Arboriculture & Urban Forestry 48(4): July 2022 rugged ROW locations and by the time constraints that are necessary to inspect the many miles of lines that need to be assessed on a rotational basis (Good- fellow 2020). Remote sensing, change-detection techniques, predictive mechanistic models, and more advanced statistical techniques may be able to pro- vide us with a broader view of the utility forest and a more complete set of tools to manage the risks asso- ciated with it. Even while the study of the likelihood of failure of trees remains a hot topic within the arboricultural world, wise management practices should recognize that the vast majority of trees will stand throughout the duration of a human lifetime, and that once cut, a tree may take many years to replace. With regards to UVM this means understanding that many of the trees that stand along ROWs are healthy and do not pose elevated risk by themselves, as it is the combina- tion of the likelihood of failure with the likelihood of impact and the consequences of failure which ulti- mately comprise risk. For example, of the 1,259 trees surveyed by Kane (2008), only 12.8% experienced failure. Put another way, 87.2% of trees survived. Electric utilities, their customers, and the vegeta- tion management industry all stand to benefit from a greater number of more varied and targeted approaches to tree-risk identification. As such, new techniques and technologies should be assessed, validated, and, when applicable, utilized by vegetation managers, for these methods may allow for some combination of decreased expenditure of financial resources, decreased vegetation-related outages, and increased safety of utility arborists, foresters, and the communities ser- viced, all the while leaving more trees standing and healthy. LITERATURE CITED Achim A, Wellpott A, Gardiner B. 2007. Competition indices as a measure of wind loading on individual trees. “Wind and Trees” Conference; 2007 August 5–9; Vancouver, Canada. Vancouver (Canada): University of British Columbia. https:// www.researchgate.net/publication/266886250_Competition _indices_as_a_measure_of_wind_loading_on_individual_ trees_Competition_indices_as_a_measure_of_wind_loading _on_individual_trees Ancelin P, Courbaud B, Fourcaud T. 2004. Development of an individual tree-based mechanical model to predict wind dam- age within forest stands. Forest Ecology and Management. 203(1-3):101-121. https://doi.org/10.1016/j.foreco.2004.07.067 Appelt PJ, Goodfellow JW. 2004. Research on how trees cause interruptions—Applications to vegetation management. In: Rural electric power conference, 2004. 48th Annual Confer- ence; 2004 May 25; Scottsdale, AZ, USA. Piscataway (NJ, 253 USA): Institute of Electrical and Electronics Engineers, Inc. p. C6-1. https://doi.org/10.1109/REPCON.2004.1307064 Asner GP, Goldstein G. 1997. Correlating stem biomechanical properties of Hawaiian canopy trees with hurricane wind damage. Biotropica. 29(2):145-150. https://doi.org/10.1111/j .1744-7429.1997.tb00018.x Baker CJ. 1995. The development of a theoretical model for the windthrow of plants. Journal of Theoretical Biology. 175(3): 355-372. https://doi.org/10.1006/jtbi.1995.0147 Bodig J, Jayne BA. 1982. Mechanics of wood and wood compos- ites. New York (NY, USA): Van Nostrand Reinhold Company. 736 p. Burgert I. 2006. Exploring the micromechanical design of plant cell walls. American Journal of Botany. 93(1):1391-1401. https://doi.org/10.3732/ajb.93.10.1391 Canham CD, Loucks OL. 1984. Catastrophic windthrow in the presettlement forests of Wisconsin. Ecology. 65(3):803-809. https://doi.org/10.2307/1938053 Ciftci C, Arwade SR, Kane B, Brena SF. 2014a. Analysis of the probability of failure for open-grown trees during windstorms. Probabilistic Engineering Mechanics. 37:41-50. https://doi .org/10.1016/j.probengmech.2014.04.002 Ciftci C, Kane B, Brena SF, Arwade SR. 2014b. Loss in moment capacity of tree stems induced by decay. Trees. 28:517-529. https://doi.org/10.1007/s00468-013-0968-8 Clair B, Fournier M, Prevost MF, Beauchene J, Bardet S. 2003. Biomechanics of buttressed trees: Bending strains and stresses. American Journal of Botany. 90(9):1349-1356. https://doi.org/ 10.3732/ajb.90.9.1349 Clough RW, Penzien J. 1993. Dynamics of structures. New York (NY, USA): McGraw-Hill. 738 p. Crook MJ, Ennos AR. 1996. The anchorage mechanics of deep rooted larch, Larix europea × L. japonica. Journal of Experi- mental Botany. 47(10):1509-1517. https://doi.org/10.1093/ jxb/47.10.1509 Cullen S. 2002. Trees and wind: Wind scales and speeds. Journal of Arboriculture. 28(5):237-242. https://doi.org/10.48044/ jauf.2002.036 Dahle G, Grabosky J, Kane B, Miesbauer J, Peterson W, Telewski FW, Koeser A, Watson GW. 2014. Tree biome- chanics: A white paper from the 2010 international meeting and research summit at The Morton Arboretum (Lisle, Illinois, U.S.). Arboriculture & Urban Forestry. 40(6):309-318. https:// doi.org/10.48044/jauf.2014.029 Dahle GA, Grabosky JC. 2010. Variation in modulus of elasticity (E) along Acer platanoides L. (Aceraceae) branches. Urban Forestry & Urban Greening. 9(3):227-233. Dahle GA, Holt HH, Chaney WR, Whalen TM, Cassens DL, Gazo R, McKenzie RL. 2006. Branch strength loss implica- tions for silver maple (Acer saccharinum) converted from round-over to V-trim. Arboriculture & Urban Forestry. 32(4):148-154. https://doi.org/10.48044/jauf.2006.020 Dahle GA, James KR, Kane B, Grabosky JC, Detter A. 2017. A review of factors that affect the static load-bearing capacity of urban trees. Arboriculture & Urban Forestry. 43(3):89-106. https://doi.org/10.48044/jauf.2017.009 de Langre E. 2008. Effects of wind on plants. Annual Review of Fluid Mechanics. 40:141-168. https://doi.org/10.1146/ annurev.fluid.40.111406.102135 ©2022 International Society of Arboriculture
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