Environmental Monitoring and Assessment

, Volume 157, Issue 1–4, pp 113–124 | Cite as

Linking multimetric and multivariate approaches to assess the ecological condition of streams



Few attempts have been made to combine multimetric and multivariate analyses for bioassessment despite recognition that an integrated method could yield powerful tools for bioassessment. An approach is described that integrates eight macroinvertebrate community metrics into a Principal Components Analysis to develop a Multivariate Condition Score (MCS) from a calibration dataset of 511 samples. The MCS is compared to an Index of Biotic Integrity (IBI) derived using the same metrics based on the ratio to the reference site mean. Both approaches were highly correlated although the MCS appeared to offer greater potential for discriminating a wider range of impaired conditions. Both the MCS and IBI displayed low temporal variability within reference sites, and were able to distinguish between reference conditions and low levels of catchment modification and local habitat degradation, although neither discriminated among three levels of low impact. Pseudosamples developed to test the response of the metric aggregation approaches to organic enrichment, urban, mining, pastoral and logging stressor scenarios ranked pressures in the same order, but the MCS provided a lower score for the urban scenario and a higher score for the pastoral scenario. The MCS was calculated for an independent test dataset of urban and reference sites, and yielded similar results to the IBI. Although both methods performed comparably, the MCS approach may have some advantages because it removes the subjectivity of assigning thresholds for scoring biological condition, and it appears to discriminate a wider range of degraded conditions.


Macroinvertebrate Bioassessment Biomonitoring Ordination New Zealand 


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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  1. 1.Environment WaikatoHamilton EastNew Zealand
  2. 2.Centre for Biodiversity and Ecology ResearchThe University of WaikatoHamiltonNew Zealand

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