Objective Climate change, biodiversity loss, and environmental pollution are widely recognized as the triple planetary crisis. Among them, climate change has intensified the frequency and magnitude of extreme wind events, particularly typhoons, resulting in substantial impacts on ecosystems and human societies. China is located within the active typhoon belt of the northwest Pacific, where approximately 80% of annual typhoons make landfall. Coastal regions exhibit pronounced spatial heterogeneity in wind disaster risk due to complex interactions among topography, climate conditions, and socioeconomic development. Protected areas, as critical spatial units for biodiversity conservation and ecological security, are increasingly exposed to wind hazards. However, systematic assessments of wind disaster risk at the protected-area scale remain limited. Existing studies predominantly adopt the three-dimensional “hazard−exposure−vulnerability” framework proposed by the Intergovernmental Panel on Climate Change (IPCC). In this framework, hazard represents the intensity and frequency of disasters, exposure reflects the degree to which natural and social elements are affected, and vulnerability indicates the likelihood of system damage. While this framework has been widely applied to floods, earthquakes, heatwaves, and other natural hazards, its application to wind disaster risk in protected areas is still insufficient. In particular, previous studies often fail to integrate long-term hazard dynamics with ecological and socio-economic characteristics, limiting their ability to support targeted risk management and spatial planning.

Methods To address these gaps, drawing on the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, we developed a three-dimensional wind disaster risk assessment framework integrating hazard, exposure, and vulnerability. The framework combined multi-source environmental and socio-economic data to quantify wind disaster risk and reveal its spatial differentiation and temporal evolution. The Fuzhou Metropolitan Area was selected as the case study because it is located along China’s southeastern coast, characterized by frequent typhoon activity, diverse protected area types, and pronounced coastal-inland gradients, making it a representative region for examining wind disaster risks under climate change. Within this framework, wind disaster risk levels of protected areas in 1980 and 2020 were quantified and compared. Multi-criteria evaluation methods were applied to construct the hazard, exposure, and vulnerability indices, while the entropy weight method was used to reduce subjectivity in indicator selection. ArcGIS spatial analysis techniques, including spatial overlay,zonal statistics, and hotspot analysis, were employed to analyze the spatial patterns and temporal dynamics of wind hazards, exposure, vulnerability, and comprehensive risk. At the indicator level, meteorological, topographic, ecological, and socio-economic data were integrated to conduct comparative risk assessments across protected areas in the Fuzhou metropolitan area.

Results 1） Wind disaster risk exhibited a clear spatial pattern characterized by higher risk in the south (0.57) and lower risk in the north (0.09), with coastal protected areas generally facing higher risk levels than inland areas. Wind disaster risk showed clear spatial clustering, with high-risk protected areas (0.61−0.66) concentrated in the southern and southwestern regions, medium−high risk areas (0.500−0.550) in the central transition zone, and low-risk areas (≤0.01) mainly distributed in the northern and northeastern regions, showing a pronounced south−north decreasing gradient. 2）Exposure levels across protected areas were generally moderate to high, while vulnerability showed an overall increasing trend from 1980 to 2020, indicating growing sensitivity of protected areas to wind hazards over time. In 1980, high-exposure areas (0.59−0.62) were located in northwest mountains and central hills, and low-exposure areas (0.04) were along the eastern coast. By 2020, high-exposure zones persisted but declined (e.g., from 0.59 to 0.31), with low coastal exposure unchanged, showing stable spatial patterns and an overall decrease. 3）Comprehensive wind disaster risk differed markedly among protected area types, ranked from high to low as forest parks to scenic areas, nature reserves, wetland parks, and geological parks. High-risk protected areas, including Jiulihu Scenic Area, Dafeishan, and Biqing Forest Parks (0.54−0.57), clustered in the south and south-central region. Medium-risk areas (0.30−0.50) occupied central and coastal transitional zones. Low-risk areas, such as Dongchong Peninsula, Sandu’ao, and Baiyunshan Parks (≤0.20), were located in the north and inland mountains.

Conclusion Based on these findings, we proposed three planning optimization strategies for protected areas: optimizing functional zoning to reflect spatial risk differentiation, establishing dynamic wind hazard monitoring and early-warning mechanisms, and implementing pilot-based differentiated risk mitigation measures tailored to specific risk profiles. We analyzed wind disaster risks across temporal and spatial scales and visualized their dynamics through spatial mapping. Focusing on the protected area level, fine-scale spatial heterogeneity and temporal evolution patterns can be identified, which are often obscured in conventional assessments. By revealing the spatial patterns and evolution characteristics of wind disaster risk from a protected-area perspective, we provided an assessment framework that balances universality and practicality. The framework can offer practical support for climate-resilient planning and governance of protected area systems under ongoing climate change.