Animal lifestyle changes acceptable mass limits for attached tags

Wilson, Rory P.; Rose, Kayleigh A. R.; Gunner, Richard; Holton, Mark D.; Marks, Nikki J.; Bennet, Nigel; Bell, Stephen H; Twining, Joshua P.; Hesketh, Jamie; Duarte, Carlos M.; Bezodis, Neil E.; Ježek, Miloš; Painter, Michael S.; Silovský, Václav; Crofoot, Meg; Harel, Roi; Arnould, John P. Y.; Allan, Blake M.; Whisson, Desley A.; Alagaili, Abdulaziz N.; Scantlebury, David

doi:10.1101/2021.04.27.441641

Cited by 3 publications

(4 citation statements)

References 31 publications

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“…The difference in signal amplitude may also arise due to changes in the stability of the tag attachment between seasons. Wilson et al ( 2021 ) note how accelerometers in loosely fitted collars on terrestrial mammals provide a signal that varies with collar tightness. Although the use of tape to attach devices to birds (Wilson et al, 1997 ) provides a much more intimate association between the tag and the bird body, we believe that if this method is not standardised (and it was not in our study, as the amount of tape varied between seasons), it can lead to major variation in acceleration values, particularly in animals with highly dynamic movement, such as flight.…”

Section: Discussionmentioning

confidence: 99%

Ecological inference using data from accelerometers needs careful protocols

et al. 2022

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1. Accelerometers in animal-attached tags are powerful tools in behavioural ecology, they can be used to determine behaviour and provide proxies for movementbased 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 according to sensor type and position on the study animal and protocols for error assessment and minimisation.2. Using laboratory trials, we examine the absolute accuracy of tri-axial accelerometers 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 simultaneously in two positions, and back-and tail-mounted tags deployed on wild kittiwakes Rissa tridactyla. Finally, we 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 backmounted tags varying by 13% in kittiwakes. The tropicbird study highlighted the

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Section: Discussionmentioning

confidence: 99%

Ecological inference using data from accelerometers needs careful protocols

et al. 2022

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“…This is backed up by the changes in wingbeat frequency between the two seasons, which would not be affected by either tag position or sensor inaccuracies. However, Wilson et al (2021) note how accelerometers on loosely fitted collar tags on mammals provide a signal that effectively depends on collar tightness: Under normal conditions, when the tag is tightly associated with the body, the unit replicates the body movement and accelerations faithfully. However, when the attachment is loose, the tag is projected forward and upward during the initial phase of a stride cycle because the tag (and/or collar) abuts the body.…”

Section: Discussionmentioning

confidence: 99%

Ecological inference using data from accelerometers needs careful protocols

Garde

Wilson

Fell

et al. 2021

Preprint

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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.Using laboratory trials, we examine the absolute accuracy of tri-axial accelerometers and determine how inaccuracies impact measurements of dynamic body acceleration (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, (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.Bench tests showed that individual acceleration axes required a two-level correction (representing up to 4.3% of the total value) to eliminate measurement error. This resulted in DBA differences of up to 5% between calibrated and uncalibrated tags for humans walking at different speeds. Device position was associated with greater variation in DBA, with upper- and lower back-mounted tags in pigeons varying by 9%, and tail- and back-mounted tags varying by 13% in kittiwakes. Finally, DBA varied by 25% in tropicbirds between seasons, which may be attributable to tag attachment procedures.Accelerometer accuracy, tag placement, and attachment details 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 should be used prior to deployments and archived with resulting data, 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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“…Additionally, the attachment methods and instrument placement appropriate for a slow-moving herbivore are very different from those appropriate for a high-speed carnivore. Instruments, especially GPS collars that are not flush with the skin, can affect the acceleration of athletic animals that rely on running speed to catch prey or escape predation [54]. In some athletic walking species, the forces exerted by instruments weighing less than 3% of the animal's body weight created much larger inertial forces when the animal was moving at speed [54].…”

Section: A Impacts To Walkersmentioning

confidence: 99%

“…For the fastest species, carrying these small instruments at top speeds was the equivalent of carrying a device weighing up to 19% of the animal's body mass [54].…”

Section: A Impacts To Walkersmentioning

confidence: 99%

Minimum reporting standards can promote animal welfare and data quality in biologging research

Payne,

Hale,

Kendall-Bar

et al. 2024

Preprint

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Biologging best practices have been carefully considered since the field’s inception six decades ago. The biologging research community has reduced instrument impacts on study animals by miniaturizing devices, employing sophisticated release mechanisms, and developing novel technological advancements. However, the field still needs standardized best practices for balancing data quality and animal welfare across the scientific process, from design to deployment to reporting. We developed a set of guidelines by reviewing over 150 recent biologging impact studies for instrument characteristics and effects on animal physiology, behavior, and/or demography. From these studies, we distilled eight best practices that can be used by biologging researchers, with a particular focus on minimum reporting standards as a low-cost, high-impact way to promote animal welfare and data quality. We present three scenarios to demonstrate how reporting instrument, data, and animal characteristics can reduce instrument impacts, support future meta-analyses, and facilitate interdisciplinary collaborations. Finally, we summarize the state of knowledge surrounding the impacts of biologging instruments to animals and data. Adopting standardized guidelines for instrumentation best practices is a crucial step towards ensuring that future biologging efforts minimize impacts on animal physiology, behavior, and demography - the very biological metrics our instruments are meant to measure.

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Animal lifestyle changes acceptable mass limits for attached tags

Cited by 3 publications

References 31 publications

Ecological inference using data from accelerometers needs careful protocols

Ecological inference using data from accelerometers needs careful protocols

Ecological inference using data from accelerometers needs careful protocols

Minimum reporting standards can promote animal welfare and data quality in biologging research

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