DOI: 10.5061/dryad.stqjq2cd3
title: Data from: Dive-by-dive variation in the diving respiratory air volume of southern elephant seals (<em>Mirounga leonina</em>)

description: The role of diving respiratory air volume (DRAV) in deep-diving phocid
 seals remains poorly understood, largely because of the lack of methods
 for measuring DRAV in free-ranging divers that exhale before diving. We
 developed a method to estimate DRAV using a hydrodynamic glide model
 applied to descent glides recorded using multi-sensor data loggers. We
 estimated dive-by-dive DRAV for six negatively buoyant female southern
 elephant seals (Mirounga leonina). During shallow descent glides, rapid
 compression of DRAV influenced net buoyancy and gliding speed, making this
 phase suitable for estimating DRAV. Our results revealed
 dive-by-dive variation in DRAV, which was positively correlated with root
 mean square (RMS) sway acceleration (a proxy for per-stroke effort) and
 the depth at which gliding began during the initial descent. DRAV
 increased with both tissue density and maximum dive depth, suggesting that
 seals adjusted their DRAV to stay closer to neutral buoyancy through their
 dives. However, the observed level of adjustment did not result in neutral
 buoyancy at half of the maximum dive depth, as predicted to minimise
 round-trip locomotion costs. Instead, the seals
 typically adjusted DRAV to reach neutral buoyancy at∼30 m depth,
 &lt;10% of their mean maximum dive depth. This indicates that strong
 negative tissue density imposes transit costs that cannot be fully
 compensated for by DRAV adjustment alone. Future work should explore
 whether other breath-hold divers show similar patterns of DRAV adjustment
 and quantify the associated physiological and ecological benefits.
description: Field site and study animals Animal-attached
 movement data were collected from six, post-breeding female southern
 elephant seals (Jouma’a et al., 2017; Goulet et al., 2020). The seals were
 tagged at two locations: the Kerguelen Islands and Península Valdés,
 Argentina. Tagging occurred in October of 2017 (seals ml17_301 and
 ml17_280), in October of 2018 (ml18_292, ml18_294a, ml18_294b), and in
 October of 2019 (ml19_295a). Each seal was anaethetised and then equipped
 with a head-mounted DTAG-4 sound and movement tag (97×55×33 mm, 200 g in
 air) as well as a neck-mounted Argos tag (SPOT-293, Wildlife Computers,
 72×54×24 mm, 119 g in air). The tags were retrieved when the seals
 returned to moult in December and January. Full details on the animal
 handling and the tagging process can be found in Jouma’a et al. (2017) and
 Goulet et al. (2020), respectively. Ethical approval was provided by the
 French Committee for Polar Environment and the University of St Andrews
 Animal Welfare and Ethics Committee. Dive
 analysis Tag-data analysis was conducted in Igor Pro 8
 (WaveMetrics, Inc., Lake Oswego, OR, USA) and MATLAB (MathWorks, Inc.,
 Natick, Massachusetts, USA). The tag sampled high-resolution depth (25 Hz)
 and triaxial acceleration (200 Hz) for over 30 days (Goulet et al., 2020).
 To capture long-term, independent changes in buoyancy (i.e., tissue
 density), each 24-hour record was spaced at least six days apart to ensure
 independent tissue density estimates. For the analysis,
 the depth and triaxial acceleration data were downsampled to 1 Hz and 25
 Hz, respectively. Speed was calculated as the change in depth per unit
 time (seconds) divided by sin(pitch) for pitch angles greater than |30|
 (Miller et al., 2004). A dive was defined as when the
 animal dived below 5 m depth (&gt; 5 m), and a glide was defined as
 the passive movement of an animal through a medium. Only glides below 5 m
 were used in this study to remove errors in the sway dynamic acceleration
 due to surface-flipper interactions. Each dive was segregated into four
 distinct phases: surface, descent, bottom, and ascent phases. The surface
 phase is when the seal was shallower than 5 m. As defined by Miller et al.
 (2004), the start of the descent phase was recorded when the animal left
 the surface and dived deeper than 5 m depth. The bottom phase started when
 the pitch angle of the seal first exceeded 0, and the ascent phase started
 at the last point in time when the pitch angle was negative. Since all the
 elephant seals were negatively buoyant, this study focused on using the
 descent phase, particularly shallow descent glides, to estimate DRAV at
 the start of each dive. Stroke analysis
 Flipper movements, or strokes, were defined as side-to-side
 oscillations, and one stroke cycle refers to the completion of one
 complete flipper oscillation. The stroking pattern was measured using
 triaxial specific acceleration in the body frame, which includes surge
 (anterior-posterior axis), sway (left-to-right axis) and heave
 (dorsal-ventral axis) accelerations. Given that phocid seals fluke on the
 left-to-right axis of the body frame, sway acceleration was used to detect
 strokes. The accelerometer recorded both gravity-based acceleration
 (reflecting body orientation) and dynamic acceleration (reflecting
 stroking) (Sato et al., 2003). Gravity-based acceleration is the overall
 movement of the body axis, while dynamic acceleration captures stroking. A
 low-pass filter was applied to the measured acceleration of each axis to
 separate the gravity-based acceleration from the dynamic acceleration. The
 filter frequency was determined from the power spectral density of the
 sway acceleration. Following Adachi et al. (2023), gravity-based
 acceleration was used to calculate pitch. Dynamic acceleration was
 filtered out by subtracting gravity-based acceleration from the total
 measured acceleration (Sato et al., 2004). The resulting high-pass
 filtered acceleration was used to detect strokes and glides, with stroke
 detection thresholds specific to each individual. Stroke intensity was
 quantified using the root mean square (RMS) of dynamic acceleration over a
 half-stroke (the period between two consecutive positive zero-crossings).
