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Decision support for sustainable forestry: enhancing the basic rational model.Author(s): H.R. Ekbia; K.M. Reynolds
Source: In: Reynolds, K.M.; Thomson, A.J.; Kohl, M.; Shannon, M.A.; Ray, D.; Rennolls, K., eds. Sustainable forestry: from monitoring and modeling to knowledge management and policy science. Oxfordshire, UK: CAB International: 497-514
Publication Series: Scientific Journal (JRNL)
PDF: View PDF (3.18 MB)
DescriptionDecision-support systems (DSS) have been extensively used in the management of natural resources for nearly two decades. However, practical difficulties with the application of DSS in real-world situations have become increasingly apparent. Complexities of decisionmaking, encountered in the context of ecosystem management, are equally present in sustainable forestry. Various writers have criticized the classical rational/technical solutions commonly employed in DSS and have proposed new approaches based on consensus building, collaborative learning and social DSS, for example. We propose that rational models provide necessary, but not sufficient, tools for effective decision support of sustainable forestry. On this basis, we hypothesize that rational models are not intrinsically limiting, as some have suggested. Rather, perceived limitations of rational models in contemporary DSS might be more a consequence of our methods or of how we have chosen to employ them. Using the Ecosystem Management Decision Support system as an example, we describe how solutions based on rational methods can be integrated with new approaches, such as collaborative learning, to better cope with the practical difficulties of decision support for sustainable forestry. The chapter also discusses ecophenomenology as an outlook that offers a more integrative view of humans and nature and that avoids some of the basic issues facing the rational model.
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CitationEkbia, H.R.; Reynolds, K.M. 2007. Decision support for sustainable forestry: enhancing the basic rational model. In: Reynolds, K.M.; Thomson, A.J.; Kohl, M.; Shannon, M.A.; Ray, D.; Rennolls, K., eds. Sustainable forestry: from monitoring and modeling to knowledge management and policy science. Oxfordshire, UK: CAB International: 497-514
KeywordsSustainable forestry, decision support, multi-agent-based systems, learning models
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