Modeling temperature-dependent life-cycle toxicity of thiamethoxam in Chironomus riparius using a DEB-TKTD model.

The neonicotinoid insecticide thiamethoxam (TMX) is widely used to protect crops against insect pests. Despite some desirable properties such as its low toxicity to birds and mammals, concerns have been raised about its toxicity to non-target arthropods, including freshwater insects like chironomids. Whereas multiple studies have investigated chronic effects of neonicotinoids in chironomid larvae at standardized laboratory conditions, a better understanding of their chronic toxicity under variable temperatures and exposure is needed for coherent extrapolation from the laboratory to the field. Here, we developed a quantitative mechanistic effect model for Chironomus riparius, to simulate the species' life history under dynamic temperatures and exposure concentrations of TMX. Laboratory experiments at four different temperatures (12, 15, 20, 23 °C) and TMX concentrations between 4 and 51 µg/L were used to calibrate the model. Observed concentration-dependent effects of TMX in C. riparius included slower growth, later emergence, and higher mortality rates with increasing concentrations. Furthermore, besides a typical accelerating effect on the organisms' growth and development, higher temperatures further increased the effects associated with TMX. With some data-informed modeling decisions, most prominently the inclusion of a size dependence that makes larger animals more sensitive to TMX, the model was parametrized to convincingly reproduce the data. Experiments at both a constant (20 °C) and a dynamically increasing temperature (15-23 °C) with pulsed exposure were used to validate the model. Finally, the model was used to simulate realistic exposure conditions using two reference exposure scenarios measured in Missouri and Nebraska, utilizing a moving time window (MTW) and either a constant temperature (20 °C) or the measured temperature profiles belonging to each respective scenario. Minimum exposure multiplication factors leading to a 10% effect (EP10) in the survival at pupation, i.e., the most sensitive endpoint found in this study, were 25.67 and 21.87 for the Missouri scenario and 38.58 and 44.64 for the Nebraska scenario, when using the respective temperature assumptions. While the results illustrate that the use of real temperature scenarios does not systematically modify the EPx in the same direction (making it either more or less conservative when used as a risk indicator), the advantage of this approach is that it increases the realism and thus reduces the uncertainty associated with the model predictions.

Physiological Dependency Explains Temperature Differences in Sensitivity Towards Chemical Exposure.

In chemical risk assessment, extrapolations from laboratory tests to more realistic conditions are essential to address the toxic effects of pesticides on individuals and populations under field conditions. To transfer toxicological laboratory tests to differing temperature conditions, or outdoor field scenarios, the consideration of temperature dependence is essential and increases realism. Special consideration is given to the impact of temperature on direct sensitivity of organisms to pesticides, for which there are only few modelling approaches available so far. We present a concept for applying physiological temperature dependencies to toxicokinetic-toxicodynamic (TKTD) parameters in the General Uniformed Threshold model of Survival (GUTS). To test this approach in an exemplary study, temperature dependencies from studies on the developmental rate of the mayfly Cloeon dipterum were applied to the parameters of a previously parameterised TKTD model of this species after exposure to imidacloprid. Using a physiologically derived temperature correction for the TKTD rate constants, model predictions for independently conducted toxicology experiments with temperature ranges between 7.8 and 26.4 °C were performed for validation. Our approach demonstrates the successful transfer of a physiological observed temperature dependency on toxicity parameters and survival patterns for Cloeon dipterum and imidacloprid as a case study.

Tool for selecting indicator substances to evaluate the impact of wastewater treatment plants on receiving water bodies.

The elimination of organic micropollutants (OMPs) from wastewater could in future become mandatory for operators of wastewater treatment plants (WWTPs). Indicator substances are a great help and a cost-efficient way in monitoring the pollution of water bodies with OMPs caused by the discharge of WWTPs. However, with the still increasing number of OMPs in our environment, the selection of suitable indicator substances presents a challenge. A concept was developed to help identify representative indicator substances. The derived indicator substances are not only used to assess water pollution, but can also be used to calculate elimination efficiencies of WWTPs. In the present investigations, the indicator substances were used to evaluate the reduction of OMPs in the water body on the basis of the expansion of a WWTP with an ozonation plant. The transferability of the tool was verified with a second WWTP. Furthermore, the impact of the number of measurements was analysed via statistical combinatorics. With the tool, 36 substances were classified, leading to the identification of 9 suggested indicator substances. Among them ibuprofen and diclofenac attracted attention due to their ecotoxicological relevance. Detailed data analyses were carried out using principal component analysis (PCA) and loads.

