DOI: 10.5061/dryad.rjdfn2zbm
title: Animal lifestyle affects acceptable mass limits for attached tags

description: Animal-attached devices have transformed our understanding of vertebrate
 ecology. To minimize any associated harm, researchers have long advocated
 that tag masses should not exceed 3% of carrier body mass. However, this
 ignores tag forces resulting from animal movement. Using data from
 collar-attached accelerometers on 10 diverse free-ranging terrestrial
 species from koalas to cheetahs, we detail a tag-based acceleration method
 to clarify acceptable tag mass limits. We quantify animal athleticism in
 terms of fractions of animal movement time devoted to different
 collar-recorded accelerations and convert those accelerations to forces
 (acceleration × tag mass) to allow derivation of any defined force limits
 for specified fractions of any animal's active time. Specifying that
 tags should exert forces that are less than 3% of the gravitational force
 exerted on the animal's body for 95% of the time led to corrected tag
 masses that should constitute between 1.6% and 2.98% of carrier mass,
 depending on athleticism. Strikingly, in four carnivore species
 encompassing two orders of magnitude in mass ( ca 2–200 kg), forces
 exerted by ‘3%' tags were equivalent to 4–19% of carrier body mass
 during moving, with a maximum of 54% in a hunting cheetah. This
 fundamentally changes how acceptable tag mass limits should be determined
 by ethics bodies, irrespective of the force and time limits specified.
description: Tag deployments on free-ranging species We
 selected 4 species of free-living carnivores for detailed analysis,
 exemplifying about 2 orders of magnitude of mass; 10 lions Panthera leo
 (mean mass ca. 152 kg), 1 cheetah Acinonyx jubatus (mass ca. 41 kg), 10
 badgers Meles meles (mean mass ca. 9.1 kg) and 5 pine martens Martes
 martes (mean mass 1.9 kg), and fitted them with collar-mounted tri-axial
 accelerometers (‘Daily Diaries - Wildbyte Technologies
 [http://www.wildbytetechnologies.com/]; measurement range 0-16 g
 [resolution 0.49 mg], recording frequency 40 Hz), all of which constituted
 less than 3% of the mass of the animal carriers (Table S1). Due to the
 weighting of the loggers, and more particularly their associated
 batteries, the units and sensors were positioned on the underside of the
 collar although during movement the collars could rotate, which could
 occasionally, temporarily bring the measuring system off the ventral
 position. After being equipped, the animals roamed freely, behaving
 normally, for periods ranging between 3 and 21 days before the devices
 were recovered. In addition to these, we also deployed collar-mounted
 accelerometers constituting &lt;3% of the carrier mass (Table S1) on
 six select free-ranging animal species. We chose these species by
 capitalizing on available data from animals equipped with high temporal
 resolution acceleration tags on collars from different mammal families
 with varying lifestyles for comparison with the carnivores. The species
 and lifestyles were; a savannah-dwelling monkey - the olive baboon Papio
 Anubis (mean mass 15 kg), an arboreal herbivorous marsupial – the koala
 Phascolarctos cinereus (mean mass 10.3 kg), a nocturnal, semi-arboreal,
 herbivorous marsupial – the mountain brushtail possum Trichosurus
 cunninghami (mean mass 3.2 kg), a grass-eating, desert-dwelling bovid –
 the Arabian oryx Oryx leucoryx (mean mass 74 kg), a grass-eating, wood-
 and moor-dwelling cervid – the red deer Cervus elaphus (mean mass 135 kg)
 and a forest-dwelling, omnivorous pig – the wild boar Sus scrofa (mean
 mass 67 kg). Extensive details on species-specific tagging procedures are
 included in the Supplementary Materials. Trials with
 domestic dogs Twelve domestic dogs (Canis lupus
 domesticus) of seven different breed combinations and three main body
 types (small, racers and northern breeds), ranging 2-45 kg in body mass
 (Table S2), were volunteered by their owners and the RSPCA’s Llys Nini
 Wildlife Centre (Penllergaer, Wales) to take part in this study. Dog body
 masses were obtained from the most recent measurements taken by a
 veterinarian or the RSPCA and we measured body length, forelimb length and
 hindlimb length to the nearest cm. Two leather dog collars (short and
 long) of the same width were used to cover the range in dog neck size.
