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Influence of riffle and snag habitat specific sampling on stream macroinvertebrate assemblage measures in bioassessment

Wang, L. Z., Weigel, B. W., Kanehl, P., and Lohman, K., 2006, Influence of riffle and snag habitat specific sampling on stream macroinvertebrate assemblage measures in bioassessment: Environmental Monitoring and Assessment, v. 119, no. 1-3, p. 245-273.

Abstract

Stream macroinvertebrate communities vary naturally among types of habitats where they are sampled, which affects the results of environmental assessment. We analyzed macroinvertebrates collected from riffle and snag habitats to evaluate influences of habitat-specific sampling on taxon occurrence, assemblage measures, and biotic indices. We found considerably more macroinvertebrate taxa unique to snags (143 taxa) than to riffles (75 taxa), and the numbers of taxa found in both riffles and snags (149 taxa) were similar to that found in snags. About 64% of the 47 macroinvertebrate measures we tested differed significantly between riffles and snags. Eighty percent intercepts of regressions between biotic indices and urban or agricultural land uses differed significantly between riffles and snags. The Hilsenhoff biotic index calculated from snag samples explained 69% of the variance of riffle samples and classified 66% of the sites into the same stream health group as the riffle samples. However, four multimetric indices for snag samples explained less than 50% of the variance of riffle samples and classified less than 50% of the sites into the same health group as the riffle samples. We concluded that macroinvertebrate indices developed for riffle/run habitat should not be used for snag samples to assess stream impairment. We recommend developing an index of biotic integrity specifically for snags and using snags as an alternate sampling substrate for streams that naturally lack riffles.

Keywords

Macro invertebrate, streams, bias, riffle habitat, snag habitat, macroinvertebrate biotic index, environmental impacts, habitat-specific sampling, multiple spatial scales, benthic invertebrates, forest ecoregion, northern lakes, rivers, classification, prediction, integrity, index