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This article in JEQ

  1. Vol. 24 No. 3, p. 516-526
     
    Received: Mar 18, 1994
    Published: May, 1995


    * Corresponding author(s):
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doi:10.2134/jeq1995.00472425002400030019x

Soil Characteristics of Oak Stands along an Urban-Rural Land-Use Gradient

  1. Richard V. Pouyat *,
  2. Mark J. McDonnell and
  3. S. T. A. Pickett
  1. USDA-Forest Service, Northeastern Forest Exp. Station, c/o Inst. of Ecosystem Studies, P.O. Box AB, Millbrook, NY 12545;
    Bartlett Arboretum, Univ. of Connecticut, Stamford, CT 06903;
    Inst. of Ecosystem Studies.

Abstract

Abstract

Urban-rural land-use gradients are environmental gradients determined by human-built structures and human activity. Although gradients of land use are readily measurable, little is known about the effects of urbanization on forest soil properties. In this research, soil properties were quantified in oak stands (Quercus sp.) along an urban-rural transect in the New York City metropolitan area. A suite of 25 soil chemical properties were subjected to a Principal Component Analysis to ordinate stands. The first principal component (PC1) accounted for 42.3% of the variation. Positive loadings of PC1 corresponded to high concentrations of Pb, Cu, Ni, Ca, Mg, and K; high total soluble salt concentrations; high organic matter; high total N; and slightly more soil acidity. Stands located closer to the urban core had positive loadings on PC1; sites located beyond 30 km of the urban core had negative loadings. The variation accounted for by PC1 was significantly explained (P < 0.005) by measures of urban development quantified along the transect, including percent urban cover (r2 = 0.735), population density (r2 = 0.700), traffic volume (r2 = 0.778), and road density (r2 = 0.700). Of the heavy metals measured, Cu and Pb showed a 2.5- to fourfold increase in concentration from the rural to the urban land use types, with maximum concentrations for Cu reaching 49.3 mg kg−1 and Pb 181.4 mg kg−1 in the urban sites, repectively. More transects must be established in this and other metropolitan areas to build a data base to develop predictive models of ecosystem change, given the amount and type of urban development in a landscape.

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