Can ethograms be automatically generated using body acceleration data from free-ranging birds?

Toward the quantification of a conceptual framework for movement ecology using circular statistical modeling

To analyze an animal’s movement trajectory, a basic model is required that satisfies the following conditions: the model must have an ecological basis and the parameters used in the model must have ecological interpretations, a broad range of movement patterns can be explained by that model, and equations and probability distributions in the model should be mathematically tractable. Random walk models used in previous studies do not necessarily satisfy these requirements, partly because movement trajectories are often more oriented or tortuous than expected from the models. By improving the modeling for turning angles, this study aims to propose a basic movement model. On the basis of the recently developed circular auto-regressive model, we introduced a new movement model and extended its applicability to capture the asymmetric effects of external factors such as wind. The model was applied to GPS trajectories of a seabird (Calonectris leucomelas) to demonstrate its applicability to various movement patterns and to explain how the model parameters are ecologically interpreted under a general conceptual framework for movement ecology. Although it is based on a simple extension of a generalized linear model to circular variables, the proposed model enables us to evaluate the effects of external factors on movement separately from the animal’s internal state. For example, maximum likelihood estimates and model selection suggested that in one homing flight section, the seabird intended to fly toward the island, but misjudged its navigation and was driven off-course by strong winds, while in the subsequent flight section, the seabird reset the focal direction, navigated the flight under strong wind conditions, and succeeded in approaching the island.

Activity time budget during foraging trips of emperor penguins

We developed an automated method using depth and one axis of body acceleration data recorded by animal-borne data loggers to identify activities of penguins over long-term deployments. Using this technique, we evaluated the activity time budget of emperor penguins (n = 10) both in water and on sea ice during foraging trips in chick-rearing season. During the foraging trips, emperor penguins alternated dive bouts (4.8 ± 4.5 h) and rest periods on sea ice (2.5 ± 2.3 h). After recorder deployment and release near the colony, the birds spent 17.9 ± 8.4% of their time traveling until they reached the ice edge. Once at the ice edge, they stayed there more than 4 hours before the first dive. After the first dive, the mean proportions of time spent on the ice and in water were 30.8 ± 7.4% and 69.2 ± 7.4%, respectively. When in the water, they spent 67.9 ± 3.1% of time making dives deeper than 5 m. Dive activity had no typical diurnal pattern for individual birds. While in the water between dives, the birds had short resting periods (1.2 ± 1.7 min) and periods of swimming at depths shallower than 5 m (0.25 ± 0.38 min). When the birds were on the ice, they primarily used time for resting (90.3 ± 4.1% of time) and spent only 9.7 ± 4.1% of time traveling. Thus, it appears that, during foraging trips at sea, emperor penguins traveled during dives >5 m depth, and that sea ice was primarily used for resting. Sea ice probably provides refuge from natural predators such as leopard seals. We also suggest that 24 hours of sunlight and the cycling of dive bouts with short rest periods on sea ice allow emperor penguins to dive continuously throughout the day during foraging trips to sea.

Using tri-axial acceleration data to identify behavioral modes of free-ranging animals: general concepts and tools illustrated for griffon vultures

Integrating biomechanics, behavior and ecology requires a mechanistic understanding of the processes producing the movement of animals. This calls for contemporaneous biomechanical, behavioral and environmental data along movement pathways. A recently formulated unifying movement ecology paradigm facilitates the integration of existing biomechanics, optimality, cognitive and random paradigms for studying movement. We focus on the use of tri-axial acceleration (ACC) data to identify behavioral modes of GPS-tracked free-ranging wild animals and demonstrate its application to study the movements of griffon vultures (Gyps fulvus, Hablizl 1783). In particular, we explore a selection of nonlinear and decision tree methods that include support vector machines, classification and regression trees, random forest methods and artificial neural networks and compare them with linear discriminant analysis (LDA) as a baseline for classifying behavioral modes. Using a dataset of 1035 ground-truthed ACC segments, we found that all methods can accurately classify behavior (80-90%) and, as expected, all nonlinear methods outperformed LDA. We also illustrate how ACC-identified behavioral modes provide the means to examine how vulture flight is affected by environmental factors, hence facilitating the integration of behavioral, biomechanical and ecological data. Our analysis of just over three-quarters of a million GPS and ACC measurements obtained from 43 free-ranging vultures across 9783 vulture-days suggests that their annual breeding schedule might be selected primarily in response to seasonal conditions favoring rising-air columns (thermals) and that rare long-range forays of up to 1750 km from the home range are performed despite potentially heavy energetic costs and a low rate of food intake, presumably to explore new breeding, social and long-term resource location opportunities.

