Estimates for energy expenditure in free-living animals using acceleration proxies: A reappraisal

Added Value of Sensor-Based Behavioural Monitoring in an Infectious Disease Study with Sheep Infected with Toxoplasma gondii

Sensor technologies are increasingly used to monitor laboratory animal behaviour. The aim of this study was to investigate the added value of using accelerometers and video to monitor the activity and drinking behaviour of three rams from 5 days before to 22 days after inoculation with Toxoplasma gondii. We computed the activity from accelerometer data as the vectorial dynamic body acceleration (VDBA). In addition, we assessed individual drinking behaviour from video, using frame differencing above the drinker to identify drinking bouts, and Aruco markers for individual identification. Four days after inoculation, rams developed fever and activity decreased. The daytime VDBA from days 4 to 10 was 60-80% of that before inoculation. Animal caretakers scored rams as lethargic on days 5 and 6 and, for one ram, also on the morning of day 7. Video analysis showed that each ram decreased its number of visits to the drinker, as well as its time spent at the drinker, by up to 50%. The fever and corresponding sickness behaviours lasted until day 10. Overall, while we recognize the limited conclusiveness due to the small number of animals, the sensor technologies provided continuous, individual, detailed, and objective data and offered additional insights as compared to routine observations. We recommend the wider implementation of such technologies in animal disease trials to refine experiments and guarantee the quality of experimental results.

Identifying animal behaviours from accelerometers: Improving predictive accuracy of machine learning by refining the variables selected, data frequency, and sample duration

Observing animals in the wild often poses extreme challenges, but animal-borne accelerometers are increasingly revealing unobservable behaviours. Automated machine learning streamlines behaviour identification from the substantial datasets generated during multi-animal, long-term studies; however, the accuracy of such models depends on the qualities of the training data. We examined how data processing influenced the predictive accuracy of random forest (RF) models, leveraging the easily observed domestic cat (Felis catus) as a model organism for terrestrial mammalian behaviours. Nine indoor domestic cats were equipped with collar-mounted tri-axial accelerometers, and behaviours were recorded alongside video footage. From this calibrated data, eight datasets were derived with (i) additional descriptive variables, (ii) altered frequencies of acceleration data (40 Hz vs. a mean over 1 s) and (iii) standardised durations of different behaviours. These training datasets were used to generate RF models that were validated against calibrated cat behaviours before identifying the behaviours of five free-ranging tag-equipped cats. These predictions were compared to those identified manually to validate the accuracy of the RF models for free-ranging animal behaviours. RF models accurately predicted the behaviours of indoor domestic cats (F-measure up to 0.96) with discernible improvements observed with post-data-collection processing. Additional variables, standardised durations of behaviours and higher recording frequencies improved model accuracy. However, prediction accuracy varied with different behaviours, where high-frequency models excelled in identifying fast-paced behaviours (e.g. locomotion), whereas lower-frequency models (1 Hz) more accurately identified slower, aperiodic behaviours such as grooming and feeding, particularly when examining free-ranging cat behaviours. While RF modelling offered a robust means of behaviour identification from accelerometer data, field validations were important to validate model accuracy for free-ranging individuals. Future studies may benefit from employing similar data processing methods that enhance RF behaviour identification accuracy, with extensive advantages for investigations into ecology, welfare and management of wild animals.

triact package for R: analyzing the lying behavior of cows from accelerometer data

Accelerometers are sensors proven to be useful to analyze the lying behavior of cows. For reasons of algorithm transparency and control, researchers often prefer to use their own data analysis scripts rather than proprietary software. We developed the triact R package that assists animal scientists in analyzing the lying behavior of cows from raw data recorded with a triaxial accelerometer (manufacturer agnostic) attached to a hind leg. In a user-friendly workflow, triact allows the determination of common measures for lying behavior including total lying duration, the number of lying bouts, and the mean duration of lying bouts. Further capabilities are the description of lying laterality and the calculation of proxies for the level of physical activity of the cow. In this publication we describe the functionality of triact and the rationales behind the implemented algorithms. The triact R package is developed as an open-source project and freely available via the CRAN repository.

Energetic trade-offs in migration decision-making, reproductive effort and subsequent parental care in a long-distance migratory bird

Migratory species trade-off long-distance movement with survival and reproduction, but the spatio-temporal scales at which these decisions occur are relatively unknown. Technological and statistical advances allow fine-scale study of animal decision-making, improving our understanding of possible causes and therefore conservation management. We quantified effects of reproductive preparation during spring migration on subsequent breeding outcomes, breeding outcomes on autumn migration characteristics and autumn migration characteristics on subsequent parental survival in Greenland white-fronted geese (Anser albifrons flavirostris). These are long-distance migratory birds with an approximately 50% population decline from 1999 to 2022. We deployed GPS-acceleration devices on adult females to quantify up to 5 years of individual decision-making throughout the annual cycle. Weather and habitat-use affected time spent feeding and overall dynamic body acceleration (i.e. energy expenditure) during spring and autumn. Geese that expended less energy and fed longer during spring were more likely to successfully reproduce. Geese with offspring expended more energy and fed for less time during autumn, potentially representing adverse fitness consequences of breeding. These behavioural comparisons among Greenland white-fronted geese improve our understanding of fitness trade-offs underlying abundance. We provide a reproducible framework for full annual cycle modelling using location and behaviour data, applicable to similarly studied migratory animals.

Ursids evolved dietary diversity without major alterations in metabolic rates

The diets of the eight species of ursids range from carnivory (e.g., polar bears, Ursus maritimus) to insectivory (e.g., sloth bears, Melursus ursinus), omnivory (e.g., brown bears, U. arctos), and herbivory (e.g., giant pandas, Ailuropoda melanoleuca). Dietary energy availability ranges from the high-fat, highly digestible, calorically dense diet of polar bears (~ 6.4 kcal digestible energy/g fresh weight) to the high-fiber, poorly digestible, calorically restricted diet (~ 0.7) of giant pandas. Thus, ursids provide the opportunity to examine the extent to which dietary energy drives evolution of energy metabolism in a closely related group of animals. We measured the daily energy expenditure (DEE) of captive brown bears in a relatively large, zoo-type enclosure and compared those values to previously published results on captive brown bears, captive and free-ranging polar bears, and captive and free-ranging giant pandas. We found that all three species have similar mass-specific DEE when travel distances and energy intake are normalized even though their diets differ dramatically and phylogenetic lineages are separated by millions of years. For giant pandas, the ability to engage in low-cost stationary foraging relative to more wide-ranging bears likely provided the necessary energy savings to become bamboo specialists without greatly altering their metabolic rate.

Advances in biologging can identify nuanced energetic costs and gains in predators

Foraging is a key driver of animal movement patterns, with specific challenges for predators which must search for mobile prey. These patterns are increasingly impacted by global changes, principally in land use and climate. Understanding the degree of flexibility in predator foraging and social strategies is pertinent to wildlife conservation under global change, including potential top-down effects on wider ecosystems. Here we propose key future research directions to better understand foraging strategies and social flexibility in predators. In particular, rapid continued advances in biologging technology are helping to record and understand dynamic behavioural and movement responses of animals to environmental changes, and their energetic consequences. Data collection can be optimised by calibrating behavioural interpretation methods in captive settings and strategic tagging decisions within and between social groups. Importantly, many species' social systems are increasingly being found to be more flexible than originally described in the literature, which may be more readily detectable through biologging approaches than behavioural observation. Integrating the effects of the physical landscape and biotic interactions will be key to explaining and predicting animal movements and energetic balance in a changing world.

Movement ecology of an endangered mesopredator in a mining landscape

BACKGROUND

Efficient movement and energy expenditure are vital for animal survival. Human disturbance can alter animal movement due to changes in resource availability and threats. Some animals can exploit anthropogenic disturbances for more efficient movement, while others face restricted or inefficient movement due to fragmentation of high-resource habitats, and risks associated with disturbed habitats. Mining, a major anthropogenic disturbance, removes natural habitats, introduces new landscape features, and alters resource distribution in the landscape. This study investigates the effect of mining on the movement of an endangered mesopredator, the northern quoll (Dasyurus hallucatus). Using GPS collars and accelerometers, we investigate their habitat selection and energy expenditure in an active mining landscape, to determine the effects of this disturbance on northern quolls.

