Assessing the condition of the Missouri, Ohio, and Upper Mississippi rivers (USA) using diatom-based indicators
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  • 作者：Amy R. Kireta (1) akireta@d.umn.edu
    Euan D. Reavie (1)
    Gerald V. Sgro (2)
    Ted R. Angradi (3)
    David W. Bolgrien (3)
    Terri M. Jicha (3)
    Brian H. Hill (3)
  • 关键词：Diatoms &#8211 ; Great rivers &#8211 ; Monitoring &#8211 ; Transfer functions
  • 刊名：Hydrobiologia
  • 出版年：2012
  • 出版时间：July 2012
  • 年：2012
  • 卷：691
  • 期：1
  • 页码：171-188
  • 全文大小：632.8 KB
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  • 作者单位：1. Center for Water and the Environment, Natural Resources Research Institute, University of Minnesota Duluth, 1900 East Camp Street, Ely, MN 55731, USA2. Department of Biology, John Carroll University, 20700 North Park Boulevard, University Heights, OH 44118, USA3. Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, US Environmental Protection Agency, 6201 Congdon Boulevard, Duluth, MN 55804, USA
  • 刊物类别：Biomedical and Life Sciences
  • 刊物主题：Life Sciences
    Hydrobiology
    Ecology
  • 出版者：Springer Netherlands
  • ISSN：1573-5117
文摘
Diatom-based indicators were developed to assess environmental conditions in the Missouri, Ohio, and Upper Mississippi rivers. Disturbance gradients, comprising the first two principal components derived from a suite of stressor variables, included a trophic gradient (Trophic) and a gradient reflecting agriculture and other development activities (Ag/Dev). Diatom-based indicators were developed by creating models using weighted average calibration and regression-based transfer functions to relate planktonic and periphytic diatom species assemblages to each disturbance gradient. The most predictive disturbance models combined phytoplankton and periphyton assemblages into a single bioindicator model (observed versus inferred: Trophic r\textboot2 = 0. 5 6 r_{\text{boot}}^{2} = 0. 5 6 ; Ag/Dev r\textboot2 = 0. 7 0 r_{\text{boot}}^{2} = 0. 7 0 ). The geographic applicability of bioindicators was assessed by limiting sample geographical range during model calibrations. Geographic scale was limited by creating bioindicators using samples from: (a) each river, and (b) combined Mississippi/Missouri samples excluding Ohio River sites which were chemically unique. Indicator performance decreased with geographically restrictive models, therefore river basin-wide models, developed across all three rivers, is recommended. The most effective diatom-based disturbance bioindicators for this great river ecosystem could be applied using phytoplankton, periphyton, or combined assemblages to infer both trophic and agriculture/development disturbances.

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