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Female Weddell seals (Leptonychotes weddellii) display a mixed capital-income breeding strategy, losing up to 40% of their body mass between birthing and weaning their pups. How and when they regain energy stores, however, remains to be fully explored. To better understand the foraging by lactating Weddell seals, we fitted time-depth recorders and head-mounted cameras on 26 seals in Erebus Bay, Ross Sea, for ~ 5 days in November and December 2018 and 2019. We aimed to (1) identify prey species and foraging depth and (2) investigate relationships between seal physiology and demographics and probability of foraging. We recorded 2782 dives, 903 of which were > 50 m, maximum depth was 449.3 m and maximum duration was 31.1 min. Pup age likely contributes to the probability of a lactating Weddell seal foraging (Est. = 1.21 (SD = 0.61), z = 1.97, p = 0.0484). Among 846 prey encounters, the most frequent prey items were crustaceans (46.2%) and Antarctic silverfish (Pleuragramma antarcticum, 19.0%); two encounters were observed with juvenile Antarctic toothfish (Dissostichus mawsoni, 0.2%). We identified substantial variability in foraging behaviour, individually and between locations, and found that lactating seals target many species and some may specialise on certain prey groups.

Female Weddell seals (Leptonychotes weddellii) display a mixed capital-income breeding strategy, losing up to 40% of their body mass between birthing and weaning their pups. How and when they regain energy stores, however, remains to be fully explored. To better understand the foraging by lactating Weddell seals, we fitted time-depth recorders and head-mounted cameras on 26 seals in Erebus Bay, Ross Sea, for ~ 5 days in November and December 2018 and 2019. We aimed to (1) identify prey species and foraging depth and (2) investigate relationships between seal physiology and demographics and probability of foraging. We recorded 2782 dives, 903 of which were > 50 m, maximum depth was 449.3 m and maximum duration was 31.1 min. Pup age likely contributes to the probability of a lactating Weddell seal foraging (Est. = 1.21 (SD = 0.61), z = 1.97, p = 0.0484). Among 846 prey encounters, the most frequent prey items were crustaceans (46.2%) and Antarctic silverfish (Pleuragramma antarcticum, 19.0%); two encounters were observed with juvenile Antarctic toothfish (Dissostichus mawsoni, 0.2%). We identified substantial variability in foraging behaviour, individually and between locations, and found that lactating seals target many species and some may specialise on certain prey groups. [ABSTRACT FROM AUTHOR]

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Bio‐logging has revealed much about high‐latitude seabird migratory strategies, but migratory behaviour in tropical species may differ, with implications for understanding nutrient deposition. Here we use combined light‐level and saltwater immersion loggers to study the year‐round movement behaviour of adult red‐footed boobies Sula sula rubripes from the Chagos Archipelago, tropical Indian Ocean, to assess migratory movements and estimate nutrient deposition rates based on the number of days they spent ashore. Light levels suggest that red‐footed boobies are resident in the Chagos Archipelago year‐round, although there are large latitudinal errors this close to the equator. Immersion data also indicate residency with tracked birds returning to land every one or two days. Spending an average of 79.86 ± 2.80 days and 280.84 ± 2.64 nights per year on land allows us to estimate that the 21 670 pairs of red‐footed boobies deposit 37.34 ± 0.56 tonnes year−1 of guano‐derived nitrogen throughout the archipelago. Our findings have implications for tropical seabird conservation and phylogenetics, as well as for assessing the impact of seabird nutrients on coral reef ecosystems. [ABSTRACT FROM AUTHOR]

Abstract The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data. Currently, the common practice is to ignore such segments during model training. In this paper we tested the hypothesis that including mixed segments in model training will improve accuracy, as the model would perform better in identifying them in the test data. We test this hypothesis using a series of data simulations on four datasets of accelerometer data coupled with behaviour observations, obtained from four study species (Damaraland mole-rats, meerkats, olive baboons, polar bears). Results show that when a substantial proportion of the test data are mixed behaviour segments (above ~ 10%), including mixed segments in machine learning model training improves the accuracy of classification. These results were consistent across the four study species, and robust to changes in segment length, sample size, and degree of mixture within the mixed segments. However, we also find that in some cases (particularly in baboons) models trained with mixed segments show reduced accuracy in classifying test data containing only single behaviour (pure) segments, compared to models trained without mixed segments. Based on these results, we recommend that when the classification model is expected to deal with a substantial proportion of mixed behaviour segments (> 10%), it is beneficial to include them in model training, otherwise, it is unnecessary but also not harmful. The exception is when there is a basis to assume that the training data contains a higher rate of mixed segments than the actual (unobserved) data to be classified—such a situation may occur particularly when training data are collected in captivity and used to classify data from the wild. In this case, excess inclusion of mixed segments in training data should probably be avoided.

The spatial use of habitat is key to understanding the ecology of animals and their area requirements. In the current study, the locations of 11 wild pale-throated three-toed sloths (Bradypus tridactylus) were tracked using GPS loggers across 92 days in a 776 ha forest fragment in the central Amazon. Although male home ranges were slightly smaller than those of females, there were no significant differences in size or its expansion patterns. For nine of 11 individuals, home range size reached a plateau within 45 days of study start, indicating that 45 days can be the basal minimum days to establish the home range size of B. tridactylus. There was a negative relationship between body mass and home range size in our study. This counterintuitive result may be caused by disparities in the food-exploring abilities between individuals. Smaller and presumably younger individuals, who have less experience, may require more time and a larger area in which to search for food, while older and more experienced individuals may be able to find food efficiently in a smaller area. Further work on the distribution of food plants and the food-exploring pattern of each animal in relation to age and/or size is thus encouraged. [ABSTRACT FROM AUTHOR]

A wide variety of attachment techniques have been used to track birds with electronic tags, with glue, tape, leg rings, neck collars and harnesses being the most common methods. In general, the choice of attachment method should strive to minimize tagging effects, but ensure that sufficient data are collected to address the research question at hand. The aim of our study was to develop and evaluate tag attachment methods to track Sandwich Terns Thalasseus sandvicensis during the last part of the incubation and the chick‐rearing period of one breeding season. Tag attachments had to stay on for the duration of the chick‐rearing period (5–6 weeks) and be non‐restraining and flexible, but strong enough to withstand the forces and submersion associated with their plunge‐diving foraging technique. We first experimentally tested the durability of flexible material under various environmental conditions with the aim of developing a self‐releasing harness. Then, in field studies, we compared three different attachment methods on terns during the breeding seasons, attaching tags to dorsal feathers using (1) tape, (2) glue or (3) a newly developed harness made specifically for short‐term deployments of one chick‐rearing period and constructed from degradable material. Assessment of the performance of attachment methods was based on retention time of the loggers and on annual survival rates of tagged individuals in comparison with non‐tagged individuals. The use of tape and glue led to premature loss of tags (median minimum retention time (range) of 3 (1–4) days and 15 (5–26) days, respectively), whereas the self‐releasing harness had a median minimum retention time of 42 (18–91) days, which is sufficient to track Sandwich Terns during the entire chick‐rearing period. The apparent annual survival of birds tagged using glue or tape did not differ from that observed in non‐tagged control birds. In contrast, birds fitted with the self‐releasing harnesses might have experienced a lower survival rate than control birds. Entanglement of birds in the harness material was incidentally observed in three cases, which may have contributed to the lower survival rates observed in this group. The risk of entanglement can potentially be mitigated with a leg‐loop harness instead of a full‐body harness. Our results highlight the necessity of careful consideration when selecting appropriate attachment methods. Specifically, there is a need to address whether the research questions and desired tracking duration justify the use of a harness and the higher impact that it entails, or whether a tape or glue‐mount is sufficient. More broadly, sharing field expertise in tag attachments across studies is essential to successful deployments while minimizing the impact on animals. [ABSTRACT FROM AUTHOR]

