Time-Variable Exposure Experiments in Conjunction with Higher Tier Population and Effect Modeling to Assess the Risk of Chlorotoluron to Green Algae.

An algae population model was applied to describe measured effects of pulsed exposure to chlorotoluron on populations of Pseudokirchneriella subcapitata in 2 laboratory flow-through chemostat tests with different exposure regimes. Both tests enabled evaluation of adverse effects on algae during the exposure and population recovery afterward. Impacts on population densities after chlorotoluron exposure were directly visible as biomass loss in the chemostats. Recovery was observed after each exposure peak. The test results indicate that P. subcapitata is unlikely to show an increased sensitivity to chlorotoluron after pulsed exposure. No altered response or adaptation of the algae to chlorotoluron was observed, with the exception of the last high peak in flow-through test 2. Therefore, an adaptation to the test substance cannot be excluded after long-term exposure. However, recovery to the steady-state level after this peak indicates that the growth rate (fitness) was not significantly reduced in the population with higher tolerance. No differences in chlorotoluron impact on the populations over time in terms of growth were detected. Model predictions agreed well with the measured data. The tests and modeling results validate the model to simulate population dynamics of P. subcapitata after pulsed exposure to chlorotoluron. Model predictions and extrapolations with different exposure patterns are considered reliable for chlorotoluron. The good reproducibility of the population behavior in the test systems supports this conclusion. An example modeled extrapolation of the experimental results to other (untested) exposure scenarios shows a potential approach to using the validated model as a supportive tool in risk assessment. Environ Toxicol Chem 2019;38:2520-2534. © 2019 SETAC.

Modelling effects of time-variable exposure to the pyrethroid beta-cyfluthrin on rainbow trout early life stages.

BACKGROUND: Available literature and regulatory studies show that the severity of effects of beta-cyfluthrin (a synthetic pyrethroid) on fish is influenced by the magnitude and duration of exposure. To investigate how the exposure pattern to beta-cyfluthrin (constant vs peak) may influence the response of the fish, we used a mechanistic effect model to predict the survival and growth of the rainbow trout over its early life stages (i.e. egg, alevin and swim-up fry). We parameterized a toxicokinetic-toxicodynamic (TKTD) module in combination with a dynamic energy budget model enabling us to describe uptake and elimination, as well as to predict the threshold concentration for survival and sublethal effects (feeding behaviour and growth). This effect model was calibrated using data from an early life stage experiment where trout was exposed to a constant concentration of cyfluthrin. The model was validated by comparing model predictions to independent data from a pulsed-exposure study with early life stages of rainbow trout. RESULTS: The co-occurrence of effects on behaviour and growth raised the possibility that these were interrelated, i.e. impairment of feeding behaviour may have led to reduced food intake and slower growth. We, therefore, included 'effect on feeding' as mode of action in the TKTD module. At higher concentrations, the constant exposure led to death. The model was able to adequately capture this effect pattern in the calibration. The model was able to adequately predict the response of fish eggs, alevins and swim-up fry, from both the qualitative (response pattern) and quantitative points of view. CONCLUSIONS: Since the model was successfully validated, it can be used to predict survival and growth of early life stages under various realistic time-variable exposure profiles (e.g. profiles from FOCUS surface water modelling) of beta-cyfluthrin.