Benoit Goussen, Cecilie Rendal, Emma Butler, Roman Ashauer, Oliver R. Price
SETAC Brussels 2017. Brussels, Belgium
Publication year: 2017
The lack of ecological realism in current prospective environmental risk assessment is widely recognised as a limitation in this field. As organisms are living in a multistressed environment, involving both chemical and environmental stressors, it is worth understanding how these combined stressors will affect the organisms and subsequently the populations. A way forward to include more ecological relevance in ERAs is the use of environmental scenarios that will represent key differences in environmental factors such as the food availability, the temperature variability, the predation, etc. and in exposure factors.
All these factors will influence the capability of an organism to grow and reproduce as well as its resilience to additional stressors. As 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 organism, how stressors can impact these fluxes, and how this will affect the organism’s life history traits.
In this project, we assessed how DEB modelling can predict effects of various chemicals in variable environmental conditions. To do so, we produced two set of data for each chemical. In the first one, Ceriodaphnia dubia individuals fed ad-libitum and were maintained at reference temperature (25°C). In the second set of data, C. dubia individuals were maintained at a different temperature and feeding regime. For the purpose of this exercise, this second set of data was not disclosed to the team in charge of the DEB modelling.
We used the first set of data only to calibrate the DEB model for C. dubia. Then knowing only the experimental conditions of the second set, we performed a blinded prediction of the growth, reproduction, and survival of C. dubia under environmental conditions that have not been used for the calibration. Blinded predictions and datasets were then compared and the ability of the DEB model to handle and accurately predict non-tested environmental conditions (temperature and feeding level) was analysed and discussed.
A DEB analysis of responses to baseline toxicant in C. dubia and D. magna
Benoit Goussen, Cecilie Rendal, Emma Butler, Jayne Roberts, Oliver R. Price, Antonio Franco, Todd Gouin, Geoff Hodges, Tjalling Jager
SETAC Nantes 2016. Nantes, France.
Publication year: 2016
Presenting author: Benoit Goussen
Mechanistic effects models are gaining interest in the scientific community and in regulatory settings. These models have the potential to facilitate species extrapolation, thereby decreasing the need for toxicity testing for risk assessment. They also provide an opportunity to quantify the complexities of multiple interacting stressors on environmental scenarios. Dynamic energy budget (DEB) theory represents a unifying framework for assessing the mechanisms that drive toxicant effects on life history traits. We report here on the progress of two case studies for an example chemical tested on two species of Cladocerans, Ceriodaphnia dubia and Daphnia magna. Over 70% of the ingredients in home and personal care products are considered baseline toxicants. We use phenol as a model baseline toxicant. A dynamic energy budget model was calibrated for each species, and differences in parameters and physiological mode of action are discussed. This work also explores how DEB based modelling can incorporate environmental factors such as food availability and temperature into risk assessment. In conclusion, the present study demonstrates the potential utility of DEB based models for species extrapolation and chemical risk assessment in an AOP framework.
Towards ecological relevance in PERA: a DEB-IBM approach
Benoit Goussen, Cécilie Rendal, Antonio Franco, Oliver R. Price, Roman Ashauer
Salt Lake City 2015. Salt Lake City, UT, USA
Publication year: 2015
Presenting author: Oliver R. Price
Ecological relevance is increasingly recognised as an important challenge for environmental risk assessment (ERA). The integration of ecological scenarios with chemical effect models to achieve quantitative ERA promises to increase ecological relevance of ERA. We discuss some of the challenges and opportunities involved in bringing these new concepts into everyday risk assessment for down-the-drain chemicals. One of the key questions revolves around understanding the protection goal for anthropogenic stressors in specific ecological scenarios, and
indeed whether certain scenarios require specific modified protection goals. Once the specific protection goal has been established, a metric to suit both the specific ecological scenario and protection goal needs to be defined and agreed. The selection of this endpoint must be carefully considered as different options will lead to different interpretation. Population-level models linked with mechanistically based bioenergetics models are potential powerful tools for ecologically relevant ERA because they provide a quantitative link between chemical effects and ecological factors. However, the practical use and communication of ecological model predictions for decision making may not always be straight forward. Probabilistic environmental risk assessment (PERA) has been suggested as a way to make uncertainty more explicit and to account for biological, spatial and temporal variability. The outcome of a PERA is typically a measure of expected risk with an associated uncertainty interval. We present how probabilistic approaches and advancements in population modeling can be linked to incorporate more ecological relevance into risk assessments while keeping both uncertainty and variability explicit and transparent. To do so, we use an individual based model integrating a dynamic energy budget model to assess the potential impact of chemicals associated with local environmental characteristics. This mechanistic model must be applicable to multiple types of stress,
both anthropogenic (e.g., chemicals, wastewater plant effluents) and environmental (e.g., temperature, predation, starvation, competition). We also discuss how the magnitude of an adverse event will impact the level of risk we are willing to accept and argue that the relation between the level of acceptable risk and the severity of the effect should be made explicit to facilitate decision-making.
Can mechanistic effects models coupled with geo-referenced exposure models add ecological relevance to risk assessment?
Population-level models are increasingly recognised as potentially powerful tools in environmental risk assessment. However, the practical application of dynamic population predictions for decision making is not straight forward in everyday risk assessment of down-the-drain chemicals. Probabilistic environmental risk assessment (PERA) has been suggested as a way to make uncertainty more explicit and to account for spatial and temporal variability. The outcome of a PERA is typically a measure of expected risk with an associated uncertainty interval. We present a conceptual framework that explores how probabilistic approaches can be applied in population models to incorporate more ecological relevance into risk assessments while keeping both uncertainty and variability explicit and transparent. One of the key challenges is understanding the protection goals for ecological scenarios exposed to anthropogenic stressors. For instance, systems that are already impaired by high volume emissions of untreated wastewater may require modified protection goals (e.g. protection of microbial purification processes and recovery of food web structure and diversity). For higher organisms, the protection goals must be reflected by a defined set of endpoint metrics that can quantify changes in population-level dynamics. These metrics must be carefully selected based on both the specific scenario and protection goal, as different options will lead to very different interpretations of effect. Finally we discuss the importance of making the relation between the willingness to accept risk and the severity of the effect explicit to facilitate decision-making. We consider these discussions a necessary first step in bringing the full potential of population-level models into risk assessment of down-the-drain chemicals.
Suivi multigénérationnel d’une toxicité chronique : le cas de la reproduction chez Caenorhabditis elegans