Operationalizing an ecosystem services-based approach using Bayesian Belief Networks: an application to riparian buffer strips

A McVittie*, L Norton, J Martin-Ortega, I Siameti, K Glenk, I Aalders

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    37 Citations (Scopus)
    10 Downloads (Pure)

    Abstract

    The interface between terrestrial and aquatic ecosystems contributes to the provision of key ecosystem services including improved water quality and reduced flood risk. We develop an ecological–economic model using a Bayesian Belief Network (BBN) to assess and value the delivery of ecosystem services fromriparian buffer strips. By capturing the interactions underlying ecosystem processes and the delivery of services we aim to further the operationalization of ecosystem services approaches. The model is developed through outlining the underlying ecological processes which deliver ecosystem services. Alternative management options and regional locations are used for sensitivity analysis. We identify optimal management options but reveal relatively small differences between impacts of different management options. We discuss key issues raised as a result of the probabilistic nature of the BBN model. Uncertainty over outcomes has implications for the approach to valuation particularly where preferences might exhibit non-linearities or thresholds. The interaction between probabilistic outcomes and the statistical nature of valuation estimates suggests the need for further exploration of sensitivity in such models. Although the BBN is a promising participatory decision support tool, there remains a need to understand the trade-off between realism, precision and the benefits of developing joint understanding of the decision context. © 2014 Elsevier B.V. All rights reserved.
    Original languageEnglish
    Pages (from-to)15 - 27
    Number of pages13
    JournalEcological Economics
    Volume110
    DOIs
    Publication statusPrint publication - 2015

    Bibliographical note

    1024334
    1023311

    Keywords

    • Bayesian networks
    • Ecosystems services
    • Interdisciplinary research
    • Valuation

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