Urban trees are often more sun- and wind-exposed than their forest-grown counterparts. These environmental differences can impact how many species grow–impacting trunk taper, crown spread, branch architecture, and other aspects of tree form. Given these differences, windthrow models derived from traditional forest production data sources may not be appropriate for urban forest management. Additionally, visual abnormalities historically labeled as “defects” in timber production, may not have a significant impact on tree failure potential. In this study, we look at urban tree failures associated with Hurricane Irma in Tampa, Florida, USA. We used spatial analysis to determine if patterns of failure existed among our inventoried trees. We also looked at risk assessment data to determine which visual defects were the most common and the most likely to be associated with branch or whole-tree failure. Results indicate that there was no spatial pattern associated with the observed tree failures–trees failed or withstood the storm as individuals. While some defects like decay and dead wood were associated with increased tree failure, other defects such as weak branch unions and poor branch architecture were less problematic.

Trees in residential landscapes provide many benefits, but can injure persons and damage property when they fail. In hurricane-prone regions like Florida, USA, the regular occurrence of hurricanes has provided an opportunity to assess factors that influence the likelihood of wind-induced tree failure and develop species failure profiles. We assessed open-grown trees in Naples, Florida, following the passage of Hurricane Irma in September 2017 to determine the effect of relevant factors on the degree of damage sustained by individual trees. Of 4034 assessed individuals (n = 15 species), 74% sustained no damage, 4% sustained only minor damage (i.e., minimal corrective pruning needed), 6% sustained significant damage (i.e., major corrective pruning needed), and 15% were whole-tree failures (i.e., overturned trees or trees requiring removal). The proportion of individuals in each damage category varied among species, stem diameter at 1.4 m above ground, and the presence of utility lines, which was a proxy for maintenance. We compared our results with the findings of seven previous hurricanes in the region to explore species’ resilience in hurricanes.

Practitioners who assess the risk associated with urban trees often factor in the presence or absence of visual tree defects when determining whether a tree may fail. Although these defects are a main fixture in many tree risk assessment systems and best-management practices, the research supporting their usefulness in predicting tree failure during storms is limited. When looking at past research involving populations of storm-damaged trees, several defects have never predicted failure (or have been associated with reduced rates of failure). In this study, we took a closer look at four such defects: codominant branches; branch unions with included bark; multiple stems originating from the same point; and overextended branches. After Hurricane Ian, we revisited 1518 risk-assessed trees where one of these four defects was identified as the primary condition of concern. Fourteen of these trees experienced branch failure during the storm (which hit the study area as a downgraded tropical storm). Upon closer inspection, none of these failures occurred at the defect of concern. Our findings indicate that none of the defects assessed appeared to increase the likelihood of tree failure in the species tested. Our results are in line with past research on these defects derived from post-storm assessments and analysis.

When professionals assess tree risk, they must consider the potential consequences associated with a branch or whole tree striking a person, vehicle, or structure. This process requires an assessor to determine the diameter and fall distance of a tree part and then gauge the likely damage to a target if failure occurred. The ability to accurately estimate diameter and fall distances is important, as direct measurements are not always possible. In this study, we examined whether differences exist between visual estimations and direction measurements of tree part diameters and fall distances among 106 arborists of differing experience levels. Our findings suggest arborists’ estimations were reasonably accurate in comparison to direct measurements. International Society of Arboriculture Certified Arborists and experienced arborists were more accurate in diameter estimations than arborists lacking assessment experience. In contrast, nonexperienced arborists were closer in their fall distance estimations than arborists with risk assessment experience.

Most tree risk assessment methods task the assessor with the evaluation of a tree’s likelihood of impact (i.e. likelihood a target is present during failure) when determining the probability that an adverse event will occur. While this is generally accomplished qualitatively based on visual cues; during the 15 to 20 minutes an assessor is at a location, site occupancy, a key component of likelihood of impact, is most accurately measured using traffic counters. The use of traffic counters reduces risk assessment bias and increases reproducibility, though commercially-available devices may be cost-prohibitive. This work addresses one potential barrier to traffic counter adoption through the creation of a low-cost vehicle and pedestrian counting system. The study compares the accuracy and consistency of our homemade traffic counting system to estimates derived from a commercially available system, as well as vehicle and pedestrian counts tallied with a hand clicker. Vehicle and pedestrian counts from the commercially available systems (p = 0.004 and p < 0.001, respectively) correlated well (r = 0.846 and r = 0.896, respectively) with the hand-tallied counts, but the homemade counters were not correlated with either. However, pedestrian counts from the homemade counter became inaccurate as afternoon temperatures went above 31.7°C.