METHODS

We fit northern quolls with GPS collars and accelerometers during breeding and non-breeding season at an active mine site in the Pilbara region of Western Australia. We investigated broad-scale movement by calculating the movement ranges of quolls using utilisation distributions at the 95% isopleth, and compared habitat types and environmental characteristics within observed movement ranges to the available landscape. We investigated fine-scale movement by quolls with integrated step selection functions, assessing the relative selection strength for each habitat covariate. Finally, we used piecewise structural equation modelling to analyse the influence of each habitat covariate on northern quoll energy expenditure.

RESULTS

At the broad scale, northern quolls predominantly used rugged, rocky habitats, and used mining habitats in proportion to their availability. However, at the fine scale, habitat use varied between breeding and non-breeding seasons. During the breeding season, quolls notably avoided mining habitats, whereas in the non-breeding season, they frequented mining habitats equally to rocky and riparian habitats, albeit at a higher energetic cost.

CONCLUSION

Mining impacts northern quolls by fragmenting favoured rocky habitats, increasing energy expenditure, and potentially impacting breeding dispersal. While mining habitats might offer limited resource opportunities in the non-breeding season, conservation efforts during active mining, including the creation of movement corridors and progressive habitat restoration would likely be useful. However, prioritising the preservation of natural rocky and riparian habitats in mining landscapes is vital for northern quoll conservation.

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.

Early and accumulated experience shape migration and flight in Egyptian vultures

Two types of experience affect animals' behavioral proficiencies and, accordingly, their fitness: early-life experience, an animal's environment during its early development, and acquired experience, the repeated practice of a specific task.1,2,3,4,5,6,7,8 Yet, how these two experience types and their interactions affect different proficiencies is still an open question. Here, we study the interactions between these two types of experience during migration, a critical and challenging period.9,10 We do so by comparing migratory proficiencies between birds with different early-life experiences and explain these differences by testing fine-scale flight mechanisms. We used data collected by GPS transmitters during 127 autumn migrations of 65 individuals to study the flight proficiencies of two groups of Egyptian vultures (Neophron percnopterus), a long-distance, soaring raptor.11,12 The two groups differed greatly in their early-life experience, one group being captive bred and the other wild hatched.13 Both groups improved their migratory performance with acquired experience, exhibiting shorter migration times, longer daily progress, and improved flight skills, specifically more efficient soaring-gliding behavior. The observed improvements were mostly apparent for captive-bred vultures, which were the least efficient during their first migration but were able to catch up in their migratory performance already in the second migration. Thus, we show how the strong negative effects of early-life experience were offset by acquired experience. Our findings uncover how the interaction between early-life and acquired experiences may shape animals' proficiencies and shed new light on the ontogeny of animal migration, suggesting possible effects of sensitive periods of learning on the acquisition of migratory skills.

Determining energy expenditure in a large seabird using accelerometry

The trade off between energy gained and expended is the foundation of understanding how, why and when animals perform any activity. Based on the concept that animal movements have an energetic cost, accelerometry is increasingly being used to estimate energy expenditure. However, validation of accelerometry as an accurate proxy for field metabolic rate in free-ranging species is limited. In the present study, Australasian gannets (Morus serrator) from the Pope's Eye colony (38°16'42″S 144°41'48″E), south-eastern Australia, were equipped with GPS and tri-axial accelerometers and dosed with doubly labelled water (DLW) to measure energy expenditure during normal behaviour for 3-5 days. The correlation between daily energy expenditure from the DLW and vectorial dynamic body acceleration (VeDBA) was high for both a simple correlation and activity-specific approaches (R2=0.75 and 0.80, respectively). Varying degrees of success were observed for estimating at-sea metabolic rate from accelerometry when removing time on land using published energy expenditure constants (R2=0.02) or activity-specific approaches (R2=0.42). The predictive capacity of energy expenditure models for total and at-sea periods was improved by the addition of total distance travelled and proportion of the sampling period spent at sea during the night, respectively (R2=0.61-0.82). These results indicate that accelerometry can be used to estimate daily energy expenditure in free-ranging gannets and its accuracy may depend on the inclusion of movement parameters not detected by accelerometry.

Direct measurement of cruising and burst swimming speeds of the shortfin mako shark (Isurus oxyrinchus) with estimates of field metabolic rate

The shortfin mako shark is a large-bodied pursuit predator thought to be capable of the highest swimming speeds of any elasmobranch and potentially one of the highest energetic demands of any marine fish. Nonetheless, few direct speed measurements have been reported for this species. Here, animal-borne bio-loggers attached to two mako sharks were used to provide direct measurements of swimming speeds, kinematics and thermal physiology. Mean sustained (cruising) speed was 0.90 m s-1 (±0.07 s.d.) with a mean tail-beat frequency (TBF) of 0.51 Hz (±0.16 s.d.). The maximum burst speed recorded was 5.02 m s-1 (TBFmax  = 3.65 Hz) from a 2 m long female. Burst swimming was sustained for 14 s (mean speed = 2.38 m s-1 ), leading to a 0.24°C increase in white muscle temperature in the 12.5 min after the burst. Routine field metabolic rate was estimated at 185.2 mg O2 kg-1  h-1 (at 18°C ambient temperature). Gliding behaviour (zero TBF) was more frequently observed after periods of high activity, especially after capture when internal (white muscle) temperature approached 21°C (ambient temperature: 18.3°C), indicating gliding probably functions as an energy recovery mechanism and limits further metabolic heat production. The results show shortfin mako sharks generally cruise at speeds similar to other endothermic fish - but faster than ectothermic sharks - with the maximum recorded burst speed being among the highest so far directly measured among sharks, tunas and billfishes. This newly recorded high-oxygen-demand performance of mako sharks suggests it may be particularly vulnerable to habitat loss due to climate-driven ocean deoxygenation.

Monitoring the Effect of Weed Encroachment on Cattle Behavior in Grazing Systems Using GPS Tracking Collars

Weed encroachment on grasslands can negatively affect herbage allowance and animal behavior, impacting livestock production. We used low-cost GPS collars fitted to twenty-four Angus crossbred steers to evaluate the effects of different levels of weed encroachment on animal activities and spatial distribution. The experiment was established with a randomized complete block design, with three treatments and four blocks. The treatments were paddocks free of weeds (weed-free), paddocks with weeds established in alternated strips (weed-strips), and paddocks with weeds spread throughout the entire area (weed-infested). Animals in weed-infested paddocks had reduced resting time and increased grazing time, distance traveled, and rate of travel (p < 0.05) compared to animals in weed-free paddocks. The spatial distribution of the animals was consistently greater in weed-free paddocks than in weed-strips or weed-infested areas. The effects of weed encroachment on animal activities were minimized after weed senescence at the end of the growing season. Pasture weed encroachment affected cattle behavior and their spatial distribution across the pasture, potentially impacting animal welfare. Further long-term studies are encouraged to evaluate the impacts of weed encroachment on animal performance and to quantify the effects of behavioral changes on animal energy balance.

Examination of head versus body heading may help clarify the extent to which animal movement pathways are structured by environmental cues?

Understanding the processes that determine how animals allocate time to space is a major challenge, although it is acknowledged that summed animal movement pathways over time must define space-time use. The critical question is then, what processes structure these pathways? Following the idea that turns within pathways might be based on environmentally determined decisions, we equipped Arabian oryx with head- and body-mounted tags to determine how they orientated their heads - which we posit is indicative of them assessing the environment - in relation to their movement paths, to investigate the role of environment scanning in path tortuosity. After simulating predators to verify that oryx look directly at objects of interest, we recorded that, during routine movement, > 60% of all turns in the animals' paths, before being executed, were preceded by a change in head heading that was not immediately mirrored by the body heading: The path turn angle (as indicated by the body heading) correlated with a prior change in head heading (with head heading being mirrored by subsequent turns in the path) twenty-one times more than when path turns occurred due to the animals adopting a body heading that went in the opposite direction to the change in head heading. Although we could not determine what the objects of interest were, and therefore the proposed reasons for turning, we suggest that this reflects the use of cephalic senses to detect advantageous environmental features (e.g. food) or to detect detrimental features (e.g. predators). The results of our pilot study suggest how turns might emerge in animal pathways and we propose that examination of points of inflection in highly resolved animal paths could represent decisions in landscapes and their examination could enhance our understanding of how animal pathways are structured.

