City foresters and arborists have been pruning shade trees as long as they have been planting them. The reasons to prune are many, ranging from public safety factors to aesthetic considerations. The need to prune is well established, but the frequency of pruning is not.
Frequency depends on factors such as species, growth rate, tree age, and location. However, the city forester usually does not have the luxury of choosing the proper time to prune a given tree, but rather will depend on an arbitrary pruning cycle determined by budgetary constraints. Discussion with city foresters in the Lake States reveals that many feel an optimum pruning cycle exists; the most favored period being 5 years. Most researchers and managers recommend “frequent” pruning, but they do not define frequent in precise terms. Fenner (2) reported the use of a four year cycle in Lansing, Michigan, while Chapman (1) suggests two to three prunings the first four years followed by infrequent pruning to remove deadwood.
Additional interest in the pruning cycle has resulted during the development of two computer programs by the authors. The first program UW/SP URBAN FOREST (4) was developed as a computer inventory system based on tree value. This program is essentially a data reduction system, providing summary tables and a listing of individual trees by location. The program uses the International Society of Arboriculture tree valuation system (3) to compute the value of city owned trees. The second program UW/SP URBAN FOREST MANAGEMENT is a management simulation model based on the inventory program. This program simulates the growth of an urban forest over time, allowing the user to make management decisions such as planting schedules and pruning cycles, and randomly remove trees based on historic mortality. UW/SP URBAN FOREST MANAGEMENT also calcuates management costs and compares them to the value of the urban forest.
A key problem in development of the management model was determining the long range impact of the pruning cycle on tree value. While it is recognized that a judicious pruning schedule will produce a higher value shade tree by raising its condition class, there has been no attempt to quantitatively determine the effect of pruning.
The objectives of this study are to determine the effect of pruning cycle on the condition class of street trees, and to determine an optimum pruning cycle for a case study.
Relationship Between Pruning and Condition Class
The UW/SP URBAN FOREST inventory program is currently being used by eight communities. Since the inventory program records condition class of street trees for use in computing tree value, this information was available for use in the analysis of the pruning cycle.
Milwaukee, Wisconsin1 was selected for the study because of the large population of shade trees and the availability of accurate pruning records. The Milwaukee Forestry Bureau subdivides the city into work units of 160 acres, with pruning and other management activities scheduled by work unit. The inventory system is designed to adapt to work unit subdivisions with output summarized by work unit and by city totals. Each work unit has the average condition class of the trees summarized. Data for Milwaukee are presented in Table 1.
The number of years since the units were last pruned and average condition class of the units are plotted in Fig. 1. The condition class of units pruned in 1978 (year 1) did not appear to be drawn from the same population as the condition class of the remaining units. Discussion with members of the inventory crew and officials from the city of Milwaukee Forestry Bureau revealed that units pruned in 1978 contained small trees that were in need of extensive corrective pruning. Removal of structurally unsound branches from these trees produced temporarily misshapen crowns, large pruning wounds, and a lower average condition class for trees pruned that year. Based on this information it was decided not to include 1978 data in further analyses.
Curvilinear regression was used to determine the relationship between the number of years since last pruning and condition class using the formula:
when,
Ŷ = condition class
X = years since last pruning
The analysis was significant (.005) with years since pruning accounting for 89.8 percent (R2) of the variation in condition class. (Fig. 1).
Economic Analysis of Pruning Cycle
The longer pruning is delayed the greater the impact on condition class, and ultimately tree value. While extending the pruning cycle lowers tree value, extending the cycle also saves cost by reducing annual pruning charges. When loss in tree value is compared to savings in pruning costs over time an optimum pruning cycle can be determined.
The curve presented in Fig. 1 represents the condition class of street trees following a given number of years since pruning. To determine the average condition class of an urban forest for a pruning cycle, all condition classes prior to and including the year of pruning must be averaged, i.e., an eight year pruning cycle will yield an average condition class for the street trees of 75.5 percent (Table 2).
Assuming a 100 percent condition class, the 40,808 trees used in this study have a value of $26,539,000 (based on UW/SP URBAN FOREST INVENTORY). Using this value as a base, values were calculated using the average condition class for all trees having pruning cycles of from two to fourteen years (Table 2). The loss in tree value resulting from extending the pruning cycle by one year is the marginal cost attributed to postponing an additional year.
Annual pruning costs are determined by dividing the total number of trees by the number of years in the pruning cycle. This is multiplied by $16.50, the average pruning cost per tree in Milwaukee (Table 2). The savings associated with extending the pruning cycle by an additional year is the marginal return associated with reduced pruning the next year (Table 2).
Comparison of the additional loss in tree value versus the additional savings in pruning costs indicates the optimum pruning cycle to be between four and five years for the city of Milwaukee (Fig. 2)
The relationship between pruning cycle and tree value is further supported by inventories in two other Wisconsin cities. City A has an average condition class of 54.5 percent and City B has an average condition class of 49.8 percent. Neither city has an established pruning cycle, but rather relies on local utility companies to prune trees which interfere with overhead wires. This pruning is infrequent, and often involves topping offending trees.
Summary & Conclusions
The length of the pruning cycle has a significant effect on tree value. Longer pruning cycles result in reduced tree value, with the decline in value accelerating over time. Savings to the city may be realized by longer pruning cycles, but only at a loss in tree value. This loss in value exceeds savings once the pruning cycle is extended to and beyond five years.
This provides a strong argument in favor of frequent pruning, with a pruning cycle of between four and five years being optimum for the city of Milwaukee. While this may be a convincing argument to city foresters, it remains the task of the city forester to convince city government officials.
Acknowledgment
The authors wish to acknowledge the assistance of Robert Skiera and Kenneth Ottman, Milwaukee Bureau of Forestry, in providing the data used in this study.
Footnotes
1 Milwaukee is currently being inventoried using UW/SP URBAN FOREST. At the time of writing approximately one fourth of the city had been inventoried.
- © 1981, International Society of Arboriculture. All rights reserved.