The limits of knowledge

Abstract

Going through the chapters of this book one may get the impression that much is known about the functioning of shallow lake ecosystems. It is tempting to try to combine all this knowledge into one big simulation model that accurately reflects the functioning of real lakes and that can be used to predict the response of the system to different management scenarios. Indeed, for many physical and chemical problems, simulation models have proven a useful tool to predict the system’s behaviour, and in the early 1970s there was great optimism about the possibilities of constructing such detailed simulation models for predicting the dynamics of entire ecosystems. Cooperation of groups of experts on all relevant biological and technical sub-topics led to models integrating the available knowledge as much as possible. The model CLEAN (Bloomfield et al., 1974), constructed as part of the International Biological Program is a good example of this approach. The model contains a diverse spectrum of components such as several fish species, algae, zooplankton, aquatic macrophytes, invertebrates and nutrients, formulated in 28 differential equations. The idea of such modelling approaches was that in the course of the modelling process missing information could be identified, and filled in after additional experimental research. The latter, however, turned out to be a ‘mission impossible’. The number of parameters in such complex models is very large, and the values of many parameters can not be determined within a reasonable amount of time, if they are measurable at all.