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


Autoria(s): Johnson, Sandra; Abal, Eva; Ahern, Kathleen; Hamilton, Grant
Data(s)

07/03/2013

Resumo

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.

Formato

application/pdf

Identificador

http://eprints.qut.edu.au/64596/

Publicador

Institute of Mathematical Statistics

Relação

http://eprints.qut.edu.au/64596/7/64596.pdf

http://www.e-publications.org/ims/submission/index.php/STS/user/submissionFile/14033?confirm=01e5cdd2

DOI:10.1214/13-STS424

Johnson, Sandra, Abal, Eva, Ahern, Kathleen, & Hamilton, Grant (2013) From science to management : using Bayesian networks to learn about Lyngbya. Statistical Science, 29(1), pp. 36-41.

Direitos

Copyright 2013 Institute of Mathematical Statistics

Fonte

School of Earth, Environmental & Biological Sciences; School of Mathematical Sciences; Science & Engineering Faculty

Palavras-Chave #010000 MATHEMATICAL SCIENCES #050000 ENVIRONMENTAL SCIENCES #Bayesian statistics #Bayesian networks #Lyngbya
Tipo

Journal Article