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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 FROM AUTHOR]

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 FROM AUTHOR]

Background: Animal-attached devices can be used on cryptic species to measure their movement and behaviour, enabling unprecedented insights into fundamental aspects of animal ecology and behaviour. However, direct observations of subjects are often still necessary to translate biologging data accurately into meaningful behaviours. As many elusive species cannot easily be observed in the wild, captive or domestic surrogates are typically used to calibrate data from devices. However, the utility of this approach remains equivocal. Methods: Here, we assess the validity of using captive conspecifics, and phylogenetically-similar domesticated counterparts (surrogate species) for calibrating behaviour classification. Tri-axial accelerometers and tri-axial magnetometers were used with behavioural observations to build random forest models to predict the behaviours. We applied these methods using captive Alpine ibex (Capra ibex) and a domestic counterpart, pygmy goats (Capra aegagrus hircus), to predict the behaviour including terrain slope for locomotion behaviours of captive Alpine ibex. Results: Behavioural classification of captive Alpine ibex and domestic pygmy goats was highly accurate (> 98%). Model performance was reduced when using data split per individual, i.e., classifying behaviour of individuals not used to train models (mean ± sd = 56.1 ± 11%). Behavioural classifications using domestic counterparts, i.e., pygmy goat observations to predict ibex behaviour, however, were not sufficient to predict all behaviours of a phylogenetically similar species accurately (> 55%). Conclusions: We demonstrate methods to refine the use of random forest models to classify behaviours of both captive and free-living animal species. We suggest there are two main reasons for reduced accuracy when using a domestic counterpart to predict the behaviour of a wild species in captivity; domestication leading to morphological differences and the terrain of the environment in which the animals were observed. We also identify limitations when behaviour is predicted in individuals that are not used to train models. Our results demonstrate that biologging device calibration needs to be conducted using: (i) with similar conspecifics, and (ii) in an area where they can perform behaviours on terrain that reflects that of species in the wild. [ABSTRACT FROM AUTHOR]

The use of animal‐attached data loggers to quantify animal movement has increased in popularity and application in recent years. High‐resolution tri‐axial acceleration and magnetometry measurements have been fundamental in elucidating fine‐scale animal movements, providing information on posture, traveling speed, energy expenditure, and associated behavioral patterns. Heading is a key variable obtained from the tandem use of magnetometers and accelerometers, although few field investigations have explored fine‐scale changes in heading to elucidate differences in animal activity (beyond the notable exceptions of dead‐reckoning).This paper provides an overview of the value and use of animal heading and a prime derivative, angular velocity about the yaw axis, as an important element for assessing activity extent with potential to allude to behaviors, using "free‐ranging" Loggerhead turtles (Caretta caretta) as a model species.We also demonstrate the value of yaw rotation for assessing activity extent, which varies over the time scales considered and show that various scales of body rotation, particularly rate of change of yaw, can help resolve differences between fine‐scale behavior‐specific movements. For example, oscillating yaw movements about a central point of the body's arc implies bouts of foraging, while unusual circling behavior, indicative of conspecific interactions, could be identified from complete revolutions of the longitudinal axis.We believe this approach should help identification of behaviors and "space‐state" approaches to enhance our interpretation of behavior‐based movements, particularly in scenarios where acceleration metrics have limited value, such as for slow‐moving animals. [ABSTRACT FROM AUTHOR]