From sensor data to animal behaviour: an oystercatcher example

Animal-borne sensors enable researchers to remotely track animals, their physiological state and body movements. Accelerometers, for example, have been used in several studies to measure body movement, posture, and energy expenditure, although predominantly in marine animals. In many studies, behaviour is often inferred from expert interpretation of sensor data and not validated with direct observations of the animal. The aim of this study was to derive models that could be used to classify oystercatcher (Haematopus ostralegus) behaviour based on sensor data. We measured the location, speed, and tri-axial acceleration of three oystercatchers using a flexible GPS tracking system and conducted simultaneous visual observations of the behaviour of these birds in their natural environment. We then used these data to develop three supervised classification trees of behaviour and finally applied one of the models to calculate time-activity budgets. The model based on accelerometer data developed to classify three behaviours (fly, terrestrial locomotion, and no movement) was much more accurate (cross-validation error = 0.14) than the model based on GPS-speed alone (cross-validation error = 0.35). The most parsimonious acceleration model designed to classify eight behaviours could distinguish five: fly, forage, body care, stand, and sit (cross-validation error = 0.28); other behaviours that were observed, such as aggression or handling of prey, could not be distinguished. Model limitations and potential improvements are discussed. The workflow design presented in this study can facilitate model development, be adapted to a wide range of species, and together with the appropriate measurements, can foster the study of behaviour and habitat use of free living animals throughout their annual routine.

Detection of feeding behaviour in common carp Cyprinus carpio by using an acceleration data logger to identify mandibular movement

Miniaturized acceleration data loggers were attached to the lower mandible of common carp Cyprinus carpio to remotely identify feeding behaviour. Whether the acceleration signal could distinguish the quantity and quality of food was also investigated. The frequency and amplitude of the lower mandible stroke, calculated from surging acceleration determined by continuous wavelet transformation, significantly increased during the feeding period compared to that during the non-feeding period. These characteristic movement patterns were maintained for mean ±s.e. 187·3 ± 38·2 s when the fish were fed a single item of food and for mean ±s.e. 419·3 ± 28·6 s when they consumed multiple items. The dominant cycle and amplitude calculated according to feeding event duration, however, did not differ significantly between the two types of diets the fish consumed. Surging acceleration could detect mean ±s.e. 89·8 ± 13·5% of feeding events, although the false detection rate was mean ±s.e. 25·9 ± 10·9%. The results indicate that the mandible acceleration measurement method could be utilized to detect and record the feeding events in fishes that use a suction feeding mode similar to C. carpio.

Accelerometer tags: detecting and identifying activities in fish and the effect of sampling frequency

Monitoring and measuring the behaviour and movement of aquatic animals in the wild is typically challenging, though micro-accelerometer (archival or telemetry) tags now provide the means to remotely identify and quantify behavioural states and rates such as resting, swimming, and migrating, and to estimate activity and energy budgets. Most studies use low frequency (≤32 Hz) accelerometer sampling due to battery and data-archiving constraints. In this study we assessed the effect of sampling frequency (aliasing) on activity detection probability using the great sculpin (Myoxocephalus polyacanthoceaphalus) as a model species. Feeding strikes and escape responses (fast-start activities) and spontaneous movements among 7 different great sculpin were triggered, observed and recorded using a tri-axial accelerometer sampling at 100 Hz and video records. We demonstrate that multiple parameters in the time and probability domains can statistically differentiate between activities with high detection (90%) and identification (80%) probabilities. Detection probability for feeding and escape activities decreased by 50% when sampling at <10 Hz. Our analyses illustrate additional problems associated with aliasing and how activity and energy-budget estimates can be compromised and misinterpreted. We recommend that high-frequency (>30 Hz) accelerometer sampling be used in similar lab and field studies. If battery and (or) data storage is limited, we also recommend archiving the events via an on-board algorithm that determines the highest likelihood and subsequent archiving of the various event-classes of interest.

Northern elephant seals adjust gliding and stroking patterns with changes in buoyancy: validation of at-sea metrics of body density

Many diving animals undergo substantial changes in their body density that are the result of changes in lipid content over their annual fasting cycle. Because the size of the lipid stores reflects an integration of foraging effort (energy expenditure) and foraging success (energy assimilation), measuring body density is a good way to track net resource acquisition of free-ranging animals while at sea. Here, we experimentally altered the body density and mass of three free-ranging elephant seals by remotely detaching weights and floats while monitoring their swimming speed, depth and three-axis acceleration with a high-resolution data logger. Cross-validation of three methods for estimating body density from hydrodynamic gliding performance of freely diving animals showed strong positive correlation with body density estimates obtained from isotope dilution body composition analysis over density ranges of 1015 to 1060 kg m(-3). All three hydrodynamic models were within 1% of, but slightly greater than, body density measurements determined by isotope dilution, and therefore have the potential to track changes in body condition of a wide range of freely diving animals. Gliding during ascent and descent clearly increased and stroke rate decreased when buoyancy manipulations aided the direction of vertical transit, but ascent and descent speed were largely unchanged. The seals adjusted stroking intensity to maintain swim speed within a narrow range, despite changes in buoyancy. During active swimming, all three seals increased the amplitude of lateral body accelerations and two of the seals altered stroke frequency in response to the need to produce thrust required to overcome combined drag and buoyancy forces.

