10.5061/DRYAD.F7M0CFXWJ
Garde, Baptiste
0000-0002-8726-6279
Swansea University
Wilson, Rory
Swansea University
Fell, Adam
0000-0003-4875-2159
University of Stirling
Cole, Nik
Durrell Wildlife Conservation Trust
Tatayah, Vikash
0000-0003-0759-254X
Mauritian Wildlife Foundation
Holton, Mark
Swansea University
Rose, Kayleigh
Swansea University
Metcalfe, Richard
Swansea University
Robotka, Hermina
Max Planck Institute for Ornithology
Wikelski, Martin
Max Planck Institute of Animal Behavior
Tremblay, Fred
McGill University
Whelan, Shannon
McGill University
Elliott, Kyle
McGill University
Shepard, Emily
Swansea University
Ecological inference using data from accelerometers needs careful protocols
Dryad
dataset
2021
FOS: Biological sciences
European Research Council
https://ror.org/0472cxd90
715874
2022-01-08T00:00:00Z
2022-01-08T00:00:00Z
en
https://doi.org/10.5281/zenodo.5830511
https://doi.org/10.1101/2021.07.07.451487
219337105 bytes
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CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
1. Accelerometers in animal-attached tags have proven to be powerful tools
in behavioural ecology, being used to determine behaviour and provide
proxies for movement-based energy expenditure. Researchers are collecting
and archiving data across systems, seasons and device types. However, in
order to use data repositories to draw ecological inference, we need to
establish the error introduced according to sensor type and position on
the study animal and establish protocols for error assessment and
minimization. 2. Using laboratory trials, we examine the absolute accuracy
of tri-axial accelerometers and determine how inaccuracies impact
measurements of dynamic body acceleration (DBA) in human participants,
with DBA as the main acceleration-based proxy for energy expenditure. We
then examine how tag type and placement affect the acceleration signal in
birds, using (i) pigeons Columba livia flying in a wind tunnel, with tags
mounted simultaneously in two positions, and (ii) back- and tail-mounted
tags deployed on wild kittiwakes Rissa tridactyla. Finally, we (iii)
present a case study where two generations of tag were deployed using
different attachment procedures on red-tailed tropicbirds Phaethon
rubricauda foraging in different seasons. 3. Bench tests showed that
individual acceleration axes required a two-level correction to eliminate
measurement error. This resulted in DBA differences of up to 5% between
calibrated and uncalibrated tags for humans walking at a range of speeds.
Device position was associated with greater variation in DBA, with upper-
and lower back-mounted tags varying by 9% in pigeons, and tail- and
back-mounted tags varying by 13% in kittiwakes. The largest variation
occurred between tropicbirds tagged in different seasons, where DBA varied
by 25%, which may be due to tag attachment procedures. In general, the
tropicbird study highlights the difficulties of attributing changes in
signal amplitude to a single factor, when confounding influences tend to
covary. 4. Accelerometer accuracy, tag placement, and attachment
critically affect the signal amplitude and thereby the ability of the
system to detect biologically meaningful phenomena. We propose a simple
method to calibrate accelerometers that can be executed under field
conditions. This should be used prior to deployments and archived with
resulting data. We also suggest a way that researchers can assess accuracy
in previously collected data, and caution that variable tag placement and
attachment can increase sensor noise and even generate trends that have no
biological meaning.