Albatrosses employ orientation and routing strategies similar to yacht racers.

The way goal-oriented birds adjust their travel direction and route in response to wind significantly affects their travel costs. This is expected to be particularly pronounced in pelagic seabirds, which utilize a wind-dependent flight style called dynamic soaring. Dynamic soaring seabirds in situations without a definite goal, e.g. searching for prey, are known to preferentially fly with crosswinds or quartering-tailwinds to increase the speed and search area, and reduce travel costs. However, little is known about their reaction to wind when heading to a definite goal, such as homing. Homing tracks of wandering albatrosses (Diomedea exulans) vary from beelines to zigzags, which are similar to those of sailboats. Here, given that both albatrosses and sailboats travel slower in headwinds and tailwinds, we tested whether the time-minimizing strategies used by yacht racers can be compared to the locomotion patterns of wandering albatrosses. We predicted that when the goal is located upwind or downwind, albatrosses should deviate their travel directions from the goal on the mesoscale and increase the number of turns on the macroscale. Both hypotheses were supported by track data from albatrosses and racing yachts in the Southern Ocean confirming that albatrosses qualitatively employ the same strategy as yacht racers. Nevertheless, albatrosses did not strictly minimize their travel time, likely making their flight robust against wind fluctuations to reduce flight costs. Our study provides empirical evidence of tacking in albatrosses and demonstrates that man-made movement strategies provide a new perspective on the laws underlying wildlife movement.

Automatic recording of rare behaviors of wild animals using video bio-loggers with on-board light-weight outlier detector.

Rare behaviors displayed by wild animals can generate new hypotheses; however, observing such behaviors may be challenging. While recent technological advancements, such as bio-loggers, may assist in documenting rare behaviors, the limited running time of battery-powered bio-loggers is insufficient to record rare behaviors when employing high-cost sensors (e.g. video cameras). In this study, we propose an artificial intelligence (AI)-enabled bio-logger that automatically detects outlier readings from always-on low-cost sensors, e.g. accelerometers, indicative of rare behaviors in target animals, without supervision by researchers, subsequently activating high-cost sensors to record only these behaviors. We implemented an on-board outlier detector via knowledge distillation by building a lightweight outlier classifier supervised by a high-cost outlier behavior detector trained in an unsupervised manner. The efficacy of AI bio-loggers has been demonstrated on seabirds, where videos and sensor data captured by the bio-loggers have enabled the identification of some rare behaviors, facilitating analyses of their frequency, and potential factors underlying these behaviors. This approach offers a means of documenting previously overlooked rare behaviors, augmenting our understanding of animal behavior.

Low-cost thermoregulation of wild sloths revealed by heart rate and temperature loggers.

Arboreal herbivores require large digestive tracts for leaf fermentation and detoxification; however, they must also have a low body mass that allows them to reach the foliage. The three-toed sloth, Bradypus tridactylus, experiences this trade-off, as leaves comprise 97.2% of its diet. Their calorie intake is extremely low owing to the low available caloric density of leaves and slow digestive processes related to leaf fibre fermentation and secondary compound detoxification. Sloths may require a high body temperature to assist fermentation; however, thermogenesis is energy-consuming. To investigate how sloths accomplish thermoregulation using marginal energy, we attached heart rate (HR) and temperature loggers to wild B. tridactylus individuals inhabiting the Amazon rainforest and recorded their HR and body surface temperature (Tskin). Tskin changed with ambient temperature (Ta) but was higher than Ta in 99.2% of cases. Increases in Tskin and HR did not coincide, suggesting that the increases were not caused by thermogenesis. Instead, they may passively increase Tskin by selecting warmer microhabitats and sunbathing. Consequently, 90.5% of Tskin were within 27.6-36.0 °C while the Ta fluctuated between 21.5 and 42.9 °C. This low-cost thermoregulation results in a low HR. In this study, the mean HR during observation was approximately 38.4% of the expected value based on the mammalian allometric relationship between body mass and HR. Thus, these properties may contribute to the low metabolic rates of sloths, alleviating their restricted energy intake.

