Using Molluscs To Assess Ecological Quality Status Of Soft-Bottom Habitats Along The Atlantic Coastline Of The United States

AMBI and M-AMBI are widely used biotic indices for assessing the ecological quality status of benthic macroinvertebrate communities in estuarine and coastal soft-bottom habitats. Identifying the species needed for estimating these indices, however, is both expensive and time-consuming, and requires a high degree of taxonomic expertise. The use of proxy taxa as a means of subsampling the target community may save time, resources, and the breadth of taxonomic expertise needed. Our study used macroinvertebrate benthic survey data from the Atlantic Coast of the United States to test the fidelity of molluscs as proxies of the whole community. We calculated the AMBI and M-AMBI scores for both the molluscan and whole communities and then adjusted the molluscan-only index scores to that of the whole community using the linear relationship between the two communities within a Bayesian framework. We found that the mollusc-only AMBI approach underperformed at classifying the ecological quality of the whole community, particularly regarding sample sites classified as needing remediation. The low performance of the mollusc-only AMBI approach is likely due to the dearth of molluscs with high environmental stress tolerances. In contrast, the mollusc-only M-AMBI outperformed AMBI at classifying ecological quality. The M-AMBI linear model correctly classified nearly all of the adjusted mollusconly sample sites needing remediation. The increased efficacy of mollusc-only M-AMBI may be due to the incorporation of species richness and diversity into the index, as both metrics were highly correlated between the molluscan and whole communities. Mollusc-only M-AMBI did have some drawbacks, however, with fidelity decreasing as ecological quality decreased. Overall, our study highlights the potential utility of a mollusc-only approach for assessing the ecological quality of estuarine and coastal soft-bottom habitats.