STAKEHOLDER CONSULTATION FOR BAYESIAN DECISION SUPPORT SYSTEMS IN ENVIRONMENTAL MANAGEMENT

Environmental management is a field where the number of variables, their interactions and feed-back loops require tools to integrate information, build scenarios and support decision-making. Among the various kinds of Decision Support Systems, Bayesian Belief networks have proven to be quite useful as they can integrate quantitative information as well as qualitative expert knowledge. Beyond knowledge integration, the consultations also help clarifying what is at stake, how variables interact and what are the conflicting interests. Gathering expert knowledge requires consultations, with a particular approach constrained by modelling requirements. In this paper based on our experience we focus on the technical aspects of such stakeholders' consultation. We describe in detail the steps of the consultation, we analyse the methodology (selection of stakeholders, collective building of a model structure, probabilities elicitation, etc). Then we review the possible pitfalls and problems encountered in the process. We ultimately propose generic guidelines for stakeholders consultation in view of building Bayesian models for environmental management.

[1]  Baruch Fischhoff,et al.  What Number is “Fifty‐Fifty”?: Redistributing Excessive 50% Responses in Elicited Probabilities , 2002, Risk analysis : an official publication of the Society for Risk Analysis.

[2]  Thomas C. Beierle,et al.  The Quality of Stakeholder‐Based Decisions , 2002, Risk analysis : an official publication of the Society for Risk Analysis.

[3]  J. Cain Planning improvements in natural resource management. Guidelines for using Bayesian networks to support the planning and management of development programmes in the water sector and beyond , 2001 .

[4]  James T. Peterson,et al.  Quantitative Decision Analysis for Sport Fisheries Management , 2003 .

[5]  Helle Munk Ravnborg,et al.  Understanding interdependencies: stakeholder identification and negotiation for collective natural resource management , 2002 .

[6]  Finn Verner Jensen,et al.  Introduction to Bayesian Networks , 2008, Innovations in Bayesian Networks.

[7]  R. Gregory,et al.  Decision Aiding, Not Dispute Resolution: Creating Insights through Structured Environmental Decisions , 2001 .

[8]  Aaron M. Ellison,et al.  AN INTRODUCTION TO BAYESIAN INFERENCE FOR ECOLOGICAL RESEARCH AND ENVIRONMENTAL , 1996 .

[9]  Bev Littlewood,et al.  Bayesian Belief Network Model for the Safety Assessment of Nuclear Computer-based Systems , 1997 .

[10]  O. Varis,et al.  Causal Bayesian network approach to integrated watershed planning and management , 2000 .

[11]  Judith L. Anderson Embracing Uncertainty: The Interface of Bayesian Statistics and Cognitive Psychology , 1998 .

[12]  Stephen M. Redpath,et al.  Using Decision Modeling with Stakeholders to Reduce Human–Wildlife Conflict: a Raptor–Grouse Case Study , 2004 .

[13]  Rod Staker 2.3.2 Towards a Knowledge Based Soft Systems Engineering Method for Systems of Systems , 2001 .

[14]  Eric Baran,et al.  ECOLOGICAL AND MODELLING APPROACH TO FLOOD-FISH RELATIONSHIPS IN THE MEKONG RIVER BASIN , 2001 .

[15]  Olli Varis,et al.  Water Resources Development in the Lower Senegal River Basin: Conflicting Interests, Environmental Concerns and Policy Options , 2002 .

[16]  A. Castelletti,et al.  Participatory decision making in reservoir planning , 2002 .

[17]  Ian W. Makin,et al.  Bayfish: a model of environmental factors driving fish production in the lower Mekong basin , 2003 .

[18]  Charles Jackson,et al.  Achieving Quality in Social Reporting: The Role of Surveys in Stakeholder Consultation , 2002 .

[19]  Muel Kaptein,et al.  Toward Effective Stakeholder Dialogue , 2003 .

[20]  Carlo Jaeger,et al.  Citizens’ perspectives on climate change and energy use , 2000 .

[21]  James T. Peterson,et al.  Evaluation of potential effects of federal land management alternatives on trends of salmonids and their habitats in the interior Columbia River basin , 2001 .

[22]  Mark E. Borsuk,et al.  Stakeholder Values and Scientific Modeling in the Neuse River Watershed , 2001 .

[23]  I. Makin,et al.  Participatory decision support for agricultural management. A case study from Sri Lanka , 2003 .

[24]  Nicole Rijkens-Klomp,et al.  A look in the mirror: reflection on participation in Integrated Assessment from a methodological perspective , 2002 .

[25]  David C. Wilkins,et al.  Collaborative decision making and intelligent reasoning in judge advisor systems , 1999, Proceedings of the 32nd Annual Hawaii International Conference on Systems Sciences. 1999. HICSS-32. Abstracts and CD-ROM of Full Papers.

[26]  François Bousquet,et al.  Adapting Science to Adaptive Managers: Spidergrams, Belief Models, and Multi-agent Systems Modeling , 2002 .

[27]  Kenneth H. Reckhow,et al.  Bayesian Approaches in Ecological Analysis and Modeling , 2002 .

[28]  Baruch Fischhoff,et al.  A multi-channel stakeholder consultation process for transmission deregulation , 2003 .

[29]  Ioannis Stamelos,et al.  On the use of Bayesian belief networks for the prediction of software productivity , 2003, Inf. Softw. Technol..

[30]  B. Marcot,et al.  Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement , 2001 .