Bayesian adaptive design: improving the effectiveness of monitoring of the Great Barrier Reef.

Kang, Su Yun; McGree, James M; Drovandi, Christopher C; Caley, M Julian; Mengersen, Kerrie L

Kang, Su Yun; McGree, James M; Drovandi, Christopher C; Caley, M Julian; Mengersen, Kerrie L.

Afiliação

Kang SY; Mathematical Sciences School and Institute for Future Environments, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia.
McGree JM; Mathematical Sciences School and Institute for Future Environments, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia.
Drovandi CC; ARC Centre of Excellence for Mathematical & Statistical Frontiers, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia.
Caley MJ; Mathematical Sciences School and Institute for Future Environments, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia.
Mengersen KL; ARC Centre of Excellence for Mathematical & Statistical Frontiers, Queensland University of Technology, GPO Box 2434, Brisbane, Queensland, 4001, Australia.

Ecol Appl ; 26(8): 2635-2646, 2016 Dec.

Article em En | MEDLINE | ID: mdl-27862584

Assuntos

Recifes de Corais; Monitoramento Ambiental; Animais; Antozoários; Austrália; Teorema de Bayes; Humanos

Palavras-chave

Australia; Bayesian inference; Great Barrier Reef; adaptive design; coral reef ecosystems; reef monitoring; utility functions

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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 2_ODS3 Base de dados: MEDLINE Assunto principal: Monitoramento Ambiental / Recifes de Corais Tipo de estudo: Prognostic_studies Limite: Animals / Humans País/Região como assunto: Oceania Idioma: En Revista: Ecol Appl Ano de publicação: 2016 Tipo de documento: Article

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