Arboriculture & Urban Forestry 38(4): July 2012 Table 4. Characteristics of methods for the evaluation of urban trees. Index Methodology Parametric Method Tedesco Swiss French Italian CTLA Finnish FEM Mixed Capitalization ICONA Norma Granada STEM Contato Removal Maintenance Subjective Sp, H&A, O Sp, H&A, O Sp, H&A, O Sp, H&A, O Sp, H&A, L Sp, H&A, O Sp, H&A, L, O Sp, H&A, L, O Sp, H&A, L, O Sp, H&A, L, O Sp, H&A, O Objective L L L L L Integration multiplicative multiplicative multiplicative multiplicative multiplicative multiplicative summative multiplicative multiplicative summative L Sp Notes: Sp = species; H&A = state of health and aesthetic value; L = location; O = others index; circum = circumference j represents the number of years during which maintenance tasks are performed for each of the specimens planted; PEC is pos- sible extra costs; q is a particular year; and i is the interest rate. Table 3 summarizes all of the methods reviewed. For each method, the table includes corrector indices (index); measures taken in the tree (variable), both to obtain the basic value of the tree and to determine the corrector index related to size; and the data used in the valuation for estimating costs and benefits (price). Table 4 shows the main features of the revised methods: the type of indices (subjective or objective), the method of integrating the indices (multiplicative or additive), the vari- able used to determine the basic value of the tree (direct- ly or indirectly), and the main factors in the assessment. DISCUSSION AND CONCLUSIONS All the methods value differently. Even for the same method and tree, appraisers obtain different valuations of different orders of magnitude (Watson 2002; Contato-Carol et al. 2008; Ponce-Donoso et al. 2009). The multiplicative or parametric methods define and quantify one, two or more physical, explanatory and objective variables and combine these with other, more subjective, difficult-to- measure variables (e.g., aesthetic appeal, location, historical sig- nificance) related to the presence of trees in cities (Price 2003). The capitalization methods are proposed by economists. They consider the tree to be the starting capital that will produce an income or profit over a period of time. Economists do not agree as to which economic reference value should be used to formu- late this econometric evaluation (Caballer 1999; Contato 2004). Parametric and mixed methods consider the location of the tree to be fundamental. The nearer it is to the city center, the higher its value (in these places the effects of urban stress on the plant are greater and the trees are costlier to maintain). The districts with a greater historical or cultural value are usually located in these areas. Most methods use a subjective index (Table 4). The location in- dex is obtained objectively in a higher number of methods, but is not very discriminating. For example, in the Swiss method, the loca- tion index takes values as large groups such as city centre (L = 10), peri-urban (L = 8) and rural area (L = 6). In recent studies, efforts have been made to objectify this index depending on the density of population (Neilan 2008) and according to the relationship be- tween population density and woodland (Ayuga-Téllez et al. 2011). To overcome the difficulties this poses with regard to value, the proposed index should be as objective as possible. This re- quires making detailed studies of numerical variables that de- termine the characteristics of the tree and its surroundings. A univocal relationship between indices and numerical vari- ables can be obtained in this way (Ayuga-Téllez et al. 2011). The integration of the indices is generally multiplicative, re- sulting in a greater increase in the differences between assess- ments made by different appraisers (Watson 2002). It would therefore be desirable to increase the use of additive methods. Only the ICONA (López Arce 1975) and Contato (Contato 2004) methods used variables measured on the tree. Most variables used parametric methods estimated from other measurements by simple expressions. Capitalization and mixed methods use tree age as a variable, estimated from statistical data (except when the exact date of planting is known). To overcome this disadvantage, the authors recommend that managers of public spaces encour- age the recording and safeguarding of this variable for all trees. The predominant factors in the valuation methods reviewed (Ta- ble 4) are of three types, and relate to size, age, and the health-related and aesthetic value of the tree. Age is not decisive in parametric meth- ods. Size is not determining in mixed and capitalization methods. The methods reviewed do not consider the award of zero value to a tree, even when it is in danger of falling and poses a risk to property and people, when it is located in an inappro- priate place, or when it no longer has any functional value. The CTLA and Contato methods assign a value of zero in some cases. The most suitable uses of each method reviewed depend on the main objective, the location of the trees, the type of land ownership, and the difficulty of the valuation procedure used (Table 5). Three main objectives are established: legal claims, damage assessment, and investment value. These objectives in- fluence the use and purpose of the different types of appraisal. Definitions collected by various authors (Swiecki and Bern- hardt 2001; Konijnendijk 2003; Konijnendijk et al. 2006) have been used to establish the types of location, which are as fol- lows: trees lining streets in towns and cities, and roadside trees (TS); parks and gardens within city boundaries (P&G); forests in urban areas or around towns and cities for the purpose of pro- viding amenities for the population (FA); and special trees (HT) for individual trees that may be considered important commu- nity resources due to their unique or noteworthy characteris- ©2012 International Society of Arboriculture multiplicative size of trunk area of crown Direct 135 Variable Indirect area size circum circum area circum age, circum, height, crown age age age age age age Predominant factors in the assessment L, H&A circum circum circum H&A circum size, H&A, O age H&A age H&A age age
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