Penguin head movement detected using small accelerometers: a proxy of prey encounter rate

Determining temporal and spatial variation in feeding rates is essential for understanding the relationship between habitat features and the foraging behavior of top predators. In this study we examined the utility of head movement as a proxy of prey encounter rates in medium-sized Antarctic penguins, under the presumption that the birds should move their heads actively when they encounter and peck prey. A field study of free-ranging chinstrap and gentoo penguins was conducted at King George Island, Antarctica. Head movement was recorded using small accelerometers attached to the head, with simultaneous monitoring for prey encounter or body angle. The main prey was Antarctic krill (>99% in wet mass) for both species. Penguin head movement coincided with a slow change in body angle during dives. Active head movements were extracted using a high-pass filter (5 Hz acceleration signals) and the remaining acceleration peaks (higher than a threshold acceleration of 1.0 g) were counted. The timing of head movements coincided well with images of prey taken from the back-mounted cameras: head movement was recorded within ±2.5 s of a prey image on 89.1±16.1% (N=7 trips) of images. The number of head movements varied largely among dive bouts, suggesting large temporal variations in prey encounter rates. Our results show that head movement is an effective proxy of prey encounter, and we suggest that the method will be widely applicable for a variety of predators.

Poor flight performance in deep-diving cormorants

Aerial flight and breath-hold diving present conflicting morphological and physiological demands, and hence diving seabirds capable of flight are expected to face evolutionary trade-offs regarding locomotory performances. We tested whether Kerguelen shags Phalacrocorax verrucosus, which are remarkable divers, have poor flight capability using newly developed tags that recorded their flight air speed (the first direct measurement for wild birds) with propeller sensors, flight duration, GPS position and depth during foraging trips. Flight air speed (mean 12.7 m s(-1)) was close to the speed that minimizes power requirement, rather than energy expenditure per distance, when existing aerodynamic models were applied. Flights were short (mean 92 s), with a mean summed duration of only 24 min day(-1). Shags sometimes stayed at the sea surface without diving between flights, even on the way back to the colony, and surface durations increased with the preceding flight durations; these observations suggest that shags rested after flights. Our results indicate that their flight performance is physiologically limited, presumably compromised by their great diving capability (max. depth 94 m, duration 306 s) through their morphological adaptations for diving, including large body mass (enabling a large oxygen store), small flight muscles (to allow for large leg muscles for underwater propulsion) and short wings (to decrease air volume in the feathers and hence buoyancy). The compromise between flight and diving, as well as the local bathymetry, shape the three-dimensional foraging range (<26 km horizontally, <94 m vertically) in this bottom-feeding cormorant.

Behaviour and buoyancy regulation in the deepest-diving reptile: the leatherback turtle

In the face of the physical and physiological challenges of performing breath-hold deep dives, marine vertebrates have evolved different strategies. Although behavioural strategies in marine mammals and seabirds have been investigated in detail, little is known about the deepest-diving reptile – the leatherback turtle (Dermochelys coriacea). Here, we deployed tri-axial accelerometers on female leatherbacks nesting on St Croix, US Virgin Islands, to explore their diving strategy. Our results show a consistent behavioural pattern within dives among individuals, with an initial period of active swimming at relatively steep descent angles (∼–40 deg), with a stroke frequency of 0.32 Hz, followed by a gliding phase. The depth at which the gliding phase began increased with the maximum depth of the dives. In addition, descent body angles and vertical velocities were higher during deeper dives. Leatherbacks might thus regulate their inspired air-volume according to the intended dive depth, similar to hard-shelled turtles and penguins. During the ascent, turtles actively swam with a stroke frequency of 0.30 Hz but with a low vertical velocity (∼0.40 ms–1) and a low pitch angle (∼+26 deg). Turtles might avoid succumbing to decompression sickness (‘the bends’) by ascending slowly to the surface. In addition, we suggest that the low body temperature of this marine ectotherm compared with that of endotherms might help reduce the risk of bubble formation by increasing the solubility of nitrogen in the blood. This physiological advantage, coupled with several behavioural and physical adaptations, might explain the particular ecological niche the leatherback turtle occupies among marine reptiles.

