Analysing modeling methods in the ecology from the systemology positions

Abstract

To obtain a forecast, models of behavior of specific systems are created, whose adequacy can be judged only within the framework of accepted hypotheses. The increase in the complexity of the object under study causes an increase in the complexity of the mathematical apparatus. However, today’s modeling device does not solve the main problem of increasing the low (or unsatisfactory) predictive ability of models of rather complicated systems. Ecosystems are the objects of complex nature, and the methodological basis for their study is the theory of complex systems. Therefore, when solving this issue, it is necessary to turn to the analysis of the basic principles of systemology. Goal: analysis of the main provisions of systemology for the application of modeling in ecosystem research. The methodological basis for the study of the ecosystem is the theory of complex systems. As a result of the work the analysis of the basic positions of systemology concerning the approaches in the study of simple and complex systems was carried out. The basic principles of systemology and the most important functions of explanation and prediction of the observed phenomena in the studied class of systems are considered, as well as the connection between the complications of the behavior of simulated objects and the methods of their modeling. It is determined that in the study of complex systems, the principle of multiplicity of models is used. In this case, none of the methods of modeling has all sets of model functions at the same time. The principle of feasibility of models is manifested in the block method of constructing simulation models. This to overcome allows to some extent the pro-oath of dimension in models of potential efficiency, where impossible situations can be rejected for real systems. The principle of incompatibility manifests itself in the fact that none of the methods of modeling realizes simultaneously the explanatory and predictive functions of the theory. Finally, the principle of counter-intuitive behavior of complex systems is taken into account when constructing self-organizing models. It is noted that mathematical modeling of complex systems should be considered as an extension of traditional natural science experiment. With regard to the analysis of environmental systems, as well as the analysis of any other complex system, the experiment should replace the power of abstraction and computer simulation.