142 Lukaszkiewicz and Kosmala: Determining the Age of Streetside Trees prediction of tree crown radius with age, because this is a useful parameter in urban designs. CONCLUSIONS The described method of determining the age of streetside tree populations based on the multifactorial regression model can find its use in situations when we have a positive knowledge about the origin of trees but the age remains unknown, whereas the invasive methods could be used in other cases, especially for single trees. The developed model is accurate and precise enough to de- termine the mean age of tree populations of low density such as the streetside and roadside locations (6b hardiness subzone). In such cases, the age readout error does not exceed ±15%. Graphic presentation of the nonlinear multifactorial regression model as nomograms has no equivalent in the cited analysis of professional literature. Nomograms find practical application in field conditions (as it is presented in the provided example; Figure 1), allowing for easy readouts of the age of homogenous populations of roadside trees. Further investigation should provide a comparison of tree spe- cies mentioned in this article to see if they share any growth trends; if so, it would suggest a potential for transfer regression model to another tree species, which shows similar growth. Although the usefulness of nomograms presented in this ar- ticle is limited to the tree species growing in sites and climate similar to those reported here, the method has a general appli- cation to tree population in any city. This research serves as a basis for developing a more universal method. The method is, at present, at its developmental stage and can be expanded with additional tree species. Currently obtained results should serve as a starting point for more extensive re- search of the streetside tree population to determine the relation between their age and dendrometric parameters and environmen- tal factors. LITERATURE CITED Assman, E. 1968. The Principles of Forest Yield Studies. PWRiL, War- saw, Poland. Banks, J.C., C.L. Brack, and R.N. James. 1999. Modeling changes in dimensions, health status and arboricultural implications for urban trees. Kluwier Urban Ecosystems 3:35–43. Bolibok, L., and B. Brzeziecki. 2000. The analyze of selected allometri- cal relationships of main tree species in Bialowieza National Park. Sylwan Year CXLIV 6:73–81. Brack, C.L., and G.B. Wood. 1998. Forest Mensuration. Measuring Trees, Stands and Forests for Effective Forest Management. Tree Growth and Increment. http://sres.anu.edu.au (accessed 9/24/2005). Brzeziecki, B. 1999. Ecological Model of Forest Stand. Principles of Construction and Parametrization. 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Geiger, J.R., and E.G. McPherson. 2004. Desert Southwest Community Tree Guide. USDA Forest Service. Center for Urban Forest Research. Pacific Southwest Research Station. Grabosky, J., and E. Gilman. 2004. Measurement and prediction of tree growth reduction from tree planting space in established parking lots. Journal of Arboriculture 30:154–165. Grabowsky, J., N. Bassuk, and P. Trowbridge. 2002. Structural Soils: A New Medium to Allow Urban Trees to Grow in Pavement. LATIS Cornell University, Washington, DC. Greacen, E.L., and R. Sands. 1980. Compaction of forest soils—a re- view. Australian Journal of Soil Research 8:163–169. Greenberg, C.H., and R.W. Simons. 1999. Age composition and stand structure of old-growth oak sites in the Florida high pine landscape: Implications for ecosystem management and restoration. Natural Ar- eas Journal 19:30–40. Gutsell, S.L., and E.A. Johnson. 2002. Accurately ageing trees and examining their height-growth rates: Implications for interpreting for- est dynamics. British Ecological Society. Journal of Ecology 90: 153–166. Heinze, W., and D. Schreiber. 1984. A new mapping of hardiness zones for trees and shrubs in Europe. Mitteilungen der Deutschen Den- drologischen Gesellschaft 75:11–56. Kaennel, M., and F.H. Schweingruber. 2004. Glossary of Dendro- chronology. www01.wsl.ch/glossary (accessed 7/9/2006). Kosmala, M. 2001. Tree root systems. Mat. Ogólnopolskiej Konferencji Naukowo-Technicznej, Warszawa-Powsin 4.10.2001:57–72. Larsen, F.K., and P. Kristoffersen. 2002. Tilia’s physical dimensions over time. Journal of Arboriculture 28:209–214. Linsen, L., B.J. Karis, G. McPherson, and B. Hamann. 2005. Tree growth visualization. The Journal of WSCG 13:81–88. Loevenstein, E.F., P.S. Johnson, and H.E. Garrett. 2000. Age and di- ameter structure of a managed uneven-aged oak forest. Canadian Journal of Forestry Resources 30:1060–1070. Lomnicki, A. 2002. Introduction to Statistics for Naturalists. PWN, Warsaw, Poland. McPherson, E.G. 2006. I-Tree: Demonstrating that Trees Pay Us Back. USDA Forest Service. Center for Urban Forest Research. www. fs.fed.us/psw/programs/cufr/products/powerpoint/cufr_650_48_ Webcast_04-25-06a.swf (accessed 10/10/2006). ———. 2007. Benefit-based tree valuation. Arboriculture and Urban Forestry 33:1–11. McPherson, E.G., S.E. Maco, J.R. Simpson, P.J. Peper, Q. Xiao, and A.E. Van der Zanden. 2002. North Western Washington and Oregon Community Tree Guide: Benefits. Costs and Strategic Planting. In- ternational Society of Arboriculture, Pacific Northwest Chapter, Sil- verton, OR. Motulsky, H.J., and A. Christopoulos. 2003. Fitting Models to Biologi- cal Data Using Linear and Nonlinear Regression. A Practical Guide to Curve Fitting. GraphPad Software Inc., San Diego CA. www. graphpad.com (accessed 4/11/2006). Neely, D. (Ed.). 1988. Valuation of Landscape Trees, Shrubs and Other Plants. 7th Ed. 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