Assessing the development and application of the accelerometry technique for estimating energy expenditure

A theoretically valid proxy of energy expenditure is the acceleration of an animal's mass due to the movement of its body parts. Acceleration can be measured by an accelerometer and recorded onto a data logging device. Relevant studies have usually derived a measure of acceleration from the raw data that represents acceleration purely due to movement of the animal. This is termed 'overall dynamic body acceleration' (ODBA) and to date has proved a robust derivation of acceleration for use as an energy expenditure proxy. Acceleration data loggers are generally easy to deploy and the measures recorded appear robust to slight variation in location and orientation. This review discusses important issues concerning the accelerometry technique for estimating energy expenditure and ODBA; deriving ODBA, calibrating ODBA, acceleration logger recording frequencies, scenarios where ODBA is less likely to be valid, and the power in recording acceleration and heart rate together. While present evidence suggests that ODBA may not quantify energy expenditure during diving by birds and mammals, several recent studies have assessed changes in mechanical work in such species qualitatively through variation in ODBA during periods of submergence. The use of ODBA in field metabolic studies is likely to continue growing, supported by its relative ease of use and range of applications.

ECG response of koalas to tourists proximity: a preliminary study

Koalas operate on a tight energy budget and, thus, may not always display behavioral avoidance reaction when placed in a stressful condition. We investigated the physiological response of captive koalas Phascolarctos cinereus in a conservation centre to the presence of tourists walking through their habitat. We compared, using animal-attached data-recorders, the electrocardiogram activity of female koalas in contact with tourists and in a human-free area. One of the koalas in the tourist zone presented elevated heart rate values and variability throughout the recording period. The remaining female in the exhibit area showed a higher field resting heart rates during the daytime than that in the isolated area. In the evening, heart rate profiles changed drastically and both the koalas in the exhibit and in the tourist-free zones displayed similar field resting heart rates, which were lower than those during the day. In parallel, the autonomic nervous systems of these two individuals evolved from sympathetic-dominant during the day to parasympathetic-dominant in the evening. Our results report ECG of free-living koalas for the first time. Although they are preliminary due to the difficulty of having sufficient samples of animals of the same sex and age, our results stress out the importance of studies investigating the physiological reaction of animals to tourists.

From the eye of the albatrosses: a bird-borne camera shows an association between albatrosses and a killer whale in the Southern Ocean

Albatrosses fly many hundreds of kilometers across the open ocean to find and feed upon their prey. Despite the growing number of studies concerning their foraging behaviour, relatively little is known about how albatrosses actually locate their prey. Here, we present our results from the first deployments of a combined animal-borne camera and depth data logger on free-ranging black-browed albatrosses (Thalassarche melanophrys). The still images recorded from these cameras showed that some albatrosses actively followed a killer whale (Orcinus orca), possibly to feed on food scraps left by this diving predator. The camera images together with the depth profiles showed that the birds dived only occasionally, but that they actively dived when other birds or the killer whale were present. This association with diving predators or other birds may partially explain how albatrosses find their prey more efficiently in the apparently ‘featureless’ ocean, with a minimal requirement for energetically costly diving or landing activities.

Scaling of soaring seabirds and implications for flight abilities of giant pterosaurs

The flight ability of animals is restricted by the scaling effects imposed by physical and physiological factors. In comparisons of the power available from muscle and the mechanical power required to fly, it is predicted that the margin between the powers should decrease with body size and that flying animals have a maximum body size. However, predicting the absolute value of this upper limit has proven difficult because wing morphology and flight styles varies among species. Albatrosses and petrels have long, narrow, aerodynamically efficient wings and are considered soaring birds. Here, using animal-borne accelerometers, we show that soaring seabirds have two modes of flapping frequencies under natural conditions: vigorous flapping during takeoff and sporadic flapping during cruising flight. In these species, high and low flapping frequencies were found to scale with body mass (mass(-0.30) and mass(-0.18)) in a manner similar to the predictions from biomechanical flight models (mass(-1/3) and mass(-1/6)). These scaling relationships predicted that the maximum limits on the body size of soaring animals are a body mass of 41 kg and a wingspan of 5.1 m. Albatross-like animals larger than the limit will not be able to flap fast enough to stay aloft under unfavourable wind conditions. Our result therefore casts doubt on the flying ability of large, extinct pterosaurs. The largest extant soarer, the wandering albatross, weighs about 12 kg, which might be a pragmatic limit to maintain a safety margin for sustainable flight and to survive in a variable environment.