Ponds as experimental arenas for studying animal movement: current research and future prospects

Animal movement is a multifaceted process that occurs for multiple reasons with powerful consequences for food web and ecosystem dynamics. New paradigms and technical innovations have recently pervaded the field, providing increasingly powerful means to deliver fine-scale movement data, attracting renewed interest. Specifically in the aquatic environment, tracking with acoustic telemetry now provides integral spatiotemporal information to follow individual movements in the wild. Yet, this technology also holds great promise for experimental studies, enhancing our ability to truly establish cause-and-effect relationships. Here, we argue that ponds with well-defined borders (i.e. "islands in a sea of land") are particularly well suited for this purpose. To support our argument, we also discuss recent experiences from studies conducted in an innovative experimental infrastructure, composed of replicated ponds equipped with modern aquatic telemetry systems that allow for unparalleled insights into the movement patterns of individual animals.

Intense scuba diving does not alter activity patterns of predatory reef fish: Evidence from a protected tourism hotspot

The rise of nature-based tourism has provided a new avenue for disturbing animal behaviour, especially in protected areas. One of the most important tourism sectors in aquatic environments is scuba diving, an activity considered sustainable given its non-extractive nature and capability of bringing relevant socio-economic benefits to local communities. However, knowledge about its impact on the activity patterns of aquatic animals is still scarce. Here, we used biotelemetry techniques to assess the importance of scuba diving in modulating the activity patterns of the dusky grouper (Epinephelus marginatus, Lowe, 1834), a marine predatory fish of high interest for fishing and tourism. We implemented Hidden Markov Models (HMMs) on high-resolution acceleration data using a temporal and spatial control while controlling for a set of environmental variables (i.e. photoperiod, time-of-day, moon phase, temperature, wave height, and intensity and direction of marine currents) within a multiple-use marine protected area, and diving tourism hot-spot, of the western Mediterranean Sea. Our results underlined the more decisive influence of environmental-related stressors on the activity patterns of the dusky grouper compared to the impact of scuba diving. A high heterogeneity existed in the response against most of the stressors, including the presence of scuba divers. Overall, the activity of dusky grouper was higher at night than at day, showing a positive relationship with wave height, water temperature, and current intensity and a negative one with the moon phase. Remarkably, our findings, based on novel biotelemetry tools, differed substantially from the common wisdom accepted for this species. In conclusion, there is no clear evidence of scuba divers influence on the general activity patterns of the dusky grouper. Beyond their relevance from an ecological perspective, these results provide useful insights for the sustainable management of coastal resources, suggesting that scuba diving, when properly carried out, can represent an important sector to foster for the blue growth of coastal communities.

What are the Metabolic Rates of Marine Mammals and What Factors Impact this Value: A review

Over the past several decades, scientists have constructed bioenergetic models for marine mammals to assess potential population-level consequences following exposure to a disturbance, stressor, or environmental change, such as under the Population Consequences of Disturbance (pCOD) framework. The animal's metabolic rate (rate of energy expenditure) is a cornerstone for these models, yet the cryptic lifestyles of marine mammals, particularly cetaceans, have limited our ability to quantify basal (BMR) and field (FMR) metabolic rates using accepted 'gold standard' approaches (indirect calorimeter via oxygen consumption and doubly labeled water, respectively). Thus, alternate methods have been used to quantify marine mammal metabolic rates, such as extrapolating from known allometric relationships (e.g. Kleiber's mouse to elephant curve) and developing predictive relationships between energy expenditure and physiological or behavioral variables. To understand our current knowledge of marine mammal metabolic rates, we conducted a literature review (1900-2023) to quantify the magnitude and variation of metabolic rates across marine mammal groups. A compilation of data from studies using 'gold standard' methods revealed that BMR and FMR of different marine mammal species ranges from 0.2 to 3.6 and 1.1 to 6.1 x Kleiber, respectively. Mean BMR and FMR varied across taxa; for both measures odontocete levels were intermediate to higher values for otariids and lower values of phocids. Moreover, multiple intrinsic (e.g. age, sex, reproduction, molt, individual) and extrinsic (e.g. food availability, water temperature, season) factors, as well as individual behaviors (e.g. animal at water's surface or submerged, activity level, dive effort and at-sea behaviors) impact the magnitude of these rates. This review provides scientists and managers with a range of reliable metabolic rates for several marine mammal groups as well as an understanding of the factors that influence metabolism to improve the discernment for inputs into future bioenergetic models.

Responses to Reduced Feeding Frequency in Captive-Born Cheetahs (Acinonyx jubatus): Implications for Behavioural and Physiological Stress and Gastrointestinal Health

Unnatural diet composition and frequent feeding regimes may play an aetiological role in the multiple diseases prevalent in captive cheetahs. This study investigated the responses of captive-born (hand-reared) cheetahs (n = 6) to a reduced feeding frequency schedule distinguished by offering larger quantities of food less frequently. The study cheetahs were fed four once-daily meals per week during the 3-week treatment period, followed by a 3-week control period in which they were fed two daily rations six days a week. Total weekly food intake was maintained throughout the study. Variations in behaviour, faecal consistency score (FCS), and faecal glucocorticoid metabolite concentration were measured. Less frequent feeding resulted in higher FCS (p < 0.01) and locomotory behaviour (p < 0.05) among the studied cheetahs. Faecal glucocorticoid metabolite concentration demonstrated an initial acute stress response to the change in feeding frequency (p < 0.05) and subsequent adaptation. The results of the FCS analysis suggest that the more natural feeding pattern could have benefited the studied cheetahs' gastrointestinal health without a significant behavioural or physiological stress response overall to the change in feeding frequency.

Effect of harness design for tag attachment on the flight performance of five soaring species

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[Formula: see text] 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.

A Summer Heat Wave Reduced Activity, Heart Rate, and Autumn Body Mass in a Cold-Adapted Ungulate

AbstractHeat waves are becoming more frequent across the globe and may impose severe thermoregulatory challenges for endotherms. Heat stress can induce both behavioral and physiological responses, which may result in energy deficits with potential fitness consequences. We studied the responses of reindeer (Rangifer tarandus tarandus), a cold-adapted ungulate, to a record-breaking heat wave in northern Finland. Activity, heart rate, subcutaneous body temperature, and body mass data were collected for 14 adult females. The post-heat wave autumn body masses were then analyzed against longitudinal body mass records for the herd from 1990 to 2021. With increasing air temperature during the day, reindeer became less active and had reduced heart rate and increased body temperature, reflecting both behavioral and physiological responses to heat stress. Although they increased activity in the late afternoon, they failed to compensate for lost foraging time on the hottest days (daily mean temperature ≥20°C), and total time active was reduced by 9%. After the heat wave, the mean September body mass of herd females (69.7±6.6 kg, n=52) was on average 16.4% ± 4.8% lower than predicted (83.4±6.0 kg). Among focal females, individuals with the lowest levels of activity during the heat wave had the greatest mass loss during summer. We show how heat waves impose a thermoregulatory challenge on endotherms, resulting in mass loss, potentially as a result of the loss of foraging time. While it is well known that environmental conditions affect large herbivore fitness indirectly through decreased forage quality and limited water supply, direct effects of heat may be increasingly common in a warming climate.

