration as the study area. The results showed that the assessment results of GI showed a decreasing trend from 2000 to 2020. LUEE in different cities displayed obvious variability with efficiency values ranging from 0.5666 to 2.4437. The relationship between GI and LUEE is in the stage of uncoordinated development in 53.8% of cities, mainly concentrated in the eastern and southern parts of the study area. The unnatural human activities are the critical factors affecting interactive coupling coordination degree of LUEE and GI. It is clarified that the level of coordination relationship of the two can be used as an important indicator to judge the sustainable development of urban agglomerations. Intensive use of land, optimal connection of geographic information, and localization of policies would help improve the balance and coordination between the two. This study provides interesting research ideas and novel modeling approaches for the study of green and sustainable development of urban agglomerations.

Environmental regulations, green development of agriculture, and residents' health-empirical analysis of Yangtze River Economic Belt in China

Environmental pollution and food safety have become key public health issues to be addressed in China. Since they are closely related to the green development of agriculture, it is of great practical significance to elucidate the intrinsic relationships between green development of agriculture, environmental regulation and residents' health. Based on the panel data of the Yangtze River Economic Belt from 2011 to 2020, this study investigates the impacts of environmental regulation and green development of agriculture on residents' health and the influencing mechanism by applying fixed effects method, mediating effectsmethod and the spatial Dubin method. Results show that the use of chemical fertilizers, pesticides and agricultural films is harmful to residents' health; environmental regulation has a negative correlation with the green development of agriculture and affect residents' health through mediating effects; the green development of agriculture has negative spillover effects on residents' health, indicating that purchasing finished products instead of producing locally reduces the input of production factors such as chemical fertilizers and pesticides and transfers health risks associated with agricultural production activities to neighboring areas. Intensifying command-and-control environmental regulation will induce the expansion of hidden economic activities and harm local residents' health, while intensifying market-incentive environmental regulation will lead to the 'Pollution Haven' phenomenon because of the 'race to the bottom', in government and is harmful to the health of residents in neighboring areas. Therefore, it is necessary to formulate reasonable and feasible policies and strengthen the control and prevention of agricultural pollution to enhance green development of agriculture and improve residents' health.

What were the spatiotemporal evolution characteristics and the influencing factors of urban land green use efficiency? A case study of the Yangtze River Economic Belt

China's rapid urbanization has had a tremendous impact on the country's limited land resources, and one of the major issues of green development is how to utilize the limited land resources to maximize social, economic, and environmental advantages. From 2005 to 2019, the super epsilon-based measure model (EBM) was employed to assess the green land use efficiency of 108 prefecture-level and above cities in the Yangtze River Economic Belt (YREB), as well as investigate its spatial and temporal evolution and influential factors. The findings demonstrate that overall, urban land green use efficiency (ULGUE) in the YREB has been ineffective; in terms of city scale, megacities have the highest efficiency, followed by large cities and small and medium-sized cities; and at the regional level, downstream efficiency does have the greatest average value, followed by upstream efficiency and middle efficiency. The results of temporal and spatial evolution reveal that the number of cities with a high ULGUE is increasing in general but that their spatial characteristics are relatively dispersed. Population density, environmental regulation, industrial structure, technology input, and the intensity of urban land investment all have major beneficial effects on ULGUE, whereas urban economic development level and urban land use scale clearly have inhibitory effects. In light of the previous conclusions, some recommendations are made to continuously improve ULGUE.

Study on eco-efficiency of cultivated land utilization based on the improvement of ecosystem services and emergy analysis

Cultivated land is the result of the cooperation between humans and nature. The utilization of cultivated land hopes to realize a "win-win" situation of food production and ecological protection to promote sustainable development. Previous studies on the eco-efficiency of agro-ecosystem mainly considered material input, agricultural product output and environmental pollution, and did not systematically include the natural input and ecological product output, which had limitations on the study of sustainable development of cultivated land utilization. Therefore, this study initially used emergy analysis and ecosystem service assessment methods to include the natural input and ecosystem service output of cultivated land into the assessment framework of eco-efficiency of cultivated land utilization (ECLU) and used the Super-SBM model to calculate the ECLU in the Yangtze River Delta (YRD) region in China. In addition, we also discussed the influencing factors of ECLU by the OLS model. Here we show that the ECLU was lower in cities with higher agricultural intensive utilization in the YRD. And in cities with better ecological conditions, the ECLU value obtained based on our adjusted ECLU assessment framework was higher than the traditional agricultural eco-efficiency assessment, indicating that the assessment method in this study paid more attention to ecological protection in the application. In addition, we found that crop diversity, paddy/dry land ratio, cultivated land fragmentation and terrain are the factors affecting the ECLU. This study helps provide a scientific basis for decision-makers to improve the ecological function of cultivated land based on ensuring food security and furthermore promote regional sustainable development.

