Integrating science through Bayesian Belief Networks : case study of Lyngbya in Moreton Bay


Autoria(s): Abal, Eva; Alston, Clair; Chiffings, Tony; Hamilton, Grant; Hart, Barry; Mengersen, Kerrie
Contribuinte(s)

Zerger, A.

Argent, R.

Data(s)

2005

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/24567/

Publicador

Modelling and Simulation Society of Australia and New Zealand Inc

Relação

http://eprints.qut.edu.au/24567/1/c24567.pdf

http://www.mssanz.org.au/modsim05/papers/hamilton.pdf

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.

Direitos

Copyright 2005 [please consult the authors]

Fonte

Faculty of Science and Technology

Palavras-Chave #060204 Freshwater Ecology #070402 Aquatic Ecosystem Studies and Stock Assessment #070404 Fish Pests and Diseases #Lyngbya Majuscula, Moreton Bay, Management
Tipo

Conference Paper