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Protecting islands from pest invasion: optimal allocation of biosecurity resources between quarantine and surveillance
Authors:Joslin L. Moore  Tracy M. Rout  Dorian Moro  Chris Wilcox
Affiliation:a AEDA, School of Botany, University of Melbourne, Parkville, Vic. 3010, Australia
b School of Earth and Environmental Sciences, The University of Adelaide, Adelaide, SA 5005, Australia
c ACERA, School of Botany, University of Melbourne, Parkville, Vic. 3010, Australia
d Chevron Australia, GPO S1580, Perth, WA 6845, Australia
e School of Zoology, University of Tasmania, Private Bag 5, Hobart, Tas. 7001, Australia
f CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tas. 7001, Australia
g The University of Queensland, School of Biology and School of Mathematics and Physics, Brisbane, Qld 4072, Australia
Abstract:Removing pests from islands, and then keeping them pest free, is a common management goal. Given that goal we face a decision: how much effort should we invest in quarantine to reduce the risk of a pest arriving vs. surveillance, looking for the pest on the island with the view of eradicating it before it gets out of control. We use models of an island under threat of invasion by a pest (animal, plant or disease) and a cost minimisation approach to optimally allocate management resources between quarantine and surveillance. In the optimal allocations joint investment in both quarantine and surveillance is uncommon. Investment in quarantine is optimal if quarantine is more effective than surveillance or if large costs associated with pest impact and eradication are incurred at low pest density. Investment in quarantine is also favoured as our ability to eradicate a pest declines. Surveillance is optimal if it is considerably more cost-effective than quarantine and we can generate significant savings through early detection of the pest population. We illustrate how theses models are useful ways to examine these trade-offs by applying the model to the prevention of black rat (Rattus rattus) invasion on Barrow Island, Western Australia. Our model predicts an optimal strategy different to the management strategy currently being used on the island. We suggest that this is due to a risk-averse tendency in managers and the difficulty of estimating costs that combine management, environmental and social factors.
Keywords:Exotic species   Introduced species   Decision theory   Management   Stochastic dynamic program   Eradication
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