Sound ecosystems are a precondition for the sustainable survival and development of human society. However, ecological deterioration caused by socioeconomic activities can result in increasing pressure on ecosystems. Exploration of the spatial interaction between ecosystem and economic development under the background of high-quality and green development is, therefore, necessary. In this study, we analyzed the spatial interaction between the ecosystem services value (ESV) and economic development with the economic and ecological coupling index method based on high-resolution remote-sensing land-use data and socioeconomic statistical data in Hunan Province from 2000 to 2018. The results revealed that the ESV provided by the ecosystems in Hunan Province decreased by US$1256.166 million from 2000 to 2018. The areas with high ESV per unit area were distributed in the mountainous areas, while the areas with low ESV per unit area were distributed in the major cities and their surroundings. The bivariate spatial autocorrelation analysis showed that the ESV had significant spatial dependence on the economic development. In addition, the coupling analysis documented that the relationship between the ESV and economic density was mostly in the low conflict and potential crisis states. These results provide important guidance for the coordinated development of the regional economy and ecosystem conservation.

Urban agglomerations have gradually formed in different Chinese cities, exerting great pressure on the ecological environment. Ecosystem health is an important index for the evaluation of the sustainable development of cities, but it has rarely been used for urban agglomerations. In this study, the ecosystem health in the middle reaches of the Yangtze River Urban Agglomeration was assessed using the ecosystem vigor, organization, resilience, and services framework at the county scale. A GeoDetector was used to determine the effects of seven factors on ecosystem health. The results show that: (1) The spatial distribution of ecosystem health differs significantly. The ecosystem health in the centers of Wuhan Metropolis, Changsha–Zhuzhou–Xiangtan City Group, and Poyang Lake City Group is significantly lower than in surrounding areas. (2) Temporally, well-level research units improve gradually; research units with relatively weak levels remain relatively stable. (3) The land use degree is the main factor affecting ecosystem health, with interactions between the different factors. The effects of these factors on ecosystem health are enhanced or nonlinear; (4) The effect of the proportion of construction land on ecosystem health increases over time. The layout used in urban land use planning significantly affects ecosystem health.

Since the 21st century, crisis events have been frequent and normalized globally, and improving resilience has become the key for the tourism industry to cope with various uncertainty risks. To reveal the reality of the economic resilience of tourism in China, this study employed the autoregressive integrated moving average model (ARIMA) to construct a counterfactual function and integrated with the peaks-over-threshold (POT) model and geographical detector model to evaluate the spatiotemporal evolution and influencing factors of the economic resilience of tourism in China from the resistance and recoverability perspective, with a view to providing a reference for consolidating the resilience of the economic system of tourism in China and promoting the sustainable development of its tourism economy. The results showed that the economic resilience of tourism in China can be divided into four types—robust, self-reliant, laissez-faire, and fragile—based on a baseline resistance of −0.361 and recoverability of 0.342. Under different contraction–recovery cycles, the resistance and recoverability of China’s tourism economy have been progressively improved, transforming from the centralized model to the discrete model, from a fragile to a self-reliant type. The type of economic resilience of tourism in China exhibited a clustered contiguous development trend, with obvious zonal distribution characteristics and self-reliant tourism economic resilience areas dominating, but most areas have not yet formed stable economic resilience in their tourism sector. The ecological environment quality, government management ability, and technological innovation level were the main factors affecting the economic resilience of tourism in China. The interactions between different influencing factors were more significant in strengthening the tourism economic resilience.

