Swimming through sand: using accelerometers to observe the cryptic, pre-emergence life-stage of sea turtle hatchlings

Animals that hatch within a subterranean nest, such as turtle hatchlings, expend some of their limited energy reserves digging out through sand or soil to reach the surface. In sea turtles, this emergence process can take the hatchlings 3-7 days. However, we have a poor understanding of this process as it is difficult to observe what is occurring underground. Here, we utilize a novel method to characterize digging-out behaviour: affixing an accelerometer directly to newly hatched green turtles (Chelonia mydas) to record movement until nest emergence. Our data revealed that buried hatchlings maintained a head-up orientation but did not move in the expected left and right swaying motion associated with alternating limb crawling. Rather, they moved using dorsal-ventral heaving and pitching as if swimming vertically through the sand to the surface. Movement activity was irregular and brief, interspersed by many short periods of inactivity, mostly lasting less than 10 min. The first 24 h of head-up activity displayed no diel patterns, but the last 24 h prior to emergence involved more intense movement during night-time hours compared with daytime hours. Thus, our results add valuable new insight, and in some cases change previous assumptions, regarding the digging behaviours during the egg-to-emergence life stage in sea turtles.

Incorporating otolith-isotope inferred field metabolic rate into conservation strategies

Fluctuating ocean conditions are rearranging whole networks of marine communities-from individual-level physiological thresholds to ecosystem function. Physiological studies support predictions from individual-level responses (biochemical, cellular, tissue, respiratory potential) based on laboratory experiments. The otolith-isotope method of recovering field metabolic rate has recently filled a gap for the bony fishes, linking otolith stable isotope composition to in situ oxygen consumption and experienced temperature estimates. Here, we review the otolith-isotope method focusing on the biochemical and physiological processes that yield estimates of field metabolic rate. We identify a multidisciplinary pathway in the application of this method, providing concrete research goals (field, modeling) aimed at linking individual-level physiological data to higher levels of biological organization. We hope that this review will provide researchers with a transdisciplinary 'roadmap', guiding the use of the otolith-isotope method to bridge the gap between individual-level physiology, observational field studies, and modeling efforts, while ensuring that in situ data is central in marine policy-making aimed at mitigating climatic and anthropogenic threats.

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.

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.

Too big to study? The biologging approach to understanding the behavioural energetics of ocean giants

Wild animals are under selective pressure to optimise energy budgets; therefore, quantifying energy expenditure, intake and allocation to specific activities is important if we are to understand how animals survive in their environment. One approach toward estimating energy budgets has involved measuring oxygen consumption rates under controlled conditions and constructing allometric relationships across species. However, studying 'giant' marine vertebrates (e.g. pelagic sharks, whales) in this way is logistically difficult or impossible. An alternative approach involves the use of increasingly sophisticated electronic tags that have allowed recordings of behaviour, internal states and the surrounding environment of marine animals. This Review outlines how we could study the energy expenditure and intake of free-living ocean giants using this 'biologging' technology. There are kinematic, physiological and theoretical approaches for estimating energy expenditure, each of which has merits and limitations. Importantly, tag-derived energy proxies can hardly be validated against oxygen consumption rates for giant species. The proxies are thus qualitative, rather than quantitative, estimates of energy expenditure, and have more limited utilities. Despite this limitation, these proxies allow us to study the energetics of ocean giants in their behavioural context, providing insight into how these animals optimise their energy budgets under natural conditions. We also outline how information on energy intake and foraging behaviour can be gained from tag data. These methods are becoming increasingly important owing to the natural and anthropogenic environmental changes faced by ocean giants that can alter their energy budgets, fitness and, ultimately, population sizes.

A computational framework for studying energetics and resource management in sea turtle migration and autonomous systems

Sea turtles complete migrations across vast distances, covering entire ocean basins. To track these migrations, satellite tracking tags are attached to their shells. The impact of these tags must be considered to ensure that turtles' natural behavior is not artificially and adversely impacted through tag-related drag, and that the data collected by a small sample of sea turtles accurately represents the larger population. Additionally, it can be difficult to study animal energetics in the field over large migration distances. In this work, we modify a computational behavior model to study how satellite tracking tags affect turtle migration behavior. Our agent based model contains synthetic magnetic field environments that are used for navigation cues, an ocean current, resource distributions that represent locations of food, and an agent that attempts to migrate to several different goals. The agent loses energy as it progresses, and searches for the resource distributions to replenish itself. Our novel simulation framework demonstrates the relationship between an agent's available energy capacity, its energy consumption based on mechanical power expended, and its ability to navigate to all migratory goal points. This study can be utilized to (1) probe the impacts of an animal's energy capacity and foraging behavior on its resulting navigation and ecology, (2) guide future satellite tag designs, and (3) develop usage recommendations for a suitable tracking tag based on the type of experiment being conducted. Our model can be expanded beyond sea turtles to study other marine species (e.g., sharks, whales). Additionally, this model could be expanded to other domains within the marine environment. For example, it could be modified to examine design trade-offs in remotely operated vehicles (ROVs), which share many of the same operational constraints as sea turtles and other migratory species.

