352 but more complex designs can potentially reduce costs and standard errors of the estimate. Stratification of the population in subareas for analysis can reduce standard error if the areas have similar population structure (e.g., similar species and/or sizes). Most stratification for street trees is done based on geography (e.g., management units, neighborhoods). This type of stratification may or may not reduce standard errors, but will provide information on subareas that may be use- ful management (e.g., neighborhood analyses). Having block length information adds increased precision to the estimate and is relatively easy to obtain via TIGER/Line files (U.S. Census Bureau 2013). A GIS-based procedure is also available at no cost through the i-Tree soſtware suite (www. itreetools.org) to help randomly tor is available online (Street Tree Calculator 2015), or data an Excel® can be select spreadsheet block segments within cities. To aid in the analysis of population or sub-class population totals and standard error, calcula- run through i-Tree. In establishing a street tree sample, the following types of information should be considered: a) fund- ing—is there funding to establish a complete street tree inventory, and if not, how much is available for sampling; b) variables—what type of information is required from the sample (e.g., number of trees, tree health, maintenance needs, tree sizes, planting sites); c) precision—what is an acceptable standard error for the types of information desired; d) what types of data are available (e.g., any existing street tree data to aid in developing sample design, GIS layer of roads); and e) sample design—will simple random sampling or ratio estimates meet the desired preci- sion, or should other sample designs be developed? Adequate sample preparation and thought can help the sampling process meet the desired objec- tives of the user in the most cost-effective manner. If an urban forester would like to sample a street tree population using this procedure, potential step-by-step procedures are as follows: 1. Obtain a list of all block segments and their lengths (e.g., from the city GIS department). If lengths are not available, then obtain a list of all block segments. Block segments should have address information so they can be located in the field. Nowak et al.: Simple Street Tree Sampling 2. Load the list into a spreadsheet and ran- domly select 3% of the block segments 3. Measure all trees on selected block segments (both sides of the street) 4. Summarize data for each block segment in a spreadsheet (e.g., number of trees per block, number of 2.5 cm Acer rubrum, number of dead trees) 5. Transfer data into i-Tree spreadsheet to cal- culate totals and standard errors (Street Tree Calculator 2015) or calculate using equations given in methods 6. Optional step: Add additional randomly- selected block segments and measure trees on these block segments if desired precision is not reached in step #5. Add these new data to existing data in step #4 7. Re-measure sampled block segments in the future to calculate change Street tree sampling can also provide a relatively inexpensive means to monitor change in a street tree population. By following a sample tree popu- lation through time, information can be attained on rates of changes and factors associated with tree survival or mortality (e.g., what environmental or species factors lead to varying mortality rates). In addition, re-measurement of street tree samples can be used to generate information on tree losses and/or debris clean-up related to storms or other natural events (e.g., pest outbreaks). As street trees are only a small component of the whole urban for- est, urban foresters should also consider sampling the whole urban forest (e.g., through i-Tree pro- tocols). This additional sampling would ascertain information on the structure and values associ- ated with entire urban forest resource, as well as potential threats (e.g., pests, climate change) that may alter urban forest structure in the future. ©2015 International Society of Arboriculture
November 2015
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