A novel transdisciplinary description of the mega-process called Global Change" in terms of functional patterns Syndromes" is presented. This approach to environmental analysis is inspired by medical sciences, where syndromes are perceived as typical combinations of pertinent co-factors. Sixteen main syndromes are identi ed as the subdynamics generating the worldwide environment and development process with all its negative aspects and impacts. The analysis relies on a speci c semi-qualitative methodology, which brings together elements from complex systems theory, fuzzy logic and expert-judgment e v aluations. The concept is illustrated by in-depth treatment and comparison of the syndromes Sahel" and Green Revolution". As a corollary of the syndrome approach, a simple operational de nition of Sustainable Development" is suggested.

Ecological and environmental sciences need new approaches to meet a two-fold challenge: first, analysing the tightly coupled system of human civilisation and its natural environment and, secondly, generating action-oriented knowledge in order to deal with global change. The syndrome approach meets this challenge by formulating a set of typical problematic man-environment interaction patterns. After shortly reviewing the basic concepts of the approach, this paper presents the global distribution of seven syndromes that were present around 1990 based on 56 indicators. Besides large regions dominated by just one problematic pattern, typical "pairs" of syndromes occur, indicating mutual reinforcement mechanisms. A discussion follows covering the implication of these multiple-syndrome situations and the need for actions to mitigate global change and its negative effects.

A qualitative functional analysis of the archetypical cause-effect pattern constituting social and environmental degradation in uncontrolled and rapidly growing cities (Favela Syndrome) is performed. This analysis is carried out in the framework of the Syndrome Concept which aims to describe the total complex of present Global Change by a limited number of archetypical cause-effect patterns, called Syndromes. Based on the qualitative analysis, which is formalized in a Favela Syndrome specific network of symptoms (qualitative state variables) and their interrelations (qualitative interactions like “enforces” or “weakens”), an indicator is developed which allows the detection of the hypothesized qualitative cause-effect pattern in a geographically explicit form. This spatial intensity measurement is performed on the basis of global data sets using Fuzzy-Logic methods. In the case of incomplete data probabilistic methods are applied in order to obtain the maximum information from the underlying data. Using this evaluation scheme it is possible to calculate truth values for the occurrence of the Favela Syndrome for 78 countries with no or relatively low uncertainty and for further 35 countries with low to medium uncertainty. Some other countries show a high uncertainty with respect to the indicator results. Therefore, even under an inherent uncertainty regarding the available knowledge and data, a generalized and systematic diagnosis of the “hot spots” of urbanism on the global scale is possible. Furthermore, the underlying model allows to introduce a sensitive factor, which enables decision makers to develop management strategies with respect to this pattern of an unadapted urban growth.