Ullrika Sahlin

1.. Implementation of the full spectra of screening tools to prevent the introduction of invasive species results in a need to evaluate the cost-efficiency of gathering the information needed to screen for these species. 2. We show how the Bayesian value of information approach can be used to derive the benefit of a screening model based on species traits, which in combination with the base rate of invasiveness, i.e. the proportion of invasive species among those introduced and established, predicts species-specific invasiveness. 3. A pre-posterior Bayesian analysis demonstrated that the benefit of the screening model of invasiveness depends on both the accuracy in predictions and the uncertainty in the base rate of invasiveness. However, even though increasing model accuracy always generates higher model benefit, acknowledging or neglecting the uncertainty in the base rate of invasiveness does not. This means that uncertainty in the base rate is important to consider in the cost-benefit analysis of the screening model. 4. As an example, we derived the benefit of basing decisions on a screening model trained for a data set on species traits of invasive and non-invasive marine macroalgae introduced into Europe. The benefit ranged from 0.6% to 19% of the loss of introducing an invasive species, where the actual value can be estimated if we know the monetary values of impacts from introducing invasive and not introducing non-invasive species. 5. Cost-benefit analyses of screening models for invasive species is one means to reach efficient management of the risks of non-indigenous species. Value of information is a useful tool for benefit analysis of predictive models with respect to decision-making, which goes beyond the investigations of model accuracy. Here, we use value of information analysis to evaluate which sources of uncertainty that is most worth while to reduce and how to set the cost of gathering further species-specific information which will improve the accuracy of a screening.