Pelagic seabirds reduce risk by flying into the eye of the storm.

Cyclones can cause mass mortality of seabirds, sometimes wrecking thousands of individuals. The few studies to track pelagic seabirds during cyclones show they tend to circumnavigate the strongest winds. We tracked adult shearwaters in the Sea of Japan over 11 y and found that the response to cyclones varied according to the wind speed and direction. In strong winds, birds that were sandwiched between the storm and mainland Japan flew away from land and toward the eye of the storm, flying within ≤30 km of the eye and tracking it for up to 8 h. This exposed shearwaters to some of the highest wind speeds near the eye wall (≤21 m s-1) but enabled them to avoid strong onshore winds in the storm's wake. Extreme winds may therefore become a threat when an inability to compensate for drift could lead to forced landings and collisions. Birds may need to know where land is in order to avoid it. This provides additional selective pressure for a map sense and could explain why juvenile shearwaters, which lack a map sense, instead navigating using a compass heading, are susceptible to being wrecked. We suggest that the ability to respond to storms is influenced by both flight and navigational capacities. This may become increasingly pertinent due to changes in extreme weather patterns.

The role of wingbeat frequency and amplitude in flight power.

Body-mounted accelerometers provide a new prospect for estimating power use in flying birds, as the signal varies with the two major kinematic determinants of aerodynamic power: wingbeat frequency and amplitude. Yet wingbeat frequency is sometimes used as a proxy for power output in isolation. There is, therefore, a need to understand which kinematic parameter birds vary and whether this is predicted by flight mode (e.g. accelerating, ascending/descending flight), speed or morphology. We investigate this using high-frequency acceleration data from (i) 14 species flying in the wild, (ii) two species flying in controlled conditions in a wind tunnel and (iii) a review of experimental and field studies. While wingbeat frequency and amplitude were positively correlated, R2 values were generally low, supporting the idea that parameters can vary independently. Indeed, birds were more likely to modulate wingbeat amplitude for more energy-demanding flight modes, including climbing and take-off. Nonetheless, the striking variability, even within species and flight types, highlights the complexity of describing the kinematic relationships, which appear sensitive to both the biological and physical context. Notwithstanding this, acceleration metrics that incorporate both kinematic parameters should be more robust proxies for power than wingbeat frequency alone.

Head direction cells in a migratory bird prefer north.

Animals exhibit remarkable navigation abilities as if they have an internal compass. Head direction (HD) cells encoding the animal's heading azimuth are found in the brain of several animal species; the HD cell signals are dependent on the vestibular nuclei, where magnetic responsive cells are present in birds. However, it is difficult to determine whether HD cell signals drive the compass orientation in animals, as they do not necessarily rely on the magnetic compass under all circumstances. Recording of HD cell activities from the medial pallium of shearwater chicks (Calonectris leucomelas) just before their first migration, during which they strongly rely on compass orientation, revealed that shearwater HD cells prefer a north orientation. The preference remained stable regardless of geolocations and environmental cues, suggesting the existence of a magnetic compass regulated by internally generated HD signals. Our findings provide insight into the integration of the direction and magnetoreception senses.

How did extinct giant birds and pterosaurs fly? A comprehensive modeling approach to evaluate soaring performance.

The largest extinct volant birds (Pelagornis sandersi and Argentavis magnificens) and pterosaurs (Pteranodon and Quetzalcoatlus) are thought to have used wind-dependent soaring flight, similar to modern large birds. There are 2 types of soaring: thermal soaring, used by condors and frigatebirds, which involves the use of updrafts to ascend and then glide horizontally; and dynamic soaring, used by albatrosses, which involves the use of wind speed differences with height above the sea surface. Previous studies have suggested that P. sandersi used dynamic soaring, while A. magnificens and Quetzalcoatlus used thermal soaring. For Pteranodon, there is debate over whether they used dynamic or thermal soaring. However, the performance and wind speed requirements of dynamic and thermal soaring for these species have not yet been quantified comprehensively. We quantified these values using aerodynamic models and compared them with that of extant birds. For dynamic soaring, we quantified maximum travel speeds and maximum upwind speeds. For thermal soaring, we quantified the animal's sinking speed circling at a given radius and how far it could glide losing a given height. Our results confirmed those from previous studies that A. magnificens and Pteranodon used thermal soaring. Conversely, the results for P. sandersi and Quetzalcoatlus were contrary to those from previous studies. P. sandersi used thermal soaring, and Quetzalcoatlus had a poor ability both in dynamic and thermal soaring. Our results demonstrate the need for comprehensive assessments of performance and required wind conditions when estimating soaring styles of extinct flying species.

