Assessing the impact of errors in sorting and identifying macroinvertebrate samples |
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Authors: | Peter Haase John Murray-Bligh Susanne Lohse Steffen Pauls Andrea Sundermann Rick Gunn Ralph Clarke |
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Institution: | 1. Department of Limnology and Conservation Research, Senckenberg – Research Institute and Natural History Museum, Clamecystra?e 12, 63571, Gelnhausen, Germany 2. Environment Agency, Manley House, Kestrel Way, EX6 8EX, Exeter, UK 3. CEH Dorset, Winfrith Technology Centre, Winfrith Newburgh, Dorchester, DT2 8ZD, Dorset, UK
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Abstract: | This study assesses the impact of errors in sorting and identifying macroinvertebrate samples collected and analysed using
different protocols (e.g. STAR-AQEM, RIVPACS). The study is based on the auditing scheme implemented in the EU-funded project
STAR and presents the first attempt at analysing the audit data. Data from 10 participating countries are analysed with regard
to the impact of sorting and identification errors. These differences are measured in the form of gains and losses at each
level of audit for 120 samples. Based on gains and losses to the primary results, qualitative binary taxa lists were deducted
for each level of audit for a subset of 72 data sets. Between these taxa lists the taxonomic similarity and the impact of
differences on selected metrics common to stream assessment were analysed. The results of our study indicate that in all methods
used, a considerable amount of sorting and identification error could be detected. This total impact is reflected in most
functional metrics. In some metrics indicative of taxonomic richness, the total impact of differences is not directly reflected
in differences in metric scores. The results stress the importance of implementing quality control mechanisms in macroinvertebrate
assessment schemes.
Peter Haase, Andrea Sundermann: These authors contributed equally to this work. |
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Keywords: | stream assessment error estimation sample sorting macroinvertebrate identification |
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