Individual variability in diving behavior of the Black-vented Shearwater in an ever-changing habitat

Oceanic mesoscale systems are characterized by inherent variability. Climatic change adds entropy to this system, making it a highly variable environment in which marine species live. Being at the higher levels of the food chain, predators maximize their performance through plastic foraging strategies. Individual variability within a population and the possible repeatability across time and space may provide stability in a population facing environmental changes. Therefore, variability and repeatability of behaviors, particularly diving behavior, could play an important role in understanding the adaptation pathway of a species. This study focuses on characterizing the frequency and timing of different dives (termed simple and complex) and how these are influenced by individual and environmental characteristics (sea surface temperature, chlorophyll a concentration, bathymetry, salinity, and Ekman transport). This study is based on GPS and accelerometer-recorded information from a breeding group of 59 Black-vented Shearwater and examine consistency in diving behavior at both individual and sex levels across four different breeding seasons. The species was found to be the best performing free diver in the Puffinus genus with a maximum dive duration of 88 s. Among the environmental variables assessed, a relationship was found with active upwelling conditions enhancing low energetic cost diving, on the contrary, reduced upwelling and warmer superficial waters induce more energetically demanding diving affecting diving performance and ultimately body conditions. The body conditions of Black-vented Shearwaters in 2016 were worse than in subsequent years, in 2016, deepest and longest complex dives were recorded, while simple dives were longer in 2017-2019. Nevertheless, the species' plasticity allows at least part of the population to breed and feed during warmer events. While carry-over effects have already been reported, the effect of more frequent warm events is still unknown.

Worse sleep and increased energy expenditure yet no movement changes in sub-urban wild boar experiencing an influx of human visitors (anthropulse) during the COVID-19 pandemic

Expansion of urban areas, landscape transformation and increasing human outdoor activities strongly affect wildlife behaviour. The outbreak of the COVID-19 pandemic in particular led to drastic changes in human behaviour, exposing wildlife around the world to either reduced or increased human presence, potentially altering animal behaviour. Here, we investigate behavioural responses of wild boar (Sus scrofa) to changing numbers of human visitors to a suburban forest near Prague, Czech Republic, during the first 2.5 years of the COVID-19 epidemic (April 2019-November 2021). We used bio-logging and movement data of 63 GPS-collared wild boar and human visitation data based on an automatic counter installed in the field. We hypothesised that higher levels of human leisure activity will have a disturbing effect on wild boar behaviour manifested in increased movements and ranging, energy spent, and disrupted sleep patterns. Interestingly, whilst the number of people visiting the forest varied by two orders of magnitude (from 36 to 3431 people weekly), even high levels of human presence (>2000 visitors per week) did not affect weekly distance travelled, home range size, and maximum displacement of wild boar. Instead, individuals spent 41 % more energy at high levels of human presence (>2000 visitors per week), with more erratic sleep patterns, characterised by shorter and more frequent sleeping bouts. Our results highlight multifaceted effects of increased human activities ('anthropulses'), such as those related to COVID-19 countermeasures, on animal behaviour. High human pressure may not affect animal movements or habitat use, especially in highly adaptable species such as wild boar, but may disrupt animal activity rhythms, with potentially detrimental fitness consequences. Such subtle behavioural responses can be overlooked if using only standard tracking technology.

Contaminant-by-environment interactive effects on animal behavior in the context of global change: Evidence from avian behavioral ecotoxicology

The potential for chemical contaminant exposure to interact with other stressors to affect animal behavioral responses to environmental variability is of mounting concern in the context of anthropogenic environmental change. We systematically reviewed the avian literature to evaluate evidence for contaminant-by-environment interactive effects on animal behavior, as birds are prominent models in behavioral ecotoxicology and global change research. We found that only 17 of 156 (10.9 %) avian behavioral ecotoxicological studies have explored contaminant-by-environment interactions. However, 13 (76.5 %) have found evidence for interactive effects, suggesting that contaminant-by-environment interactive effects on behavior are understudied but important. We draw on our review to develop a conceptual framework to understand such interactive effects from a behavioral reaction norm perspective. Our framework highlights four patterns in reaction norm shapes that can underlie contaminant-by-environment interactive effects on behavior, termed exacerbation, inhibition, mitigation and convergence. First, contamination can render individuals unable to maintain critical behaviors across gradients in additional stressors, exacerbating behavioral change (reaction norms steeper) and generating synergy. Second, contamination can inhibit behavioral adjustment to other stressors, antagonizing behavioral plasticity (reaction norms shallower). Third, a second stressor can mitigate (antagonize) toxicological effects of contamination, causing steeper reaction norms in highly contaminated individuals, with improvement of performance upon exposure to additional stress. Fourth, contamination can limit behavioral plasticity in response to permissive conditions, such that performance of more and less contaminated individuals converges under more stressful conditions. Diverse mechanisms might underlie such shape differences in reaction norms, including combined effects of contaminants and other stressors on endocrinology, energy balance, sensory systems, and physiological and cognitive limits. To encourage more research, we outline how the types of contaminant-by-environment interactive effects proposed in our framework might operate across multiple behavioral domains. We conclude by leveraging our review and framework to suggest priorities for future research.

Combining accelerometry with allometry for estimating daily energy expenditure in joules when in-lab calibration is unavailable

BACKGROUND

All behaviour requires energy, and measuring energy expenditure in standard units (joules) is key to linking behaviour to ecological processes. Animal-borne accelerometers are commonly used to infer proxies of energy expenditure, termed 'dynamic body acceleration' (DBA). However, converting acceleration proxies (m/s2) to standard units (watts) involves costly in-lab respirometry measurements, and there is a lack of viable substitutes for empirical calibration relationships when these are unavailable.

METHODS

We used past allometric work quantifying energy expenditure during resting and locomotion as a function of body mass to calibrate DBA. We used the resulting 'power calibration equation' to estimate daily energy expenditure (DEE) using two models: (1) locomotion data-based linear calibration applied to the waking period, and Kleiber's law applied to the sleeping period (ACTIWAKE), and (2) locomotion and resting data-based linear calibration applied to the 24-h period (ACTIREST24). Since both models require locomotion speed information, we developed an algorithm to estimate speed from accelerometer, gyroscope, and behavioural annotation data. We applied these methods to estimate DEE in free-ranging meerkats (Suricata suricatta), and compared model estimates with published DEE measurements made using doubly labelled water (DLW) on the same meerkat population.

RESULTS

ACTIWAKE's DEE estimates did not differ significantly from DLW (t(19) = - 1.25; P = 0.22), while ACTIREST24's estimates did (t(19) = - 2.38; P = 0.028). Both models underestimated DEE compared to DLW: ACTIWAKE by 14% and ACTIREST by 26%. The inter-individual spread in model estimates of DEE (s.d. 1-2% of mean) was lower than that in DLW (s.d. 33% of mean).

CONCLUSIONS

We found that linear locomotion-based calibration applied to the waking period, and a 'flat' resting metabolic rate applied to the sleeping period can provide realistic joule estimates of DEE in terrestrial mammals. The underestimation and lower spread in model estimates compared to DLW likely arise because the accelerometer only captures movement-related energy expenditure, whereas DLW is an integrated measure. Our study offers new tools to incorporate body mass (through allometry), and changes in behavioural time budgets and intra-behaviour changes in intensity (through DBA) in acceleration-based field assessments of daily energy expenditure.

The behaviour and activity budgets of two sympatric sloths; Bradypus variegatus and Choloepus hoffmanni

It is usually beneficial for species to restrict activity to a particular phase of the 24-hour cycle as this enables the development of morphological and behavioural adaptations to enhance survival under specific biotic and abiotic conditions. Sloth activity patterns are thought to be strongly related to the environmental conditions due to the metabolic consequences of having a low and highly variable core body temperature. Understanding the drivers of sloth activity and their ability to withstand environmental fluctuations is of growing importance for the development of effective conservation measures, particularly when we consider the vulnerability of tropical ecosystems to climate change and the escalating impacts of anthropogenic activities in South and Central America. Unfortunately, the cryptic nature of sloths makes long term observational research difficult and so there is very little existing literature examining the behavioural ecology of wild sloths. Here, we used micro data loggers to continuously record, for the first time, the behaviour of both Bradypus and Choloepus sloths over periods of days to weeks. We investigate how fluctuations in the environmental conditions affect the activity of sloths inhabiting a lowland rainforest on the Caribbean coast of Costa Rica and examined how this might relate to their low power lifestyle. Both Bradypus and Choloepus sloths were found to be cathemeral in their activity, with high levels of between-individual and within-individual variation in the amounts of time spent active, and in the temporal distribution of activity over the 24-hour cycle. Daily temperature did not affect activity, although Bradypus sloths were found to show increased nocturnal activity on colder nights, and on nights following colder days. Our results demonstrate a distinct lack of synchronicity within the same population, and we suggest that this pattern provides sloths with the flexibility to exploit favourable environmental conditions whilst reducing the threat of predation.

