From science to management : using Bayesian networks to learn about Lyngbya
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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|Item Type:||Journal Article|
|Keywords:||Bayesian statistics, Bayesian networks, Lyngbya|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000)
Australian and New Zealand Standard Research Classification > ENVIRONMENTAL SCIENCES (050000)
|Divisions:||Current > Schools > School of Earth, Environmental & Biological Sciences
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2013 Institute of Mathematical Statistics|
|Deposited On:||18 Nov 2013 23:37|
|Last Modified:||19 Nov 2014 08:42|
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