Weather reports, predictions for flooding and landslides, or models to calculate the carbon balance of woodlands are all key scientific instruments that allow analysis and understanding of complex, dynamic human-environmental systems in the long term. These environmental models additionally enable the transfer of academic, scientific knowledge into daily life and support the work of decision-makers. Yet the audience and purpose for which the predictions are intended can have a decisive influence on the forecasts and explanations generated. The new research focus at the Freiburg Institute for Advanced Studies (FRIAS) is dedicated to this issue. A team headed by Prof. Dr. Carsten Dormann, Prof. Dr. Stefan Baumgärtner, and Prof. Dr. Kerstin Stahl of the Faculty of Environment and Natural Resources of the University of Freiburg will cooperate in the next twelve months with international researchers in investigating the range of methodological approaches used for models in the environmental sciences. They will also assess their scientific credibility and pursue the question of how environmental models can serve as a basis of information for the general public.
In order to do this, the team will examine models from disciplines such as ecosystem ecology, economics, forestry, geology, the history and methodology of science, as well as hydrology, information science, industrial ecology, and meteorology. The project is opening with a workshop lasting several days. German and international researchers are to attend. Together they will discuss the aspects that influence the generation of environmental models. Among the factors they are trying to obtain better understanding of are how and if scientists’ own attitudes and world-views consciously or unconsciously influence the generation of models.
With this workshop as a basis and aided by the FRIAS research focus, the team from Freiburg aims to advance interdisciplinary exchanges regarding models in the environmental sciences. The researchers suspect that the broad range of traditions, methods, and techniques can impede the comparison and evaluation of model results and their practical applications beyond academic disciplines, leading to misunderstandings and doubts about the credibility of environmental forecasts. As a result, their aim is to shape “best practice” from experiences of varied disciplines in order to make credible environmental forecasting possible as well as to formulate a research agenda that will resolve existing deficits.