MONITORING THE URBAN FOREST: CASE STUDIES AND EVALUATIONS* EA. BAKER Department of Forest Resources, Utah State University, Logan, UT 84322-5215, U.S.A. (Received: 18 May 1992)
Abstract. Urban forestry is a new science, with monitoring techniques that are still evolving. Tree inventory is most commonly practiced, but we are learning to better monitor the benefits and liabilities provided by urban trees. These results are often for political, social, and biological purposes. Although most monitoring is done at the project or local level, examples of state and national projects are given. Quality control procedures are infrequently used, but could substantially improve the accuracy of data collected.
1. Introduction Monitoring in the urban forest, to many, means tree inventory. Tree inventory is a beginning, but monitoring is much mose. Monitoring usually implies repeated measurements. Many communities are still making their first measurements, or have yet to make their second. Urban forestry is a new management science, and is still grappling with understanding the resources that it must steward. Techniques are still being developed for sampling urban forests, and for using geographical information systems to inventory the complex infrastructure - of which trees are a part - that makes up our cities. Monitoring urban forests poses further challenges. I have used a working definition of urban forestry that is 75% urban - which means people - and only 25% trees. This suggests that our concept of monitoring the urban forest includes gathering information not only about trees, but also about the benefits they provide to people, and even the people who reap the benefits and must provide care for the trees. This presentation is organized into three sections. First, I will briefly review some of the purposes of monitoring. Then, I will discuss scopes of monitoring, and will conclude with a discussion of quality control, a key but often omitted element of the process.
2. Purposes of Monitoring Monitoring proves information, which can be used for many purposes. Whether it be protecting a population of trees from pests, or developing a national urban forestry initiative, monitoring provides the information needed to establish program * Paper No. 4373 of the Utah Agricultural Experiment Station, Utah State University, Logan, UT 84322, U.S.A. Environmental Monitoring and Assessment 26: 153-163, 1993. (~) 1993 Kluwer Academic Publishers. Printed in the Netherlands.
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goals and to evaluate progress toward them. This information is essential if we are to be effective managers of our urban forests. The information we collect is useful for three broad purposes: political, social, and biological. These are artificial groups, with considerable overlap. Yet, they are useful categories in that they focus thinking on why the information is being collected. 2.1. POLITICAL Information is often collected for political use. Communities, counties, or other jurisdictions often require information about trees and tree care programs to show the need for establishing or maintaining programs (Tate, 1985). Monitoring can provide information for programs to educate the public to make informed political choices. Increasing program budgets is often a driving force behind community forest inventories. An estimate of the dollar value of the urban forest resource can be computed using the Council of Tree and Landscape Appraisers' formula. This estimate can be very helpful in convincing citizens and their governing body to increase investment in the community forest. Information from urban forest monitoring can be used for many purposes, even for political gain. In one ward of a large midwestern community, the city forester must notify the alderman whenever a tree is planted in his ward. The alderman then sends a letter to the adjacent homeowner telling him or her about the tree, and how the alderman had it planted there! 2.2. SOCIAL Efforts are increasing to monitor the social values produced by the urban forest. A well-planned, functional community forest can provide a sense of well-being to the citizens, and provides a sense of relief and escape from urban life (Schroeder, 1990). While the benefits are often poorly understood, many communities undertake an inventory of their heritage tress. These are usually the largest (or oldest) trees. Once found, attempts are made to preserve them for their historical value. Identifying heritage trees is a common justification for a community undertaking a tree inventory, and even for establishing a community forestry program. Another common goal of monitoring is to promote public safety by identifying hazard trees. This is the minimum standard of care that every community should provide its citizens. Monitoring can detect hazardous trees before they fail and protect the citizens. As community forestry programs become more sophisticated, we are learning to use monitoring to project maintenance needs, which can prevent hazard trees, and prolong the useful life of the trees. Such information is often used politically to seek budget increases for tree care programs. Related to the public safety issue, is the public perception of safety from crime and other social problems, for example, drug use. Some people perceive unmanicured, brushy, densely wooded areas as 'dangerous', while feeling safe in the open, grassy areas with long viewing distances (Schroeder, 1990). Yet many people con-
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sider these same unmanaged areas more scenically attractive. Further studies are being done to assist forest managers in determining how to manage these areas for the maximum benefit and safety of the citizens. Although society must be protected from trees, people are more aware of their own need to enjoy the benefits provided by trees. Monitoring is beginning to consider the physical benefits provided by trees. Trees cool and shade our homes, reduce storm runoff, increase our property values, and make out habitat a nice place to be. We want these benefits today and into the future. Bartsch et al. (1985) addressed the issue of a sustained urban forest, in this example to provide continuous shading of city streets. While physical benefits could be considered in a class of their own, maintaining the benefits provided by trees is becoming a broad-based social issue, one which is influencing our cities and citizens. The recent impetus behind tree planting as a means to reduce potential global climate change can be sold as a biological issue, but public awareness and involvement suggests that this may well be a social issue. Solar access and clearing trees for maintaining views are two other examples of issues that citizens in the Pacific Northwest have begun to deal with. Issues such as these which arise long after the trees have been planted will continue to become important in the wake of current tree planting efforts.
