Table of Contents

Handbook of Research methods and Applications in Environmental Studies

Handbook of Research methods and Applications in Environmental Studies

Handbooks of Research Methods and Applications series

Edited by Matthias Ruth

This volume presents methods to advance the understanding of interdependencies between the well-being of human societies and the performance of their biophysical environment. It showcases applications to material and energy use; urbanization and technological transition; economic growth and social vulnerabilities; development and governance of social and industrial networks; the role of history, culture, and science itself in carrying out analysis and guiding policy; as well as the role of theory, data, and models in guiding decisions.

Chapter 7: Fuzzy cognitive mapping: applications to urban environmental decision-making

Marta Olazabal and Diana Reckien

Subjects: environment, research methods in the environment, geography, research methods in geography, research methods, research methods in the environment


Managing environmental and socio-ecological systems often means dealing with multiple challenges including the following: (1) the high degree of complexity of socio-ecological systems, which are often not well understood; (2) the large number of stakeholders involved, generally with competing interests; and (3) the large number of potential management options (Maier et al. 2008). In our view, two more challenges could also be added: (4) uncertainty, for example, about future climate or about the future environmental, social and political conditions; and (5) the related lack of appropriate data for assessing current or future states of the system, for example, when social system variables are not defined, indicators are scarce and assessment or calculation methods are absent. Complexity is an inherent characteristic of socio-ecological systems in which nature and people maintain a certain level of self-organization (Holling 2001) and adaptation to current and potentially future stressors. The main characteristics of complex adaptive systems include (1) diversity and individuality of components; (2) localized interactions between components; and (3) autonomous processes of adaptation that use the outcomes of those local interactions to strengthen the system (Levin 1999). These system features are also often found at the core of current and emerging management challenges. Studying complex systems and factoring complexity into various research disciplines and real-world applications is therefore increasingly regarded as critical for understanding and dealing with socio-ecological challenges (Rogers et al. 2013).

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