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Filter-feeding bivalve molluscs (such as oysters, clams, mussels and cockles) can concentrate contaminants from the water column. The extent of faecal contamination in shellfish is usually estimated by determining the concentration of faecal coliforms and/or Escherichia coli. Three sample points in each of three geographically separate commercial shellfisheries were selected for analysis for the effect of season, spring/neap and high/low tidal cycles, rainfall and wind direction on the results of routine E. coli monitoring. General linear modelling was used for the analyses. The principle factors affecting the contamination of shellfisheries were season, high/low tidal cycle and rainfall. The effects varied between harvesting areas and between individual sampling points within harvesting areas. Undertaking such analyses for all harvesting areas would contribute to the management of monitoring programmes and assist in the evaluation of potentially contaminating sources, such as sewage discharges. The type of analyses undertaken on E. coli monitoring data would also be pertinent for the analysis of putative viral indicators, such as F+ coliphage, and could be extended to data on bacterial and viral pathogens.

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Environmental conditions and xenobiotic exposure can be sources of stress to living organisms. Biological markers are measurable indicator of changes which may happen at any biological level and which can be considered an early warning signal of some biological or environmental state or condition. A structured field study was undertaken to investigate the relationship between three biomarker assays and the spatial and temporal variation of each biomarker in samples of Mytilus edulis. The three biomarkers were the neutral red retention assay, micronucleus assay and comet assay, which indicate damage at different cellular/molecular levels. Three sites in Poole Harbour, an area on the South coast of the UK were sampled on six separate occasions at least three weeks apart. The results for the comet assay showed a significant difference between sites and between sampling dates whereas the results for the other two assays did not show a significant difference for either factor. There was no significant correlation between the results of any pair of the three biomarkers. The results of the micronucleus assay showed a significant correlation with water temperature. This temperature effect, as well as induced repair, may contribute to explain the lack of a strict correspondence between pollution gradients and biomarkers responses. Highlights ► The CA results, but not those of NRR or MN, showed a significant variation with respect to sampling site and date. ► No significant correlation between NRR or CA and any of the measured environmental variables (temperature, salinity, pH). ► The MN Index showed a significant correlation with water temperature but no significant correlation with salinity or pH. ► There was no correlation reported between the results of the three biomarkers (NRR, MN and CA).

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