[MARMAM] New paper: Head-mounted accelerometry accurately detects prey capture in California sea lions

Mason Cole masonrcole at gmail.com
Sat Oct 23 10:16:01 PDT 2021


Dear Colleagues,

My coauthors and I are excited to share our new paper in Animal
Biotelemetry describing an analytical method to accurately detect feeding
using head-mounted accelerometry in California sea lions.  The article is
open access and can be found here:

https://rdcu.be/czXAW

Cole, M.R., Zeligs, J.A., Skrovan, S., and McDonald, B.I.  Head-mounted
accelerometry accurately detects prey capture in California sea lions.
Anim Biotelemetry 9, 44 (2021).
https://doi.org/10.1186/s40317-021-00267-7

Abstract:
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.

Please feel free to contact me at masonrcole at gmail.com if you have any
questions.

Cheers,
Mason Cole

-- 
Mason Cole, MSc
Vertebrate Ecology Lab
Moss Landing Marine Laboratories
mcole at mlml.calstate.edu
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