Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay
Abal, Eva, Alston, Clair, Chiffings, Tony, Hamilton, Grant, Hart, Barry, & Mengersen, Kerrie (2005) Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay. In Zerger, A. & Argent, R. (Eds.) Proceedings of International Congress on Modelling and Simulation 2005, Modelling and Simulation Society of Australia and New Zealand Inc, Melbourne, Victoria, pp. 392-399.
Bayesian Belief Networks (BBNs) are emerging as valuable tools for investigating complex ecological problems. In a BBN, the important variables in a problem are identified and causal relationships are represented graphically. Underpinning this is the probabilistic framework in which variables can take on a finite range of mutually exclusive states. Associated with each variable is a conditional probability table (CPT), showing the probability of a variable attaining each of its possible states conditioned on all possible combinations of it parents. Whilst the variables (nodes) are connected, the CPT attached to each node can be quantified independently. This allows each variable to be populated with the best data available, including expert opinion, simulation results or observed data. It also allows the information to be easily updated as better data become available ----- ----- This paper reports on the process of developing a BBN to better understand the initial rapid growth phase (initiation) of a marine cyanobacterium, Lyngbya majuscula, in Moreton Bay, Queensland. Anecdotal evidence suggests that Lyngbya blooms in this region have increased in severity and extent over the past decade. Lyngbya has been associated with acute dermatitis and a range of other health problems in humans. Blooms have been linked to ecosystem degradation and have also damaged commercial and recreational fisheries. However, the causes of blooms are as yet poorly understood.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||Lyngbya Majuscula, Moreton Bay, Management|
|Subjects:||Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000) > ECOLOGY (060200) > Freshwater Ecology (060204)
Australian and New Zealand Standard Research Classification > AGRICULTURAL AND VETERINARY SCIENCES (070000) > FISHERIES SCIENCES (070400) > Aquatic Ecosystem Studies and Stock Assessment (070402)
Australian and New Zealand Standard Research Classification > AGRICULTURAL AND VETERINARY SCIENCES (070000) > FISHERIES SCIENCES (070400) > Fish Pests and Diseases (070404)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2005 [please consult the authors]|
|Deposited On:||17 Jun 2009 14:35|
|Last Modified:||29 Feb 2012 13:17|
Repository Staff Only: item control page