Arboriculture & Urban Forestry 38(6): November 2012 niques failed to show any reliable connection between the statisti- cal representations of surface temperature (mean, standard devia- tion, skewness, deviation from linear trend) and internal defects. Although one significant correlation was discovered between the amount of discoloration and surface temperature variability, simi- lar results were not obtained for more severe defect categories. For the range of internal defects encountered in this study, the IR camera diagnostic technique was unable to identify such cases distributed throughout the evaluated specimens. The larg- est defect encountered was a termite-induced cavity occupying, at one position, 21.8% stem cross-sectional area. The absence of defects measuring at least 76% stem cross-sectional area could be one explanation for the negative results obtained, as defects smaller than this have not been shown to produce a measureable temperature change (Burcham et al. 2012). Although the de- fects affecting these trees did not necessarily render individual specimens hazardous based on published criteria (Smiley and Fraedrich 1992; Kane and Ryan 2004), the defects were suffi- ciently large to serve as a calibration test for this diagnostic de- vice. Based on existing literature, comparatively sized internal defects are detectable with a range of professional diagnostic tools, including resistance recording drills (Johnstone et al. 2007) and acoustic tomography devices (Gilbert and Smiley 2004). CONCLUSION This study demonstrated the difficulty encountered when inter- preting and analyzing surface temperature measurements to as- sess internal stem condition. Surface temperature distributions displayed in the IR images of the 48 trees did not demonstrate a relationship with internal condition when analyzed using a mixed-methods approach. These results are practically important for the arboriculture professional community because they show the technique does not provide accurate results about the internal condition of trees containing decay and termite-induced cavita- tion up to and including the size of those encountered in this study (21.8% relative defect CSA). However, there was substantial evi- dence that surface temperature anomalies are regularly associated with damaged external stem tissue, and the camera may be use- ful in detecting cankers, detached bark, or mechanical damage. LITERATURE CITED Bellett-Travers, M., and S. Morris. 2010. The relationship between sur- face temperature and radial wood thickness of twelve trees harvested in Nottinghamshire. Arboricultural Journal 33:15–26. Bo, M.W., J. Chu, and V. Choa. 2005. The Changi east reclamation proj- ect in Singapore. In: B. Indraratna, J. Chu, and J.A. Hudson (Eds.). Ground Improvement: Case Histories. Elsevier, Oxford, UK. Burcham, D.C., E.C. Leong, and Y.K. Fong. 2012. Passive infrared cam- era measurements demonstrate modest effect of mechanically in- duced internal voids on Dracaena fragrans stem temperature. Urban Forestry & Urban Greening doi:10.1016/j.ufug.2012.01.001 Burcham, D.C., S. Ghosh, E.C. Leong, and Y.K. Fong. 2011. Evaluation of an infrared camera technique for detecting mechanically induced internal voids in Syzygium grande. Arboriculture & Urban Forestry 37(3):93–98. Cartwright, K.S.G., and W.P.K. Findlay. 1958. Decay of timber and its prevention. HM Stationery Office, London. 332 pp. Catena, A. 2003. Thermography reveals hidden tree decay. Arboricultural Journal 27:27–42. 285 Catena, A., and G. Catena. 2008. Overview of thermal imaging for tree assessment. Arboricultural Journal 30:259–270. Catena, G., L. Palla, and M. Catalano. 1990. Thermal infrared detection of cavities in trees. European Journal of Forest Pathology 20:201–210. Costello, L.R., and S.L. Quarles. 1999. Detection of wood decay in blue gum and elm: An evaluation of the Resistograph® drill. Journal of Arboriculture 25(6):311–318. and the portable Dahle, G.A., and J.C. Grabosky. 2010. Variation in modulus of elasticity (E) along Acer platanoides L. (Aceraceae) branches. Urban Forestry & Urban Greening 9(3):227–233. Derby, R.W., and D.M. Gates. 1966. The temperature of tree trunks – calculated and observed. American Journal of Botany 53(6):580–587. Ellison, M.J. 2005. Quantified tree risk assessment used in the manage- ment of amenity trees. Journal of Arboriculture 31(2):57–65. Fisher, J.B., and J.W. Stevenson. 1981. Occurrence of reaction wood in branches of dicotyledons and its role in tree architecture. Botanical Gazette 142(1):82–93. Gilbert, E.A., and E.T. Smiley. 2004. Picus sonic tomography for the quantification of decay in white oak (Quercus alba) and hickory (Carya spp.). Journal of Arboriculture 30(5):277–281. Harris, R.W., J.R. Clark, and N.P. Matheny. 2003. Arboriculture: Inte- grated management of landscape trees, shrubs, and vines (4th Edi- tion). Prentice Hall, Englewood Cliffs, New Jersey, U.S. 592 pp. Hickman, G., E. Perry, and R. Evans. 1995. Validation of a tree failure evaluation system. Journal of Arboriculture 21(5):23–34. Hickman, G., J. Caprille, and E. Perry. 1989. Oak tree hazard evaluation. Journal of Arboriculture 15(8):177–184. IBM, Corp., 2010. IBM® SPSS® Statistics Version 19.0. International Business Machines Corp., NewYork, New York, U.S. James, K.R., N. Haritos, and P.K. Ades. 2006. Mechanical stability of trees under dynamic loads. American Journal of Botany 93(10):1522–1530. Johnstone, D.M., G. Moore, M. Tausz, and M. Nicolas. 2010. The mea- surement of wood decay in landscape trees. Arboriculture & Urban Forestry 36(3):121–127. Johnstone, D.M., P.K. Ades, G.M. Moore, and I.W. Smith. 2007. Predict- ing wood decay in eucalypts using an expert system and the IML- Resistograph drill. Arboriculture & Urban Forestry 33(2):76–82. Kane, B.C.P., and H.D.P. Ryan III. 2004. The accuracy of formulas used to assess strength loss due to decay in trees. Journal of Arboriculture 30(6):347–356. Kersten, W., and F.W.M.R. Schwarze. 2005. Development of decay in the sapwood of trees wounded by the use of decay detecting devices. Arboricultural Journal 28:165–181. Larsson, B., B. Bengtsson, and M. Gustafsson. 2004. Nondestructive de- tection of decay in living trees. Tree Physiology 24:853–858. Matheny, N.P., and J.R. Clark. 1994. A photographic guide to the evalua- tion of hazard trees in urban areas (2nd Edition). International Society of Arboriculture, Urbana. 85 pp. Mattheck, C., and H. Breloer. 1994. The body language of trees: A hand- book for failure analysis. The Stationery Office, London. 320 pp. Nicolotti, G., P. Gonthier, F. Guglielmo, and M.M. Garbelotto. 2009. A biomolecular method for the detection of wood decay fungi: A focus on tree stability assessment. Arboriculture & Urban Forestry 35(1):14–19. Ouis, D. 2003. Non-destructive techniques for detecting decay in stand- ing trees. Arboricultural Journal 27:159–177. Potter, B.E., and J.A. Andresen. 2002. A finite-difference model of tem- peratures and heat flow within a tree stem. Canadian Journal of Forest Research 32:548–555. ©2012 International Society of Arboriculture
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