The application of supervised machine learning methods to identify behavioural modes from inertial measurements of bio-loggers has become a standard tool in behavioural ecology. Several design choices can affect the accuracy of identifying the behavioural modes. One such choice is the inclusion or exclusion of segments consisting of more than a single behaviour (mixed segments) in the machine learning model training data. Currently, the common practice is to ignore such segments during model training. In this paper we tested the hypothesis that including mixed segments in model training will improve accuracy, as the model would perform better in identifying them in the test data. We test this hypothesis using a series of data simulations on four datasets of accelerometer data coupled with behaviour observations, obtained from four study species (Damaraland mole-rats, meerkats, olive baboons, polar bears). Results show that when a substantial proportion of the test data are mixed behaviour segments (above ~ 10%), including mixed segments in machine learning model training improves the accuracy of classification. These results were consistent across the four study species, and robust to changes in segment length, sample size, and degree of mixture within the mixed segments. However, we also find that in some cases (particularly in baboons) models trained with mixed segments show reduced accuracy in classifying test data containing only single behaviour (pure) segments, compared to models trained without mixed segments. Based on these results, we recommend that when the classification model is expected to deal with a substantial proportion of mixed behaviour segments (> 10%), it is beneficial to include them in model training, otherwise, it is unnecessary but also not harmful. The exception is when there is a basis to assume that the training data contains a higher rate of mixed segments than the actual (unobserved) data to be classified—such a situation may occur particularly when training data are collected in captivity and used to classify data from the wild. In this case, excess inclusion of mixed segments in training data should probably be avoided. [ABSTRACT FROM AUTHOR]

The heterogeneity of the physical environment determines the cost of transport for animals, shaping their energy landscape. Animals respond to this energy landscape by adjusting their distribution and movement to maximize gains and reduce costs. Much of our knowledge about energy landscape dynamics focuses on factors external to the animal, particularly the spatio-temporal variations of the environment. However, an animal’s internal state can significantly impact its ability to perceive and utilize available energy, creating a distinction between the ‘fundamental’ and the ‘realized’ energy landscapes. Here, we show that the realized energy landscape varies along the ontogenetic axis. Locomotor and cognitive capabilities of individuals change over time, especially during the early life stages. We investigate the development of the realized energy landscape in the Central European Alpine population of the golden eagle Aquila chrysaetos, a large predator that requires negotiating the atmospheric environment to achieve energy-efficient soaring flight. We quantified weekly energy landscapes using environmental features for 55 juvenile golden eagles, demonstrating that energetic costs of traversing the landscape decreased with age. Consequently, the potentially flyable area within the Alpine region increased 2170-fold during their first three years of independence. Our work contributes to a predictive understanding of animal movement by presenting ontogeny as a mechanism shaping the realized energy landscape.

Density-dependent competition for food influences the foraging behaviour and demography of colonial animals, but how this influence varies across a species’ latitudinal range is poorly understood. Here we used satellite tracking from 21 Northern Gannet Morus bassanus colonies (39% of colonies worldwide, supporting 73% of the global population) during chick-rearing to test how foraging trip characteristics (distance and duration) covary with colony size (138–60 953 breeding pairs) and latitude across 89% of their latitudinal range (46.81–71.23° N). Tracking data for 1118 individuals showed that foraging trip duration and maximum distance both increased with square-root colony size. Foraging effort also varied between years for the same colony, consistent with a link to environmental variability. Trip duration and maximum distance also decreased with latitude, after controlling for colony size. Our results are consistent with density-dependent reduction in prey availability influencing colony size and reveal reduced competition at the poleward range margin. This provides a mechanism for rapid population growth at northern colonies and, therefore, a poleward shift in response to environmental change. Further work is required to understand when and how colonial animals deplete nearby prey, along with the positive and negative effects of social foraging behaviour.

Bio‐logging has revealed much about high‐latitude seabird migratory strategies, but migratory behaviour in tropical species may differ, with implications for understanding nutrient deposition. Here we use combined light‐level and saltwater immersion loggers to study the year‐round movement behaviour of adult red‐footed boobies Sula sula rubripes from the Chagos Archipelago, tropical Indian Ocean, to assess migratory movements and estimate nutrient deposition rates based on the number of days they spent ashore. Light levels suggest that red‐footed boobies are resident in the Chagos Archipelago year‐round, although there are large latitudinal errors this close to the equator. Immersion data also indicate residency with tracked birds returning to land every one or two days. Spending an average of 79.86 ± 2.80 days and 280.84 ± 2.64 nights per year on land allows us to estimate that the 21 670 pairs of red‐footed boobies deposit 37.34 ± 0.56 tonnes year−1 of guano‐derived nitrogen throughout the archipelago. Our findings have implications for tropical seabird conservation and phylogenetics, as well as for assessing the impact of seabird nutrients on coral reef ecosystems.

Abstract Machine learning‐based behaviour classification using acceleration data is a powerful tool in bio‐logging research. Deep learning architectures such as convolutional neural networks (CNN), long short‐term memory (LSTM) and self‐attention mechanism as well as related training techniques have been extensively studied in human activity recognition. However, they have rarely been used in wild animal studies. The main challenges of acceleration‐based wild animal behaviour classification include data shortages, class imbalance problems, various types of noise in data due to differences in individual behaviour and where the loggers were attached and complexity in data due to complex animal‐specific behaviours, which may have limited the application of deep learning techniques in this area. To overcome these challenges, we explored the effectiveness of techniques for efficient model training: data augmentation, manifold mixup and pre‐training of deep learning models with unlabelled data, using datasets from two species of wild seabirds and state‐of‐the‐art deep learning model architectures. Data augmentation improved the overall model performance when one of the various techniques (none, scaling, jittering, permutation, time‐warping and rotation) was randomly applied to each data during mini‐batch training. Manifold mixup also improved model performance, but not as much as random data augmentation. Pre‐training with unlabelled data did not improve model performance. The state‐of‐the‐art deep learning models, including a model consisting of four CNN layers, an LSTM layer and a multi‐head attention layer, as well as its modified version with shortcut connection, showed better performance among other comparative models. Using only raw acceleration data as inputs, these models outperformed classic machine learning approaches that used 119 handcrafted features. Our experiments showed that deep learning techniques are promising for acceleration‐based behaviour classification of wild animals and highlighted some challenges (e.g. effective use of unlabelled data). There is scope for greater exploration of deep learning techniques in wild animal studies (e.g. advanced data augmentation, multimodal sensor data use, transfer learning and self‐supervised learning). We hope that this study will stimulate the development of deep learning techniques for wild animal behaviour classification using time‐series sensor data.

Machine learning‐based behaviour classification using acceleration data is a powerful tool in bio‐logging research. Deep learning architectures such as convolutional neural networks (CNN), long short‐term memory (LSTM) and self‐attention mechanism as well as related training techniques have been extensively studied in human activity recognition. However, they have rarely been used in wild animal studies. The main challenges of acceleration‐based wild animal behaviour classification include data shortages, class imbalance problems, various types of noise in data due to differences in individual behaviour and where the loggers were attached and complexity in data due to complex animal‐specific behaviours, which may have limited the application of deep learning techniques in this area.To overcome these challenges, we explored the effectiveness of techniques for efficient model training: data augmentation, manifold mixup and pre‐training of deep learning models with unlabelled data, using datasets from two species of wild seabirds and state‐of‐the‐art deep learning model architectures.Data augmentation improved the overall model performance when one of the various techniques (none, scaling, jittering, permutation, time‐warping and rotation) was randomly applied to each data during mini‐batch training. Manifold mixup also improved model performance, but not as much as random data augmentation. Pre‐training with unlabelled data did not improve model performance. The state‐of‐the‐art deep learning models, including a model consisting of four CNN layers, an LSTM layer and a multi‐head attention layer, as well as its modified version with shortcut connection, showed better performance among other comparative models. Using only raw acceleration data as inputs, these models outperformed classic machine learning approaches that used 119 handcrafted features.Our experiments showed that deep learning techniques are promising for acceleration‐based behaviour classification of wild animals and highlighted some challenges (e.g. effective use of unlabelled data). There is scope for greater exploration of deep learning techniques in wild animal studies (e.g. advanced data augmentation, multimodal sensor data use, transfer learning and self‐supervised learning). We hope that this study will stimulate the development of deep learning techniques for wild animal behaviour classification using time‐series sensor data. [ABSTRACT FROM AUTHOR]