 The RMS of strokes across depths between 5 and 30 m with at least three
 complete half-strokes during the descent phase were analysed to assess the
 correlation with DRAV estimates.
description: # Data from: Dive-by-dive variation in the diving respiratory air volume
 of southern elephant seals (*Mirounga leonina*)
 [https://doi.org/10.5061/dryad.stqjq2cd3](https://doi.org/10.5061/dryad.stqjq2cd3) ## **Datasets included:** * DRAV_Analysis.Rmd * DRAV_hypothesis_testing_0.03.csv * DRAV_kinematic_correlation_0.03.csv * Sensitivity_analysis.zip * Stroke_Analysis.Rmd ## Description of the data and file structure DRAV was estimated from descent glides between 5 – 50 m depth using the hydrodynamic model. DRAV was analysed for glides that met the following criteria: 1. Dive descents wherein gliding started shallower than 30 m depth. 2. Dive descents with a glide duration longer than 10 seconds. 3. Dive descents with an average pitch angle steeper than -60 . 4. Stable glides with a circular variance of roll and pitch less than 0.1. Criteria 1 and 2 were important to record the deceleration from DRAV. Changes in air volume deeper than 50 m (16.7% of surface DRAV) were not substantial enough to affect the speed of the passive glide. In order to compare the measured and simulated speed over sufficient time for forces to affect speed, only glides with a duration longer than 10 seconds were used. Criteria 3 was set to minimise the error in the DRAV estimation. For instance, glides with a pitch angle shallower than -60  may be affected by the induced drag by lift-generating organs, underestimating the DRAV for the dive. Criteria 4 was essential to extract stable glides where the animal is passively gliding during the descent phase. The dives based on these criteria yielded dives with a maximum dive depth deeper than 100 m, because the behaviour of the seals appeared to be more variable for shallower dives. ### Files and variables #### File: DRAV_hypothesis_testing_0.03.csv **Description:** This dataset contains the estimated diving respiratory air volume (DRAV) along with variables for hypothesis testing. DRAV was calculated assuming a drag coefficient of 0.03. ##### Variables * individual: The unique ID of the animal (e.g. ml17_280a) * day: The number of days after deployment when the data were collected * dive_no: The dive number of the analysed dive * max_depth: Maximum dive depth (m) * Vair: Diving respiratory air volume (ml/kg) * BD: Tissue density of the animal (kg/m^3) * initial_depth: The depth of stroke cessation (m) * avg_pitch: The average pitch during the descent glide phase (deg) * avg_speed: The average speed during the descent glide phase (m/s) * glide_duration: The duration of the glide until reaching 50m depth (s) * cvar_pitch: Circular variance of pitch * cvar_roll: Circular variance of roll * depth_NB: Depth at which neutral buoyancy was achieved (m) #### #### File: DRAV_kinematic_correlation_0.03.csv **Description:** This dataset contains the estimated DRAV for dives that include at least three complete half-strokes during the descent phase, at depths between 5 and 30 meters, to assess the correlation with DRAV estimates. DRAV was calculated assuming a drag coefficient of 0.03. ##### Variables * individual: The unique ID of the animal (e.g. ml17_280a) * day: The number of days after deployment when the data were collected * dive_no: The dive number of the analysed dive * rms: The mean root mean square (RMS) of sway dynamic acceleration during a half-stroke (the period between two consecutive positive zero-crossings) at depths between 5 and 30 metres (m/s^2) * max_depth: Maximum dive depth (m) * Vair: Diving respiratory air volume (ml/kg) * initial_depth: The depth of stroke cessation (m) * avg_pitch: The average pitch during the descent glide phase (deg) * avg_speed: The average speed during the descent glide phase (m/s) * glide_duration: The duration of the glide until reaching 50m depth (s) * cvar_pitch: Circular variance of pitch * cvar_roll: Circular variance of roll #### File: Sensitivity_analysis.zip **Description:** This dataset contains the estimated DRAV for both hypothesis testing and kinematic correlations calculated with drag coefficients of 0.02, 0.03, 0.04, and 0.05. #### File: DRAV_Analysis.Rmd **Description:** This is the R code used to perform the statistical analysis for assessing the association between DRAV to body density and maximum dive depth. This code also includes the code for sensitivity analysis. #### File: Stroke_Analysis.Rmd **Description:** This is the R code used to perform the statistical analysis for kinematic correlation with DRAV. ## Code/software R Version 4.3.2 (R Core Team, 2023) was used to perform the analysis. The nlme package was used for constructing linear mixed models for analysis.