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386 Nowak et al.: Effect of Plot and Sample Size on Timing and Precision
<br />Arboriculture & Urban Forestry 2008. 34(6):386-390.
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<br />ARBO LTURE
<br />URSA FORESTRY
<br />SciaMitlir Journal M It
<br />Inteln5lonal 5oeELY of ArborlclJMMllre
<br />Effect of Plot and Sample Size on Timing and Precision of
<br />Urban Forest Assessments
<br />David J. Nowak, Jeffrey T. Walton, Jack C. Stevens, Daniel E. Crane, and Robert E. Hoehn
<br />Abstract. Accurate field data can be used to assess ecosystem services from trees and to improve urban forest management, yet
<br />little is known about the optimization of field data collection in the urban environment. Various field and Geographic Information
<br />System (GIS) tests were performed to help understand how time costs and precision of tree population estimates change with
<br />varying plot and sample sizes in urban areas using random sampling approaches. Using one -tenth acre (0.04 ha) plots, it is
<br />estimated that, on average, approximately three plots per day can be measured with plot data collected on several variables for all
<br />trees greater than 1 in (2.54 cm) in diameter along with general plot, ground cover, and shrub data. A field crew of two people
<br />can gather approximately 200 one -tenth acre (0.04 ha) plots during a 14 week summer field season depending on city traffic, city
<br />area, and tree cover conditions. These 200 plots typically yield approximately a 12% relative standard error on the total number
<br />of trees.
<br />Key Words. Tree measurement; urban forest monitoring; urban forest sampling.
<br />Measuring the urban forest structure (i.e., species composi-
<br />tion, number of trees, tree sizes and locations, tree health)
<br />can give managers and planners a basis with which to develop
<br />and evaluate programs for managing urban trees and forests
<br />throughout a city. In addition, long-term monitoring of urban
<br />forest structure can provide essential data related to rates and
<br />factors of change affecting population totals, tree mortality, tree
<br />planting and natural regeneration, tree health, and species
<br />changes.
<br />An accurate quantification of urban forest structure is also
<br />needed to assess the various ecosystem services and values pro-
<br />vided by the urban forest. Urban vegetation, particularly trees,
<br />provides numerous benefits that can improve environmental
<br />quality and human health in and around urban areas. These ben-
<br />efits include improvements in air and water quality, building
<br />energy conservation, cooler air temperatures, reductions in ul-
<br />traviolet radiation, and many other environmental and social
<br />benefits (Nowak and Dwyer 2007). By having accurate infor-
<br />mation on urban forest structure, managers can understand what
<br />the current urban forest provides in terms of various en-
<br />vironmental benefits and also alter the structure of the urban
<br />forest (e.g., tree plantings, species and site selections, and tree
<br />maintenance and removals) to enhance these benefits in the fu-
<br />ture.
<br />One of the best ways to assess the entire urban forest is
<br />through sampling procedures. However, varying sample and
<br />plot sizes affect total cost (time) of data collection and the
<br />precision of the urban forest estimate. The purpose of this ar-
<br />ticle is to illustrate, based on field data collection tests, how plot
<br />and sample size of randomly located circular plots in urban
<br />areas can affect data collection time, number of permissions
<br />needed to access plots, and precision of tree cover and total
<br />tree population estimates. These types of data have been lack-
<br />ing related to urban forest sampling and can be useful in devel-
<br />oping sampling schemes to help provide desired precision of
<br />estimates and understand the costs associated with obtaining that
<br />precision.
<br />METHODS
<br />Effect of Plot Size on Data Collection Time and
<br />Total Population Estimate Precision
<br />To estimate the effect of plot size on time needed to collect field
<br />data and on total population estimates, a random sample of 26
<br />residential plots (from a total of 100 residential plots that were
<br />measured and analyzed using the Urban Forest Effects [UFORE]
<br />model in Syracuse, NY, U.S. [Nowak and Crane 2000; Nowak
<br />and O'Connor 20011) were measured and timed using a field
<br />crew of two people. Crews were trained before field data col-
<br />lection and were experienced in urban forest field data collec-
<br />tion. For each plot, permission was obtained from the lot owner
<br />(where the plot center was located) by knocking on the front
<br />door of the lot residence. If the plot encompassed more than one
<br />lot, additional lot owners were contacted for permission if trees
<br />in those additional lots were located within the plot boundary.
<br />On each plot, all UFORE variables (i-Tree 2007) were col-
<br />lected on concentric one -twenty-fourth acre (24 ft radius circle),
<br />one -tenth (37.2 ft radius), and one -sixth acre plots (48.1 ft ra-
<br />dius) (0.0168 ha [7.3 m radius], 0.04 ha [11.3 m radius], and
<br />0.067 ha [14.7 m radius] plots, respectively). These variables
<br />include several tree variables (e.g., species, diameter at breast
<br />height, crown, and health parameters) on all trees greater than 1
<br />in (2.54 cm) in diameter at breast height (4.5 ft [1.37 m]) and
<br />general plot information (e.g., location, plot center, tree and
<br />shrub cover), ground cover types, and general shrub types and
<br />dimensions. Electronic distance measuring devices were used to
<br />record trees distances from plot center and tree heights. Data
<br />collection also included measures of general plot slope and as-
<br />pect.
<br />Data collection was cumulatively timed moving from the
<br />smallest to largest plot and number of access permissions needed
<br />was recorded. Average measurement time, number of lots ac-
<br />cessed, and number of trees along with associated standard errors
<br />were assessed for each plot design. In addition, an estimated total
<br />number of trees in the residential area was calculated and com-
<br />pared with an estimate using 100 one -tenth acre (0.04 ha) plots
<br />©2008 International Society of Arboriculture
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