2.3. BIOLOGICAL
We are probably best at monitoring biological aspects of trees, as these are things we can measure or count. We are frequently interested in the species composition of our urban forests, so we can adjust our planint to increase species diversity, and reduce the risk of another catastrophic pest outbreak such as Dutch Elm Disease. Recommendations are that no more than 10% of the shade tree population should be in a single genus, and no more than 5% in one species. Yet, many communities find the most commonly overused species are Norway maple and green ash and P r u n u s spp., often used as substitutes for American elms (Figure 1). We are also becoming increasingly aware of the need for age class diversity in the urban forest. Most trees in western urban forests are about 60 years old. Unless new trees are planted to provide sizable replacements for these aging trees, old age and decadence will leave our urban forests looking like the aftermath of a catastrophic pest outbreak. When we think a monitoring in the urban forest, we may most often think of monitoring for pests as part of an integrated pest management program. The best example would probably be monitoring for gypsy moth. When a threshold level of insects is detected, some management action is taken. With the gypsy moth, when male moths are trapped in the same locations in consecutive years, the area is often sprayed to prevent establishment of the insect. Other pests cause problems in our urban forests, but in spite of the need, rarely do we formally monitor them (Laut, 1978).
156
EA. BAKER Prunus
Ace 14
Tilia 8 Fraxin 5 ~ ~u,~, Species 86
Fig. 1. Species compositionof Vancouver, B.C., Canada. (Redrawn after: Ken Joehlin, ACRT,Inc., Kent, OH).
3. Examples of Monitoring Monitoring is done for many purposes, and is done at national, state, local and project scopes. The purposes and level of monitoring must be considered when interpreting results. 3.1. NATIONAL/REGIONALMONITORING Surveys done at Michigan State University are perhaps the best known examples of monitoring at a national level (Kielbaso, 1990; Anonymous, 1976, 1982). These reports document a written survey of urban forestry programs in more than 2800 cities in the United States. The stated goal of one report was "to provide background information useful in formulating plans for municipal tree planting and maintenance programs that will maintain a healthy tree population to enhance the quality of urban life" (Anonymous, 1982). These reports contain much useful information. This survey estimated a total of 61 653 904 street trees in the United States, with another 12 trees on private property for each street tree. The average value of street trees in 1986 was $525, up from $343 in 1974. Many community foresters use these figures to convince their community to invest in urban forestry, as few other community investments increase in value with time. Other figures exhibited by community foresters include the mean annual tree care cost of $10.62 per tree, and the per capita tree care cost of $2.60 per tree. The per capita tree care cost is often compared with those of police protection ($103), fire protection ($68), and refuse collection ($32). These national surveys have been repeated at 6 year intervals since 1974, pro-
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viding information on trends. These surveys will also serve as a valuable baseline for evaluating the effects of the recent federal program efforts in urban forestry. 3.2. STATEMONITORING An excellent example of state level monitoring was done recently in California, as an attempt to monitor the state of urban forestry in its communities (Bernhardt and Swiecki, 1989). Like the national survey, this was also based on a written survey. However, because this was done at the state level, more detailed information was collected, and recommendations were made for future program direction. Bernhardt and Swiecki (1989) estimated there were 5.9 million city trees in California, one for every four urban residents. Although California cities plant as many trees as they remove, urban areas were growing, so there is the potential to double the number of street trees in the state. The lack of species diversity was particularly alarming. In 45% of responding cities, more than 1/3 of the urban forest is composed of a single species! And more than half of the cities reported that just five species made up more than 80% of their urban forest. This result will no doubt have a profound effect on tree planting programs in the next few years. Another concern raised is that 80-90% of the immature trees will be less than 60 feet tall at maturity. While there is a limited understanding of the role of structural diversity in the urban forest, the need for taller trees and the benefits they provide was recognized. Monitoring for pests was not practiced regularly, even in an environmentally aware state like California. Rather, this survey showed that in most communities, pest levels were assessed by resident calls. This type of monitoring may not be monitoring a biological damage threshold, but a social threshold. This study provides many more insights into urban forestry as practiced in California, and provides a worthwhile example for other states about to undertake a similar task. 3.3. MONITORING AT THE LOCAL LEVEL At the local, or city level, we often equate monitoring with tree inventory. There are several types of tree inventories (Bassett, 1978; Smiley and Baker, 1988). These include specific problem inventories, partial inventories, complete inventories, and cover type surveys. Inventories can be further classified into static and continuous inventories. Specific problem inventories are usually designed to gather information about a single problem. Hazard tree inventories, pest surveys, and vacant planting site lists are classic examples of single problem inventories. Because the inventory has a precise purpose, only information pertinent to the problem need be collected. For this reason, specific problem inventories can usually be completed quickly and for relatively low cost. Partial inventories are so named because they collect the information of interest from a part or a sample of the tree population. Information on tree species, size, condition and value are often collected. Because this is a sample of the tree popu-
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lation, tree locations are usually not recorded, unless some management action is imminent. Thus, information from a sample is of limited value in scheduling tree maintenance to be performed on individual trees and species. The population of trees to be sampled can be determined by selecting some proportion of the total miles of street in the community, or a proportion of the number of blocks (Smiley, 1988). Ten percent is a typical sampling intensity. Confidence intervals or some measure of variation are rarely presented, although Mohai et al. (1978) have demonstrated procedures for optimizing sample size to minimize the coefficient of variation. Partial inventories can be very useful for meeting some objectives, but they are rarely used, perhaps due to the 'perceived difficulty of using statistical analysis. Complete inventories are those which examine the entire tree population within the specified area. These inventories may focus only on municipal trees, or they may include trees on both public and private property. In addition to collecting tree information, tree location is also established, greatly increasing the time and cost of completing the inventory, while also greatly increasing the accuracy and utility of the data. Computer printouts of all trees of a particular species that need a specific type of maintenance, or all trees on a street or block can be given to crews or contractors as work lists. If the operations performed are recorded for each tree, a history is available for help in dealing with homeowner requests. Perhaps even more important, these history data will permit monitoring species performance and maintenance cost in that specific community. Community foresters can then use species to increase benefits and reduce maintenance costs. Sometimes complete inventories are phased in over several years, especially if in-house staff or volunteers are used to perform the inventory (Graham 1987). Until the inventory is completed, it is a partial inventory, and extrapolations to the entire population can be made. Many communities opt for complete inventories, when a partial inventory would provide them the information they will use at much less cost. Before undertaking a street tree inventory, carefully consider what information will be needed and how that information will be used. Static and continuous inventories. Inventory longevity is often used to distinguish types of inventories. Specific problem and partial inventories usually provide 'snapshots' of the urban forest condition. For this reason, they must be repeated at relatively short intervals (five years?). Continuous inventories are updated constantly, which most always requires that the data be computerized. When the tree is visited or is treated, this information is added to the computerized information, so the data in the computer reflect the most recent information available about that tree. Even continuous inventories, however, must be repeated periodically because trees grow in size and their condition changes with time. Other errors also propagate in the data set. For example, removals by emergency crews, and trees planted by homeowners may not be recorded. Ten years is about the maximum interval between inventories. The cost of updating a continuous inventory will be
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Fig. 2. Aerialphotograph of city block in St. Paul, MN, showingplanting and removalneeds. Taken with 35 mm camera from a helicopter. Original slide was in color (Ektachrome),convertedto black and white for publication.
