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.

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.

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.

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.

Flight paths of seabirds soaring over the ocean surface enable measurement of fine-scale wind speed and direction.

Ocean surface winds are an essential factor in understanding the physical interactions between the atmosphere and the ocean. Surface winds measured by satellite scatterometers and buoys cover most of the global ocean; however, there are still spatial and temporal gaps and finer-scale variations of wind that may be overlooked, particularly in coastal areas. Here, we show that flight paths of soaring seabirds can be used to estimate fine-scale (every 5 min, ∼5 km) ocean surface winds. Fine-scale global positioning system (GPS) positional data revealed that soaring seabirds flew tortuously and ground speed fluctuated presumably due to tail winds and head winds. Taking advantage of the ground speed difference in relation to flight direction, we reliably estimated wind speed and direction experienced by the birds. These bird-based wind velocities were significantly correlated with wind velocities estimated by satellite-borne scatterometers. Furthermore, extensive travel distances and flight duration of the seabirds enabled a wide range of high-resolution wind observations, especially in coastal areas. Our study suggests that seabirds provide a platform from which to measure ocean surface winds, potentially complementing conventional wind measurements by covering spatial and temporal measurement gaps.

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.

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.

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.

Environmental perturbations influence telomere dynamics in long-lived birds in their natural habitat.

Telomeres are regarded as markers of biological or cellular ageing because they shorten with the degree of stress exposure. Accordingly, telomere lengths should show different rates of change when animals are faced with different intensities of environmental challenges. However, a relationship between telomere length and the environment has not yet been tested within a natural setting. Here, we report longitudinal telomere dynamics in free-living, black-tailed gulls (Larus crassirostris) through the recapture of birds of a known age over 2-5 consecutive years. The rate of change in telomere lengths differed with respect to year but not sex or age. The years when gulls showed stable telomere lengths or increases in telomere lengths (from 2009 to 2010) and decreases in telomere lengths (from 2010 to 2011) were characterized by El Niño and the Great Japan Earthquake, respectively. Both events are suspected to have had long-lasting effects on food availability and/or weather conditions. Thus, our findings that telomere dynamics in long-lived birds are influenced by dramatic changes in environmental conditions highlight the importance of environmental fluctuations in affecting stress and lifespan.

Contaminants in tracked seabirds showing regional patterns of marine pollution.

Ocean-scale monitoring of pollution is challenging. Seabirds are useful indicators because they travel over a broad foraging range. Nevertheless, this coarse spatial resolution is not fine enough to discriminate pollution in a finer scale. Previous studies have demonstrated that pollution levels are higher in the Sea of Japan and South and East China Seas than the Northen Pacific Ocean. To test these findings in a wide-ranging animal, we tracked streaked shearwaters (Calonectris leucomelas) from four islands in Japan using global positioning system (GPS) and measured persistent organic pollutants (POPs) in the oil of their preen glands. The POPs did not change during 6 to 21 days when birds from Awashima were foraging only in the Sea of Japan, while it increased when they crossed to the Pacific through the Tsugaru Strait and foraged along the eastern coast of Hokkaido where industrial cities occur. These results indicate that POPs in the oil reflect relatively short-term exposure. Concentrations of POPs displayed greater variation among regions. Total polychlorinated biphenyls were highest in birds foraging in a small area of the semiclosed Seto Inland Sea surrounded by urbanized coast, p,p'-dichlorodiphenyltrichloroethane (DDT) was highest in birds foraging in the East China Sea, and total hexachlorocyclohexanes were highest in birds foraging in the Sea of Japan. All were lowest in birds foraging in the Pacific. This distribution of POPs concentration partly agrees with previous findings based on mussels, fish, and seawater and possibly reflects the mobility and emission sources of each type of POP. These results highlight the importance of information on the foraging area of highly mobile top predators to make them more effective monitors of regional marine pollution.

Variation in the production rate of biosonar signals in freshwater porpoises.

The biosonar (click train) production rate of ten Yangtze finless porpoises and their behavior were examined using animal-borne data loggers. The sound production rate varied from 0 to 290 click trains per 10-min time interval. Large individual differences were observed, regardless of body size. Taken together, however, sound production did not differ significantly between daytime and nighttime. Over the 172.5 h of analyzed recordings, an average of 99.0% of the click trains were produced within intervals of less than 60 s, indicating that during a 1-min interval, the number of click trains produced by each porpoise was typically greater than one. Most of the porpoises exhibited differences in average swimming speed and depth between day and night. Swimming speed reductions and usage of short-range sonar, which relates to prey-capture attempts, were observed more often during nighttime. However, biosonar appears to be affected not only by porpoise foraging, but also by their sensory environment, i.e., the turbid Yangtze River system. These features will be useful for passive acoustic detection of the porpoises. Calculations of porpoise density or abundance should be conducted carefully because large individual differences in the sound production rate will lead to large estimation error.

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.

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.

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.

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.

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.

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.

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.

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.