Assessing the impact of errors in sorting and identifying macroinvertebrate samples

Haase, Peter; Murray‐Bligh, John; Lohse, Susanne; Pauls, Steffen U.; Sundermann, Andrea; Gunn, R.J.M.; Clarke, Ralph T.

doi:10.1007/s10750-006-0075-6

Cited by 72 publications

(31 citation statements)

References 30 publications

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“…The same is true concerning precision and errors (Haase, Murray-Bligh, et al, 2006). On the other hand, all these studies clearly indicate that observed differences are not a weakness of the STAR/AQEM protocol but a general problem in sampling invertebrates in streams.…”

Section: Impact Of Modifications and Variability Of The Star/aqem Metsupporting

confidence: 54%

Effects of sampling microhabitats with low coverage within the STAR/AQEM macroinvertebrate sampling protocol on stream assessment

et al. 2008

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In the STAR/AQEM protocol microhabitats covering less than 5% of the sampling area were neglected. Driven by an ongoing discussion on the importance of these underrepresented microhabitats we tested the influence of sampling them. We investigated 48 streams representing 14 different stream types from all over Germany. Macroinvertebrates of underrepresented microhabitats were sampled in addition to the STAR/AQEM protocol. To ensure the method remains feasible in routine monitoring programmes the total sampling and sorting effort of additional sampling was limited to 20 min. Particularly those taxa were picked, which were not recognised during the routine STAR/AQEM sorting.To identify the effect of additional sampling on stream assessment results, we calculated the stream type-specific Multimetric Index (MMI) with the ''main'' and the ''main+additional'' data for each sample. The mean and median difference in MMI values between ''main'' and ''main+additional'' samples was 0.02 and 0.01, respectively. In seven of 48 samples (14.6%) a different ecological quality class was calculated with the ''main+additional'' dataset. Regarding common metrics within the MMI as well as intercalibration metrics differences between ''main'' and ''main+additional'' samples were analysed. The values differed most in richness metrics (e.g., number of EPTCBO Taxa, number of Trichoptera Taxa). The results of the present study show that additional sampling of underrepresented microhabitats could alter multimetric assessment results.

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Section: Impact Of Modifications and Variability Of The Star/aqem Metsupporting

confidence: 54%

Effects of sampling microhabitats with low coverage within the STAR/AQEM macroinvertebrate sampling protocol on stream assessment

et al. 2008

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“…Taxa were identified to the level proposed by Haase et al (2006a), which ensured that taxa lists were comparable with regard to their taxonomic resolution. For most taxa, the resolution was at the genus or species level, but selected families such as Chironomidae, Naididae, or Tubificidae were determined only to the sub-family or family level.…”

Section: Sampling Designmentioning

confidence: 99%

River restoration success depends on the species pool of the immediate surroundings

Sundermann

Stoll

Haase

2011

Ecological Applications

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Previous studies evaluating the success of river restorations have rarely found any consistent effects on benthic invertebrate assemblages. In this study, we analyzed data from 24 river restoration projects in Germany dating back 1 to 12 years and 1231 data sets from adjacent river reaches that lie within 0-5, 5-10, and 10-15 km rings centered on the restored sites. We calculated restoration success and recolonization potential of adjacent river reaches based on stream-type-specific subsets of taxa indicative for good or bad habitat quality. On average, the restorations did not improve the benthic invertebrate community quality. However, we show that restoration success depends on the presence of source populations of desired taxa in the surrounding of restored sites. Only where source populations of additional desired taxa existed within a 0-5 km ring around the restored sites were benthic invertebrate assemblages improved by the restoration. Beyond the 5-km rings, this recolonization effect was no longer detected. We present here the first field results to support the debated argument that a lack of source populations in the areas surrounding restored sites may play an important role in the failure to establish desired invertebrate communities by the means of river restorations. In contrast, long-range dispersal of invertebrates seems to play a subordinate role in the recolonization of restored sites. However, because the surroundings of the restored sites were far from good ecological quality, the potential for improvement of restored sites was limited.

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“…found that subsampling of STAR-AQEM samples caused more than 50% of the overall replicate sampling variance for nearly half of all metrics analysed. In a companion study, Haase et al (2006) found significant effects of laboratory sampling sorting and taxonomic identification errors on the values of several macroinvertebrate metrics for the STAR-AQEM and RIVPACS methods.…”

Section: Comparison Of Precision Of Metricsmentioning

confidence: 92%

Estimates and comparisons of the effects of sampling variation using ‘national’ macroinvertebrate sampling protocols on the precision of metrics used to assess ecological status

Clarke

Davy‐Bowker²,

Sandin³

et al. 2006

Hydrobiologia

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The Water Framework Directive (WFD) of the European Union requires all member countries to provide information on the level of confidence and precision of results in their river monitoring programmes to assess the ecological status class of river sites. As part of the European Union project STAR, the overall effects of sampling variation for a wide range of commonly used metrics and sampling methods were assessed. Replicate samples were taken in each of two seasons at 2-6 sites of varying ecological status class within each of 18 stream types spread over 12 countries, using both the STAR-AQEM method and a national sampling method or, where unavailable, the RIVPACS sampling protocol. The sampling precision of a combination of sampling method and metric was estimated by expressing the replicate sampling variance as a percentage P samp of the total variance in metric values with a stream type; low values of P samp indicate high precision. Most metrics had percentage sampling variances less than 20% for all or most stream types and methods. Most national methods including RIVPACS had sampling precisions at least as good as those for the STAR-AQEM method as used in their country at the same sites; the main exceptions were the national methods used in Latvia and Sweden. The national methods used in the Czech Republic, Denmark, France, Poland and the RIVPACS method used in the UK and Austria all had percentage sampling variances of less than 10% for the majority of metrics assessed. In contrast, none of the metrics had percentage sampling variances less than 10% when based on either the Italian (IBE) method, which used bank-side sorting, or the Latvian national method which identifies only a limited set of taxa. P samp was lowest on average for the two stream types sampled in the Czech Republic using either the PERLA national method or the STAR-AQEM method. Averaged over all stream types and methods, the three Saprobicbased metrics had the lowest average percentage sampling variances (3-6%) amongst the 26 metrics assessed. These estimates of sampling standard deviation can be used to help assess the uncertainty in single or multi-metric systems for estimating site ecological status using the general STAR Bioassessment Guidance Software (STARBUGS) developed within the STAR project.

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Assessing the impact of errors in sorting and identifying macroinvertebrate samples

Cited by 72 publications

References 30 publications

Effects of sampling microhabitats with low coverage within the STAR/AQEM macroinvertebrate sampling protocol on stream assessment

Effects of sampling microhabitats with low coverage within the STAR/AQEM macroinvertebrate sampling protocol on stream assessment

River restoration success depends on the species pool of the immediate surroundings

Estimates and comparisons of the effects of sampling variation using ‘national’ macroinvertebrate sampling protocols on the precision of metrics used to assess ecological status

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