Prediction of Ecological Zoning and Optimization Strategies Based on Ecosystem Service Value and Ecological Risk

As a typical coastal tourist city, Sanya has experienced large-scale urbanization driven by tourism development, leading to landscape fragmentation, disorderly urban sprawl, and irrational resource utilization. These factors have intensified regional ecological risks and caused the degradation of ecosystem service functions, thereby constraining sustainable urban development. Therefore, establishing urban ecological zoning can identify the dynamic relationship between ecological conditions and urban growth, ease human-land conflicts, and promote high-quality urban development. This study employed the value equivalency method and the landscape ecological risk index method to calculate the ecosystem service value (ESV) and the ecological risk index (ERI) of Sanya City from 2000 to 2020 and to delineate ecological zones. The PLUS model was used to predict the changes in ecological zoning of Sanya City under a natural development scenario in 2030. The results demonstrate the following: (1) The ecological risk in the study area shows a distribution pattern of “high in the south and low in the north,” with low-risk areas being the dominant type, accounting for about 80% of the total area. Over time, the area of high-risk zones has shown an increasing trend, while that of low-risk zones has decreased year by year. (2) The ecosystem service value in the study area shows a distribution pattern of “high in the north and low in the south,” with a decreasing trend over time, with a cumulative reduction of 2.11 × 10 8 ten thousand yuan from 2000 to 2020. (3) Among the four ecological zones, the ecological protection zone is the dominant type, accounting for about 50%. The increase in the ecological early warning zone is the most significant. In contrast, the ecological optimization and improvement zones show a marked decrease. The prediction results show that by 2030, the ecological early warning and ecological protection zones will increase, while the other zones will decrease. This study adopts a temporal-dynamic approach by constructing a framework that integrates historical evolution with future simulation, providing scientific evidence for building Sanya’s ecological security pattern and spatial governance. It offers practical significance for coordinating regional ecological conservation with urban development.