, 12:604 | Cite as

Socio-Economics and Vegetation Change in Urban Ecosystems: Patterns in Space and Time

  • Gary W. LuckEmail author
  • Lisa T. Smallbone
  • Rachel O’Brien


By 2050, 70% of the Earth’s human population will live in urban areas. Urbanization can have a devastating impact on local ecosystems, but these impacts vary across time and space. Identifying links between spatiotemporal change in urban ecosystems and neighborhood socio-economics is crucial to management aimed at maintaining flora and fauna in urban areas. Here, we tracked 20 years of socio-economic change and 15 years of vegetation change in 32 residential neighborhoods in south-eastern Australia. Regression models that explicitly accounted for a time lag between neighborhood socio-economic characteristics and vegetation response explained more variation in vegetation cover than models that ignored the effects of time. Also, relationships between vegetation and socio-economic factors were stronger in later years for the same neighborhoods suggesting the influence of socio-economics is more readily identified in established neighborhoods. Socio-economic variables alone, or in combination with biophysical variables, were better predictors of vegetation cover than only biophysical variables. Across space, vegetation cover had a negative quadratic relationship with neighborhood housing density, peaking at mid-density values, and a positive relationship with education level and immigration status (the percentage of residents with a non-Australian background). Over time, housing density had a positive relationship with vegetation cover, reflecting an increase in vegetation as neighborhoods develop. Our results highlight the need to understand temporal context when attempting to explain contemporary patterns in vegetation cover and the increasing importance of socio-economic factors in influencing cover as neighborhoods become established.


urban ecosystems vegetation cover vegetation change socio-economics urbanization spatiotemporal patterns time lag 



This project was funded by an Australian Research Council Discovery Grant (DP0770261). Thanks to Simon McDonald (Spatial Data Analysis Network, Charles Sturt University) for assistance with remote sensing and GIS analyses and local government authorities in each study area for guidance in the collection of field data. Penny Davidson, Ian Lunt, Digby Race, and two anonymous reviewers provided thoughtful comments on a draft manuscript. The NCAS data were used under licence agreement from the Department of Climate Change© Commonwealth of Australia.

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Gary W. Luck
    • 1
    Email author
  • Lisa T. Smallbone
    • 1
  • Rachel O’Brien
    • 1
  1. 1.Institute for Land Water and SocietyCharles Sturt UniversityAlburyAustralia

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