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Urban Ecosystems

, Volume 15, Issue 3, pp 721–738 | Cite as

Long-term urbanization effects on tree canopy cover along an urban–rural gradient

  • Adam Berland
Article

Abstract

Urban forestry can benefit from improved knowledge of urbanization’s effects on tree canopy cover (TCC), a prominent urban forest indicator. This study examined changes in TCC over a long time frame, with respect to land cover (LC) changes, and across municipal boundaries. Specifically, I used air photos at 14 dates from 1937 to 2009 to develop an exceptionally long record of TCC change in Minnesota’s Twin Cities Metropolitan Area. During the study period overall TCC nearly doubled from 17% to 33% while the proportion urban land cover rose by 47%, highlighting the opportunity for substantial TCC gains following urbanization in previously agricultural landscapes, even in regions that were forested prior to European settlement. Results demonstrate that more intensely developed sites generally had lower TCC, and older urban sites had higher TCC. Modern TCC was not adequately characterized by linear distance along the urban–rural gradient, but instead peaked near the center of the gradient where mature residential neighborhoods are prevalent. Compared to other land cover changes, urbanization events caused the highest rate of immediate TCC loss (9.6% of events), yet urban areas had the second highest TCC (>35%) in 2009, indicating that urban land gained TCC relatively efficiently following development. The results of this study provide new historical context for urban forest management across an urban–rural gradient, and emphasize the need to consider ecological legacies and temporal lags following land cover changes when considering TCC goals in urban settings.

Keywords

Urban forest Tree canopy cover Urban–rural gradient Aerial photography Minnesota 

Abbreviations

ANOVA

Analysis of variance

GIS

Geographic information system

LC

Land cover

TCC

Tree canopy cover

TCMA

Twin Cities Metropolitan Area

Notes

Acknowledgements

Air photos were obtained from the Minnesota Geospatial Information Office (http://www.mngeo.state.mn.us/) and the University of Minnesota’s John R. Borchert Map Library (http://map.lib.umn.edu/mhapo/index.html). Impervious surface data were obtained from the University of Minnesota’s Remote Sensing and Geospatial Analysis Laboratory (http://land.umn.edu/). All websites remain accessible as of 22 June 2011. Thanks to Steve Manson for helpful comments on the manuscript. The research was supported by the University of Minnesota’s Doctoral Dissertation Fellowship.

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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  1. 1.Department of GeographyUniversity of MinnesotaMinneapolisUSA

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