Sampling variation in macroinvertebrate data and implications for river quality indices

By R. Clarke, M. Furse, R. Gunn, J. Winder, J. Wright. 2002

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A review of approaches for classifying benthic habitats and evaluating habitat quality. (2004, background): “Variation in natural phenomena, sampling strategy and differences in operator efficiency have also been highlighted as potential sources of bias that may lead to misinterpretation (Gammon and Simon, 2000; Fore et al., 2001; Clarke et al., 2002; Dauwalter and Pert, 2003; Reynolds et al., 2003).”
Effects of sampling and sub-sampling variation using the STAR-AQEM sampling protocol on the precision of macroinvertebrate metrics (2006, methodology): “For example, Clarke et al. (2002) found that the variance in the number of macroinvertebrate taxa found in replicate RIVPACS samples increased roughly in proportion to the average number of taxa found in samples from the same site, but that by transforming the data, the replicate variability in the…”
Assessing the impact of errors in sorting and identifying macroinvertebrate samples (2006, background): “It arises from every stage of data collection, from sampling (e.g. Carter & Resh, 2001; Clarke et al., 2002; Ostermiller & Hawkins, 2004) to sample analysis and data handling (e.”