How often should dead-reckoned animal movement paths be corrected for drift?

BACKGROUND: Understanding what animals do in time and space is important for a range of ecological questions, however accurate estimates of how animals use space is challenging. Within the use of animal-attached tags, radio telemetry (including the Global Positioning System, 'GPS') is typically used to verify an animal's location periodically. Straight lines are typically drawn between these 'Verified Positions' ('VPs') so the interpolation of space-use is limited by the temporal and spatial resolution of the system's measurement. As such, parameters such as route-taken and distance travelled can be poorly represented when using VP systems alone. Dead-reckoning has been suggested as a technique to improve the accuracy and resolution of reconstructed movement paths, whilst maximising battery life of VP systems. This typically involves deriving travel vectors from motion sensor systems and periodically correcting path dimensions for drift with simultaneously deployed VP systems. How often paths should be corrected for drift, however, has remained unclear. METHODS AND RESULTS: Here, we review the utility of dead-reckoning across four contrasting model species using different forms of locomotion (the African lion Panthera leo, the red-tailed tropicbird Phaethon rubricauda, the Magellanic penguin Spheniscus magellanicus, and the imperial cormorant Leucocarbo atriceps). Simulations were performed to examine the extent of dead-reckoning error, relative to VPs, as a function of Verified Position correction (VP correction) rate and the effect of this on estimates of distance moved. Dead-reckoning error was greatest for animals travelling within air and water. We demonstrate how sources of measurement error can arise within VP-corrected dead-reckoned tracks and propose advancements to this procedure to maximise dead-reckoning accuracy. CONCLUSIONS: We review the utility of VP-corrected dead-reckoning according to movement type and consider a range of ecological questions that would benefit from dead-reckoning, primarily concerning animal-barrier interactions and foraging strategies.

Exhausted with foraging: Foraging behavior is related to oxidative stress in chick-rearing seabirds.

To understand foraging strategies and behavioral flexibility in wild animals, it is important to evaluate the physiological costs imposed by foraging efforts and how these costs affect foraging and provisioning behavior. Oxidative stress is a possible physiological indicator associated with foraging behavior in wild seabirds, and may also affect their reproductive performance. However, no previous study has simultaneously recorded foraging behavior and the associated oxidative stress in wild seabirds. Using an integrative approach based on oxidative stress measurements and bio-logging techniques (i.e., the use of animal-borne sensors), we determined the relationships between foraging behavior and oxidative stress in chick-rearing streaked shearwaters Calonectris leucomelas in 2018 and 2019. To quantify their oxidative stress, we measured reactive oxygen metabolites (d-ROMs) and biological antioxidant potential (BAP) in their plasma. We found that the d-ROMs levels were positively related to the maximum distance from the colony and the number of takeoffs, especially in 2019 when shearwaters flew further to forage. In 2018, when they flew relatively short distances, the BAP levels were positively related to the levels of their physical activity (overall dynamic body acceleration; ODBA). We conclude that longer and less successful foraging may lead to increase oxidative stress, while successful foraging may mitigate the oxidative stress of foraging by providing dietary antioxidants. Our results highlight that the combined data from bio-logging and oxidative stress measurements aid in evaluating the underlying physiological costs of foraging behavior in wild animals.

Mapping marine debris encountered by albatrosses tracked over oceanic waters.