Spatio-Temporal Difference in Agricultural Eco-Efficiency and Its Influencing Factors Based on the SBM-Tobit Models in the Yangtze River Delta, China

In the Yangtze River Delta region, where the agricultural economy is well developed and agricultural pollution and carbon emissions are significant, a regional study of AEE (Agricultural Eco-Efficiency) is crucial to reducing agricultural environmental pollution, improving the rationalization of agricultural production layout, and promoting the realization of low-carbon goals. The SBM-Tobit model and GIS were employed to analyze AEE based on the carbon emission evaluation system in the spatial and temporal characteristics, as well as the influencing factors and the migration path of the center of gravity in the "low carbon" context. A rational plan of agricultural production was proposed according to the results. The following results were obtained: (1) The level of AEE in the Yangtze River Delta region was high, and the region exhibited a U-shaped curve change from 2000 to 2020, with a fluctuating decrease from 2000 to 2003 and a fluctuating increase from 2004 to 2020. The regional spatial development balance was enhanced, while there was a spatial incongruity in the development process of AEE enhancement, high in the southwest and low in the northeast; (2) AEE generally had a high regionalized agglomeration of low-low in the southwest and high-high in the northeast. Nonetheless, temporal heterogeneity was observed in spatial correlation, and the correlation weakened with time variation; (3) Urbanization level, agricultural production structure, crop cultivation structure, and fertilizer application intensity were the main factors influencing AEE in the Yangtze River Delta region; (4) The center of gravity of AEE in the Yangtze River Delta region shifted to the southwest under the influence of "low-carbon" related policies. Therefore, the improvement of AEE in the Yangtze River Delta region should focus on inter-regional coordination and linkages, rational planning of production factors, and the formulation of measures under relevant carbon policies.

Development of multidimensional water poverty in the Yangtze River Economic Belt, China

As a basic natural and strategic resource, water is of great significance to the sustainable development of economies and societies. Owing to population growth, industrialization, the acceleration of urbanization, and global warming, water poverty is gradually increasing in some parts of the world. Effectively assessing water poverty from different dimensions is still a serious challenge for global water resources planning. This paper establishes a framework of multidimensional water poverty (MWP) from six dimensions: water management, water technology, water assets, water welfare, water resources, and water environment. The measurement model of MWP is built based on the Back Propagation Neural Network (BPNN), and the Spatial Correlation Analysis tool is used to visualize the spatial effects of MWP. The Yangtze River Economic Belt (YREB) was used as a case study and the main factors affecting the MWP of the YREB were determined by the Geodetector. When analyzing the results the following observations were made: (1) In terms of time distribution, the level of MWP in the YREB has gradually increased, and the poverty gap between the upper reaches, as well as the middle and lower reaches, shows an increasing trend. (2) With respect to spatial distribution, there is a continuously increasing agglomeration effect that shows a gradient-increasing distribution pattern of "West-Central-East." (3) The MWP in the YREB is mainly affected by these indicators in the three dimensions consisting of water resources, water technology, and water management. Specifically, R&D expenditure as a percentage of GDP, the proportion of water-saving irrigation area in the cultivable land area, the urban daily wastewater treatment capacity, the land surface water resources per capita, and the groundwater resources per capita play an important role in the MWP. Based on the above findings, targeted policy recommendations are proposed to alleviate the MWP in the YREB.

Spatially Non-Stationary Response of Carbon Emissions to Urbanization in Han River Ecological Economic Belt, China

Within the context of the "30·60 dual carbon" goal, China's low-carbon sustainable development is affected by a series of environmental problems caused by rapid urbanization. Revealing the impacts of urbanization on carbon emissions (CEs) is conducive to low-carbon city construction and green transformation, attracting the attention of scholars worldwide. The research is rich concerning the impacts of urbanization on CEs but lacking in studies on their spatial dependence and heterogeneity at multiple different scales, especially in areas with important ecological statuses, such as the Han River Ecological Economic Belt (HREEB) in China. To address these gaps, this study first constructed an urbanization level (UL) measurement method. Then, using a bivariate spatial autocorrelation analysis and geographically weighted regression model, the spatial relationships between UL and CEs from 2000 to 2020 were investigated from a multiscale perspective. The results were shown as follows. The total CEs in the HREEB witnessed an upsurge in the past two decades, which was mainly dispersed in the central urban areas of the HREEB. The ULs in different regions of the HREEB varied evidently, with high levels in the east and low levels in the central and western regions, while the overall UL in 2020 was higher than that in 2000, regardless of the research scale. During the study period, there was a significant, positive spatial autocorrelation between UL and CEs, and similar spatial distribution characteristics of the bivariate spatial autocorrelation between CEs and UL at different times, and different scales were observed. UL impacted CEs positively, but the impacts varied at different grid scales during the study period. The regression coefficients in 2020 were higher than those in 2000, but the spatial distribution was more scattered, and more detailed information was provided at the 5 km grid scale than at the 10 km grid scale. The findings of this research can advance policy enlightenment for low-carbon city construction and green transformation in HREEB and provide a reference for CE reduction in other similar regions of the world.