considerably less than the cost of a new inventory, because for most of the trees, the location has been determined and the data are entered; all that must be done is to inspect the tree in the field and update any changed fields in the data set. Cover type surveys have been used infrequently in urban forestry, but they provide an untapped opportunity to monitor tree cover in our communities. Hathout and Simpson (1986) successfully used aerial photographs to measure tree density in Winnipeg, Manitoba, Canada. A growing number of communities have ordinances requiring retention of tree cover during development. Aerial photographs provide one means of monitoring compliance with these ordinances. Viewing the urban forest from the air can provide benefits well worth the cost. It can provide community foresters with a "holistic" view of their entire community. Patterns of development and planting that may not be visible from the ground become obvious, and may help in completing a community pattern inventory (Johnson et al., 1990). The community forester can file this away in his head, or record the images with a 35 mm camera and a normal lens to provide a more permanent record (Figure 2).
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3.4. PROJECT LEVEL MONITORING Project level monitoring is done at the scale of a park, campus or development project. Project level monitoring may be little more than a very focussed tree inventory, or it may focus on special needs or characteristics of the site. Kelsey and Hootman (1988) inventoried parts of a campus to explore relationships between tree decline and soil characteristics. More often, however, project level monitoring involves a map of tree locations. The recent application of computer assisted drafting (CAD) to tree inventory has resulted in a sometimes useful technique (Downie, 1988; Lindhult and Ryan, 1987). These systems provide useful maps, however, their ability to integrate tree data is limited. Geographic information systems (GIS) are much more efficient at managing both map and tree data. As GIS technology becomes more affordable, more communities are implementing these systems. The community forest becomes another of the data layers in the system, much like streets, sidewalks, sewers and other utilities. The ability to access data about the trees and site constraints such as underground utilities, sidewalks or overhead wires is intriguing. However, the improved efficiency may not justify the cost of assembling these data. Several examples and results of monitoring have been presented. Keep in mind the scope and level of monitoring when interpreting the information. For example, the survey by Kielbaso (1990) estimated a total of 61 653 904 street trees in the United States. While the author rounded this to 60 million, it is based on inventories of only 16% of responding cities! Experience with communities doing inventories suggests that an estimate of the number of trees before the inventory is likely to be within 10-20% of the actual number based on inventory. The quality of the data must be considered when using the information gained by monitoring.
4. Quality Control Quality control during urban forest monitoring is often overlooked, yet it is crucial to the integrity of the data. Quality control must be designed into the inventory or monitoring process. However, descriptions of quality control programs are lacking in most references about street tree inventory. Until quality control is incorporated into the tree inventory literature, it will likely continue to be overlooked. Proper crew training is the first step in collecting accurate information. Often, data are collected by volunteers or students on summer vacation. These people should be instructed on the procedures to collect data. Each crew should have a written copy of data collecting procedures and standards with them in the field. If they encounter a tree that forks below the height at which they are to measure diameter, they can look to the standards to determine the proper procedure. There must also be a procedure in place to deal with unforeseen problems. For example, how should they handle a tree on a street with no street address? Quality control can detect and correct errors and omissions that can occur at any
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step in the monitoring process from observation of a particular trait to interpretation of the results. Data errors at the observation stage indicate insufficient training. The data collectors may not be familiar with all the tree species, leading to errors in species identification. In the data collecting standards, there should be simple guides to help the person assign the correct value to the data. For example, data collecting standards used by one of the larger private firms specializing in tree inventory contain a guide of the diagnostic features of tree species likely to be encountered during the inventory. Taking the group into an area and collecting data as a group will help the crews to better understand the procedures, and will illustrate further training needs. Another part of the data collection standards is a procedure for handling tree species and other data categories which are unknown. Even with extensive experience, some unforeseen situations will arise. Crew members must be given clear instructions for handling such situations as, for example, species which they do not recognize. This procedure should ensure that such cases do not 'drop through the cracks'. If 'UNKN' is entered for a species code, someone must return to the tree to make an identification. Any new codes, new procedures, or changes to procedures must be communicated to all crews to maintain consistency. Even when crews observe a trait correctly, they may record the data improperly. Entering the wrong code for a data iten, or entering it in the wrong place on the data sheet are common mistakes. Using mnemonic codes rather than numeric codes helps to prevent these errors. Other errors may occur because of dyslexia, carelessness, or