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应用生态学报 ›› 2024, Vol. 35 ›› Issue (12): 3275-3284.doi: 10.13287/j.1001-9332.202412.024

• 生态系统服务与区域可持续专栏(专栏策划:孙晓、冯喆、陶宇、李春林、林锦耀) • 上一篇    下一篇

武夷山国家公园(福建区域)生态系统文化服务簇识别及影响因素

高扬仪, 朱里莹*, 庄迎鑫, 张丽甜, 严敏珑, 郭铭煌, 龚晓玲, 廖凌云   

  1. 福建农林大学风景园林与艺术学院, 福州 350100
  • 收稿日期:2024-07-04 接受日期:2024-10-07 出版日期:2024-12-18 发布日期:2025-06-18
  • 通讯作者: *E-mail: fjndzly@126.com
  • 作者简介:高扬仪, 女, 2001年生, 硕士研究生。主要从事园林与景观设计研究。E-mail: 979550408@qq.com
  • 基金资助:
    国家自然科学基金项目(32401461)、福建省891号科技专项(115-KLY23110XA)和福建农林大学专项(XJQ2021S2)

Identification and influencing factors of cultural ecosystem service bundle in Wuyishan National Park (Fujian region), Southeast China

GAO Yangyi, ZHU Liying*, ZHUANG Yingxin, ZHANG Litian, YAN Minlong, GUO Minghuang, GONG Xiaoling, LIAO Lingyun   

  1. College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350100, China
  • Received:2024-07-04 Accepted:2024-10-07 Online:2024-12-18 Published:2025-06-18

摘要: 厘清不同类型生态系统文化服务(CES)在空间上的潜在关联特征,并探索其驱动机制是有效管理空间资源的先决条件。然而,CES量化和空间化一直是CES研究的难点。本研究以武夷山国家公园(福建区域)为例,构建PPGIS-MaxEnt-SOM模型,借助公众参与式地理信息系统识别并量化CES点位,利用最大熵模型将点状数据拓展为面状分区,通过自组织特征映射网络实现多类型CES组合的生态系统文化服务簇(CESB)识别,并探究其影响因素。结果表明: 研究区6类CES(美学、文化与教育、娱乐、康养、灵感、地方认同感服务)主要分布在东部景区,零星分布于中西部;CES热点区与东部景区游览路线上的游憩资源位置相似,呈一带二核的分布格局;CESB可划分为美学-康养服务簇、娱乐-美学服务簇、文化-灵感服务簇和多功能服务簇4类,呈现以多功能服务簇为中心向外分类发散的空间格局;景亭、水域景点等自然因素是影响美学、娱乐、地方认同感服务以及美学-康养服务簇、娱乐-美学服务簇和多功能服务簇的关键因素,而康养、灵感、文化与教育服务以及文化-灵感服务簇主要受历史文化遗址、距道路距离等因素的影响。PPGIS-MaxEnt-SOM模型可以将CES映射于地理空间,实现CESB的空间化识别,为量化CES空间问题提供新的视角和方法。

关键词: 生态系统文化服务, 服务簇, 影响因素, 武夷山国家公园

Abstract: Clarifying the potential spatial correlation characteristics of different cultural ecosystem service (CES) types and their influencing factors is a prerequisite for effective management of spatial resources. However, the quantification and spatialization of CES are great challenges in CES research. Taking Wuyishan National Park (Fujian region) as an example, we constructed a PPGIS-MaxEnt-SOM model to identify and quantify CES points with the assistance of a public participation geographic information system, expanded the point data into area partitions by using the maximum entropy modeling and realized the identification of a cultural ecosystem service bundle (CESB) with multi-type CES combinations through a self-organizing feature map network, and explored the influencing factors of these CES and CESB. The results showed that the six types of CES (aesthetic, cultural and educational, entertainment, health, inspiration, and local identity services) were mainly distributed in the eastern scenic spots and sporadically distributed in the central and western regions. The location of recreation resources in the CES hotspot area was similar to that on the tour route of the eastern scenic spots, showing a distribution pattern of one belt and two cores. CESB could be divided into four types: aesthetic-health service bundle, entertainment-aesthetic service bundle, culture-inspiration service bundle, and multi-functional service bundle, which presented the spatial pattern of outward classification and divergence with multi-functional service bundle as the center. Natural factors such as landscape pavilion and water attraction were the key factors influencing aesthetic service, entertainment service, local identity service, aesthetic-health services bundle, entertainment-aesthetic service bundle, and multi-functional service bundle. Health service, inspiration service, cultural and educational service, and culture-inspiration service bundle were mainly affected by factors such as historical and cultural sites, and distance from road. Overall, the PPGIS-MaxEnt-SOM model can map CES geospatially to realize the spatial identification of CESB and provide a new perspective and method for quantifying CES spatial problems.

Key words: cultural ecosystem service, service bundle, influencing factor, Wuyishan National Park