A Study Of Ctla Formula Values

Data Collection

Formula method tree appraisal data were actively solicited from appraisers throughout the United States. Complete detailed information used in calculating the appraised values was required for each appraisal record (Table 1). Only trees 4 in. (10 cm) dbh and greater were used, based on a review of what is commonly used as the “largest commonly available transplantable tree” across the United States. Species names were converted to uniform species codes. Data were entered into Dbase for Windows™ and appraised values were calculated according to the appropriate edition of the Guide, with one exception. To reduce the number of variables, condition was not factored into individual appraised value calculations (i.e., rated at 100%). Condition data were recorded for use in other and data analysis.

Data Summary

Using programming features of Dbase 5.0, appraisal records were grouped by published species rating, size class, and landscape site type (residential, park, etc.). Records were sorted by published species rating rather than the rating used in the appraisal in order to allow decisions by individual appraisers to use a different value to be reflected in appraised value variation. When the published rating for any species differed from region to region, the midpoint value was used. Whenever possible, size classes represented consistent trunk cross-sectional area increases between classes. The mean, standard deviation, and the number of appraisal records for each group were calculated.

For greater consistency, the average appraised values used in the tables were drawn from linear regression curves (f = y₀+ax+bx², SigmaPlot 5.0) for each species class within each size class. Regression coefficients were always greater than 0.86 and usually greater than 0.90. This mean ± one standard deviation was used to determine the comparable value range.

A t-test (P ≤ 0.05) was used to compare current values, condition, location, and dbh between casualty loss and inventory appraisals, and also between casualty loss appraisals performed for parties responsible for the loss of the trees and those who owned the trees.

Table of Comparable Values

Recent editions of the Guide emphasize that appraisals should be reasonable. Suggestions are provided for comparing tree values to overall property values, but there is no mention of comparing formula values to values of similar trees, as is often standard in other appraisal disciplines, such as real estate. Many appraisers would not have enough personal experience to perform a comparison to similar situations over a wide variety of circumstances. The data from this study were used to develop a reference table of comparable tree appraisal values by size and species class (Table 2).The adjusted mean ± one standard deviation was used to define this “range of comparable values.” This range includes 67% of all the values, while excluding the one-third of the values that are very high or very low. The table is not intended to replace the formula but simply provides an appraiser with the opportunity to compare how his or her appraised value compares to values produced by other appraisers. The table data represent trees with a 54% condition rating, the average condition rating of all appraisals (See “Condition” on page 295). Condition of individual appraised trees being compared to the table could be higher or lower, and any comparison to table values would have to take this into consideration. Appraised values higher or lower than the comparable ranges in the table can be valid but would probably involve special circumstances.

The comparable ranges are fairly large in many cases, due to high standard deviations. In some cases, these deviations have produced range limits that do not closely follow the increases in size and species rating. Variation among appraisers (often due to the subjective factors) is a major contributor. Differences between species rating actually used by the appraiser in the formula, and species rating used to sort records (the median published value from across the country) also contribute. The original intent was to divideappraisal records by geographic region. When divided, there was then insufficient data in many of the species class/size rating categories. The subsequent need to sort records by only one species rating increased variation.

The way size classes are determined also contributes to the variation. Because size is measured as trunk cross-sectional area, size classes were increased by increments that represented consistent increases in cross-sectional area instead of increases in dbh [a 2-in. (5-cm) dbh increase from 4 to 6 in. (10 to 15 cm) results in a cross sectional area increase of 124%, while a similar increase from 40 to 42 in. (100 to 105 cm) dbh increases the area only 10%). A 25% increase in cross-sectional area was desired, but size classes had to be divided by wholeinch increments because many appraisers round to the nearest inch. As a result, the percentage increase from one class to the next varied somewhat. Most fell between 20% and 30%, but increases between some of the smallest size classes were much larger. This variation no doubt increased the standard deviation and, therefore, the range.

Formula Components

Appraised values of inventory trees were significantly higher (P < 0.001) than values of casualty loss trees. Average location rating and size were both significantly (P < 0.001) higher for inventory trees, while species rating was higher (P < 0.001) for casualty loss trees (Table 3). Condition was not factored in.

These differences in the variables used in the formula do not seem to adequately explain the higher appraised values of inventory trees. The higher average location rating (27%) of inventory trees alone more than accounts for the 25% higher appraised value of inventory trees.Inventory trees were also 33% larger (based on crosssectional area) and offset by only a 16% lower species rating. The remaining difference (18%) must somehow be explained by the only remaining factor, price per square inch.

