Arboriculture & Urban Forestry 42(1): January 2016 valuation of urban trees. The response rate was 57%. The survey consisted of one main question: Which plant nurseries do you mainly buy trees from? The six tree nurseries used for base value cal- culation were chosen from the list of nurseries mentioned in responses in order to represent international tree nurseries and the most popu- lar Swedish nurseries. The chosen nurseries are listed below in alphabetical order, with the nursery catalog printing year included in parentheses. • Billbäcks, Sweden (2012) • Bruns Pflanzen, Germany (2011) • Lappen, Germany (2012) • Lorenz von Ehren, Germany (2012) • Splendor Plant, Sweden (2012) • Stångby, Sweden (2012) Tree Species The tree species selected for calculation of the base value were the three most common urban tree spe- cies in the Nordic countries, according to Sjöman et al. (2012). These were Acer platanoides L., Betula pendula L., and Tilia × europaea L. Accurate taxo- nomic identification of the species was carried out according to Aldén and Ryman (2009). In addition, a fourth species, Quercus robur L., was chosen due to its comparatively large price deviation from the other three species, with a higher price in all tree nursery catalogs. More in-depth analysis was con- ducted on Tilia × europaea due to its dominance in urban Nordic environments, where it occurs with a mean frequency of 16.0% (Sjöman et al. 2012). Data Analysis The cross-sectional area for each tree size consid- ered was measured in square centimeters (cm2 ) and calculated from the given circumference (at 1 m height, in accordance with Swedish and Euro- pean nursery standards), on the assumption that a circular trunk shape is an adequate approxima- tion. This procedure yielded a data set with price as a function of tree trunk area for each of the se- lected tree species (Acer platanoides, Betula pendula, Quercus robur, and Tilia × europaea). Linear func- tions were fitted to the data using the Proc GLM procedure in the statistical soſtware SAS 9.2 (SAS Institute Inc., Indianapolis, Indiana, U.S.). These fits were obtained for each individual species. The 23 goodness-of-fit/coefficient of determination (R2 ) was also calculated, again using the SAS soſtware. In addition, linear and polynomial functions were fit- ted to the original circumference versus price data. A linear model for tree price as a function of its trunk cross-sectional area [the Linear Index of Tree Appraisal (LITA) model] was developed inspired by these fits, to allow for extrapola- tion to large tree sizes from a single data point. Tree Planting Costs The tree planting costs were calculated using a calcu- lation system for outdoor constructions (KP-Kalkyl 2012), with the results verified through contacts with municipal authorities and contractors in Swe- den. The items included in the tree planting costs in the model are in accordance with CTLA (2000) and VAT03 (Randrup 2003). Inspired by VAT03 (Randrup 2003), the following costs were included: • Removal of the damaged tree (trunk, branches, and roots), excluding the sale of wood replacement of soil • • • restoration of the growing site • planting of new trees • establishment of aeration and irrigation sys- tems and tethering restoration of surface pavings and other sur- rounding areas • maintenance of the tree for five years RESULTS AND DISCUSSION Circumference or Cross-Sectional Area Regarding the relationship between tree price and tree circumference, for the data obtained from the nurs- eries, a linear and a second order polynomial both proved to be good fits to the Tilia data (R2 = 0.970 and 0.994, respectively) (Figure 1). A noteworthy fea- ture of the linear fit was the large constant offset. It was also found that the three most common species of trees were very similar in their price behavior, and therefore, for reasons of clarity, only the Tilia data are shown in Figure 1 and Figure 2. Quercus robur deviated as expected by being consistently more expensive, but the general shape of the curve was similar. Similarly, a second order polynomial and a linear function of the cross-sectional area gave a good fit to the data for all individual species ©2016 International Society of Arboriculture
January 2016
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