The potential of individual based population models to extrapolate effects measured at standardized test conditions to relevant environmental conditions--an example for 3,4-dichloroaniline on Daphnia magna.

In current risk assessment ecotoxicological biotests (e.g.Daphnia reproduction test) are used to assess the potential impact of xenobiotics on ecosystems. The effects of chemicals and pesticides on populations of non-target organisms in the field depend not only on the exposure and the toxicity, but also on other factors such as life history characteristics. The effects of 3,4-dichloroaniline (3,4-DCA) measured with standardized test procedures, namely the Daphnia immobilisation test (OECD 202) and Daphnia reproduction test (OECD 211), were extrapolated to the population level using an individual-based Daphnia magna population model (IDamP) integrating only the effects on mortality and reproduction. The application of IDamP to extrapolate the effects on population levels was tested on two different population datasets, differing in the start population as well as in the feeding regime. The simulation results were compared to data derived from population experiments under semi-static and flow-through conditions. The IDamP model with an integrated toxicity module was able to predict the effects of 3,4-DCA on the population level under constant laboratory conditions for both datasets. This modelling approach was used to establish concentration-response relationships for 3,4-DCA on the population level. For this purpose two endpoints, the population capacity and the extinction probability, were calculated for different food levels. It turned out that the concentration-response relationship of the population capacity was less influenced by food supply, whereas for daphnid populations exposed to 3,4-DCA the extinction risk was twice as high with lower (environmental relevant) food supply. For both endpoints the lowest EC(50) was calculated to be 25 and 35 µg l(-1). The calculation of concentration-effect relationships on the population level by using a modelling approach provides a tool to extrapolate from effects derived from lab experiments to effects on the population level and can improve the ecological risk assessment of chemicals and pesticides.