Arboriculture & Urban Forestry 35(2): March 2009 Arboriculture & Urban Forestry 2009. 35(2): 53–62 53 Identification of Significant Street Tree Inventory Parameters Using Multivariate Statistical Analyses Pierre Jutras, Shiv O. Prasher, and Pierre Dutilleul Abstract. Street tree inventories are costly procedures that must be designed to optimally meet management and operation- al requirements. 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 occidentalis), 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. Ac- cordingly, it was proposed that quantitative parameters be preferred for urban tree inventory. The second step aimed at reduc- ing the volume of necessary information needed for urban tree growth estimation. Various simple and complex combinations of quantitative parameters were tested. Results were conclusive and species independent: the simplified models were sta- tistically 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 param- eter 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. City trees provide environmental services that directly improve human health and the quality of life (Dwyer et al. 2003). In re- tail districts, visitors perceive the streetscape canopy to be an integral amenity of the city’s shopping environment and well- planned canopy-covered streets are highly appreciated (Wolf 2004). Trees provide relief from high temperatures by reduc- ing the effects of warming of urban environments caused by absorption, advection, and reradiation of heat from streets and buildings (Shashua-Bar and Hoffman 2000). Additionally, trees are vital due to their ability to remove contaminants from the air (Beckett et al. 2000). Trees absorb gaseous pollutants, such as ozone, nitrogen oxides, and sulphur dioxide, release oxygen through photosynthesis, store carbon dioxide, reduce evaporative hydrocarbon emissions from parked vehicles, and intercept dust, ash, pollen and smoke, removing significant amounts of par- ticulate pollution from urban atmospheres (Nowak et al. 2006). The impact of trees on increased property values and social functional benefits is largely acknowledged (Behe et al. 2005). Despite that, municipal administrations face serious challenges when allotting budget to the different essential activities needed to preserve street trees. For example, maintaining an inventory is a lengthy and costly process. When defining inventory pro- cedures, one must keep in mind that trees are highly complex organisms, and that a complete description of all physiological processes is unrealistic (Constable and Friend 2000). Rather, the physiological complexity must be simplified without excessive loss of the fundamental responses to environmental variables. Therefore, analysis and prediction of growth response must take place at an appropriate level of physiological resolution (Con- stable and Friend 2000). Additionally, inventory methodology and tools must be adapted to the day-to-day work and must cor- respond to an optimal balance between cost, effort, and accuracy. Over the years, many researchers have attempted to ful- fill these objectives. Some have measured shoot growth (Close et al. 1996), while others opted for diameter at breast height, height, and crown spread as relevant growth parameters (Lar- sen and Kristoffersen 2002; Yang et al. 2005). Cumming et al. (2001) assessed tree health using qualitative scales. Iakovoglou et al. (2002) and Quigley (2004) estimated growth by increment core measurements and tree diameter. Kent et al. (2004) and Per- cival et al. (2006) determined tree stress with leaf chlorophyll concentration, chlorophyll luminescence, leaf temperature, and water potential. Kopinga and van den Berg (1995) favored fo- liar analysis. In recent years, high-resolution spatial and aerial data acquisition equipment has been developed, and much effort has been devoted to obtain dendrometric and tree-health data sets by using these high technology products. Most of this re- search has been conducted in the forestry context (Wulder et al. 2003), but it is now expanding to the study of urban forests and trees (Jensen et al. 2005). However, these techniques are still ex- perimental and most cities use traditional inventory procedures. Historically, data sets collected to ascertain tree growth models were analyzed with standard statistical tools: trends in tree growth and stature were examined with regression tech- niques and analysis of variance. Per se, these one-dimensional models are usually characteristic of simple conditions. How- ever, because of the numerous variables influencing urban tree survival, relationships between tree growth and environmen- tal factors can be said to be, for the most part, complex and multidimensional. Hence, assessing these relationships with one-dimensional statistics may only extract minimum infor- mation from data. The use of multivariate statistical analy- ses might be an elegant solution to circumvent this difficulty. ©2009 International Society of Arboriculture
March 2009
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