Advancing breeding phenology is a commonly observed response to climate warming among bird species, potentially in response to shifts in the phenology of key resources. However, for migratory birds breeding at high latitudes, their capacity to breed earlier may be constrained by the time available between arrival on the breeding grounds and nesting, especially for later‐arriving individuals. This may have consequences for productivity, as early laying is often linked to higher breeding success, particularly in such seasonal environments. We investigated how migratory arrival timing influences subsequent timing of breeding, in particular whether the time between arrival and laying (arrival–laying gap) varies with arrival date, and if later‐arriving individuals are able to catch up with early‐arriving conspecifics. We tracked individual Icelandic Black‐tailed Godwit Limosa limosa islandica with GPS and PTT tags for one to two complete breeding seasons between 2013 and 2022. After arrival in Iceland, most Godwits visited their breeding territory within 5 days, though this interval was longer for earlier‐arriving birds. The total gap between arrival and laying was also longer for earlier‐arriving birds, such that laying date did not vary significantly with arrival date. These results suggest that, despite individual consistency in migratory phenology, subsequent timing of nesting is probably influenced by other factors, such as mate arrival timing and/or annual variation in environmental conditions. Regular pre‐nesting visits to the breeding territory may indicate that Godwits are able to monitor such factors closely and to nest early when conditions allow, but a larger sample of individuals and years is needed to assess whether early‐arriving individuals contribute disproportionately to population‐level advances in breeding phenology. Widespread tracking with high temporal and spatial resolution helps improve our understanding of phenological variation during the breeding season and its consequences for productivity and variation in juvenile phenology. [ABSTRACT FROM AUTHOR]

Adélie penguins are considered indicators of Antarctic ecosystems. Their populations have declined by more than 50% in the West Antarctic Peninsula, an area strongly affected by global warming, and that concentrates most of Antarctic krill harvesting. The use of high-resolution data to identify foraging areas regularly used by krill predators could provide valuable information for current discussions on the development of small-scale management and conservation measures for this region. We used information on the foraging trips of 57 individuals breeding in King George Island, tracked over 2019/2020, 2020/2021 and 2021/2022 breeding seasons during the chick-rearing stage, to identify their key foraging areas. Using an accelerometry-based latent behavioral analysis approach, we identified an area within 10 km of the colony consistently used by over 60% of the population throughout and between seasons. We also observed that almost 20% of the population uses the area near a seamount located 35 km from the colony for foraging, mainly during the late guarding phase when chick energy demands are highest or the effects of prey depletion might become more evident. The distances and duration of trips and the area explored increased as the season progressed and varied between seasons, consistent with annual differences in krill availability observed in the region. Foraging dives comprise roughly 40% of the dives performed during foraging trips, irrespective of the stage of the chick-rearing period, or the season analyzed. Our results emphasize the need to understand how variability in environmental conditions, prey availability, and energetic demands affect how predators use space, and the role that bathymetric features might play in providing reliable foraging grounds, for penguins, in a rapidly changing region. [ABSTRACT FROM AUTHOR]

Predator-prey arms races have led to the evolution of finely tuned disguise strategies. While the theoretical benefits of predator camouflage are well established, no study has yet been able to quantify its consequences for hunting success in natural conditions. We used high-resolution movement data to quantify how barn owls (Tyto alba) conceal their approach when using a sit-and-wait strategy. We hypothesized that hunting barn owls would modulate their landing force, potentially reducing noise levels in the vicinity of prey. Analysing 87,957 landings by 163 individuals equipped with GPS tags and accelerometers, we show that barn owls reduce their landing force as they approach their prey, and that landing force predicts the success of the following hunting attempt. Landing force also varied with the substrate, being lowest on man-made poles in field boundaries. The physical environment, therefore, affects the capacity for sound camouflage, providing an unexpected link between predator-prey interactions and land use. Finally, hunting strike forces in barn owls were the highest recorded in any bird, relative to body mass, highlighting the range of selective pressures that act on landings and the capacity of these predators to modulate their landing force. Overall, our results provide the first measurements of landing force in a wild setting, revealing a new form of motion-induced sound camouflage and its link to hunting success.

The bio-logging method could be a valuable approach to studying the underwater movement of marine fish. We investigated the horizontal and vertical movement patterns of two yellowtails Seriola quinqueradiata weighing 8.7 kg and 9.5 kg with a pop-up satellite archival tag from October 2020 to January 2021 in the East Sea of Korea. Our results showed that a yellowtail migrated northward in October and November, and then shifted southward in mid-December. The average swimming depth and temperature of the fish monitored over 82 days were 24.9 ± 9.3 m (average ± SD) and 16.5 ± 1.9°C, respectively, and the total traveled distance was 1,172.4 km. The fish swam significantly deeper during the daytime (33.70 ± 14.80 m) than at nighttime (20.65 ± 8.44 m) from November to December (p < 0.05). These results suggest that the horizontal migratory route of yellowtails in accordance with the East Korea Warm Current which is the main branch of Tsushima Warm Current in the fall and early winter seasons, and showed significant diel vertical movement patterns from November to December.

Fish are an essential resource in human society, and while ecological research on them is challenging, it is absolutely necessary. Recent technologies enabled researchers to monitor underwater fish behavior. Acoustic signals, satellite-mediated location estimation, and light-based geolocation are powerful tools for tracking fish movements from freshwater to deep-sea habitats. These tools allow us to track various fish species and elucidate their ecology. Furthermore, based on these technologies, we can develop fisheries management plans and enhance aquaculture productivity. In this review, we also discuss challenges in improving current technologies and provide future recommendations for fish bio-logging studies.

The darkness of the deep ocean limits the vision of diving predators, except when prey emit bioluminescence. It is hypothesized that deep-diving seals rely on highly developed whiskers to locate their prey. However, if and how seals use their whiskers while foraging in natural conditions remains unknown. We used animal-borne tags to show that free-ranging elephant seals use their whiskers for hydrodynamic prey sensing. Small, cheek-mounted video loggers documented seals actively protracting their whiskers in front of their mouths with rhythmic whisker movement, like terrestrial mammals exploring their environment. Seals focused their sensing effort at deep foraging depths, performing prolonged whisker protraction to detect, pursue, and capture prey. Feeding-event recorders with light sensors demonstrated that bioluminescence contributed to only about 20% of overall foraging success, confirming that whiskers play the primary role in sensing prey. Accordingly, visual prey detection complemented and enhanced prey capture. The whiskers' role highlights an evolutionary alternative to echolocation for adapting to the extreme dark of the deep ocean environment, revealing how sensory abilities shape foraging niche segregation in deep-diving mammals. Mammals typically have mobile facial whiskers, and our study reveals the significant function of whiskers in the natural foraging behavior of a marine predator. We demonstrate the importance of field-based sensory studies incorporating multimodality to better understand how multiple sensory systems are complementary in shaping the foraging success of predators.

Understanding the foraging behavior of marine animals is crucial for assessing their ecological significance and responses to environmental changes. In the context of Antarctica, marine animals face rapid and profound environmental changes related with global warming. However, our understanding of their responses remains limited owing to the formidable challenges inherent in conducting observations, particularly during the harsh austral winter months. In this study, we investigated the influence of changes in seawater properties and light conditions on the seasonal foraging behavior of Weddell seals (Leptonychotes weddellii) in the Ross Sea, Antarctica. We affixed 35 Weddell seals with CTD tags to record their locations and dive profiles, including depth, head acceleration, temperature, and salinity. We found that seals foraged more frequently in modified shelf water and ice shelf water compared to Antarctic surface water. This preference could be connected to greater food availability. Additionally, seals also dove to greater depths and displayed increased activity in capturing prey during daylight hours. This behavior may correspond to the diel vertical migration of pelagic prey in response to varying light conditions. Our findings suggest that Weddell seals have adjusted their foraging behaviors to adapt to spatial and temporal changes in oceanographic conditions. This highlights the importance of extrinsic factors in estimating their seasonal foraging behavior. [ABSTRACT FROM AUTHOR]