Activity of loggerhead turtles during the U-shaped dive: insights using angular velocity metrics

Understanding the behavioural ecology of endangered taxa can inform conservation strategies. The activity budgets of the loggerhead turtle Caretta caretta are still poorly understood because many tracking methods show only horizontal displacement and ignore dives and associated behaviours. However, time-depth recorders have enabled researchers to identify flat, U-shaped dives (or type 1a dives) and these are conventionally labelled as resting dives on the seabed because they involve no vertical displacement of the animal. Video- and acceleration-based studies have demonstrated this is not always true. Focusing on sea turtles nesting on the Cabo Verde archipelago, we describe a new metric derived from magnetometer data, absolute angular velocity, that integrates indices of angular rotation in the horizontal plane to infer activity. Using this metric, we evaluated the variation in putative resting behaviours during the bottom phase of type 1a dives for 5 individuals over 13 to 17 d at sea during a single inter-nesting interval (over 75 turtle d in total). We defined absolute resting within the bottom phase of type 1a dives as periods with no discernible acceleration or angular movement. Whilst absolute resting constituted a significant proportion of each turtle’s time budget for this 1a dive type, turtles allocated 16-38% of their bottom time to activity, with many dives being episodic, comprised of intermittent bouts of rest and rotational activity. This implies that previously considered resting behaviours are complex and need to be accounted for in energy budgets, particularly since energy budgets may impact conservation strategies.

Accounting for body mass effects in the estimation of field metabolic rates from body acceleration

Dynamic body acceleration (DBA), measured through animal-attached tags, has emerged as a powerful method for estimating field metabolic rates of free-ranging individuals. Following respirometry to calibrate oxygen consumption rate (ṀO2) with DBA under controlled conditions, predictive models can be applied to DBA data collected from free-ranging individuals. However, laboratory calibrations are generally performed on a relatively narrow size range of animals, which may introduce biases if predictive models are applied to differently sized individuals in the field. Here, we tested the mass dependence of the ṀO2-DBA relationship to develop an experimental framework for the estimation of field metabolic rates when organisms differ in size. We performed respirometry experiments with individuals spanning one order of magnitude in body mass (1.74-17.15 kg) and used a two-stage modelling process to assess the intraspecific scale dependence of the ṀO2-DBA relationship and incorporate such dependencies into the coefficients of ṀO2 predictive models. The final predictive model showed scale dependence; the slope of the ṀO2-DBA relationship was strongly allometric (M1.55), whereas the intercept term scaled closer to isometry (M1.08). Using bootstrapping and simulations, we evaluated the performance of this coefficient-corrected model against commonly used methods of accounting for mass effects on the ṀO2-DBA relationship and found the lowest error and bias in the coefficient-corrected approach. The strong scale dependence of the ṀO2-DBA relationship indicates that caution must be exercised when models developed using one size class are applied to individuals of different sizes.

Drivers of realized satellite tracking duration in marine turtles

BACKGROUND

Satellite tags have revolutionized our understanding of marine animal movements. However, tags may stop transmitting for many reasons and little research has rigorously examined tag failure. Using a long-term, large-scale, multi-species dataset, we evaluated factors influencing tracking duration of satellite tags to inform study design for future tracking studies.

METHODS

We leveraged data on battery status transmitted with location data, recapture events, and number of transmission days to probabilistically quantify multiple potential causes of failure (i.e., battery failure, premature detachment, and tag damage/fouling). We used a combination of logistic regressions and an ordinary linear model including several predictor variables (i.e., tag type, battery life, species, sex, size, and foraging region).

RESULTS

We examined subsets of data from 360 satellite tags encompassing 86,889 tracking days deployed on four species of marine turtles throughout the Gulf of Mexico, Caribbean, and Bahamas from 2008 to 2019. Only 4.1% of batteries died before failure due to other causes. We observed species-specific variation in how long tags remain attached: hawksbills retained 50% of their tags for 1649 days (95% CI 995-1800), loggerheads for 584 days (95% CI 400-690), and green turtles for 294 days (95% CI 198-450). Estimated tracking duration varied by foraging region (Caribbean: 385 days; Bahamas: 356; southern Gulf of Mexico [SGOM]: 276, northern Gulf of Mexico [NGOM]: 177). Additionally, we documented species-specific variation in estimated tracking duration among foraging regions. Based on sensor data, within the Gulf of Mexico, across species, we estimated that 50% of tags began to foul after 83 95% CI (70-120) days.