Anthropogenic marine debris is a threat to marine organisms. Understanding how this debris spatially distributes at sea and may become associated with marine wildlife are key steps to tackle this current issue. Using bird-borne GPS- and video-loggers on 13 black-footed albatrosses Phoebastria nigripes breeding in Torishima, Japan, we examined the distribution of large floating debris in the Kuroshio Current area, western North Pacific. A total of 16 floating debris, including styrofoam (n = 4), plastic pieces (n = 3), plastic sheet (n = 1), fishery-related items (rope or netting, n = 4), and unidentified debris (n = 4), were recorded across the 9003 km covered by nine birds. The debris was concentrated in the southern area of the Kuroshio Current, where the surface current was weak, and the albatrosses were foraging. The albatrosses displayed changes in flight direction towards the debris when at a mean distance of 4.9 km, similarly to when approaching prey, and one bird was observed pecking at a plastic sheet; indicating that albatrosses actively interacted with the debris. This paper shows the usefulness of studying wide-ranging marine predators through the use of combined biologging tools, and highlights areas with increased risk of debris exposure and behavioral responses to debris items.

Machine learning enables improved runtime and precision for bio-loggers on seabirds.

Unravelling the secrets of wild animals is one of the biggest challenges in ecology, with bio-logging (i.e., the use of animal-borne loggers or bio-loggers) playing a pivotal role in tackling this challenge. Bio-logging allows us to observe many aspects of animals' lives, including their behaviours, physiology, social interactions, and external environment. However, bio-loggers have short runtimes when collecting data from resource-intensive (high-cost) sensors. This study proposes using AI on board video-loggers in order to use low-cost sensors (e.g., accelerometers) to automatically detect and record complex target behaviours that are of interest, reserving their devices' limited resources for just those moments. We demonstrate our method on bio-loggers attached to seabirds including gulls and shearwaters, where it captured target videos with 15 times the precision of a baseline periodic-sampling method. Our work will provide motivation for more widespread adoption of AI in bio-loggers, helping us to shed light onto until now hidden aspects of animals' lives.

Deep learning-assisted comparative analysis of animal trajectories with DeepHL.

A comparative analysis of animal behavior (e.g., male vs. female groups) has been widely used to elucidate behavior specific to one group since pre-Darwinian times. However, big data generated by new sensing technologies, e.g., GPS, makes it difficult for them to contrast group differences manually. This study introduces DeepHL, a deep learning-assisted platform for the comparative analysis of animal movement data, i.e., trajectories. This software uses a deep neural network based on an attention mechanism to automatically detect segments in trajectories that are characteristic of one group. It then highlights these segments in visualized trajectories, enabling biologists to focus on these segments, and helps them reveal the underlying meaning of the highlighted segments to facilitate formulating new hypotheses. We tested the platform on a variety of trajectories of worms, insects, mice, bears, and seabirds across a scale from millimeters to hundreds of kilometers, revealing new movement features of these animals.

STEFTR: A Hybrid Versatile Method for State Estimation and Feature Extraction From the Trajectory of Animal Behavior.

Animal behavior is the final and integrated output of brain activity. Thus, recording and analyzing behavior is critical to understand the underlying brain function. While recording animal behavior has become easier than ever with the development of compact and inexpensive devices, detailed behavioral data analysis requires sufficient prior knowledge and/or high content data such as video images of animal postures, which makes it difficult for most of the animal behavioral data to be efficiently analyzed. Here, we report a versatile method using a hybrid supervised/unsupervised machine learning approach for behavioral state estimation and feature extraction (STEFTR) only from low-content animal trajectory data. To demonstrate the effectiveness of the proposed method, we analyzed trajectory data of worms, fruit flies, rats, and bats in the laboratories, and penguins and flying seabirds in the wild, which were recorded with various methods and span a wide range of spatiotemporal scales-from mm to 1,000 km in space and from sub-seconds to days in time. We successfully estimated several states during behavior and comprehensively extracted characteristic features from a behavioral state and/or a specific experimental condition. Physiological and genetic experiments in worms revealed that the extracted behavioral features reflected specific neural or gene activities. Thus, our method provides a versatile and unbiased way to extract behavioral features from simple trajectory data to understand brain function.

