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A Bayesian approach to ecosystem service trade-off analysis utilizing expert knowledge

Author

Listed:
  • Solveig Höfer

    (Deltares)

  • Alex Ziemba

    (Deltares
    Delft University of Technology)

  • Ghada El Serafy

    (Deltares
    Delft University of Technology)

Abstract

The concept of ecosystem services is gaining attention in the context of sustainable resource management. However, it is inherently difficult to account for tangible and intangible services in a combined model. The aim of this study is to extend the definition of ecosystem service trade-offs by using Bayesian Networks to capture the relationship between tangible and intangible ecosystem services. Tested is the potential of creating such a network based on existing literature and enhancement via expert elicitation. This study discusses the significance of expert elicitation to enhance the value of a Bayesian Network in data-restricted case studies, underlines the importance of inclusion of experts’ certainty, and demonstrates how multiple sources of knowledge can be combined into one model accounting for both tangible and intangible ecosystem services. Bayesian Networks appear to be a promising tool in this context, nevertheless, this approach is still in need of further refinement in structure and applicable guidelines for expert involvement and elicitation for a more unified methodology.

Suggested Citation

  • Solveig Höfer & Alex Ziemba & Ghada El Serafy, 2020. "A Bayesian approach to ecosystem service trade-off analysis utilizing expert knowledge," Environment Systems and Decisions, Springer, vol. 40(1), pages 67-83, March.
    • Handle: RePEc:spr:envsyd:v:40:y:2020:i:1:d:10.1007_s10669-019-09742-2
    DOI: 10.1007/s10669-019-09742-2
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    References listed on IDEAS

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    1. Hamilton, Serena H. & Pollino, Carmel A. & Jakeman, Anthony J., 2015. "Habitat suitability modelling of rare species using Bayesian networks: Model evaluation under limited data," Ecological Modelling, Elsevier, vol. 299(C), pages 64-78.
    2. Fisher, Brendan & Turner, R. Kerry & Morling, Paul, 2009. "Defining and classifying ecosystem services for decision making," Ecological Economics, Elsevier, vol. 68(3), pages 643-653, January.
    3. Uusitalo, Laura, 2007. "Advantages and challenges of Bayesian networks in environmental modelling," Ecological Modelling, Elsevier, vol. 203(3), pages 312-318.
    4. Andrew Speirs‐Bridge & Fiona Fidler & Marissa McBride & Louisa Flander & Geoff Cumming & Mark Burgman, 2010. "Reducing Overconfidence in the Interval Judgments of Experts," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 512-523, March.
    5. Marcot, Bruce G., 2017. "Common quandaries and their practical solutions in Bayesian network modeling," Ecological Modelling, Elsevier, vol. 358(C), pages 1-9.
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    Cited by:

    1. Zachary A. Collier & James H. Lambert & Igor Linkov, 2020. "Interdisciplinary mathematical methods for societal decision-making and resilience," Environment Systems and Decisions, Springer, vol. 40(1), pages 1-2, March.
    2. Milad Zamanifar & Timo Hartmann, 2021. "A prescriptive framework for recommending decision attributes of infrastructure disaster recovery problems," Environment Systems and Decisions, Springer, vol. 41(4), pages 633-650, December.

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