The division of the territorial space functional area is the primary method to study the rational exploitation and use of land space. The research on the Production–Living–Ecological Space (PLES) change and its motivating factors has major implications for managing and optimizing spatial planning and may open up a new research direction for inquiries into environmental change on a global scale. In this study, the transfer matrix and landscape pattern index methods were used to analyze the temporal changes as well as the evolution features of the landscape pattern of the PLES in the Chaohu Lake Basin from 2000 to 2020. Using principal component analysis and grey correlation analysis, the primary driving indicators of the spatial changes of the PLES in the Chaohu Lake Basin and the degree of the influence of various driving factors on various spatial types were determined. The study concluded with a few findings. First, from the standpoint of landscape structure, the Chaohu Lake Basin’s agricultural production space (APS) makes up more than 60% of the total area, and it and urban living space (ULS) are the two most visible spatial categories. Second, the pattern of the landscape demonstrates that the area used for agricultural production holds a significant advantage within the overall structure of the landscape. Although there is less connectedness between different landscape types, less landscape dominance, and more landscape fragmentation, the structure of different landscape types tends to be more varied. Third, the findings of the driving analysis demonstrate that the natural climate, population structure of agricultural development, and industrial structure of economic development are the three driving indicators of the change of the PLES. Finally, in order to promote the formation of a territorial space development pattern with intensive and efficient production space, appropriate living space, and beautiful ecological space, it is proposed to carry out land regulation according to natural factors, economic development, national policies, and other actual conditions.

Ecosystem services (ES) are directly affected by land use and land cover changes (LUCC); however, the impacts of extended period LUCC on ES are poorly explored. Here, we mapped the 1998–2019 annual land use and land cover in the Dongting Lake Region (China) and explored the spatiotemporal evolution of LUCC and landscape patterns (i.e., composition, shape, and aggregation) and their relationship with ES, including carbon storage, gross primary production (GPP), water conservation capacity, and crop yield in the region. The results showed a significant increase in forest areas and impervious surfaces and a decrease in croplands and bare lands with spatial heterogeneity. Carbon storage was strongly correlated with forest, cropland, waterbody, impervious surface, and bare land, and there was a nonlinear relationship between landscape patterns and ES. The trade-offs and synergies (correlations) among ES varied considerably, with crop yield being significantly synergistic with carbon stocks, GPP, or GPP with carbon stocks. This study revealed the nonlinear relationship between landscape patterns and ES, and the mechanism of landscape characteristics on ES. The findings can provide scientific support for regional land use planning, ES regulation, and landscape optimization in the lake region.

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.