Rémy Beaudouin

Mesocosms have been proposed as a tool to study the effects of chemicals at the population level. However, studies conducted in mesocosms are limited to a low number of replicates. This, together with the high variability characterising the population level, constitutes a limiting factor for detecting significant effects. To tackle this main drawback, I developed stochastic modelling of control fish populations to assess the probabilistic distributions of the population endpoints.

That was to topic of my PhD thesis on "Individual-based modelling of the population dynamics of fish in an experimental ecosystem, to help detect and interpret the effects of chemicals" (under the joint supervision of G. Monod, INRA Rennes and V. Ginot, INRA Avignon).

This methodology is currently applied to the lotic mesocosms located at INERIS. The mesocosm platform (INERIS, Verneuil-en-Halatte, France) is composed of 12 channels of 20 m long, and 1 m in width. In these outdoor mesocosms, the three-spined stickleback (Gasterosteus aculeatus) is the highest trophic level predator and the only fish species. Two PhD projects were carried out to develop the modelling methodology. From 2010 to 2013, I jointly supervised the PhD thesis of G. de Kermoysan "Development of ecotoxicological experiment on stickleback population dynamics in a lotic mesocosm: application to assess the bisphenol A effects" and from 2013 to 2016, the PhD of C. Leloutre "Improvement of the data analysis of ecotoxicological experiment on stickleback population dynamics in a lotic mesocosm: individual-based modelling of the control populations dynamics".

Starting in 2016, I am supervising the PhD of Viviane David: "Prediction of the effects of chemical on the population dynamics of the stickleback" (funded by INERIS).

Modelling endocrine disruption in fish at different biological levels to assess ecological risk

Certain chemicals possess the ability of modulating the endocrine systems, associated with reproductive and developmental dysfunctions, probably related to abnormal levels of circulating steroids hormones. Endocrine disruptor compounds (EDCs) are of great ecotoxicological concern because of their potential harmful effects on humans and wildlife, including fish.

The extrapolation of subtle functional deficits within individuals into population-level effects is a great challenge for the risk assessment of EDCs. Ecological risk assessment should protect the long-term persistence of populations of species in space and time under naturally varying field conditions and in the presence of other stressors (e.g. food limitation). However, excepting the ecotoxicological data provided by mesocosm experiments and a few field studies, data on impacts of chemical substances on populations or higher biological levels are very sparse. In this context, models can play an important role in bridging the gap between what is measured (organism-level endpoints) and what needs to be protected (population-level endpoints).

Among model species for ecotoxicological investigations, zebrafish (Danio reiro) is a vertebrate organism extensively used for scientific purposes and an increasing amount of toxicological data of EDCs toward zebrafish have been gathered during the past years.

Accordingly, the aim of this part of my activities is to propose an integrated modelling framework for zebrafish to assess how EDCs modify the level of hormones in individuals and how such disruption will impact individual fitness and population dynamics.

One of the key aspects of extrapolating from molecular scale to individual scale is toxicokinetics modelling which describes accumulation, distribution and elimination of molecules in the body. During MOZAIC project, we proposed and successfully challenged with literature data the first PBPK (physiologically based pharmacokinetic) model for the zebrafish. This model was developed using original experimental data produced by our INERIS colleagues and validated and/or new QSAR/QSPR models to predict some toxicokinetic parameters.

Zebrafish

In the same project, in parallel, a population dynamics model for zebrafish was develloped coupling a model of individual bioenergetics with an individual-based model taking into account the main ecological factors. The predictions of the DEB-IBM were compared to existing observations on natural zebrafish populations and the predicted population dynamics agree with empirical observations. Even if, our zebrafish DEB-IBM model can still be improved by acquiring new experimental data on the most uncertain processes (e.g. survival or feeding), it can already serve to predict the impact of compounds at the population level.

We currently work to develop a first model of the hypothalamic–pituitary–gonadal axis (HPG axis) for the zebrafish, which will be linked to the PBPK model to predict the kinetics of natural hormones under normal and exposed conditions.

In addition, since 2015, I have been supervising Audrey Grech's PhD "Development and application of generic toxicokinetic models for environmental risk assessment in fish".

Mechanistic modelling to analyse evolutionary experiments

Modelling the consequences on population dynamics of a long-term exposure to understand and assess adaptation and tolerance processes and to improve ecological risk assessment.

2008 - 2010. Individual-based model of Chironomus riparius population dynamics over several generations to explore adaptation following exposure to uranium-spiked sediments
2010 - 2013. Joint supervision of a Ph.D. Student (B. Goussen). «Taking into account of a bioenergetic model in an adaptive dynamic model for a better evaluation of the ecological risks: case of a population of Caenorhabditis elegans subjected to different anthropic stresses». Funded by INERIS and IRSN.