There is growing evidence that, in order to effectively assess the risk of chemicals, it is crucial to take the role of species interactions into account. Due to the large number of possible species assemblies, it is desirable to develop predictive, mechanistic models that can be calibrated with standard toxicity data.
Therefore, we have conducted life-table experiments with Daphnia magna, D. pulex and D. longispina, exposed to Cu, Ni and Zn, in order to calibrate individual-based models based on Dynamic Energy Budget Theory (DEB-IBM). We derived DEB parameters from control data and calibrated modules for lethal and sublethal effects of Cu, Ni and Zn.
Species were combined in silico into binary and tertiary communities and community dynamics under metal exposure were simulated.
In the DEB-IBM, interspecific interactions emerge from physiological properties via competition for a shared resource. Each DEB parameter has direct or indirect consequences for resource utilization, and therefore for species interactions. Chemical stressors have the potential to alter these interactions, because effects are implemented as changes in DEB parameters.
We modelled the effects of metals on two community-level endpoints, productivity and community structure. The two endpoints are inherently different because only productivity is subject to functional redundancy, leading to large differences in community-level sensitivity, based on which endpoint is chosen.
While effects of metals on community-level endpoints can in principle be deduced from DEB theory, experiments to validate the predictions generated with the DEB-IBM are still lacking, and are crucial to evaluate the usefulness of our approach in application.
We believe that the use of DEB-IBMs to investigate effects of chemical stressors on higher levels of biological organizations can be fruitful, because data for calibration can be generated relatively easily and models can be developed from established, biology-based frameworks
