Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability

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dc.contributor.advisorApril, Kurten_ZA
dc.contributor.advisorPotgieter, Aneten_ZA
dc.contributor.authorPeter, Camarenen_ZA
dc.date.accessioned2016-03-28T14:35:26Z
dc.date.available2016-03-28T14:35:26Z
dc.date.issued2010en_ZA
dc.descriptionIncludes bibliographical references (pages. 379-400).en_ZA
dc.description.abstractThis 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.en_ZA
dc.identifier.apacitationPeter, C. (2010). <i>Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability</i>. (Thesis). University of Cape Town ,Unknown ,GSB: Faculty. Retrieved from http://hdl.handle.net/11427/18284en_ZA
dc.identifier.chicagocitationPeter, Camaren. <i>"Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability."</i> Thesis., University of Cape Town ,Unknown ,GSB: Faculty, 2010. http://hdl.handle.net/11427/18284en_ZA
dc.identifier.citationPeter, 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.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Peter, Camaren AB - 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. DA - 2010 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2010 T1 - Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability TI - Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability UR - http://hdl.handle.net/11427/18284 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/18284
dc.identifier.vancouvercitationPeter C. Bayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainability. [Thesis]. University of Cape Town ,Unknown ,GSB: Faculty, 2010 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/18284en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentGSB: Facultyen_ZA
dc.publisher.facultyUnknownen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherDesicion analysisen_ZA
dc.subject.otherBayesian networksen_ZA
dc.titleBayesian participatory-based decision analysis : an evolutionary, adaptive formalism for integrated analysis of complex challenges to social-ecological system sustainabilityen_ZA
dc.typeDoctoral Thesis
dc.type.qualificationlevelDoctoral
dc.type.qualificationnamePhDen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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