Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface-associated marine species: a case study on reef sharks Carcharhinus melanopterus shoaling behaviour
Abstract
A novel image analysis-based technique applied to unmanned aerial vehicle (UAV) survey data is
described to detect and locate individual free-ranging sharks within aggregations. The method
allows rapid collection of data and quantification of fine-scale swimming and collective patterns
of sharks. We demonstrate the usefulness of this technique in a small-scale case study exploring
the shoaling tendencies of blacktip reef sharks Carcharhinus melanopterus in a large lagoon
within Moorea, French Polynesia. Using our approach, we found that C. melanopterus displayed
increased alignment with shoal companions when distributed over a sandflat where they are
regularly fed for ecotourism purposes as compared with when they shoaled in a deeper adjacent
channel. Our case study highlights the potential of a relatively low-cost method that combines
UAV survey data and image analysis to detect differences in shoaling patterns of free-ranging
sharks in shallow habitats. This approach offers an alternative to current techniques commonly
used in controlled settings that require time-consuming post-processing effort.