Please use this identifier to cite or link to this item: http://buratest.brunel.ac.uk/handle/2438/12313
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dc.contributor.authorFranco, C-
dc.contributor.authorHepburn, LA-
dc.contributor.authorSmith, DJ-
dc.contributor.authorNimrod, S-
dc.contributor.authorTucker, A-
dc.date.accessioned2016-03-10T12:32:49Z-
dc.date.available2016-03-10T12:32:49Z-
dc.date.issued2016-
dc.identifier.citationEnvironmental Modelling and Software, 80: pp. 132-142, (2016)en_US
dc.identifier.issn1364-8152-
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S1364815216300494-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/12313-
dc.description.abstractIt is crucial to identify sources of impacts and degradation to maintain functions and services that the physical structure of coral reef provides. Here, a Bayesian Network approach is used to evaluate effects that anthropogenic and climate change disturbances have on coral reef structure. The network was constructed on knowledge derived from the literature and elicited from experts, and parameterised on independent data. Evaluation of the model was conducted through sensitivity analyses and data integration was fundamental to obtain a balanced dataset. Scenario analyses, conducted to assess the effects of stressors on the reef framework state, suggested that calcifying organisms and carbonate production, rather than bioerosion, had the largest influence on the reef carbonate budgetary state. Despite the overall budget remaining positive, anthropogenic pressures, particularly deterioration of water quality, affected reef carbonate production, representing a warning signal for potential changes in the reef state.en_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectCoral reefen_US
dc.subjectCalcium carbonate budgeten_US
dc.subjectBayesian networken_US
dc.subjectAnthropogenic disturbancesen_US
dc.subjectClimate changeen_US
dc.subjectEnvironmental managementen_US
dc.titleA Bayesian Belief Network to assess rate of changes in coral reef ecosystemsen_US
dc.typeArticleen_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.envsoft.2016.02.029-
dc.relation.isPartOfEnvironmental Modelling and Software-
pubs.publication-statusAccepted-
pubs.publication-statusAccepted-
Appears in Collections:Dept of Computer Science Research Papers

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