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Plant pest risks posed by trade in agricultural commodities are managed through pest risk analysis which involves assessing risk and selecting phytosanitary measures to manage unrestricted risk if it is unacceptably high. Diverse measures can be used to reduce risk. However, calibrating risk management protocols with the level of unrestricted risk is challenging. Agreed methods and user-friendly tools for comparatively evaluating risk-reducing measures in different pest-host systems are lacking. Here, we describe the Pest Risk Reduction Scenario Tool (PRReSTo), a generic Bayesian network model that estimates likely infestation rates of host items in consignments. PRReSTo considers host items' vulnerability to pest infestation, the pest abundance to which host items are exposed during production, and the individual and cumulative effects of risk-reducing measures aimed at either minimising host vulnerability, pest exposure or infestation rates. We apply a PRReSTo implementation developed for assessing trappable insect pests in horticultural produce to test its versatility. First, we evaluate likely (unrestricted) host infestation rates under different levels of pest exposure and host vulnerability. Next, we evaluate the adequacy of risk-reducing measures under different host infestation scenarios and acceptability thresholds. We find that equivalent risk reduction may be achieved by highly effective individual measures or combinations of measures in a phytosanitary systems approach. The current implementation of PRReSTo is supported by an open access web application to facilitate adoption as a scenario analysis and decision-support tool by industry and regulators. • Here we present and test the new Pest Risk Reduction Scenario Tool (PRReSTo). • PRReSTo estimates likely infestation rates of host items in consignments. • PRReSTo allows for evaluating the individual or combined effects of risk-reducing measures. • The current implementation of PRReSTo is supported by an open access web application. • PRReSTo may support trading partners in trialling innovative risk-based protocols. [ABSTRACT FROM AUTHOR]

Managing and monitoring invasive alien species (IAS) is costly, and because resources are limited, prioritization decisions are required for planning and management. We present findings on plant pest prioritization for 63 established invader species of natural and grazing ecosystems of Queensland, Australia. We used an expert elicitation approach to assess risk (species occurrence, spread, and impact) and feasibility of control for each IAS. We elicit semi-quantitative responses from diverse expert stakeholders to score IAS on three management approaches (biocontrol, chemical and mechanical) in relation to cost, effectiveness and practicality, and incorporate uncertainty in expert inputs and model outputs. In the process, we look for promising management opportunities as well as seek general trends across species' ecological groups and management methods. Stakeholders were cautiously optimistic about the feasibility of managing IAS. Taking into consideration all factors, the overall feasibility of control was uncorrelated with the stakeholders' level of confidence. However, within individual management criterion, positive trend was observed for the same bivariate traits for chemical control, and negative trends for biocontrol and mechanical controls. Utility and confidence in IAS management options were in the order: chemical > biocontrol = mechanical, with practicality and effectiveness being the main driver components. Management feasibility differed significantly between IAS life forms but not between habitats invaded. Lastly, we combined IAS risk assessment and management feasibility scores to create a risk matrix to guide policy goals (i.e. eradication, spread containment, protection of sensitive sites, targeted control, site management, monitoring, and limited action). The matrix identifies promising species to target for each of these policy outcomes. Overall, our general approach illustrates (i) the importance of understanding the feasibility of IAS control actions and the factors that drive it, and (ii) demonstrates how quantifying management feasibility can be used to enhance traditional risk assessment rankings to improve policy outcomes. • Managing invasive alien species (e.g. weeds) is costly, so prioritization is needed. • Experts assessed feasibility of control methods for weeds of Queensland, Australia. • Chemical control was most effective, followed by biological and mechanical controls. • Practicality and effectiveness were the drivers of control feasibility, not the cost. • Results are linked to on-ground decision actions using a risk assessment matrix. [ABSTRACT FROM AUTHOR]