Supervised versus unsupervised approaches to classification of accelerometry data

Sophisticated animal-borne sensor systems are increasingly providing novel insight into how animals behave and move. Despite their widespread use in ecology, the diversity and expanding quality and quantity of data they produce have created a need for robust analytical methods for biological interpretation. Machine learning tools are often used to meet this need. However, their relative effectiveness is not well known and, in the case of unsupervised tools, given that they do not use validation data, their accuracy can be difficult to assess. We evaluated the effectiveness of supervised (n = 6), semi-supervised (n = 1), and unsupervised (n = 2) approaches to analyzing accelerometry data collected from critically endangered California condors (Gymnogyps californianus). Unsupervised K-means and EM (expectation-maximization) clustering approaches performed poorly, with adequate classification accuracies of <0.8 but very low values for kappa statistics (range: -0.02 to 0.06). The semi-supervised nearest mean classifier was moderately effective at classification, with an overall classification accuracy of 0.61 but effective classification only of two of the four behavioral classes. Supervised random forest (RF) and k-nearest neighbor (kNN) machine learning models were most effective at classification across all behavior types, with overall accuracies >0.81. Kappa statistics were also highest for RF and kNN, in most cases substantially greater than for other modeling approaches. Unsupervised modeling, which is commonly used for the classification of a priori-defined behaviors in telemetry data, can provide useful information but likely is instead better suited to post hoc definition of generalized behavioral states. This work also shows the potential for substantial variation in classification accuracy among different machine learning approaches and among different metrics of accuracy. As such, when analyzing biotelemetry data, best practices appear to call for the evaluation of several machine learning techniques and several measures of accuracy for each dataset under consideration.

The impact of shape and attachment position of biologging devices in Northern Bald Ibises

Background

The impact of biologging devices on the aerodynamics or hydrodynamics of animals is still poorly understood. This stands in marked contrast to the ever more extensive use of such technologies in wild-living animals. Recently, increasing concerns have been raised about the impairing effects of these devices on the animals concerned. In the early days of biotelemetry, attention was focused solely on reducing weight, but now aerodynamic effects are also increasingly being considered. To investigate these effects, we trained Northern Bald Ibises to fly in a wind tunnel in which we measured heart rate and dynamic body acceleration (VeDBA) as proxies for energy expenditure in relation to different logger shapes and wind flow directions.

Results

Our data provide evidence that the position of biologging devices significantly influence the flight distances, and the shape of biologging devices has a considerable effect on heart rate and VeDBA, both of which have been used as proxies for energy expenditure. Unfavorable shape and positioning go beyond merely affecting the effort required during flapping flight. The energetically probably more important effect is that the devices impair the bird's ability to glide or soar and thus force them to perform the energetically much more demanding flapping flight more frequently. This effect was more pronounced in rising air than in horizontal airflow. A complementary study with wild Northern Bald Ibises during spring migration provides evidence that the position of the devices on the bird's back affects the length of the flight stages. Birds carrying the devices on the upper back, fixed by wing-loop harnesses, had significantly shorter flight stages compared to birds with a more caudally positioned device, fixed by leg-loop harnesses.

Conclusion

The attachment of biologging devices on birds affects their performance and behavior and thus may influence their fitness and mortality. Our results show that detrimental effects can be reduced with relatively little effort, in particular through a strictly aerodynamic design of the housing and increased consideration of aerodynamics when attaching the device to the body. In birds, the attachment of biologging devices via leg loops to the lower back is clearly preferable to the common attachment via wing loops on the upper back, even if this affects the efficiency of the solar panels. Nevertheless, the importance of drag reduction may vary between systems, as the benefits of having a biologging devices close to the center of gravity may outweigh the increase in drag that this involves. Overall, more research is required in this field. This is both in the interest of animal welfare and of avoiding biasing the quality of the collected data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40317-023-00322-5.

Biologging and Biotelemetry: Tools for Understanding the Lives and Environments of Marine Animals

Addressing important questions in animal ecology, physiology, and environmental science often requires in situ information from wild animals. This difficulty is being overcome by biologging and biotelemetry, or the use of miniaturized animal-borne sensors. Although early studies recorded only simple parameters of animal movement, advanced devices and analytical methods can now provide rich information on individual and group behavior, internal states, and the surrounding environment of free-ranging animals, especially those in marine systems. We summarize the history of technologies used to track marine animals. We then identify seven major research categories of marine biologging and biotelemetry and explain significant achievements, as well as future opportunities. Big data approaches via international collaborations will be key to tackling global environmental issues (e.g., climate change impacts), and curiosity about the secret lives of marine animals will also remain a major driver of biologging and biotelemetry studies.

Impact of test, vaccinate or remove protocol on home ranges and nightly movements of badgers a medium density population

In the British Isles, the European badger (Meles meles) is thought to be the primary wildlife reservoir of bovine tuberculosis (bTB), an endemic disease in cattle. Test, vaccinate or remove ('TVR') of bTB test-positive badgers, has been suggested to be a potentially useful protocol to reduce bTB incidence in cattle. However, the practice of removing or culling badgers is controversial both for ethical reasons and because there is no consistent observed effect on bTB levels in cattle. While removing badgers reduces population density, it may also result in disruption of their social behaviour, increase their ranging, and lead to greater intra- and inter-species bTB transmission. This effect has been recorded in high badger density areas, such as in southwest England. However, little is known about how TVR affects the behaviour and movement of badgers within a medium density population, such as those that occur in Northern Ireland (NI), which the current study aimed to examine. During 2014-2017, badger ranging behaviours were examined prior to and during a TVR protocol in NI. Nightly distances travelled by 38 individuals were determined using Global Positioning System (GPS) measurements of animal tracks and GPS-enhanced dead-reckoned tracks. The latter was calculated using GPS, tri-axial accelerometer and tri-axial magnetometer data loggers attached to animals. Home range and core home range size were measured using 95% and 50% autocorrelated kernel density estimates, respectively, based on location fixes. TVR was not associated with measured increases in either distances travelled per night (mean = 3.31 ± 2.64 km) or home range size (95% mean = 1.56 ± 0.62 km², 50% mean = 0.39 ± 0.62 km²) over the four years of study. However, following trapping, mean distances travelled per night increased by up to 44% eight days post capture. Findings differ from those observed in higher density badger populations in England, in which badger ranging increased following culling. Whilst we did not assess behaviours of individual badgers, possible reasons why no differences in home range size were observed include higher inherent 'social fluidity' in Irish populations whereby movements are less restricted by habitat saturation and/or that the numbers removed did not reach a threshold that might induce increases in ranging behaviour. Nevertheless, short-term behavioural disruption from trapping was observed, which led to significant increases in the movements of individual animals within their home range. Whether or not TVR may alter badger behaviours remains to be seen, but it would be better to utilise solutions such as oral vaccination of badgers and/or cattle as well as increased biosecurity to limit bTB transmission, which may be less likely to cause interference and thereby reduce the likelihood of bTB transmission.

