Ecological inference using data from accelerometers needs careful protocols

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.

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