Grégoire BALLUAIS
Ineris - Verneuil-en-Halatte
Parc Technologique ALATA - BP2
60550 Verneuil-en-Halatte
The Water Framework Directive is currently based on measuring the concentrations of certain chemicals to assess the state of aquatic environments. However, this approach, which focuses on threshold values established in laboratories, has its limitations: it does not accurately reflect the actual complexity of the pollutant mixtures present in the environment. To better understand the overall impact of these chemical cocktails, the use of biomarkers in biomonitoring is a promising and rich area of research. These biological indicators (bioindicators) enable early detection of the influence of contaminants on organisms.
Nevertheless, their integration into regulatory programs still faces several difficulties, including the lack of reliable protocols and uncertainties related to their interpretation.
Sebio/Ineris has participated in various projects aimed at better regulating the use of biomarkers, defining their ranges of natural variability, and modeling the links between biological responses, individual effects, and consequences on populations (DEB-IBM).
This thesis project is part of this dynamic. It aims to strengthen the operational use of biomarkers by linking early biological responses observed in the field to measurable effects on the performance and life history traits of organisms. The objective is then to assess what these effects imply for population dynamics and viability.
This research is therefore based on data from the Interreg Orion project and on the scaling models developed at Sebio/Ineris, particularly those that have already made it possible to link certain reproductive biomarkers to population impacts in sticklebacks. Three main objectives have been defined: (1) to analyze biomarker responses after in situ exposure, (2) to consolidate and model the links between biomarkers and biological traits in the natural environment, and (3) to predict the effects of multiple contaminations on populations based on data obtained along the Meuse River.