title: Bayesian inference-based environmental decision support systems for oil spill response strategy selection.
abstract: Contingency plans are essential in guiding the response to marine oil spills. However, they are written before the pollution event occurs so must contain some degree of assumption and prediction and hence may be unsuitable for a real incident when it occurs. The use of Bayesian networks in ecology, environmental management, oil spill contingency planning and post-incident analysis is reviewed and analysed to establish their suitability for use as real-time environmental decision support systems during an oil spill response. It is demonstrated that Bayesian networks are appropriate for facilitating the re-assessment and re-validation of contingency plans following pollutant release, thus helping ensure that the optimum response strategy is adopted. This can minimise the possibility of sub-optimal response strategies causing additional environmental and socioeconomic damage beyond the original pollution event.
authors.affiliation: 40 Raemoir Road, Banchory, Kincardineshire AB31 5UJ, UK. Electronic address: davies-a1@email.ulster.ac.uk.
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Davies
authors.affiliation: University of Ulster, Room G271, School of Environmental Sciences, Coleraine Campus, Cromore Road, Coleraine, Co. Londonderry BT52 1SA, UK. Electronic address: mj.hope@ulster.ac.uk.
authors.forename: Max J
authors.initials: MJ
authors.lastname: Hope
mesh_terms: D001499:Bayes Theorem; D003247:Conservation of Natural Resources / Q000379:methods*; D003661:Decision Support Techniques; D017753:Ecosystem; D058735:Environmental Policy; D059392:Petroleum Pollution / Q000032:analysis* / Q000517:prevention & control*
keywords: Bayesian inference; Bayesian network; Contingency planning; Environmental decision support system; Oil spill; Pollution response