Canadian Forest Service Publications
An information ecology approach to science–policy integration in adaptive management. 2014. Eddy, B.G., Hearn, B.; Luther, J.; van Zyll de Jong, M.; Bowers, W.W.; Parsons, R.; Piercy, D.; Strickland, G.; Wheeler, B. Ecology and Society 19(3): 40.
Available from: Atlantic Forestry Centre
Catalog ID: 35742
CFS Availability: PDF (download)
Available from the Journal's Web site. †
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Adaptive management of social-ecological systems requires integration and collaboration among scientists, policy makers, practitioners, and stakeholders across multiple disciplines and organizations. Challenges associated with such integration have been attributed to gaps between how human systems are organized and how ecosystems function. To address this gap, we explore the application of information ecology as a theoretical basis for integrating human systems and natural systems. First, we provide an overview of information ecology with reference to its relationship with information theory and how we define “information.” Principles governing whole-part relationships, i.e., holons and holarchies, are then used to develop a general information flow model for evolutionary, complex adaptive systems. This general model is then applied to examine a number of issues related to science–policy integration and in the development of a reference framework for practical application in adaptive management. A number of additional considerations for practical use of the framework are also discussed.
Plain Language Summary
The forest sector requires improved integration between science and policy in order to address critical issues in sustainable forest management. This paper addresses the integration between science and policy as an ‘information process’. We first describe what ‘information’ is, and how it functions within organizations that are continually evolving and adapting to changing circumstances. Our analysis reveals that scientific research, and policy and decision making, are "two cultures" that require facilitated integration. In order to address this need, we develop an integration framework that provides a roadmap and some guiding principles for managers, scientists, and policy makers. The framework describes both "horizontal" and "vertical" integration within and across three distinct levels: Primary (Primary Research), Secondary (Decision Support), and Tertiary (Policy and Decision Making). Technical, scientific, organizational, and information processing requirements are distinct within each of these three levels; and need to be managed in such a way that enables information to flow effectively in an adaptive management process. The framework is both scalable and adaptable to a wide range of projects and organizational requirements.
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