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Hounslow JL, Fossette S, Byrnes EE, Whiting SD, Lambourne RN, Armstrong NJ, Tucker AD, Richardson AR, Gleiss AC. Multivariate analysis of biologging data reveals the environmental determinants of diving behaviour in a marine reptile. ROYAL SOCIETY OPEN SCIENCE 2022; 9:211860. [PMID: 35958091 PMCID: PMC9364005 DOI: 10.1098/rsos.211860] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 07/20/2022] [Indexed: 06/10/2023]
Abstract
Diving behaviour of 'surfacers' such as sea snakes, cetaceans and turtles is complex and multi-dimensional, thus may be better captured by multi-sensor biologging data. However, analysing these large multi-faceted datasets remains challenging, though a high priority. We used high-resolution multi-sensor biologging data to provide the first detailed description of the environmental influences on flatback turtle (Natator depressus) diving behaviour, during its foraging life-history stage. We developed an analytical method to investigate seasonal, diel and tidal effects on diving behaviour for 24 adult flatback turtles tagged with biologgers. We extracted 16 dive variables associated with three-dimensional and kinematic characteristics for 4128 dives. K-means and hierarchical cluster analyses failed to identify distinct dive types. Instead, principal component analysis objectively condensed the dive variables, removing collinearity and highlighting the main features of diving behaviour. Generalized additive mixed models of the main principal components identified significant seasonal, diel and tidal effects on flatback turtle diving behaviour. Flatback turtles altered their diving behaviour in response to extreme tidal and water temperature ranges, displaying thermoregulation and predator avoidance strategies while likely optimizing foraging in this challenging environment. This study demonstrates an alternative statistical technique for objectively interpreting diving behaviour from multivariate collinear data derived from biologgers.
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Affiliation(s)
- Jenna L. Hounslow
- Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, Western Australia, Australia
- Environmental and Conservation Science, Murdoch University, Western Australia, Australia
| | - Sabrina Fossette
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Evan E. Byrnes
- Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, Western Australia, Australia
- Environmental and Conservation Science, Murdoch University, Western Australia, Australia
- Faculty of Science, Simon Fraser University, British Columbia, Canada
| | - Scott D. Whiting
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Renae N. Lambourne
- Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, Western Australia, Australia
- Environmental and Conservation Science, Murdoch University, Western Australia, Australia
| | - Nicola J. Armstrong
- School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University, Bentley, Western Australia, Australia
| | - Anton D. Tucker
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Anthony R. Richardson
- Parks and Wildlife Service, West Kimberley District, Department of Biodiversity, Conservation and Attractions, Broome, Western Australia, Australia
| | - Adrian C. Gleiss
- Centre for Sustainable Aquatic Ecosystems, Harry Butler Institute, Murdoch University, Western Australia, Australia
- Environmental and Conservation Science, Murdoch University, Western Australia, Australia
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