Mercury Contamination Challenges the Behavioral Response of a Keystone Species to Arctic Climate Change

Combined effects of multiple, climate change-associated stressors are of mounting concern, especially in Arctic ecosystems. Elevated mercury (Hg) exposure in Arctic animals could affect behavioral responses to changes in foraging landscapes caused by climate change, generating interactive effects on behavior and population resilience. We investigated this hypothesis in little auks (Alle alle), a keystone Arctic seabird. We compiled behavioral data for 44 birds across 5 years using accelerometers while also quantifying blood Hg and environmental conditions. Warm sea surface temperature (SST) and low sea ice coverage reshaped time activity budgets (TABs) and diving patterns, causing decreased resting, increased flight, and longer dives. Mercury contamination was not associated with TABs. However, highly contaminated birds lengthened interdive breaks when making long dives, suggesting Hg-induced physiological limitations. As dive durations increased with warm SST, subtle toxicological effects threaten to increasingly constrain diving and foraging efficiency as climate change progresses, with ecosystem-wide repercussions.

Time-varying effects of local weather on behavior and probability of breeding deferral in two Arctic-nesting goose populations

Arctic-nesting geese face energetic challenges during spring migration, including ecological barriers and weather conditions (e.g., precipitation and temperature), which in long-lived species can lead to a trade-off to defer reproduction in favor of greater survival. We used GPS location and acceleration data collected from 35 greater white-fronted geese of the North American midcontinent and Greenland populations at spring migration stopovers, and novel applications of Bayesian dynamic linear models to test daily effects of minimum temperature and precipitation on energy expenditure (i.e., overall dynamic body acceleration, ODBA) and proportion of time spent feeding (PTF), then examined the daily and additive importance of ODBA and PTF on probability of breeding deferral using stochastic antecedent models. We expected distinct responses in behavior and probability of breeding deferral between and within populations due to differences in stopover area availability. Time-varying coefficients of weather conditions were variable between ODBA and PTF, and often did not show consistent patterns among birds, indicating plasticity in how individuals respond to conditions. An increase in antecedent ODBA was associated with a slightly increased probability of deferral in midcontinent geese but not Greenland geese. Probability of deferral decreased with increased PTF in both populations. We did not detect any differentially important time periods. These results suggest either that movements and behavior throughout spring migration do not explain breeding deferral or that ecological linkages between bird decisions during spring and subsequent breeding deferral were different between populations and across migration but occurred at different time scales than those we examined.

Energetic and behavioral consequences of migration: an empirical evaluation in the context of the full annual cycle

Seasonal migrations are used by diverse animal taxa, yet the costs and benefits of migrating have rarely been empirically examined. The aim of this study was to determine how migration influences two ecological currencies, energy expenditure and time allocated towards different behaviors, in a full annual cycle context. We compare these currencies among lesser black-backed gulls that range from short- (< 250 km) to long-distance (> 4500 km) migrants. Daily time-activity budgets were reconstructed from tri-axial acceleration and GPS, which, in conjunction with a bioenergetics model to estimate thermoregulatory costs, enabled us to estimate daily energy expenditure throughout the year. We found that migration strategy had no effect on annual energy expenditure, however, energy expenditure through time deviated more from the annual average as migration distance increased. Patterns in time-activity budgets were similar across strategies, suggesting migration strategy does not limit behavioral adjustments required for other annual cycle stages (breeding, molt, wintering). Variation among individuals using the same strategy was high, suggesting that daily behavioral decisions (e.g. foraging strategy) contribute more towards energy expenditure than an individual's migration strategy. These findings provide unprecedented new understanding regarding the relative importance of fine versus broad-scale behavioral strategies towards annual energy expenditures.

On the Development of a Wearable Animal Monitor

Animal monitoring is a task traditionally performed by pastoralists, as a way of ensuring the safety and well-being of animals; a tremendously arduous and lonely task, it requires long walks and extended periods of contact with the animals. The Internet of Things and the possibility of applying sensors to different kinds of devices, in particular the use of wearable sensors, has proven not only to be less invasive to the animals, but also to have a low cost and to be quite efficient. The present work analyses the most impactful monitored features in the behavior learning process and their learning results. It especially addresses the impact of a gyroscope, which heavily influences the cost of the collar. Based on the chosen set of sensors, a learning model is subsequently established, and the learning outcomes are analyzed. Finally, the animal behavior prediction capability of the learning model (which was based on the sensed data of adult animals) is additionally subjected and evaluated in a scenario featuring younger animals. Results suggest that not only is it possible to accurately classify these behaviors (with a balanced accuracy around 91%), but that removing the gyroscope can be advantageous. Results additionally show a positive contribution of the thermometer in behavior identification but evidences the need for further confirmation in future work, considering different seasons of different years and scenarios including more diverse animals' behavior.

Barnacle geese Branta leucopsis breeding on Novaya Zemlya: current distribution and population size estimated from tracking data

The Russian breeding population of barnacle geese Branta leucopsis has shown a rapid increase in numbers since 1980, which has coincided with a southwest-wards breeding range expansion within the Russian Arctic. Here barnacle geese also started to occupy coastal and marsh land habitats, in which they were not know to nest on their traditional breeding grounds. While these changes have been well documented by studies and observations throughout the new breeding range of barnacle geese, observations are lacking from the traditional breeding grounds on Novaya Zemlya, as this area is remote and difficult to access. This is especially relevant given rapid climate warming in this area, which may impact local distribution and population size. We used GPS-tracking and behavioural biologging data from 46 individual barnacle geese captured on their wintering grounds to locate nest sites in the Russian Arctic and study nesting distribution in 2008–2010 and 2018–2020. Extrapolating from nest counts on Kolguev Island, we estimate the breeding population on Novaya Zemlya in 2018–2020 to range around 75,250 pairs although the confidence interval around this estimate was large. A comparison with the historical size of the barnacle goose population suggests an increase in the breeding population on Novaya Zemlya, corresponding with changes in other areas of the breeding range. Our results show that many barnacle geese on Novaya Zemlya currently nest on lowland tundra on Gusinaya Zemlya Peninsula. This region has been occupied by barnacle geese only since 1990 and appears to be mainly available for nesting in years with early spring. Tracking data are a valuable tool to increase our knowledge of remote locations, but counts of breeding individuals or nests are needed to further corroborate estimates of breeding populations based on tracking data.

Developing a classification system to assign activity states to two species of freshwater turtles

Research in ecology often requires robust assessment of animal behaviour, but classifying behavioural patterns in free-ranging animals and in natural environments can be especially challenging. New miniaturised bio-logging devices such as accelerometers are increasingly available to record animal behaviour remotely, and thereby address the gap in knowledge related to behaviour of free-ranging animals. However, validation of these data is rarely conducted and classification model transferability across closely-related species is often not tested. Here, we validated accelerometer and water sensor data to classify activity states in two free-ranging freshwater turtle species (Blanding's turtle, Emydoidea blandingii, and Painted turtle, Chrysemys picta). First, using only accelerometer data, we developed a decision tree to separate motion from motionless states, and second, we included water sensor data to classify the animal as being motionless or in-motion on land or in water. We found that accelerometers separated in-motion from motionless behaviour with > 83% accuracy, whereas models also including water sensor data predicted states in terrestrial and aquatic locations with > 77% accuracy. Despite differences in values separating activity states between the two species, we found high model transferability allowing cross-species application of classification models. Note that reducing sampling frequency did not affect predictive accuracy of our models up to a sampling frequency of 0.0625 Hz. We conclude that the use of accelerometers in animal research is promising, but requires prior data validation and development of robust classification models, and whenever possible cross-species assessment should be conducted to establish model generalisability.

The role of individual variability on the predictive performance of machine learning applied to large bio-logging datasets

Animal-borne tagging (bio-logging) generates large and complex datasets. In particular, accelerometer tags, which provide information on behaviour and energy expenditure of wild animals, produce high-resolution multi-dimensional data, and can be challenging to analyse. We tested the performance of commonly used artificial intelligence tools on datasets of increasing volume and dimensionality. By collecting bio-logging data across several sampling seasons, datasets are inherently characterized by inter-individual variability. Such information should be considered when predicting behaviour. We integrated both unsupervised and supervised machine learning approaches to predict behaviours in two penguin species. The classified behaviours obtained from the unsupervised approach Expectation Maximisation were used to train the supervised approach Random Forest. We assessed agreement between the approaches, the performance of Random Forest on unknown data and the implications for the calculation of energy expenditure. Consideration of behavioural variability resulted in high agreement (> 80%) in behavioural classifications and minimal differences in energy expenditure estimates. However, some outliers with < 70% of agreement, highlighted how behaviours characterized by signal similarity are confused. We advise the broad bio-logging community, approaching these large datasets, to be cautious when upscaling predictions, as this might lead to less accurate estimates of behaviour and energy expenditure.

