Growth prediction for five tree species in an Italian urban forest

Modeling the environmental benefits of urban trees requires data which relate crown height, crown diameter, and leaf area to tree age or stem diameter (DBH). Growth prediction curves, that can be derived from the same data, can also be very useful for a better planning, design and development of the urban forest. However, very little information is available on the growth behavior of urban trees, and limited to few species and regional contexts. The aim of this study was to determine the relationships between tree age and various parameters of tree size in order to develop models to predict the growth of the most important species of an urban forest in northeastern Italy. The logarithmic regression model, proposed by Peper et al., 2001a and Peper et al., 2001b and applied by Stoffberg et al., 2008 and Stoffberg et al., 2009, and other equations were tested in order to obtain the best fit for each species and parameter. All the models provided a better fit for the larger species (Tilia x vulgaris Hayne, Fraxinus angustifolia Vahl., Acer platanoides L.) than for the smaller ones (Prunus cerasifera “pissardi” (Carriere) L.H. Bailey and Lagerstroemia indica L.). The equations for predicting tree sizes and leaf area are presented and applied to compare size and growth 15 and 25 years after planting. According to the models A. platanoides attained the largest average annual DBH growth with values ranging from an average of 1.25 cm years−1 between 0 and 15 years after planting and 1.52 cm years−1 between 15 and 25 years after planting. L. indica showed the smaller DBH growth, ranging from 0.34 cm years−1 in the first period to 0.48 cm years−1 in the second period. 25 years after planting. A. platanoides L. is the tallest species and reaches the largest crown diameter, whith the largest average annual growth, followed by F. angustifolia and Tilia x vulgaris that show similar growth patterns. A comparison with predicted sizes in other studies confirms the need to extend the knowledge to the behavior of more species and more site specific conditions.