Lessons learned from BEEP and MED POL on the biomarker use: application on the Adriatic and Algerian coasts.

The health status of coastal marine environments and transitional waters, exposed more than others to the consequences of domestic and industrial discharges, is a major concern at international level. At the same time, the monitoring of these ecosystems is rather difficult because of the high variability of chemical and physical parameters, that also limits the powerness of chemical and ecotoxicological analysis. For these and other reasons, the scientific community suggests new tools for environmental monitoring, addressed to as biomarkers. These are biochemical, physiological or histological indices that, measured in sentinel organisms exposed to a contaminated environment, reflect the exposure or the effects of pollutants at the molecular, cellular or organism level. Biomarkers do not substitute but integrate the more conventional analysis, providing an early warning of environmental contamination. Moreover, they give a specific contribution for the identification of toxicity due to a mixture of contaminants, although each present at very low concentration. The scientific research gave a relevant contribution to the identification of biomarkers and sentinel organisms. The lessons learned from international environmental biomonitoring programs such as MED-POL (Gabrielides, 1997; http://www.unepmap.gr/) and BEEP [http://www.lptc.u-bordeaux.fr/beep] indicated that different animals have different sensitivity to the same stress stimuli, and that not all the observed alterations are consistent with the extent of the environmental contamination. As a consequence, some animals better than others can be used as sentinel organisms; similarly, only a number of selected biochemical, physiological or histological alterations can be addressed to as biomarkers. As a result of many years of research and application, the biomonitoring through biomarkers is a reliable tool for the systematic evaluation of environmental health (Cajaraville et al., 2000) also with the contribution of the Espert System for data interpretation recently developed