Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability
Doctoral Thesis
2010
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University of Cape Town
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Abstract
This dissertation responds to the need for integration between researchers and decision-makers who are dealing with complex social-ecological system sustainability and decision-making challenges. To this end, we propose a new approach, called Bayesian Participatory-based Decision Analysis (BPDA), which makes use of graphical causal maps and Bayesian networks to facilitate integration at the appropriate scales and levels of descriptions. The BPDA approach is not a predictive approach, but rather, caters for a wide range of future scenarios in anticipation of the need to adapt to unforeseeable changes as they occur. We argue that the graphical causal models and Bayesian networks constitute an evolutionary, adaptive formalism for integrating research and decision-making for sustainable development. The approach was implemented in a number of different interdisciplinary case studies that were concerned with social-ecological system scale challenges and problems, culminating in a study where the approach was implemented with decision-makers in Government. This dissertation introduces the BPDA approach, and shows how the approach helps identify critical cross-scale and cross-sector linkages and sensitivities, and addresses critical requirements for understanding system resilience and adaptive capacity.
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Includes bibliographical references (pages. 379-400).
Reference:
Peter, C. 2010. Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability. University of Cape Town.