Lactation is the most energy‐demanding event in mammals' reproduction. In pinnipeds, females are the only food providers to the young and have developed numerous behavioral and physiological lactation strategies, from capital‐breeding to income‐breeding. Lactating females' fine‐scale foraging strategy, and precise understanding of how females supplement their pup's needs as well as their own are important to understand the species' ecology and energetic balance. Polar pinnipeds, inhabiting extreme environments, are sensitive to climate change and variability, understanding their constraints and foraging strategy during lactation is therefore important. In 2019, three sonar tags were deployed on lactating Weddell seals in Terre Adélie (East Antarctica) for 7 days, to study fine‐scale predator–prey interactions. Feeding activity was mostly benthic, reduced, central‐placed, and spatially limited. Females spent most of their time hauled‐out. A total of 331 prey capture attempts (PrCAs) were recorded using triaxial acceleration data, with 125 prey identified on echograms (5 cm, acoustic size). All PrCAs occurred on the seafloor, shallower than usual records (mean depth of 88 m, vs 280 m after their molt). We also found that they only fed in three of the five identified dive shapes, during the ascent or throughout the dive. Half of the prey were reactive to the seal's approach, either leaving the seafloor, or escaping just above the seafloor, suggesting that the seals hunt by chasing them from the seabed. Seals continuously scanned the area during the approach phase, evoking opportunistic foraging. Our results provide additional evidence that Weddell seal forage during lactation, displaying a mix of capital‐breeding and income‐breeding strategies during this period of physiological stress. This work sheds light on previously unexplored aspects of their foraging behavior, such as shallow water environments, targeting benthic prey, generally focusing on single prey rather than schools, and evidence of visual scanning through observed head movements. [ABSTRACT FROM AUTHOR]

This article discusses the impact of extreme weather events on the movement and behavior of wild animals, specifically airborne animals like birds. The study focuses on the behavior of a GPS-equipped streaked shearwater caught in a large typhoon over mainland Japan. The bird exhibited swirling flight at high altitudes, with speeds and altitudes much higher than its regular flights. The study highlights the need to understand how volant animals survive and navigate under extreme weather conditions and how the increasing frequency of severe storms affects wildlife. [Extracted from the article]

What new questions could ecophysiologists answer if physio-logging research was fully reproducible? We argue that technical debt (computational hurdles resulting from prioritizing short-term goals over long-term sustainability) stemming from insufficient cyberinfrastructure (field-wide tools, standards, and norms for analyzing and sharing data) trapped physio-logging in a scientific silo. This debt stifles comparative biological analyses and impedes interdisciplinary research. Although physio-loggers (e.g., heart rate monitors and accelerometers) opened new avenues of research, the explosion of complex datasets exceeded ecophysiologys informatics capacity. Like many other scientific fields facing a deluge of complex data, ecophysiologists now struggle to share their data and tools. Adapting to this new era requires a change in mindset, from data as a noun (e.g., traits, counts) to data as a sentence, where measurements (nouns) are associate with transformations (verbs), parameters (adverbs), and metadata (adjectives). Computational reproducibility provides a framework for capturing the entire sentence. Though usually framed in terms of scientific integrity, reproducibility offers immediate benefits by promoting collaboration between individuals, groups, and entire fields. Rather than a tax on our productivity that benefits some nebulous greater good, reproducibility can accelerate the pace of discovery by removing obstacles and inviting a greater diversity of perspectives to advance science and society. In this article, we 1) describe the computational challenges facing physio-logging scientists and connect them to the concepts of technical debt and cyberinfrastructure, 2) demonstrate how other scientific fields overcame similar challenges by embracing computational reproducibility, and 3) present a framework to promote computational reproducibility in physio-logging, and bio-logging more generally.

Abstract GPS‐based tracking is widely used for studying wild social animals. Much like traditional observational methods, using GPS devices requires making a number of decisions about sampling that can affect the robustness of a study's conclusions. For example, sampling fewer individuals per group across more distinct social groups may not be sufficient to infer group‐ or subgroup‐level behaviours, while sampling more individuals per group across fewer groups limits the ability to draw conclusions about populations. Here, we provide quantitative recommendations when designing GPS‐based tracking studies of animal societies. We focus on the trade‐offs between three fundamental axes of sampling effort: (1) sampling coverage—the number and allocation of GPS devices among individuals in one or more social groups; (2) sampling duration—the total amount of time over which devices collect data and (3) sampling frequency—the temporal resolution at which GPS devices record data. We first test GPS tags under field conditions to quantify how these aspects of sampling design can affect both GPS accuracy (error in absolute positional estimates) and GPS precision (error in the estimate relative position of two individuals), demonstrating that GPS error can have profound effects when inferring distances between individuals. We then use data from whole‐group tracked vulturine guineafowl Acryllium vulturinum to demonstrate how the trade‐off between sampling frequency and sampling duration can impact inferences of social interactions and to quantify how sampling coverage can affect common measures of social behaviour in animal groups, identifying which types of measures are more or less robust to lower coverage of individuals. Finally, we use data‐informed simulations to extend insights across groups of different sizes and cohesiveness. Based on our results, we are able to offer a range of recommendations on GPS sampling strategies to address research questions across social organizational scales and social systems—from group movement to social network structure and collective decision‐making. Our study provides practical advice for empiricists to navigate their decision‐making processes when designing GPS‐based field studies of animal social behaviours, and highlights the importance of identifying the optimal deployment decisions for drawing informative and robust conclusions.

Abstract Background Bio-logging devices play a fundamental and indispensable role in movement ecology studies, particularly in the wild. However, researchers are aware of the influence that attaching devices can have on animals, particularly on their behaviour, energy expenditure and survival. The way a device is attached to an animal’s body has also potential consequences for the collected data, and quantifying the type and magnitude of such potential effects is fundamental to enable researchers to combine and compare data from different studies, as much as it is to improve animal welfare. For over two decades, large terrestrial birds have been in the focus of long-term movement ecology research, employing bio-logging devices attached with different types of harnesses. However, comparative studies investigating the effects of different harness types used on these species are scarce. Methods In this study, we tested for potential differences in data collected by two commonly used harness types, backpack and leg-loop, on the flight performance of 10 individuals from five soaring raptor species, equipped with high resolution bio-logging devices, in the same area and time. We explored the effect of harness type on vertical speed, airspeed, glide ratio, height above sea level, distance travelled, proportion of soaring and flapping behaviour, and VeDBA (a proxy for energy expenditure) between and within individuals, all used as fine-scale measures of flight performance. Results Birds equipped with leg-loops climbed up to 0.36 ms $$^{-1}$$ - 1 faster, reached 25.9% greater altitudes while soaring and spent less time in active flight compared to birds equipped with backpacks, suggesting that backpack harnesses, compared to leg-loops, might cause additional drag affecting the birds’ flight performance. A lower VeDBA, a lower rate of sinking while gliding and slightly higher glide ratio and airspeeds were also indicative of less drag using leg-loops, even though the effect on these parameters was comparable to inter-individual differences. Conclusions Our results add to the existing literature highlighting the design-related advantages of leg-loops, and support the use of leg-loops as a better alternative to backpack harnesses for large soaring birds, when possible. Our study also highlights how apparently small changes in device attachment can lead to notable improvements in tagging practice, with implications for animal welfare, data interpretation and comparability.

Abstract The ability of marine mammals to accumulate sufficient lipid energy reserves is vital for mammals' survival and successful reproduction. However, long‐term monitoring of at‐sea changes in body condition, specifically lipid stores, has only been possible in elephant seals performing prolonged drift dives (low‐density lipids alter the rates of depth change while drifting). This approach has limited applicability to other species. Using hydrodynamic performance analysis during transit glides, we developed and validated a novel satellite‐linked data logger that calculates real‐time changes in body density (∝lipid stores). As gliding is ubiquitous amongst divers, the system can assess body condition in a broad array of diving animals. The tag processes high sampling rate depth and three‐axis acceleration data to identify 5 s high pitch angle glide segments at depths >100 m. Body density is estimated for each glide using gliding speed and pitch to quantify drag versus buoyancy forces acting on the gliding animal. We used tag data from 24 elephant seals (Mirounga spp.) to validate the onboard calculation of body density relative to drift rate. The new tags relayed body density estimates over 200 days and documented lipid store accumulation during migration with good correspondence between changes in body density and drift rate. Our study provided updated drag coefficient values for gliding (Cd,f = 0.03) and drifting (Cd,s = 0.12) elephant seals, both substantially lower than previous estimates. We also demonstrated post‐hoc estimation of the gliding drag coefficient and body density using transmitted data, which is especially useful when drag parameters cannot be estimated with sufficient accuracy before tag deployment. Our method has the potential to advance the field of marine biology by switching the research paradigm from indirectly inferring animal body condition from foraging effort to directly measuring changes in body condition relative to foraging effort, habitat, ecological factors and anthropogenic stressors in the changing oceans. Expanding the method to account for diving air volumes will expand the system's applicability to shallower‐diving (

