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Applying Ecological Principles to Land-Use Decision Making in Agricultural Watersheds

  • Mary Santelmann
  • Kathryn Freemark
  • Denis White
  • Joan Nassauer
  • Mark Clark
  • Brent Danielson
  • Joseph Eilers
  • Richard M. Cruse
  • Susan Galatowitsch
  • Stephen Polasky
  • Kellie Vache
  • Junjie Wu

Abstract

The use of ecological principles and guidelines in land-use planning, as advocated by the Ecological Society of America Committee on Land Use (Dale et al., Chapter 1) will be critically important to achieving sustainable ecosystems in the next few decades as the world’s human population continues to grow and land area under human management increases. Definition of these principles and articulation of guidelines for use by planners and decision makers is an important first step, but there are many obstacles to the application of ecological guidelines in the land-use planning process. The use of alternative future scenarios can help overcome some of the difficulties associated with application of ecologically healthy land-use practices in agricultural watersheds. With the future scenario approach, abstract goals such as enhancing water quality and restoring biological diversity are translated into specific land-use practices (wetland restoration, riparian buffers, alternative cropping practices, preserves) expected to help achieve these goals. Maps and Geographic Information Systems (GIS) databases of the future alternatives become the spatial data used to evaluate the responses of the various modeled endpoints as well as the response of human perceptions of changes in land use. Alternative futures can be used to frame landscape ecological hypotheses (cf. Ahern 1999); models can then be employed to test those hypotheses and focus additional research on components that are poorly understood.

Keywords

Geographic Information System Wetland Restoration Conservation Reserve Program Agricultural Watershed Corn Belt 
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.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • Mary Santelmann
  • Kathryn Freemark
  • Denis White
  • Joan Nassauer
  • Mark Clark
  • Brent Danielson
  • Joseph Eilers
  • Richard M. Cruse
  • Susan Galatowitsch
  • Stephen Polasky
  • Kellie Vache
  • Junjie Wu

There are no affiliations available

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