haste. Crews are often encouraged to work quickly, but they must also be permitted to take enough time to do accurate work. A sample of each crew's work should be checked early in the inventory to make sure they are collecting accurate information. Data collectors must be aware that they will be checked, and they should be informed of the results. If problems are found, further training is indicated. When data are recorded on paper in the field, the data must be entered into a computer for further analysis. Data entry introduces another source of error into the process. Facing a large pile of data entry sheets to check against the computer file is not an exciting prospect, but it must be done. An alternative approach is to enter the data twice, compare the resulting data files, and reconcile differences. Field data recorders, including the 'palmtop' personal computers, are increasing the speed and accuracy of data collection, while decreasing cost. Instead of recording the data on paper field sheets for later entry into a computer, the data collector enters the data into the data recorder, with a keyboard or a bar-code reader. Later, the data are sent electronically to a larger computer. Increasingly sophisticated data recorders now permit data entry programs to provide menus of codes for each field, and to check the data entered against a list or range of allowable values. While this will reduce the number of errors, the data files must still be checked against trees in the field to detect and correct errors in observation or recording. Errors of omission must also be considered, not only for individual trees, but for
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whole blocks and wards. One large community found a box of data sheets that had not been entered into the computer more than one year after they thought all the data had been entered - while cleaning their office ! One way to solve this problem is to place a large map on the wall, and mark the blocks that have been examined on the ground. This also serves to motivate the crews by showing them their progress (K. Joehlin, personal communication). The blocks can be colored with a different color when the corrected data are available for computer analysis. W h e n these data are summarized, care must be taken to ensure that proper interpretations are made. Computers tend to do exactly what they are told, whether it is what we wanted or not. For example, a query of the data to determine the n u m b e r of trees along a certain street will yield erroneous results if trees on intersecting streets of c o m e r lots with the first street address are not excluded. Errors of this nature are difficult to detect by a systematic approach. Nevertheless, we must consider the possibility of such errors. Monitoring the urban forest is a much bigger, more complex job than many urban foresters realized. Even the process of tree inventory can be complicated. There are many reasons, and therefore many biological and sociological processes, to monitor. These processes can be examined at the level of individual project sites or anywhere along the continuum to national, continental or even global scales. Regardless of the project scope, the quality of the data must be known and considered in interpreting results. Monitoring is a new concept in the urban forest. Methods are still being developed and improved. If we apply what we know today, we can avoid many problems, and make living in our cities more pleasant. Using information obtained by monitoring, we can improve our management of this valuable resource, and inform and involve the public in managing their forest.
References Anonymous: 1982, Municipal Tree Management. Urban Data Service, Volume 14, Number 1. Washington, D.C.: International City Management Association, 14 pp. Anonymous: 1976, Managing Urban Trees. Urban Data Service Reports, Volume 8, Number 11, 14 PP. Bartsch, D., Hook, J., Prince, E. and Schrom, D.: 1985, 'Using Computer Simulation to Plan a Sustained Yield Urban Forest', J. For. 83, 372-375. Bassett, J.R.: 1978, 'Vegetation Inventories: Needs and Uses', Proc. Natl. Urban For. Conf. November 13-16, 1978. Washington, D.C., pp. 632-644. Bernhardt, E. and Swiecki, T.: 1988, 'The State of Urban Forestry in California'. Prepared for the California Department of Forestry and Fire Protection, Urban Forestry Program, 68 pp. Downie, A.M.: 1988, 'Firmly Planted', CADalyst 5, 31-35, Hathout, S. and Simpson, K.: 1986, 'Boulevard Tree Studies from Aerial Photographs of Winnipeg City, Manitoba, Canada', J. Env. Management 23, 203-214. Johnson, C., Baker, EA. and Johnson, W.: 1990, Urban and Community Forestry: A Guide for the Interior Western States. USDA Forest Service, Intermountain Region, Ogden, UT, 215 pp. Kelsey, P.D. and Hootman, R.G.: 1988, 'Soil and Tree Resource Inventories for Campus Landscapes', J. Arboric. 14, 243-249. Kielbaso, J.J.: 1990, 'Trends and Issues in City Forests', J. Arboric. 16, 69-76.
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Laut, J.G.: 1978, 'Detection of Insect and Disease Conditions: A Necessity for Urban Forest Inventories', Proc. NatL Urban For. Conf. November 13-16, 1978. Washington, D.C., pp. 645-649. Lindhult, M.S. and Ryan, H.D.P., III: 'Street Tree Management: The Next Generation', ArborAge 7, 13-20. Majerus, K.A.: 1988, Urban Forest Management: Guidelines for Planning and Administration, University of Illinois, Department of Forestry, 46 pp. Mohai, P., Smith, L., Valentine, E, Stiteler, W., Elias, T. and Westfall, R.: 1976, 'Structure of Urban Street Tree Populations and Sampling Designs for Estimating their Parameters', METRIA : 1, Proc. First Conf. of the Metropolitan Tree Improvement Alliance, pp. 28-43. Schroeder, H.W.: 1990, 'Perceptions and Preferences of Urban Forest Users', J. Arboric. 16, 58-61. Smiley, E.T.: 1988, 'Test Your Town's Trees', Am. For. 94, 69-72. Smiley, E.T. and Baker, EA.: 1988, 'Options in Street Tree Inventories', J. Arboric. 14, 36--42. Tate, R.L.: 1985, 'Uses of Street Tree Inventory Data', J. Arboric. 11, 210-213.