Abstract Lactation is the most energy‐demanding event in mammals' reproduction. In pinnipeds, females are the only food providers to the young and have developed numerous behavioral and physiological lactation strategies, from capital‐breeding to income‐breeding. Lactating females' fine‐scale foraging strategy, and precise understanding of how females supplement their pup's needs as well as their own are important to understand the species' ecology and energetic balance. Polar pinnipeds, inhabiting extreme environments, are sensitive to climate change and variability, understanding their constraints and foraging strategy during lactation is therefore important. In 2019, three sonar tags were deployed on lactating Weddell seals in Terre Adélie (East Antarctica) for 7 days, to study fine‐scale predator–prey interactions. Feeding activity was mostly benthic, reduced, central‐placed, and spatially limited. Females spent most of their time hauled‐out. A total of 331 prey capture attempts (PrCAs) were recorded using triaxial acceleration data, with 125 prey identified on echograms (5 cm, acoustic size). All PrCAs occurred on the seafloor, shallower than usual records (mean depth of 88 m, vs 280 m after their molt). We also found that they only fed in three of the five identified dive shapes, during the ascent or throughout the dive. Half of the prey were reactive to the seal's approach, either leaving the seafloor, or escaping just above the seafloor, suggesting that the seals hunt by chasing them from the seabed. Seals continuously scanned the area during the approach phase, evoking opportunistic foraging. Our results provide additional evidence that Weddell seal forage during lactation, displaying a mix of capital‐breeding and income‐breeding strategies during this period of physiological stress. This work sheds light on previously unexplored aspects of their foraging behavior, such as shallow water environments, targeting benthic prey, generally focusing on single prey rather than schools, and evidence of visual scanning through observed head movements.

Knowledge of fisheries impacts, past and present, is essential for understanding the ecology and conservation of seabirds, but in a rapidly changing world, knowledge and research directions require updating. In this Introduction and in the articles in this Themed Set "Impacts of fishing on seabirds", we update our understanding of how fishing impacts seabird communities and identify areas for future research. Despite awareness of the problems and mitigation efforts for >20 years, fisheries still negatively impact seabirds via the effects of bycatch, competition, and discards. Bycatch continues to kill hundreds of thousands of seabirds annually, with negative population-level consequences. Fisheries for forage fish (e.g. anchovy, sandeel, and krill) negatively impact seabirds by competing for the same stocks. Historically, discards supplemented seabird diets, benefitting some species but also increasing bycatch rates and altering seabird community composition. However, declining discard production has led to potentially deleterious diet switches, but reduced bycatch rates. To improve research into these problems, we make the following recommendations: (1) improve data collection on seabird–vessel interaction and bycatch rates, on fishing effort and vessel movements (especially small-scale fleets), and on mitigation compliance, (2) counter the current bias towards temperate and high-latitude ecosystems, larger-bodied species and particular life stages or times of year (e.g. adults during breeding), and (3) advance our currently poor understanding of combined effects of fisheries and other threats (e.g. climate change, offshore renewables). In addition, research is required on under-studied aspects of fishing impacts: consequences for depleted sub-surface predators, impacts of illegal, unreported and unregulated fishing, artisanal and emerging fisheries, such as those targeting mesopelagic fish, have received insufficient research attention. Some of these shortfalls can be overcome with new tools (e.g. electronic monitoring, remote sensing, artificial intelligence, and big data) but quantifying and addressing fishing impacts on seabirds requires greater research investment at appropriate spatio-temporal scales, and more inclusive dialogue from grassroots to national and international levels to improve governance as fishing industries continue to evolve. [ABSTRACT FROM AUTHOR]

Context: One of the welfare and ethical challenges with tracking animals is ensuring that the tracking device is removed from the animal at the conclusion of the study. However, for animals that are not readily re-trapped, the impact of devices and alternatives for their retrieval are rarely examined. Aims: We compared the retention time of two types of break-away mechanisms for tracking collars deployed on mainland quokkas (Setonix brachyurus). Methods: We tested a cotton thread (CT) weak-link, where the collar was cut and then a looping stitch was made to link the cut ends of the collar. We compared collar retention time of this simple mechanism with a lightweight automatic micro timed-release device (mTRD, Sirtrack). Key results: Of the 17 radio collars with CT, the fates of 15 collars contributed to retention time data. Seven collars released: six fell off and were recovered 148 ± 64 (s.d.) days after deployment and another collar fell off 136 days after deployment but could not be recovered. Eight quokkas were recaptured (161 ± 109 days after deployment) and collars removed. Two quokkas were each tracked for over a year but then disappeared. Of the 11 GPS collars fitted with a mTRD, the fates of nine collars contributed to retention time data. Two released early at 16 and 29 days and were recovered. Seven fell off around the scheduled release date. There were two unknown fates. Re-trapped collared quokkas did not show evidence of injuries from wearing collars or any significant change in body mass (P = 0.442). Conclusions: The timing of release for the CT weak-link was unpredictable, with a third of the collars releasing within 1 year and 7/15 lasting only about 6 months. Over two-thirds (7/9) of the GPS collars fitted with timed-release device released on schedule while 2/9 released early. Implications: Tracking devices equipped with break-away mechanisms are essential for safeguarding animal welfare outcomes for species where the chance of recapture is not certain. For both break-away types examined in this study, the release timing was unpredictable and poor collar recovery rates show the importance of adding camera traps to monitor the outcomes for collared animals. The ethical and welfare challenges with radio tracking animals is ensuring that the device is removed from the animal at the conclusion of the study. We tested two types of collar break-away mechanisms, designed to release the collars over time. One is Cotton Thread weak-link and a second Timed Release Device. For both break-away types, the release timing was unpredictable, and poor collar recovery rates show the importance in adding camera traps to monitor collared animals. Photograph by Leticia F. Povh. [ABSTRACT FROM AUTHOR]

Abstract Background Animal-borne telemetry instruments (tags) have greatly advanced our understanding of species that are challenging to observe. Recently, non-recoverable instruments attached to cetaceans have increased in use, but these devices have limitations in data transmission bandwidth. We analyze trade-offs in the longevity, resolution, and continuity of data records from non-recoverable satellite-linked tags on deep-diving Ziphius cavirostris in the context of a behavioral response study of acute noise exposure. We present one data collection programming scheme that balances resolution and continuity against longevity to address specific questions about the behavioral responses of animals to noise exposure in experimental contexts. We compare outputs between two programming regimes on a commercially available satellite-linked tag: (1) dive behavior summary defined by conductivity thresholds and (2) depth time-series at various temporal resolutions. Results We found that time-series data vary from the more precisely defined dives from a dive summary record data stream by an acceptable error range for our application. We determined a 5-min time-series data stream collected for 14 days balanced resolution with longevity, achieving complete or nearly complete diving records in 6 out of 8 deployments. We increased our data message reception rate several fold by employing a boat based data capture system. Finally, a tag deployed in a group concurrently with a high-resolution depth recorder showed high depth concordance. Conclusions We present the conceptual framework and iterative process for matching telemetry tag programming to research questions that we used and which should be applicable to a wide range of studies. Although designing new hardware for our specific questions was not feasible at the time, we were able to optimize the sampling regime of a commercially available instrument to meet the needs of our research questions and proposed analyses. Nevertheless, for other study species or designs, the complicated intersection between animal behavior and bandwidth of telemetry systems can often create a severe mismatch among research questions, data collection, and analysis tools. More flexible programming and purpose-built instruments will increase the efficacy of these studies and increase the scientific yield relative to the inherently higher risk of invasive studies.

