17Stable isotope analysis (SIA) of whiskers is increasingly used to investigate the foraging

California sea lions (Zalophus californianus) are a highly maneuverable species of marine mammal. During uninterrupted, rectilinear swimming, sea lions oscillate their foreflippers to propel themselves forward without aid from the collapsed hindflippers, which are passively trailed. During maneuvers such as turning and leaping (porpoising), the hindflippers are spread into a delta-wing configuration. There is little information defining the role of otarrid hindflippers as aquatic control surfaces. To examine Z. californianus hindflippers during maneuvering, trained sea lions were video recorded underwater through viewing windows performing porpoising behaviors and banking turns. Porpoising by a trained sea lion was compared to sea lions executing the maneuver in the wild. Anatomical points of reference (ankle and hindflipper tip) were digitized from videos to analyze various performance metrics and define the use of the hindflippers. During a porpoising bout, the hindflippers were considered to generate lift when surfacing with a mean angle of attack of 14.6±6.3°. However, while performing banked 180o turns, the mean angle of attack of the hindflippers was 28.3±7.3°, and greater by another 8-12° for the maximum 20% of cases. The delta-wing morphology of the hindflippers may be advantageous at high angles of attack to prevent stalling during high-performance maneuvers. Lift generated by the delta-shaped hindflippers, in concert with their position far from the center of gravity, would make these appendages effective aquatic control surfaces for executing rapid turning maneuvers.

Detecting when and where animals feed is key to understanding their ecophysiology, but our ability to collect these data in marine mammals remains limited. Here, we test a tag-based accelerometry method to detect prey capture in California sea lions. From synchronized underwater video and acceleration data of two trained sea lions, we isolated a combined acceleration and Jerk pattern that reliably indicated prey capture in training datasets. We observed a stereotyped feeding motion in underwater video that included (1) mouth opening while approaching prey; (2) head deceleration to allow initial suction or prey engulfment, and (3) jaw closure. This motion (1–3) was repeated if a prey item was not initially engulfed. This stereotyped feeding motion informed a signal pattern phrase that accurately detected feeding in a training dataset. This phrase required (1) an initial heave-axis Jerk signal surpassing a threshold based on sampling rate; (2) an estimated dynamic surge-axis deceleration signal surpassing −0.7 g beginning within 0.2 s of the initial Jerk signal; and (3) an estimated dynamic surge-axis acceleration signal surpassing 1.0 g within 0.5 s of the beginning of the prior deceleration signal. We built an automated detector in MATLAB to identify and quantify these patterns. Blind tests of this detector on non-training datasets found high true-positive detection rates (91%–100%) with acceleration sampled at 50–333 Hz and low false-positive detection rates (0%–4.8%) at all sampling rates (16–333 Hz). At 32 Hz and below, true-positive detection rates decreased due to attenuation of signal detail. A detector optimized for an adult female was also accurate at 32–100 Hz when tested on an adult male’s data, suggesting the potential future use of a generalized detector in wild subjects. When tested on the same data, a published triaxial Jerk method produced high true-positive detection rates (91–100%) and low-to-moderate false-positive detection rates (15–43%) at ≥ 32 Hz. Using our detector, larger prey elicited longer prey capture duration in both animals at almost all sampling rates 32 Hz or faster. We conclude that this method can accurately detect feeding and estimate relative prey length in California sea lions.

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