Search

Abstract Background Studies describing the movement of free-ranging animals often use remotely collected global positioning system (GPS) data. However, such data typically only include intermittent positional information, with a sampling frequency that is constrained by battery life, producing sub-sampling effects that have the potential to bias interpretation. GPS-enhanced ‘dead-reckoning’ of animal movements is an alternative approach that utilises combined information from GPS devices, tri-axial accelerometers, and tri-axial magnetometers. Continuous detailed information of animal movement, activity and habitat selection can then be inferred from finer-scale GPS-enhanced dead-reckoning. It is also a useful technique to reveal the minutiae of an animal’s movements such as path tortuosity. However, examples of studies using these approaches on terrestrial species are limited. Methods Collars equipped with GPS, tri-axial accelerometer, and tri-axial magnetometer loggers were deployed on European badgers, Meles meles, to collect data on geo-position, acceleration and magnetic compass heading, respectively. This enabled us to compare GPS data with calculated GPS-enhanced dead-reckoned data. We also examined space use, distances travelled, speed of travel, and path tortuosity in relation to habitat type. Results Nightly distances travelled were 2.2 times greater when calculated using GPS-enhanced dead-reckoned data than when calculated using GPS data alone. The use of dead-reckoned data reduced Kernel Density Estimates (KDE) of animal ranges to approximately half the size (0.21 km2) estimated using GPS data (0.46 km2). In contrast, Minimum Convex Polygon (MCP) methods showed that use of dead reckoned data yielded larger estimates of animal ranges than use of GPS-only data (0.35 and 0.27 km2, respectively). Analyses indicated that longer periods of activity were associated with greater travel distances and increased activity-related energy expenditure. Badgers also moved greater distances when they travelled at faster speeds and when the routes that they took were less tortuous. Nightly activity-related energy expenditure was not related to average travel speed or average ambient temperature but was positively related to the length of time individuals spent outside the sett (burrow). Badger activity varied with habitat type, with greater distance, speed, track tortuosity, and activity undertaken within woodland areas. Analyses of the effects of varying GPS sampling rate indicate that assessments of distance travelled depend on the sampling interval and the tortuosity of the animal’s track. Where animal paths change direction rapidly, it becomes more important to use dead-reckoned data rather than GPS data alone to determine space use and distances. Conclusions This study demonstrates the efficacy of GPS-enhanced dead-reckoning to collect high-resolution data on animal movements, activity, and locations and thereby identify subtle differences amongst individuals. This work also shows how the temporal resolution of position fixes plays a key role in the estimation of various movement metrics, such as travel speed and track tortuosity.

Abstract Background Recent technological advances have resulted in low-cost GPS loggers that are small enough to be used on a range of seabirds, producing accurate location estimates (± 5 m) at sampling intervals as low as 1 s. However, tradeoffs between battery life and sampling frequency result in studies using GPS loggers on flying seabirds yielding locational data at a wide range of sampling intervals. Metrics derived from these data are known to be scale-sensitive, but quantification of these errors is rarely available. Very frequent sampling, coupled with limited movement, can result in measurement error, overestimating movement, but a much more pervasive problem results from sampling at long intervals, which grossly underestimates path lengths. Methods We use fine-scale (1 Hz) GPS data from a range of albatrosses and petrels to study the effect of sampling interval on metrics derived from the data. The GPS paths were sub-sampled at increasing intervals to show the effect on path length (i.e. ground speed), turning angles, total distance travelled, as well as inferred behavioural states. Results We show that distances (and per implication ground speeds) are overestimated (4% on average, but up to 20%) at the shortest sampling intervals (1–5 s) and underestimated at longer intervals. The latter bias is greater for more sinuous flights (underestimated by on average 40% when sampling > 1-min intervals) as opposed to straight flight (11%). Although sample sizes were modest, the effect of the bias seemingly varied with species, where species with more sinuous flight modes had larger bias. Sampling intervals also played a large role when inferring behavioural states from path length and turning angles. Conclusions Location estimates from low-cost GPS loggers are appropriate to study the large-scale movements of seabirds when using coarse sampling intervals, but actual flight distances are underestimated. When inferring behavioural states from path lengths and turning angles, moderate sampling intervals (10–30 min) may provide more stable models, but the accuracy of the inferred behavioural states will depend on the time period associated with specific behaviours. Sampling rates have to be considered when comparing behaviours derived using varying sampling intervals and the use of bias-informed analyses are encouraged.

