186 RESULTS Field Measurements August average tree canopy temperatures ranged from 23.20°C to 26.96°C, with a mean (±SD) of 25.11 (±0.85). For all 82 study trees, M. tenebricosa abundance per 0.15 m of twig ranged from 0 to 2241 live individuals with a mean of 261.21 (±510.65). Melanaspis tenebri- cosa abundance increased with average Au- gust tree canopy temperature (simple linear regression, R2 = 0.29, P < 0.0001) (Figure 3b). Tree condition ratings included 6 excellent, 23 good, 22 fair, and 14 poor trees. Melanaspis tenebricosa abundance significantly predicted A. rubrum street tree condition (N = 65, χ2 = 33.41, P < 0.0001). As scale insect abundance increased, the probability of finding a tree in poor condi- tion significantly increased, while the probabil- ity of finding a tree in good condition decreased. Percent impervious surface cover was calcu- lated at 13 different radii for each study site. At the smallest radius (10 m), percent impervious sur- face ranged from 0% to 99.2%, while at the largest radius (125 m), percent impervious surface ranged from 3.8% to 72.7%. Percent impervious surface cover significantly predicted mean August tree canopy temperature at all radii (P < 0.01). Tree canopy temperature was best predicted at the 125 m radius (R2 = 0.22, P < 0.0001) (Figure 3a). For every percentage increase in impervious surface cover in the 125 m radius, tree canopy temperature increased by 0.02°C. Since M. tenebricosa abun- dance increased with temperature, and tempera- ture increased with impervious surface, researchers tested the relationship between M. tenebricosa abundance and percent impervious surface. It was found that, at all radii, as percent impervi- ous surface cover increased, mean M. tenebricosa abundance per 0.15 m of twig also increased (P < 0.01). Scale insect abundance was best predicted by percent impervious surface cover at a 60 m radius around the tree (R2 = 0.48, P < 0.0001) (Figure 3c). Given the relationships between impervious surface cover, M. tenebricosa abundance, and A. rubrum condition, researchers used impervi- ous surface to predict tree condition rating. At all measured radii, percent impervious surface cover significantly predicted the likelihood of ©2016 International Society of Arboriculture Figure 3. Simple linear regression of a) percent impervious surface (125 m radius) and tree canopy temperature, b) tree canopy temperature and M. tenebricosa abundance, and c) percent impervious surface cover (60 m radius) and M. tene- bricosa abundance. finding a tree in a given condition (N = 65, P < 0.01). All condition ratings were significantly pre- dicted from 40 to 125 m radii. Excellent, good, and poor condition ratings were significantly predicted from 15 to 35 m radii. Impervious surface cover at a 10 m radius only statistically predicts good and poor condition ratings. The best predictor of tree condition rating, based on goodness of from the study tree (χ2 fit indices, was at a 100 m radius = 29.87, P < 0.0001). For each model (10–125 m radius), the most likely condition rating for every percentage increase in impervious surface was determined. Dale et al.: Forecasting the Effects of Heat and Pests on Urban Trees
May 2016
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