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dc.contributor.authorSmith, Ron I.
dc.contributor.authorBarton, David Nicholas
dc.contributor.authorDick, Jan
dc.contributor.authorHaines-Young, Roy
dc.contributor.authorMadsen, Anders L.
dc.contributor.authorRusch, Graciela
dc.contributor.authorTermansen, Mette
dc.contributor.authorWoods, Helen
dc.contributor.authorCarvalho, Laurence
dc.contributor.authorGiucă, Relu Constantin
dc.contributor.authorLuque, Sandra
dc.contributor.authorOdee, David
dc.contributor.authorRusch, Veronica E.
dc.contributor.authorSaarikoski, Heli
dc.contributor.authorAdamescu, Cristian Mihai
dc.contributor.authorDunford, Robert
dc.contributor.authorOchieng, John
dc.contributor.authorGonzalez-Redino, Julen
dc.contributor.authorStange, Erik
dc.contributor.authorVădineanuh, Angheluță
dc.contributor.authorVerweijq, Peter
dc.contributor.authorVikström, Suvi
dc.date.accessioned2017-12-07T11:51:27Z
dc.date.available2017-12-07T11:51:27Z
dc.date.created2017-12-06T10:10:13Z
dc.date.issued2017
dc.identifier.issn2212-0416
dc.identifier.urihttp://hdl.handle.net/11250/2469543
dc.description.abstractNine Bayesian Belief Networks (BBNs) were developed within the OpenNESS project specifically for modelling ecosystem services for case study applications. The novelty of the method, its ability to explore problems, to address uncertainty, and to facilitate stakeholder interaction in the process were all reasons for choosing BBNs. Most case studies had some local expertise on BBNs to assist them, and all used expert opinion as well as data to help develop the dependences in the BBNs. In terms of the decision scope of the work, all case studies were moving from explorative and informative uses towards decisive, but none were yet being used for decision-making. Three applications incorporated BBNs with GIS where the spatial component of the management was critical, but several concerns about estimating uncertainty with spatial modelling approaches are discussed. The tool proved to be very flexible and, particularly with its web interface, was an asset when working with stakeholders to facilitate exploration of outcomes, knowledge elicitation and social learning. BBNs were rated as very useful and widely applicable by the case studies that used them, but further improvements in software and more training were also deemed necessary.nb_NO
dc.language.isoengnb_NO
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/deed.no*
dc.subjectDecision scopenb_NO
dc.subjectSpatial modellingnb_NO
dc.subjectUncertaintynb_NO
dc.subjectStakeholder participationnb_NO
dc.subjectWeb interfacenb_NO
dc.titleOperationalising ecosystem service assessment in Bayesian Belief Networks: experiences within the OpenNESS projectnb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.subject.nsiVDP::Samfunnsvitenskap: 200::Økonomi: 210nb_NO
dc.source.journalEcosystem Servicesnb_NO
dc.identifier.doi10.1016/j.ecoser.2017.11.004
dc.identifier.cristin1523365
dc.relation.projectEC/FP7/OpenNESS (Grant agreement no. 308428)nb_NO
cristin.unitcode7511,6,0,0
cristin.unitcode7511,2,0,0
cristin.unitcode7511,5,0,0
cristin.unitnameOslo
cristin.unitnameAvdeling for terrestrisk økologi
cristin.unitnameLillehammer
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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Attribution-NonCommercial-NoDerivatives 4.0 Internasjonal
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