Modelling for Pest Risk Analysis: Spread and Economic Impacts

Abstract

The introduction of invasive pests beyond their natural range is one of the main causes of the loss of biodiversity and leads to severe costs. Bioeconomic models that integrate biological invasion spread theory, economic impacts and invasion management would be of great help to increase the transparency of pest risk analysis (PRA) and provide for more effective and efficient management of invasive pests. In this thesis, bioeconomic models of management of invasive pests are developed. The models are applied to three cases of study. The main case looks at the invasion in Europe by the western corn rootworm (WCR), Diabrotica virgifera ssp. virgifera LeConte (Coleoptera: Chrysomelidae). A range of quantitative modelling approaches was employed: (i) dispersal kernels fitted to mark-release-recapture experimental data; (ii) optimal control models combined with info-gap theory; (iii) spatially explicit stochastic simulation models; and (iv) agent-based models. As a result of the application of the models new insights on the management of invasive pests and the links between spread and economic impacts were gained: (i) current official management measures to eradicate WCR were found to be ineffective; (ii) eradication and containment programmes that are economically optimal under no uncertainty were found out to be also the most robustly immune policy to unacceptable outcomes under severe uncertainty; (iii) PRA focusing on single invasive pests might lead to management alternatives that dot not correspond to the optimal economic allocation if the rest of the invasive pests sharing the same management budget are considered; (iv) the control of satellite colonies of an invasion occurring by stratified dispersal is ineffective when a strong propagule pressure is generated from the main body of the invasion and this effect is increased by the presence of human-assisted long-distance dispersal; and (v) agent-based models were shown to be an adequate tool to integrate biological invasion spread models with economic analysis models.