As an emerging industrial form integrating forest ecosystems with diversified health services, forest wellness shows growing development potential, yet research on its spatial patterns and coordinated development mechanisms remains limited. Using 1,150 national pilot construction units of forest health and wellness bases (FHWBs) in China as samples, this study employs mathematical statistics and spatial analysis to examine their multi-scale spatiotemporal evolution. The Optimal Parameter-Based GeoDetector model is applied to identify dominant influencing factors of spatial differentiation, together with a multidimensional evaluation index system to assess forest wellness tourism development potential. Results indicate that China’s FHWBs exhibit a spatial distribution characterized by clustering in the southeast and sparsity in the northwest. At the county level, Theil index decomposition reveals significant inter-provincial and inter-prefectural disparities, indicating severe spatial imbalance, with high-value areas predominantly located along and west of the Hu Huanyong Line, while Heilongjiang Province stands as the sole exceptional high-value region east of this dividing line. This pattern results from the interactive coupling of multiple factors, with annual average temperature, sunshine duration, population density, and GDP per land area exerting significant influences. High-potential forest wellness tourism zones are strategically anchored around core cities in the Beijing-Tianjin-Hebei and Chengdu-Chongqing urban agglomerations, displaying an agglomerated development trend. Based on systematic evaluation of development potential and location matching, the study area is classified into five functional zones: Core-Leading Zone, Distinctive-Empowerment Zone, Integration-Optimization Zone, Collaborative Co-Construction Zone, and Standardization-Quality-Improvement Zone. This research is expected to provide a theoretical foundation for spatial pattern optimization and cross-regional coordinated development.
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Zhang et al. (2026) studied this question.
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