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Modelling effects of exposure to mixtures of chemicals on a multi-species level

Final Report Summary - BIOME (Modelling effects of exposure to mixtures of chemicals on a multi-species level)

This project goes to the heart of our thinking about environmental quality and effects of compounds like: metals, minerals, pesticides, nutrients, PAHs, etc. that can be found in our environment. Typically in real life species are not exposed to only one single compound but to a mixture of different compounds at the same time, something that is not incorporated in current environmental management and assessment. Still in past research we have shown that combined exposure to only 8 metals can cause a species (e.g. daphnids) to go extinct within 24 hrs even if the corresponding surface water complies with regulations and none of the concentrations of individual metals exceeds their individual environmental quality standard.
The overall aim of this research is to understand effects of mixtures of compounds on biodiversity. In any approach where effects of exposure to more than one compound is involved, models are of vital importance, as a mixture of 20 different compounds will lead to over 1,000,000 different possible mixtures. The scale of which makes it impossible to tackle this problem in a pure experimental setting. We started off with a process-based model based on the energy use of species. This modelling approach has very good extrapolation potential from one species to the next but also from one compound to another. The model was based on previous work for the interpretation of mixture data for a single species.
The overall aim of the project was split down in more manageable project objectives:

• Further develop the model to predict effects for untested species;
• Apply QSAR approaches to predict effects for untested compounds;
• Make use of existing experimental data on exposures, effects and the occurrence of species to evaluate the approach.

The project started with the aim of address the question ‘What is it that makes a species sensitive to toxic poisoning?’
In answering this question like this there are two major sub-questions that need to be answered. The first is about effects of different compounds and the second is about why species differ in their sensitivity. Both were addressed in the research. The first step was to focus on a large group of chemicals with a general mode of action, usually called narcotics. I mined the available literature for suitable data and used existing and new QSAR approaches to predict the sensitivity of species. It showed that the predictive power of this approach is good and the whole time course of toxic effects can be predicted with accuracy for a huge variety of species, solely based on the physico-chemical properties of the compounds involved (Baas et al. SAR and QSAR in Env. Res. Vol. 26, No. 3, 165–180, 2015).

From there the focus was shifted to compounds with a very specific mode of action (insecticides) and how this affects different species. Again the scientific literature was mined for suitable data on effects of insecticides combined with data metabolic turnover for different species. I was able to link the sensitivity of a species to its metabolic turnover. This is a rather intuitive idea, but it was not tested or published before. The general idea is that a high metabolic turnover (so very active species that burn a lot of energy) makes it easier to interfere with the species, making it more sensitive. A spin off of this insight is that the size of a species, which is often suggested in scientific literature as a factor determining sensitivity, is not the driving force. It appears to be the metabolic turnover that is the driving force and not size. Though, size appears to be important as smaller species tend to have a higher metabolic turnover (Baas and Kooijman. Ecotoxicology, 24:657-663, 2015).

The QSAR work and the work on pesticides provided the basis for the evaluation of large scale monitoring programmes on pesticides. UK and Dutch government bodies responsible for environmental monitoring programmes on pesticides kindly made their data available for a re-interpretation of the data for mixture effects. I interpreted the data of the different monitoring programmes with the mixture model that we developed earlier and based on the species sensitivity research that was described above. In total well over 1 million individual measurements were evaluated. This part of the research was summarised in a manuscript submitted for publication. The most important insights are:

• Mixture effects are important in the majority of cases, in the most extreme cases severe acute effects can be expected. The most polluted samples would cause a population of a sentinel species to go extinct within 30 hrs of exposure.
• Due to mixture effects it is impossible to make a statement on whether or not the environment is actually affected at the sample sites, despite all the effort that is put in the monitoring programmes.

From an environmental management point of view the most important conclusion is that due to the high toxicity, insufficient sensitivity of the analytical procedures and the combined exposure to pesticides it is impossible to make a statement on whether or not the environment is actually affected at the sample sites, despite all the physical and financial effort that is put in the monitoring programmes!

The model proved to be versatile in the sense that its line of reasoning also allowed for new insights in the field of nano-materials. Efects of nano-materials are basically mixture effects of the nano-materials themselves and their (slow released) ions. The results of our work on nano-materials were published in three papers (He et al. Env Tox and Chem, 9999, pp. 1-10, 2014; Liu et al. Ecotox and Env Saf. 122, 37–44, 2015; Liu et al., 2016).
The modelling approach was also used for the assessment of effects of mixtures of pesticide and metals on different bee species. In the host institute (NERC-CEH) toxicity of single compounds and mixtures of metals and pesticides was tested in a laboratory setting to get a better understanding of the observed (almost) world-wide decline in bee populations. The data generated from this work was ideal to be analysed with my modelling approach. This resulted in a total of three manuscripts which will be submitted in 2016.

In addition to the scientific papers the results of the research were communicated in different lectures in national and international forums, both governmental and scientific. In addition the research that was conducted resulted in invitations to take part in discussions about bee decline, assessment of oil drilling in the arctic and in general biologically based modelling as an invited expert. My approach is also the focus of an appraisal of its feasibility for future implementation in to risk assessment approaches being organised and supported by the European Food Safety Authority.

The final results of the project can be summarised as a better understanding of species sensitivity, the possibility to include impacts of mixtures on different species and a far better understanding of the underlying mechanisms in toxic effects, which allows for an improved Environmental Quality Assessment.