Arboriculture & Urban Forestry 36(3): May 2010 Bacterial wetwood, cavities, and cracks produce inaccuracies in Picus data processing and may be interpreted as areas of decay (Schwarze and Heuser 2006; Wang et al. 2007; Schwarze 2008; Wang and Allison 2008; Wang et al. 2009). The position of decay within the trunk reduces the accuracy of decay assessment us- ing sonic or ultrasonic wave velocity (Deflorio et al. 2008; Lin et al. 2008; Wang et al. 2009), although recent advances in sig- nal processing and data interpretation may improve this problem (Socco et al. 2004). Lin et al. (2008) found that ultrasonic ve- locities decreased when the size of a manually created circular hole in a cross-section (simulating decay in a cross-section) in 30–35 cm cross-sections increased, but not always in a clear lin- ear relationship. Sections where a predrilled hole was 9–11 cm in diameter showed a blue area (denotes slowest sonic velocities), 11–21 cm diameter predrilled holes showed a green area (denotes third slowest sonic velocities), and predrilled holes more than 21 cm in diameter showed a violet area (denotes second slowest sonic velocities). Schubert et al. (2009) found that cavities greater than 5% of the cross-section of a tree trunk could be detected under laboratory conditions by sonic tomography, by converting a digital signal to analog, rather than using manually generated stress waves as with the Picus. Maurer et al. (2006) found that very low velocity areas are difficult to identify within areas where acoustic velocities are already decreased when using the Picus. The sound frequency of the trunk has also been used experi- mentally to assess Norway spruce wood decay (Axmon 2004). First the surface (circumferential) wave velocity is measured, and must be above a minimum level in order to allow for sources of error such as low moisture or decayed outer sapwood. The theoretical modal frequency is then calculated for a sound tree using the surface wave velocity. A significant deviation from the modal frequency would indicate decay or a defect in the stem. Currently, this technique requires as many sensors as the Picus or PUNDIT instruments, and it is not yet as accurate for detecting decay, but eventually only two or three sensors may be required, greatly reducing the time taken to measure an individual tree. CONCLUSION Assessing decay in tree trunks remains in its infancy and is problematic. Devices vary considerably in their invasiveness, reliability, ease of use, and interpretation. The variable mois- ture content of green and decayed wood may reduce the accu- racy of acoustic devices, constant feed drills, and conductiv- ity meters. Devices using electrical conductivity require a high level of specialized knowledge and experience in their use. Core sampling techniques are the most damaging to the xylem and rely heavily on the correct orientation of samples. Core sampling is portable and inexpensive. Constant feed drills and most conductivity meters are also invasive instruments, though less so than the core sampling techniques. Ultrasound and stress wave techniques can offer detailed information on the qual- ity of wood tested, but there may be difficulty in distinguish- ing between decayed wood and bacterial wetwood, or between decayed wood and cavities. Single pulse ultrasound and stress wave equipment is expensive and requires removing bark plugs. Tomographic technologies yield an accurate assessment of de- cay compared to core sampling, single sample conductivity and single pulse sonic devices. Tomography is less invasive than con- stant feed drills and core sampling devices, despite being less able 125 to indicate the location, and in some instances the quantity, of de- cay. Thermal imaging and radar tomography are completely non- invasive, but appear to be less accurate in calculating the quantity of decay. Sonic or ultrasonic tomography seems to offer a good balance between accuracy, invasiveness, and ease of use, but at high cost. Acknowledgments. We would like to thank the anonymous reviewers for their time, careful consideration, and editing of this article. LITERATURE CITED Axmon, J., M. Hansson, and L. Sörnmo. 2004. Experimental study on the possibility of detecting internal decay in standing Picea abies by blind impact response analysis. Forestry 77:179–192. Beall, F., and W. Wilcox. 1987. Relationship of acoustic emission during radial compression to mass loss from decay. Forest Products Journal 37:38–42. Bethge, K., C. Mattheck, and E. Hunger. 1996. Equipment for detec- tion and evaluation of incipient decay in trees. Arboricultural Journal 20:13–37. Blazé, K. 1992. Electronic assessment of tree condition. Scientific man- agement of Plants in the Urban Environment. editors, Moore, G., P. May, J. Hitchmough, J. Delpratt, P. Kenyon and P. Esdale, Con- ference Proceedings. Melbourne, Centre for Urban Horticulture. pp. 135–145. Bootle, K.R. 2005. Wood in Australia (2nd Edition). Sydney, McGraw- Hill. 452 pp. Bucur, V. 2003. Nondestructive Characterization and Imaging of Wood. Berlin, Springer-Verlag. 354 pp. Bucur, V. 2006a. Acoustics of Wood (2nd Edition). Berlin, Springer- Verlag. 393 pp. Bucur, V. 2006b. Urban Forest Acoustics. Berlin, Springer-Verlag. 181 pp. Bulleit, W. M., and R.H. Falk. 1985. Modeling stress wave passage times in wood utility poles. Wood Science and Technology 19:183–191. Catena, A. 2003. Thermography reveals hidden tree decay. Arboricultural Journal 27:27–42. Catena, A., and G. Catena. 2008. Overview of thermal imaging for tree assessment. Arboricultural Journal 30:259–270. Costello, L., and S. Quarles. 1999. Detection of wood decay in blue gum and elm: an evaluation of the IML-Resistograph and the portable drill. Journal of Arboriculture 25:311–317. Deflorio, G., S. Fink, and F.W.M.R. Schwarze. 2008. Detection of incipi- ent decay in tree stems with sonic tomography after wounding and fungal infection. Wood Science Technology 42:117–132. Dolwin, J.A., D. Lonsdale, and J. Barnett. 1999. Detection of decay in trees. Arboricultural Journal 23:139–149. Downes, G.M., I.L. Hudson, C.A. Raymond, G.H Dean, A.J. Michell, L.R. Schimleck, R. Evans, and A. Muneri. 1997. Sampling Plantation Eucalypts for Wood and Fibre Properties. Canberra, CSIRO Publish- ing. 132 pp. Giancoli, D.C. 2005. Physics. Principles with Applications (6th Edition). New Jersey, Pearson Prentice Hall. 1004 pp. Gilbert, E., and E. Smiley. 2004. Picus sonic tomography for the quan- tification of decay in white oak (Quercus alba) and hickory (Carya spp.). Journal of Arboriculture 30:277–281. al Hagrey, S. 2007. Geophysical imaging of root-zone, trunk, and mois- ture heterogeneity. Journal of Experimental Botany 58:839–854. Harris, R.W. 1992. Arboriculture. Integrated Management of Landscape Trees, Shrubs, and Vines (2nd Edition). New Jersey, Prentice Hall. 674 pp. ©2010 International Society of Arboriculture
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