Animal behavior is elicited, in part, in response to external conditions, but understanding how animals perceive the environment and make the decisions that bring about these behavioral responses is challenging. Animal heads often move during specific behaviors and, additionally, typically have sensory systems (notably vision, smell, and hearing) sampling in defined arcs (normally to the front of their heads). As such, head‐mounted electronic sensors consisting of accelerometers and magnetometers, which can be used to determine the movement and directionality of animal heads (where head "movement" is defined here as changes in heading [azimuth] and/or pitch [elevation angle]), can potentially provide information both on behaviors in general and also clarify which parts of the environment the animals might be prioritizing ("environmental framing"). We propose a new approach to visualize the data of such head‐mounted tags that combines the instantaneous outputs of head heading and pitch in a single intuitive spherical plot. This sphere has magnetic heading denoted by "longitude" position and head pitch by "latitude" on this "orientation sphere" (O‐sphere). We construct the O‐sphere for the head rotations of a number of vertebrates with contrasting body shape and ecology (oryx, sheep, tortoises, and turtles), illustrating various behaviors, including foraging, walking, and environmental scanning. We also propose correcting head orientations for body orientations to highlight specific heading‐independent head rotation, and propose the derivation of O‐sphere‐metrics, such as angular speed across the sphere. This should help identify the functions of various head behaviors. Visualizations of the O‐sphere provide an intuitive representation of animal behavior manifest via head orientation and rotation. This has ramifications for quantifying and understanding behaviors ranging from navigation through vigilance to feeding and, when used in tandem with body movement, should provide an important link between perception of the environment and response to it in free‐ranging animals. [ABSTRACT FROM AUTHOR]

Two prime issues can detrimentally affect animals that have been equipped with tags: (i) the effect of the capture and restraint process; and (ii) the effect of the tag itself. This work examines some of the issues surrounding quantification of tag effects on wild animals for both restrained and free‐living animals. A new method to quantify stress effects based on monitoring ventilation rates in relation to activity is suggested for restrained animals which may help improve the practice of handling animals. It is also suggested that various metrics, many derived from accelerometers, can be examined in tagged wild animals to examine the change in behaviors over time with a view to having a better understanding of welfare issues, assuring the quality of recorded data and informing best practice. [ABSTRACT FROM AUTHOR]

Decomposing the life track of an animal into behavioral segments is a fundamental challenge for movement ecology. The proliferation of high‐resolution data, often collected many times per second, offers much opportunity for understanding animal movement. However, the sheer size of modern data sets means there is an increasing need for rapid, novel computational techniques to make sense of these data. Most existing methods were designed with smaller data sets in mind and can thus be prohibitively slow. Here, we introduce a method for segmenting high‐resolution movement trajectories into sites of interest and transitions between these sites. This builds on a previous algorithm of Benhamou and Riotte‐Lambert (2012). Adapting it for use with high‐resolution data. The data's resolution removed the need to interpolate between successive locations, allowing us to increase the algorithm's speed by approximately two orders of magnitude with essentially no drop in accuracy. Furthermore, we incorporate a color scheme for testing the level of confidence in the algorithm's inference (high = green, medium = amber, low = red). We demonstrate the speed and accuracy of our algorithm with application to both simulated and real data (Alpine cattle at 1 Hz resolution). On simulated data, our algorithm correctly identified the sites of interest for 99% of "high confidence" paths. For the cattle data, the algorithm identified the two known sites of interest: a watering hole and a milking station. It also identified several other sites which can be related to hypothesized environmental drivers (e.g., food). Our algorithm gives an efficient method for turning a long, high‐resolution movement path into a schematic representation of broadscale decisions, allowing a direct link to existing point‐to‐point analysis techniques such as optimal foraging theory. It is encoded into an R package called SitesInterest, so should serve as a valuable tool for making sense of these increasingly large data streams. We have constructed a new method for identifying sites of interest, tailored specifically for use with high resolution data. This allows for a complicated movement trajectory to be simplified into a "Markov chain‐like" description of behavioural choices, highlighting the animal's broadscale decisions. [ABSTRACT FROM AUTHOR]

