Modelling the Effects of toxicants on population recovery and extinction – Example of Daphnia magna for toxicants with different mechanisms of action.
Faten Gabsi, PhD project, RWTH Aachen, Germany
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Fig.1 Conceptual diagram of the asexual life-cycle of Daphnia magna in the IDamP model
Potential pesticide exposure effects on freshwater communities need to be addressed in ecological risk assessment and environmental science. In addition to determining the impact of these toxicants at the level of the individual, it is essential to consider the population level effects as in most cases, the sustainability of the population is the primary aim of protection.
However, the effects of chemicals and pesticides on populations in the field depend not only on the exposure and the toxicity, but also on other factors such as life history characteristics. Population models are increasingly being considered as a major tool for ecological risk assessment of chemicals. In addition to their potential of establishing population-level endpoints, they also allow exploring how risk depends on exposure and toxicity as well as on relevant ecological factors. Besides, population models also permit the extrapolation of risk assessments between species and different environments.
In this project, we aim to define a strategy for implementing the effects of pesticides with various mechanisms of action on the cladoceran Daphnia magna in an existing individual-based population model (IDamP) (Fig.1) which will be used as the starting point to extrapolate effects from the individual to the population level.
Therefore, different effect models (mathematical description of the relation between exposure and an individual level endpoint, e.g number and size of neonates) will be implemented in IDamP in order to investigate how effects of sub-lethal concentrations will manifest on population dynamics. The model outcome will be tested against measured population dynamics for three toxicants with different mechanisms of action including inhibition of reproduction (Dispersogen A) and male formation (Periproxyfen). Exposure to an undefined plant protection product will also be tested.
The selected mechanisms of action require some adds on for the IDamP model to be able to simulate the mechanism of interest without the impact of a toxicant. For example, implementing the reproductive shift effect caused by Dispersogen A into the model asks for the adequate simulation of neonate size depending on food concentration, density and size of the mother which is not included in IDamP yet. Additionally, male production has to be implemented, including male growth and feeding, in order to simulate the effects of Periproxyfen on the individual level.
The used effect models will be selected for their suitability to describe the sub-lethal effects and their data need. Thereby, the balance between complexity and data availability will be considered. If sub-lethal effects do not vary in time, a simple concentration-response curve will be used. Otherwise dynamic models either empirical or mechanistic will be selected.
Once the model achieved, the output of the simulation will be tested against laboratory and mesocosm data available, which will be collected for different exposure scenarios. After integrating the different effect models into the IDamP, we will be able to extrapolate the effects from laboratory to mesocosm and to predict the effects at the field level.
Supervisor: Thomas G. Preuss (RWTH Aachen)
Co-supervisor: Volker Grimm (UFZ)
Associated partners: gaiac; Bayer; BASF; UBA
