Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions
Stanaway, Mark, Mengersen, Kerrie, & Reeves, Robert (2011) Hierarchical Bayesian modelling of early detection surveillance for plant pest invasions. Environmental and Ecological Statistics, 18(3), pp. 569-591.
Early detection surveillance programs aim to find invasions of exotic plant pests and diseases before they are too widespread to eradicate. However, the value of these programs can be difficult to justify when no positive detections are made. To demonstrate the value of pest absence information provided by these programs, we use a hierarchical Bayesian framework to model estimates of incursion extent with and without surveillance. A model for the latent invasion process provides the baseline against which surveillance data are assessed. Ecological knowledge and pest management criteria are introduced into the model using informative priors for invasion parameters. Observation models assimilate information from spatio-temporal presence/absence data to accommodate imperfect detection and generate posterior estimates of pest extent. When applied to an early detection program operating in Queensland, Australia, the framework demonstrates that this typical surveillance regime provides a modest reduction in the estimate that a surveyed district is infested. More importantly, the model suggests that early detection surveillance programs can provide a dramatic reduction in the putative area of incursion and therefore offer a substantial benefit to incursion management. By mapping spatial estimates of the point probability of infestation, the model identifies where future surveillance resources can be most effectively deployed.
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|Item Type:||Journal Article|
|Keywords:||Invasive species, Risk Analysis, Quarantine, Non-indigenous species, Detectability|
|Subjects:||Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000)|
Australian and New Zealand Standard Research Classification > ENVIRONMENTAL SCIENCES (050000)
Australian and New Zealand Standard Research Classification > BIOLOGICAL SCIENCES (060000)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Past > Schools > Mathematical Sciences
|Copyright Statement:||The final publication is available at link.springer.com|
|Deposited On:||13 Jul 2011 23:11|
|Last Modified:||23 Apr 2013 15:17|
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