An efficient semi-quantitative macroinvertebrate multimetric index for the assessment of water and sediment contamination in streams. Issue 3 (3rd July 2017)

• Record Type: Journal Article
• Authors: Pallottini, Matteo; Goretti, Enzo; Selvaggi, Roberta; Cappelletti, David; Dedieu, Nicolas; Céréghino, Régis
• Is Part Of: Inland waters. Volume 7:Issue 3(2017)
• Page Start: 314
• Page End: 322
• Publication Date: 2017-07-03
• Subjects: Benthic invertebrates -- biomonitoring -- Ecological Quality Ratio -- ecosystem health -- heavy metals pollution -- water chemistry; Limnology -- Periodicals; Hydrology -- Periodicals; Aquatic biology -- Periodicals; Lake ecology -- Periodicals; Lakes -- Environmental aspects -- Periodicals; 551.48205
• DOI: 10.1080/20442041.2017.1329912
• Languages: English
• ISSNs: 2044-2041

Abstract

Abstract: Environmental issues and their associated legislative pressures are demanding, especially regarding costs, limited budgets, and data collection efforts. The development of effective biotic indices for monitoring generated via comprehensive data collection within human-impacted landscapes can support district- to regional-level environmental management plans. We designed a macroinvertebrate multimetric index that fulfills the requirements of the EU Water Framework Directive and measures ecological health as a deviation from a reference state, taking into consideration water and sediment contamination in streams of Central Italy. Macroinvertebrate samples were obtained by a semi-quantitative technique. The Semi-quantitative Multimetric Index (SMI) we developed has a high discrimination efficiency (reference vs. impacted sites), high stability (i.e., low coefficient of variation) at reference sites, and low specificity regarding the environmental variables reflecting contamination. The SMI is composed of 4 metrics weighted by their discrimination efficiency against reference conditions: number of families, score of the biological monitoring waters pollution index (SBWMP), Margalef's diversity index, and relative richness of shredders. These metrics that best distinguished reference from impacted sites were selected from 71 metrics divided into 4 categories (one metric for each category): richness/abundance, tolerance, diversity, bioecological traits. The SMI exemplifies a cost-effective method that could complement supranational techniques because it is robust in terms of biological, ecological, and socioeconomic contexts used to generate it; requires little effort for the data collection; and responds to a large number of environmental stressors. To ensure comparability, however, we recommend calibrating the new SMI index against the national index currently in use.