Arboriculture & Urban Forestry 38(6): November 2012 283 internal defects. The average deviation from the linear trend was relatively small (mean = 0.2°C) near internal defects for all trees in the experiment. In contrast, a large deviation (mean = 1.5°C) consistently occurred near the external marking tape used to mark forest specimens as experimental trees. Overall, the size of the internal defects, represented by relative defect CSA, was weakly correlated (r2 = 0.018) with the localized deviation from the lin- ear trend. The scatterplot displaying these two variables did not display clear linear relationships or grouping among the plotted points. The qualitatively categorized data similarly did not reveal significant relationships between the two variables (Figure 8d). DISCUSSION The frequency of discoloration, decay, and cavitation among the sampled Casuarina equisetifolia specimens is broadly congru- ent with similar reports of fungal infections and termite infes- tations in tree populations. Sudin et al. (1992) found 35.5% of six- to nine-year-old Acacia mangium (Leguminosae) specimens contained heart rot wood decay lesions and 4% contained ter- mite infestations in commercial forestry plantations near Sabah, Malaysia. In this study, 27% of sampled trees were decayed and 6% contained termite infestations, and the existing reports, cou- pled with these findings, generally indicate that a considerable fraction of individuals among a species in natural and managed forests suffer wood decay infections and termite infestations. The majority of trees sampled were exclusively discolored. Al- though a theory of succession has been postulated in which wood- inhabiting fungi and bacteria modify discolored wood to create an amenable substrate for wood decay fungi (Shigo 1972), the in- dependent ability of wood decay fungi to degrade wood has since been illustrated (Rayner and Boddy 1988). As there is no evidence that discolored trees will inevitably become decayed, their iden- tification during tree risk assessment is relatively unimportant. Visual observation of IR images consistently showed the Figure 7. The two histograms, representing surface temperature distributions extracted from the trunk surface of trees “I” and “N,” do not exhibit strong visual similarity, in spite of comparable in- ternal cavity sizes. grams displaying surface temperature distributions for trees with comparable defects were often visually dissimilar (Figure 7). The size of the internal stem defects, represented by relative de- fect CSA (%), was weakly correlated (r2 = 0.001- 0.022) with the three evaluated statistical representations of surface temperature extracted from rectangular transects. Scatterplots displaying the extent of internal defects and surface temperature mean, standard deviation, and skewness did not exhibit clear linear relationships or grouping among the plotted points (Figure 8a–d). After group- ing the cases into three categories of similar defects, a significant but weak positive correlation (r2 = 0.096, P-value = 0.011, d.f. = 66) was discovered between relative defect CSA and the standard deviation for the discolored and undamaged stem segments (Fig- ure 8b). Among the remaining defect categories, linear correla- tion analyses of the relationship between internal defect CSA (%) and statistical representations of surface temperature (i.e., mean, standard deviation, skewness) did not yield significant results. Vertical temperature plots for individual trees displayed spo- radic localized temperature irregularities often disassociated with close association between temperature anomalies and external trunk features, suggesting that trunk surface temperature dis- tributions are mostly products of external thermodynamic pro- cesses whose magnitude is affected, in turn, by such features as irregular stem geometry, cankers, bark damage, wounds, and surface cracks. Derby and Gates (1966), as well as Potter and Andresen (2002), attempted to model tree trunk temperature by characterizing the conditional input parameters affecting three external (convective heat exchange, solar radiative heating, in- frared radiative exchange) and one internal (thermal conductiv- ity) thermodynamic process. Their model simulations of trunk temperature distributions acknowledged the relative importance of the external environment over internal stem conditions in its theoretical design. Within this framework, changes in conductiv- ity resulting from internal defects may affect surface tempera- tures, but they must compete with the rate and magnitude of temperature changes caused by the remaining thermodynamic processes at the surface. Presumably, the contributions of the ex- ternal processes toward surface temperature distributions could be held constant or removed to selectively evaluate anomalies resulting from defect-related changes in thermal conductivity using these models, but they would require substantial compu- tative improvement to accurately predict quantitative tempera- ture changes across space and time (Potter and Andresen 2002). Without the ability to isolate the irrelevant contributions of these ©2012 International Society of Arboriculture
November 2012
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