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标题：Estimating Pruning-Caused Loss on Ecosystem Services of Air Pollution Removal and Runoff Avoidance
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作者：Shuo Wei ; Su-Ting Cheng
期刊名称：Sustainability
印刷版ISSN：2071-1050
出版年度：2022
卷号：14
期号：11
页码：6637
DOI：10.3390/su14116637
语种：English
出版社：MDPI, Open Access Journal
摘要：Trees provide multiple ecosystem services (ES) and are generally considered an important natural-based approach for climate change adaptation and mitigation. In urban areas, proper pruning practices can help enhance ES provided by trees, but in areas with issues of typhoons or storms, routinely intensive pruning may reduce ES. Therefore, it is critical to determine proper pruning intensity in balancing the ES provision and life/property protection. With the aim of promoting sustainable urban forestry management, we applied the i-Tree Eco to quantify ES and ES values of air pollution removal and runoff avoidance provided by a total of 87,014 Taipei street trees and developed an analytical method to estimate the potential loss caused by different pruning intensities. Based on the i-Tree Eco estimates, the Taipei street trees on average provide ES values of air pollution removal and runoff avoidance at $2.31 and $1.87 USD/tree/y, respectively. By changing the ratio of crown missing as a surrogate for different pruning intensities, we found that with a less than 25% pruning intensity, the decline ratio of ES values was relatively constant, and the potential loss was estimated at $0.47 USD/tree/y at the 25% pruning intensity. As such, in general maintenance situations, we recommend a less than 25% pruning intensity. However, during typhoon or monsoon seasons, a less than 45% pruning intensity is suggested to balance the ES provision and public safety with an estimated loss at $0.96 USD/tree/y. We also suggest creating visualization maps incorporating the potential ES and the local in situ environmental and tree conditions at a community level to support decision making for a more comprehensive management plan. Based on the framework and method developed in this study, the science-based information can be used to assist maintenance practices and highlight the potential ES values to be enhanced by choosing proper pruning intensity for a more sustainable future.