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Cost-effective surveillance strategies are needed for efficient responses to biological invasions and must account for the trade-offs between surveillance effort and management costs. Less surveillance may allow greater population growth and spread prior to detection, thereby increasing the costs of damages and control. In addition, surveillance strategies are usually applied in environments under continual invasion pressure where the number, size and location of established populations are unknown prior to detection. We develop a novel modeling framework that accounts for these features of the decision and invasion environment and determines the long term sampling effort that minimises the total expected costs of new invasions. The optimal solution depends on population establishment and growth rates, sample sensitivity, and sample, eradication, and damage costs. We demonstrate how to optimise surveillance systems under budgetary constraints and find that accounting for spatial heterogeneity in sampling costs and establishment rates can greatly reduce management costs.

Eradication is the deliberate elimination of a species from an area. Given that international quarantine measures can never be 100% effective, surveillance for newly arrived populations of nonnative species coupled with their eradication represents an important strategy for excluding potentially damaging insect species. Historically, eradication efforts have not always been successful and have sometimes been met with public opposition. But new developments in our understanding of the dynamics of low-density populations, the availability of highly effective treatment tactics, and bioeconomic analyses of eradication strategies offer new opportunities for developing more effective surveillance and eradication programs. A key component that connects these new developments is the harnessing of Allee effects, which naturally promote localized species extinction. Here we review these developments and suggest how research might enhance eradication strategies.

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