Handbook of Research methods and Applications in Environmental Studies
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Handbook of Research methods and Applications in Environmental Studies

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.
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Chapter 14: System dynamics for environmental applications

Krystyna Stave


When we try to pick out anything by itself we find that it is bound fast by a thousand invisible cords that cannot be broken, to everything in the universe. (John Muir 1869) The whole-system concept that ‘everything is connected to everything else’ pervades environmental thought. Environmental scientists, managers, and educators understand that all environmental activity takes place in a marvelous, intricate, and irreducible network of ‘invisible cords’, and that this complex web of connections means changes in one part of an ecosystem can have unanticipated consequences distant in space and time from the initial change. At the same time, it is clear that some connections are more relevant than others for explaining particular observed phenomena. We focus on food chains and webs to understand energy transfer among organisms, biogeochemical cycles to trace the movement of material, and succession processes to understand ecosystem responses to disturbance, for example. Understanding or influencing environmental change requires sifting through the complex web of connections to find the essential subset that drives particular behaviors of interest. System dynamics provides an analytic framework and a set of methods for identifying the subset of connections in the larger system that explain particular problems of interest. The framework and methods help structure problems, organize information, visually and mathematically represent relationships among system variables, and simulate the interactions of system variables over time.

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