The impacts of seawater physicochemical parameters and sediment metal contents on trace metal concentrations in musselsa chemometric approach

The concentrations of Al, Ba, Cd, Co, Cr, Cu, Fe, Li, Mn, Ni, Pb, Sr, Zn, and Hg were studied in Mytilus galloprovincialis collected from the coastal area of Montenegro. The impact of seawater temperature, salinity, dissolved oxygen, total organic carbon (TOC), and metal content in sediment samples on the metal contents in mussels collected from three locations in four different seasons was analyzed by a Pearson correlation coefficient (r), principal component analysis (PCA), and cluster analysis (CA). These analyses were used to discriminate groups of samples, elements, and seawater parameters, according to similarity of samples chemical composition in different seasons, as well as the impact of seawater parameters and surface sediment composition on the mussels' element concentrations. Synergistic interactions occurred between seawater TOC, Fe, and Al concentrations in mussels. Compared with other studies, which are usually performed under constant laboratory conditions where mussels undergo only one stress at a time, this study was performed in nature. The analyses showed the importance of considering simultaneously acting environmental parameters that make determining of separate impacts of each factor selected very difficult and complex

Towards an integrated ecosystem-based bioaccumulation and metal speciation model

Heavy metal bioaccumulation models are important for interpreting water quality data, predicting bioaccumulation in organisms, and investigating the provenance of contaminants. To date they have been predominantly used as single-issue models, under steady-state conditions and in isolation of the biogeochemical processes that control metal bioaccumulation. Models that incorporate these processes would allow a more holistic approach to bioaccumulation modeling and contaminant assessment; however, this has been rarely undertaken, probably because it requires the integration of inter-disciplinary areas. In this study, we have developed such a model that integrates three key multi-disciplinary areas (biological, metal speciation, and bioaccumulation processes) and responds to variations in temporal external and internal forcing. Furthermore, spatial context is provided by developing the model within a simple hydrodynamic box-modeling framework. The calibrated model was able to predict with reasonable accuracy the temporal and spatial trends of soft-tissue copper bioaccumulation in a coastal oyster. This exploratory model was also used to highlight the importance of phytoplankton as an important vector of copper uptake dynamics by an oyster, therefore reinforcing the importance of the integrated approach. Finally, our model provides a framework for greater application beyond this specific example such as in the areas of waterway restoration, which has been shown to be an important area of ecological and environmental research. © 2010 Springer Science+Business Media, LLC