Watersheds provide a spatial framework for tightly coupling human activities and the natural environment. Investigating the spatial distribution patterns of traditional villages within watersheds is crucial for comprehending their origins and advancing conservation and development efforts. This study employs methods such as the nearest neighbor index, kernel density estimation, spatial auto-correlation analysis, stepwise regression, and geographically weighted regression to explore the watershed characteristics and influential factors governing the spatial differentiation of traditional villages in Fujian Province. The findings indicate that traditional villages in Fujian exhibit an overall clustered distribution within the watershed space, with a tendency to cluster along basin boundaries, primarily concentrated in three hot spot regions. In the remaining small watersheds, the distribution is more balanced. Traditional villages are predominantly located near low-order streams, displaying a distribution pattern along tributaries, while in the Huotongxi river basin, they are more evenly distributed near second-, third-, and fourth-order streams. Relief, annual average temperature, annual average precipitation, arable land, per capita GDP, distance to county-level or higher-grade cities, and the concentration of cultural heritage preservation units are the primary factors affecting the spatial differentiation of traditional villages within watersheds, exhibiting significant spatial heterogeneity. Finally, this study proposes recommendations for the cluster protection and development of traditional villages in watersheds, addressing spatial, cultural, landscape, industrial, and governance aspects.

Service satisfaction with public policies is an important component of public service quality management, which is of great significance to the improvement of public service quality. Based on an online questionnaire survey and in combination with the characteristics of public policies and services, in this study the influencing factors of residents’ satisfaction with COVID-19 pandemic prevention services were analyzed with structural equation modeling. The results reveal that the data fit the model well, and all the hypotheses formulated in this study were supported. Among the factors that were found to directly affect residents’ satisfaction with pandemic prevention services, perceived quality (PQ) has the greatest impact on satisfaction, followed by the disaster situation (DS) and policy expectation (PE). The observed variables that have significant impacts on the latent variables were also explored. Regarding the main findings, the residents who were seriously affected by the pandemic tended to have lower satisfaction with the policies and services provided by the government. Moreover, the improvement of PQ was found to significantly increase pandemic prevention service satisfaction (SS). Finally, the residents with a good psychological status during the pandemic were found to have higher satisfaction. According to the results, implications for the prevention and control practices of similar public health emergencies are proposed.