Although climate change is predicted to have a substantial effect on the energetic requirements of organisms, the longer-term implications are often unclear. Sloths are limited by the rate at which they can acquire energy and are unable to regulate core body temperature (Tb) to the extent seen in most mammals. Therefore, the metabolic impacts of climate change on sloths are expected to be profound. Here we use indirect calorimetry to measure the oxygen consumption (VO2) and Tb of highland and lowland two-fingered sloths (Choloepus hoffmanni) when exposed to a range of different ambient temperatures (Ta) (18 °C –34 °C), and additionally record changes in Tb and posture over several days in response to natural fluctuations in Ta. We use the resultant data to predict the impact of future climate change on the metabolic rate and Tb of the different sloth populations. The metabolic responses of sloths originating from the two sites differed at high Ta’s, with lowland sloths invoking metabolic depression as temperatures rose above their apparent ‘thermally-active zone’ (TAZ), whereas highland sloths showed increased RMR. Based on climate change estimates for the year 2100, we predict that high-altitude sloths are likely to experience a substantial increase in metabolic rate which, due to their intrinsic energy processing limitations and restricted geographical plasticity, may make their survival untenable in a warming climate.

Abstract Observing animals in the wild often poses extreme challenges, but animal‐borne accelerometers are increasingly revealing unobservable behaviours. Automated machine learning streamlines behaviour identification from the substantial datasets generated during multi‐animal, long‐term studies; however, the accuracy of such models depends on the qualities of the training data. We examined how data processing influenced the predictive accuracy of random forest (RF) models, leveraging the easily observed domestic cat (Felis catus) as a model organism for terrestrial mammalian behaviours. Nine indoor domestic cats were equipped with collar‐mounted tri‐axial accelerometers, and behaviours were recorded alongside video footage. From this calibrated data, eight datasets were derived with (i) additional descriptive variables, (ii) altered frequencies of acceleration data (40 Hz vs. a mean over 1 s) and (iii) standardised durations of different behaviours. These training datasets were used to generate RF models that were validated against calibrated cat behaviours before identifying the behaviours of five free‐ranging tag‐equipped cats. These predictions were compared to those identified manually to validate the accuracy of the RF models for free‐ranging animal behaviours. RF models accurately predicted the behaviours of indoor domestic cats (F‐measure up to 0.96) with discernible improvements observed with post‐data‐collection processing. Additional variables, standardised durations of behaviours and higher recording frequencies improved model accuracy. However, prediction accuracy varied with different behaviours, where high‐frequency models excelled in identifying fast‐paced behaviours (e.g. locomotion), whereas lower‐frequency models (1 Hz) more accurately identified slower, aperiodic behaviours such as grooming and feeding, particularly when examining free‐ranging cat behaviours. While RF modelling offered a robust means of behaviour identification from accelerometer data, field validations were important to validate model accuracy for free‐ranging individuals. Future studies may benefit from employing similar data processing methods that enhance RF behaviour identification accuracy, with extensive advantages for investigations into ecology, welfare and management of wild animals.

Abstract Understanding the processes that determine how animals allocate time to space is a major challenge, although it is acknowledged that summed animal movement pathways over time must define space-time use. The critical question is then, what processes structure these pathways? Following the idea that turns within pathways might be based on environmentally determined decisions, we equipped Arabian oryx with head- and body-mounted tags to determine how they orientated their heads – which we posit is indicative of them assessing the environment – in relation to their movement paths, to investigate the role of environment scanning in path tortuosity. After simulating predators to verify that oryx look directly at objects of interest, we recorded that, during routine movement, > 60% of all turns in the animals’ paths, before being executed, were preceded by a change in head heading that was not immediately mirrored by the body heading: The path turn angle (as indicated by the body heading) correlated with a prior change in head heading (with head heading being mirrored by subsequent turns in the path) twenty-one times more than when path turns occurred due to the animals adopting a body heading that went in the opposite direction to the change in head heading. Although we could not determine what the objects of interest were, and therefore the proposed reasons for turning, we suggest that this reflects the use of cephalic senses to detect advantageous environmental features (e.g. food) or to detect detrimental features (e.g. predators). The results of our pilot study suggest how turns might emerge in animal pathways and we propose that examination of points of inflection in highly resolved animal paths could represent decisions in landscapes and their examination could enhance our understanding of how animal pathways are structured.

