The Water Framework Directive requires the assessment of the ecological status of transitional waters considering the fish component. An original methodology, based on a pressure-impact approach, was established to develop a multimetric fish-based index to characterize the ecological quality of French estuaries. An index of contamination, based on the chemical pollution affecting aquatic systems, was used as a proxy of anthropogenic pressure. The fish metric selection was based on their response to disturbances tested via statistical models (generalized linear models) taking into account sampling strategy and estuarine features. Four metrics, for which discriminating responses to level of pressure were demonstrated, were retained to constitute the estuarine multimetric fish index. This new tool appeared particularly relevant to detect the contamination effects on fish communities in estuaries. It could help managers to take decisions in order to maintain or reach the good status required by the Water Framework Directive for 2015.

In the Water Framework Directive (European Union) context, a multimetric fish based index is required to assess the ecological status of French estuarine water bodies. A first indicator called ELFI was developed, however similarly to most indicators, the method to combine the core metrics was rather subjective and this indicator does not provide uncertainty assessment. Recently, a Bayesian method to build indicators was developed and appeared relevant to select metrics sensitive to global anthropogenic pressure, to combine them objectively in an index and to provide a measure of uncertainty around the diagnostic. Moreover, the Bayesian framework is especially well adapted to integrate knowledge and information not included in surveys data. In this context, the present study used this Bayesian method to build a multimetric fish based index of ecological quality accounting for experts knowledge. The first step consisted in elaborating a questionnaire to collect assessments from different experts then in building relevant priors to summarize those assessments for each water body. Then, these priors were combined with surveys data in the index to complement the diagnosis of quality. Finally, a comparison between diagnoses using only fish data and using both information sources underlined experts knowledge contribution. Regarding the results, 68% of the diagnosis matched demonstrating that including experts knowledge thanks to the Bayesian framework confirmed or slightly modified the diagnosis provided by survey data but influenced uncertainty around the diagnostic and appeared especially relevant in terms of risk management.

In the context of the European Water Framework Directive (WFD), monitoring programs and related indicators have been developed to assess anthropogenic impacts on various components of aquatic ecosystems. While great precautions are usually taken when selecting and calculating relevant core metrics, little attention is generally paid to the generation of the multimetric indicator, i.e. the combination of the different core metrics. Indeed, most multimetric indicators are generated by simply averaging or summing metrics, without taking into account their sensitivity and their variability. Moreover, few indicators provide a rigorous estimate of the uncertainty of the assessments, while this estimation is essential for managers. In this context, we developed a Bayesian framework to build multimetric indicators aiming at improving those two weaknesses. This framework is based on two phases. First, pressure-impact statistical models are developed to quantify the impact of pressure on various fish metrics. Then the Bayesian theorem is applied to estimate probabilities of being at a certain anthropogenic pressure level from fish observation and pressure-impact models outputs. The Bayesian theorem allows to combine objectively the different core metrics, taking into account their sensitivity and their variability, and to provide rigorous uncertainty quantification, which is especially valuable in the WFD context. The method is applied as illustrative example on transitional French water bodies to demonstrate its relevance, especially in the Water Framework Directive context though the method is generic enough to be applied in various contexts