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”.

As an important ecological ecotone of water and land ecosystems, the lakeside is characterized by a variety ecosystem services and high vulnerability. Forest land is important in resolving the ecological risks of the lakeside area and building its ecological base. It is important to explore the effect of change in forest land on landscape ecological risk in the lakeside area, alleviate the contradiction between ecological protection and construction and development in the area, and realize sustainable development. The present study attempted to explore the spatial and temporal evolutionary features of forest land in the Erhai rim region from 2000 to 2020 using bivariate spatial autocorrelation and multi-scale geographical weighted regression (MGWR) models. The following are the findings of this investigation of the 2000–2020 period: (1) the forest land area in the region generally decreased, first increasing and then decreasing, and was mainly occupied by cultivated land and artificial surfaces; (2) the total landscape ecological risk in the region presented an upward trend, and medium- and higher-risk areas were the main risk areas, with the latter increasing; (3) the impact of forest land expansion and contraction intensity on landscape ecological risk exhibited spatial and temporal heterogeneity. The main forms of forest land change at different stages differed, and the impacts on landscape ecological risk were also different. Reasonable forest land expansion can effectively alleviate the growth in landscape ecological risk, whereas the shrinkage of forest land would aggravate the landscape ecological risk in the Erhai rim region. Moreover, the findings can offer reference for the exploration of ecological protection and coordinated optimization of economic development in Erhai Lake.

Land use change in urban agglomerations is gradually becoming a major cause and a key factor of global environmental change. As a consequence of the interaction between land use and ecological processes, the transformation in natural ecosystem structure and function with human activity disturbances demands a systematic assessment of ecosystem health. Taking the Central Yunnan urban agglomeration, undergoing transition and development, as an example, the current study reveals the typical land use change processes and then emphasizes the importance of spatial heterogeneity of ecosystem services in health assessment. The InVEST model-based ecosystem service assessment is incorporated into the ecosystem health evaluation, and hotspot analysis is performed to quantitatively measure the ecosystem health response degree to land use according to spatial latitude. The study had three major findings: First, the urban land expansion in the urban agglomeration of central Yunnan between 1990 and 2020 is the most significant. Further, the rate of the dynamic change of urban land is 16.86%, which is the highest among all land types. Second, the ecosystem health of the central Yunnan urban agglomeration is improving but with obvious spatial differences, showing a trend of increasing from urban areas to surrounding areas, with the lowest ecosystem health level and significant clustering in the areas where the towns are located. The ecosystem health level is mainly dominated by the two classes of ordinary and well grades, and the sum of the two accounts for 63.35% of the total area. Third, the process of land transfer, mutual transfer between forest and grassland, and conversion from cropland to forest land contributed the most to the improvement of ecosystem health across the study area. Furthermore, the conversion from cropland and grassland to urban land is an important cause of the sustained exacerbation of ecosystem health. Significantly, the study provides a scientific reference for maintaining ecosystem health and formulating policies for macro-control of land in the urban agglomerations of the mountain plateau.

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.