The development of multisensor animal‐attached tags, recording data at high frequencies, has enormous potential in allowing us to define animal behaviour.The high volumes of data, are pushing us towards machine‐learning as a powerful option for distilling out behaviours. However, with increasing parallel lines of data, systems become more likely to become processor limited and thereby take appreciable amounts of time to resolve behaviours.We suggest a Boolean approach whereby critical changes in recorded parameters are used as sequential templates with defined flexibility (in both time and degree) to determine individual behavioural elements within a behavioural sequence that, together, makes up a single, defined behaviour.We tested this approach, and compared it to a suite of other behavioural identification methods, on a number of behaviours from tag‐equipped animals; sheep grazing, penguins walking, cheetah stalking prey and condors thermalling.Overall behaviour recognition using our new approach was better than most other methods due to; (1) its ability to deal with behavioural variation and (2) the speed with which the task was completed because extraneous data are avoided in the process.We suggest that this approach is a promising way forward in an increasingly data‐rich environment and that workers sharing algorithms can provide a powerful library for the benefit of all involved in such work. [ABSTRACT FROM AUTHOR]

The article discusses a study which describes a mathematical model that considers the impact of body mass and the turning ability of animals on the outcome of land-based pursuits between predators and their preys.

The Magellanic penguin Spheniscus magellanicus has recently colonized two new coastal sites (Islote Lobos and El Pedral), increasing the number of colonies in northern Patagonia, Argentina. Assuming foraging parameters during the breeding season to be valid short-term indicators of population health, we studied several foraging parameters of penguins from the two new established sites and from an older and well-established colony (Punta Norte) also localized in the north of Patagonia. Penguins from the recently formed colonies performed shorter foraging trips and visited waters closer to their colony than birds from Punta Norte, with penguins from Punta Norte spending almost twice the time at sea spent by penguins from El Pedral. Penguins from Punta Norte also spent more time underwater, spent a higher proportion of the complete diving cycle searching for prey, performed more wiggles (indicative of prey capture) and had fewer estimated prey captures per unit time underwater than penguins from Islote Lobos and El Pedral. This information suggests that, given no limitations on nest-site availability and no prevalence of predators, the good foraging conditions around El Pedral and Islote Lobos may be implicated in the increase in these two relatively new colonies. [ABSTRACT FROM AUTHOR]

Biologists studying animals in their natural environment are increasingly using sensors such as accelerometers in animal-attached 'smart' tags because it is widely acknowledged that this approach can enhance the understanding of ecological and behavioural processes. The potential of such tags is tempered by the difficulty of extracting animal behaviour from the sensors which is currently primarily dependent on the manual inspection of multiple time series graphs. This is time consuming and error-prone for the domain expert and is now the limiting factor for realising the value of tags in this area. We introduce TimeClassifier, a visual analytic system for the classification of time series data for movement ecologists. We deploy our system with biologists and report two real-world case studies of its use. [ABSTRACT FROM AUTHOR]

Assessment of animal internal "state" - which includes hormonal, disease, nutritional, and emotional states - is normally considered the province of laboratory work, since its determination in animals in the wild is considered more difficult. However, we show that accelerometers attached externally to animals as diverse as elephants, cockroaches, and humans display consistent signal differences in micro-movement that are indicative of internal state. Originally used to elucidate the behavior of wild animals, accelerometers also have great potential for highlighting animal actions, which are considered as responses stemming from the interplay between internal state and external environment. Advances in accelerometry may help wildlife managers understand how internal state is linked to behavior and movement, and thus clarify issues ranging from how animals cope with the presence of newly constructed roads to how diseased animals might change movement patterns and therefore modulate disease spread. [ABSTRACT FROM AUTHOR]

Introduction: Our ability to document insect preference for semiochemicals is pivotal in pest control as these agents can improve monitoring and be deployed within integrated pest management programmes for more efficacious control of pest species. However, methods used to date have drawbacks that limit their utility. We present and test a new concept for determining insect motivation to move towards, or away from, semiochemicals by noting direction and speed of movement as animals work against a defined energy landscape (environmentally dependent variation in the cost of transport) requiring different powers to negotiate. We conducted trials with the pine weevils Hylobius abietis and peach-potato aphids Myzus persicae exposed to various attractants and repellents and placed so that they either moved up defined slopes against gravity or had to travel over variously rough surfaces. Results: Linear Mixed Models demonstrated clear reductions in travel speed by insects moving along increasingly energetically taxing energy landscapes but also that responses varied according to different semiochemicals, thus highlighting the value of energy landscapes as a new concept to help measure insect motivation to access or avoid different attractants or repellents across individuals. Conclusions: New sensitive, detailed indicators of insect motivation derived from this approach should prove important in pest control across the world. [ABSTRACT FROM AUTHOR]

