The monitoring of contaminated environments via multilevel biomarker studies is a classical approach in ecotoxicology. Nevertheless, mechanistic links are rarely set up between the different levels of biological organization (sub-organism, organism, population). Population models are now recognized as useful tools to solve this extrapolation issue in predictive approaches, but environmental realism of these models could be improved in order to yield more pertinent risk assessment at the population level. This work proposes a new way to take advantage from the complementary nature of population modelling and in situ caging methodologies. On the basis of case studies with two environmental relevant species, the main purpose is to improve the extrapolation procedure by linking in situ biomarkers classically used in ecotoxicology at the organism level (laboratory bioassays or in situ biotests) and their consequences at a level of ecological interest: the population. Our approach proceeds in two steps. (i) Population models are developed to mechanistically link life history traits (survival, growth, reproductive activity, fecundity) and the dynamics of reference native populations all along a year. For this, we use a dual approach combining laboratory and field experiments. The latter consisting in a demographic follow-up based on monthly population census (evolution of densities and age-size structures) and an individual approach with field organisms caged in situ (reproduction, growth, survival). (ii) Effects of contamination, observed at the organism level through the exposure of transplanted individuals caged in contaminated stations, will be projected into the dynamics of these reference populations in order to propose a diagnostic assessment of water quality at the population level.