Evaluating the Spatiotemporal Characteristics of Agricultural Eco-Efficiency Alongside China's Carbon Neutrality Targets

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.

Cultivated Land Input Behavior of Different Types of Rural Households and Its Impact on Cultivated Land-Use Efficiency: A Case Study of the Yimeng Mountain Area, China

Analyzing cultivated land input behavior (CLIB) at the scale of rural households links with cultivated land-use efficiency (CLUE), this study examined the Yimeng Mountain area in northern China, supported by field survey data from 737 rural households. This research systematically analyzed the characteristics of CLIB of different types of rural households, measured the CLUE of different types of rural households by using a data envelopment analysis (DEA) model, and explored the influence of CLIB on CLUE based on the Tobit regression model. The results show (1) significant differences in the characteristics of the CLIB of different types of rural households in the Yimeng Mountain area. Among them, the highest land, labor, and capital inputs were I part-time rural households (I PTRH), followed by full-time rural households (FTRH). In contrast, II part-time rural households (II PTRH) and non-agricultural rural households (NARH) had higher levels of non-agricultural employment; however, their input levels gradually declined. (2) The CLUE of the sample rural households was generally low and had considerable potential for improvement. Regarding the types of rural households, as the degree of part-time employment increased, the CLUE showed an inverted U-shaped trend of first increased and then decreased, namely, I PTRH > FTRH > II PTRH > NARH. This finding indicates that appropriate part-time employment could help to promote investment in agricultural production and improve the CLUE. (3) The CLIB of rural households had significant effects on CLUE; the literacy of the agricultural labor force, yield-increasing input per unit area, per capita household income, share of agricultural income, operation scale of cultivated land, effective irrigation rate of cultivated land, and soil and water conservation rate of cultivated land had positive effects on improving CLUE. Even so, there was still significant heterogeneity in the degree of influence of different rural household types. The study concluded with some policy recommendations from the perspective of different rural household types to provide references for optimizing farming inputs and improving CLUE.

Estimating potential illegal land development in conservation areas based on a presence-only model

Conservation areas are facing increasing threats from anthropogenic land use activities. It is important to reasonably recognize and predict suspected illegal land development in advance. However, traditional methods easily suffer from selection bias due to the lack of accurate and reliable absence data. To tackle this problem, we have presented a novel method for estimating potential illegal land development based on the presence-only maximum entropy (MAXENT) model. The principle of MAXENT can guarantee that no additional unknown information (e.g., inaccurate pseudo-absence samples) will be introduced into the estimation procedure. This method was applied to the conservation areas in a fast-growing city, and the robustness of the MAXENT models was confirmed by the high AUC scores (over 0.80). The results indicated that the proposed method performs more effectively than the presence-absence random forest model. In addition, topographic conditions and proximity to transportation networks played dominant roles in the emergence of suspected illegal land development. Moreover, the probability map generated by MAXENT suggests that a considerable amount of forest, farmland, grassland, and water bodies will face a high degree of danger. Therefore, both superior and local governments should pay much more attention to regions with a higher potential for illegal land development. In summary, our findings are expected to support decision-making in the management and assessment of conservation areas in fast-growing regions. More importantly, the proposed method can be further applied to illegal land development estimation in many other regions.

Cultivated Land Transfer, Management Scale, and Cultivated Land Green Utilization Efficiency in China: Based on Intermediary and Threshold Models

Cultivated land utilization around the world is accompanied by the cultivated land fragmentation, which is a significant agricultural feature of countries with economies in transition. Thereby, governments of the PRC have successively promulgated a series of relevant policies to promote the cultivated land transfer (CLT) and stimulate the transformation of cultivated land utilization to be both green and efficient. In the context of large-scale CLT and the implementation of a rural revitalization strategy for China, it is of great significance to explore the effect of CLT on cultivated land green utilization efficiency (CLGUE). In this work, 30 provinces of China were selected as the objects of investigation; the super-efficiency SBM model was used to evaluate CLGUE; the mediation effect model and threshold regression model were used to gain a more comprehensive understanding of the CLT's influence on CLGUE. According to the results of this study, the following conclusions were drawn. First of all, the CLGUE in China as a whole showed an upward trend improvement from 2005 to 2019. Due to the different natural and economic conditions, the CLGUE trends showed significant spatial disparities at both the grain functional areas level and provincial level. Secondly, the CLT could promote CLGUE directly, and the mediation regression results demonstrated that CLT was able to enhance CLGUE indirectly through the mediator of cultivated land management scale. Thirdly, the threshold effect test confirmed the existence of a single threshold, indicating that when the level of CLT gradually crossed the threshold, the promotion effects of CLT on CLGUE would slow down. Lastly, the heterogeneity analysis indicated that the promotion effects of CLT on CLGUE in different geographical location areas and grain functional areas were positive, and that there were significant differences in regression coefficients.

