ARBORICULTURE ARBORICULTU & CONTENTS URBAN FORESTRY Volume 35, Issue 2, March 2009 Formerly the Journal of Arboriculture, 1975 – 2005 (Volumes 1 – 31) www.isa-arbor.com Pierre Jutras, Shiv O. Prasher, and Pierre Dutilleul Identification of Significant Street Tree Inventory Parameters Using Multivariate Statistical Analyses ........................................................................................................................ 53 Abstract. Street tree inventories are costly procedures that must be designed to optimally meet management and operational require- ments. To assess the importance of several low-technology inventory parameters, a three-step multivariate statistical analysis was designed and tested on growth models of Norway maple (Acer platanoides), silver maple (Acer saccharinum), common hackberry (Celtis occiden- talis), green ash (Fraxinus pennsylvanica), honeylocust (Gleditsia triacanthos), littleleaf linden (Tilia cordata), and Siberian elm (Ulmus pumila). The first step appraised and compared the significance of qualitative and quantitative parameters. Results revealed that using qualitative indices decreased the explanatory power of models. Accordingly, it was proposed that quantitative parameters be preferred for urban tree inventory. The second step aimed at reducing the volume of necessary information needed for urban tree growth estima- tion. Various simple and complex combinations of quantitative parameters were tested. Results were conclusive and species independent: the simplified models were statistically non-significant. The best model was composed of multiple parameters. The third step looked for the identification of an inventory parameter that could be used to assess any urban tree physiological stage. It was found that no single parameter can adequately delineate the complexity of all tree physiological stages. The optimal model is rather multidimensional. Key Words. Correspondence Analysis; Principal Coordinate Analysis; Qualitative Inventory Parameters; Quantitative Inventory Parameters; Street Trees; Urban Tree Inventory. Tomas Martinez-Trinidad, W. Todd Watson, Michael A. Arnold, and Leonardo Lombardini Temporal and Spatial Glucose and Starch Partitioning in Live Oak ............................................... 63 Abstract. Carbohydrate translocation, which follows anatomical and developmental patterns, is ruled by source-sink relations where energy- containing compounds are moved from sources of production to sinks of utilization. Seasonal carbohydrate concentrations in various tree parts were measured and compared in 10 cm (4 in) trunk diameter live oaks (Quercus virginiana P. Miller). Tissue samples from roots, trunks, twigs and leaves were collected from three-year-old field-grown trees on four dates throughout the 2005–2006 seasons. Labora- tory analyses of glucose and starch were performed, and values were compared and contrasted according to sample location and time of year. Glucose levels were significantly higher in leaves during the winter (P ≤ 0.001), while starch concentrations were significantly higher in root and trunk tissues during the spring and winter assessments (P ≤ 0.001). Carbohydrate concentrations varied among tissues sampled within the tree. This study provides valuable information on the spatial and temporal partitioning of energy reserves, glucose and starch, in live oak so that arborists will have a better understanding of tree vitality, and the effects and environmental impacts of arboricultural treatments. Key Words. Carbohydrates; Quercus virginiana; Source-Sink Relations; Sugar. Brian Kane, Sergio Brena, and Wesley Autio Forces and Stresses Generated During Rigging Operations ........................................................... 68 Abstract. Rigging is one of the most dangerous aspects of arboriculture, yet there are no robust studies of the forces and stresses generated during rigging. Compounding the inherent danger of rigging is the structurally-deficient condition of many trees that are removed using rigging. Red pines (Pinus resinosa Ait.) (n = 13) were removed using conventional techniques, and forces at the block and in the rope were measured as the top, and four subsequent pieces were rigged with a block and Port-A-Wrap. Stress in the trunk at breast height was calculated from strain measurements and each tree’s modulus of elasticity. Multiple regression was used to determine which independent variables (mass of piece, fall distance and fall ratio, notch angle and depth) best predicted forces. Tops and pieces exhibited different relationships with mass, which was the best predictor of force at the block and tension in the rope. Other variables were not as important and exhibited counter-intuitive relationships with forces. There were few differences in stress generated when removing tops and pieces, which appeared to be due to greater deflection higher in the trunk when tops were removed. Key Words. Rigging; Trunk Stress; Biomechanics. ©2009 | International Society of Arboriculture | ISSN:1935-5297
March 2009
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