Abstract:

The lack of ecological realism in current prospective environmental risk assessment (ERA) is widely recognised as a limitation in this field. Since organisms live in a multistressed environment, involving both chemical and environmental stressors, it is important to understand how these combined stressors can affect individuals and subsequently their populations. One way of including more ecological relevance in ERAs is the use of environmental scenarios that represent variation in environmental factors such as food, temperature, predation, competition and in factors that influence exposure.

All these factors will influence the capability of an organism to grow and reproduce as well as its resilience to additional stressors. Since growth and reproduction are driven by an organisms’ energy balance, Dynamic Energy Budget models are particularly well suited to integrate toxicant and environmental stressors. Indeed, the DEB theory analyses the fluxes of energy within an individual, how stressors can impact these fluxes, and how this will affect the organism’s life history traits. This mechanistic description of an individual can then be used as a building block for a population model.

In this project, we performed a meta-analysis of the literature in order to analyse the effects of combinations of ecological and chemical stressors on individuals. We then used this analysis to derive quantitative relationships that describe the effects on their bioenergetic fluxes. We analysed how these stressor combinations affected the life-history traits of the organisms and their ability to cope.

We assessed the implementation of these patterns using a DEB based model for Ceriodaphnia dubia. Using the derived quantitative relationships, we predicted the effects of mixtures of environmental and/or chemical stressors on the growth, the reproduction and the survival of individuals. This mechanistic description of the organisms can then be used as a building block in order to assess the effects of these mixtures on a higher level of organisation, through a population model for instance. The accuracy of our predictions was evaluated by comparison with experimental data.

The resulting models will have the potential to account for the effect of chemicals on individuals and populations in different environmental scenarios

Presenting author: Sandrine Charles

Abstract:

The General Unified Threshold model of Survival (GUTS) provides a theoretical framework for analysing stressor effects on survival over time through consistent model equations based on different assumptions about the stressor quantification, the compensatory processes and the nature of the death process. In ecotoxicology, stressors are toxicants characterised by a dose metric, e.g. the concentration in the medium surrounding an organism or inside the organism, or by the damage quantity they cause. The key GUTS feature is that mortality is estimated when the dose metric exceeds a certain threshold. Several GUTS flavours can be derived according to the assumption underlying the death process: (i) the threshold is distributed within a population, and when exceeded, the individual dies (individual tolerance, IT); (ii) there is one common threshold for all individuals, and when exceeded, the probability to die increases (stochastic death, SD); (iii) a unification of both previous assumptions (GUTS proper). While more realistic, GUTS proper requires the estimation of one additional parameter. Because environmental risk assessment of chemicals depends on robust estimates of GUTS parameters, we investigated parameter identification for GUTS proper, in relation to the experimental design of ‘short-term’ laboratory bioassays. In practice, standard survival datasets generally do not contain enough information to estimate all parameters of GUTS proper with sufficient precision. This is because a large number of individuals is required to provide strong information on probabilistic events. Hence, based on simulated datasets we identify appropriate experimental designs suitable to estimate all parameters of GUTS proper with the best possible precision. We show that datasets with a high number of animals per treatment allow for parameter estimation of GUTS proper with reasonable accuracy and precision. Moreover, increasing the number of animals or the duration of the experiment substantially reduce the uncertainty around the median value of the threshold. Nevertheless, general statements about optimisation for any chemical, any species, any test duration and/or any exposure concentration profile remain difficult. As take-home message, to the extent possible, we recommend not to use fixed experimental set-up for GUTS analyses, but rather tailor dedicated designs according to the chemical, the species and/or the research/regulatory question at hand.

Presenting author: Benoit Goussen

Abstract:

Presenting author: Adeline Buisset-Goussen

Abstract:

The assessment of environmental impact of exposure to ionizing radiation (natural and ubiquitous phenomenon enriched by human activities) has become a major concern. However, this environmental risk assessment is currently hampered by the lack of knowledge, and hence, is often based on extrapolation from data obtained for acute exposure. Studies on chronic exposure over several generations are so needed to understand the disturbances related to ionizing radiation and their possible consequences on the population. Regarding this background, we assessed the effects of chronic exposure to ionizing radiation over three generations of the ubiquitous nematode Caenorhabditis elegans. In this study C. elegans were chronically and individually exposed to gamma radiation (dose rates ranging from 6.6 to 42.7 mGy/h). The evolution of growth and reproduction (here, cumulated number of larvae per individual) of individuals were followed daily. Comparisons within and between the generations of C. elegans subjected to different exposure statuses: (i) three generations continuously exposed (F0, F1, and F2) and (ii) parental generation exposed (F0) and the following generations placed in recovery (F1’ and F2’) were performed. Our experiment showed no significant difference in growth between the control and the exposed individuals whatever the generation and the exposed status. However we observed a decrease in the reproductive ability between F0 and F2 at the highest dose rate (42.7 mGy/h). We also observed significant differences in the same generation subjected to different exposure statuses (exposed (F1) or recovery (F1’)). Surprisingly, the non-exposed generation (F1’) laid out less number of eggs than the exposed generation (F1). Our results confirmed that reproduction is the most sensitive endpoint affected by ionizing radiation and revealed transgenerational effects from parental exposure in the second generation (F1’) and the third generation (F2). Using these results on reproduction, molecular and cellular effects of chronic exposure to ionizing radiations on germline are examined to better understand the mechanisms underlying the observed effects

Presenting author: Benoit Goussen

Abstract (French):

L’évaluation des effets des polluants à des échelles biologiquement et écologiquement pertinentes est un important problème dans la protection des écosystèmes. En effet, les conséquences à long terme de polluants sur les populations sont très peu étudiées alors que les populations naturelles sont souvent exposées à des polluants de façon chronique sur de nombreuses générations. Dans ce contexte, nous avons élaboré un nouveau modèle de type individu-centré couplé avec un modèle bioénergétique de type Dynamic Energy Budget (DEB) afin d’étudier la dynamique évolutive de populations soumises à des contraintes environnementales. Il s’agit d’une base pertinente pour comprendre et modéliser les liens entre (i) les perturbations liées à l’assimilation et (ii) les fluctuations de croissance et de reproduction chez des individus exposés à des stress anthropiques (e.g. polluant, changements globaux). Ce modèle permet une meilleure évaluation des conséquences potentielles sur les populations sur plusieurs générations.

Afin d’illustrer la pertinence de ce type de modélisation, nous présenterons les résultats obtenus suite à des travaux concernant les effets multi-générationnels d’un métal lourd radioactif, l’uranium, sur deux modèles d’invertébrés (Chironomus riparius et Caenorhabditis elegans).

Par exemple, les résultats obtenus chez C. riparius nous ont permis de modéliser la dynamique des populations au cours des générations et de caractériser les effets de l’uranium sur les populations exposées. Ces résultats montrent que (i) l’uranium conduit à une sélection de phénotypes particuliers via une survie différentielle et (ii) entraîne une augmentation de la tolérance des populations exposées au fil des générations.

En conclusion, l’application de ce type de modèle nous a permis de quantifier et de mieux comprendre les effets d’un stress sur la dynamique d’une population à partir des règles de comportement et de structuration de ses différents éléments (i.e. les individus, avec leurs propres caractéristiques biologiques et toxicologiques).

Presenting author: Benoit Goussen

Presenting author: Morgan Dutilleul

Presenting author: Benoit Goussen

Presenting author: Morgan Dutilleul

Presenting author: Benoit Goussen