The Spatial and Temporal Evolution of the Coordination Degree in Regard to Farmland Transfer and Cultivated Land Green Utilization Efficiency in China

In many parts of the world, the shortage of cultivated land and the food crisis are worsening on a continued basis. Hence, the central and local governments of the PRC have successively issued various related policies to encourage the practice of farmland transfer, promote the eco-friendly utilization of cultivated land, and ameliorate the efficiency of cultivated land utilization. Under the context of large-scale farmland transfer and rural revitalization strategy in China, it is significant to ensure agricultural sustainability through the coordination of farmland transfer and the amelioration of cultivated land green utilization efficiency (CLGUE). In the present study, 30 Chinese provinces were taken as the research object, with the super-efficient SBM model, the coupling coordination degree model and the spatial analysis model applied in combination. Based on the measurement of CLGUE, a thorough analysis was conducted to explore the evolution of coordination degree in regard to farmland transfer and CLGUE in China from both spatial and temporal perspectives. The conclusions drawn from this study are as follows. Firstly, the overall CLGUE exhibited an upward tendency in the PRC, from 0.440 in 2005 to 0.913 in 2019, with a yearly growth rate of 5.47% on average. However, there were significant spatial disparities in CLGUE between different regions and provinces. Secondly, there was a steady increasing trend shown by the level of coordination degree regarding farmland transfer and CLGUE across China. Further, due to the variation in natural and economic conditions, there were significant spatial-temporal disparities in the coordination degree among these 30 provinces. Lastly, there were obvious spatial aggregation patterns at the provincial level regarding the coordination degree in farmland transfer and CLGUE across China. However, there was a declining trend in the level of spatial aggregation patterns for coordination degree.

Impacts of land finance on green land use efficiency in the Yangtze River Economic Belt: a spatial econometrics analysis

This paper uses the Global Malmquist-Luenberger Index (GMLI) based on directional distance function (DDF) super efficiency model to measure the urban green land use efficiency (UGLUE) of 108 cities in the Yangtze River Economic Belt (YREB) from 2007 to 2018, and it utilizes the spatial economic model to analyze the impact of land finance on the UGLUE and its mechanism of action. The results show that, firstly, the UGLUE in the YREB shows a steady development trend, the overall efficiency level is high, and there are spatial agglomeration characteristics. Secondly, the impact of land finance on the UGLUE presents "inverted U-shaped." With the continuous expansion of the scale of land finance, the impact of land finance on the UGLUE in the city has changed from positive to negative. Thirdly, land finance has a spatial spillover effect. Land finance will inhibit the improvement of UGLUE in surrounding areas through the "peer effect." With the continuous expansion of land finance scale, land finance will promote the improvement of UGLUE in surrounding cities through the "warning effect."

Evaluating the Impact of the Highway Infrastructure Construction and the Threshold Effect on Cultivated Land Use Efficiency: Evidence from Chinese Provincial Panel Data

Highway infrastructure construction is regarded as one of the effective policy tools used to promote the flow of production factors and upgrade the industrial structure in China, and it may also be an important precondition to improving Cultivated Land Use Efficiency (CLUE). This paper uses a slack-based model (SBM) based on provincial-level panel data from China from 2004 to 2017 to measure CLUE. Then a dynamic spatial Durbin model and a panel threshold regression model were established to analyze the spatial spillover effect and threshold effect of highway infrastructure construction on CLUE. The results showed that the CLUE of China has a fluctuating but overall rising trend. The dynamic spatial Durbin model demonstrated that the Chinese government’s policy of supporting highway infrastructure construction has played an important role in promoting CLUE by spatial spillover effects, and the driving effect of expressways and first–second highways on CLUE is particularly significant in this regard. More interestingly, the results of the panel threshold regression indicated that there is a single threshold effect in the influence of highway infrastructure construction on CLUE. This paper suggested that the spatial correlation between regions should be considered in the construction of regional highway infrastructure and land use planning to improve CLUE. Moreover, the planning of highway infrastructure construction should be balanced according to the actual demand of economic and agricultural development, so as to promote the full flow and reasonable allocation of cultivated land use factors among regions.