GPS‐based tracking is widely used for studying wild social animals. Much like traditional observational methods, using GPS devices requires making a number of decisions about sampling that can affect the robustness of a study's conclusions. For example, sampling fewer individuals per group across more distinct social groups may not be sufficient to infer group‐ or subgroup‐level behaviours, while sampling more individuals per group across fewer groups limits the ability to draw conclusions about populations.Here, we provide quantitative recommendations when designing GPS‐based tracking studies of animal societies. We focus on the trade‐offs between three fundamental axes of sampling effort: (1) sampling coverage—the number and allocation of GPS devices among individuals in one or more social groups; (2) sampling duration—the total amount of time over which devices collect data and (3) sampling frequency—the temporal resolution at which GPS devices record data.We first test GPS tags under field conditions to quantify how these aspects of sampling design can affect both GPS accuracy (error in absolute positional estimates) and GPS precision (error in the estimate relative position of two individuals), demonstrating that GPS error can have profound effects when inferring distances between individuals. We then use data from whole‐group tracked vulturine guineafowl Acryllium vulturinum to demonstrate how the trade‐off between sampling frequency and sampling duration can impact inferences of social interactions and to quantify how sampling coverage can affect common measures of social behaviour in animal groups, identifying which types of measures are more or less robust to lower coverage of individuals. Finally, we use data‐informed simulations to extend insights across groups of different sizes and cohesiveness.Based on our results, we are able to offer a range of recommendations on GPS sampling strategies to address research questions across social organizational scales and social systems—from group movement to social network structure and collective decision‐making.Our study provides practical advice for empiricists to navigate their decision‐making processes when designing GPS‐based field studies of animal social behaviours, and highlights the importance of identifying the optimal deployment decisions for drawing informative and robust conclusions. [ABSTRACT FROM AUTHOR]

Background: Bio-logging devices play a fundamental and indispensable role in movement ecology studies, particularly in the wild. However, researchers are aware of the influence that attaching devices can have on animals, particularly on their behaviour, energy expenditure and survival. The way a device is attached to an animal's body has also potential consequences for the collected data, and quantifying the type and magnitude of such potential effects is fundamental to enable researchers to combine and compare data from different studies, as much as it is to improve animal welfare. For over two decades, large terrestrial birds have been in the focus of long-term movement ecology research, employing bio-logging devices attached with different types of harnesses. However, comparative studies investigating the effects of different harness types used on these species are scarce. Methods: In this study, we tested for potential differences in data collected by two commonly used harness types, backpack and leg-loop, on the flight performance of 10 individuals from five soaring raptor species, equipped with high resolution bio-logging devices, in the same area and time. We explored the effect of harness type on vertical speed, airspeed, glide ratio, height above sea level, distance travelled, proportion of soaring and flapping behaviour, and VeDBA (a proxy for energy expenditure) between and within individuals, all used as fine-scale measures of flight performance. Results: Birds equipped with leg-loops climbed up to 0.36 ms - 1 faster, reached 25.9% greater altitudes while soaring and spent less time in active flight compared to birds equipped with backpacks, suggesting that backpack harnesses, compared to leg-loops, might cause additional drag affecting the birds' flight performance. A lower VeDBA, a lower rate of sinking while gliding and slightly higher glide ratio and airspeeds were also indicative of less drag using leg-loops, even though the effect on these parameters was comparable to inter-individual differences. Conclusions: Our results add to the existing literature highlighting the design-related advantages of leg-loops, and support the use of leg-loops as a better alternative to backpack harnesses for large soaring birds, when possible. Our study also highlights how apparently small changes in device attachment can lead to notable improvements in tagging practice, with implications for animal welfare, data interpretation and comparability. [ABSTRACT FROM AUTHOR]

The growing diversity of animal‐borne sensor types is revolutionizing our understanding of wildlife biology. For example, researcher‐developed sensors, such as audio and video loggers, are being increasingly attached to wildlife tracking collars to provide insights into a range of topics from species interactions to physiology. However, such devices are often prohibitively power‐intensive, relative to conventional wildlife collar sensors, and their retrieval without compromising long‐term data collection and animal welfare remains a challenge. We present an open‐source system (SensorDrop) for remotely detaching individual sensors from wildlife collars. SensorDrop facilitates the retrieval of power‐intensive sensors while leaving non‐resource‐intensive sensors intact on animals. SensorDrop systems can be made using commercially available components and are a fraction of the cost of other timed drop‐off devices that detach full wildlife tracking collars. From 2021 to 2022, eight SensorDrop units were successfully deployed on free‐ranging African wild dog packs in the Okavango Delta as part of audio‐accelerometer sensor bundles attached to wildlife collars. All SensorDrop units detached after 2–3 weeks and facilitated the collection of audio and accelerometer data while leaving wildlife GPS collars intact to continue collecting locational data (>1 year), critical for long‐term conservation population monitoring in the region. SensorDrop offers a low‐cost method to remotely detach and retrieve individual sensors from wildlife collars. By selectively detaching battery‐depleted sensors, SensorDrop maximizes the amount of data collected per wildlife collar deployment and mitigates ethical concerns on animal rehandling. SensorDrop adds to the growing body of open‐source animal‐borne technologies being utilized by wildlife researchers to innovate and expand upon data collection practices and supports the continued ethical use of novel technologies within wildlife studies. [ABSTRACT FROM AUTHOR]

Understanding the behavioral ecology of wildlife that experiences negative interactions with humans and the outcome of any wildlife management intervention is essential. In the Cape Peninsula, South Africa, chacma baboons (Papio ursinus) search for anthropogenic food sources in both urban and agricultural areas. In response, the city of Cape Town and private farmers employ "rangers" to keep baboons within the Table Mountain National Park. In this study, we investigated the success of rangers' intervention in keeping baboons in their natural habitat. Based on our findings in year one, we recommended adjustments to the rangers' management strategy in year two. We recommended improved consensus of actions toward baboons (that is, when/where to herd them), and the construction of a baboon‐proof fence around one of the farms that provided a corridor to urban areas. During the 2 months following recommendations, these interventions combined resulted in a significant reduction in the time baboons spent in both urban and agricultural land. Our case study illustrates the importance of integrating research findings into ongoing management actions to improve both human livelihoods and baboon conservation through an adaptive management framework. We expect similar approaches to be beneficial in a wide range of species and contexts. [ABSTRACT FROM AUTHOR]

The ability of marine mammals to accumulate sufficient lipid energy reserves is vital for mammals' survival and successful reproduction. However, long‐term monitoring of at‐sea changes in body condition, specifically lipid stores, has only been possible in elephant seals performing prolonged drift dives (low‐density lipids alter the rates of depth change while drifting). This approach has limited applicability to other species.Using hydrodynamic performance analysis during transit glides, we developed and validated a novel satellite‐linked data logger that calculates real‐time changes in body density (∝lipid stores). As gliding is ubiquitous amongst divers, the system can assess body condition in a broad array of diving animals. The tag processes high sampling rate depth and three‐axis acceleration data to identify 5 s high pitch angle glide segments at depths >100 m. Body density is estimated for each glide using gliding speed and pitch to quantify drag versus buoyancy forces acting on the gliding animal.We used tag data from 24 elephant seals (Mirounga spp.) to validate the onboard calculation of body density relative to drift rate. The new tags relayed body density estimates over 200 days and documented lipid store accumulation during migration with good correspondence between changes in body density and drift rate. Our study provided updated drag coefficient values for gliding (Cd,f = 0.03) and drifting (Cd,s = 0.12) elephant seals, both substantially lower than previous estimates. We also demonstrated post‐hoc estimation of the gliding drag coefficient and body density using transmitted data, which is especially useful when drag parameters cannot be estimated with sufficient accuracy before tag deployment.Our method has the potential to advance the field of marine biology by switching the research paradigm from indirectly inferring animal body condition from foraging effort to directly measuring changes in body condition relative to foraging effort, habitat, ecological factors and anthropogenic stressors in the changing oceans. Expanding the method to account for diving air volumes will expand the system's applicability to shallower‐diving (<100 m) species, facilitating real‐time monitoring of body condition in a broad range of breath‐hold divers. [ABSTRACT FROM AUTHOR]

Abstract Global Position System (GPS) tags are widely used in animal tracking to address far‐ranging ecological, behavioural and conservation‐related questions. However, GPS tags with transmitting functions via Global System for Mobile communications (GSM) and long‐lasting batteries are too cumbersome for animals with small body sizes. In addition, GSM is expensive with strict signal limitations in remote areas. Downloading locations from small GPS tags also requires animal recapture, which can result in large workloads. Combined, these problems limit the use of GPS tags in tracking small animals. To overcome these challenges, we present an integrated technology to pinpoint animal locations, especially those of medium‐ and small‐sized species. Our system consists of 3.7 g solar‐powered GPS tags (Nano), whose sampling frequency can be changed flexibly, and a combination of a receiver and an unmanned aerial vehicle (UAV) to retrieve data. The UAV carries the receiver that can retrieve data from Nanos via Bluetooth. Data are uploaded to a platform via GSM by the receiver and then downloaded by users in real time. Users can also directly download data from tags or the receiver via Bluetooth. We conducted stationary and field tests to assess the system's performance in Thousand Island Lake, China. Stationary tests were conducted at eight sites near the buildings, in open fields and on an island. Nanos can transmit data to the receiver within distances of 600–1000 m and at speeds of 6–72 records/s. The mean accuracy was 10.44–23.32 m and the fix success rates (FSRs) were larger than 97%. In field tests, we captured and attached Nanos on six Eurasian jays Garrulus glandarius. The FSRs were larger than 98%. Using the UAV reduced the time spent in field. Our system is labour‐saving and accurate in locating animals larger than 80 g as tested in a land‐bridge island system. Bluetooth transmission assisted by the UAV can overcome signal limitations and landscape blocks, and has the potential to be applied in inaccessible landscapes. The large memory of Nanos also allows for the retrieval of data from migratory species with strong site fidelity on their returns.

