A flow-through system was developed to investigate the effects of time-variable exposure of pesticides on algae. A recently developed algae population model was used for simulations supported and verified by laboratory experiments. Flow-through studies with Desmodesmus subspicatus and Pseudokirchneriella subcapitata under time-variable exposure to isoproturon were performed, in which the exposure patterns were based on the results of FOrum for Co-ordination of pesticide fate models and their USe (FOCUS) model calculations for typical exposure situations via runoff or drain flow. Different types of pulsed exposure events were realized, including a whole range of repeated pulsed and steep peaks as well as periods of constant exposure. Both species recovered quickly in terms of growth from short-term exposure and according to substance dissipation from the system. Even at a peak 10 times the maximum predicted environmental concentration of isoproturon, only transient effects occurred on algae populations. No modified sensitivity or reduced growth was observed after repeated exposure. Model predictions of algal growth in the flow-through tests agreed well with the experimental data. The experimental boundary conditions and the physiological properties of the algae were used as the only model input. No calibration or parameter fitting was necessary. The combination of the flow-through experiments with the algae population model was revealed to be a powerful tool for the assessment of pulsed exposure on algae. It allowed investigating the growth reduction and recovery potential of algae after complex exposure, which is not possible with standard laboratory experiments alone. The results of the combined approach confirm the beneficial use of population models as supporting tools in higher-tier risk assessments of pesticides.

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