Female-biased stranding in Magellanic penguins.

Magellanic penguins (Spheniscus magellanicus) have been reported to become stranded along the coasts of northern Argentina, Uruguay and southern Brazil during the austral winter [1-3]. This location is more than a thousand kilometers distant from their northernmost breeding colony in northern Patagonia. Curiously, females typically outnumber males at stranding sites (approximately three females per male) [2]. To date, no conspicuous sex differences have been reported in their migratory movements [3], although records are lacking during the peak stranding season. Consequently, the reason(s) for the female-biased stranding remain unknown, despite the growing necessity for understanding their behavior outside the breeding season [3]. We recorded at-sea distributions of Magellanic penguins throughout the non-breeding period using animal-borne data loggers and found that females reached more northern areas than males and did not dive as deep during winter (Figure 1). Such sexual differences in spatial domains might be driven by mechanisms related to sexual size dimorphism, such as the avoidance of intraspecific competition for food resources [4], differences in thermal habitat preference [5] or differences in the ability to withstand the northward-flowing ocean circulation [6]. Individual penguins that winter in northern areas are likely to be at greater risk of natural [7] and anthropogenic threats [8], and probably more so in females, as more females than males tend to frequent areas closer to the sites where penguins strand. Our results highlight the importance of understanding the spatial domains of each sex throughout the annual cycle that are associated with different mortality risks.

Individual differences in heart rate reveal a broad range of autonomic phenotypes in a free-living seabird population.

Animals in the same population consistently differ in their physiology and behaviour, but the underlying mechanisms remain poorly understood. As the autonomic nervous system regulates wide-ranging physiological functions, many of these phenotypic differences may be generated by autonomic activity. We investigated for the first time in a free-living animal population (the streaked shearwater, Calonectris leucomelas, a long-lived seabird) whether individuals consistently differ in autonomic activity, over time and across contexts. We repeatedly recorded electrocardiograms from individual shearwaters, and from heart rate and heart rate variability quantified sympathetic activity, which drives the 'fight-or-flight' response, and parasympathetic activity, which promotes 'rest-and-digest' processes. We found a broad range of autonomic phenotypes that persisted even across years: heart rate consistently differed among individuals during periods of stress and non-stress and these differences were driven by parasympathetic activity, thus identifying the parasympathetic rest-and-digest system as a central mechanism that can drive broad phenotypic variation in natural animal populations.

Compass orientation drives naïve pelagic seabirds to cross mountain ranges.

Wildlife migration is a spectacular phenomenon [1]. Studies using telemetry - tracking devices attached on free-living animals - have shown that large topographic barriers and obstacles, such as oceans and deserts, elicit extreme feats of migration [2]. Overcoming the challenges of these obstacles might require experience and skill that young individuals lack [2-5]. Further, younger, inexperienced animals might determine their migration routes using navigation strategies different from those of older animals [6-9], but our knowledge of how orientation mechanisms and experience drive migration strategy is limited. We have studied how experienced (adults) and inexperienced (first-time migrating fledglings) streaked shearwaters (Calonectris leucomelas) approach the challenge of migration using animal-borne tracking devices. The study birds migrate from a colony on the north of a large topographic barrier, Honshu Island, Japan. Shearwaters use a wind- and wave-based flight pattern-dynamic soaring-to extract energy for highly efficient travel over oceans [10]. We therefore expected that shearwaters migrating southward from the colony would make substantial detours to avoid any landmasses. We found that migrating adults followed one of two paths that detour around landmasses that hinder direct southerly migration. In contrast, inexperienced fledglings followed a straight course in a south-oriented direction that forced them to complete a trans-mountain journey, suggesting that the birds rely on an innate compass. Thus, we suggest that fledglings would eventually override the simple compass navigation, which appears to be the primary driver for their extreme migration, before being able to interact appropriately with the marine environment.

Asymmetry hidden in birds' tracks reveals wind, heading, and orientation ability over the ocean.

