Modelling is an essential tool in the scientists' kit that allows them to indulge in their favourite pastime, ie, trying to understand reality. I am convinced that not many scientists would claim that an absolutely accurate simulation of even little bits of reality is an easy task. Yet, modelling enables the scientist to interact iteratively with reality, continuously testing the assumptions used to build models against the extent to which model predictions match reality.
Environment, however, is a complex subject. It can be studied from a variety of disciplinary perspectives ranging from the physical to the sociological. Single-disciplinary experts attempting to describe reality at the human-environment interface is like the four blind men trying to imagine the shape of the elephant by touching different parts of the animal’s body. When decisions for positive human-environment relations must be based upon integrated multidisciplinary data and knowledge, modelling becomes an indispensable skill and tool.
Interdisciplinary collaboration among scientists is a hallmark of all UNESCO's environmental sciences initiatives, which all use modelling frequently to address scientific as well as policy questions at the human-environment interface. The Man and the Biosphere (MAB) Programme in particular has promoted interdisciplinary collaboration for understanding environmental issues and problems for over 30 years. Teams at UNESCO's International Centre for Theoretical Physics (ICTP) build models to visualize global climate change scenarios; this Centre has served as an incubator for ecological and environmental economists who have used modelling approaches to understanding natural resource use and management conflicts worldwide. ICTP organizes training workshops that promote the use of quantitative methods, including specialized disciplines like mathematical ecology, that are essential to mastering environmental modelling techniques.
Using model predictions in a guarded and precise manner is part of the scientific integrity of modellers. Where environmental issues have entered the political mainstream it is not always easy to separate advocacy prescriptions from rigorous scientific interpretation of model predictions. In recent years climate change predictions have been largely based on scientific models, but such predictions are used not only by modellers or scientists. A wide range of advocacy groups have interpreted model predictions and may have contributed to widespread disagreement about those decisions and actions that nations, businesses and civil society must pursue to reverse or stabilize current climate trends.
As modelling becomes a tool increasingly used to provide scientific insights into solving environmental puzzles, concern about the level of awareness of policy and decision makers, the general public and politicians is growing. To what extent are those who will set policy and influence decisions for the implementation of important environmental agreements aware of the strengths and weaknesses of modelling? How many of them have the background and curiosity to check the assumptions of models against the validity of interpretations given to model predictions?
I hope that groups like ERCIM will not only advocate for greater application of modelling approaches to studying and understanding environmental issues; I would also like to invite them to consider working with organizations like UNESCO, particularly during the newly launched UN Decade of Education for Sustainable Development, to build skills and competencies among decision makers and the public, for a better appreciation and awareness of modelling methodologies and approaches, their constraints and strengths, and the intricacies of interpreting model outcomes into policy prescriptions.
Environmental Modelling