The growth discourse,growth policy and sustainable development: two thought experiments

This paper addresses three aspects of ‘growth’: the discourse, the policy, and the impacts. The growth discourse claims that the central factor for social, economic, political and environmental progress is economic growth – it is assumed to create wealth, and provide the necessary means for social and environmental purposes. On the basis of the growth discourse, different growth policies can be derived, based on different economic and political ideologies.In order to reveal the implications of de facto degrowth, two thought experiments are conducted, for physical and economic end-to-growth strategies. The latter is capable of meeting environmental objectives, but implies significant social tensions and hardships and calls for transition strategies consisting of carefully designed steps.     

Quantitative Bestimmung des lokalen Flusses mit elektrochemisch erzeugtem Wasserstoff

The Science of Nature -     

Parameterizing,evaluating and comparing metapopulation models with data from individual-based simulations

Due to the lack of sufficient data and appropriate ecological information parameterizing predictive population dynamical models usually is a difficult task. The approach proposed in this study is meant to overcome this problem by using detailed individual-based simulations to generate artificial data. With short-term data samples, the models to be investigated can be parameterized and their predictions be compared. The flexibility of individual-based simulations as experimental tools also facilitates the evaluation and comparison of different (aggregated) model types. The presented approach is a step towards unifying models of different complexity. As an example we applied it to two metapopulation models of insect species in a highly fragmented landscape: the well-known incidence function model with a patch-based representation of space and a grid-based analogue. The models are tested with respect to their data requirement and recommendations for a better data sampling are derived.