Development and specification of a toxicokinetic and toxicodynamic growth model of Myriophyllum spicatum for use in risk assessment

Time-variable pesticide exposure occurs regularly in edge-of-field water bodies. The risk for non-target organisms, such as aquatic macrophytes is, however, not based on the time-variable exposure, but on the maximum chemical concentration that occurs. This approach is conservative and protective, but not realistic and might cause an overestimation of the real risk. Alternative risk assessment procedures that experimentally evaluate long-term exposure-profiles can hardly be realized because of the complexity that such experiments require. In this dissertation, a mechanistic toxicokinetic and toxicodynamic growth model of Myriophyllum spicatum was developed that can be used to analyse the effects of long-term exposure-profiles. The model can predict the uptake, the distribution and the elimination of organic chemicals within M. spicatum and link internal chemical concentrations to growth inhibitions. The dissertation is divided into distinct chapters that describe the development of the growth model and of the toxicokinetic and toxicodynamic submodels, in detail. The growth models acts as a basis for the toxicokinetic and the toxicodynamic submodels. It can predict growth under laboratory conditions, by calculating the yield in dry weight in dependency on the light intensity, the temperature, the pH and the amount of dissolved inorganic carbon. The toxicokinetic submodel predicts the internal concentration of organic chemicals on the basis of the external concentration. To parameterize the toxicokinetic submodel, uptake- and elimination-experiments with Isoproturon and Iofensulfuron were conducted, and combined with data that was extracted from the literature. Methods how to estimate chemical-specific parameters, such as the cuticular permeability or the plant/water partition coefficient are presented. The toxicodynamic submodel links the toxicokinetics with the growth of M. spicatum. It establishes an internal dose-response relationship that is used to inhibit plant growth. Based on the effects of Iofensulfuron, it was shown, that the model is able to predict growth inhibitions caused by short-term exposures when toxicological data from a standard toxicity test with constant exposure is available for the model parameterization. To use the model in risk assessment, in which annual chemical exposure-profiles are generated, further physiological processes, that describe the annual life-cycle of M. spicatum, were integrated into the growth model. In this state, the model can be used as a tool in risk assessment, linking the toxicological standard tests from effect assessments with the annual exposure-profiles from exposure assessments. Furthermore, a method is presented on how the outcome of model predictions might be placed in the risk assessment scheme of the European Food Safety Authority