Arboriculture & Urban Forestry 33(2): March 2007 77 Table 1. Summary of the advantages and disadvantages of devices that measure wood decay. Type of device Ease of X-ray diffraction Thermal and microwave Imaging neutron imaging Transmission acoustic devices Constant feed drills Compression meters Electrical conductivity Breaking core samples Computerized tomography interpreting results Relative cost High1 High1 Imaging nuclear magnetic resonance High1 High1 Moderate5–7 High8,10–12,24 Moderate10,14,15 Moderate8,10,18 Low22,26 High1,23,25 High1 High1 Very high1 Very high1 Low7 Low11 Low11 Low19 Low22 High1 Reliability in Eucalypts High2 Probably high1 Probably high1 Probably high1 Unknown Probably high24 Moderate16,17 Low20 Unsuitable3,22,26 Probably high1,20,23,25 Invasiveness in Eucalypts High3 Low1 Low1 Low1 Moderate7,8 Moderate12,13 Moderate15 Moderate8,10 High22 Low1,23,25 Portability Low1,2,4 Low1 Low1 Low1 High5,7–9 High8,10–12 High10,15 High8,10,21 High22 High23,25 References: 1. Bucur 2003, 2. Evans et al. 1995, 3. Downes et al. 1997, 4. Bergsten et al. 2001, 5. Ouis 2003, 6. Mishiro 1996, 7. Wade 1975, 8. Nicolotti and Migietta 1998, 9. Smiley and Fraedrich 1992, 10. Seaby 1991, 11. Isik and Li 2003, 12. Rinn et al. 1996, 13. Kersten and Schwarze 2005, 14. Barrett 1987, 15. Cown 1978, 16. Moura et al. 1987, 17. Greaves et al. 1996, 18. Harris 1992, 19. Blazé 1992, 20. Wilkes and Heather 1983, 21. Shigo 1991, 22. Mattheck et al. 1995, 23. Nicolotti et al. 2003, 24. Costello and Quarles 1999, 25. Gilbert and Smiley 2004, 26. Matheny et al. 1999. model “wall 4” is formed in the annual ring by the cambium after injury and resists the outward spread of decay from the center of the tree (Shigo 1979). Therefore, rather than pre- dicting decay would be present in a straight line from one graph trace to another, the line was predicted following a notional growth ring. Diagrams of each cross-section were drawn in reference to the CODIT model and the interpretation of raw data from the Resistograph. The diagrams were used to predict the area of decay in millimeters squared in a cross- section (Figure 3A). The E. globulus subsp. pseudoglobulus were felled and cross-sections were retained. The trunk sections were traced on clear plastic with observed cavities, decayed wood, and sound wood clearly marked. The drawings were photo- reduced when necessary. The areas of the two drawings, pre- dicted (using the expert system) and actual (from tracing the section), were then compared (Figure 3A and B). The area of the predicted cross-section was estimated as for a circle of the same radius, whereas the area of predicted decay was calcu- lated using a dot matrix grid on overhead transparency paper and counting dots spaced 2 mm (0.08 in) apart. The area of the actual cross-section and the decay in the cross-section were calculated using the same dot grid. Simple linear regression analyses testing the dependence of actual and predicted decayed wood were calculated using the software package SAS (Statistical Analysis System) version 8.2. For the data from the trees, simple regression analysis tested the dependence of: 1. Predicted area of decay in millimeters squared (as part of the expert system) for each section on the actual area of decay in the same tree sections; 2. Predicted linear distance of decay in millimeters across each section on the actual linear distance of decay in the same sections; and 3. Predicted location of decay in millimeters from the bark to the decay for each section on the actual location of decay in the same sections. RESULTS The results from the E. globulus subsp. pseudoglobulus in Expt. 3 suggest that the expert system can be used to predict the area of decay in a trunk cross-section of a eucalypt. A statistically very significant relationship was established be- tween the predicted total area of decay in a wood section using the expert system and the actual area of decay (Figure 4). In this experiment, an analysis of variance of predicted and decayed area data indicated that 76% of the variation in the actual data set could be explained by the predicted de- cayed area in the cross-section (P < 0.0001, n17). In terms of the percentage area of decay, the expert system overesti- mated decay by up to 7% (on average 4%) and underesti- mated decay by up to 9% (on average 3%). The percentage area of decay was predicted within a total range of 16% (−9% to +7%) and the decay in the sections was between 1% and 15% of the total area. In nine of the 17 samples, the expert system overestimated the percentage area of decay; in seven samples, it underestimated decay; and in one, the per- centage was the same. This is a very good level of accuracy, particularly in trees that were quite small (diameter at 1.3 m [4.3 ft] of 198 mm [7.9 in], 132 mm [5.3 in], and 212 mm [8.5 in]). There did appear to be two outlying points in the data set, but the two samples had the most decay of any cross-section in the data set. The test trees were small as previously stated and hence these points were not removed, because the more decayed samples are more representative of decayed trees that are usually larger. Although the data set for the number of samples is quite small (n17), the statistical relationship ©2007 International Society of Arboriculture
March 2007
| Title Name |
Pages |
Delete |
Url |
| Empty |
Search Text Block
Page #page_num
#doc_title
Hi $receivername|$receiveremail,
$sendername|$senderemail wrote these comments for you:
$message
$sendername|$senderemail would like for you to view the following digital edition.
Please click on the page below to be directed to the digital edition:
$thumbnail$pagenum
$link$pagenum
Your form submission was a success. You will be contacted by Washington Gas with follow-up information regarding your request.
This process might take longer please wait
