Background: Why this SESSS?
One of the biggest challenges in the ecological risk assessment of chemicals like pesticides, pharmaceuticals, industrial chemicals, personal and home care products and biocides is to extrapolate effects of chemicals across different levels of biological organisation. We measure for example the survival of water fleas in the laboratory but we want to protect aquatic invertebrate populations in the field. In most cases, extrapolation is assumed to be covered by the use of Assessment Factors applied to the results of single species toxicity tests, typically at the organism level. Nevertheless, there is uncertainty on whether this extrapolation is protective enough or overprotective. Extrapolation itself is always a model-driven exercise.
In higher tier risk assessment of some chemicals like pesticides and biocides, experimental approaches are available to address the higher levels of biological organisation, e.g. population studies at the laboratory, field or community level (aquatic micro/mesocosm studies or field studies on soil invertebrates). However, due to their higher complexity, their use in risk assessment is often a matter of debate, and such experiments cannot cover the diversity of potential situations in the field.
Chemical legislations (e.g., REACH and the Biocidal Product Regulation) have on the one hand a high need for standard toxicity testing, but at the same time promote the use of non-animal alternative methods to create this information in order to reduce testing on vertebrate animals. For this purpose, prediction of toxicity across substances is recognised as a potential tool. Alternatively, prediction of the effects on organisms may be done based on sub-individual, in vitro, (cell-based) assays or biomarkers and extrapolating the effects to the organism level. However, although significant progress has been made with respect to modelling approaches, the actual incorporation into the regulatory risk assessment has been very limited.
As of yet, mechanistic models to extrapolate from lower to higher levels of biological organisation have been rarely applied in regulatory risk assessments, e.g. for the assessment of bio-concentration/magnification or dietary exposure in the risk assessment for birds and mammals. New developments which facilitate the extrapolation of effects observed in experiments amongst different levels of biological organisation include the development of quantitative Adverse Outcome Pathways (AOPs), toxicokinetic-toxicodynamic (TK-TD) modelling (link exposure to the organism level), population models (organism to population level) and ecosystem/food-chain models (population to community/ecosystem level) and landscape level models (explicit consideration of spatial heterogeneity in population or ecosystem models). These models can, in general, be linked with each other in order to extrapolate the effects of chemicals from the sub-organism level to the ecosystem level and to use experimental data to parameterise the extrapolations and/or validate them.
One of the biggest advantages of these modelling approaches is that they can not only extrapolate, but also integrate. For example, lethal and sub-lethal effects at the population level can be interactively analysed, and by linking such modelling to landscape scaled models, multiple stressors can be evaluated for different environmental scenarios. Such analyses could help to bring answers to some of today’s big questions in ecological risk assessment, e.g. questions related to the propagation of sub-lethal effects to the population level, effects at landscape scales, multiple stressors and ecological interactions. A key element for data rich substances is to discuss how all available information can be integrated into realistic higher level assessments, e.g. addressing the expected impacts on ecosystem services.