A mechanistic sub-model predicting the influence of potassium on radiocesium uptake in aquatic biota.

It is often argued that the quality of science is related to the possibilities of making accurate predictions. It has also long been argued that due to the complex nature of ecosystems, it will never be possible to predict important target variables, especially with more comprehensive dynamic models. New results in radioecology have, however, demonstrated that those arguments are no longer valid. The key to the predictive success lies in the structuring of the model. The accident at Chernobyl has, in fact, provided science with an intriguing opportunity to study how the pulse of 137Cs is transported through ecosystem pathways, thus revealing the basic structure of these ecosystems, i.e. which are the key and the less-important pathways. It is paradoxical to conclude that the Chernobyl accident is, perhaps, the most important factor behind the revolution in predictive ecosystem modelling which lies behind the decrease in the uncertainty factor from 10 to 0.25-0.5. The sub-model for the potassium moderator presented in this paper is an example of a mechanistically based sub-model used within the framework of a more comprehensive lake model for 137Cs. The K-moderator presented is derived from the existing knowledge on ion transport in biological membranes and takes into account ion equilibria modelled by the Nernst equation and the uptake kinetics quantified by the Michaelis-Menten model. It provides the type of structure to this overall lake model that helps to explain the excellent predictive power of this model.