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dc.contributor.authorHorne, Avril C
dc.contributor.authorSzemis, Joanna M
dc.contributor.authorWebb, J Angus
dc.contributor.authorKaur, Simranjit
dc.contributor.authorStewardson, Michael J
dc.contributor.authorBond, Nick
dc.contributor.authorNathan, Rory
dc.date.accessioned2019-06-09T01:34:10Z
dc.date.available2019-06-09T01:34:10Z
dc.date.issued2018
dc.identifier.issn0364-152X
dc.identifier.doi10.1007/s00267-017-0874-8
dc.identifier.urihttp://hdl.handle.net/10072/383528
dc.description.abstractOne important aspect of adaptive management is the clear and transparent documentation of hypotheses, together with the use of predictive models (complete with any assumptions) to test those hypotheses. Documentation of such models can improve the ability to learn from management decisions and supports dialog between stakeholders. A key challenge is how best to represent the existing scientific knowledge to support decision-making. Such challenges are currently emerging in the field of environmental water management in Australia, where managers are required to prioritize the delivery of environmental water on an annual basis, using a transparent and evidence-based decision framework. We argue that the development of models of ecological responses to environmental water use needs to support both the planning and implementation cycles of adaptive management. Here we demonstrate an approach based on the use of Conditional Probability Networks to translate existing ecological knowledge into quantitative models that include temporal dynamics to support adaptive environmental flow management. It equally extends to other applications where knowledge is incomplete, but decisions must still be made.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherSPRINGER
dc.relation.ispartofpagefrom347
dc.relation.ispartofpageto357
dc.relation.ispartofissue3
dc.relation.ispartofjournalENVIRONMENTAL MANAGEMENT
dc.relation.ispartofvolume61
dc.subject.fieldofresearchEnvironmental management
dc.subject.fieldofresearchEnvironmental assessment and monitoring
dc.subject.fieldofresearchcode4104
dc.subject.fieldofresearchcode410402
dc.titleInforming Environmental Water Management Decisions: Using Conditional Probability Networks to Address the Information Needs of Planning and Implementation Cycles
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.hasfulltextNo Full Text
gro.griffith.authorBond, Nick R.


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