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Surveying multiple invasive pest species at the same time can help reduce the cost of detecting new pest invasions. In this paper, we describe a new method for mapping the relative likelihood of pest invasion via plant propagation material in a geographic setting. The method simulates the invasion of a range of pest species, including arrival in an uninvaded area, spread, and survival in a novel landscape, using information on the spatial and temporal distribution of the suitable host crop species and tentative knowledge of the spread and survival capacities of the target pests. The methodology is applied to a gridded map in which each map cell represents a site in a landscape. The method uses stochastic simulations to depict plausible realizations of the invasion outcomes and estimate the distribution of pest invasion likelihood for each cell in the area of concern. The method then prioritizes the cells based on the stochastic invasion outcomes using a pairwise stochastic dominance rule and a hypervolume indicator. We demonstrate the approach by assessing the relative likelihood of pest invasion for strawberry production in Finland. Our method helps to differentiate sites in a landscape using both the estimates of pest invasion risk and their uncertainty. It can be applied to prioritize sites for plant health surveys and allocate survey resources among large geographic regions. The approach is generalizable and can be used in situations where knowledge of the harmful pest species is poor or nonexistent.

Mapping risks of pest invasions based on the spatio-temporal distribution of hosts