From science to management: using Bayesian networks to learn about Lyngbya

Johnson, Sandra, Abal, Eva, Ahern, Kathleen and Hamilton, Grant (2014) From science to management: using Bayesian networks to learn about Lyngbya. Statistical Science, 29 1: 36-41. doi:10.1214/13-STS424

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Author Johnson, Sandra
Abal, Eva
Ahern, Kathleen
Hamilton, Grant
Title From science to management: using Bayesian networks to learn about Lyngbya
Formatted title
From science to management: using Bayesian networks to learn about Lyngbya
Journal name Statistical Science   Check publisher's open access policy
ISSN 0883-4237
Publication date 2014-02-01
Year available 2014
Sub-type Article (original research)
DOI 10.1214/13-STS424
Volume 29
Issue 1
Start page 36
End page 41
Total pages 6
Place of publication Beachwood, OH, United States
Publisher Institute of Mathematical Statistics
Language eng
Formatted abstract
Toxic blooms of Lyngbya majuscula occur in coastal areas worldwide and have major ecological, health and economic consequences. The exact causes and combinations of factors which lead to these blooms are not clearly understood. Lyngbya experts and stakeholders are a particularly diverse group, including ecologists, scientists, state and local government representatives, community organisations, catchment industry groups and local fishermen. An integrated Bayesian network approach was developed to better understand and model this complex environmental problem, identify knowledge gaps, prioritise future research and evaluate management options.
Keyword Bayesian statistics
Bayesian networks
Lyngbya
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Office of the Vice-Chancellor
Official 2015 Collection
 
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Created: Tue, 17 Jun 2014, 13:13:59 EST by System User on behalf of Office of Deputy Vice-Chancellor (Research)