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The Drone Revolution of Shark Science: A Review

Drones are everywhere these days and have endless uses. One application that is increasing in popularity is wildlife management. In this article, the authors explore how drones, including underwater drones like ROVs and AUVs, can be used to study and monitor sharks.

Abstract: Over the past decade, drones have become a popular tool for wildlife management and research. Drones have shown significant value for animals that were often difficult or dangerous to study using traditional survey methods. In the past five years drone technology has become commonplace for shark research with their use above, and more recently, below the water helping to minimise knowledge gaps about these cryptic species. Drones have enhanced our understanding of shark behaviour and are critically important tools, not only due to the importance and conservation of the animals in the ecosystem, but to also help minimise dangerous encounters with humans. To provide some guidance for their future use in relation to sharks, this review provides an overview of how drones are currently used with critical context for shark monitoring. We show how drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. We further detail the advancement in technology across sensors, automation, and artificial intelligence that are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety. An investigation of the shark-based research potential for underwater drones (ROV/AUV) is also provided. Finally, this review provides baseline observations that have been pioneered for shark research and recommendations for how drones might be used to enhance our knowledge in the future.

Author: Butcher, P. A.; Colefax, A. P.; Gorkin, R. A.; Kajiura, S. M.; Naima A. López, N. A.; Mourier, J.; Purcell, C. R.; Skomal, G. B.; Tucker, J. P.; Walsh, A. J.; Williamson, J. E.; Vincent Raoult, V.

Journal: MDPI

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