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A Bayesian Modelling Framework for Integration of Ecosystem Services into Freshwater Resources Management.

Michael Bruen1, Thibault Hallouin2, Michael Christie3

  • 1University College Dublin, CWRR, Belfield, Dublin 4, Ireland. michael.bruen@ucd.ie.

Environmental Management
|February 16, 2022
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Summary

This study presents a Bayesian belief network (BBN) method to integrate ecosystem services (ES) into water management. Riparian management and reduced livestock numbers improved ES delivery, informing practical catchment management decisions.

Keywords:
AnglingBayesian belief networkEcosystem servicesExpert knowledgeFreshwaterMulti-stressorsSensitivity analysis

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Area of Science:

  • Environmental Science
  • Water Resource Management
  • Ecological Modeling

Background:

  • Models integrating multiple stressors and ecosystem services (ES) are limited.
  • Water resource management requires tools to assess the impact of interventions on ES delivery.

Purpose of the Study:

  • To develop a methodology for constructing a Bayesian Belief Network (BBN) integrating catchment and water quality models with expert knowledge.
  • To support the integration of ES into water resource management and assess the impact of different management options.

Main Methods:

  • Developed a BBN combining model outputs, data, and expert knowledge elicited through small group workshops.
  • Assessed four selected ES under management scenarios: no-change, riparian management, and altered livestock numbers.
  • Analyzed expert agreement and disagreement, and performed sensitivity analysis on expert information.

Main Results:

  • Riparian management and decreased livestock numbers improved the investigated ES to varying degrees compared to a no-change scenario.
  • Sensitivity analysis indicated expert disagreements primarily occurred in low-probability situations, minimally impacting overall results.
  • High expert agreement was observed for more probable, likely situations, enhancing model applicability.

Conclusions:

  • The developed BBN methodology effectively supports ES integration into water resource management.
  • Despite complexity and multiple stressors, the model aids decision-making by focusing on the nature of solutions (e.g., riparian or livestock management).
  • Expert knowledge, particularly when in agreement for likely scenarios, is crucial for practical catchment management support.