Landscape Ecology

, Volume 26, Issue 7, pp 983–997 | Cite as

Scaling relations between riparian vegetation and stream order in the Whitewater River network, Kansas, USA

  • William C. Dunn
  • Bruce T. Milne
  • Ricardo Mantilla
  • Vijay K. Gupta
Research Article


Riparian communities have been well-studied along individual streams, but not within the context of networks of which streams are a part. To study networks, hydrologists use Horton–Strahler ordering to assign streams to discrete categories in which increasing numerical value (ω) reflects increasing size of the stream and complexity of the network. A key use of this classification method has been to demonstrate scaling relations between hydrogeomorphic variables and order. These relations now provide a foundation to determine how ecological processes are associated with the geometry and topology of river networks. We used geographic information systems (GIS) to map and measure the stream network and riparian vegetation of the Whitewater River basin of eastern Kansas, USA. With the resulting data, we tested if (1) riparian vegetation scaled with order, and (2) riparian vegetation at confluences of two streams differed from that found along constituent streams. Most characteristics of riparian vegetation scaled with order. In confluence zones, density and diversity of riparian vegetation generally were equivalent to that of the largest constituent stream. Scaling relations between riparian vegetation and order provide a framework to quantify the role of riparian vegetation in the water balance of stream networks and a tool to predict area and distribution of riparian vegetation from network topology.


Basins Horton laws Horton–Strahler Network Order Riparian Scaling Self-similarity Streams 



T. and P. Neville, New Mexico Natural Heritage Program, and K. Menke, BirdsEyeView GIS, Inc. assisted with GIS analyses. H. Delaney, University of New Mexico, assisted with statistical analysis. J. H. Brown, University of New Mexico, and two anonymous reviewers provided helpful comments of earlier drafts. This study was partially funded by NSF Grant No. 04-50385 to the University of New Mexico, and NSF Grant No. EAR 1005311 to the University of Colorado.


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • William C. Dunn
    • 1
  • Bruce T. Milne
    • 1
  • Ricardo Mantilla
    • 2
  • Vijay K. Gupta
    • 3
  1. 1.Department of Biology, 1 MSC 03 2020University of New MexicoAlbuquerqueUSA
  2. 2.IIHR—Hydroscience & EngineeringThe University of IowaIowa CityUSA
  3. 3.Department of Civil, Environmental and Architectural Engineering, Cooperative Institute for Research in Environmental SciencesUniversity of ColoradoBoulderUSA

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