Abstract In the British Isles, the European badger (Meles meles) is thought to be the primary wildlife reservoir of bovine tuberculosis (bTB), an endemic disease in cattle. Test, vaccinate or remove (‘TVR’) of bTB test-positive badgers, has been suggested to be a potentially useful protocol to reduce bTB incidence in cattle. However, the practice of removing or culling badgers is controversial both for ethical reasons and because there is no consistent observed effect on bTB levels in cattle. While removing badgers reduces population density, it may also result in disruption of their social behaviour, increase their ranging, and lead to greater intra- and inter-species bTB transmission. This effect has been recorded in high badger density areas, such as in southwest England. However, little is known about how TVR affects the behaviour and movement of badgers within a medium density population, such as those that occur in Northern Ireland (NI), which the current study aimed to examine. During 2014–2017, badger ranging behaviours were examined prior to and during a TVR protocol in NI. Nightly distances travelled by 38 individuals were determined using Global Positioning System (GPS) measurements of animal tracks and GPS-enhanced dead-reckoned tracks. The latter was calculated using GPS, tri-axial accelerometer and tri-axial magnetometer data loggers attached to animals. Home range and core home range size were measured using 95% and 50% autocorrelated kernel density estimates, respectively, based on location fixes. TVR was not associated with measured increases in either distances travelled per night (mean = 3.31 ± 2.64 km) or home range size (95% mean = 1.56 ± 0.62 km2, 50% mean = 0.39 ± 0.62 km2) over the four years of study. However, following trapping, mean distances travelled per night increased by up to 44% eight days post capture. Findings differ from those observed in higher density badger populations in England, in which badger ranging increased following culling. Whilst we did not assess behaviours of individual badgers, possible reasons why no differences in home range size were observed include higher inherent ‘social fluidity’ in Irish populations whereby movements are less restricted by habitat saturation and/or that the numbers removed did not reach a threshold that might induce increases in ranging behaviour. Nevertheless, short-term behavioural disruption from trapping was observed, which led to significant increases in the movements of individual animals within their home range. Whether or not TVR may alter badger behaviours remains to be seen, but it would be better to utilise solutions such as oral vaccination of badgers and/or cattle as well as increased biosecurity to limit bTB transmission, which may be less likely to cause interference and thereby reduce the likelihood of bTB transmission.

Abstract Background Locomotion is often a necessity for animal survival and can account for a large proportion of an individual’s energy budget. Therefore, determining the energy costs of locomotion is an important part of understanding the interaction between an animal and its environment. Measures of animal acceleration, specifically ‘dynamic body acceleration’ (DBA) has proved to be a useful proxy of the energy cost of locomotion. However, few studies have considered the effects of interacting factors such as the animal’s speed or changes to the terrain slope on the putative acceleration versus energy expenditure relationship and how this may affect the relationship between DBA and energy expenditure. Methods Here we conducted a methodological study to evaluate the ability of the metric ‘vectorial dynamic body acceleration’, VeDBA, obtained from tri-axial accelerometer data loggers, to act as a proxy for energy expenditure in non-uniform environments. We used indirect calorimetry to measure the oxygen consumption (V̇O2) of domestic sheep (Ovis aries) that were exposed to different ambient temperatures when immobile (resting) and that walked at various speeds (0.8 to 2.9 km h−1) and slope angles (− 6° to 6°) on a treadmill while simultaneously measuring tri-axial acceleration recorded at 40 Hz by body-mounted tags. Results The lower critical temperature of sheep was identified as 18 °C, and V̇O2 when they were immobile was 3.67 mL O2 kg−1 min−1. There were positive relationships between V̇O2, VeDBA, and speed of walking. However, VeDBA correlated less well with V̇O2 when the terrain slope either inclined or declined. Conclusions We advocate caution when using DBA metrics for establishing energy use in animals moving over uneven terrain and suggest that each study species or location must be examined on a case-by-case basis. Reliance upon the relationship described between acceleration and energy expenditure on horizontal-surface treadmills can lead to potential under- or over-estimates of energy expenditure when animals walk on uneven or inclined ground.

