An ecosystem approach for sustainability: addressing the challenge of complexity
Introduction
Much discussion about ecosystem management, or taking an ecosystem approach, emphasizes the need to work across all manner of human boundaries at different geographic scales. However, the growing understanding of the dynamics of ecosystems entails much more 1, 2, 3. In this paper we suggest an approach to understanding these systems in the context of post-normal science grounded in complex systems thinking. At its heart is the portrayal of ecological and human systems as Self-Organizing Holarchic Open (SOHO) systems whose dynamics are predominated by both positive and negative feedback processes operating over a range of spatial and temporal scales. These systems exhibit loose hierarchical structures, various emergent phenomena, and relatively sudden reconfigurations from one state of system organization to another. Some changes in these systems are inherently unpredictable.
The understanding of SOHO systems requires a major change in some of the ways in which science and decision making are conducted. Traditional reductionistic disciplinary science and expert predictions, the basis for much of the advice given to decision makers, have limited applicability. Narratives about possible futures for given SOHO systems are better able to capture the richness of possibilities. Other epistemological mindsets or causal metatypes [4]must be brought to bear, notably explanations based on morphogenetic causal loops that involve both positive and negative feedback processes and autocatalysis. Expectations that decision makers can carefully control or manage changes in societal or ecological systems have also to be challenged. Adaptive learning and adjustment, guided by a much wider range of human experience and understanding than disciplinary science, are also necessary.
This paper sketches a theoretical approach for understanding the dynamics of SOHO systems. It also situates this approach within an extensive heuristic framework for relating human choices and preferences concerning the attributes of SOHO systems to the implications for achieving them through adaptive management, monitoring and governance. The main focus of this paper is on the features of SOHO systems that require different modes of human responses, and also constitute the initial steps for using the heuristic framework.
Section snippets
Self-Organizing Holarchic Open (SOHO) systems
Complex systems thinking follows in the tradition of von Bertalanffy's general systems theory, and draws upon other concepts from the new science emerging over the past three decades, for example, catastrophe theory, chaos and complexity theory, non-equilibrium thermodynamics and self-organization, and Jaynesian information theory. The phenomenon of special interest is self-organization (for more information see Refs 3, 5, 6, 7, 8, 9, 10, 11).
Science and decision making in the context of complexity
Some facets of complexity have been highlighted in this discussion. The first is that self-organization inherently involves internal causality. A self-organizing system has the ability to maintain itself at an attractor despite changes in its environment. It is possible for a system's environment to change substantially, without the system exhibiting major change. Self-organizing systems can respond in a synergistic way to multiple environmental factors such that changes in the system cannot be
Preparing the narratives
In the post-normal paradigm, a scientist's role in decision making shifts from inferring what will happen, that is, making predictions which are the basis of decisions, to providing decision makers and the community with an appreciation, through narrative descriptions, of how the future might unfold. As noted earlier, these narratives consist of several scenarios of how the SOHO systems in question might evolve. These narratives focus on a qualitative/quantitative understanding which describes:
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Decision making in the post-normal mode
Funtowicz and Ravetz [40]distinguish problem-solving strategies for different circumstances defined by the inherent uncertainties in the situation and the severity of consequences arising from the decision to be made. Normal science, either as applied science or mission-oriented research, succeeds where the relative uncertainties are low (and most of it can be handled by standardized procedures), and the stakes or outcomes associated with decisions to be made are modest. In contrast, SOHO
Acknowledgements
Many, many conversations with David Waltner-Toews and Tamsyn Murray helped refine these ideas. Other members of the informal `Dirk Gently gang' have also contributed a great deal (Silvio Funtowicz, Jerry Ravetz, Mario Giampietro, Martin O'Connor and Gilberto Gallopin). Our students, Nina-Marie Lister, Kate Oxley, Richard Martell and Beth Dempster (University of Waterloo), and Charlotte Sunde (Massey University, New Zealand) and other members of our post-normal science discussion group at
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