Devices attached to flying birds can hugely enhance our understanding of their behavioural ecology for periods when they cannot be observed directly. For this, scientists routinely attach units to either birds' backs or their tails. However, inappropriate payload distribution is critical in aircraft and, since birds and planes are subject to the same laws of physics during flight, we considered aircraft aerodynamic constraints to explain flight patterns displayed by northern gannets Sula bassana equipped with (small ca. 14 g) tail- and back-mounted accelerometers and (larger ca. 30 g) tail-mounted GPS units. Tail-mounted GPS-fitted birds showed significantly higher cumulative numbers of flap-glide cycles and a higher pitch angle of the tail than accelerometer-equipped birds, indicating problems with balancing inappropriately placed weights with knock-on consequences relating to energy expenditure. These problems can be addressed by carefully choosing where to place tags on birds according to the mass of the tags and the lifestyle of the subject species. [ABSTRACT FROM AUTHOR]

Researchers hoping to elucidate the behaviour of species that aren’t readily observed are able to do so using biotelemetry methods. Accelerometers in particular are proving particularly effective and have been used on terrestrial, aquatic and volant species with success. In the past, behavioural modes were detected in accelerometer data through manual inspection, but with developments in technology, modern accelerometers now record at frequencies that make this impractical. In light of this, some researchers have suggested the use of various machine learning approaches as a means to classify accelerometer data automatically. We feel uptake of this approach by the scientific community is inhibited for two reasons; 1) Most machine learning algorithms require selection of summary statistics which obscure the decision mechanisms by which classifications are arrived, and 2) they are difficult to implement without appreciable computational skill. We present a method which allows researchers to classify accelerometer data into behavioural classes automatically using a primitive machine learning algorithm, k-nearest neighbour (KNN). Raw acceleration data may be used in KNN without selection of summary statistics, and it is easily implemented using the freeware program R. The method is evaluated by detecting 5 behavioural modes in 8 species, with examples of quadrupedal, bipedal and volant species. Accuracy and Precision were found to be comparable with other, more complex methods. In order to assist in the application of this method, the script required to run KNN analysis in R is provided. We envisage that the KNN method may be coupled with methods for investigating animal position, such as GPS telemetry or dead-reckoning, in order to implement an integrated approach to movement ecology research. [ABSTRACT FROM AUTHOR]

Increasing experience in long-lived species is fundamental to improving breeding success and ultimately individual fitness. Diving efficiency of marine animals is primarily determined by their physiological and mechanical characteristics. This efficiency may be apparent via examination of biomechanical performance (e.g. stroke frequency and amplitude, change in buoyancy or body angle, etc.), which itself may be modulated according to resource availability, particularly as a function of depth. We investigated how foraging and diving abilities vary with age in a long-lived seabird. During two breeding seasons, small accelerometers were deployed on young (5year old) and older (8/9year old) brooding king penguins (Aptenodytes patagonicus) at the Crozet Archipelago, Indian Ocean. We used partial dynamic body acceleration (PDBA) to quantify body movement during dive and estimate diving cost. During the initial part of the descent, older birds exerted more effort for a given speed but younger penguins worked harder in relation to performance at greater depths. Younger birds also worked harder per unit speed for virtually the whole of the ascent. We interpret these differences using a model that takes into account the upthrust and drag to which the birds are subjected during the dive. From this, we suggest that older birds inhale more at the surface but that an increase in the drag coefficient is the factor leading to the increased effort to swim at a given speed by the younger birds at greater depths. We propose that this higher drag may be the result of young birds adopting less hydrodynamic postures or less direct trajectories when swimming or even having a plumage in poorer condition. [ABSTRACT FROM AUTHOR]

