Optimal and robust control of invasive alien species spreading in homogeneous landscapes

Government agencies lack robust modelling tools to manage the spread of invasive alien species (IAS). In this paper, we combine optimal control and simulation methods with biological invasion spread theory to estimate the type of optimal policy and switching point of control efforts against a spreading IAS. We employ information-gap (info-gap) theory to assess how the optimal solutions differ from a policy that is most robustly immune to unacceptable outcomes. The model is applied to the potential invasion of the Colorado potato beetle in the UK. Under no uncertainty, we demonstrate that for many of the parameter combinations the optimal control policy corresponds to slowing down the invasion. The info-gap analysis shows that eradication policies identified as optimal under no uncertainty are robustly the best policies even under severe uncertainty, i.e. even if they are likely to turn into slowing down policies. We also show that the control of satellite colonies, if identified as optimal under no uncertainty, will also be a robust slowing down policy for IAS that can spread by long distance dispersal even for relatively ineffective control measures. The results suggest that agencies adopt management strategies that are robustly optimal, despite the severe uncertainties they face