How Does Different Cropland Expansion Trajectories Affect Cropland Fragmentation? Insights From Three Urban Agglomerations in Yangtze River Economic Belt, China

A clear understanding of cropland expansion dynamics and their effects is vital for cropland protection and food security. However, the trajectories of cropland expansion have been less discussed. This study referred to the modes of landscape expansion and assessed the cropland expansion trajectory in three urban agglomerations in the Yangtze River Economic Belt and its impact on cropland fragmentation. Specifically, we identified three cropland expansion trajectories using the landscape expansion index, namely, infilling, edge-expansion, and outlying. Moreover, the surface relief amplitude model was employed to characterize the relief amplitude effect on cropland expansion trajectories. By coupling landscape metrics (e.g., patch density, landscape shape index, the largest patch index, and aggregation index) and Spearman correlation analysis, the relationship between cropland expansion trajectories and cropland fragmentation was assessed. Results show that (1) three urban agglomerations experience cropland expansion, in which the edge-expansion trajectory is primary, followed by infilling and outlying trajectories; (2) the cumulative frequency curve indicates that infilling and edge-expansion trajectories are likely to be distributed in low topographic relief amplitude regions, while the outlying trajectory is located in relatively higher topographic relief amplitude regions; and (3) infilling and edge-expansion trajectories contribute to a significantly positive relationship with the decrease of cropland fragmentation, while the outlying trajectory has a negative relationship with cropland fragmentation. This research highlights that cropland protection policies should considerably focus on the trajectory of cropland expansion, not only request the total area of cropland in a dynamic balance.

Relationship between Urban Land Use Efficiency and Economic Development Level in the Beijing–Tianjin–Hebei Region

Due to limited land resources, it is necessary to balance urban economic development and efficient land use. Clarifying the relationship between the two is crucial to improving both economic efficiency and land use efficiency. Considering the undesirable output of urban land use, this paper adopts a super efficiency SBM model to quantify the urban land use efficiency (ULUE) of the Beijing–Tianjin–Hebei (BTH) region from 1999 to 2019, and analyzes the relationship between ULUE and economic development level (EDL) by combining the Tapio model and the environmental Kuznets curve (EKC) model. The results show the following: (1) During the study period, the ULUE showed a fluctuating upward trend on the temporal scale, with the lowest and highest inflection points occurring in 2002 and 2018, respectively, and a distribution pattern of “high in the southeast and low in the northwest” on the spatial scale. (2) The decoupling relationship between ULUE and EDL showed repeated fluctuations between decoupling and coupling states on the temporal scale, but the overall showed a transition trend from decoupling state to coupling state. On the spatial scale, from north to south, there were a strong decoupling state (SDS), weak decoupling state (WDS), strong decoupling state (SDS), and weak decoupling state (WDS) in order, showing a regular interval repetition distribution pattern. (3) The relationship between ULUE and EDL showed an EKC “U-shaped” curve, that is, ULUE decreases first and then increases with the increases in EDL. The results of this study can provide a reference for the coordinated and sustainable development of the BTH region.

Land Use Change under Population Migration and Its Implications for Human–Land Relationship

With the rural-to-urban population migration under the new era of rapid urbanization, China has experienced dramatic rural land change, especially the change in cultivated land and rural residential land, resulting in the serious uncoordinated human–land relationships in rural areas. The efficient use of these two kinds of land resources becomes one of the paramount challenges for governments to achieve sustainable and balanced rural development. This challenge highlights the need for quantifying the formation mechanism of the relationship between cultivated land and rural residential land (RCR) and exploring the corresponding relation between human–land relationships with RCR to guide the high-efficiency rural land use structure and coordinated development of human–land relationships. This study aims to quantitatively characterize the matching modes of RCR and the underlying formation mechanism via a grid-based, integrated decoupling model and multiclass explainable boosting machine analysis method. The findings are as follows: (1) The variation in cultivated land and rural residential land is characterized by quantity match and spatial mismatch. The six matching modes of RCR are strong decoupling (SD) (33.36%), weak decoupling (9.86%), recessive decoupling (4.15%), expansive negative decoupling (15.05%), weak negative decoupling (4.92%), and strong negative decoupling (SND) (18.65%). (2) Average grain product per cultivated land and population variation have the highest relative importance and play the greatest role in determining the type of matching modes. A concomitant phenomenon is noted in the matching modes; that is, SD occurs with recessive decoupling and weak negative decoupling, and the weak decoupling and expansive negative decoupling occur with SND in the same conditions. (3) A significant corresponding relationship exists between the matching modes and human–land relationship, indicating that the six matching modes correspond to four different stages of the human–land relationship. The study could provide some decision-making guidance for sustainable rural development, so as to improve the differentiated land management and regional response strategies.

