Conservation Genetics

, Volume 14, Issue 1, pp 41–53 | Cite as

Effects of urbanization on Song Sparrow (Melospiza melodia) population connectivity

  • Thomas M. UnfriedEmail author
  • Lorenz Hauser
  • John M. Marzluff
Research Article


Urbanization may affect genetic differentiation among animal populations because it converts native vegetation to novel land cover types that can affect population connectivity. The effect of land cover change on genetic differentiation may vary among taxa; mobile birds may be least affected. Regardless, genetic differentiation between populations should be best predicted by measures of distance that incorporate the effect of land cover on movement. We studied the relationship between land cover and genetic differentiation in Song Sparrows (Melospiza melodia) at eighteen sites in the Seattle metropolitan region. We generated a series of hypothetical “resistance surfaces” based on land cover and development age, calculated “resistance distances” between pairs of sampling sites, and related them to pairwise genetic differentiation. Genetic differentiation was best described by a multiple regression model where resistance to gene flow (1) linearly increased with age of development and (2) was greater in high- and medium-density urbanization than in native forest land cover types (R 2 = 0.15; p = 0.003). The single variable with the highest correlation with genetic differentiation was derived from a linear relationship between development age and resistance (R 2 = 0.08; p = 0.007). Our results thus suggested that urban development reduced population connectivity for Song Sparrows. However, the relation of development age to genetic differentiation suggested that equilibrium was not yet reached. Hence, the effects of lost connectivity will increase. Our understanding of the landscape genetics of this recently anthropogenically modified landscape benefited from considering population history.


Urban ecology Avian population biology Landscape genetics Bird dispersal Landscape resistance Least cost path analysis 



M. Alberti and J. Hepinstall of the University of Washington’s Urban Ecology Research Laboratory provided the classified Landsat TM imagery. Sample collection was aided by M. D. Oleyar, S. Rullman, K. Whittaker, J. Delap, M. Dickerson, and C. Templeton. J. Lawler provided computing resources. Molecular laboratory and analytical assistance was provided by T. R. Seamons, M. Baird, L. Newton, B. Godfrey, and H. D. Bradshaw. The research was conducted under an animal use protocol overseen by the University of Washington IACUC and permits issued by the Washington Department of Fish & Wildlife and USGS Bird Banding Laboratory. This material is based upon work supported under a National Science Foundation Graduate Research Fellowship to TMU. Project funding was also provided by NSF Integrative Graduate Education and Research Traineeship for Urban Ecology (National Science Foundation awards DEB-9875041, BCS0120024, BCS 0508002 and IGERT0114351), Achievement Rewards for College Scientists Seattle Chapter, and University of Washington College of Forest Resources. We thank R. Holderegger and four anonymous reviewers for helpful comments on this manuscript.

Supplementary material

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Copyright information

© Springer Science+Business Media Dordrecht 2012

Authors and Affiliations

  • Thomas M. Unfried
    • 1
    • 3
    Email author
  • Lorenz Hauser
    • 2
  • John M. Marzluff
    • 1
  1. 1.School of Environmental and Forest SciencesUniversity of WashingtonSeattleUSA
  2. 2.School of Aquatic and Fishery SciencesUniversity of WashingtonSeattleUSA
  3. 3.BellinghamUSA

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