Growth, condition indices and biomarker responses of juvenile turbot, Scophtalmus maximus, exposed to contaminated sediment
Résumé
Since sediments have the potential to form associations with several classes of pollutants, they have been recognized as a possible and significant source of stress for the benthic environment. Flatfish maintain a close association with sediments for food and cover and are therefore more likely to be exposed to contaminated sediments, especially in coastal areas. The assessment of these potential biological effects implies to use adapted biomonitoring tools. The main objective of this study is to assess and compare the response of several biological indicators measured on juvenile turbot (Scophtalmus maximus) exposed to contaminated sediments. Sediments were collected at three stations in a northern France harbour (Boulogne-sur-Mer), in an anthropogenic French estuary (Seine) and in a reference site. Juvenile turbots were exposed to sediments during 7 and 21 days in laboratory conditions. Sediments were analyzed for metals, PAHs and PCBs contamination. Growth and several condition indices were individually measured on tagged fish and metal bioaccumulation was measured in fish gills. The response of some hepatic biotransformation enzymes (EROD, GST) and antioxidant enzyme (CAT) were also analyzed as first indicators of exposure. Results showed a significant correlation between level of contamination and fish biological responses. Indeed, growth rate, morphometric index and the lipid storage index, based on the ratio of the quantity of triacylglycerols on sterols (TAG:ST), were significantly higher in the less contaminated station. The RNA:DNA ratio tend also to decrease with chemical contamination. This decrease of growth and condition indices, associated with a metal accumulation in gills, reflected the adverse effects of contaminated sediment on fish biological performance. In addition, the simultaneous use of several hepatic biomarkers and condition indices could give information on the relevance of molecular biomarker to predict adverse effects of contaminants.