Explaining variation in front gardens between suburbs of Hobart, Tasmania, Australia
Kirkpatrick, JB and Daniels, G and Zagorski, T, Explaining variation in front gardens between suburbs of Hobart, Tasmania, Australia, Landscape and Urban Planning, 79, (3-4) pp. 314-322. ISSN 0169-2046 (2007) [Refereed Article]
This paper determines the relationships between the dependent variables, presence of trees in front garden and front garden type, and socio-economic, environmental and demographic variables, at the suburb scale in Hobart, Tasmania, Australia. Garden type, largely following a pre-existing classification, and the presence/absence of trees, were recorded from 50 randomly located front gardens in each of 31 suburbs. The suburbs were classified into four groups on the basis of their spectrum of garden types and the percentage frequency of trees. Group one consisted of coastal suburbs of relatively high socio-economic status. Group 2 consisted of suburbs of moderate socio-economic status. Group 3 consisted of the poorest suburbs. The fourth group was composed of suburbs of high socio-economic status, located close to the centre of the city in hilly terrain. All except the rarest garden type occurred in all four groups of suburbs. Multiple regression and general linear models were used to predict tree presence, and the prevalence of particular garden types at the suburb level. Household income was the best predictor of the percentage frequency of trees in front gardens. The variables that appeared in models for garden types were: the percentage of the population with tertiary education (four instances); percentage of population older than 65 years (4); household income (3); percentage of households renting dwellings (3); altitude (3), rainfall (3); unemployment rate (2); percentage of population born in Australia (2); percentage of medium-sized gardens (2); suburb age (1); percentage of workforce in professional and managerial occupations (1). The 12 garden types that could be modelled responded individualistically to these independent variables.