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

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.