Nutrient optima and tolerances of benthic invertebrates, the effects of taxonomic resolution and testing of selected metrics in lakes using an extensive European data base

• Published in: Aquatic ecology 2008-06, Vol.42 (2), p.277-291
• Main Authors: O’Toole, C., Donohue, I., Moe, S. J., Irvine, K.
• Format: Article
• Language: English
• Subjects: Alkalinity; Benthic fauna; Biomedical and Life Sciences; Ecology; Ecosystems; Eutrophic environments; Eutrophication; Freshwater & Marine Ecology; Invertebrates; Lakes; Larvae; Life Sciences; Macroinvertebrates; Nutrient status; Nutrients; Rivers; Sampling methods; Studies; Taxa; Taxonomy
• ISSN: 1386-2588; 1573-5125
• DOI: 10.1007/s10452-008-9185-8

A large dataset from 1,077 lakes in Finland, Ireland, Sweden and the United Kingdom was collated to analyse the relationship between nutrient status and occurrence of different taxa, as well as between total phosphorus or chlorophyll and commonly used macroinvertebrate metrics developed for river assessment. We found that most taxa were associated with mesotrophic conditions ( sensu OECD). Species associated with oligotrophic status included Baetis rhodani , Gammarus lacustris and plecopteran larvae, a group commonly associated with low nutrient status also in rivers. Species tolerant of eutrophic conditions were the chironomid larvae ( Chironomus plumosus and Cryptochironomus defectus ); and two species of tubificids ( Psammoryctides barbatus and Potamothrix hammoniensis ). For a number of taxa the associations of benthic invertebrates with nutrient state reported in the literature were not supported by analysis of the REBECCA data. The analysis indicated a variable response of littoral macroinvertebrates to eutrophication pressure when using common metrics developed for macroinvertebrates in rivers. Several metrics showed significantly different responses in lakes with different alkalinity, justifying the use of alkalinity for typing water bodies. These significant responses suggest that benthic invertebrates may be a useful component for classification of ecological status in lakes. The low amount of variance explained by the regressions (