Browsing by Subject "Experimental systems"
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Publication Models for the representation of ecological systems? The validity of experimental model systems and of dynamical simulation models as to the interaction with ecological systems(2001) Haag, Daniel; Kaupenjohann, MartinModels guide the investigation of ecological phenomena and the managemant of man-environment interactions. Based on six papers, this thesis critically examines characteristic features, limitations and the scientific and societal role of experimental model systems (as well-tried instruments of knowledge production) and of dynamical simulation models (as representatives of relatively recent computer models). Experimental model systems are described as materially and conceptually closed systems with a limited number of parameters. They consist of a material component which is encoded into a formal (numerical) system through the measurement of defined parameters. The transfer of statements derived from model systems to natural systems is critically discussed. Dynamical systems - the paradigm for the representation of ecosystems - permit the simultaneous handling of a large number of parameters. Dynamical systems are conceptually closed systems and are based on the notion of an abstract state (focussing on 'being'). I contrast this view with an image of ecosystems as conceptually open systems ('becoming') which emphasizes the evolutionary openness of ecological systems, the internal production of novelty, and the emergence of system level properties. Taking the nitrogen cycle and its human alterations as an example, model concepts and limitations to the derivation of cause-effect-relationships in ecological systems are illustrated. Acknowledging the limited predictive capacity of simulation models and the intrinsic perspectivity of the identification of 'relevant' phenomena and parameters and drawing on new forms of knowledge production (as described by science studies), a modified role for model building and for simulation models - particularly with respect to science for policy - is sketched.