Optimal planning of multi-day invasive species surveillance campaigns.
Multi-day survey campaigns are critical for timely detection of biological invasions. We propose a new modelling approach that helps allocate survey inspections in a multi-day campaign aimed at detecting the presence of an invasive organism. We adopt a team orienteering problem to plan daily inspections and use an acceptance sampling approach to find an optimal surveillance strategy for emerald ash borer in Winnipeg, Manitoba, Canada. The manager's problem is to select daily routes and determine the optimal number of host trees to inspect with a particular inspection method in each survey location, subject to upper bounds on the survey budget, daily inspection time, and total survey time span. We compare optimal survey strategies computed with two different management objectives. The first problem minimizes the expected number of survey sites (or area) with undetected infestations. The second problem minimizes slippage - the expected number of undetected infested trees in sites that were not surveyed or where the surveys did not find infestation. We also explore the impact of uncertainty about site infestation rates and detection probabilities on the surveillance strategy. Accounting for uncertainty helps address temporal and spatial variation in infestation rates and yields a more robust surveillance strategy. The approach is generalizable and can support delimiting survey programs for biological invasions at various spatial scales.