An understanding of the relationships among multiple ecosystem services (ES) facilitates ecosystem management and decision-making. The study of ES bundles can well explain the complex interactions between different ES in a region. Shenyang is a significant economic development and food production area in Northeast China, with a diverse range of ES types. In this study, we quantified eleven ES from Shenyang, China (two provisioning services, eight regulating services, and one cultural service). The trade-offs and synergies among ES were analyzed by Spearman’s correlation analysis. The ES bundles were identified using principal component analysis and k-means cluster analysis. Finally, the random forest method was employed to identify the driving factors affecting the ES bundles. The results showed: (1) all ES in Shenyang improved between 2000 and 2019; (2) the most obvious trade-off was found between sand fixation and water conservation; (3) the ES in the study region could be clustered into five different ES bundles which were primarily affected by land-use type; and (4) social-ecological factors largely explained and predicted the formation and distribution of ES bundles. The study provides reference information for the management and optimization of Shenyang’s ecosystems and land use regulation.

Ecosystem service research is essential to identify the contribution of the ecosystem to human welfare. As an important ecological barrier zone, the Qinghai-Tibet Plateau (QTP) supports the use of a crucial wind erosion prevention service (WEPS) to improve the ecological environment quality. This study simulated the spatiotemporal patterns of the WEPS based on the Revised Wind Erosion Equation (RWEQ) and its driving factors. From 2000 to 2015, the total WEPS provided in the QTP ranged from 1.75 × 10⁹ kg to 2.52 × 10⁹ kg, showing an increasing and then decreasing trend. The average WEPS service per unit area was between 0.72 kg m⁻² and 1.06 kg m⁻². The high-value areas were concentrated in the northwest and north of the QTP, and the total WEPS in different areas varied significantly from year to year. The average retention rate of the WEPS in the QTP was estimated to be 57.24–62.10%, and high-value areas were mainly located in the southeast of the QTP. The total monetary value of the WEPS in the QTP was calculated to be between 223.56 × 10⁹ CNY and 321.73 × 10⁹ CNY, and the average WEPS per unit area was between 0.08 CNY m⁻² and 0.13 CNY m⁻², showing a declining–rising–declining trend. The high-value areas gradually expanded to the west and east of the QTP. The slope was the most important factor controlling the spatial differentiation of the WEPS, followed by the landform type, average annual precipitation, and average annual wind speed, and human activities such as land-use change could improve the WEPS by returning farmland to grassland and desertification control in the QTP.

Human food safety should be given priority during a major public health crisis. As the primary element of agricultural production, labor tends to suffer the most during a period of public health concern. Studying the impact of epidemic-affected labor shortages on agricultural production, trade, and prices has important implications for food security. This study used a calculable general equilibrium model to study the changes in agricultural production, trade, and prices under different labor damage scenarios. The results showed that agricultural production was less affected under a scenario where the epidemic was controlled locally. The output of agricultural products decreased by about 2.19%, and the prices of agricultural products increased slightly. However, the nationwide output of agricultural products decreased by only 0.1%, and the prices remained largely stable. In the case of the spread of the epidemic, the output of agricultural products in the epidemic area decreased by 2.11%, and the prices of certain agricultural products increased significantly. For example, the price of vegetables increased by 0.78%, the price of pork increased by about 0.7%, and those of agricultural products in other parts of the country also increased slightly. Compared with the national spread scenario, the local outbreak scenario had a smaller impact on Chinese food security, indicating Chinese effective policy against the epidemic. Although the impact of labor shortage under the influence of the epidemic on China was relatively limited, and considering its stable food security, we should pay attention to the increase in the process of agricultural products and changes in agricultural trade in the epidemic area. The residents in the epidemic areas could not effectively obtain nutritious food, which affected their health. Thus, the government should also completely mobilize agricultural resources to ensure the nutrition safety of residents during major public health incidents.

Inner Mongolia is the important ecological barrier zone in northern China, which plays an important role in the prevention and control of wind in the regional ecosystem. Based on the Revised Wind Erosion Equation (RWEQ) model and the cost-recovery method, this study simulated the wind erosion prevention service (WEPS) in Inner Mongolia in 2010 and 2015, investigated the spatial pattern of material and monetary value of WEPS, and analyzed the differences among various cities and various ecosystems. The results indicated that the total WEPS of Inner Mongolia was estimated to be 73.87×108 t in 2015, which was 4.61×108 t less than in 2010, while the monetary value of WEPS was calculated to be 738.66×108 yuan in 2015, which was 46.16×108 yuan less than in 2010. Among all the leagues and cities, Xilin Gol League supported the highest WEPS, reaching 18.65×108 t in 2015, while Wuhai provided the lowest. The WEPS of Hulunbeier increased the most, by 4.37×108 t from 2010 to 2015. The WEPS in the grassland ecosystem was the highest among the different ecosystems, accounting for more than 55% of the total WEPS in Inner Mongolia, but it was reduced by 1.05×108 t during the same period. The WEPS in the forest ecosystem increased the most, reaching 0.19×108 t. This study found that the implementation of projects such as returning farmland to forests and grasses and sand control effectively increased the WEPS by increasing the forest area. However, unsuitable land use increased the desertification of ecosystems which resulted in a reduction of WEPS in Inner Mongolia.

The Blue Economic Zone of the Shandong Peninsula is located in the transitional zone between land and sea, with a complex ecological environment. The determination of hot and cold spots in various ecosystem services is crucial for the coordinated development of ecosystem services and the optimization of the spatial pattern of the ecological environment. This study, based on natural and socio-economic data, utilizes various ecological models to simulate water yield (provisioning service), carbon sequestration (regulating service), biodiversity (supporting service), and aesthetic and scientific research values (cultural service). Using a multi-criteria decision-making approach, it identifies hot and cold spots of ecosystem services in different development–conservation scenarios. Combining the protection efficiency of different areas, it proposes a spatial pattern promotion scheme. The research indicates significant spatial differences in ecosystem services without clear trade-offs and synergies. Changes in the weights of ecosystem services in 11 scenarios result in significant differences in hot and cold spots. Compared to the neutral scenario (S6), the distribution of hot and cold spots in protection scenarios (S1–S5) is relatively scattered, while in development scenarios (S7–S11), hot spots show an increasing trend of concentration in the southeast, with cold spots scattered in the west and northwest. Four spatial pattern promotion schemes are proposed based on protection efficiency and policy preferences. Promotion areas should focus on ecological restoration and improvement to raise local ecosystem service levels. Protection areas should emphasize maintaining their existing high-level ecosystem services to achieve a synergistic enhancement of various ecosystem services.