CONCLUSIONS

The main factor that limited tracking duration was tag damage (i.e., fouling and/or antenna breakage). Turtles that spent most of their time in the Gulf of Mexico had shorter tracking durations than those in the Bahamas and Caribbean, with shortest durations observed in the NGOM. Additionally, tracking duration varied by species, likely as a result of behaviors that damage tags. This information will help researchers, tag companies, permitting agencies, and funders better predict expected tracking durations, improving study designs for imperiled marine turtles. Our results highlight the heterogeneity in telemetry device longevity, and we provide a framework for researchers to evaluate telemetry devices with respect to their study objectives.

Open-flow respirometry under field conditions: How does the airflow through the nest influence our results?

Open-flow respirometry is a common method to measure oxygen-uptake as a proxy of energy expenditure of organisms in real-time. Although most often used in the laboratory it has seen increasing application under field conditions. Air is drawn or pushed through a metabolic chamber or the nest with the animal, and the O₂ depletion and/or CO₂ accumulation in the air is analysed to calculate metabolic rate and energy expenditure. Under field conditions, animals are often measured within the microclimate of their nest and in contrast to laboratory work, the temperature of the air entering the nest cannot be controlled. Thus, the aim of our study was to determine the explanatory power of respirometry in a set-up mimicking field conditions. We measured O₂ consumption of 14 laboratory mice (Mus musculus) using three different flow rates [50 L*h^-1 (834 mL*min^-1), 60 L*h^-1 (1000 mL*min^-1) and 70 L*h^-1 (1167 mL*min^-1)] and two different temperatures of the inflowing air; either the same as the temperature inside the metabolic chamber (no temperature differential; 20 °C), or cooler (temperature differential of 10 °C). Our results show that the energy expenditure of the mice did not change significantly in relation to a cooler airflow, nor was it affected by different flow rates, despite a slight, but significant decrease of about 1.5 °C in chamber temperature with the cooler airflow. Our study emphasises the validity of the results obtained by open-flow respirometry when investigating energy budgets and physiological responses of animals to ambient conditions. Nevertheless, subtle changes in chamber temperature in response to changes in the temperature and flow rate of the air pulled or pushed through the system were detectable. Thus, constant airflow during open-flow respirometry and consequent changes in nest/chamber temperature should be measured.

Hormonal correlates of the annual cycle of activity and body temperature in the South-American tegu lizard (Salvator merianae)

Life history transitions and hormones are known to interact and influence many aspects of animal physiology and behavior. The South-American tegu lizard (Salvator merianae) exhibits a profound seasonal shift in metabolism and body temperature, characterized by high daily activity during warmer months, including reproductive endothermy in spring, and metabolic suppression during hibernation in winter. This makes S. merianae an interesting subject for studies of interrelationships between endocrinology and seasonal changes in physiology/behavior. We investigated how plasma concentrations of hormones involved in regulation of energy metabolism (thyroid hormones T₄ and T₃; corticosterone) and reproduction (testosterone in males and estrogen/progesterone in females) correlate with activity and body temperature (Tb) across the annual cycle of captive held S. merianae in semi-natural conditions. In our initial model, thyroid hormones and corticosterone showed a positive relationship with activity and Tb with independent of sex: T₃ positively correlated with activity and Tb, while T₄ and corticosterone correlated positively with changes in Tb only. This suggests that thyroid hormones and glucocorticoids may be involved in metabolic transitions of annual cycle events. When accounting for sex-steroid hormones, our sex separated models showed a positive relationship between testosterone and Tb in males and progesterone and activity in females. Coupling seasonal endocrine measures with activity and Tb may expand our understanding of the relationship between animal's physiology and its environment. Manipulative experiments are required in order to unveil the directionality of influences existing among abiotic factors and the hormonal signaling of annual cyclicity in physiology/behavior.

