Dynamic multi-compartmental modelling of metal bioaccumulation in fish: Identifiability implications

Metal bioaccumulation in fish is influenced by factors specific to the chemical and environmental conditions, the exposure route and the species. For a better understanding of the main interactions among these factors, models are needed to capture the basic principles driving the dynamics of metal bioaccumulation in fish, taking into account different exposure routes and the distribution among representative organs. There is a significant amount of data in the literature concerning metal bioaccumulation experiments in different species of fish. Quantitative information about rate constants of the processes involved in bioaccumulation (diffusion, uptake and elimination) can be obtained from these data by means of dynamic models, that, once validated, can be used for predictive purposes. In this work, a compartmental model structure is developed aiming, in the first instance, to obtain the maximum amount of information from published experimental data. Once calibrated, the model can be further used to predict metal bioaccumulation under different scenarios. The model structure is able to reproduce the experimental behaviour for those species-metal pairs tested and, in addition, is demonstrated to be robust and identifiable. Then, the complete set of parameters can be estimated uniquely, for a specific species-metal pair by using concentration measures in a reduced number of organs. In this way, the optimal parameter sets obtained for different pairs can be compared, and the parameter specificity with respect to the metal or the species can be investigated.