Land surface elements, such as land use, are in constant change and dynamically balanced, driving changes in global ecological processes and forming the regional differentiation of surface landscapes, which causes many ecological risks under multiple sources of stress. The landscape pattern index can quickly identify the disturbance caused by the vulnerability of the ecosystem itself, thus providing an effective method to support the spatial heterogeneity of landscape ecological risk. A landscape ecological risk model based on the degree of interference and fragility was constructed and spatiotemporal differentiation of risk between 1980 and 2017 in Shaanxi Province was analyzed. The spatiotemporal migration of risk was demonstrated from the perspective of geomorphological regionalization and risk gravity. Several conclusions were drawn: The risk of Shaanxi Province first increased and then decreased, at the same time, the spatial differentiation of landscape ecological risk was very significant. The ecological risk presented a significant positive correlation but the degree of autocorrelation decreased. The risk of the Qinba Mountains was low and the risk of the Guanzhong Plain and Han River basin was high. The risk of Loess Plateau and sandstorm transition zone decreased greatly and their risk gravities shifted to the southwest. The gravity of the Guanzhong Plain and Qinling Mountains had a northward trend, while the gravity of the Han River basin and Daba Mountains shifted to the southeast. In the analysis of typical regions, there were different relationships between morphological indicators and risk indexes under different geomorphological features. The appropriate engineering measures and landscape management for different geomorphological regionalization were suggested for effective reduction of ecological risks.

As a tool that can effectively support ecosystem management, ecological risk assessment is closely related to the sustainable development of ecosystems and human well-being and has become an active area of research in ecology, geography and other disciplines. Taking Dujiashi Gully for the study of gully loess erosion, a comprehensive risk assessment system for identifying risk probability, sensitivity and impairment was established. The spatial distribution of comprehensive ecological risk was analyzed, the ecological risk management categories were simultaneously delineated based on the risk dominant factor and the risk management strategies were formulated in loess regions. The results were as follows: (1) the spatial differences in comprehensive ecological risk were significantly different in the research area. The regions with extremely high and high risk were mainly located in gully areas and secondary erosion gullies, which are in 28.02% of study area. The extremely low-risk areas covered 1/3 of the study area and were mainly distributed to the northwest and south of the study area, where hills are widely spaced. (2) The combined analysis of ecological risk and terrain found that the elevation decreased first and then rose but the comprehensive ecological risk increased first and then decreased from north to south. Comprehensive ecological risk and terrain generally showed an inverse relationship. (3) The study area was divided into four types of risk management categories. Risk monitoring zones, habitat recovery zones, monitoring and recovery zones and natural regulation zones encompass 14.84%, 12.44%, 26.47% and 46.25% of the study area, respectively. According to four types of risk management categories, different risk reduction measures were designed to improve regional sustainable development capacity. Risk identification and risk management categories based on comprehensive ecological risk model can design a sustainable development path for social ecosystem and local farmers and provide a method for sustainable development for similar gully landscapes.

Cultural ecosystem services (CESs) are an important part of ecosystem services (ESs). Correctly understanding the supply and demand relationship of CES is the premise of ES sustainable management and helps to improve human well-being. However, the evaluation and mapping of CES supply and demand represents a significant gap in ES research. Using the Shigou Township of Mizhi County in China as an example, in this study, we evaluated CES supply and demand at the village scale. We first considered three aspects of supply potential, accessibility and quality to construct an indicator system of six types of CES supply, including aesthetic (Aest), sense of place (SP), social relations (SR), cultural heritage (Cult), education (Edu) and recreation (Recr) and obtained demand data through a questionnaire. Then, we identified the imbalance in the supply and demand of CES by Z-score standardization based on the quantification of the CES supply and demand. Secondly, bivariate spatial autocorrelation analysis was used to identify tradeoffs/synergies on the CES supply side, and chi-square tests were used to identify CES demand differences between stakeholder groups. The results indicated that the supply–demand patterns of CES presented evident spatial differences. The low-supply–high-demand patterns of Aest, SR and Recr accounted for the largest proportions, with values of 33.33%, 33.33% and 30.95%, respectively. The low-supply–low-demand patterns of SP and Cult accounted for the largest proportions, with values of 30.95% and 38.10%, respectively. The low-supply–low-demand pattern of Edu accounted for the smallest proportion (21.43%) and was mainly located in the south of Shigou Township. The southwest, northeast and central areas of Shigou Township were the key regions of tradeoffs/synergies of CES supply. There were significant differences in CES demand for SR, Cult and Edu among stakeholder groups. The results could contribute to optimizing regional ecosystem management and provide effective information for improving the imbalance between the supply and demand of CES.

In general, specific indicators of landscape sustainability are missing. To spatially evaluate landscape sustainability and its change in a rural landscape, the authors combined ecological and social components to develop an indicator system and a model based on information entropy. Four types of information entropy, namely, landscape service capability, landscape service demand, landscape vulnerability and landscape adaptation, were calculated using year-based information entropy to analyze the spatial-temporal differentiation of a rural ecosystem. Combined with the landscape composition and configuration indicators, the spatial and temporal differentiation of landscape sustainability was analyzed, and the effect of landscape structure on landscape sustainability was explored. Based on survey data from Mizhi County, Shaanxi Province, China from 2009 to 2014, the following results were obtained: (1) An analysis of entropy change could be used to evaluate landscape sustainability. (2) The carrying capacity of the complex ecosystem in the study area increased during the study period. (3) If the effect of landscape structure is not considered, then the landscape sustainability of the study area might be overestimated. Additionally, it was pointed out that the analysis of landscape sustainability through Boltzmann entropy also provides a new way to test and verify the research results in the future.

Exploring and analyzing the common demands and behavioral responses of different stakeholders is important for revealing the mediating mechanisms of ecosystem service (ES) and realizing the management and sustainable supply of ES. This study took Mizhi County, a poverty-stricken area on the Loess Plateau in China, as an example. First, the main stakeholders, common demands, and behavioral responses in the food provision services were identified. Second, the relationship among stakeholders was analyzed. Finally, this study summarized three types of mediating mechanisms of food provision services and analyzed the influence of the different types of mediating mechanisms. The main conclusions are as follows: (1) Five main stakeholders in the study area were identified: government, farmers, enterprises, cooperatives, and middlemen. (2) Increasing farmers’ income is the common demand of most stakeholders in the study area, and this common demand has different effects on the behavioral responses of different stakeholders. (3) There are three types of mediating mechanisms in the study area: government + farmers mediating corn and mutton, government + enterprises mediating millet, and government + cooperatives mediating apples. On this basis, the effects of the different types of mediating mechanisms on variations in food yield, and trade-offs and synergies in typical townships, were analyzed.