76 [9] Ponce-Donoso et al.: Appraisal Using Twelve Valuation Formulas and Two Appraiser Groups Value (€EUR) = (trunk area (cm2 cm2 ) * basic price ) * species * location * condition where the trunk area is expressed in cm2 sic price is expressed per unit of cm2 factor relates attributes of the tree and the ba- . The species associated with tree growth, life expectancy, adaptability to environmental conditions, maintenance re- quirements, and other amenities. The condi- tion is related to the characteristics of the health and vigor of the tree. The location factor cor- responds to the location of the tree in the city. The Burney Method of Australia (Moore and Arthur 1992) is as follows: [10] Value (€EUR) = tree volume * base value * life expectancy * shape and vigor * localization where a number of points related to the vol- ume of the tree are assigned, which correspond to an inverted cone, including the base value, which is the cost per cubic meter in retail nurser- ies, and other shape factors, vigor, and location. The Danish Method (Randrup 2005) is as follows: [11] Value (€EUR) = B * H * L * A where B = base, which is expressed as E + (Pn / Cn) * (Cd / Cn), where E = costs of establishing value, Pn = price of a new tree, Cn = circum- ference of a new tree, and Cd = circumference of the evaluated tree; H = the health index, which is expressed as the condition of (r + t + rp + rs + f) / 25, being roots (r), trunk (t), main branches (rp), secondary branches and twigs (rs), leaves and buds (f); L = index loca- tion, which is expressed as (n + a + ve + v + F) / 25, where natural ecological adaptation is (n), architecture (a), aesthetic value (ve), visibility (v) and environmental factors (F); and A = age index, which is expressed as [((b – a) * 2) / b] – 2, where a = current age and b = life expectancy. The Swiss Method (Ferraris 1984) is as follows: [12] Value (€EUR) = Pb * ID * IP * IER * IR where Pb = base price; ID = dimension index in function of the circumference trunk; IP = loca- tion index, which varies from the center of the city to a rural area; IER = aesthetic index and sanitary condition, which is related to vegeta- tive vigor; and IR = reduction due to damage in- dex, which is applied as a percentage of the trunk. For the statistical analysis, researchers used both mean and median values to better reduce the effects of outliers. The following hypotheses were used to account for sources of variation such as the spe- cific valuation formulas used, type of appraisers used, and inter- and intra-appraiser comparisons: • Ho: αi = αj / i ≠ j; (i.e., there are no statis- tically significant differences between the medians of the variation sources). • Ho: αi ≠ αj / i ≠ j; (i.e., there are statistically significant differences between the medians of the variation sources). Analyses of variance (ANOVAs) were used to determine if there were statistically signifi- cant differences between the sources of varia- tion. The assumptions of homoscedasticity and normality were not met in all cases because of a high coefficient of variation (209.26%). Similarly, despite the transformation of data, the bias and standardized kurtosis were high (143.20 and 704.48, respectively), exceeding Kirk’s (1995) preset limit value of 2.0. In these cases, the non-parametric ANOVA Kruskal- Wallis (Conover 1999) was used, as it is less sensitive to the presence of atypical values. Both the data obtained from the SG and JG experience groups were ranked, according to their position in the ascending order of the data; with 1 having the lowest valuation and ranking, and 2,880 the highest, while the intermediate rank- ings corresponded to intermediate values for each group. Statistically significant differences were found between sources of variation, so the least significant difference test (DMS; P ≤ 0.001) was applied (Conover 1999). Also, an analysis of non- parametric variance was separately conducted for each of the formulas to better observe the vari- ability among them. Microsoſt® Excel® Version 2003 and Statgraphics Centurion for Windows® (StatPoint Technologies, Inc., Warrenton, Vir- ginia, U.S.) were used for all statistical analyses. ©2017 International Society of Arboriculture
March 2017
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