Performance of the STAR-ICMi macroinvertebrate index and implications for classification and biomonitoring of rivers

Abstract

Although biomonitoring is the core approach adopted by the European Union's Water Framework Directive (WFD), many biotic indices still lack a thorough analysis of their performance and uncertainty. The multihabitat sampling and the application of STAR-ICMi index on macroinvertebrates are the standard methods to assess the ecological status of rivers in Italy. Ever since the Italians' implementation, dates back to 2010, few studies have tested the index performance with different sampling efforts, and even rarer are those assessing index uncertainty. However, these are worthwhile topics to investigate because all the Environmental Agencies are applying this index with both ecological and economic consequences. Aims of this study were (i) to assess the effect of subsampling on the STAR-ICMi index, (ii) to propose a standard method to calculate the index precision, and (iii) to test several less time-consuming alternatives to census all the individuals in the sample. I showed that the index is strongly affected by subsampling, and unbiased comparisons of ecological status can only be done at the same sampling effort. The index precision, calculated by bootstrapping the observed abundance of taxa, was so low in some circumstances, to increase the risk of misclassification. Finally, I showed that to avoid counting all the individuals in a sample, it is possible to estimate the most abundant taxa using a rank-abundance model. With this less time-consuming method, the STAR-ICMi index is predicted with sufficient precision.