184 Dale et al.: Forecasting the Effects of Heat and Pests on Urban Trees hours depending on the tree subsample. Because all sites have daily temperature data for August, the average August temperature was used for all analyses; 24 of the site temperatures were record- ed in August 2014, while the remaining 56 were recorded in August 2013. Due to loss of iButton data loggers for unknown reasons in the field, 80 of the 82 sites were used for temperature analyses. To determine M. tenebricosa abundance, research- ers pruned one randomly selected 0.3 m terminal twig from four cardinal directions of each tree using a pole pruner as described in Dale and Frank (2014a); Dale and Frank (2014b); Youngsteadt et al. (2014). In the laboratory, twigs were exam- ined under a dissecting microscope to count live M. tenebricosa adult females per 0.15 m of twig. Tree condition was rated as excellent, good, fair, or poor. Condition was assigned based on leaf condition, amount of branch dieback, cen- tral leader health, and other characteristics as described in Dale and Frank (2014a) and similar to Berrang et al. (1985). The City of Raleigh assigned condition ratings to most tree species listed in the inventory as they were assessed over the previous seven years. Within the data set, which was selected from this inventory, 39 A. rubrum had condition ratings assigned to them by the City of Raleigh Urban Forestry Division, 26 were assigned condition ratings as part of a previous study in 2013, and 17 did not have con- dition ratings, so they were omitted (final N for condition analyses = 65) (Dale and Frank 2014a). To determine the amount of impervious surface around each of the study trees, ArcMap (ArcGIS 10.2) was used to calculate the percent impervi- ous surface cover within given radii of each tree. Impervious surface cover was delineated at a 1 m resolution as described in Bigsby et al. (2013), and included buildings, pavement, and asphalt (e.g., parking lots, roads, and sidewalks). Using a shapefile of the study sites (N = 82), circular buf- fer regions were created around each tree at 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 80, 100, and 125 m radii (Figure 1b). Researchers calculated the total area (m2 ) within each buffer region that contained pixels scored as impervious in the raster image. Using the total area of impervious surface, the per- centage of the buffer region that was composed of impervious surface at each radius was calculated. ©2016 International Society of Arboriculture to meet assumptions of linear regression, as de- termined by inspecting plots of residuals. Simple logistic regression was used (JMP Pro 11) to de- termine how scale insect abundance or impervi- ous surface cover at each radius predicted tree condition. Using the probability formulas gener- ated from the logistic regression for each radius, researchers calculated the likelihood of a given tree condition across a range of 0% to 100% im- perious surface. To establish impervious surface cover thresholds, researchers calculated the av- erage percentage of impervious surface cover for all measured radii at which the most likely condi- tion changed from good to fair and fair to poor. Statistical Analyses Simple linear regression was used (JMP Pro 11) to determine the relationships between temperature, scale insect abundance, and impervious surface cover. Researchers log10 (x+1) transformed scale counts Impervious Surface Estimation The ‘Pace-to-Plant’ technique was developed to create a tool for on-the-ground application of the results. Aſter testing each measured radius from the tree as described previously, it was de- cided that a 20 m radius provided the best bal- ance of accuracy and practicality. A 20 m radius predicts significant effects of impervious surface on tree condition rating while also being short enough for someone to walk. Using this method, one can walk 25 steps (approximately 20 m) from the planting site in four directions at 45 degrees to the longest adjacent impervious edge, and estimate the percentage of impervious surface surround- ing it (Figure 2). Once each of four paths has been walked, the total number of steps onto impervi- ous surface is divided by the total number of steps taken (100) to give an estimate of the percent of impervious surface surrounding the planting site. To refine and test this technique, four hypo- thetical scenarios of urban planting sites were created (Figure 2). These scenarios do not encompass all possible site characteristics and may not conform to all urban planting regula- tions, but provided the necessary framework for technique development. Figure 2a, Figure 2b, Figure 2c, and Figure 2d illustrate street tree plantings in a median strip, three-way intersec- tion, four-way intersection, and a permeable
May 2016
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