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dc.contributor.authorStewart-Koster, Ben
dc.contributor.authorNguyen, Dieu Anh
dc.contributor.authorBurford, Michele A
dc.contributor.authorCondon, Jason
dc.contributor.authorNguyen, Van Qui
dc.contributor.authorLe, Huu Hiep
dc.contributor.authorDoan, Van Bay
dc.contributor.authorSammut, Jesmond
dc.date.accessioned2017-10-30T12:31:32Z
dc.date.available2017-10-30T12:31:32Z
dc.date.issued2017
dc.identifier.issn0308-521X
dc.identifier.doi10.1016/j.agsy.2017.08.001
dc.identifier.urihttp://hdl.handle.net/10072/346109
dc.description.abstractIn recent years, across tropical regions of the world, there has been an expansion of integrated farming systems that combine rice and shrimp production. While these systems were developed as a form of crop-rotation – growing rice in the wet season and shrimp in the dry season – some farmers grow both rice and brackish-water shrimp simultaneously during the wet season. Climatic variability has resulted in considerable crop losses in this system across many regions. Research has yet to identify the complete array of key risk factors, and their potential interactions, for integrated rice-shrimp farming. Consequently, different farming practices and environmental factors that may affect crop production need to be clarified to guide research efforts. We applied a staged, iterative process to develop a probabilistic Bayesian belief network based on expert knowledge that describes the relationships that contribute to the risk of failure of both crops in integrated rice-shrimp farming systems during the wet season. We applied the approach in the Southern Mekong Delta, Vietnam, in the context of a broader research program into the sustainability of the rice-shrimp farming system. The resulting network represents the experts' perceptions of the key risk factors to production and the interactions among them. While both farmers and extension officers contributed to the identification of the processes included in the network, the farmers alone provided estimates of the probability of the relationships among them. The network identified the challenges to minimise the risk of failure for both crops, and the steps farmers can take to mitigate some of them. Overall, farmers perceived they have a better chance to minimise risk of failure for shrimp rather than rice crops, and limited opportunities appear to exist for successful production of both. By engaging the farmers in this process of model development, we were able to identify additional research questions for the broader research team and to identify simple steps the farmers could take to reduce the risk of crop failure. Integrating additional empirical data into this network, as it becomes available, will help identify clear opportunities for improvements in farming practices which should reduce the risk of crop failure into the future.
dc.description.peerreviewedYes
dc.languageEnglish
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofpagefrom230
dc.relation.ispartofpageto240
dc.relation.ispartofjournalAgricultural Systems
dc.relation.ispartofvolume157
dc.subject.fieldofresearchAgricultural and Veterinary Sciences not elsewhere classified
dc.subject.fieldofresearchEnvironmental Sciences
dc.subject.fieldofresearchAgricultural and Veterinary Sciences
dc.subject.fieldofresearchcode079999
dc.subject.fieldofresearchcode05
dc.subject.fieldofresearchcode07
dc.titleExpert based model building to quantify risk factors in a combined aquaculture-agriculture system
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
dcterms.licensehttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.description.versionAccepted Manuscript (AM)
gro.facultyGriffith Sciences, Griffith School of Environment
gro.rights.copyright© 2017 Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (http://creativecommons.org/licenses/by-nc-nd/4.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
gro.hasfulltextFull Text
gro.griffith.authorStewart-Koster, Ben D.
gro.griffith.authorBurford, Michele A.
gro.griffith.authorNguyen, Dieu Anh A.


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