Abstract. Urban forestry is a new science, with monitoring techniques that are still evolving. Tree inventory is most commonly practiced, but we are learning to better monitor the benefits and liabilities provided by urban trees. These results are often for political, social, and biological purposes. Although most monitoring is done at the project or local level, examples of state and national projects are given. Quality control procedures are infrequently used, but could substantially improve the accuracy of data collected.
1. Introduction Monitoring in the urban forest, to many, means tree inventory. Tree inventory is a beginning, but monitoring is much mose. Monitoring usually implies repeated measurements. Many communities are still making their first measurements, or have yet to make their second. Urban forestry is a new management science, and is still grappling with understanding the resources that it must steward. Techniques are still being developed for sampling urban forests, and for using geographical information systems to inventory the complex infrastructure - of which trees are a part - that makes up our cities. Monitoring urban forests poses further challenges. I have used a working definition of urban forestry that is 75% urban - which means people - and only 25% trees. This suggests that our concept of monitoring the urban forest includes gathering information not only about trees, but also about the benefits they provide to people, and even the people who reap the benefits and must provide care for the trees. This presentation is organized into three sections. First, I will briefly review some of the purposes of monitoring. Then, I will discuss scopes of monitoring, and will conclude with a discussion of quality control, a key but often omitted element of the process.
2. Purposes of Monitoring Monitoring proves information, which can be used for many purposes. Whether it be protecting a population of trees from pests, or developing a national urban forestry initiative, monitoring provides the information needed to establish program * Paper No. 4373 of the Utah Agricultural Experiment Station, Utah State University, Logan, UT 84322, U.S.A. Environmental Monitoring and Assessment 26: 153-163, 1993. (~) 1993 Kluwer Academic Publishers. Printed in the Netherlands.
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goals and to evaluate progress toward them. This information is essential if we are to be effective managers of our urban forests. The information we collect is useful for three broad purposes: political, social, and biological. These are artificial groups, with considerable overlap. Yet, they are useful categories in that they focus thinking on why the information is being collected. 2.1. POLITICAL Information is often collected for political use. Communities, counties, or other jurisdictions often require information about trees and tree care programs to show the need for establishing or maintaining programs (Tate, 1985). Monitoring can provide information for programs to educate the public to make informed political choices. Increasing program budgets is often a driving force behind community forest inventories. An estimate of the dollar value of the urban forest resource can be computed using the Council of Tree and Landscape Appraisers' formula. This estimate can be very helpful in convincing citizens and their governing body to increase investment in the community forest. Information from urban forest monitoring can be used for many purposes, even for political gain. In one ward of a large midwestern community, the city forester must notify the alderman whenever a tree is planted in his ward. The alderman then sends a letter to the adjacent homeowner telling him or her about the tree, and how the alderman had it planted there! 2.2. SOCIAL Efforts are increasing to monitor the social values produced by the urban forest. A well-planned, functional community forest can provide a sense of well-being to the citizens, and provides a sense of relief and escape from urban life (Schroeder, 1990). While the benefits are often poorly understood, many communities undertake an inventory of their heritage tress. These are usually the largest (or oldest) trees. Once found, attempts are made to preserve them for their historical value. Identifying heritage trees is a common justification for a community undertaking a tree inventory, and even for establishing a community forestry program. Another common goal of monitoring is to promote public safety by identifying hazard trees. This is the minimum standard of care that every community should provide its citizens. Monitoring can detect hazardous trees before they fail and protect the citizens. As community forestry programs become more sophisticated, we are learning to use monitoring to project maintenance needs, which can prevent hazard trees, and prolong the useful life of the trees. Such information is often used politically to seek budget increases for tree care programs. Related to the public safety issue, is the public perception of safety from crime and other social problems, for example, drug use. Some people perceive unmanicured, brushy, densely wooded areas as 'dangerous', while feeling safe in the open, grassy areas with long viewing distances (Schroeder, 1990). Yet many people con-
MONITORING THE URBAN FOREST
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sider these same unmanaged areas more scenically attractive. Further studies are being done to assist forest managers in determining how to manage these areas for the maximum benefit and safety of the citizens. Although society must be protected from trees, people are more aware of their own need to enjoy the benefits provided by trees. Monitoring is beginning to consider the physical benefits provided by trees. Trees cool and shade our homes, reduce storm runoff, increase our property values, and make out habitat a nice place to be. We want these benefits today and into the future. Bartsch et al. (1985) addressed the issue of a sustained urban forest, in this example to provide continuous shading of city streets. While physical benefits could be considered in a class of their own, maintaining the benefits provided by trees is becoming a broad-based social issue, one which is influencing our cities and citizens. The recent impetus behind tree planting as a means to reduce potential global climate change can be sold as a biological issue, but public awareness and involvement suggests that this may well be a social issue. Solar access and clearing trees for maintaining views are two other examples of issues that citizens in the Pacific Northwest have begun to deal with. Issues such as these which arise long after the trees have been planted will continue to become important in the wake of current tree planting efforts.
