Autor: |
Mitchell JD; Queensland Government, Department of Agriculture and Fisheries, Animal Science, Ecosciences Precinct, 41 Boggo Road, Dutton Park, QLD 4102, Australia., Scott-Holland TB; Queensland Government, Department of Agriculture and Fisheries, Fisheries Queensland, 41 George Street, Brisbane, QLD 4000, Australia., Butcher PA; New South Wales Department of Primary Industries, Fisheries, National Marine Science Centre, Southern Cross University, Coffs Harbour, NSW 2450, Australia. |
Jazyk: |
angličtina |
Zdroj: |
Biology [Biology (Basel)] 2022 Oct 23; Vol. 11 (11). Date of Electronic Publication: 2022 Oct 23. |
DOI: |
10.3390/biology11111552 |
Abstrakt: |
Drones enable the monitoring for sharks in real-time, enhancing the safety of ocean users with minimal impact on marine life. Yet, the effectiveness of drones for detecting sharks (especially potentially dangerous sharks; i.e., white shark, tiger shark, bull shark) has not yet been tested at Queensland beaches. To determine effectiveness, it is necessary to understand how environmental and operational factors affect the ability of drones to detect sharks. To assess this, we utilised data from the Queensland SharkSmart drone trial, which operated at five southeast Queensland beaches for 12 months in 2020−2021. The trial conducted 3369 flights, covering 1348 km and sighting 174 sharks (48 of which were >2 m in length). Of these, eight bull sharks and one white shark were detected, leading to four beach evacuations. The shark sighting rate was 3% when averaged across all beaches, with North Stradbroke Island (NSI) having the highest sighting rate (17.9%) and Coolum North the lowest (0%). Drone pilots were able to differentiate between key shark species, including white, bull and whaler sharks, and estimate total length of the sharks. Statistical analysis indicated that location, the sighting of other fauna, season and flight number (proxy for time of day) influenced the probability of sighting sharks. |
Databáze: |
MEDLINE |
Externí odkaz: |
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