Effects of sampling and sub-sampling variation using the STAR-AQEM sampling protocol on the precision of macroinvertebrate metrics

Abstract

As part of the extensive field sampling programme within the European Union STAR project, replicate macroinvertebrate samples were taken using the STAR-AQEM sampling method at each of 2-13 sites of varying ecological quality within each of 15 stream types spread over 12 countries throughout Europe. The STAR-AQEM method requires the sub-sampling and taxonomic identification of at least onesixth of the sample and at least 700 individuals. Replicate sub-samples were also taken at most of these sites. Sub-sampling effects caused more than 50% of the overall variance between replicate samples values for 12 of the 27 macroinvertebrate metrics analysed and was generally greatest for metrics that depend on the number of taxa present. The sampling precision of each metric was estimated by the overall replicate sampling variance as a percentage P samp of the total variance in metric values within a stream type. Average over all stream types, the three Saprobic indices had the lowest percentage sampling variances with median values of only 3-6%. Most of the metrics had typical replicate sampling variances of 8-18% of the total variability within a stream type; this gives rise to estimated rates of mis-classifying sites to ecological status class of between 22 and 55% with an average of about 40%. This suggests that the precision of such metrics based on the STAR-AQEM method is only sufficient to indicate gross changes in the ecological status of sites, but there will be considerable uncertainty in the assignment of sites to adjacent status classes. These estimates can be used to provide information on the effects of STAR-AQEM sampling variation on the expected uncertainty in multi-metric assessments of the ecological status of sites in the same or similar stream types, where only one sample has been taken at a point in time and thus there is no replication.

Lessons from practice: assessing early progress and success in river rehabilitation

“…The poor response of macroinvertebrate indicators may be due to the natural variability that is attributed to this group. Natural variation has been demonstrated to reduce the sensitivity of macroinvertebrate indicators to change (Clarke et al, 2006;Blocksom & Flortmersch, 2008). Variability in relation to space, time and sampling methods have been stated as significant factors that result in difficulties in identifying significant change in macro-invertebrate monitoring (Brooks et al, 2002;Sporka et al, 2006;Haase et al, 2008).…”

Assessing Macroinvertebrate Biodiversity in Freshwater Ecosystems: Advances and Challenges in DNA-based Approaches

“…This small number of individuals is then used to characterize the entire benthic assemblage-i.e., millions of individuals-at the site. Both assessment accuracy and precision improve when the area sampled or the number of individuals included in such a sample can be increased (Cao et al 2002a, b;Lorenz et al 2004;Ostermiller and Hawkins 2004;Cao and Hawkins 2005;Clarke et al 2006;Nichols et al 2006) (Figure 1), yet small subsamples continue to be used because of the unacceptable costs associated with processing larger samples (Carter and Resh 2001). Variability in descriptions of freshwater benthic invertebrate assemblages is considerably influenced by the type of water body as well as with the specific biological metric examined.…”

The STAR project: context, objectives and approaches

“…In the case of STAR-AQEM samples, two separate blind estimates of the proportion of the habitats present were normally made and the number of sample units on each habitat in each sample was based on their respective substratum recording forms. Additional replicate sampling was undertaken at some sites as itemised by Clarke et al (2006aClarke et al ( , 2006b.…”