Background: Animal-borne telemetry instruments (tags) have greatly advanced our understanding of species that are challenging to observe. Recently, non-recoverable instruments attached to cetaceans have increased in use, but these devices have limitations in data transmission bandwidth. We analyze trade-offs in the longevity, resolution, and continuity of data records from non-recoverable satellite-linked tags on deep-diving Ziphius cavirostris in the context of a behavioral response study of acute noise exposure. We present one data collection programming scheme that balances resolution and continuity against longevity to address specific questions about the behavioral responses of animals to noise exposure in experimental contexts. We compare outputs between two programming regimes on a commercially available satellite-linked tag: (1) dive behavior summary defined by conductivity thresholds and (2) depth time-series at various temporal resolutions. Results: We found that time-series data vary from the more precisely defined dives from a dive summary record data stream by an acceptable error range for our application. We determined a 5-min time-series data stream collected for 14 days balanced resolution with longevity, achieving complete or nearly complete diving records in 6 out of 8 deployments. We increased our data message reception rate several fold by employing a boat based data capture system. Finally, a tag deployed in a group concurrently with a high-resolution depth recorder showed high depth concordance. Conclusions: We present the conceptual framework and iterative process for matching telemetry tag programming to research questions that we used and which should be applicable to a wide range of studies. Although designing new hardware for our specific questions was not feasible at the time, we were able to optimize the sampling regime of a commercially available instrument to meet the needs of our research questions and proposed analyses. Nevertheless, for other study species or designs, the complicated intersection between animal behavior and bandwidth of telemetry systems can often create a severe mismatch among research questions, data collection, and analysis tools. More flexible programming and purpose-built instruments will increase the efficacy of these studies and increase the scientific yield relative to the inherently higher risk of invasive studies. [ABSTRACT FROM AUTHOR]

Simple Summary: Broiler chickens are specifically bred for meat, and conventional breeds have been genetically selected for faster growth rates. Rapid growth is associated with a greater risk of lameness in broiler chickens, which is a major welfare concern associated with an economic loss for producers. Although defined as an individual's physical and mental state, welfare is often monitored at the group level and is at risk of overlooking individual issues. Body-mounted accelerometers measure movement and could potentially monitor individual welfare, including lameness. However, body-mounted sensors may alter behavior and/or impact welfare. We investigated relationships between accelerometer-recorded activity (all movement), weight, and lameness in broiler breeds with different growth rates. Wearing the device did not negatively impact lameness, and, except for preening more, birds behaved similarly to those not wearing accelerometers after 24 h. We found that faster-growing, heavier birds were less active compared to slower-growing, lighter birds, demonstrating that accelerometers could detect known influences on activity useful for general monitoring, but that accelerometer-detected activity was not linearly associated with lameness. Further research on accelerometer detection of more specific behavioral changes likely to be associated with lameness, such as non-linear acceleration with gait score, offers the possibility of better continuous monitoring of individuals to assess lameness objectively. Accelerometers are increasingly being investigated to detect animal behavior as a method for monitoring individual welfare that overcomes manual challenges associated with time, resource, and discrete sampling. We investigated the effects of broiler chicken hybrid (hereafter breed) and weight on accelerometer activity (activityA; calculated as percentage of time spent active (%)) and its association with lameness as a major broiler welfare concern. Accelerometers were attached to birds of different breeds on between 2 and 4 occasions from 26 to 30 days old (conventional breed CNV) and 26 to 49 days old (two slower-growing breeds SGH; SGN). At 2.2 kg, lameness was scored using a 6-point gait scoring system (0: unaffected to 5: severely lame). Linear mixed effects models and breed-stratified generalized linear models together with a random-effect meta-analysis were used for data analyses. ActivityA was lower in faster-growing, heavier birds compared to slower-growing, lighter birds, showing overall consistency with previous behavioral research, but did not vary linearly with gait score. Accelerometers offer the potential for simple broad-scale continuous monitoring of broiler chicken activity behavior that requires limited data processing. Exploration of the ability of accelerometers to capture more subtle and specific changes in behavioral patterning, such as non-linear acceleration with gait score that could indicate early development of lameness, warrants further investigation. [ABSTRACT FROM AUTHOR]

Central place foragers such as pelagic seabirds often travel large distances to reach profitable foraging areas. King penguins (Aptenodytes patagonicus) are well known for their large-scale foraging movements to the productive Antarctic Polar Front, though their fine-scale travelling and foraging characteristics remain unclear. Here, we investigated the horizontal movements and foraging patterns of king penguins to understand their fine-scale movement decisions during distant foraging trips. We attached multi-channel data loggers that can record depth, speed, tri-axis acceleration, tri-axis magnetism, and environmental temperature of the penguins and obtained data (n = 8 birds) on their horizontal movement rates from reconstructed dive paths and their feeding attempts estimated from rapid changes in swim speed. During transit toward main foraging areas, penguins increased the time spent on shallow travelling dives (< 50 m) at night and around midday, and increased the time spent on deep foraging dives (≥ 50 m) during crepuscular hours. The horizontal movement rates during deep dives were negatively correlated with maximum dive depths, suggesting that foraging at greater depths is associated with a decreased horizontal travelling speed. Penguins concentrated their foraging efforts (more deep dives and higher rates of feeding attempts) at twilight during transit, when prey may be more accessible due to diel vertical migration, while they travelled rapidly at night and midday when prey may be difficult to detect and access. Such behavioural adjustments correspond to a movement strategy adopted by avian deep divers to travel long distances while feeding on prey exhibiting diel vertical migration. [ABSTRACT FROM AUTHOR]

Abstract The growing diversity of animal‐borne sensor types is revolutionizing our understanding of wildlife biology. For example, researcher‐developed sensors, such as audio and video loggers, are being increasingly attached to wildlife tracking collars to provide insights into a range of topics from species interactions to physiology. However, such devices are often prohibitively power‐intensive, relative to conventional wildlife collar sensors, and their retrieval without compromising long‐term data collection and animal welfare remains a challenge. We present an open‐source system (SensorDrop) for remotely detaching individual sensors from wildlife collars. SensorDrop facilitates the retrieval of power‐intensive sensors while leaving non‐resource‐intensive sensors intact on animals. SensorDrop systems can be made using commercially available components and are a fraction of the cost of other timed drop‐off devices that detach full wildlife tracking collars. From 2021 to 2022, eight SensorDrop units were successfully deployed on free‐ranging African wild dog packs in the Okavango Delta as part of audio‐accelerometer sensor bundles attached to wildlife collars. All SensorDrop units detached after 2–3 weeks and facilitated the collection of audio and accelerometer data while leaving wildlife GPS collars intact to continue collecting locational data (>1 year), critical for long‐term conservation population monitoring in the region. SensorDrop offers a low‐cost method to remotely detach and retrieve individual sensors from wildlife collars. By selectively detaching battery‐depleted sensors, SensorDrop maximizes the amount of data collected per wildlife collar deployment and mitigates ethical concerns on animal rehandling. SensorDrop adds to the growing body of open‐source animal‐borne technologies being utilized by wildlife researchers to innovate and expand upon data collection practices and supports the continued ethical use of novel technologies within wildlife studies.

