Oscar N. Villalta

Predicting the benefits of banana bunchy top virus exclusion from commercial plantations in Australia.

Benefit cost analysis is a tried and tested analytical framework that can clearly communicate likely net changes in producer welfare from investment decisions to diverse stakeholder audiences. However, in a plant biosecurity context, it is often difficult to predict policy benefits over time due to complex biophysical interactions between invasive species, their hosts, and the environment. In this paper, we demonstrate how a break-even style benefit cost analysis remains highly relevant to biosecurity decision-makers using the example of banana bunchy top virus, a plant pathogen targeted for eradication from banana growing regions of Australia. We develop an analytical approach using a stratified diffusion spread model to simulate the likely benefits of exclusion of this virus from commercial banana plantations over time relative to a nil management scenario in which no surveillance or containment activities take place. Using Monte Carlo simulation to generate a range of possible future incursion scenarios, we predict the exclusion benefits of the disease will avoid Aus

A bio-economic ‘war game’ model to simulate plant disease incursions and test response strategies at the landscape scale

15.9-27.0 million in annual losses for the banana industry. For these exclusion benefits to be reduced to zero would require a bunchy top re-establishment event in commercial banana plantations three years in every four. Sensitivity analysis indicates that exclusion benefits can be greatly enhanced through improvements in disease surveillance and incursion response.

Assessment of pathogenicity and infection requirements of Monilinia species causing brown rot of stone fruit in Australian orchards

Loss of area freedom from invasive alien species can have serious food security implications and place huge responsibility on incursion response managers. They make critical decisions despite profound uncertainty surrounding invasion ecology, surveillance and control technology effectiveness and human behaviour. We propose a spatially-explicit model that can aid response managers in devising and testing management strategies in a virtual world where the costs of failure are negligible. We apply the model in a group-based decision setting in which participants practise responding to fictional disease incursions in a pome fruit production area in Australia. Using the model, the response management group was able to develop mutually satisfactory rules of thumb for the use of quarantine and destruction zones and for when to withdraw resources from eradication efforts.