Using the Urban–Rural Gradient Approach to Determine the Effects of Land Use on Forest Remnants

  • Margaret M. Carreiro

Urban growth provides many benefits to people by bringing economic and cultural vitality to a region. However, the landscape modification and pollution that follow urbanization profoundly alter the organisms and ecological functions occurring on land and in water bodies, like streams, that drain the land. As stress on our natural environment increases, we lose the ecosystem services they once provided free of charge to society (air and water purification, soil stabilization, flood control, meso- and microclimate modification, pest and disease control) (Daily et al., 1997; Millennium Ecosystem Assessment, 2005; Farber et al., 2006; see also Chapter 5). Often these ecological services must then be replaced with expensive engineered solutions to reduce negative impacts on people’s physical and psychological well-being (Farber, 2005). To decrease the unintended negative consequences of city growth, there needs to be increased recognition among planners and policy makers that natural habitats and other green spaces in metropolitan areas are vital infrastructural components of a functioning urban ecosystem, as vital to our quality of life as our engineered infrastructure (Alberti et al., 1999; see also Chapter 2). There is an obvious and pressing need to find integrated ways to work “with” instead of “against” nature to create cities that are more resource efficient and more resilient to fluctuations in economic and environmental forces, and that provide healthier conditions so people can not only exist but also thrive (Grimm et al., 2000). While some solutions are useful for many cities, others must be tailored to the geographic location, history, culture, and resources of each individual city. Indeed, many chapters in this book offer examples of such general as well as locally tailored solutions and plans.


York City Urban Forest Urban Ecosystem Forest Remnant Rural Gradient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Margaret M. Carreiro
    • 1
  1. 1.Department of BiologyUniversity of LouisvilleLouisvilleUSA

Personalised recommendations