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Ecological inference using data from accelerometers needs careful protocols

Ecological inference using data from accelerometers needs careful protocols

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GARDE, Baptiste, Rory P. WILSON, Adam FELL, Nik COLE, Vikash TATAYAH, Mark D. HOLTON, Kayleigh A. ROSE, Richard S. METCALFE, Hermina ROBOTKA, Martin WIKELSKI, Fred TREMBLAY, Shannon WHELAN, Kyle H. ELLIOTT, Emily L. C. SHEPARD, 2022. Ecological inference using data from accelerometers needs careful protocols. In: Methods in Ecology and Evolution. British Ecological Society, Wiley-Blackwell. 13(4), pp. 813-825. ISSN 2041-210X. eISSN 2041-210X. Available under: doi: 10.1111/2041-210X.13804

@article{Garde2022-04Ecolo-56937, title={Ecological inference using data from accelerometers needs careful protocols}, year={2022}, doi={10.1111/2041-210X.13804}, number={4}, volume={13}, issn={2041-210X}, journal={Methods in Ecology and Evolution}, pages={813--825}, author={Garde, Baptiste and Wilson, Rory P. and Fell, Adam and Cole, Nik and Tatayah, Vikash and Holton, Mark D. and Rose, Kayleigh A. and Metcalfe, Richard S. and Robotka, Hermina and Wikelski, Martin and Tremblay, Fred and Whelan, Shannon and Elliott, Kyle H. and Shepard, Emily L. C.} }

Holton, Mark D. Fell, Adam Garde, Baptiste Fell, Adam Wikelski, Martin Metcalfe, Richard S. Rose, Kayleigh A. Tatayah, Vikash 2022-03-22T10:09:43Z Whelan, Shannon Cole, Nik Robotka, Hermina Attribution 4.0 International 2022-03-22T10:09:43Z Tremblay, Fred Robotka, Hermina Ecological inference using data from accelerometers needs careful protocols Shepard, Emily L. C. Wikelski, Martin Shepard, Emily L. C. Holton, Mark D. 2022-04 Whelan, Shannon Tatayah, Vikash Rose, Kayleigh A. Elliott, Kyle H. Tremblay, Fred Metcalfe, Richard S. eng Wilson, Rory P. 1. Accelerometers in animal-attached tags are powerful tools in behavioural ecol-ogy, they can be 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, using data repositories to draw ecological inference requires a good understanding of the error introduced ac-cording to sensor type and position on the study animal and protocols for error assessment and minimisation.<br />2. Using laboratory trials, we examine the absolute accuracy of tri-axial accelerom-eters and determine how inaccuracies impact measurements of dynamic body acceleration (DBA), a proxy for energy expenditure, in human participants. We then examine how tag type and placement affect the acceleration signal in birds, using pigeons Columba livia flying in a wind tunnel, with tags mounted simul-taneously in two positions, and back- and tail- mounted tags deployed on wild kittiwakes Rissa tridactyla. Finally, we present a case study where two genera-tions of tag were deployed using different attachment procedures on red-tailed tropicbirds Phaethon rubricauda foraging in different seasons.<br />3. Bench tests showed that individual acceleration axes required a two- level cor-rection 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 tropicbird study highlighted the difficulties of attributing changes in signal amplitude to a single factor when confounding influences tend to covary, as DBA varied by 25% between seasons.<br />4. Accelerometer accuracy, tag placement and attachment critically affect the sig-nal amplitude and thereby the ability of the system to detect biologically mean-ingful phenomena. We propose a simple method to calibrate accelerometers that can be executed under field conditions. This should be used prior to deploy-ments 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. Elliott, Kyle H. Wilson, Rory P. Garde, Baptiste Cole, Nik

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