Coupling Coordination Development of New-Type Urbanization and Cultivated Land Low-Carbon Utilization in the Yangtze River Delta, China

Although urbanization greatly benefits economy-society development in China, it poses enormous challenges to cultivated land utilization. In the context of urbanization acceleration and carbon neutrality, it’s of significance to achieve high-quality economy-society development and sustainable agricultural development. Thus, the coupling coordination relationship between new-type urbanization and cultivated land low-carbon utilization (CLLCU) needs to be examined. However, this topic has not been adequately addressed in previous studies. To fill the gap, this paper adopted a comprehensive evaluation model and a super-efficiency SBM (Slacked Based Measure) model to evaluate the level of new-type urbanization and the cultivated land low-carbon utilization efficiency (CLLCUE) of cities in the Yangtze River Delta in China from 2000 to 2018. Furthermore, the coupling coordination degree model (CCDM) and the relative development degree model (RDDM) were employed to measure the coupling coordination degree and the relative state of the new-type urbanization and CLLCU The results show that the coupling coordination degree between the new-type urbanization level and CLLCUE experienced a process of “rapid increase-steady develop” and presented a spatial pattern of “polarization-regional equilibrium”. In addition, the relative state of the new-type urbanization and CLLCU presented the “reversal” phenomenon. In other words, the relative state changed from the new-type urbanization lagging behind CLLCU to the new-type urbanization ahead of CLLCU. None of the cities were in the state of simultaneous development. Finally, this paper puts forward policy recommendations to explore differentiated CLLCU modes and improve the quality and efficiency of new-type urbanization.

Industrial Transformation and Urban Economic Efficiency Evolution: An Empirical Study of the Yangtze River Economic Belt

Industrial transformation and high-quality urban development have become the core issues of urban-rural coordination and the leap forward in development in the new era. The research perspective of 'pattern-process-mechanism' is needed to reveal the spatiotemporal correlation characteristics of industrial transformation and urban economic efficiency evolution, and to expand its systematic, comprehensive and regional characteristics. Based on the geographical cognitive of local effects and spatial non-stationarity, we used a quantile regression model and a geographically weighted regression model to analyze the dynamic mechanism of industrial transformation and urban economic efficiency to explain the path characteristics of urban development and industrial transformation of the Yangtze River economic belt. The conclusions are as follows: (1) From 2000 to 2015, the average economic efficiency in the Yangtze River economic belt increased from 0.05 to 0.332, and the pattern gradually changed from spatial homogeneity to spatial mosaic; (2) From 2000 to 2015, the range and intensity of industrial transformation in the Yangtze River economic belt showed an increasing trend, while the speed of industrial transformation showed a downward trend, and the high-value unit of the three showed the characteristics of gradual homogenization; (3) From the perspective of the impact of industrial transformation on urban economic efficiency, the impact of the range and speed of industrial transformation on urban economic efficiency was gradually weakened, while the impact of the intensity of industrial transformation on urban economic efficiency was gradually strengthened, and the patterns of the three show the characteristics of a spatially inverted U-shaped distribution with high values in the middle reaches and low values in the upstream and downstream areas.

The Evolution and Response of Space Utilization Efficiency and Carbon Emissions: A Comparative Analysis of Spaces and Regions

Space utilization and climate change are related to human survival and development. Identifying the relationship between development and conservation is the foundation of sustainable development. We used the kernel density curve, spatial analysis, and the sensitivity model to study the spatial use efficiency and carbon emissions evolution characteristics at the provincial and regional levels in China from 1999 to 2019. The results show that a trend of high efficiency and low carbon emissions in southeast coastal cities and towns is gradually forming, and agricultural spaces are moving toward high efficiency and high carbon emissions patterns. The evolution paths of space utilization efficiency and carbon emissions differ significantly across spaces and regions. We also found similarities in how carbon emissions intensity responds to changes in spatial utilization efficiency in the Yangtze and Yellow River basin urban agglomeration. The study provides practical suggestions for the high-quality development of territorial space, ecological environment management, and sustainable development in light of spatiotemporal changes.

