294 Roman et al: Common Practices and Challenges for Urban Tree Monitoring Programs related to survival, such as species, planting stock, and mainte- nance. One participant explained the program goals as follows: [Our organization] had an assumed survival rate when I start- ed, but nothing to back it up. I wanted to have a legit number that we can claim as the success of our planting and care work. Another common motivation was conducting monitor- ing as a proactive approach toward tree care, maintenance, and management (44%). Monitoring data collection was some- times done at the same time as, or in preparation for, tree maintenance work. Twenty-one percent of program—mostly at non-profit organizations—conducted tree monitoring to educate and engage volunteers, residents, and communities. Tree monitoring programs were sometimes required by grants or contract obligations; 16% of programs men- tioned this as part of their motivation for conducting moni- toring. Of all programs, 51% had external funding, and of those with funding, monitoring was required for 48%. Monitoring Methods Programs developed their field methods for urban forest monitor- ing using a mix of in-house program staff (46%) and external assistance (17%). Participants worked with paid consultants, uni- versity or USDA Forest Service researchers, and other local ur- ban forestry organizations. Some programs (12%) adapted their monitoring methods from the i-Tree inventory software (www. itreetools.org), which was developed by the Forest Service. Field work was carried out mostly by program staff (62%), followed by volunteers (42%), arborists (36%), researchers (16%), in- terns (16%), and contractors (4%). Thirty-three percent of pro- grams developed a field manual for their monitoring project. The most commonly recorded tree characteristics for urban tree monitoring programs were species (96%), condition rat- ing (89%), mortality status (76%), diameter at breast height (DBH; 71%), and specific health problems (67%). Many other tree size metrics, maintenance issues, and site characteristics were recorded (Table 1). Half (53%) of the programs exclu- sively monitor trees planted by their organization, while others monitor only trees not planted by their organization (9%) or both (38%). Street trees were the most common (86%) type of tree location included in these programs, followed by public park trees (45%), institutional trees (34%), resi- dential yard trees (25%), conservation areas (7%), and other (14%). The most common way to record tree location was street address (78%), with many other techniques employed (Table 2); tree location was often recorded in several ways. The sampling designs for these monitoring programs also varied widely. Seventy-three percent used a complete survey of all trees in a particular program or neighborhood, 16% used a stratified random sample, 9% used a simple random sample, 7% used a convenience sample (i.e., trees or plots selected based on convenience for program personnel), 7% used a targeted sample (i.e., trees chosen based on program interests, such as limiting to a few species), and 4% used another sampling technique. In terms of observation intervals, 64% of programs used a fixed time interval, 43% used a one-time monitoring of recently planted trees, 18% used a rolling schedule (e.g., visit 20% of all trees every year, to reach all trees in five years), and 30% used another observation interval. Some of these monitoring programs were very recently implemented (43% of programs ©2013 International Society of Arboriculture had been instituted within 1–5 years of the survey), while other programs were well established within the organization (26% for 6–10 years, 14% for 11–20 years, and 17% for >20 years). Monitoring data were managed using a wide assortment of software, including Excel (49%), Access (44%), GIS (22%), i-Tree (18%), Lucity (7%), TreeKeeper (4%), and other (20%). Thirty-seven percent of programs have a paid staffer dedicated to the management of tree monitoring databases. Table 1. Field data included by practitioner-based urban tree monitoring programs (n = 45). Data collected Tree characteristics Species Health condition rating Mortality status Diameter at breast height Specific health problems Height Canopy width Canopy dieback Maintenance issues Pruning Watering Mulching Infrastructure conflicts Staking Other tree care issues Site characteristics Location type Land use Ground cover Soil characteristics Canopy cover Other site characteristics Other Percent of total 96% 89% 76% 71% 67% 38% 31% 27% 56% 47% 47% 42% 36% 9% 47% 36% 27% 13% 4% 13% 13% Table 2. Methods of recording tree location in monitoring programs (n = 45). Method Street address GPS Site maps Tree tags Google maps Reference point Map cell number Other Percent of total 78% 42% 31% 16% 13% 11% 4% 18% Challenges with Monitoring Resource limitation (63%) was the most common challenge to urban tree monitoring at these organizations. Specifi- cally, 50% mentioned lack of staff time and 25% mentioned lack of dedicated funding. Data management and technol- ogy challenges were also common (47%), such as time-in- tensive data entry and management, identifying appropri- ate software for long-term tree records, and adapting other technologies for tree monitoring. Twenty-eight percent of organizations had challenges developing protocols, includ- ing deciding what data to collect, subjectivity of tree con- dition ratings, and instituting quality assurance and quality
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