Tag-based estimates of bottlenose dolphin swimming behavior and energetics

Current estimates of marine mammal hydrodynamic forces tend to be made using camera-based kinematic data for a limited number of fluke strokes during a prescribed swimming task. In contrast, biologging tag data yield kinematic measurements from thousands of strokes, enabling new insights into swimming behavior and mechanics. However, there have been limited tag-based estimates of mechanical work and power. In this work, we investigated bottlenose dolphin (Tursiops truncatus) swimming behavior using tag-measured kinematics and a hydrodynamic model to estimate propulsive power, work and cost of transport. Movement data were collected from six animals during prescribed straight-line swimming trials to investigate swimming mechanics over a range of sustained speeds (1.9-6.1 m s-1). Propulsive power ranged from 66 W to 3.8 kW over 282 total trials. During the lap trials, the dolphins swam at depths that mitigated wave drag, reducing overall drag throughout these mid- to high-speed tasks. Data were also collected from four individuals during undirected daytime (08:30-18:00 h) swimming to examine how self-selected movement strategies are used to modulate energetic efficiency and effort. Overall, self-selected swimming speeds (individual means ranging from 1.0 to 1.96 m s-1) tended to minimize cost of transport, and were on the lower range of animal-preferred speeds reported in literature. The results indicate that these dolphins moderate propulsive effort and efficiency through a combination of speed and depth regulation. This work provides new insights into dolphin swimming behavior in both prescribed tasks and self-selected swimming, and presents a path forward for continuous estimates of mechanical work and power from wild animals.

Interacting lethal and nonlethal human activities shape complex risk tolerance behaviors in a mountain herbivore

Animals perceive human activities as risky and generally respond with fear-induced proactive behaviors to buffer the circadian patterns of lethal and nonlethal disturbances, such as diel migrations (DMs) between risky places during safe nighttime and safer places during risky daytime. However, such responses potentially incur costs through movement or reduced foraging time, so individuals should adjust their tolerance when human activities are harmless, through habituation. Yet this is a challenging cognitive task when lethal and nonlethal risks co-occur, forming complex landscapes of fear. The consequences of this human-induced complexity have, however, rarely been assessed. We studied the individual DM dynamics of chamois (Rupicapra rupicapra rupicapra), 89 GPS-tracked individual-years, from/to trails in the French Alps in areas with co-occurring lethal (hunting) and nonlethal (hiking and skiing) disturbances, with different intensities across seasons. We developed a conceptual framework relying on the risk-disturbance hypothesis and habituation to predict tolerance adjustments of chamois under various disturbance contexts and across contrasted seasonal periods. Based on spatial and statistical analyses combining periodograms and multinomial logistic models, we found that DM in relation to distance to a trail was a consistent response by chamois (~85% of individuals) to avoid human disturbance during daytime, especially during the hiking and hunting periods. Such behavior revealed a low tolerance of most chamois to human activities, although there was considerable interindividual heterogeneity in DM. Interestingly, there was an increased tolerance among the most disturbed diel migrants, potentially through habituation, with chamois performing shorter DMs in areas highly disturbed by hikers. Crucially, chamois that were most human-habituated during the hiking period remained more tolerant in the subsequent harvesting period, which could increase their risk of being harvested. In contrast, individuals less tolerant to hiking performed longer DMs when hunting risk increased, and compared to hiking, hunting exacerbated the threshold distance to trails triggering DMs. No carryover effect of hunting beyond the hunting period was observed. In conclusion, complex human-induced landscapes of fear with co-occurring disturbances by nature-based tourism and hunting may shape unexpected patterns of tolerance to human activities, whereby animal tolerance could become potentially deleterious for individual survival.

Wake respirometry allows breath-by-breath assessment of ventilation and CO2 production in unrestrained animals

Quantifying stress and energetic responses in animals are major challenges, as existing methods lack temporal resolution and elevate animal stress. We propose "wake respirometry," a new method of quantifying fine-scale changes in CO2 production in unrestrained animals, using a nondispersive infrared CO2 sensor positioned downwind of the animal, i.e., in its wake. We parameterize the dispersion of CO2 in wakes using known CO2 flow rates and wind speeds. Tests with three bird species in a wind tunnel demonstrated that the system can resolve breath-by-breath changes in CO2 concentration, with clear exhalation signatures increasing in period and integral with body size. Changes in physiological state were detectable following handling, flight, and exposure to a perceived threat. We discuss the potential of wake respirometry to quantify stress and respiratory patterns in wild animals and provide suggestions for estimating behavior-specific metabolic rates via full integration of CO2 production across the wake.

Key questions in marine mammal bioenergetics

Bioenergetic approaches are increasingly used to understand how marine mammal populations could be affected by a changing and disturbed aquatic environment. There remain considerable gaps in our knowledge of marine mammal bioenergetics, which hinder the application of bioenergetic studies to inform policy decisions. We conducted a priority-setting exercise to identify high-priority unanswered questions in marine mammal bioenergetics, with an emphasis on questions relevant to conservation and management. Electronic communication and a virtual workshop were used to solicit and collate potential research questions from the marine mammal bioenergetic community. From a final list of 39 questions, 11 were identified as 'key' questions because they received votes from at least 50% of survey participants. Key questions included those related to energy intake (prey landscapes, exposure to human activities) and expenditure (field metabolic rate, exposure to human activities, lactation, time-activity budgets), energy allocation priorities, metrics of body condition and relationships with survival and reproductive success and extrapolation of data from one species to another. Existing tools to address key questions include labelled water, animal-borne sensors, mark-resight data from long-term research programs, environmental DNA and unmanned vehicles. Further validation of existing approaches and development of new methodologies are needed to comprehensively address some key questions, particularly for cetaceans. The identification of these key questions can provide a guiding framework to set research priorities, which ultimately may yield more accurate information to inform policies and better conserve marine mammal populations.

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.

Highlighting when animals expend excessive energy for travel using Dynamic Body Acceleration

Travel represents a major cost for many animals so there should be selection pressure for it to be efficient – at minimum cost. However, animals sometimes exceed minimum travel costs for reasons that must be correspondingly important. We use Dynamic Body Acceleration (DBA), an acceleration-based metric, as a proxy for movement-based power, in tandem with vertical velocity (rate of change in depth) in a shark (Rhincodon typus) to derive the minimum estimated power required to swim at defined vertical velocities. We show how subtraction of measured DBA from the estimated minimum power for any given vertical velocity provides a “proxy for power above minimum” metric (PPA_min), highlighting when these animals travel above minimum power. We suggest that the adoption of this metric across species has value in identifying where and when animals are subject to compelling conditions that lead them to deviate from ostensibly judicious energy expenditure.

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Plots of vertical speed vs DBA in sharks show swimming with minimum power

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DBA values above this minimum indicate higher speeds or increases in drag

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Linked to space use, this can identify regions and times of excess power use

Multivariate analysis of biologging data reveals the environmental determinants of diving behaviour in a marine reptile

Diving behaviour of 'surfacers' such as sea snakes, cetaceans and turtles is complex and multi-dimensional, thus may be better captured by multi-sensor biologging data. However, analysing these large multi-faceted datasets remains challenging, though a high priority. We used high-resolution multi-sensor biologging data to provide the first detailed description of the environmental influences on flatback turtle (Natator depressus) diving behaviour, during its foraging life-history stage. We developed an analytical method to investigate seasonal, diel and tidal effects on diving behaviour for 24 adult flatback turtles tagged with biologgers. We extracted 16 dive variables associated with three-dimensional and kinematic characteristics for 4128 dives. K-means and hierarchical cluster analyses failed to identify distinct dive types. Instead, principal component analysis objectively condensed the dive variables, removing collinearity and highlighting the main features of diving behaviour. Generalized additive mixed models of the main principal components identified significant seasonal, diel and tidal effects on flatback turtle diving behaviour. Flatback turtles altered their diving behaviour in response to extreme tidal and water temperature ranges, displaying thermoregulation and predator avoidance strategies while likely optimizing foraging in this challenging environment. This study demonstrates an alternative statistical technique for objectively interpreting diving behaviour from multivariate collinear data derived from biologgers.