Regional Disparities and Influencing Factors of Eco-Efficiency of Arable Land Utilization in China

Eco-efficiency of arable land utilization (EALU) emphasizes efficient coordination between land use systems and ecosystems. It is therefore of great significance for agricultural sustainability based on the systematic assessment of EALU. This study took carbon emissions and non-point source pollution resulting from arable land utilization into the measurement system of EALU, and a super-SBM model, kernel density estimation and Tobit regression model were used to analyze regional differences and influencing factors of EALU for 31 provinces in China from 2000 to 2019. The results showed that there was an upward trend in EALU in China from 0.4393 in 2000 to 0.8929 in 2019, with an average annual growth rate of 4.01%. At the regional level, the EALU of three categories of grain functional areas generally maintains an increasing trend, with the highest average value of EALU in main grain marketing areas (MGMAs), followed by grain producing and marketing balance areas (GPMBAs) and main grain producing areas (MGPAs). There are obvious differences in EALU among provinces, and the number of provinces with high eco-efficiency has increased significantly, showing a spatial distribution pattern of “block” clustering. In terms of dynamic evolution, kernel density curves reflect the evolution of EALU in China and grain functional areas with different degrees of polarization characteristics. The results of Tobit regression show that natural conditions, financial support for agriculture, science and technology inputs, level of industrialization, agricultural mechanization, and the living standards of farmers are significant factors resulting in regional disparities of EALU. Therefore, this study proposes the implementation of differentiated arable land use/agricultural management strategies to improve the sustainable utilization of arable land.

Analysis of the spatial characteristics and influencing factors of agricultural eco-efficiency: evidence from Anhui Province, China, during the period 2011-2018

Sustainable agriculture is important for preserving environmental health and simultaneously gaining economic profits while maintaining social and economic equity. One way to evaluate sustainable agriculture is by studying agricultural eco-efficiency (AEE). Hence, this study constructed a data-driven method to evaluate and optimize AEE with the aim of providing a basis for improving the sustainable development of regional agriculture. Sixteen cities in Anhui Province, China, were considered in the study, and the variables used were agricultural resource inputs, environmental pollution, and agricultural economic development. Agricultural non-point source pollution (NPSP) emissions were considered the undesired output to build an AEE evaluation index system. Furthermore, a data envelopment analysis (DEA) model was established to analyse AEE from the static and dynamic perspectives. The spatial development and the temporal and spatial characteristics of AEE were also analysed. In addition, we applied a random effect (RE) panel Tobit model to quantitatively analyse the influencing factors of AEE from the input perspective and then proposed reasonable suggestions for improving the sustainable development of regional agriculture. Our findings show that the overall agricultural development in the 16 cities in Anhui Province has been continuously improving, even though there is an agglomeration of spatial development in some regions. In conclusion, this study provides suggestions and references for policy makers and agricultural practitioners regarding how to improve regional AEE and promote the sustainable development of the regional agricultural economy.

Input-Output Efficiency of Water-Energy-Food and Its Driving Forces: Spatial-Temporal Heterogeneity of Yangtze River Economic Belt, China

The high-quality development of the Yangtze River Economic Belt (YREB) plays a crucial role in economic transformation in China. Climate change, rapid population growth, and increased urbanization have contributed towards increased pressures on the water, energy, food (WEF) nexus system of YREB. Thus, there is an imperative need to improve the efficiency of WEF in YREB. However, few studies have conducted spatial-temporal heterogeneity exploration of YREB about the input-output efficiency of WEF (IOE-WEF). Using panel data from 2008–2017, a super slack based model (SSBM), combined with the spatial autocorrelation and spatial econometric method, were proposed to calculate the IOE-WEF of YREB’s 11 provinces, the results indicated that: (1) From the perspective of time, the IOE-WEF in YREB was relatively low and displayed a fluctuating downward pattern while considering the undesirable outputs. (2) From the perspective of space, the spatial distribution of IOE-WEF in YREB was uneven. The efficiency values of the three sub-regions of YREB were “the lower reaches > the middle reaches > the upper reaches”. The IOE-WEF of YREB had a prominent positive spatial correlation and also had a spatial spillover effect. (3) The spatial aggregation effect of IOE-WEF of YREB is gradually weakening. The spatial aggregation types of IOE-WEF in YREB were “high-high” cluster areas in lower reaches and “low-low” cluster areas in upper reaches. (4) From the perspective of driving forces, environmental regulation and technological innovation promoted the improvement of IOE-WEF of YREB, while the industrial structure and mechanization level inhibited the improvement of IOE-WEF of YREB. Furthermore, the role of government support of IOE-WEF of YREB was not obvious. The improvement of IOE-WEF in adjacent regions also had a notable positive spatial spillover effect on the region.

