Estimating eradication probabilities and trade-offs for decision analysis in invasive species eradication programs

Abstract

Eradication of invasive species can have substantial benefits but programs often fail and have high costs. Costs can be reduced by substituting lower cost management actions for higher cost actions that have a similar impact on the probability of eradication. A first step towards minimizing costs is to determine all combinations of management actions that achieve eradication with the same probability, which is a form of trade-off analysis. Trade-off analysis can have a high computational cost when large numbers of management alternatives are compared with a complex spatial simulation model. Here, we apply a practical method for conducting trade-off analysis in which statistical methods are applied to data generated by a complex spatial model to derive a simpler model (the meta-model) that is used to determine trade-offs. We demonstrate this approach with a case study focusing on Australia's largest eradication program, the campaign to eradicate red imported fire ants ('Solenopsis invicta'). Trade-offs were estimated for two surveillance methods, remote surveillance and ground surveillance, that are currently used in the eradication program. The methods are applied adaptively, with remote surveillance applied over all potentially infested locations ("area-wide surveillance") and ground surveillance applied near remotely sensed detection points to find and remove remaining undetected individuals ("local surveillance"). The meta-modelling approach provided useful insights for management. When area-wide and local surveillance methods are applied adaptively, increases in the sensitivity of area-wide surveillance can allow for large reductions in the area of local surveillance and treatment. This can potentially result in substantial cost savings in circumstances where local search methods have a high cost.