In the face of rapid urbanization and global climate change, understanding the trade-offs and synergies of wetland city ecosystem services is vital for mitigating regional ecological and environmental risks, and enhancing human well-being. The Dongting Lake Basin is an ecologically fragile area of global significance. Uncontrolled resource utilization and intensive human activities have severely damaged the ecological environment, including in Miluo. Thus, it is of paramount research importance to uncover the trade-offs and synergies of ecosystem services and their driving mechanisms in Miluo. To achieve this, we classified Miluo’s land use data over the past two decades using a random forest model and Landsat imagery. We quantified the major ecosystem services in Miluo by employing ecological process models such as InVEST, RUSLE, and CASA. Additionally, we examined the trade-offs and synergies between ecosystem services at different scales and identified the driving mechanisms using multi-source remote sensing data. The results revealed that forests exhibited the highest level of ecosystem services, while urban ecosystem services experienced a significant decline. Over the past two decades, Miluo displayed notable trade-offs and synergies between ecosystem services, with synergies prevailing as the dominant pattern, particularly at the county scale. Furthermore, human activities emerged as the primary driver of changes in Miluo’s ecosystem services during the 20-year period. Therefore, it is imperative for scientists, policymakers, and civil society to develop effective and scientifically sound strategies to mitigate the ecological risks resulting from rapid urbanization and climate change in the future.

The study of spatial layout in China is changing from land use/land cover to territorial spatial layout and is mostly carried out at the administrative division scale. However, the driving factors affecting the evolution of territorial spatial layout are not all influenced by administrative boundaries. As cities are mostly centered on lakes and water systems, the evolution of territorial spatial layout in lake-type basins must have its own special characteristics. Taking the Dongting Lake Basin (DLB), a representative lake-type basin in China, as an example, this study identifies its territorial spatial layout elements and couples the system dynamics model with the patch-generating land-use simulation model based on multi-layer perceptron artificial neural networks. This study identified the best combination of driving factors and research step size affecting the evolution of territorial spatial layout. An improved quantitative spatial coupling model was used to simulate the territorial spatial layout of the DLB from 2000 to 2050 and identify its evolutionary characteristics and trends at both the elemental level and for three types of space. The simulation and prediction of territorial spatial layout from the lake-type basin hydrology scale can provide a reference for the formulation of regional territorial spatial planning policies.

Hilly mountainous regions are ecologically complex, featuring diverse environmental ecosystem services (ESs) and intricate interactions. However, the variability, drivers, and management of these ESs remain poorly understood, particularly in regions with significant topographical and climatic heterogeneity. This study focuses on the southern hilly mountain belt of China, examining five key ecosystem services: food production (FP), carbon storage (CS), water yield (WY), habitat quality (HQ), and soil conservation (SC). This study examines these ESs across long-term, pixel, and regional scales, exploring the interactive relationships and identifying the driving factors and cluster characteristics. The results indicate the following: (1) Over the past 23 years, although food production and carbon storage have increased, habitat quality has declined. (2) From a spatial perspective, the differences in trade-offs and synergies across the years are relatively small. However, significant differences are observed when considering continuous temporal change, and trade-off relationships are generally prevalent. Additionally, the distribution of trade-offs and synergies is also influenced by a combination of factors. (3) Climatic, vegetation, topographical, and socioeconomic factors are key factors influencing the distribution and changes in ESs. For instance, climate–vegetation interactions enhance carbon storage and soil conservation. Socioeconomic factors, though less impactful, optimize ESs through land management and policy. (4) We found that the ecological priority region covers the largest area, followed by the hilly agricultural development zone, the mountainous agricultural and forestry development zone, and the integrated ecological security zone. These findings deepen our understanding of ESs in hilly mountainous regions, providing actionable insights for enhancing conservation and sustainable management in complex landscapes.