Arboriculture & Urban Forestry 34(3): May 2008 Arboriculture & Urban Forestry 2008. 34(3):137–143. 137 Determining the Age of Streetside Trees with Diameter at Breast Height-based Multifactorial Model Jan Lukaszkiewicz and Marek Kosmala Abstract. This article evaluates the possibility of determining tree age based simultaneously on diameter at breast height (dbh) (1.3 m [4.3 ft]) and total tree height using common lime, common ash, and horsechestnut species. The first step was the identification and measuring groups of trees growing in similar conditions (streetside trees in Warsaw area, Poland) in which planting ages were known (mainly from archives). Next, multifactorial regression model was developed describing the growth of both tree parameters (dbh and height) over time. In the majority of cases, plotting tree age against diameter and height yielded a regression coefficient r value and determination coefficient r2 value above 0.9. For graphic interpretation of elaborated multifactorial models, nomograms were applied. This kind of graph allows explaining tree age based on both dbh and height of trees. Another step was verification. The resulting model was applied to unrelated groups of trees of known age. Mean bias values were established for each model. The difference between the actual age and mean age calculated with the model was less than ±15%. Presented model, although not meant for application to individual trees, might be useful to determine the age of groups of trees growing along streets and roads. Key Words. Common ash; common lime; dbh–height regression model; horse chestnut; streetside trees; tree age nomograms. The knowledge of tree age is necessary for examining growth stage and age structure in urban tree stands to ensure their proper maintenance and preservation. The tree age data find a signifi- cant potential of application in tree maintenance, especially in preparation of management plans for urban stands. These kinds of plans provide directions about frequency and benefits of maintenance aspects such as fertilizer requirements, different ways of pruning, removing trees causing threats, and planning new planting. Tree age data should be also taken into account among factors like plant species, damage rate, and location for assessment threats caused by old trees old with weakened static. In addition to that, data concerning the relationship of tree age and dendrometric parameters is very important for determining monetary value of trees and costs of tree replacement (McPher- son 2007). Tree growth formulae make possible forecasting the effect of urban trees on energy savings, atmosphere CO2 reduc- tions, air quality benefits, storm water runoff, and the cost of tree maintenance. Research on the correlation of tree age and the growth of dendrometric parameters serves as a starting point for developing various computer programs (e.g., DISMUT [Austra- lian National University, Canberra, Australia], eco-Smart [USDA Forest Service, Davis, CA], or Stratum [i-Tree, Kent, OH]) enabling one to calculate the economic effect of trees on savings and expenditure of individual households, towns, and cities (Banks et al. 1999; Gardner 2006; McPherson 2006) or to develop tridimensional visualizations of tree growth in a chang- ing urban environment (Linsen et al. 2005; Sterck et al. 2005). Results of tree growth research prove that savings resulting from the presence of trees in towns can be more than three times the cost of tree maintenance (McPherson et al. 2002; Geiger and McPherson 2004; Gardner 2006; McPherson 2006). Another important benefit is the ability to provide optimum space for trees in urban plans to avoid the collision of trees with technical infrastructure and buildings (Neely 1988; Banks et al. 1999; Peper et al. 2001a; Larsen and Kristoffersen 2002, Linsen et al. 2005). It is also worth mentioning that tree age data are an important element of inventory databases for trees and urban tree stands (e.g., as planting date) developed in large cities of West- ern Europe, the United States, and Australia (Banks et al. 1999; Peper et al. 2001a, 2001b; Larsen and Kristoffersen 2002; Frank et al. 2006). According to Olig and Miller (1997), the United States at the end of 1990s had available on the market at least a dozen specialized programs for urban tree inventory and man- agement such as Inventree, TreeKeeper (Davey Tree Expert Co., Kent, OH), TreeMaster (Urban Forestry Consultants, Sobrante, CA), and Urban Forest Inventory (Forest Data Corp., Inverness, CA). Until recently, the growth rates of urban trees were not well documented (McPherson 2007). The literature provides few ex- amples of research in which tree age is a characteristic deter- mined by noninvasive methods in situ based on dendrometric parameters. Most of the researchers (e.g., Banks et al. 1999; Peper et al. 2001a, 2001b; Larsen and Kristoffersen 2002; Grabosky and Gilman 2004; Linsen et al. 2005) focus on exam- ining the growth of dendrometric parameters over time such as the increase of diameter at breast height (dbh), total tree height, crown radius, and leaf area. This equally concerns the research on forestry and in arboriculture. Mathematical models of expo- nential tree growth over time are chiefly based on the regression principle (see Pigott 1989; Brack and Wood 1998; Brzeziecki 1999; Greenberg and Simons 1999; Bolibok and Brzeziecki 2000; Peper et al. 2001b; Gutsell and Johnson 2002; Larsen and Kristoffersen 2002). The regression allows users to calculate the best fit of model parameters to data (Neter and Wassermann 1974; Sokal and Rohlf 1981; Lomnicki 2002; Motulsky and Christopoulos 2003). It is necessary to say that there is hardly any research available to present the same issue from the reverse perspective, estimating age based on dendrometric parameters. Such an approach was adopted, for instance, by Loevenstein et al. (2000), however, with reference to forest environment. ©2008 International Society of Arboriculture
May 2008
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