MIP2AM Decision Analytic Approaches for Integrated Risk Management
Monday, 14 November 2005: 8:00 AM - 11:40 AM in 347-348

(BER-1118-078859) An Integrated Assessment Approach to Development of If-Then Hypotheses for Managing Complex Social-Ecological Systems.

Beratan, K¹, ¹ Nicholas School, Duke University, Durham, NC, USA

ABSTRACT- An understanding of dynamic interactions among policy, human behavior, and biophysical processes is necessary to craft effective mitigation and risk management strategies that lead to desired outcomes with a minimum of unanticipated negative consequences. A fundamental difficulty in managing social-ecological systems (SES) is that their great complexity makes it difficult to forecast the future in any meaningful way. Current negative changes in biophysical systems are largely driven by the cumulative impact of individual human decisions and behaviors. Decision makers generally have to deal with information overload, dynamic conditions, and multiple processes interacting across scales. Slow changes in background (contextual) conditions/processes cause changes in the system elements of interest that are difficult to anticipate, and human responses to changing conditions are extremely difficult to predict. Standard decision analysis methods can provide some insight into the choices people make, but cannot provide sufficient knowledge to permit assessment of the likely outcomes of real-world policy decisions. An integrative assessment approach utilizing diffusion of innovations concepts and participative inquiry methods shows promise as a means of developing policy-relevant knowledge of the causal relations and feedback loops in specific SESs. This approach involves development of a conceptual system model around a particular issue, in the form of a network, with nodes consisting of key entities (biophysical and socio-economic) linked by connections representing causal chains and information transfer (feedback) channels. Construction of such a model requires elicitation and integration of experiential knowledge distributed among people who live in and work directly with relevant parts of the system, as well as explicit knowledge derived from technical experts and focused disciplinary research. The communicative and decision components of the model are informed by diffusion studies which provide a framework for assessing the factors that can help or hinder behavior change needed to produce desired environmental or health outcomes.

Key words: complex social-ecological systems, diffusion of innovations, collaborative inquiry, applied research