Benoit Goussen
Research Fellow

Profile

Biography

Benoit's research focuses on the adaptation and on the population dynamics of populations exposed to anthropogenic stressors.

His approach involves experiments and modelling (essentially using a bioenergetic approach).

His work contributes to increase the knowledge on the ecological and evolutionary effects of pollutants, and its aim is to demonstrate how mechanistical modelling can be used to improve environmental risk assessment.

Career

Research

Overview

The assessment of toxic effects at a relevant scale is an important challenge for the ecosystem protection and management. Indeed, pollutants may impact populations over long-term and represent a new evolutionary force which can be adding itself to the natural selection forces. Thereby, it is necessary to acquire knowledge on the phenotypics and genetics changes that may appear in populations submitted to stress over several generations. Usually statistical analyses are performed to analyse such multigenerational studies. The use of a mechanistic mathematical model may provide a way to fully understand the impact of pollutants on the populations’ dynamics. Such kind of model allows the integration of ecological, evolutionary, and toxic processes into the analysis of ecotoxicological data and the assessment of interactions between these processes.

Aims of the project

The lack of ecological realism in the environmental risk assessment of chemicals has been recognised as a major challenge. Recent advances in the field of ecotoxicological & ecological modelling have the potential to overcome these challenges. Thus the aims of this project are to

(i)  transfer state of the art knowledge in toxicokinetic (TK) & toxicodynamic (TD) and individual based population modelling to an industrial associate,

(ii)  integrate and further develop TK-TD modelling with population level ecological models (specifically individual based models),

(iii)  increase the ecological relevance of the industrial associate’s environmental risk assessment by including ecological factors and processes,

(iv)  integrate mechanistic knowledge into the effect models and

(v)  establish a risk based assessment framework.

Publications

Selected publications

GOUSSEN B., BEAUDOUIN R., DUTILLEUL M., BUISSET-GOUSSEN A., BONZOM J.-M., PERY A.R.R. (2015) Energy-based modelling to assess effects of chemicals on Caenorhabditis elegans: A case study on uranium. Chemosphere 120:507-514. DOI 10.1016/j.chemosphere.2014.09.006

DUTILLEUL M., BONZOM J.-M., LECOMTE C., GOUSSEN B., DAIAN F., GALAS S., RÉALE D. (2014) Rapid evolutionary responses of life history traits to different experimentally-induced pollutions in Caenorhabditis elegans. BMC Evolutionary Biology 14:252. DOI 10.1186/s12862-014-0252-6

BUISSET-GOUSSEN A., GOUSSEN B., DELLA-VEDOVA C., GALAS S., ADAM-GUILLERMIN C., LECOMTE-PRADINE C. (2014) Effects of chronic gamma irradiation: a multigenerational study using Caenorhabditis elegans. Journal of Environmental Radioactivity 127:190-197. DOI 10.1016/j.jenvrad.2014.07.014

GOUSSEN B. (2013) Analyse par modélisation mécanistique des réponses microévolutives d’une population de Caenorhabditis elegans exposée à un stress métallique radioactif. Institut des Sciences et Industries du Vivant et de l’Environnement (AgroParisTech). Doctorat ParisTech. Ph.D. Thesis

GOUSSEN B., PARISOT F., BEAUDOUIN R., DUTILLEUL M., BUISSET-GOUSSEN A., PERY A.R.R., BONZOM J.-M. (2013) Consequences on Caenorhabditis elegans life parameters and sensitivity of multi-generation exposure to uranium. Ecotoxicology 22(5):869-878. DOI 10.1007/s10646-013-1078-5