This paper proposes a surveillance model for plant pests that can optimally allocate resources among survey tools with varying properties. While some survey tools are highly specific for the detection of a single pest species, others are more generalized. There is considerable variation in the cost and sensitivity of these tools, but there are no guidelines or frameworks for identifying which tools are most cost-effective when used in surveillance programs that target the detection of newly invaded populations. To address this gap, we applied our model to design a trapping surveillance program in New Zealand for bark- and wood-boring insects, some of the most serious forest pests worldwide. Our findings show that exclusively utilizing generalized traps (GTs) proves to be highly cost-effective across a wide range of scenarios, particularly when they are capable of capturing all pest species. Implementing surveillance programs that only employ specialized traps (ST) is cost-effective only when these traps can detect highly damaging pests. However, even in such cases, they significantly lag in cost-effectiveness compared to GT-only programs due to their restricted coverage. When both GTs and STs are used in an integrated surveillance program, the total expected cost (TEC) generally diminishes when compared to programs relying on a single type of trap. However, this relative reduction in TEC is only marginally larger than that achieved with GT-only programs, as long as highly damaging species can be detected by GTs. The proportion of STs among the optimal required traps fluctuates based on several factors, including the relative pricing of GTs and STs, pest arrival rates, potential damage, and, more prominently, the coverage capacity of GTs. Our analysis suggests that deploying GTs extensively across landscapes appears to be more cost-effective in areas with either very high or very low levels of relative risk density, potential damage, and arrival rate. Finally, STs are less likely to be required when the pests that are detected by those tools have a higher likelihood of successful eradication because delaying detection becomes less costly for these species.

中文翻译：

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植物害虫生物安全监测通用工具和特定物种工具之间的资源优化配置

本文提出了一种植物害虫监测模型，可以在具有不同特性的调查工具之间优化分配资源。虽然一些调查工具对于检测单一害虫物种具有高度针对性，但其他调查工具则更为通用。这些工具的成本和敏感性存在很大差异，但没有指南或框架来确定哪些工具在用于检测新入侵人群的监测计划时最具成本效益。为了解决这一差距，我们应用我们的模型在新西兰设计了一个针对树皮和木材蛀虫（世界上一些最严重的森林害虫）的诱捕监测计划。我们的研究结果表明，事实证明，专门使用通用诱捕器 (GT) 在多种情况下都具有很高的成本效益，特别是当它们能够捕获所有害虫物种时。仅当这些诱捕器能够检测到具有高度破坏性的害虫时，实施仅使用专门诱捕器（ST）的监测计划才具有成本效益。然而，即使在这种情况下，由于覆盖范围有限，与仅 GT 计划相比，它们的成本效益也明显落后。当综合监测计划中同时使用 GT 和 ST 时，与依赖单一类型陷阱的计划相比，总体预期成本 (TEC) 通常会降低。然而，只要 GT 能够检测到高破坏性物种，TEC 的相对减少量仅略高于仅 GT 计划所实现的水平。 ST 在​​最佳所需诱捕器中的比例会根据多种因素而波动，包括​​ GT 和 ST 的相对价格、害虫到达率、潜在损害，以及更重要的是 GT 的覆盖能力。我们的分析表明，在相对风险密度、潜在损害和到达率水平非常高或非常低的地区，在不同地区广泛部署 GT 似乎更具成本效益。最后，当这些工具检测到的害虫成功根除的可能性较高时，就不太可能需要 ST，因为延迟检测对这些物种来说成本较低。