Urban agglomeration is the highest stage of urban development, which reasonable planning will be conducive to the rapid and healthy development of the regional economy. However, in recent years, unreasonable urban agglomeration planning has changed landscape patterns and brought huge challenges to ecosystem services. Moreover, there is currently a lack of understanding of the relationship between landscape patterns and ecosystem services, especially in the process of urban agglomeration construction. In this study, we attempt to reveal the impact of landscape patterns on ecosystem services value (ESV) based on many years of remote sensing data in the Central Plains Urban Agglomeration (CPUA). The results show that landscape patterns have significant spatiotemporal evolution characteristics, and there are significant differences between different landscape patterns in the CPUA. Moreover, most of landscape patterns show significant east-west differences. Total ESV has decreased from USD 838.53 million in 2000 to USD 792.32 million in 2018. From a spatial perspective, the areas with high ESV are mostly distributed in the western mountainous and southern hilly areas, but low ESV area are mainly concentrated in the central and northern plains. In addition, the results of model analysis reveal that there is a remarkable positive correlation between ESV and patch density, interspersion juxtaposition index, cohesion index, and splitting index, but a remarkable negative correlation between ESV and total edge. These results provide critical guidance and suggestions for the improvement of future urban agglomeration construction.

As China’s economy shifts from rapid development to high-quality development, exploring the harmony between human activities and the ecological environment has become the focus of many scholars. As the center of human activities, urbanized areas have complex and diverse impacts on the ecological environment. Previous studies have mainly focused on highly urbanized areas of importance in China, and there are fewer studies covering all prefecture-level cities across the country. Therefore, this study measured the spatial and temporal characteristics of urbanization and eco-environment quality (EEQ) in all prefecture-level cities in China from 2000 to 2020 and explored the coupling coordination degree (CCD) relationship between urbanization and EEQ through the CCD model. The results showed that the average EEQ showed a fluctuating upward trend, with the southern and northeastern regions scoring significantly higher than the western and northern regions. In terms of spatial evolution, most prefecture-level cities had small changes in EEQ, with changes ranging from −0.05 to 0.05 per decade. The average urbanization showed a rapid increasing trend, spatially distributed with high values in the east and low values in the west. In the North China Plain and along the southeast coast, urbanization was concentrated in high-value areas, showing a trend of rapid growth. From 2000 to 2020, the average CCD between urbanization and EEQ showed a continuous increasing trend, from 0.32 to 0.37, indicating a medium imbalance. However, the proportion of low-coordination and moderate-coordination prefecture-level cities increased continuously, from 31.5% and 1.0% in 2000 to 35.3% and 1.9% in 2020, respectively. This indicates that Chinese urbanization efforts are constantly being optimized and moving toward the goal of sustainable development. The results of the study provide a scientific reference basis for coordinating the relationship between urbanization development and EEQ, and they support the formulation of policies for urbanization planning and high-quality economic development in China.

Forest types are associated with differences in soil properties and microbial communities, but the environmental correlates of microbial variation across soil depths remain poorly resolved. We examined whether PLFA-derived microbial community structure was more closely associated with bulk soil carbon (C) concentrations or with variation in soil C stoichiometry across five representative subtropical forest types in central China. Soil physicochemical properties and phospholipid fatty acid (PLFA) profiles were assessed in surface (0–10 cm) and subsurface (10–30 cm) soils. Forest types were associated with differences in soil moisture, pH, inorganic nitrogen, available phosphorus, total C (TC), total N (TN), and C ratio, accompanied by distinct patterns of PLFA-derived microbial characteristics. Oak forest had the highest TC and TN concentrations but the lowest total PLFA abundance, whereas dawn redwood forest had relatively high microbial biomass despite comparatively low TC and TN concentrations. RDA showed that soil C ratio was the strongest environmental variable associated with PLFA-based microbial community variation in both soil layers, followed by pH and NO₃⁻, while SWC showed an additional association in the surface soil. At the microbial-group level, soil C ratio was negatively associated with bacterial and actinomycete biomarkers, whereas soil pH showed positive associations with fungal and arbuscular mycorrhizal fungal PLFAs. These results indicate that variation in PLFA-derived microbial characteristics among the sampled forest types was more closely associated with bulk soil C stoichiometry and other soil environmental conditions than with TC concentration alone. Overall, bulk soil C stoichiometry provides an informative correlate of below-ground microbial variation across the sampled forest types, although these associations do not establish causal effects of forest type.