Smartphone technology monitoring shark behaviour November 13, 2017 Monitoring sharks: Murdoch students Jenna Houslow (left) and Evan Byrnes with a lemon shark (Image: Ryan Daly, SOSF) Technology found in smartphones and Fitbits is helping a Murdoch University honours student classify the behaviour of a vulnerable shark species to boost long-term conservation efforts. Jenna Hounslow, with her supervisor Dr Adrian Gleiss, is leading a project with Ryan Daly from the Save Our Seas Foundation D’Arros Research Centre in Seychelles using tags called Accelerometer Data Loggers (ADLs) – fitted in smartphones and Fitbits – to monitor the behavioural changes and three-dimensional movements of sicklefin lemon sharks. Due to heavy fishing and its narrow habitat range, sicklefin lemon sharks are classified as globally vulnerable on the IUCN Red List. Little is known about the tropical shark species, which are often found around the East Indian Ocean, Indonesia and northern Australia. In conjunction with drone video footage, the Murdoch student is matching tagged ADL data to direct observations of the behaviour of tagged sharks swimming in a purpose built pen in the pristine and sheltered natural lagoon of St Joseph Atoll. Hounslow, who is based Murdoch University’s Centre for Fish and Fisheries Research, said understanding shark behaviour would result in improved long term conservation and management strategies. By refining the programming of movement sensor tags such? as ADLs, more data can be gathered from wild free-swimming deployments. “Observing the natural behaviour of sharks is very difficult as they lead cryptic lives underwater and many species are nocturnal or highly migratory,” Hounslow said. “That is why I’m particularly interested in using ADLs to classify behaviour of the tropical population of the sicklefin lemon shark, which is of conservation concern. “Observed behaviours such as resting, swimming and quick acceleration can be time-synchronised to different patterns in the ADL data. “By pinpointing movement data against key behaviours of the sharks, such as fast swimming or head shaking, it will allow us to identify important areas of hunting and eating, which will lead to informed recommendations for conservation and marine park management.” Hounslow will also train a statistical computer model so that ultimately, the behaviour of tagged wild sharks can be inferred from logged data alone, without the need for captive trials or direct observation. This will contribute to the long-term protection of this species and management of its habitat. “Developing a machine learning algorithm that accurately classifies the behaviour of the lemon sharks will allow other researchers to use it for this species with tagged data,” Hounslow added. “By establishing accurate methods for classifying shark behaviour, fewer sharks will need to be tagged in the future, which is great for the vulnerable species.” Hounslow completed her undergraduate degree at Murdoch University, majoring in environmental science and is the first honours student to be funded by the Save Our Seas Foundation. She hopes the project will lead into her PhD. Print This Post Media contact: Luke McManus Tel: (08) 9360 2491 | Mobile: 0400 297 221 | Email: L.McManus@murdoch.edu.au Categories: General, Future Students, Domestic students, Murdoch achievements, Research, School of Veterinary and Life Sciences, School of Veterinary and Life Sciences Research Tags: Research, adrian gleiss, behaviour, environmental science, fitbits, honours, jenna hounslow, lemon sharks, monitoring, murdoch university, ryan daly, seychelles, sharks, smartphones, sosf, students Leave a comment Name (required) Mail (will not be published) (required) Website You can use these tags : <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <s> <strike> <strong> We read every comment and will make every effort to approve each new comment within one working day. To ensure speedy posting, please keep your comments relevant to the topic of discussion, free of inappropriate language and in-line with the editorial integrity of this newsroom. If not, your comments may not be published. Thanks for commenting!