Abstract

To support sustainable environmental management, uncertain knowledge about complex human-environment-systems from both inside and outside of academia needs to be integrated. Bayesian Network (BN) modeling is a promising method to achieve this, in particular if done in a participatory manner. Based on a review of 30 cases of participatory BN modeling of environmental problem fields, and of three guidelines, we summarize recommendations for BN modeling with stakeholder involvement. In addition, strengths and limitations of BNs are synthesized. We found that BNs were successfully applied for knowledge integration and identification of sustainable management strategies within participatory processes. Due to many favorable characteristics, BNs have the potential to become a core method of transdisciplinary knowledge integration in environmental management.

Highlights

  • Sustainability-oriented environmental management and planning deals with problem fields that are characterized by (1) a significant degree of uncertainty or even ignorance and (2) different and legitimate perspectives on what is pertinent and what is best

  • The 30 reviewed case studies have shown that Bayesian Network (BN) modeling can be successfully applied within a participative process

  • Many features make BNs suitable for supporting the identification of sustainable management strategies in problem fields related to complex human-environment systems

Read more

Summary

Introduction

Sustainability-oriented environmental management and planning deals with problem fields that are characterized by (1) a significant degree of uncertainty or even ignorance and (2) different and legitimate perspectives on what is pertinent and what is best This prevents identification of “optimal” management strategies based on purely scientific evidence (Giampietro, 2002). For integrated water resources management that aims at optimizing ecosystem services, for example, there may be a need to estimate the impact of a certain water management measure on both farmer income and the health of riparian vegetation All these problem fields are embedded in complex human-environment systems. Uusitalo (2007) reviewed the advantages as well as the challenges of using BNs in environmental modeling and summarized the state of the art of applying BNs. Fernández, Rumí and Salmerón (2011) found that less than 5% of all identified applications of BNs were in the field of environmental sciences.

Bayesian Networks
Elements of Bayesian Networks
Top-down and Bottom-Up Modeling
BN Software
Recent Applications on Participatory BN Modeling in Environmental Management
Application of Participatory BN Modeling in Environmental Management
Number and Type of Stakeholders Involved
Stages of BN Modeling Process that Stakeholders were Involved in
Information Basis for the Generation of CPTs
Time and Effort Required
BNs Used as DSS
Recommendations for the Application of BNs in Participatory Processes
Stage 3 - Designing a Pilot Causal Network
Stage 6 - Construct CPTs
Evaluating the Success of Participatory BN Modeling
General Recommendations for Participatory BN-Modeling
Strengths and Limitations of Bayesian Networks as Participatory Modeling Tool
Strengths
Limitations
Findings
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.