Detecting the Spatial Matching Relationship between Supply-Side and Demand-Side of Recreation Ecosystem Services (RES) from the Perspectives of Resource, Management, and Beneficiary: A Case Study in Yangmingshan National Park

Abstract

Recreation ecosystem services (RES) link closely to human well-being and might mutually benefit biodiversity conservation while well managed. However, assessing and detecting the spatial matching of RES remains challenging. This study considered the nature of RES supply-side and demand-side in assessing and detecting the spatial matching relationship from the resource, management, and beneficiary perspectives. The proposed method consisted of assessment and overlay analysis parts. RES Supply Potential and Recreation Accessibility were assessed from the resource and management perspectives. RES Demand Potential, RES Flow, and RES Match/Mismatch were assessed from the beneficiary perspective. An overlay analysis was then conducted to examine the spatial relationship between the RES Match/Mismatch and the resource supply and management status to provide specific management information for protected areas. For the Yangmingshan National Park (YNP) in Taiwan, as a case study, this study revealed four RES Match/Mismatch levels in YNP, including MM+2 (RES Demand Potential ≫ RES Flow), MM+1 (RES Demand Potential > RES Flow), M (RES Demand Potential ≈ RES Flow), and MM−1 (RES demand Potential < RES flow). Only 5.51% of YNP belonged to M, where the areas’ RES Demand Potential were close to RES Flow and mainly located in Zone SA (Scenic Area). MM−1, where the areas were over-visited, accounted for 7.12% and were mainly located in Zones SA and EUA (Existing Use Area). As a protected area, most areas of YNP were with high RES Supply Potential; and were mainly located in MM+2 (70.87%) and MM+1 (16.50%), where the areas’ RES Demand Potential much greater or greater than RES Flow and the Recreation Accessibility were low. MM−1 were the areas where the managers should first launch actions to avoid or minimize over-visited impacts. The proposed method could detect RES Match/Mismatch rationally and directly and obtain multiple spatial datasets to support decision-making.