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.

Trails are important recreation settings; determining an appropriate trail usage amount to avoid unacceptable ecological impacts is important for protected areas. However, there is a lack of studies examining trail usage’s direct and indirect relationships and the influence of landscape-level conditions to evaluate ecological carrying capacity. This study integrated a path analysis model and stakeholder assessment to estimate the ecological carrying capacity of trails in a protected area. This study surveyed the biophysical environment along the trails and conducted a path analysis to establish the use–impact model for the trails in the study area. Based on the use–impact model, this study developed four-level usage scenarios and collected the stakeholders’ acceptance evaluation to determine the ecological carrying capacity range. The results showed that the weekly usage of the trails directly affected the soil hardness and plant coverage of the trail. The trail’s soil hardness directly affected the surrounding soil hardness, decreasing its plant coverage, while the vegetation type and slope also affected its plant cover. The stakeholders of the Mt. Xiaoguanyin Area reached a consensus on the ecological carrying capacity range, which was 288 to 404 total weekly hikers. The study results revealed the effect paths of the landscape-level conditions and usage impacts and provided managers with an implementable ecological carrying capacity. The estimation framework could be a reference for determining ecological carrying capacity in other protected areas.

This study conducted field measurements to explore the effects of street spatial structure on micrometeorological condition and air quality on both hot and cool days in Taipei City. Six street canyons with an aspect ratio of one, but varied in street orientation, street width, sky view factor, and number of planting strips, were selected for observations. In this case study, it was observed that, as well as the meso-scale phenomena, the local and micro-scale (street canyon structure) had influences on street air temperature, mean radiant temperature, and wind velocity. However, the local and micro-scales only had minor effects on relative humidity for both hot and cool days. Shade effect on temperature by street trees was observed; this effect could cause 2 degrees drop on mean radiant temperature and about 0.5 degree drop on air temperature. Our analyses and field measurements also revealed that, in some cases, concentrations of PM_2.5 and PM₁₀ were found to be correlated with local street canopy structure; however, in some cases, the meso-scale process was found to be the dominant factor. We also found that concentrations of CO and O₃ were inversely correlated in the street canyon. The findings of this study provide introductory scientific data and guidelines for urban street designers to improve thermal comfort and air quality.