Arboriculture & Urban Forestry 45(2): March 2019 the hedonic model). Significant explanatory variables reveal a marginal implicit price (or hedonic price) that represents home-buyers’ willingness to pay (WTP) for an incremental increase in that component which may be positive or negative. The hedonic price mod- elling technique has become popular in valuing eco- system services of urban forests and greenspace (Roy et al. 2012; Saphores and Li 2012). Study Location Our study was conducted in Brisbane, Australia. Bris- bane is located 500 km south of the Tropic of Capri- corn at latitude 27º 25’ south and longitude 153º 9’ east on the east coast of Australia and is the third most populated and one of the fastest growing cities in Australia (Australian Bureau of Statistics 2011). Rapid growth and changing patterns of residential development in Australian cities is reducing the space for trees on private house lots and increasing the importance of tree cover in the public realm, includ- ing streetscapes (Byrne et al. 2010; Hall 2010; Daniel 2012). In 2010, tree canopy covered 51.2% (70,673 ha [706.73 km2 ]) of the land area within the Brisbane City Council (BCC) boundaries. Almost half of Bris- bane’s tree canopy cover was growing on public land, including 4.1% (2,960 ha [29.6 km2 ]) of street tree canopies specifically within BCC road reserves. In Australia, trees in the footpath zone of the road reserve are, most often, the responsibility of the local municipality, yet residents have a strong influence on the presence and species of trees fronting their prop- erty (Kirkpatrick et al. 2012). Brisbane is a useful place to explore resident pref- erences for street tree diversity. High levels of both species richness and diversity of Brisbane’s street tree population have been reported (Plant and Sipe 2016). The municipal authority in Brisbane has also set requirements for developments to provide street frontage (verge) treatments that include a mixture of species within each level of the streetscape hierarchy to promote Brisbane’s subtropical identity (Brisbane City Council 2014). To support multipurpose street- scapes, especially walking and cycling, BCC also aims to increase tree shade along residential footpaths from 35% canopy cover, measured in 2010, to 50% by 2031 by planting a variety of shade trees along the most “shade-hungry” parts of the footpath network (Plant 2006; Favelle and Plant 2009; Brisbane City Council 2013; Davison and Kirkpatrick 2014). 43 Study Data Data from house sales between 2008 and 2010 within 80 sample sites were combined with attribute data from spatial analysis, Census 2011 data, and BCC 2010 street tree survey data. These same 80 sites were used by BCC in a separate field-based exercise to estimate street tree population, stocking level, com- position, and condition within residential suburbs (residential suburbs are defined as those suburbs with 50% or more of their land area designated in Brisbane City Council - City Plan 2000 as a type of residential zoning). The sample sites were chosen using stratified random sampling to account for the uneven distribu- tion and density of street tree canopy cover (Plant and Sipe 2016). Two data sets were analysed—house sales with street trees on their front footpath (n = 459), and house sales with street trees within 100 m of the prop- erty, but not on the front footpath (n = 1882). Four anomalies were removed from the second data set, three where average tree height was over 50 m and one where 146 species were recorded growing within 100 m of a house sale site. House, property, suburb, and street tree features used in this study are sum- marised in Table 1. Street tree features from the 2010 BCC street tree survey data were converted to four (4) continuous variables—average number and height of trees, spe- cies richness, and species diversity (Shannon Weiner Index)—and three (3) coded variables—presence of overhead powerlines, tree health, and age categories— relevant to each house sale. Dummy variables were used to test the contribution of just two scenarios of a particular attribute, such as footpath frontages with or without powerline constraints and the effect of mature and aged street trees nearby compared to all other tree age categories. Street tree age categories from the survey data were new: 0 to 2 years; juvenile: 3 to 5 years; maturing: 6 to 15 years; mature: 16 to 30 years; aged: > 30 years. Statistical Analysis A series of hedonic price models were developed from analysis of the data. Those features of street trees on the front footpath not found to be significant in the first-stage models (i.e., powerline constrained and tree health) were not tested again in the nearby streetscape data set (second stage of analysis), and species richness was only explored within 100 m of house-sales sites and not frontages. Tolerance for ©2019 International Society of Arboriculture
March 2019
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