Introduction: Animal travel speed is an ecologically significant parameter, with implications for the study of energetics and animal behaviour. It is also necessary for the calculation of animal paths by dead-reckoning. Dead-reckoning uses heading and speed to calculate an animal's path through its environment on a fine scale. It is often used in aquatic environments, where transmission telemetry is difficult. However, its adoption for tracking terrestrial animals is limited by our ability to measure speed accurately on a fine scale. Recently, tri-axial accelerometers have shown promise for estimating speed, but their accuracy appears affected by changes in substrate and surface gradients. The purpose of the present study was to evaluate four metrics of acceleration; Overall dynamic body acceleration (ODBA), vectorial dynamic body acceleration (VDBA), acceleration peak frequency and acceleration peak amplitude, as proxies for speed over hard, soft and inclined surfaces, using humans as a model species. Results: A general linear model (GLM) showed a significant difference in the relationships between the metrics and speed depending on substrate or surface gradient. When the data from all surface types were considered together, VeDBA had the highest coefficient of determination. Conclusions: All of the metrics showed some variation in their relationship with speed according to the surface type. This indicates that changes in the substrate or surface gradient during locomotion by animals would produce errors in speed estimates, and also in dead-reckoned tracks if they were calculated from speeds based entirely on a priori calibrations. However, we describe a method by which the relationship between acceleration metrics and speed can be corrected ad hoc, until tracks accord with periodic ground truthed positions, obtained via a secondary means (e.g. VHF or GPS telemetry). In this way, dead-reckoning provides a means to obtain fine scale movement data for terrestrial animals, without the need for additional data on substrate or gradient. [ABSTRACT FROM AUTHOR]

Elephant seals are one of the most proficient diving mammals in the world and are also one of the most studied. However, their long periods at sea and pelagic habits make research into their foraging ecology particularly challenging. Most current understanding comes from the use of time-depth recorders (TDRs). We used TDRs that additionally recorded body pitch and roll on four juvenile southern elephant seals ( Mirounga leonina) foraging over the Patagonian Shelf to describe their diving behaviour and compared them with those of adults, using standard descriptions of elephant seal dive profile types provided by the literature. Over 280 days of diving data showed that dive types were similar to those of adults (types: A, B, C, D, E and E) but that dive types A and C differed slightly, probably because our animals were constrained by bottom topography. Steep dive and return-to-surface angles in all dive types except type B indicate that animals generally attempt to maximize vertical displacement. Horizontal displacement was much greater in type B dives, which indicates a travelling function. Pitching and rolling behaviour lends support to the functions ascribed to the dive types already described for adult elephant seals, although type E dives are unusual in that the animals appear to be taking prey by up-ending in the benthos. [ABSTRACT FROM AUTHOR]

Animals respond to environmental variation by exhibiting a number of different behaviours and/or rates of activity, which result in corresponding variation in energy expenditure. Successful animals generally maximize efficiency or rate of energy gain through foraging. Quantification of all features that modulate energy expenditure can theoretically be modelled as an animal energetic niche or power envelope; with total power being represented by the vertical axis and n-dimensional horizontal axes representing extents of processes that affect energy expenditure. Such an energetic niche could be used to assess the energetic consequences of animals adopting particular behaviours under various environmental conditions. This value of this approach was tested by constructing a simple mechanistic energetics model based on data collected from recording devices deployed on 41 free-living Magellanic penguins (Spheniscus magellanicus), foraging from four different colonies in Argentina and consequently catching four different types of prey. Energy expenditure was calculated as a function of total distance swum underwater (horizontal axis 1) and maximum depth reached (horizontal axis 2). The resultant power envelope was invariant, irrespective of colony location, but penguins from the different colonies tended to use different areas of the envelope. The different colony solutions appeared to represent particular behavioural options for exploiting the available prey and demonstrate how penguins respond to environmental circumstance (prey distribution), the energetic consequences that this has for them, and how this affects the balance of energy acquisition through foraging and expenditure strategy. [ABSTRACT FROM AUTHOR]

