The Index of Biological Integrity and the bootstrap: Can random sampling error affect stream impairment decisions?

Christine L. Dolph, Aleksey Y. Sheshukov, Christopher J. Chizinski, Bruce Vondracek, Bruce Wilson

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

Multimetric indices, such as the Index of Biological Integrity (IBI), are increasingly used by management agencies to determine whether surface water quality is impaired. However, important questions about the variability of these indices have not been thoroughly addressed in the scientific literature. In this study, we used a bootstrap approach to quantify variability associated with fish IBIs developed for streams in two Minnesota river basins. We further placed this variability into a management context by comparing it to impairment thresholds currently used in water quality determinations for Minnesota streams. We found that 95% confidence intervals ranged as high as 40 points for IBIs scored on a 0-100 point scale. However, on average, 90% of IBI scores calculated from bootstrap replicate samples for a given stream site yielded the same impairment status as the original IBI score. We suggest that sampling variability in IBI scores is related to both the number of fish and the number of rare taxa in a field collection. A comparison of the effects of different scoring methods on IBI variability indicates that a continuous scoring method may reduce the amount of bias in IBI scores.

Original languageEnglish (US)
Pages (from-to)527-537
Number of pages11
JournalEcological Indicators
Volume10
Issue number2
DOIs
StatePublished - Mar 2010

Bibliographical note

Funding Information:
The authors thank David Wright and the Minnesota Department of Natural Resources for funding this research, and Scott Niemela, Joel Chirhart, and Mike Feist and the Minnesota Pollution Control Agency for providing biomonitoring data, IBI scoring criteria, and assistance in developing and carrying out project objectives. We also thank Leska Fore, Scott Niemela, and two anonymous reviewers for highly constructive reviews of this manuscript. The use of trade, product, industry or firm names or products or software or models, whether commercially available or not, is for informative purposes only and does not constitute an endorsement by the U.S. Government or the U.S. Geological Survey.

Keywords

  • Bioassessment
  • Fish
  • Multimetric
  • Nonparametric
  • Rare
  • Streams
  • Variability

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