Agricultural Eco-Efficiency: Challenges and Progress

The research on agricultural eco-efficiency has become an important point to deeply understand the interaction between ecological and environmental conditions and socio-economic factors as well as realize the coordinated development of agricultural economic development and environmental protection. (1) Background: This paper attempts to provide scientific support for the healthy and stable development of the agricultural economy and the sustainable development of ecological agriculture. (2) Methods: From a comprehensive perspective, this paper systematically analyze the overall situation, development trend, key fields, and hot fields of agricultural eco-efficiency in the past two decades. It consists of two complementary parts, including systematic quantitative literature review (based on CiteSpace) and traditional literature review. (3) Results: Agricultural eco-efficiency has evolved significantly with the popularization of agricultural machinery and the wide application of science and technology in the field of agricultural ecology. Its future development relies on the advances in our knowledge on theories and hypothesis, evaluation methods, impact on “socio-economic ecological” system, and drivers and regulation of agricultural eco-efficiency. For each of these fields, we find that challenges still exist. At present, the quantitative methods and index selection are not unified. We should deeply analyze the internal and external driving force of the development and change of ecological efficiency by constructing a complete theoretical framework for the research of agricultural ecological efficiency. At the same time, new technologies and methods are needed to evaluate agricultural eco-efficiency, and a balanced consensus between the improvement of agricultural eco-efficiency and the improvement of the ecological environment should be formed through empirical research.

Spatial-temporal evolution of coupling relationship between land development intensity and resources environment carrying capacity in China

Land development poses challenges to the sustainable use of resources and environmental health in regions. This study explores the coupling relationship and its spatial-temporal evolution trend between land development intensity and resources environment carrying capacity of 31 provinces in China from 2005 to 2017. The information entropy method, coupling degree model, and coupling coordination degree model are used to calculate the index weight, coupling degree, and coupling coordination degree. The results show that: (1) Three change types of resources environment carrying capacity are presented with land development intensity increasing: first decrease and then increase; first increase and then decrease; and alternating fluctuations. (2) The proportion of construction land, GDP per land, and population density are dominate determinants of land development intensity, while the water resources per capita, energy consumption per unit of GDP, and per capita cultivated land area are that of resources environment carrying capacity. (3) From the perspective of temporal evolution, both coupling and coordination relationship were found to have continuously strengthened. (4) In terms of spatial evolution, the coupling level presented a constantly narrowing inter-regional gap, and the coordination level has changed from initial two-level differentiation to final regional gap narrowing. These findings can provide evidence in support for integrating land development with resources environmental protection to promote regional coordinated development.

Spatial-temporal evolution of agricultural ecological risks in China in recent 40 years

Excessive use of agricultural chemicals and unreasonable utilization of agricultural wastes have led to severe agricultural non-point source pollution (ANPSP) problems in China. Based on the agricultural pollution loads and pollution control strength, the ecological risk index (ERI) was constructed and was used to explore the spatial-temporal pattern of agricultural ecological risks in China during 1978-2017. The findings indicated that Chinese agricultural ERI was gradually increased from 0.031 to 0.348 in 1978-2017, which has the same phased change characteristics as the succession of agricultural policies. At present, the ecological risk grade of ANPSP was present in the stair-step distribution characteristics of "high in the east and south and low in the west and north" as a whole. Southern China, as the main producing area of aquatic products, had the higher ecological risks. Northeastern China, the Huang-Huai-Hai Area, and the middle and lower reaches of the Yangtze River, as the grain-producing bases, had moderate ecological risks, but Southwestern China and Northwestern China with the poor agricultural production conditions had the lower ecological risks. It evidently showed that the ecological risk problems faced by the high-quality development of Chinese agricultural industrialization are increasingly severe.

Spatial-Temporal Pattern and Evolution Trend of the Cultivated Land Use Eco-Efficiency in the National Pilot Zone for Ecological Conservation in China

The cultivated land use eco-efficiency (CLUE) is an important indicator to evaluate ecological civilization construction in China. Research on the spatial-temporal pattern and evolution trend of the CLUE can help to assess the level of ecological civilization construction and reveal associated demonstration and driving effects on surrounding areas. Based on the perspective of the CLUE, this paper obtains cultivated land use data pertaining to National Pilot Zones for Ecological Conservation in China and neighboring provinces from 2008 to 2018. In this study, the SBM-undesirable, Moran's I, and Markov chain models are adopted to quantitatively measure and analyze the CLUE and its temporal and spatial patterns and evolution trend. The research results indicate that the CLUE in the whole study area exhibited the characteristics of one growth, two stable, and two decline stages, with a positive spatial autocorrelation that increased year by year, and a spatial spillover effect was observed. Geographical spatial patterns and spatial spillover effects played a major role in the evolution of the CLUE, and there occurred a higher probability of improvement in the vicinity of cities with high CLUE values. In the future, practical construction experience should be disseminated at the provincial level, and policies and measures should be formulated according to local conditions. In addition, a linkage model between prefecture-level cities should be developed at the municipal level to fully manifest the positive spatial spillover effect. Moreover, we should thoroughly evaluate the risk associated with CLUE transition from high to low levels and establish a low-level early warning mechanism.