 Combinations of pre-prepared lead plates (up to 10 cm in length) and
 varying in mass (25, 35, 45, 50, 100, 150 and 175 g) were fashioned into
 collar loads equivalent to 1, 2 and 3% of each carrier dog’s body mass.
 The lead plates were stacked, the longest of them (for the greatest
 masses) being bent to replicate a 10 cm section of the collar
 circumference and attached securely to the ventral collar along their
 full-length using Tesa® tape. A tri-axial accelerometer and its supporting
 battery (3.2 V lithium ion) were taped securely to the load. The tag and
 battery combined weighed 11.9 g and, in the absence of any additional
 load, were considered negligible in mass and used as a control (0 %
 carrier body mass). All trials were approved by the Swansea University
 Animal Welfare Ethical Review Body (ethical approval number IP-1617-21D).
 Each dog was encouraged to traverse along a 25 m stretch of level,
 short-cut grass at slow (walk/amble), moderate (pace/trot) and fast
 (canter/gallop) speeds (because gait affects acceleration signatures
 substantially [24]) wearing collar-tags equivalent to 0, 1, 2 and 3% of
 their body mass (twelve gait and tag mass combinations) and trial order
 was randomized. Posts were spaced every 5 m along the track. A stopwatch
 was used to record the time taken (to the nearest s) for a dog to travel
 20 m in order to calculate an average speed of travel (m s-1).
 Data processing In all cases of animals
 equipped with accelerometers, the 3 channels of raw acceleration data were
 converted to a single metric by calculating the vectorial sum of the
 acceleration following Vect sum = √(ax2+ay2+az2), where a is the
 instantaneous acceleration and the subscripts denote the different
 (orthogonally placed) acceleration axes. We chose to use the Vect sum
 rather than dynamic body acceleration metrics [26] because DBA values do
 not represent peak accelerations due to the gravity-based component being
 removed [27]. The specifics of the surge, heave and sway accelerations
 were not considered separately due to some collar roll. In the case of the
 free-living carnivores, we examined how travel gait affected the Vect sum
 by plotting the cumulative frequency distribution from each species during
 periods of walking, trotting and bounding. For the domestic dogs, we
 selected the maximum 4 peak accelerations in the Vect sum from the gait
 waveforms using the peak analysis tool in OriginLab (2020) to examine them
 as a function of average speed, gait, body mass and tag mass as a
 percentage of carrier body mass in the dogs. We standardized the use of
 four peaks because at the highest speeds some dogs only had four full
 waveforms during the test stretch. Gait was assessed visually in the dogs
 as a walk, trot or bound. The relative forces (% body mass) exerted by the
 tags on their animal carriers were calculated using F = ma, where m is the
 mass of the tag plus collar as a percentage of carrier mass and a is the
 acceleration (g). Tag-based acceleration method
 (TbAM) Finally, in a full cross-species comparison of
 the free-living animals, we plotted the cumulative frequency distribution
 of the Vect sum from each species during periods when they were active (by
 excluding periods where the acceleration signals were constant) to define
 the vector sum of the acceleration at species-specific 95% and 99%
 limits.  Statistical analyses Linear
 mixed-effects models were conducted in R Studio (version 4.0.3, [28])
 within the ‘Lme4’ package (version 1.1-26) in order to investigate how the
 period between acceleration peaks, gait and body mass influenced peak
 accelerations across four species of wild carnivores, and separately in
 domestic dogs. Additionally, we investigated how travel speed (covariate),
 body mass (covariate), collar mass as a percentage of carrier body mass
 (covariate) and gait (fixed factor) influence peak accelerations and
 consequent forces exerted by the tags. Dog ID was included as a random
 factor in all models to accound for repeated measures. All potential
 interaction effects were first investigated and a step-wise back-deletion
 of non-significant interaction terms was conducted. Standard model
 diagnostics were conducted in order to ensure that model assumptions were
 met (examining q-q plots and plotting the residuals against fitted values)
 and data transformations were conducted in order to meet assumptions where
 appropriate. The F statistic and marginal and conditional R2 were
 determined using the ‘car (3.0-5)’ and ‘MuMIn (1.46.6)’ packages,
 respectively. Coefficients for best-fit lines in the figures were
 extracted from the final outputs of the models.