Using mock surveillance to quantify pest detectability prior to establishment of exotic leafminers.
Quantifying detectability of exotic pests in local contexts is crucial for designing efficient and regionally relevant surveillance guidelines. Ironically, for areas most in need of preparedness advice, the study of detectability is hampered by the pest's absence. Here, we present a mock surveillance method whereby pest symptoms are simulated on plants, and the detection probability of visual inspection by practitioners is measured across a range of high priority regions at risk of incursions. Detectability of simulated leaf mining damage was found to be no different to real damage in surveillance trials conducted on the vegetable leafminer, Liriomyza sativae, a recently established pest in Australia. Additional trials confirmed that reducing the natural search speed of survey participants by half increased the odds of detecting a leaf mine by an estimated 3.0 times. However, as movement speed mediates a trade-off between the total area covered (the number of pest encounters) and sensitivity (detection probability for each encounter), we found that a survey effort of 10 s per transect meter enhanced field-level detection of L. sativae at a variety of abundances and available times for surveillance. This study demonstrates that mock surveillance trials, through their use of visual effects to mimic plant pest symptoms, can produce locally tested recommendations to enhance preparedness for exotic pests.