A method to identify estuarine macroinvertebrate pollution indicator species in the Virginian Biogeographic Province

Abstract

Abstract Macroinvertebrates are commonly used as biomonitors to detect pollution impacts in estuaries. The goal of this research was to identify estuarine benthic invertebrates that could be used as indicator species to detect presence or absence of pollution in the Virginian Biogeographic Province using available monitoring data from the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program. The data were first subdivided by habitat. Then we summarized the benthic community using principal coordinates analysis and projected the results onto a pollution gradient. Then we compared medians and corrected interquartile ranges to identify indicator species that were sensitive to pollution (or lack thereof) and showed low variation in response. Our data set was divided into smaller subsets that ranged from 108 to 532 stations per habitat. Out of 707 species in the Virginian Province, 67 were identified as pollution indicator species; 37 pollution sensitive taxa and 30 pollution tolerant taxa. The pollution sensitive taxa were represented by more phyla than were the pollution tolerant taxa. The pollution tolerant taxa were dominated by deposit feeders while the pollution sensitive taxa were not dominated by animals using any one feeding strategy. The pollution sensitive taxa included many crustaceans, known to be sensitive to pollution, while the pollution tolerant taxa included many tubificid oligochaetes, which are common indicators of pollution. Our empirically based results corresponded well with other studies that identified tolerance values or indicator species. One advantage of this technique is that it can be used on smaller data sets, assuming that there are not major habitat differences among the samples. We believe that this parsimonious technique can be applied to other coastal areas where mid-size (100–500 stations) monitoring data sets are available.