Agricultural Economics and Rural Policy Group, Wageningen University and Research, Wageningen, The Netherlands.
Inholland University of Applied Sciences, Domain Agri, Food and Life Sciences, Delft, The Netherlands.
PLoS One. 2021 Feb 16;16(2):e0246805. doi: 10.1371/journal.pone.0246805. eCollection 2021.
Recent research has indicated an increase in the likelihood and impact of tree failure. The potential for trees to fail relates to various biomechanical and physical factors. Strikingly, there seems to be an absence of tree risk assessment methods supported by observations, despite an increasing availability of variables and parameters measured by scientists, arborists and practitioners. Current urban tree risk assessments vary due to differences in experience, training, and personal opinions of assessors. This stresses the need for a more objective method to assess the hazardousness of urban trees. The aim of this study is to provide an overview of factors that influence tree failure including stem failure, root failure and branch failure. A systematic literature review according to the PRISMA guidelines has been performed in databases, supported by backward referencing: 161 articles were reviewed revealing 142 different factors which influenced tree failure. A meta-analysis of effect sizes and p-values was executed on those factors which were associated directly with any type of tree failure. Bayes Factor was calculated to assess the likelihood that the selected factors appear in case of tree failure. Publication bias was analysed visually by funnel plots and results by regression tests. The results provide evidence that the factors Height and Stem weight positively relate to stem failure, followed by Age, DBH, DBH squared times H, and Cubed DBH (DBH3) and Tree weight. Stem weight and Tree weight were found to relate positively to root failure. For branch failure no relating factors were found. We recommend that arborists collect further data on these factors. From this review it can further be concluded that there is no commonly shared understanding, model or function available that considers all factors which can explain the different types of tree failure. This complicates risk estimations that include the failure potential of urban trees.
最近的研究表明，树木故障的可能性和影响都在增加。树木故障的潜在因素与各种生物力学和物理因素有关。引人注目的是，尽管科学家、树木学家和从业者可以测量越来越多的变量和参数，但似乎缺乏基于观察的树木风险评估方法。由于评估员的经验、培训和个人意见的差异，目前的城市树木风险评估各不相同。这强调了需要一种更客观的方法来评估城市树木的危险性。本研究旨在提供一个影响树木故障的因素概述，包括树干故障、根系故障和树枝故障。根据 PRISMA 指南在数据库中进行了系统的文献回顾，并通过回溯引用进行了支持：共回顾了 161 篇文章，揭示了 142 个不同的因素影响树木故障。对与任何类型的树木故障直接相关的因素进行了效应大小和 p 值的元分析。贝叶斯因子用于评估所选因素在树木故障情况下出现的可能性。通过漏斗图和回归测试分析了发表偏倚。结果表明，高度和树干重量等因素与树干故障呈正相关，其次是年龄、胸径、胸径平方乘以高度和立方胸径（DBH3）和树干重量。树干重量和树干重量与根系故障呈正相关。对于树枝故障，没有发现相关因素。我们建议树木学家收集这些因素的进一步数据。从这项研究可以进一步得出结论，没有一个通用的共识、模型或功能可以考虑所有可以解释不同类型树木故障的因素。这使得包括城市树木故障潜力在内的风险估计变得复杂。