Empirical Evidence for Energy Efficiency Using Intermittent Gliding Flight in Northern Bald Ibises

Birds face exceptionally high energy demands during their flight. One visible feature of some species is alternating between flapping and gliding, which should allow them to save energy. To date, there is no empirical evidence of an energetic benefit to this. To understand the physiology behind the strategy, we equipped hand-raised Northern Bald Ibises (Geronticus eremita) with data loggers during human-guided migration. We monitored the position of the birds, wingbeats, overall dynamic body acceleration (ODBA), and heart rates as a proxy for energy expenditure. The energy expenditure was significantly affected by the length of flapping and gliding bouts. A pronounced decrease in heart rate was measured after already 1 s of gliding. Additionally, the heart rate at flapping bouts up to 30 s increased steadily but stabilized thereafter. The gilding proportion during intermittent flight affected the energy saving compared to continuous flapping. At a gliding proportion of about 20%, we measured a maximum of 11% saving based on heart rate measurement. At higher gliding proportions, the additional energy saving was negligible. Furthermore, as during flight, not all energy is used for mechanical work, we found a greater decrease rate of ODBA at different gliding proportions compared to heart rate. Nevertheless, the combination of the two methods is essential to determine birds’ movement and energy expenditure. This study provides empirical evidence that intermittent flight is energetically beneficial and can reduce the high costs of flights.

Recent trends in movement ecology of animals and human mobility

Movement is fundamental to life, shaping population dynamics, biodiversity patterns, and ecosystem structure. In 2008, the movement ecology framework (MEF Nathan et al. in PNAS 105(49):19052-19059, 2008) introduced an integrative theory of organismal movement-linking internal state, motion capacity, and navigation capacity to external factors-which has been recognized as a milestone in the field. Since then, the study of movement experienced a technological boom, which provided massive quantities of tracking data of both animal and human movement globally and at ever finer spatio-temporal resolutions. In this work, we provide a quantitative assessment of the state of research within the MEF, focusing on animal movement, including humans and invertebrates, and excluding movement of plants and microorganisms. Using a text mining approach, we digitally scanned the contents of [Formula: see text] papers from 2009 to 2018 available online, identified tools and methods used, and assessed linkages between all components of the MEF. Over the past decade, the publication rate has increased considerably, along with major technological changes, such as an increased use of GPS devices and accelerometers and a majority of studies now using the R software environment for statistical computing. However, animal movement research still largely focuses on the effect of environmental factors on movement, with motion and navigation continuing to receive little attention. A search of topics based on words featured in abstracts revealed a clustering of papers among marine and terrestrial realms, as well as applications and methods across taxa. We discuss the potential for technological and methodological advances in the field to lead to more integrated and interdisciplinary research and an increased exploration of key movement processes such as navigation, as well as the evolutionary, physiological, and life-history consequences of movement.

Covariation between glucocorticoids, behaviour and immunity supports the pace-of-life syndrome hypothesis: an experimental approach

The biomedical literature has consistently highlighted that long-term elevation of glucocorticoids might impair immune functions. However, patterns are less clear in wild animals. Here, we re-explored the stress-immunity relationship considering the potential effects of behavioural profiles. Thirteen captive roe deer (Capreolus capreolus) were monitored over an eight-week period encompassing two capture events. We assessed how changes in baseline faecal cortisol metabolite (FCM) concentrations following a standardized capture protocol and an immune challenge using anti-rabies vaccination affected changes in 13 immune parameters of innate and adaptive immunity, and whether these changes in baseline FCM levels and immune parameters related to behavioural profiles. We found that individuals with increased baseline FCM levels also exhibited increased immunity and were characterized by more reactive behavioural profiles (low activity levels, docility to manipulation and neophilia). Our results suggest that the immunity of large mammals may be influenced by glucocorticoids, but also behavioural profiles, as it is predicted by the pace-of-life syndrome hypothesis. Our results highlight the need to consider covariations between behaviour, immunity and glucocorticoids in order to improve our understanding of the among-individual variability in the stress-immunity relationships observed in wildlife, as they may be underpinned by different life-history strategies.

Accelerating animal energetics: High dive costs in a small seabird disrupt the dynamic body acceleration - energy expenditure relationship

Accelerometry has been widely used to estimate energy expenditure in a broad array of terrestrial and aquatic species. However, a recent reappraisal of the method showed that relationships between dynamic body acceleration (DBA) and energy expenditure weaken as the proportion of non-mechanical costs increase. Aquatic air breathing species often exemplify this pattern, as buoyancy, thermoregulation and other physiological mechanisms disproportionately affect oxygen consumption during dives. Combining biologging with the doubly-labelled water method, we simultaneously recorded daily energy expenditure (DEE) and triaxial acceleration in one of the world's smallest wing-propelled breath-hold divers, the dovekie (Alle alle). These data were used to estimate the activity-specific costs of flying and diving and to test whether overall dynamic body acceleration (ODBA) is a reliable predictor of DEE in this abundant seabird. Average DEE for chick-rearing dovekies was 604±119 kJ/d across both sampling years. Despite recording lower stroke frequencies for diving than for flying (in line with allometric predictions for auks), dive costs were estimated to surpass flight costs in our sample of birds (flying: 7.24, diving: 9.37 X BMR). As expected, ODBA was not an effective predictor of DEE in this species. However, accelerometer-derived time budgets did accurately estimate DEE in dovekies. This work represents an empirical example of how the apparent energetic costs of buoyancy and thermoregulation limit the effectiveness of ODBA as the sole predictor of overall energy expenditure in small shallow-diving endotherms.

Ecological inference using data from accelerometers needs careful protocols

Accelerometers in animal-attached tags are powerful tools in behavioural ecology, they can be used to determine behaviour and provide proxies for movement-based energy expenditure. Researchers are collecting and archiving data across systems, seasons and device types. However, using data repositories to draw ecological inference requires a good understanding of the error introduced according to sensor type and position on the study animal and protocols for error assessment and minimisation.Using laboratory trials, we examine the absolute accuracy of tri-axial accelerometers and determine how inaccuracies impact measurements of dynamic body acceleration (DBA), a proxy for energy expenditure, in human participants. We then examine how tag type and placement affect the acceleration signal in birds, using pigeons Columba livia flying in a wind tunnel, with tags mounted simultaneously in two positions, and back- and tail-mounted tags deployed on wild kittiwakes Rissa tridactyla. Finally, we present a case study where two generations of tag were deployed using different attachment procedures on red-tailed tropicbirds Phaethon rubricauda foraging in different seasons.Bench tests showed that individual acceleration axes required a two-level correction to eliminate measurement error. This resulted in DBA differences of up to 5% between calibrated and uncalibrated tags for humans walking at a range of speeds. Device position was associated with greater variation in DBA, with upper and lower back-mounted tags varying by 9% in pigeons, and tail- and back-mounted tags varying by 13% in kittiwakes. The tropicbird study highlighted the difficulties of attributing changes in signal amplitude to a single factor when confounding influences tend to covary, as DBA varied by 25% between seasons.Accelerometer accuracy, tag placement and attachment critically affect the signal amplitude and thereby the ability of the system to detect biologically meaningful phenomena. We propose a simple method to calibrate accelerometers that can be executed under field conditions. This should be used prior to deployments and archived with resulting data. We also suggest a way that researchers can assess accuracy in previously collected data, and caution that variable tag placement and attachment can increase sensor noise and even generate trends that have no biological meaning.