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• W2807129143 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." @default.
• W2807129143 created "2018-06-13" @default.
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• W2807129143 date "2018-07-01" @default.
• W2807129143 modified "2023-10-05" @default.
• W2807129143 title "Using unmanned aerial vehicle (UAV) surveys and image analysis in the study of large surface-associated marine species: a case study on reef sharks <i>Carcharhinus melanopterus</i> shoaling behaviour" @default.
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• W2807129143 doi "https://doi.org/10.1111/jfb.13645" @default.
• W2807129143 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29855056" @default.
• W2807129143 hasPublicationYear "2018" @default.
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