Comparison of bioassays with different exposure time patterns: the added value of dynamic modelling in predictive ecotoxicology

In Silico Methods for Environmental Risk Assessment: Principles, Tiered Approaches, Applications, and Future Perspectives

This chapter aims to introduce the reader to the basic principles of environmental risk assessment of chemicals and highlights the usefulness of tiered approaches within weight of evidence approaches in relation to problem formulation i.e., data availability, time and resource availability. In silico models are then introduced and include quantitative structure-activity relationship (QSAR) models, which support filling data gaps when no chemical property or ecotoxicological data are available. In addition, biologically-based models can be applied in more data rich situations and these include generic or species-specific models such as toxicokinetic-toxicodynamic models, dynamic energy budget models, physiologically based models, and models for ecosystem hazard assessment i.e. species sensitivity distributions and ultimately for landscape assessment i.e. landscape-based modeling approaches. Throughout this chapter, particular attention is given to provide practical examples supporting the application of such in silico models in real-world settings. Future perspectives are discussed to address environmental risk assessment in a more holistic manner particularly for relevant complex questions, such as the risk assessment of multiple stressors and the development of harmonized approaches to ultimately quantify the relative contribution and impact of single chemicals, multiple chemicals and multiple stressors on living organisms.

Modelling algae-duckweed interaction under chemical pressure within a laboratory microcosm

Contaminant effects on species are generally assessed with single-species bioassays. As a consequence, interactions between species that occur in ecosystems are not taken into account. To investigate the effects of contaminants on interacting species dynamics, our study describes the functioning of a 2-L laboratory microcosm with two species, the duckweed Lemna minor and the microalgae Pseudokirchneriella subcapitata, exposed to cadmium contamination. We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae, growth of duckweeds, interspecific competition between the two species and cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 μg·L(-1). For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. Only duckweed dynamics was affected by interspecific competition, while algal dynamics was not impaired. Growth rate of both species decreased with cadmium concentration, as well as competition intensity showing that the interspecific competition pressure on duckweed decreased with cadmium concentration. This innovative combination of mechanistic modelling and model-guided experiments was successful to understand the algae-duckweed microcosm functioning without and with contaminant. This approach appears promising to include interactions between species when studying contaminant effects on ecosystem functioning.

Comparison of laboratory batch and flow-through microcosm bioassays

Since 1997, we have been developing a protocol for ecotoxicological bioassays in 2-L laboratory microcosms and have applied it to the study of various pollutants and ecotoxicological risk assessment scenarios in the area of urban facilities and transport infrastructures. The effects on five different organisms (micro-algae, duckweeds, daphnids, amphipods, chironomids) are assessed using biological responses such as growth, emergence (chironomids), reproduction (daphnids) and survival, with a duration of exposure of 3 weeks. This bioassay has mainly been used as a batch bioassay, i.e., the water was not renewed during the test. A flow-through microcosm bioassay has been developed recently, with the assumption that conditions for the biota should be improved, variability reduced, and the range of exposure patterns enlarged (e.g., the possibility of maintaining constant exposure in the water column). This paper compares the results obtained in batch and flow-through microcosm bioassays, using cadmium as a model toxicant. As expected, the stabilization of physico-chemical parameters, increased organism fitness and reduced variability were observed in the flow-through microcosm bioassay.

Statistical handling of reproduction data for exposure-response modeling

Reproduction data collected through standard bioassays are classically analyzed by regression in order to fit exposure-response curves and estimate ECx values (x% effective concentration). But regression is often misused on such data, ignoring statistical issues related to (i) the special nature of reproduction data (count data), (ii) a potential inter-replicate variability, and (iii) a possible concomitant mortality. This paper offers new insights in dealing with those issues. Concerning mortality, particular attention was paid not to waste any valuable data-by dropping all the replicates with mortality-or to bias ECx values. For that purpose we defined a new covariate summing the observation periods during which each individual contributes to the reproduction process. This covariate was then used to quantify reproduction-for each replicate at each concentration-as a number of offspring per individual-day. We formulated three exposure-response models differing by their stochastic part. Those models were fitted to four data sets and compared using a Bayesian framework. The individual-day unit proved to be a suitable approach to use all the available data and prevent bias in the estimation of ECx values. Furthermore, a nonclassical negative-binomial model was shown to correctly describe the inter-replicate variability observed in the studied data sets.

The molecular basis of simple relationships between exposure concentration and toxic effects with time

Understanding the toxicity of chemicals to organisms requires considering the molecular mechanisms involved as well as the relationships between exposure concentration and toxic effects with time. Our current knowledge about such relationships is mainly explained from a toxicodynamic and toxicokinetic perspective. This paper re-introduces an old approach that takes into account the biochemical mode of action and their resulting biological effects over time of exposure. Empirical evidence demonstrates that the Druckrey-Küpfmüller toxicity model, which was validated for chemical carcinogens in the early 1960s, is also applicable to a wide range of toxic compounds in ecotoxicology. According to this model, the character of a poison is primarily determined by the reversibility of critical receptor binding. Chemicals showing irreversible or slowly reversible binding to specific receptors will produce cumulative effects with time of exposure, and whenever the effects are also irreversible (e.g. death) they are reinforced over time; these chemicals have time-cumulative toxicity. Compounds having non-specific receptor binding, or involving slowly reversible binding to some receptors that do not contribute to toxicity, may also be time-dependent; however, their effects depend primarily on the exposure concentration, with time playing a minor role. Consequently, the mechanism of toxic action has important implications for risk assessment. Traditional risk approaches cannot predict the impacts of toxicants with time-cumulative toxicity in the environment. New assessment procedures are needed to evaluate the risk that the latter chemicals pose on humans and the environment. An example is shown to explain how the risk of time-dependent toxicants is underestimated when using current risk assessment protocols.