format (1.1M) Kay, J.J., 2000, "Complex systems theory applied to ecosystem management" Keynote address at Modelling complex systems conference, Montreal, 1 August, 2000.
A new understanding of ecosystems, as complex systems, is emerging. Their hierarchical nature requires that they be studied from different types of perspectives and at different scales of examination. Thus a diversity of perspectives is required for understanding. Ecosystems are self-organizing. Their dynamics are largely a function of feedback loops. This precludes linear causal mechanical explanations of ecosystem dynamics. Emergence and surprise are normal phenomena in systems dominated by feedback loops. Inherent uncertainty and limited predictability are inescapable consequences of these system phenomena. Such systems organize about attractors. Even when the environmental situation changes, the system's feedback loops tend to maintain its current state. However, when ecosystem change does occur, it tends to be very rapid and even catastrophic. When precisely the change will occur, and what state the system will change to, are often not predictable. Often there are several possible ecological states (attractors), that are equivalent. Which the ecosystem currently occupies is a function of its history. There is not a "correct" preferred state for the ecosystem. This new understanding of ecosystems as complex systems mandates a different role for science in the business of ecosystem governance for sustainability.
Ecological systems are self-organizing dissipative systems whose manifestation reflects the state of the physical environment and the exergy, materials, and information available to them. Using this observation, and ideas from complex systems thinking, we have developed a conceptual model which explicitly describes the linkages between ecological and economic systems at different scales. The model identifies the important ecological process and structures, how they set the stage for the important socio-economic processes and structures, and how these in turn influence the ecological processes and structures. It closes the ecological-economic loop.
This model is a centerpeice for an approach to dealing with ecosystems in the mode of post normal science and complex systems theory. In this approach the role of the scientists changes to that of narrator. Their task is to scope out the attractors available to the ecosystem, the potential flips between them, and the underlying morphogenetic causal structure of the organization. This is reported as a narrative of possible futures for the system. This informs decision makers about the ecological options, the tradeoffs and uncertainties involved, and various strategies for influencing what happens on a landscape. The role of scientist changes from problem solver, in the sense of providing a solution, to the role of facilitating understanding about the bio-physical realities and in so doing contributing to the resolution of the situation.
In this context modelling becomes less about prediction and more about exploring how the situation might unfold. It informs people about potential tradeoffs that will need to be made. It gives people a sense of the internal rules of the system, that is its canon.
A tutorial version of the talk.
Download the powerpoint presentation in Acrobat format (1.1M)
Due to limitations of the software some of the figures in the PDF file are of less than wonderful quality. Better quality versions of the images:
The ecosystem approach figures.
The Huron Natural Area holarchy
Kay. J. 2000. "Ecosystems as Self-organizing Holarchic Open Systems : Narratives and the Second Law of Thermodynamics" in Sven Erik Jorgensen, Felix Muller (eds), Handbook of Ecosystems Theories and Management, CRC Press - Lewis Publishers. pp 135-160
Boyle, M., Kay. J., and Pond, B., 2001. Monitoring in Support of Policy: an Adaptive Ecosystem Approach, in Munn, T., (editor in chief), Vol.4 Encylopedia of Global Environmental Change, London, John Wiley and Son. pp.116-137.
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