2.3. BIOLOGICAL
We are probably best at monitoring biological aspects of trees, as these are things we can measure or count. We are frequently interested in the species composition of our urban forests, so we can adjust our planint to increase species diversity, and reduce the risk of another catastrophic pest outbreak such as Dutch Elm Disease. Recommendations are that no more than 10% of the shade tree population should be in a single genus, and no more than 5% in one species. Yet, many communities find the most commonly overused species are Norway maple and green ash and P r u n u s spp., often used as substitutes for American elms (Figure 1). We are also becoming increasingly aware of the need for age class diversity in the urban forest. Most trees in western urban forests are about 60 years old. Unless new trees are planted to provide sizable replacements for these aging trees, old age and decadence will leave our urban forests looking like the aftermath of a catastrophic pest outbreak. When we think a monitoring in the urban forest, we may most often think of monitoring for pests as part of an integrated pest management program. The best example would probably be monitoring for gypsy moth. When a threshold level of insects is detected, some management action is taken. With the gypsy moth, when male moths are trapped in the same locations in consecutive years, the area is often sprayed to prevent establishment of the insect. Other pests cause problems in our urban forests, but in spite of the need, rarely do we formally monitor them (Laut, 1978).
156
EA. BAKER Prunus
Ace 14
Tilia 8 Fraxin 5 ~ ~u,~, Species 86
Fig. 1. Species compositionof Vancouver, B.C., Canada. (Redrawn after: Ken Joehlin, ACRT,Inc., Kent, OH).
3. Examples of Monitoring Monitoring is done for many purposes, and is done at national, state, local and project scopes. The purposes and level of monitoring must be considered when interpreting results. 3.1. NATIONAL/REGIONALMONITORING Surveys done at Michigan State University are perhaps the best known examples of monitoring at a national level (Kielbaso, 1990; Anonymous, 1976, 1982). These reports document a written survey of urban forestry programs in more than 2800 cities in the United States. The stated goal of one report was "to provide background information useful in formulating plans for municipal tree planting and maintenance programs that will maintain a healthy tree population to enhance the quality of urban life" (Anonymous, 1982). These reports contain much useful information. This survey estimated a total of 61 653 904 street trees in the United States, with another 12 trees on private property for each street tree. The average value of street trees in 1986 was $525, up from $343 in 1974. Many community foresters use these figures to convince their community to invest in urban forestry, as few other community investments increase in value with time. Other figures exhibited by community foresters include the mean annual tree care cost of $10.62 per tree, and the per capita tree care cost of $2.60 per tree. The per capita tree care cost is often compared with those of police protection ($103), fire protection ($68), and refuse collection ($32). These national surveys have been repeated at 6 year intervals since 1974, pro-
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viding information on trends. These surveys will also serve as a valuable baseline for evaluating the effects of the recent federal program efforts in urban forestry. 3.2. STATEMONITORING An excellent example of state level monitoring was done recently in California, as an attempt to monitor the state of urban forestry in its communities (Bernhardt and Swiecki, 1989). Like the national survey, this was also based on a written survey. However, because this was done at the state level, more detailed information was collected, and recommendations were made for future program direction. Bernhardt and Swiecki (1989) estimated there were 5.9 million city trees in California, one for every four urban residents. Although California cities plant as many trees as they remove, urban areas were growing, so there is the potential to double the number of street trees in the state. The lack of species diversity was particularly alarming. In 45% of responding cities, more than 1/3 of the urban forest is composed of a single species! And more than half of the cities reported that just five species made up more than 80% of their urban forest. This result will no doubt have a profound effect on tree planting programs in the next few years. Another concern raised is that 80-90% of the immature trees will be less than 60 feet tall at maturity. While there is a limited understanding of the role of structural diversity in the urban forest, the need for taller trees and the benefits they provide was recognized. Monitoring for pests was not practiced regularly, even in an environmentally aware state like California. Rather, this survey showed that in most communities, pest levels were assessed by resident calls. This type of monitoring may not be monitoring a biological damage threshold, but a social threshold. This study provides many more insights into urban forestry as practiced in California, and provides a worthwhile example for other states about to undertake a similar task. 3.3. MONITORING AT THE LOCAL LEVEL At the local, or city level, we often equate monitoring with tree inventory. There are several types of tree inventories (Bassett, 1978; Smiley and Baker, 1988). These include specific problem inventories, partial inventories, complete inventories, and cover type surveys. Inventories can be further classified into static and continuous inventories. Specific problem inventories are usually designed to gather information about a single problem. Hazard tree inventories, pest surveys, and vacant planting site lists are classic examples of single problem inventories. Because the inventory has a precise purpose, only information pertinent to the problem need be collected. For this reason, specific problem inventories can usually be completed quickly and for relatively low cost. Partial inventories are so named because they collect the information of interest from a part or a sample of the tree population. Information on tree species, size, condition and value are often collected. Because this is a sample of the tree popu-
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lation, tree locations are usually not recorded, unless some management action is imminent. Thus, information from a sample is of limited value in scheduling tree maintenance to be performed on individual trees and species. The population of trees to be sampled can be determined by selecting some proportion of the total miles of street in the community, or a proportion of the number of blocks (Smiley, 1988). Ten percent is a typical sampling intensity. Confidence intervals or some measure of variation are rarely presented, although Mohai et al. (1978) have demonstrated procedures for optimizing sample size to minimize the coefficient of variation. Partial inventories can be very useful for meeting some objectives, but they are rarely used, perhaps due to the 'perceived difficulty of using statistical analysis. Complete inventories are those which examine the entire tree population within the specified area. These inventories may focus only on municipal trees, or they may include trees on both public and private property. In addition to collecting tree information, tree location is also established, greatly increasing the time and cost of completing the inventory, while also greatly increasing the accuracy and utility of the data. Computer printouts of all trees of a particular species that need a specific type of maintenance, or all trees on a street or block can be given to crews or contractors as work lists. If the operations performed are recorded for each tree, a history is available for help in dealing with homeowner requests. Perhaps even more important, these history data will permit monitoring species performance and maintenance cost in that specific community. Community foresters can then use species to increase benefits and reduce maintenance costs. Sometimes complete inventories are phased in over several years, especially if in-house staff or volunteers are used to perform the inventory (Graham 1987). Until the inventory is completed, it is a partial inventory, and extrapolations to the entire population can be made. Many communities opt for complete inventories, when a partial inventory would provide them the information they will use at much less cost. Before undertaking a street tree inventory, carefully consider what information will be needed and how that information will be used. Static and continuous inventories. Inventory longevity is often used to distinguish types of inventories. Specific problem and partial inventories usually provide 'snapshots' of the urban forest condition. For this reason, they must be repeated at relatively short intervals (five years?). Continuous inventories are updated constantly, which most always requires that the data be computerized. When the tree is visited or is treated, this information is added to the computerized information, so the data in the computer reflect the most recent information available about that tree. Even continuous inventories, however, must be repeated periodically because trees grow in size and their condition changes with time. Other errors also propagate in the data set. For example, removals by emergency crews, and trees planted by homeowners may not be recorded. Ten years is about the maximum interval between inventories. The cost of updating a continuous inventory will be
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Fig. 2. Aerialphotograph of city block in St. Paul, MN, showingplanting and removalneeds. Taken with 35 mm camera from a helicopter. Original slide was in color (Ektachrome),convertedto black and white for publication.