Blue mussels Mytilus edulis (n = 14) were studied in the laboratory using Hall sensor systems to record their gaping behaviour when exposed to varying food rations and levels of predation risk. Mussel response to increasing daily algal ration was to increase mean gape angle per day and was associated with copious pseudofaeces production at excessive initial algal concentrations, e.g. 250 cells/µl. Mean gape angle decreased (backward S-shaped curve) when fed a fixed algal ration per day where simulated predation risk (introduced fresh mussel homogenate) increased in the water, presumably as an anti-predation strategy. However, this behaviour is presumed to lower feeding rates. There was a general positive relationship between both gape angle and the extent of valve movement (abduction/adduction) per event and valve movement speed. However, the fastest valve adduction events, which resulted in valve closure, were recorded independent of gape angle and only when mussels were first exposed to high perceived predation risk. We interpret this as an appropriate response, with high energetic cost, as a first line of defence from predators such as starfish and crabs. Overall, mussel response to predation appears graded and complex, indicating a trade-off between maximizing feeding/pseudofaeces production and minimizing predation risk. [ABSTRACT FROM PUBLISHER]

A correction is presented to the article "Animal lifestyle affects acceptable mass limits for attached tags" which appeared in the 27 October 2021 issue.

Recent severe hurricanes in the Caribbean and south-east United States have had devastating socio-economic effects, and there is a pressing need to learn how animals are impacted by such events. We serendipitously deployed a multi-channel data logger onto a hawksbill turtle (Eretmochelys imbricata) during the breeding season in 1998 and logged various aspects of her behaviour before, during and after passage of hurricane Georges. As Georges passed by, the turtle made shorter dives, became more active and spent less time at the surface between dives compared with its baseline, non-storm activity. However, after passage of the hurricane the turtle quickly resumed its pre-hurricane behaviour and nested successfully a few days later. These results show that, in this case, the hurricane had a minor impact on the submerged animal presumably because of the dampening effect of depth on high winds over water. [ABSTRACT FROM AUTHOR]

1. Time and energy are key currencies in animal ecology, and judicious management of these is a primary focus for natural selection. At present, however, there are only two main methods for estimation of rate of energy expenditure in the field, heart rate and doubly labelled water, both of which have been used with success; but both also have their limitations. 2. The deployment of data loggers that measure acceleration is emerging as a powerful tool for quantifying the behaviour of free-living animals. Given that animal movement requires the use of energy, the accelerometry technique potentially has application in the quantification of rate of energy expenditure during activity. 3. In the present study, we test the hypothesis that acceleration can serve as a proxy for rate of energy expenditure in free-living animals. We measured rate of energy expenditure as rates of O2 consumption ( ) and CO2 production ( ) in great cormorants ( Phalacrocorax carbo) at rest and during pedestrian exercise. and were then related to overall dynamic body acceleration (ODBA) measured with an externally attached three-axis accelerometer. 4. Both and were significantly positively associated with ODBA in great cormorants. This suggests that accelerometric measurements of ODBA can be used to estimate and and, with some additional assumptions regarding metabolic substrate use and the energy equivalence of O2 and CO2, that ODBA can be used to estimate the activity specific rate of energy expenditure of free-living cormorants. 5. To verify that the approach identifies expected trends in from situations with variable power requirements, we measured ODBA in free-living imperial cormorants ( Phalacrocorax atriceps) during foraging trips. We compared ODBA during return and outward foraging flights, when birds are expected to be laden and not laden with captured fish, respectively. We also examined changes in ODBA during the descent phase of diving, when power requirements are predicted to decrease with depth due to changes in buoyancy associated with compression of plumage and respiratory air. 6. In free-living imperial cormorants, ODBA, and hence estimated , was higher during the return flight of a foraging bout, and decreased with depth during the descent phase of a dive, supporting the use of accelerometry for the determination of activity-specific rate of energy expenditure. [ABSTRACT FROM AUTHOR]

