Browsing by Person "Kaupenjohann, Martin"

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Ecosystemic Effect Indicators to assess Effects of agricultural Landuse on Ecosystems
(2000) Merkle, Andrea Hildegard; Kaupenjohann, Martin
Agricultural production and its material and non-material emissions may cause side-effects in ecosystems. These effects have to be assessed and evaluated. The aim of the present study is to provide a tool that relates emissions of agricultural production and affected ecosystems. This tool represents an indicator approach. The needed indicators are defined as ecosystemic effect indicators (EEI). Within the study a multistage procedure is developed which should be pursued in identifying indicators. To assess which emissions must be regarded in detail an estimation of relevance by means of an emission and input classification preceeds the indicator development. Subsequently, EEI are developed for the relevant emissions and inputs. The derivation of EEI is carried out by the following steps: 1) One starts top-down at the target 'maintaining the ecosystem functioning' in this work depicted by the utility functions. A list with characteristics that are dependent on hierarchical levels is compiled for each relevant function. 2) Starting at one specific input a list of potential receptors is compiled bottom-up. These represent potential effect indicators. 3) By overlapping the lists of the steps 1 and 2 one yields EEI specific for the utility function and the input under consideration. The step 3 is performed by means of expert knowledge. The advantage of the indicator approach is its operativeness which is site-independent. The results of the study show that EEI may be deemed to be promising tools to picture human influences in particular of agricultural production on ecosystems. The results of the case study provide the basis to assess effects on ecosystems for some major stressors. In cases where critical values are available site specific quantitative statements concerning ecological effects within the frame of sustainable agriculture are enabled by the present method for the derivation of indicators. Subsequently, necessary measures can be deduced
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, Martin
Models 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.