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Uncertainty analysis in integrated environmental models for ecosystem service assessments: Frameworks, challenges and gaps

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  • Baustert, Paul
  • Othoniel, Benoit
  • Rugani, Benedetto
  • Leopold, Ulrich

Abstract

Integrated Environmental Models (IEMs) incorporating ecosystem services (ES) can be useful tools to support the decision-making. However, their successful application strongly depends upon the confidence decision-makers can place in their outputs. Uncertainty analysis (UA), including uncertainty location, identification, characterization, treatment and communication to decision-makers, can increase their confidence in the used model. To support the use of UA in practice we first focus on the purpose, concepts and methods underpinning UA in environmental modelling. As a main contribution, we then review existing UA frameworks and their coverage, before reviewing the current practice of performing UA for a set of 25 IEM tools. Based on our review we derive and discuss four perceived challenges and gaps whose significance may vary in different contexts: (1) the lack of consensus on terminologies for uncertainty locations; (2) characterization of uncertainty locations beyond variables; (3) treatment of heterogeneous uncertainty; and (4) the lack of a practical framework toward uncertainty communication. We suggest some steps forward for each of these challenges aiming at facilitating the application of UA to IEMs.

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  • Baustert, Paul & Othoniel, Benoit & Rugani, Benedetto & Leopold, Ulrich, 2018. "Uncertainty analysis in integrated environmental models for ecosystem service assessments: Frameworks, challenges and gaps," Ecosystem Services, Elsevier, vol. 33(PB), pages 110-123.
  • Handle: RePEc:eee:ecoser:v:33:y:2018:i:pb:p:110-123
    DOI: 10.1016/j.ecoser.2018.08.007
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    6. Bryant, Benjamin P. & Borsuk, Mark E. & Hamel, Perrine & Oleson, Kirsten L.L. & Schulp, C.J.E. & Willcock, Simon, 2018. "Transparent and feasible uncertainty assessment adds value to applied ecosystem services modeling," Ecosystem Services, Elsevier, vol. 33(PB), pages 103-109.

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