Predictors of tropical cyclone-induced urban tree failure: an international scoping review - Salisbury, Allyson B.; Koeser, Andrew K.; Andreu, Michael G.; Chen, Yujuan; Freeman, Zachary; Miesbauer, Jason W.; Herrera-Montes, Adriana; Kua, Chai-Shian; Nukina, Ryo Higashiguchi; Rockwell, Cara A.; Shibata, Shozo; Thorn, Hunter; et al. (Frontiers in Forests and Global Change, 2023)
Background Trees are critical components of rural and urban ecosystems throughout the world. While they have adapted to the historic conditions of their native environments, climate change, urbanization, and human-assisted range expansion may test the storm resiliency of many tree species. Objective In this global multilingual scoping review, we investigate a range of intrinsic (i.e., tree characteristics) and external (i.e., environmental and management) factors which have been used to predict tree failure during tropical cyclones. Design We searched online databases and journals in English, Chinese, French, Japanese, Portuguese, and Spanish to find peer-reviewed papers and dissertations. We retained papers that used ground-based methods to study tree damage following a tropical cyclone and conducted a statistical analysis of factors that influence tree resistance to damage. From each paper we extracted details of study methods, and the relationships between damage and predictors. Results Our efforts generated 65 peer-reviewed papers and dissertations that met our final criteria for inclusion (i.e., data on the relative proportion of trees failed/intact as assessed no more than a year after the storm event). Of these papers 37 independent variables were assessed to predict tree failure. Research in both urban and rural settings tends to be concentrated in regions frequently impacted by tropical cyclones. Characteristics of species such as wood density have been studied in rural environments and are also relevant predictors for tree failure in urban trees. Environmental characteristics unique to urban settings such as planting areas surrounded by pavement need further research. Several urban studies demonstrate that risk assessment methods can predict tree failure during a storm. Conclusion Results can be used by future storm researchers to identify both predictors may warrant inclusion in their models as well as predictors which have yet to be tested. Results can also inform planning and activities that can mitigate tropical cyclone damage to the urban forest.