A healthy ecosystem is fundamental for sustainable urban development. Rapid urbanization has altered landscape patterns and ecological functions, resulting in disturbances to ecosystem health. Exploring the effects of urbanization on ecosystem health and the spatial relationships between them is significant for cities along the “Belt and Road” aiming to achieve sustainable regional development. This study took the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as an example and measured the urbanization level (UL) and ecosystem health index (EHI) from 2000 to 2020 using multisource data. We used bivariate spatial autocorrelation, the geographically weighted regression model (GWR), and the optimal parameters-based geographical detector (OPGD) model to clarify the impact of urbanization on ecosystem health and the spatial relationship between them from multiple perspectives. The major findings of this study were: (1) the EHI in the GBA decreased significantly during the study period, dropping from 0.282 to 0.255, whereas the UL increased significantly, exhibiting opposite spatial distribution features; (2) there was a significant negative spatial correlation between UL and the EHI and significant spatial heterogeneity between high–low and low–high types in the GBA; (3) the negative effects of urbanization on ecosystem health were predominant and becoming more pronounced in the central GBA. Moreover, urbanization had an increasingly significant negative effect, leading to the deterioration of ecosystem health, in the central GBA. Population urbanization drove land urbanization, which became the main factor affecting ecosystem health in the GBA. Overall, urbanization had a significant negative effect on ecosystem health, with this impact being particularly prominent in the core urban junctions of the GBA, which require urgent attention. The results of the study provide a basis for decision making in the context of the steady urbanization and ecosystem health protection of cities along the “Belt and Road”.

Rapid socio-economic development has had a significant impact on land use/cover (LULC) changes, which bring great pressure to the ecological environment. LULC changes affect ecosystem services by altering the structure and function of ecosystems. It is of great significance to reveal the internal relationship between LULC changes and ecosystem service value (ESV) for the protection and restoration of ecological environments. In this study, based on the spatial and temporal evolution of ecological service values in the Manas River basin from 1980 to 2020 and considering ecological and economic benefits, we coupled the gray multi-objective optimization model (GMOP) and patch-generating land-use simulation (PLUS) model (GMOP–PLUS model) to optimize the LULC structure under three scenarios (a natural development scenario, ND; ecological priority development scenario, (EPD); and balanced ecological and economic development scenario, EED) in 2030, and analyzed the trade-offs and synergies in the relationships among the four services. We found that from 1980 to 2020, farmland and construction land expanded 2017.90 km² and 254.27 km², respectively, whereas the areas of grassland and unused land decreased by 1617.38 km² and 755.86 km², respectively. By 2030, the trend of LULC changes will be stable under the ND scenario, the area of ecological land will increase by 327.42 km² under the EPD scenario, and the area of construction land will increase most under the EED scenario, reaching 65.01 km². From 1980 to 2020, the ESV exhibited an upward trend in the basin. In 2030, the ESV will increase by 7.18%, 6.54%, and 6.04% under the EPD, EED, and ND scenarios, respectively. The clustering of the four services is obvious in the desert area and around the water system with “low–low synergy” and “high–high synergy”; the plain area and mountainous area are mainly “high–low trade-off” and “low–high trade-off” relationships. This paper provides a scientific reference for coordinating economic development and ecological protection in the basin. It also provides a new technical approach to address the planning of land resources in the basin.

Land use changes induced by human activities change landscape patterns and ecological processes, threatening regional and global ecosystems. Terrain gradient and anthropogenic multi-policy regulation can have a pronounced effect on landscape components. Forecasting the changing trend of landscape ecological risk (LER) is important for national ecological security and regional sustainability. The present study assessed changes in LER in the Sichuan-Yunnan Ecological Barrier over a 20-year period using land use data from 2000, 2010, and 2020. The enhanced Markov-PLUS (patch-generating land use simulation) model was used to predict and analyze the spatial distribution pattern of LER under the following three scenarios. These were business-as-usual (BAU), urban development and construction (UDC), and ecological development priority (EDP) in 2030. The influence of terrain conditions on LER was also explored. The results showed that over the past 20 years, the LER index increased and then decreased and was dominated by medium and low risk, accounting for more than 70% of the total risk-rated area. The highest and higher risk areas for the three future scenarios have increased in spatial extent. The UDC scenario showed the largest increase of 3341.13 km² and 2684.85 km², respectively. The highest-risk level has a strong selectivity for low gradients, with high-level risks more likely to occur at low gradients. The response of ecological risk to gradient changes shows a positive correlation distribution for high-gradient areas and a negative correlation distribution for low-gradient areas. The influence of future topographic gradient changes on LER remains significant. The value of multiscale geographically weighted regression (MGWR) for identifying the spatial heterogeneity of terrain gradient and LER is highlighted. It can play an important role in the formulation of scientific solutions for LER prevention and of an ecological conservation policy for mountainous areas with complex terrain.