Abstract The energy used by animals is influenced by intrinsic (e.g. physiological) and extrinsic (e.g. environmental) factors. Accelerometers within biologging devices have proven useful for assessing energy expenditures and their behavioural context in free-ranging animals. However, certain assumptions are frequently made when acceleration is used as a proxy for energy expenditure, with factors, such as environmental variation (e.g. ambient temperature or slope of terrain), seldom accounted for. To determine the possible interactions between behaviour, energy expenditure and the environment (ambient temperature and terrain slope), the rate of oxygen consumption ( $${\dot{\text{V}}\text{O}}_{2}$$ V ˙ O 2 ) was measured in pygmy goats (Capra hircus aegarus) using open-flow indirect calorimetry. The effect of temperature (9.7–31.5 °C) on resting energy expenditure was measured. The relationship between $${\dot{\text{V}}\text{O}}_{2}$$ V ˙ O 2 and dynamic body acceleration (DBA) was measured at different walking speeds (0.8–3.0 km h−1) and on different inclines (0, + 15°, − 15°). The daily behaviour of individuals was measured in two enclosures: enclosure A (level terrain during summer) and enclosure B (sloped terrain during winter) and per diem energy expenditures of behaviours estimated using behaviour, DBA, temperature, terrain slope and $${\dot{\text{V}}\text{O}}_{2}$$ V ˙ O 2 . During rest, energy expenditure increased below 22 °C and above 30.5 °C. $${\dot{\text{V}}\text{O}}_{2}$$ V ˙ O 2 (ml min−1) increased with DBA when walking on the level. Walking uphill (+ 15°) increased energetic costs three-fold, whereas walking downhill (− 15°) increased energetic costs by one third. Based on these results, although activity levels were higher in animals in enclosure A during summer, energy expenditure was found to be significantly higher in the sloped enclosure B in winter (means of enclosures A and B: 485.3 ± 103.6 kJ day−1 and 744.5 ± 132.4 kJ day−1). We show that it is essential to account for extrinsic factors when calculating animal energy budgets. Our estimates of the impacts of extrinsic factors should be applicable to other free ranging ungulates.

Summary: Quantifying stress and energetic responses in animals are major challenges, as existing methods lack temporal resolution and elevate animal stress. We propose “wake respirometry,” a new method of quantifying fine-scale changes in CO2 production in unrestrained animals, using a nondispersive infrared CO2 sensor positioned downwind of the animal, i.e., in its wake. We parameterize the dispersion of CO2 in wakes using known CO2 flow rates and wind speeds. Tests with three bird species in a wind tunnel demonstrated that the system can resolve breath-by-breath changes in CO2 concentration, with clear exhalation signatures increasing in period and integral with body size. Changes in physiological state were detectable following handling, flight, and exposure to a perceived threat. We discuss the potential of wake respirometry to quantify stress and respiratory patterns in wild animals and provide suggestions for estimating behavior-specific metabolic rates via full integration of CO2 production across the wake.

Summary: Travel represents a major cost for many animals so there should be selection pressure for it to be efficient – at minimum cost. However, animals sometimes exceed minimum travel costs for reasons that must be correspondingly important. We use Dynamic Body Acceleration (DBA), an acceleration-based metric, as a proxy for movement-based power, in tandem with vertical velocity (rate of change in depth) in a shark (Rhincodon typus) to derive the minimum estimated power required to swim at defined vertical velocities. We show how subtraction of measured DBA from the estimated minimum power for any given vertical velocity provides a “proxy for power above minimum” metric (PPAmin), highlighting when these animals travel above minimum power. We suggest that the adoption of this metric across species has value in identifying where and when animals are subject to compelling conditions that lead them to deviate from ostensibly judicious energy expenditure.

Abstract Global warming is expected to affect movement‐related thermoregulation in ectotherms, but the likely effects on thermoconforming lizards, which spend little energy in thermoregulation behavior, are unclear. We used the Guatemalan beaded lizard (Heloderma charlesbogerti) as a model thermoconforming species to investigate the effects of ambient temperature and barometric pressure (a cue for rain in the study area) on activity intensity and the structure of movement paths. We tracked 12 individuals over a total of 148 animal days during the wet season of 2019 using Global Positioning System tags and triaxial accelerometry. We found a clear positive effect of ambient temperature on activity (using vectorial dynamic body acceleration [VeDBA]) and step length of lizard movements. The movement also became more directional (longer step lengths and smaller turning angles) with increasing ambient temperatures. There was a small negative effect of barometric pressure on VeDBA. We propose that our patterns are indicative of internal state changes in the animals, as they move from a state of hunger, eliciting foraging, which is enhanced by lower temperatures and rainfall to a thermally stressed state, which initiates shelter‐seeking. Our findings highlight the sensitivity of this species to temperature change, show that not all thermoconforming lizards are thermal generalists, and indicate that predicted regional increases in temperature and reduction in rainfall are likely to negatively impact this species by reducing the width of their operational thermal window.