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