Open Access
February 2014 From Science to Management: Using Bayesian Networks to Learn about Lyngbya
Sandra Johnson, Eva Abal, Kathleen Ahern, Grant Hamilton
Statist. Sci. 29(1): 36-41 (February 2014). DOI: 10.1214/13-STS424


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.


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Sandra Johnson. Eva Abal. Kathleen Ahern. Grant Hamilton. "From Science to Management: Using Bayesian Networks to Learn about Lyngbya." Statist. Sci. 29 (1) 36 - 41, February 2014.


Published: February 2014
First available in Project Euclid: 9 May 2014

zbMATH: 1332.62421
MathSciNet: MR3201844
Digital Object Identifier: 10.1214/13-STS424

Keywords: Bayesian networks , Bayesian statistics , Lyngbya

Rights: Copyright © 2014 Institute of Mathematical Statistics

Vol.29 • No. 1 • February 2014
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