The maximum exergy principle presumes that an ecosystem with its species composition tends to move as far away from thermodynamic equilibrium as possible under the prevailing conditions. If this principle is valid, the species composition (or rather their properties) found in any ecosystem represent the best "solution" among the possible ones for the ecosystem to move away from thermodynamic equilibrium. The application of structurally biogeochemical models with exergy as goal function could be used to explain the biological structure observed, because it would be the structure giving the highest exergy of the system under the prevailing conditions. Five cases have been examined by this method combining modeling and the maximum exergy principle. In all five cases, the observed biological structure (sizes and biomass concentrations) gave the highest exergy. In principle, this method with a high causality could replace the application of artificial neural network (ANN) or any other predictive approach to find a relationship between dominant species and water quality in an aquatic ecosystem; but the method is unfortunately too time consuming to be applicable on a medium to large data-set covering many sites. Therefore, it is recommended to develop a method to incorporate the maximum exergy principle in the ANN procedure.