considerably less than the cost of a new inventory, because for most of the trees, the location has been determined and the data are entered; all that must be done is to inspect the tree in the field and update any changed fields in the data set. Cover type surveys have been used infrequently in urban forestry, but they provide an untapped opportunity to monitor tree cover in our communities. Hathout and Simpson (1986) successfully used aerial photographs to measure tree density in Winnipeg, Manitoba, Canada. A growing number of communities have ordinances requiring retention of tree cover during development. Aerial photographs provide one means of monitoring compliance with these ordinances. Viewing the urban forest from the air can provide benefits well worth the cost. It can provide community foresters with a "holistic" view of their entire community. Patterns of development and planting that may not be visible from the ground become obvious, and may help in completing a community pattern inventory (Johnson et al., 1990). The community forester can file this away in his head, or record the images with a 35 mm camera and a normal lens to provide a more permanent record (Figure 2).
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3.4. PROJECT LEVEL MONITORING Project level monitoring is done at the scale of a park, campus or development project. Project level monitoring may be little more than a very focussed tree inventory, or it may focus on special needs or characteristics of the site. Kelsey and Hootman (1988) inventoried parts of a campus to explore relationships between tree decline and soil characteristics. More often, however, project level monitoring involves a map of tree locations. The recent application of computer assisted drafting (CAD) to tree inventory has resulted in a sometimes useful technique (Downie, 1988; Lindhult and Ryan, 1987). These systems provide useful maps, however, their ability to integrate tree data is limited. Geographic information systems (GIS) are much more efficient at managing both map and tree data. As GIS technology becomes more affordable, more communities are implementing these systems. The community forest becomes another of the data layers in the system, much like streets, sidewalks, sewers and other utilities. The ability to access data about the trees and site constraints such as underground utilities, sidewalks or overhead wires is intriguing. However, the improved efficiency may not justify the cost of assembling these data. Several examples and results of monitoring have been presented. Keep in mind the scope and level of monitoring when interpreting the information. For example, the survey by Kielbaso (1990) estimated a total of 61 653 904 street trees in the United States. While the author rounded this to 60 million, it is based on inventories of only 16% of responding cities! Experience with communities doing inventories suggests that an estimate of the number of trees before the inventory is likely to be within 10-20% of the actual number based on inventory. The quality of the data must be considered when using the information gained by monitoring.
4. Quality Control Quality control during urban forest monitoring is often overlooked, yet it is crucial to the integrity of the data. Quality control must be designed into the inventory or monitoring process. However, descriptions of quality control programs are lacking in most references about street tree inventory. Until quality control is incorporated into the tree inventory literature, it will likely continue to be overlooked. Proper crew training is the first step in collecting accurate information. Often, data are collected by volunteers or students on summer vacation. These people should be instructed on the procedures to collect data. Each crew should have a written copy of data collecting procedures and standards with them in the field. If they encounter a tree that forks below the height at which they are to measure diameter, they can look to the standards to determine the proper procedure. There must also be a procedure in place to deal with unforeseen problems. For example, how should they handle a tree on a street with no street address? Quality control can detect and correct errors and omissions that can occur at any
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step in the monitoring process from observation of a particular trait to interpretation of the results. Data errors at the observation stage indicate insufficient training. The data collectors may not be familiar with all the tree species, leading to errors in species identification. In the data collecting standards, there should be simple guides to help the person assign the correct value to the data. For example, data collecting standards used by one of the larger private firms specializing in tree inventory contain a guide of the diagnostic features of tree species likely to be encountered during the inventory. Taking the group into an area and collecting data as a group will help the crews to better understand the procedures, and will illustrate further training needs. Another part of the data collection standards is a procedure for handling tree species and other data categories which are unknown. Even with extensive experience, some unforeseen situations will arise. Crew members must be given clear instructions for handling such situations as, for example, species which they do not recognize. This procedure should ensure that such cases do not 'drop through the cracks'. If 'UNKN' is entered for a species code, someone must return to the tree to make an identification. Any new codes, new procedures, or changes to procedures must be communicated to all crews to maintain consistency. Even when crews observe a trait correctly, they may record the data improperly. Entering the wrong code for a data iten, or entering it in the wrong place on the data sheet are common mistakes. Using mnemonic codes rather than numeric codes helps to prevent these errors. Other errors may occur because of dyslexia, carelessness, or