Ecosystems

, Volume 9, Issue 4, pp 578–597 | Cite as

Characterization of Households and its Implications for the Vegetation of Urban Ecosystems

  • J. M. Grove
  • A. R. Troy
  • J. P. M. O’Neil-Dunne
  • W. R. BurchJr.
  • M. L. Cadenasso
  • S. T. A. Pickett
Article

Abstract

Our understanding of the dynamics of urban ecosystems can be enhanced by examining the multidimensional social characteristics of households. To this end, we investigated the relative significance of three social theories of household structure—population, lifestyle behavior, and social stratification—to the distribution of vegetation cover in Baltimore, Maryland, USA. Our ability to assess the relative significance of these theories depended on fine-scale social and biophysical data. We distinguished among vegetation in three areas hypothesized to be differentially linked to these social theories: riparian areas, private lands, and public rights-of-way (PROWs). Using a multimodel inferential approach, we found that variation of vegetation cover in riparian areas was not explained by any of the three theories and that lifestyle behavior was the best predictor of vegetation cover on private lands. Surprisingly, lifestyle behavior was also the best predictor of vegetation cover in PROWs. The inclusion of a quadratic term for housing age significantly improved the models. Based on these research results, we question the exclusive use of income and education as the standard variables to explain variations in vegetation cover in urban ecological systems. We further suggest that the management of urban vegetation can be improved by developing environmental marketing strategies that address the underlying household motivations for and participation in local land management.

Keywords

urban ecology population household social stratification lifestyle behavior vegetation Baltimore long term ecological research (LTER) 

Notes

AcknowledgEments

We thank the US Forest Service’s Northeastern Research Station and Northeastern Area State and Private Forestry Program (USDA 03-CA-11244225-531), and the National Science Foundation for their support of the Baltimore ecosystem study, long-term ecological research (LTER) project (NSF DEB-9714835). We also thank the Maryland Department of Natural Resources’ Forest Service, the City of Baltimore, Space Imaging, LLC, and the Parks and People Foundation for their generous contribution of data and expertise to this project. This paper has benefited from insights gained through interactions since 1989 with generous collaborators, students, and community partners from Baltimore. We thank Amy Bigham for her assistance with the figures in this manuscript and John Stanovick, Peter Groffman, Erika Svendsen, and Amanda Vemuri for their comments on earlier drafts. Paige Warren helped to clarify research from the CAP LTER. Ann Kinzig, Paige Warren, and Chris Martin have shared ideas about comparable work at the CAP LTER. Paul Robbins provided crucial and timely help with some of his publications. Two anonymous reviewers and Jack Liu provided constructive comments and suggestions that greatly improved the paper.

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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • J. M. Grove
    • 1
  • A. R. Troy
    • 2
  • J. P. M. O’Neil-Dunne
    • 2
  • W. R. BurchJr.
    • 3
  • M. L. Cadenasso
    • 3
  • S. T. A. Pickett
    • 4
  1. 1.Northeastern Research StationUSDA Forest ServiceSouth BurlingtonUSA
  2. 2.Rubenstein School of Environment and Natural Resources, Aiken CenterUniversity of VermontBurlingtonUSA
  3. 3.School of Forestry and Environmental StudiesYale UniversityNew HavenUSA
  4. 4.Institute of Ecosystem StudiesMillbrookUSA

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