There is little information on the effort put into foraging by seabirds, even though it is fundamental to many issues in behavioural ecology. Recent researchers have used changes in the underwater cruising speed of penguins to allude to prey ingestion since accelerations are thought to reflect the encounter and pursuit of prey. In this study, we attached minute accelerometers, to determine flipper beat frequency as a proxy for prey pursuit, to Little Penguins Eudyptula minor foraging in shallow waters in Western Australia. During diving, Little Penguins flapped continuously and at a regular pace of 3.16 Hz while descending the water column and throughout the bottom phase of most dives. However, the frequency and amplitude of wingbeats increased transitorily, reaching 3.5–5.5 Hz, during some dives indicating prey pursuit. Pursuit phases lasted a mean of 2.9±3.3 s and occurred principally during the bottom phases of dives (75.4%). Most dives in all birds (86%) had a clear square-shaped depth profile indicating feeding activity near the seabed in the shallow waters of the bays. Hourly maximum depth, time spent underwater, percentage of dives with pursuit events and catch per unit effort showed an overall increase from zero at ca. 0500 h to a maximum during the hours around mid-day before decreasing to zero by 1900 h. During pursuit phases, Little Penguins headed predominantly downward, probably using the seabed to assist them in trapping their prey. In the light of our results, we discuss depth use by Little Penguins and their allocation of foraging effort and prey capture success as a function of environmental conditions. [ABSTRACT FROM AUTHOR]

Detailed studies of the behavior and location of free-ranging animals can be considerably enhanced with the use of animal-mounted devices. A few devices, such as data loggers, have to be recovered to access the data, whereas satellite tags or radiocollars often are left on the animal after the study period. Recovery of devices, which usually necessitates animal recapture, can be problematic, especially in larger species. This paper presents a new, non-electronic release mechanism, requiring no power source on the animal, that was successfully tested on South American sea lions (Otaria flavescens) in Argentina during the 2003-2004 austral summer. The system has potential for many larger terrestrial or aquatic animals. [ABSTRACT FROM AUTHOR]

Presents a study that examined the short underwater beak opening behavior of seven captive penguin species. Correlations between beak opening and the dive duration; Differences in the duration of beak opening in the different penguin species; Determination of beak opening following porpoising.

Studies the traveling behavior of the Magellanic Penguin. Swimming trajectories of the penguins; Comparison between the energy utilized by penguins when walking and swimming.

The article features the research conducted by C. Saraux and colleagues that investigates the impact of flipper bands on the survival and breeding of king penguins. Due to the efforts of biologists to track and to monitor the effects of climatic change and how they respond to the environment, biologist attached flipper bands to penguins. Researchers discovered that have adverse effects on penguins due to rubbing while swimming.

Abstract: This study was performed to assess the extent to which an intermandibular angle sensor (IMASEN) may be used to elucidate the behaviour of six captive loggerhead turtles. The measuring system was glued to the beak of turtles and set to measure the intermandibular distance at 5 Hz while the turtles fed (on anchovies, squid, and live crabs), swam, rested, and breathed. The behaviour of the equipped turtles was filmed and compared afterwards to the sensor readings. The IMASEN output data allowed quantification of the number of food items ingested as well as the time between food seizure and deglutition and the type of food ingested. However, nonfeeding turtles exhibited regular jaw movements with a reduced amplitude of ca. 2.2 mm, which clearly differed from feeding movements and were caused by buccal oscillations. Such movements of the base of the buccal cavity generate a steady flow of water pass the chemosensory organs and were interrupted only during food ingestion, resting, and breathing. Breathing was clearly distinguishable by the IMASEN. The beak sensor is thus a reliable system to investigate a number of behaviours in sea turtles which encompass foraging, buccal oscillation, and respiratory frequency. It has potential for allocating time to different activities in free-ranging sea turtles and thus allows us to gain insight to their foraging and diving strategies. [Copyright &y& Elsevier]