haste. Crews are often encouraged to work quickly, but they must also be permitted to take enough time to do accurate work. A sample of each crew's work should be checked early in the inventory to make sure they are collecting accurate information. Data collectors must be aware that they will be checked, and they should be informed of the results. If problems are found, further training is indicated. When data are recorded on paper in the field, the data must be entered into a computer for further analysis. Data entry introduces another source of error into the process. Facing a large pile of data entry sheets to check against the computer file is not an exciting prospect, but it must be done. An alternative approach is to enter the data twice, compare the resulting data files, and reconcile differences. Field data recorders, including the 'palmtop' personal computers, are increasing the speed and accuracy of data collection, while decreasing cost. Instead of recording the data on paper field sheets for later entry into a computer, the data collector enters the data into the data recorder, with a keyboard or a bar-code reader. Later, the data are sent electronically to a larger computer. Increasingly sophisticated data recorders now permit data entry programs to provide menus of codes for each field, and to check the data entered against a list or range of allowable values. While this will reduce the number of errors, the data files must still be checked against trees in the field to detect and correct errors in observation or recording. Errors of omission must also be considered, not only for individual trees, but for
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whole blocks and wards. One large community found a box of data sheets that had not been entered into the computer more than one year after they thought all the data had been entered - while cleaning their office ! One way to solve this problem is to place a large map on the wall, and mark the blocks that have been examined on the ground. This also serves to motivate the crews by showing them their progress (K. Joehlin, personal communication). The blocks can be colored with a different color when the corrected data are available for computer analysis. W h e n these data are summarized, care must be taken to ensure that proper interpretations are made. Computers tend to do exactly what they are told, whether it is what we wanted or not. For example, a query of the data to determine the n u m b e r of trees along a certain street will yield erroneous results if trees on intersecting streets of c o m e r lots with the first street address are not excluded. Errors of this nature are difficult to detect by a systematic approach. Nevertheless, we must consider the possibility of such errors. Monitoring the urban forest is a much bigger, more complex job than many urban foresters realized. Even the process of tree inventory can be complicated. There are many reasons, and therefore many biological and sociological processes, to monitor. These processes can be examined at the level of individual project sites or anywhere along the continuum to national, continental or even global scales. Regardless of the project scope, the quality of the data must be known and considered in interpreting results. Monitoring is a new concept in the urban forest. Methods are still being developed and improved. If we apply what we know today, we can avoid many problems, and make living in our cities more pleasant. Using information obtained by monitoring, we can improve our management of this valuable resource, and inform and involve the public in managing their forest.
References Anonymous: 1982, Municipal Tree Management. Urban Data Service, Volume 14, Number 1. Washington, D.C.: International City Management Association, 14 pp. Anonymous: 1976, Managing Urban Trees. Urban Data Service Reports, Volume 8, Number 11, 14 PP. Bartsch, D., Hook, J., Prince, E. and Schrom, D.: 1985, 'Using Computer Simulation to Plan a Sustained Yield Urban Forest', J. For. 83, 372-375. Bassett, J.R.: 1978, 'Vegetation Inventories: Needs and Uses', Proc. Natl. Urban For. Conf. November 13-16, 1978. Washington, D.C., pp. 632-644. Bernhardt, E. and Swiecki, T.: 1988, 'The State of Urban Forestry in California'. Prepared for the California Department of Forestry and Fire Protection, Urban Forestry Program, 68 pp. Downie, A.M.: 1988, 'Firmly Planted', CADalyst 5, 31-35, Hathout, S. and Simpson, K.: 1986, 'Boulevard Tree Studies from Aerial Photographs of Winnipeg City, Manitoba, Canada', J. Env. Management 23, 203-214. Johnson, C., Baker, EA. and Johnson, W.: 1990, Urban and Community Forestry: A Guide for the Interior Western States. USDA Forest Service, Intermountain Region, Ogden, UT, 215 pp. Kelsey, P.D. and Hootman, R.G.: 1988, 'Soil and Tree Resource Inventories for Campus Landscapes', J. Arboric. 14, 243-249. Kielbaso, J.J.: 1990, 'Trends and Issues in City Forests', J. Arboric. 16, 69-76.
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Laut, J.G.: 1978, 'Detection of Insect and Disease Conditions: A Necessity for Urban Forest Inventories', Proc. NatL Urban For. Conf. November 13-16, 1978. Washington, D.C., pp. 645-649. Lindhult, M.S. and Ryan, H.D.P., III: 'Street Tree Management: The Next Generation', ArborAge 7, 13-20. Majerus, K.A.: 1988, Urban Forest Management: Guidelines for Planning and Administration, University of Illinois, Department of Forestry, 46 pp. Mohai, P., Smith, L., Valentine, E, Stiteler, W., Elias, T. and Westfall, R.: 1976, 'Structure of Urban Street Tree Populations and Sampling Designs for Estimating their Parameters', METRIA : 1, Proc. First Conf. of the Metropolitan Tree Improvement Alliance, pp. 28-43. Schroeder, H.W.: 1990, 'Perceptions and Preferences of Urban Forest Users', J. Arboric. 16, 58-61. Smiley, E.T.: 1988, 'Test Your Town's Trees', Am. For. 94, 69-72. Smiley, E.T. and Baker, EA.: 1988, 'Options in Street Tree Inventories', J. Arboric. 14, 36--42. Tate, R.L.: 1985, 'Uses of Street Tree Inventory Data', J. Arboric. 11, 210-213.