Most inventory appraisals used the 6th and 7th editions of the Guide. The $22 and $27 per square inch value published respectively in 1983 and 1988 would both be equivalent to $37 in 1998 dollars (http://stats.bls.gov/cpihome.htm). Many of the casualty loss appraisals were more recent and used the 8th edition. The regionally determined dollar per square inch values for the 8th edition were $18 to $36, averaging $28. Most of these published values were determined soon after the 8th edition was published in 1992. Inflation between 1993 and 1998 would increase this average value to $31, 16% lower than the equivalent fixed published values in previous editions. It would appear that once tree values were made dependent on nursery stock values, appraised values of trees were lower relative to the era of fixed published cost per square inch.

Species

Species ratings have always been published regionally and not often modified by individual appraisers. The higher average species rating of casualty loss trees may simply be due to a different mix of species encountered in the two situations. Inventories typically consist of street and park trees, where larger numbers of fast-growing, lower-quality species have often been planted. Casualty loss appraisers may be more likely to encounter a wider variety and higher quality species on private properties.

Location

The higher average location rating of inventory trees does not appear to result from the difference in their position in the landscape. Guidelines for determining location ratings were provided by the 7th edition of the Guide (CTLA 1988).These guidelines were abandoned in the 8th edition, but it would be hard for appraisers not to continue to be influenced by them to some degree. These recommendations indicate that the street and park trees dominating the inventories should be rated 40% to 80%. Casualty loss trees include a wider variety of residential, commercial, and some public sites. The guidelines suggest similar location ratings of 50% to 90% for these sites. With so much overlap, average location ratings for all trees should be quite similar. If there is a difference, street tree inventory appraisals might be expected to be a little lower than casualty loss appraisals. The inventory mean of 69% is higher than the casualty loss mean of 54%, and not what would be predicted.

The inventory appraisal data included in this study often used a “default” location value (i.e., 70% for all street trees) unless circumstances warranted it be changed for individual trees. The result is that thousands of inventory location ratings may represent just a single decision from the inventory software developer. Are these inventory location ratings too high? Street trees are generally highly regarded by professionals and the public for their aesthetic and functional properties. The 69% average is above midpoint of the recommended range and may be slightly, but not unreasonably, high. Are location ratings of casualty loss trees too low? A 54% rating implies that appraisers must believe that the trees are providing only a small fraction of the aesthetic and functional benefits possible on these sites (80% to 90% maximum). The data cannot tell us why casualty loss appraisers used such low location ratings, but further study by the appraisal community may be useful.

Data were collected in such a way as to allow analysis of location rating by landscape site type (street, residential property, commercial, parking lots, etc.). There was no significant difference in location rating between landscape site types (data not shown).This again may be traced back to the small difference in location rating guidelines in the 7th edition of the Guide, as described above.

Condition

Though condition was not used in individual appraised value calculations, analysis shows that it was higher (P < 0.001) for casualty loss trees (Table 3). Why? Do privately owned trees receive better care or are the trees growing under better conditions? Are they less subject to vandalism and damage than street trees? Perhaps they were just more carefully examined, revealing their true condition (which may be more likely to decrease the condition rating).

The average condition rating (54%) of appraised trees would be considered “fair” as defined in the guide (50% to 69%). Is this an accurate representation of the condition of the average tree in the landscape? Street tree surveys done in the late 1980s showed that 34% of the trees were considered to be in good condition and 28% in fair condition, though there was no clear definition of the condition categories (Kielbaso 2000). Further examination of the appraisal records from this study showed that 24% were rated good and 37% (the highest of any class) of the trees were rated fair as defined in the Guide. This finding is very similar to those in the previous study. Any differences could easily lie in the interpretation of “fair” and “good” by evaluators involved in each case. Fair-to-good is probably an accurate description of landscape tree condition.

Fault

Appraisers for casualty losses can be working for only one side of the dispute; the party whose tree was damaged, or the party who was in some way responsible for the damage. Values determined by appraisers working for those responsible for casualty losses were higher (P < 0.001). Higher location and condition ratings explain most of this difference (Table 4). Appraisers may have contact only with their own client and may be working with slightly different information, which could indirectly influence their perspective without their knowledge. If this were the case, then the reverse difference might be expected. This is another aspect that deserves more investigation.