Modelling population dynamics in mesocosms using an individual-based model coupled to a bioenergetics model

Developing population models is of great interest as these models enable to extrapolate toxicity observed at the molecular or individual levels to the population level, and thus improve environmental risk assessment of chemical substances. For this purpose, accounting for natural variations of environmental conditions and prey dynamics along with the chemical stress is needed. In this study, an individual-based model (IBM) coupled to a Dynamic Energy Budget (DEB) model was developed in order to predict three-spined stickleback population dynamics in semi-controlled stream experiments (in mesocosms). Datasets obtained in mesocosms offer the opportunity to develop and evaluate the model predictions. The most sensitive parameters of the DEB-IBM were identified by sensitivity analyses and were calibrated based on data from two independent mesocosm experiments. The predictive capacities of our model were subsequently evaluated using three independent mesocosm datasets under different environmental scenarios. Finally, our model was applied to a theoretical case of toxic effects to show an example of application of the model in a regulatory context. While the most uncertain population processes (in particular, competition for food in mesocosms) in our three-spined stickleback DEB-IBM could be modelled more accurately, our model can already serve to assess the impacts of toxicants at the population level by improving the analyses of mesocosm experiments, in decreasing the uncertainty of the experimental results. Therefore, in a second step, it could be used to predict the consequences on viability of a population exposed to a contaminant under various environmental and exposure scenarios.