Arboriculture & Urban Forestry 34(6): November 2008 389 Table 3. Effect of plot size and design on number of parcels per plot, number of access permissions required, and percent tree cover in Syracuse, NY, using 2 ft resolution tree cover and land use/parcel boundary maps of 500 randomly located plots. Percent of plot area Number of parcels Plot size (ac)z 1/24 1/12 1/10 1/8 1/6 1/4 FIAr Total Perm. req.y 1.9 2.3 2.4 2.6 2.9 3.4 5.3 0.9 1.2 1.3 1.4 1.6 2.0 3.2 Perm. quest.x No perm.w 0.4 0.4 0.4 0.4 0.5 0.5 0.8 0.6 0.7 0.7 0.8 0.8 0.9 1.3 First parcelv 84 78 76 74 70 65 48 Additional parcels Perm. req.y 9 13 14 15 17 20 27 Perm. quest.x No perm.w 2 3 3 4 4 5 8 z1/24 ac 0.017 ha; 1/12 ac 0.034 ha; 1/10 ac 0.04 ha; 1/8 ac 0.05 ha; 1/6 ac 0.067 ha; 1/4 ac 0.1 ha. yPermission required (residential land). xPermission requirement is questionable; uncertain if crew would need to obtain permission (commercial/industrial; institutional; utility/transportation). wNo permission needed (greenspace; street right-of-way; vacant). vAverage percent of plot within parcel where plot center is located. uAverage tree cover in Syracuse 26.6%. tStandard error. sRelative standard error (SE/mean × 100). rUSDA Forest Service, Forest Inventory and Analysis plot design of four 1/24 ac (0.067 ha) subplots. However, when subdividing the analysis into smaller units (e.g., species, land use), the RSE will tend to increase. To increase precision for various estimates, more crews could be used to collect more plot data by either increasing plot size and/or in- crease the number of plots. In addition, stratification of plots in similar groups (e.g., land use classes, as done in the UFORE analyses) tends to increase precision. Increasing the number of plots from 200 to 500 will likely reduce the RSE on the total number of trees to 7.7% (a 36% reduction). Thus, increasing the number of plots enhances the precision of the estimate, but at an increased cost. A sampling of 150 to 200 plots is a reasonable sample size given the costs associated with measuring field plots during a summer season and a goal of maximizing reduction in SE of the estimates per unit cost. If sample size increases to greater than 200 plots, it is likely a second field crew will be needed to collect the additional plot data. Thus, increasing sample size to greater than 200 plots increases costs (adding an additional crew) with relatively minimal gains in the reduction in SE as compared with the first 200 plots sampled. Increasing the plot size from one- tenth acre (0.04 ha) to one-sixth acre (0.067 ha) will also likely reduce the RSE by approximately 16% to 20%. However, in- creasing the plot size will increase the number of permissions needing to be obtained for the sample and thus the overall project time required. CONCLUSION Data gathered on urban forest structure is essential to improve urban forest management. Random sampling offers a relatively easy means to accurately assess urban forest structure and sub- sequently estimate its ecosystem services and values. The pre- cision and cost of the estimate is dependent on sample and plot size. Managers need to plan their data collection procedures properly to ensure a desired precision of the estimate and ad- equately plan for data collection costs. Ensuring that the proper variables are collected will help guarantee that the data are useful for urban forest management. Incorporating these data within models to assess ecosystem services and values, and within long- term management and monitoring plans, can help improve urban forest health and sustain or increase urban tree cover and con- sequently environmental and human health in urban and urban- izing areas. Acknowledgments. This work was funded, in part, by the USDA Forest Service, Forest Health Monitoring Staff. We thank Sue Sissini for as- sistance with field data collection. We also thank Drs. Jerry Bond and John Stanovick for their review of an earlier draft of this manuscript. LITERATURE CITED Cumming, A.B., D.B. Twardus, and D.J. Nowak. 2008. Urban forest health monitoring: Large scale assessments in the United States. Ar- boriculture and Urban Forestry 34:341–346. Figure 1. Estimated relative standard error (SE/total × 100) of total number of trees based on varying number of total one- tenth acre (0.04 ha) field plots. Dwyer, J.F., D.J. Nowak, M.H. Noble, and S.M. Sisinni. 2000. Assess- ing our Nation’s Urban Forests: Connecting People With Ecosystems in the 21st Century. USDA Forest Service Gen. Tech. Rep. PNW- 460. 540 pp. i-Tree. 2007. i-Tree Software Suite v1.2 User’s Manual. www.itreetools. org (accessed 7/23/2007). ©2008 International Society of Arboriculture 5 7 7 7 8 8 17 Percent tree cover Meanu SEt RSEs 25.8 26.1 26.2 26.3 26.4 26.6 26.2 1.1 4.1 0.9 3.3 0.8 3.1 0.8 2.9 0.7 2.6 0.6 2.2 0.8 3.0
November 2008
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