The overall aim of QTOX is the development of quantitative extrapolation tools based on mechanistic knowledge of the underlying processes in the chain from exposure to effects, across all levels of biological organisation, with a close connection to regulatory endpoints, and under environmentally realistic conditions, i.e., including the dynamics of chronic exposures to mixtures of chemicals. The aim is to develop predictive models for describing the adverse effects of chemicals under realistic long-term exposure scenarios based on systematic knowledge acquired under laboratory and semi-field conditions.
QTOX will focus on mesocosm studies and test the predictive capability of models on all levels of chemical and biological organisation within a biological community context: the wealth of chemical and biological data from mesocosm experiments provides mechanistic information for the development, evaluation and validation of model predictions.
Radboud research within this project
In Work Package 5 (From individual to community), PhD students relate effects on individuals to impact on populations and communities.
In DC3 (Field indicators of biodiversity) we mechanistically relate lab data to field indicators of biodiversity and productivity widely used in research and management, including mean species abundance, species richness, transfer efficiency and ecological quality classes. Based on previous studies, extended population theory to community models. For parameterisation, data will be obtained from databases and literature. For validation(semi-)field observations from past studies as well experiments carried out by other PhDs will be used. The project will yield a set of theoretically and empirically underpinned relationships to be used both for fundamental understanding as well as practical risk assessment.
In DC4 (Community structure and function) we derive statistically robust and mechanistically based temperature dependence functions covering accumulation and effects of chemicals in scientific (e.g., individual toxicokinetic and -dynamics, population, community) as well as regulatory (e.g., Species Sensitivity Distributions SSDs) models. Literature is reviewed to obtain temperature functions as well as data to derive these functions. The relationships obtained are independently tested on experimental data either from existing or anticipated lab experiments. The project will yield a set of theoretically and empirically underpinned relationships to be used both for fundamental understanding as well as practical risk assessment.
More information about QTOX can be found on the
