Hydrobiologia (2006) 566:477–503 Springer 2006 M.T. Furse, D. Hering, K. Brabec, A. Buffagni, L. Sandin & P.F.M. Verdonschot (eds), The Ecological Status of European Rivers: Evaluation and Intercalibration of Assessment Methods DOI 10.1007/s10750-006-0076-5
Estimates and comparisons of the effects of sampling variation using ‘national’ macroinvertebrate sampling protocols on the precision of metrics used to assess ecological status Ralph T. Clarke1,*, John Davy-Bowker1, Leonard Sandin2, Nikolai Friberg3, Richard K. Johnson2 & Barbara Bis4 1
Centre for Ecology & Hydrology, Winfrith Technology Centre, DT2 8ZD, Dorchester, Dorset, United Kingdom Department of Environmental Assessment, Swedish University of Agricultural Sciences, P.O. Box 7050, SE-750 07, Uppsala, Sweden 3 Department of Freshwater Ecology, National Environmental Research Institute, Vejlsøvej 25, DK-8600 Silkeborg, Denmark 4 Institute of Ecology and Nature Protection, Department of Invertebrate Zoology and Hydrobiology, University of Łodz´, Banacha 12/16, 90-237 Łodz´, Poland (*Author for correspondence: E-mail:
[email protected]) 2
Key words: replicate sampling variation, uncertainty, macroinvertebrate metrics, Water Framework Directive, RIVPACS, STAR-AQEM, PERLA
Abstract 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 Psamp of the total variance in metric values with a stream type; low values of Psamp 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. Psamp 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.
478 Introduction Most quantitative assessments of the biological status of water bodies are based on the values of one or more biological indices or metrics derived from the taxonomic composition of the sample (Smith et al., 1999; Wright et al., 2000). The metrics are often designed to measure the ecological response to some specific form of stress, such as organic or toxic pollution, acid stress, or degradation in stream morphology and the diversity of habitats (Herring et al., 2004). Any measure of ecological quality or status is of little value without some knowledge of its levels of uncertainty (Clarke, 2000; REFCOND, 2003). All assessments of the ecological status of river sites using macroinvertebrate sampling are subject to uncertainty and errors due to a range of factors (Ostermiller & Hawkins, 2004). Replicate sample values will vary because of inherent natural small-scale spatial heterogeneity in the fauna at a site. Subsequent sample processing, perhaps involving sub-sampling or identifying only a fixed number of individuals, and the taxonomic resolution (family, genus or species) will all affect the precision and uncertainty in site assessments. Assessment methods which are prone to high levels of variation between replicate sample values will tend to provide less reliable estimates of the ecological status for a site and provide less power and confidence to detect changes in ecological quality (Clarke, 2000). Therefore, it is important to have quantitative estimates of the effects of sampling variation on the values of any biotic index or metric used to assess the ecological status of a river site (Clarke et al., 1996). There have, surprisingly, been few extensive quantitative field studies of the susceptibility of freshwater biotic metrics to sampling variation. Clarke et al. (2002) quantified the sampling variation in BMWP score, number of BMWP families (taxa) and Average Score Per Taxon (ASPT) for the RIVPACS sampling method (Murray-Bligh et al., 1997) by taking three replicate samples in each of three seasons at each of 16 UK sites selected to cover a balanced range of ecological qualities and physical types. They showed that with trained staff, inter-personnel differences contributed less than 12% of the total variance between replicate RIVPACS samples in each of the
three metrics. Johnson (1998) took five or six replicate macroinvertebrate samples from littoral, sub-littoral and profundal habitats in each of 16 Swedish lakes and assessed sampling variation in six metrics. In contrast, Hose et al. (2004) assessed the within-season short-term temporal variation in observed number of taxa at two reference quality sites in New South Wales, Australia by sampling the same riffle and edge habitats on three occasions over a 6 week autumn period and found that the O/E ratio of the observed to AUSRIVAS-predicted expected number of taxa did not vary significantly within the season. Within Europe, the EU Water Framework Directive (WFD) (Council of the European Union, 2000) requires all partner countries to provide information in their river basin management plans on the level of confidence and precision of results in their river monitoring programmes to assess the ecological status class of river sites (WFD: Annexe V, Section 1.3). The STAR project of the European Union 5th Framework Programme included an extensive field sampling programme across 13 countries using existing nationally used macroinvertebrate sampling methods and protocols, together with a standard STAR-AQEM method (Furse et al., 2006). The STAR-AQEM method and protocol was developed originally during the AQEM project within an earlier EU 5th Framework Programme (Herring et al., 2004). The protocol was designed as a possible approach to providing a standardised sampling and assessment methodology across Europe (see special issue volume 516 of Hydrobiologia). The AQEM method has subsequently been modified for use within the STAR project, and is now referred to as the STARAQEM method and described in detail in Furse et al. (2006). This paper summarises the results of an extensive replicated sampling programme within the main STAR field sampling programme. It quantifies the overall effects of sampling variation and subsequent laboratory sample processing procedures on the sampling variability of a wide range of macroinvertebrate metric values for ‘national’ sampling methods (or, where unavailable, the RIVPACS method) and compares these with the estimates of variability obtained for the STARAQEM samples taken at the same sites at the same times.
479 Methods Replicate field sampling programme The replicated sampling study covered 12 countries encompassing 22 stream types spread over 11 Ecoregions (sensu Illies, 1978; as used in the WFD). Within the STAR field sampling programme, STAR-AQEM samples were taken at all sites by each participating partner (Clarke et al., 2006; Furse et al., 2006). At each site in nearly all of the main stream types, each partner also collected samples using a notional ‘national’ method. This was normally a widely used protocol within the individual partner’s Member State, but in Germany, Austria and Greece where there were no existing common ‘national’ sampling protocols, the UK RIVPACS protocol was used (Murray-Bligh et al., 1997) (Table 1). Both STAR-AQEM and ‘national’ or RIVPACS samples were collected in two seasons – spring and either summer or autumn. Further details of all of the sampling methods and protocols are given in Furse et al. (2006).
Most STAR project partners took a second replicate field sample at a subset of their sites, usually by both methods and usually in both sampling seasons (Table 1). These sites were carefully selected within each sampled stream type to cover a range of perceived (i.e., pre-classified) ecological status classes (sensu WFD) of sites from ‘high’ and ‘good’ to ‘moderate’ or ‘poor’/’bad’. This was important because the sampling variability of many metrics may depend on the quality of a site; poorer quality sites with fewer taxa present might be less variable in some taxonomic richness/diversity metrics, but more variable in metrics based on some form of average stresstolerance score of the taxa present (e.g., ASPT or a Saprobic Index). Taking replicate samples at the same set of sites using both methods provided valid direct comparisons of the sampling standard deviation (SD) for individual metrics between the ‘national’ or RIVPACS method and the STAR-AQEM method, because both sampling methods were then based on the same range of site qualities and within-site
Table 1. Number of sites in each stream type and country with replicate samples obtained using either the RIVPACS or ‘national’ sampling method in at least one season; (small-sized=10–100 km2, medium sized=100–1000 km2, lowland=
