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Application of Multiple Index Development Approaches to Benthic Invertebrate Data from the Virginian Biogeographic Province, USA
Citation:
PELLETIER, M. C., A. J. Gold, L. Gonzalez, AND C. Oviatt. Application of Multiple Index Development Approaches to Benthic Invertebrate Data from the Virginian Biogeographic Province, USA. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, 23:176-188, (2012).
Impact/Purpose:
Macroinvertebrates are commonly used as biomonitors to detect pollution impacts in estuaries. The condition of these communities has been commonly assessed using benthic indices, which can be assembled using a variety of techniques. The goal of this research was to assess three common approaches used in the United States to develop indices using available monitoring data from the US Environmental Protection Agency=s Environmental Monitoring and Assessment Program. Although the Chesapeake Bay IBI approach has been successfully utilized in the area for which it was developed, it did not perform well in this study. In contrast, another multimetric approach, the Mebane IBI approach, performed well, as did the multivariate logistic regression approach. The results from this study were within the range of accuracies seen with other studies. The Mebane IBI approach produced index values that were relatively stable across habitats, implying that important natural environmental gradients have been accounted for. In contrast the logistic regression approach had different index values across habitats and so may be able to distinguish potential contaminant differences in sand and mud. In addition, this technique allows an approved method to select a more parsimonious model. Both techniques have promise for index development and could be useful in applying a biological condition gradient to estuaries.
Description:
Previous work had indicated that the Virginian Province Index did not perform well in a smaller estuarine complex. While it was hoped that the existing Chesapeake Bay Benthic Index of Biotic Integrity, with its greater number of metrics and habitat separation would be more adaptable, this index also did not perform well outside of Chesapeake Bay. In this study we assembled additional metrics and applied different methods of index compilation to explore the indices relative strengths and weaknesses. Three different approaches were utilized -- two multimetric indices (Chesapeake Bay IBI and the Mebane IBI) and a multivariate logistic regression technique. The data were subdivided by habitat (salinity and grain size), and indices compiled using the same initial group of benthic metrics. Each approach was examined for its classification accuracy for both reference and impaired sites for the entire Virginian Province. The Chesapeake Bay IBI approach did not perform well in this study. In contrast, another multimetric approach, the Mebane IBI approach, performed well, as did the multivariate logistic regression approach. Both techniques have promise for index development and could be useful in applying a biological condition gradient to estuaries.