Multivariate analysis of biologging data reveals the environmental determinants of diving behaviour in a marine reptile

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.

I still call Australia home: Satellite telemetry informs the protection of flatback turtles in Western Australian waters

“…By compiling one of the world's largest single‐species satellite tracking datasets, we were able to resolve large and remote areas of importance for multiple stocks of a vulnerable species. The next step into the journey of refining management strategies and management targets for flatbacks is to understand the environmental and biological drivers of their movements at various scales (Hounslow et al, 2022) within the areas of importance outlined here. Identifying hotspots of cumulative impacts from anthropogenic threats within these areas would subsequently allow for dynamic management measures to be established in selected marine reserves (Game et al, 2009; Sequeira, Hays, et al, 2019; Welch et al, 2019) and the likelihood of multiple stocks to be impacted by anthropogenic threats to be examined (Ferreira et al, 2023).…”

Behaviour‐specific spatiotemporal patterns of habitat use by sea turtles revealed using biologging and supervised machine learning

“…Dives encompass fundamental aspects of sea turtle behaviour, yet it has proved challenging to reliably interpret behaviour from the characteristics of dives alone (Hounslow et al, 2022; Seminoff et al, 2006). We used ancillary video data to validate descriptive dive features characterising kinematic and three‐dimensional aspects of dives, to provide reliable and objective biological insight that so far has remained elusive in dive classification from time‐depth data.…”

“…Adult flatback turtles were equipped with either a CATS-Diary (Customised Animal Tracking Solutions; CATS, Moffat Beach, Australia) or CATS-Cam (aka Diary plus video camera) tag on an ad-hoc basis for up to 1 week each. For detailed capture, tag attachment, programming, and retrieval information, see Hounslow et al (2022).…”

“…Data available from the Dryad Digital Repository https://doi.org/10.5061/dryad.7wm37pvzb (Hounslow et al, 2023).…”

Reducing the Impact of Tagging on Flatback Turtles Using Double Passive Integrated Transponder Tags

“…For flatback turtles, their foraging behavior in relatively shallow coastal environments (Whittock et al 2016; Thums et al 2017; Hounslow et al 2022; Peel et al in press) may increase the likelihood of heavy biofouling on flipper tags (Fig. 1).…”