A biotic index using benthic macroinvertebrates for Italian lakes

The relationship between benthic macroinvertebrates and environmental variables from 42 Italian lakes were analysed with the aim of developing a biotic index. investigated lakes, 570 species were found of which 373 belonged to the family of Chironomidae and 85 to the class of oligochaeta. Rare species, those present in less than 10 samples, were excluded from the analysis, leaving 57 species for data analysis. ariate analysis: canonical correlation analysis (CANON) and multivariate analysis of variance and covariance (MANCOVA) were carried out on a large database of 1060 sampling points, for which both environmental data (16 chemical and morphometric variables) and 57 species counts from soft bottom samples were available. In addition, a second dataset of 94 sites from small lakes sampled in 2005 in Northern Italy (Lombardy), was analysed for comparison. ta analysis (CANON) from the large database gave the following results:(1) rst canonical variate was related to conductivity, pH and alkalinity and accounted for 17% of the total variation; cond canonical variate was related to total phosphorus, N-NH4 and dissolved oxygen, and accounted for 15% of the total variation; aximum depth, volume and water temperature were related to the third canonical variate, which accounted for 14% of the source of variation. alysis of the database from small lakes revealed that in the plane of the first two canonical variates dissolved oxygen was inversely correlated with the depth of sampling and that the second canonical variate showed an inverse relationship between transparency and nutrients. A found evidence for differences between lake types and sampling years, confirmed the CANON results and allowed the quantification of the contribution of different target variables on species composition. hic status index was calculated ranking percentage oxygen saturation (O2 %sat), transparency (transp) and total phosphorus (TP). The means of O2 %sat, transp and TP weighted by the species abundances were calculated to have optimum values for each species; a benthic quality index was then obtained by multiplying the weighted means of O2 %sat, transp and TP by species abundances and dividing the product by the total number of specimens present at each station. A significant correlation was observed between trophic status and the benthic quality index. A good agreement was also observed between the indexes calculated using the large database and the second dataset on small lakes.