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<p>Understanding how multidimensional cultural ecosystem services (CES) vary across large, heterogeneous landscapes is critical for integrated protected area governance but hindered by methodological constraints. This study develops a reproducible, phrase driven framework to assess eight CES categories across 836 National Forest Parks in China. Utilizing a large-scale dataset of online visitor reviews from Ctrip, we employed a crowdsourced phrasal lexicon for context aware text matching and derived park level positive and negative CES intensity metrics. Unsupervised clustering of these multidimensional profiles revealed six distinct park typologies. Results demonstrate that visitor narratives are predominantly focused on single CES category, with co-occurrence being limited. The spatial distribution of CES intensity is highly uneven, following a long-tailed pattern where a small subset of parks accounts for most high-value expressions. While negative perceptions are infrequent overall, they provide critical diagnostic signals for specific dissatisfactory services. Analysis confirms structured spatiotemporal differentiation, with clear seasonal peaks for different CES and systematic variation across climate zones and regions. The identified typologies exhibit significant spatial clustering. This framework translates unstructured public perception into a scalable evidence chain, offering a practical tool for supporting differentiated park positioning, seasonal management strategies, and refined governance that explicitly incorporates cultural service values alongside ecological objectives.</p>

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Mapping cultural ecosystem services at scale: a phrase-driven profiling of China’s national forest parks

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月9日

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  • Wenjie Liu,
  • Jiaxuan Li,
  • Yuanyi Yang,
  • Huan Li,
  • Jiadong Shen,
  • Dengkai Huang

摘要

Understanding how multidimensional cultural ecosystem services (CES) vary across large, heterogeneous landscapes is critical for integrated protected area governance but hindered by methodological constraints. This study develops a reproducible, phrase driven framework to assess eight CES categories across 836 National Forest Parks in China. Utilizing a large-scale dataset of online visitor reviews from Ctrip, we employed a crowdsourced phrasal lexicon for context aware text matching and derived park level positive and negative CES intensity metrics. Unsupervised clustering of these multidimensional profiles revealed six distinct park typologies. Results demonstrate that visitor narratives are predominantly focused on single CES category, with co-occurrence being limited. The spatial distribution of CES intensity is highly uneven, following a long-tailed pattern where a small subset of parks accounts for most high-value expressions. While negative perceptions are infrequent overall, they provide critical diagnostic signals for specific dissatisfactory services. Analysis confirms structured spatiotemporal differentiation, with clear seasonal peaks for different CES and systematic variation across climate zones and regions. The identified typologies exhibit significant spatial clustering. This framework translates unstructured public perception into a scalable evidence chain, offering a practical tool for supporting differentiated park positioning, seasonal management strategies, and refined governance that explicitly incorporates cultural service values alongside ecological objectives.