Abstract Understanding the behavioral ecology of wildlife that experiences negative interactions with humans and the outcome of any wildlife management intervention is essential. In the Cape Peninsula, South Africa, chacma baboons (Papio ursinus) search for anthropogenic food sources in both urban and agricultural areas. In response, the city of Cape Town and private farmers employ “rangers” to keep baboons within the Table Mountain National Park. In this study, we investigated the success of rangers' intervention in keeping baboons in their natural habitat. Based on our findings in year one, we recommended adjustments to the rangers' management strategy in year two. We recommended improved consensus of actions toward baboons (that is, when/where to herd them), and the construction of a baboon‐proof fence around one of the farms that provided a corridor to urban areas. During the 2 months following recommendations, these interventions combined resulted in a significant reduction in the time baboons spent in both urban and agricultural land. Our case study illustrates the importance of integrating research findings into ongoing management actions to improve both human livelihoods and baboon conservation through an adaptive management framework. We expect similar approaches to be beneficial in a wide range of species and contexts.

Species of open-space bats that are relatively large, such as bats from the genus Nyctalus, are considered as high-risk species for collisions with wind turbines (WTs). However, important information on their behaviour and movement ecology, such as the locations and altitudes at which they forage, is still fragmentary, while crucial for their conservation in light of the increasing threat posed by progressing WT construction. We adopted two different methods of microphone array recordings and GPS-tracking capturing data from different spatio-temporal scales in order to gain a complementary understanding of the echolocation and movement ecology of Nyctalus aviator, the largest open-space bat in Japan. Based on microphone array recordings, we found that echolocation calls during natural foraging are adapted for fast flight in open-space optimal for aerial-hawking. In addition, we attached a GPS tag that can simultaneously monitor feeding buzz occurrence, and confirmed that foraging occurred at 300 m altitude and that the flight altitude in mountainous areas is consistent with the turbine conflict zone, suggesting that the birdlike noctule is a high-risk species in Japan. Further investigations on this species could provide valuable insights into their foraging and movement ecology, facilitating the development of a risk assessment regarding WTs.

Abstract Despite spending most time underwater, the technology in use to track whales over large geographic ranges via satellite has been largely limited to locational data, with most applications focusing on characterizing their horizontal movements. We describe the development of the RDW tag, a new Argos-based satellite telemetry device that incorporates sensors for monitoring the movements and dive behavior of large whales over several months without requiring recovery. Based on an implantable design, the tag features a saltwater conductivity switch, a tri-axial accelerometer, and an optional pressure transducer, along with onboard software for data processing and detection of behavioral events or activities of interest for transmission. We configured the software to detect dives and create per-dive summaries describing behavioral events associated with feeding activities in rorqual whales. We conducted a validation by proxy of the dive summary and event detection algorithms using field data from a medium-duration archival tag. We also conducted a simulation exercise to examine how the expected data recovery would vary under different dive behavior scenarios and compared those results to empirical values from field deployments of the RDW tag on blue (Balaenoptera musculus) and humpback (Megaptera novaeangliae) whales. The dive summary algorithm accurately reported dive depth and duration, while the accuracy of the lunge-feeding event detection algorithm was dependent on the precision of the accelerometer data that was used, with a predicted accuracy of 0.74 for correctly classifying feeding dives from 1/64-G precision data and 0.95 from 1-mG precision data. Simulated data recovery was lower with sparser transmission schedules, shorter mean dive durations, and lower rates of successfully received transmissions. Empirical data recovery was lower than expected from the simulation, suggesting the effect of additional factors, such as data gaps. By measuring key aspects of the per-dive behavior of large whales over multi-month timescales of movement, the RDW tags provide the ability to monitor previously unobservable behaviors across entire geographic ranges, extending the applications of satellite telemetry devices to new areas of whale physiology, behavior, ecology, and conservation.

Abstract Background Bio-logging and animal tracking datasets continuously grow in volume and complexity, documenting animal behaviour and ecology in unprecedented extent and detail, but greatly increasing the challenge of extracting knowledge from the data obtained. A large variety of analysis methods are being developed, many of which in effect are inaccessible to potential users, because they remain unpublished, depend on proprietary software or require significant coding skills. Results We developed MoveApps, an open analysis platform for animal tracking data, to make sophisticated analytical tools accessible to a global community of movement ecologists and wildlife managers. As part of the Movebank ecosystem, MoveApps allows users to design and share workflows composed of analysis modules (Apps) that access and analyse tracking data. Users browse Apps, build workflows, customise parameters, execute analyses and access results through an intuitive web-based interface. Apps, coded in R or other programming languages, have been developed by the MoveApps team and can be contributed by anyone developing analysis code. They become available to all user of the platform. To allow long-term and cross-system reproducibility, Apps have public source code and are compiled and run in Docker containers that form the basis of a serverless cloud computing system. To support reproducible science and help contributors document and benefit from their efforts, workflows of Apps can be shared, published and archived with DOIs in the Movebank Data Repository. The platform was beta launched in spring 2021 and currently contains 49 Apps that are used by 316 registered users. We illustrate its use through two workflows that (1) provide a daily report on active tag deployments and (2) segment and map migratory movements. Conclusions The MoveApps platform is meant to empower the community to supply, exchange and use analysis code in an intuitive environment that allows fast and traceable results and feedback. By bringing together analytical experts developing movement analysis methods and code with those in need of tools to explore, answer questions and inform decisions based on data they collect, we intend to increase the pace of knowledge generation and integration to match the huge growth rate in bio-logging data acquisition.

Global Position System (GPS) tags are widely used in animal tracking to address far‐ranging ecological, behavioural and conservation‐related questions. However, GPS tags with transmitting functions via Global System for Mobile communications (GSM) and long‐lasting batteries are too cumbersome for animals with small body sizes. In addition, GSM is expensive with strict signal limitations in remote areas. Downloading locations from small GPS tags also requires animal recapture, which can result in large workloads. Combined, these problems limit the use of GPS tags in tracking small animals.To overcome these challenges, we present an integrated technology to pinpoint animal locations, especially those of medium‐ and small‐sized species. Our system consists of 3.7 g solar‐powered GPS tags (Nano), whose sampling frequency can be changed flexibly, and a combination of a receiver and an unmanned aerial vehicle (UAV) to retrieve data. The UAV carries the receiver that can retrieve data from Nanos via Bluetooth. Data are uploaded to a platform via GSM by the receiver and then downloaded by users in real time. Users can also directly download data from tags or the receiver via Bluetooth.We conducted stationary and field tests to assess the system's performance in Thousand Island Lake, China. Stationary tests were conducted at eight sites near the buildings, in open fields and on an island. Nanos can transmit data to the receiver within distances of 600–1000 m and at speeds of 6–72 records/s. The mean accuracy was 10.44–23.32 m and the fix success rates (FSRs) were larger than 97%. In field tests, we captured and attached Nanos on six Eurasian jays Garrulus glandarius. The FSRs were larger than 98%. Using the UAV reduced the time spent in field.Our system is labour‐saving and accurate in locating animals larger than 80 g as tested in a land‐bridge island system. Bluetooth transmission assisted by the UAV can overcome signal limitations and landscape blocks, and has the potential to be applied in inaccessible landscapes. The large memory of Nanos also allows for the retrieval of data from migratory species with strong site fidelity on their returns. [ABSTRACT FROM AUTHOR]

Despite urbanization's general erosion of biodiversity, towns and cities provide novel opportunities for some species. During the 20th century, gulls (Laridae) colonized urban areas around the world where they flourished. At the same time, some coastal populations declined. The reasons for this difference are not fully understood, partly because little is known about any ecological differences between urban and non‐urban gulls, such as their foraging ecology. Here we compare the movement ecology and habitat selection of Lesser Black‐backed Gulls Larus fuscus graellsii breeding at two neighbouring colonies – one urban and one coastal – in north‐west England. We used bird‐borne GPS loggers to first compare colony‐level movement behaviour and habitat selection and then investigated individual‐level habitat use. We observed clear colony‐level habitat segregation: urban breeders preferentially foraged in urban areas whereas coastal breeders foraged primarily in coastal habitats and avoided urban areas. Coastal breeders also had larger core and home‐ranges than urban breeders, possibly due to differences in colony size. However, we also found inter‐individual differences in habitat use, which may have important management implications. These findings suggest a link between nesting and foraging ecology, and thus management or environmental change altering food availability will impact gulls at the coastal and urban sites differently. [ABSTRACT FROM AUTHOR]