Learning to fly: integrating spatial ecology with unmanned aerial vehicle surveys

Despite the increasing importance of new survey tools such as unmanned aerial vehicles ( UAV s), the implications of how their spatial deployment may interact with species detection errors have not yet been assessed. Acknowledging and incorporating these errors are crucial for accurate population estimation and improved management. To address this important gap in our knowledge, and to discover how flight plans should be selected to reduce overall error, we simulated contrasting UAV flight surveys over a range of population densities and dispersion patterns using different detection errors. We found that if a survey is carried out using an individual transect that low and slow flights consistently provide the best estimates of abundance and occupancy. However, the greater sampling area afforded by higher or faster flights resulted in more complex guidelines for estimates of abundance or occupancy over larger study areas. For highly clustered populations, especially those at low densities, a high and fast survey is preferable, as its greater area coverage best enables detection of local occupancy. The performance rankings of flight plans were sensitive to the underlying species detectability and, to a lesser extent, population density and aggregation. This suggests that UAV survey plans need to account for the spatial and movement ecology of target species, and that flight plans should adapt as an invasive species spreads, or a threatened species contracts. We encapsulate our results in a decision tree to guide flight planning for given survey objectives, detectability, and ecological context. Importantly, these findings provide guidance to other fields with transect‐based surveys such as manned aviation and road or ground transects that trade‐off sampling area and precision of estimates. Promising new technologies such as UAV s will be best utilized by ecologists if detection errors, and their interaction with the spatial ecology of the species, are carefully assessed.