TOWARDS A MOLLUSC-ONLY GEOHISTORICAL M-AMBI FOR ESTABLISHING REMEDIATION BASELINES IN COASTAL AND ESTUARINE HABITATS

M-AMBI is a commonly used biotic index for monitoring the ecological quality status of benthic macroinvertebrate communities in coastal and estuarine habitats. In calculating M-AMBI scores, baseline conditions corresponding to undisturbed ecological conditions are needed to estimate the ecological quality of the habitat. However, modern ecosystems have already undergone extensive degradation due to decades or centuries of anthropogenic change, thus the baselines used often do not represent the natural, undisturbed condition of the ecosystem. Over time, baselines may shift to increasingly degraded states, which can lead to the misallocation of valuable resources needed for remediation. Death assemblages of molluscs, which are formed from the accumulation of skeletal remains within the top layer of marine sediments, may provide a solution to avoiding the shifting baseline problem by allowing a glimpse into the past before the onset of human impact. Before a geohistorical M-AMBI can be implemented, the fidelity of a mollusc-only metric relative to the entire benthic macroinvertebrate community needs to be evaluated. Using macroinvertebrate benthic survey data from the Atlantic Coast of the United States, we calculated the M-AMBI scores for both the molluscan and whole communities and then adjusted the mollusc-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 M-AMBI linear model correctly classified nearly all of the adjusted mollusc-only sample sites needing remediation. Our results highlight the potential utility of a mollusc-only M-AMBI approach for assessing ecological quality, opening the door to applying the approach to death assemblages to establish geohistorical baselines that represent local undisturbed ecological conditions. But, before M-AMBI can be applied to the geohistorical record, future work is needed to examine the effects of factors associated with the formation of death assemblages (e.g., time-averaging, preservational biases) on M-AMBI scores.