Numerous flying and swimming animals constantly need to control their heading (that is, their direction of orientation) in a flow to reach their distant destination. However, animal orientation in a flow has yet to be satisfactorily explained because it is difficult to directly measure animal heading and flow. We constructed a new animal movement model based on the asymmetric distribution of the GPS (Global Positioning System) track vector along its mean vector, which might be caused by wind flow. This statistical model enabled us to simultaneously estimate animal heading (navigational decision-making) and ocean wind information over the range traversed by free-ranging birds. We applied this method to the tracking data of homing seabirds. The wind flow estimated by the model was consistent with the spatiotemporally coarse wind information provided by an atmospheric simulation model. The estimated heading information revealed that homing seabirds could head in a direction different from that leading to the colony to offset wind effects and to enable them to eventually move in the direction they intended to take, even though they are over the open sea where visual cues are unavailable. Our results highlight the utility of combining large data sets of animal movements with the "inverse problem approach," enabling unobservable causal factors to be estimated from the observed output data. This approach potentially initiates a new era of analyzing animal decision-making in the field.

Heart rate variability reveals that a decrease in parasympathetic ('rest-and-digest') activity dominates autonomic stress responses in a free-living seabird.

The autonomic stress response, often referred to as the 'fight-or-flight' response, is a highly conserved physiological reaction to stress in vertebrates that occurs via a decrease in parasympathetic (PNS) activity, which promotes self-maintenance 'rest and digest' processes, and an increase in sympathetic (SNS) activity, which prepares an animal for danger ('fight-or-flight'). Though the PNS and SNS both innervate most organs, they often control different tissues and functions within those organs (though the pacemaker of the heart is controlled by both). Moreover the PNS and SNS are regulated independently. Yet until now, most studies of autonomic stress responses in non-model species focused only on the SNS response. We used external electrocardiogram loggers to measure heart rate and heart rate variability indexes that reflect PNS and SNS activity in a seabird, the Streaked Shearwater (Calonectris leucomelas), during the stress of handling, and during recovery in the nest burrow or during restraint in a cloth bag. We show for the first time in a free-living animal that the autonomic stress response is mediated primarily by a rapid decrease in PNS activity: handling stress induced a large and long-lasting depression of PNS 'rest-and-digest' activity that required two hours to recover. We also found evidence for a substantially smaller and shorter-lasting SNS 'fight-or-flight' response. Confinement in a cloth bag was less stressful for birds than handling, but more stressful than recovering in nest burrows. We show that quantifying autonomic activity from heart rate variability is effective for non-invasively studying stress physiology in free-living animals.

How Do Growth and Sibling Competition Affect Telomere Dynamics in the First Month of Life of Long-Lived Seabird?

Telomeres are nucleotide sequences located at the ends of chromosomes that promote genome stability. Changes in telomere length (dynamics) are related to fitness or life expectancy, and telomere dynamics during the development phase are likely to be affected by growth and stress factors. Here, we examined telomere dynamics of black-tailed gull chicks (Larus crassirostris) in nests with and without siblings. We found that the initial telomere lengths of singletons at hatching were longer than those of siblings, indicating that singletons are higher-quality chicks than siblings in terms of telomere length. Other factors likely affecting individual quality (i.e., sex, laying date, laying order of eggs, and clutch size) were not related to telomere lengths. Within broods, initial telomere lengths were longer in older chicks than in younger chicks, suggesting that maternal effects, which vary with laying sequence, influence the initial lengths. Additionally, telomeres of chicks with a sibling showed more attrition between hatching and fledging than those of singleton chicks, suggesting that being raised with siblings can cause a sustained competitive environment that leads to telomere loss. High growth rates were associated with a low degree of telomere shortening observed in older siblings, perhaps because slower growth reflects higher food stress and/or higher aerobic metabolism from increased begging effort. Our results show that developmental telomere attrition was an inevitable consequence in two-chick nests in the pre- and post-hatching microenvironments due to the combination of social stress within the nest and maternal effects. The results of our study shed light on telomere dynamics in early life, which may represent an important physiological undercurrent of life-history traits.