Mechanistic Effect Modeling Approach for the Extrapolation of Species Sensitivity.

In the higher-tier environmental risk assessment of chemicals, species sensitivity distributions (SSDs) are used to statistically describe differences in sensitivity between species and derive community level endpoints. SSDs are usually based on the results from short-term laboratory experiments performed under constant environmental conditions. However, different species may be kept at different "optimal" temperatures, which influence their apparent sensitivity and thus the derivation of endpoints. Also, the extrapolation capacity of SSDs is largely limited to the tested species and conditions. Time-variable exposures and effects at higher levels of biological organization, including biological interactions, are not considered. The quantitative effect prediction at higher tiers would ultimately require the extrapolation of toxicokinetics and toxicodynamics to untested species and the involvement of population and community modeling. In this regard, we tested a toxicokinetic-toxicodynamic modeling approach to mechanistically consider and correct endpoints for ambient temperature and demonstrate the significance for SSDs. We explored correlations in toxicokinetic-toxicodynamic model parameters which would allow for the extrapolation of sensitivities to untested species. Finally, we illustrate the applicability of the approach for higher level effect predictions using an individual-based model. Our results suggest that mechanistic effect modeling approaches can reduce the uncertainties in higher tier effect assessments related to knowledge gaps.

Ecological Recovery Potential of Freshwater Organisms: Consequences for Environmental Risk Assessment of Chemicals.

Chemical contaminants released into the in the environment may have adverse effects on (non-target) species, populations and communities. The return of a stressed system to its pre-disturbance or other reference state, i.e. the ecological recovery, may depend on various factors related to the affected taxon, the ecosystem of concern and the type of stressor with consequences for the assessment and management of risks associated with chemical contaminants. Whereas the effects caused by short-term exposure might be acceptable to some extent, the conditions under which ecological recovery can serve as a decision criterion in the environmental risk assessment of chemical stressors remains to be evaluated. For a generic consideration of recovery in the risk assessment of chemicals, we reviewed case studies of natural and artificial aquatic systems and evaluate five aspects that might cause variability in population recovery time: (1) taxonomic differences and life-history variability, (2) factors related to ecosystem type and community processes, (3) type of disturbance, (4) comparison of field and semi-field studies, and (5) effect magnitude, i.e., the decline in population size following disturbance. We discuss our findings with regard to both retrospective assessments and prospective risk assessment.

Identification of realistic worst case aquatic macroinvertebrate species for prospective risk assessment using the trait concept.

PURPOSE: Approaches in environmental risk assessment for pesticides are becoming more and more realistic. Thereby, risk assessment has to be protective in a way that no long-lasting (adverse) effects on populations will occur in the environment. Since this imperative includes species generally showing high population vulnerability due to their life history traits, prospective risk assessment should be based on realistic worst cases. Based on life history traits, the purpose of the current study was to verify whether a worst case combination of low potential for intrinsic recovery and low ability for recolonisation can be found in the field. METHODS: Combinations of traits related to dispersal ability and reproduction of macroinvertebrates were investigated using monitoring data from edge of field water bodies in Germany. The relative distribution of traits was analyzed across different agricultural regions and across sites of different potential for exposure to pesticides. Species were sorted in a tiered approach in order to gain a list of realistic worst case species. RESULTS: Life history traits were found equally distributed across different regions. Thereby, dispersal ability and voltinism were not randomly combined. Within the data analysed, low dispersal ability was found to be exclusive to semivoltine taxa. Owing to their appearance in reference sites, poor dispersal ability and a long time reproduction, three species were considered potentially worst case. CONCLUSIONS: The trait approach was found to be suitable in comparing trait distributions within different regions and in compiling a list of critical taxa for consideration in environmental risk assessment.