Modeling the emergence of migratory corridors and foraging hot spots of the green sea turtle

Environmental factors shape the spatial distribution and dynamics of populations. Understanding how these factors interact with movement behavior is critical for efficient conservation, in particular for migratory species. Adult female green sea turtles, Chelonia mydas, migrate between foraging and nesting sites that are generally separated by thousands of kilometers. As an emblematic endangered species, green turtles have been intensively studied, with a focus on nesting, migration, and foraging. Nevertheless, few attempts integrated these behaviors and their trade-offs by considering the spatial configurations of foraging and nesting grounds as well as environmental heterogeneity like oceanic currents and food distribution. We developed an individual-based model to investigate the impact of local environmental conditions on emerging migratory corridors and reproductive output and to thereby identify conservation priority sites. The model integrates movement, nesting, and foraging behavior. Despite being largely conceptual, the model captured realistic movement patterns which confirm field studies. The spatial distribution of migratory corridors and foraging hot spots was mostly constrained by features of the regional landscape, such as nesting site locations, distribution of feeding patches, and oceanic currents. These constraints also explained the mixing patterns in regional forager communities. By implementing alternative decision strategies of the turtles, we found that foraging site fidelity and nesting investment, two characteristics of green turtles' biology, are favorable strategies under unpredictable environmental conditions affecting their habitats. Based on our results, we propose specific guidelines for the regional conservation of green turtles as well as future research suggestions advancing spatial ecology of sea turtles. Being implemented in an easy to learn open-source software, our model can coevolve with the collection and analysis of new data on energy budget and movement into a generic tool for sea turtle research and conservation. Our modeling approach could also be useful for supporting the conservation of other migratory marine animals.

Physiological determinants of the internesting interval in sea turtles: a novel 'water-limitation' hypothesis

The internesting interval separates successive clutches of sea turtle eggs, and its duration varies both among and within species. Here, we review the potential physiological limits to this interval, and develop the hypothesis that desalination capacity limits the internesting interval owing to the requirement for water deposition in eggs. Sea turtles deposit 1-4 kg of water per clutch in egg albumen; for most species, this represents about 2% of adult body mass. We calculate how quickly turtles can recover this water by estimating maximal salt excretion rates, metabolic water production and urinary losses. From this water balance perspective, the 'water-limitation' hypothesis is plausible for green turtles but not for leatherbacks. Some plasma biochemistry studies indicate dehydration in sea turtles during the nesting season, although this is not a universal finding and these data have rarely been collected during the internesting interval itself. There is mixed support for a trade-off between clutch size and the length of the interval. We conclude that the 'water-limitation' hypothesis is plausible for most sea turtle species, but requires direct experimentation.

Using Respiratory Sinus Arrhythmia to Estimate Inspired Tidal Volume in the Bottlenose Dolphin (Tursiops truncatus)

Man-made environmental change may have significant impact on apex predators, like marine mammals. Thus, it is important to assess the physiological boundaries for survival in these species, and assess how climate change may affect foraging efficiency and the limits for survival. In the current study, we investigated whether the respiratory sinus arrhythmia (RSA) could estimate tidal volume (V T) in resting bottlenose dolphins (Tursiops truncatus). For this purpose, we measured respiratory flow and electrocardiogram (ECG) in five adult bottlenose dolphins at rest while breathing voluntarily. Initially, an exponential decay function, using three parameters (baseline heart rate, the change in heart rate following a breath, and an exponential decay constant) was used to describe the temporal change in instantaneous heart rate following a breath. The three descriptors, in addition to body mass, were used to develop a Generalized Additive Model (GAM) to predict the inspired tidal volume (V Tinsp). The GAM allowed us to predict V Tinsp with an average ( ± SD) overestimate of 3 ± 2%. A jackknife sensitivity analysis, where 4 of the five dolphins were used to fit the GAM and the 5th dolphin used to make predictions resulted in an average overestimate of 2 ± 10%. Future studies should be used to assess whether similar relationships exist in active animals, allowing V T to be studied in free-ranging animals provided that heart rate can be measured.

Resting Metabolic Rate and Lung Function in Wild Offshore Common Bottlenose Dolphins, Tursiops truncatus, Near Bermuda

Diving mammals have evolved a suite of physiological adaptations to manage respiratory gases during extended breath-hold dives. To test the hypothesis that offshore bottlenose dolphins have evolved physiological adaptations to improve their ability for extended deep dives and as protection for lung barotrauma, we investigated the lung function and respiratory physiology of four wild common bottlenose dolphins (Tursiops truncatus) near the island of Bermuda. We measured blood hematocrit (Hct, %), resting metabolic rate (RMR, l O₂ ⋅ min^-1), tidal volume (V_T, l), respiratory frequency (f_R, breaths ⋅ min^-1), respiratory flow (l ⋅ min^-1), and dynamic lung compliance (C_L, l ⋅ cmH₂O^-1) in air and in water, and compared measurements with published results from coastal, shallow-diving dolphins. We found that offshore dolphins had greater Hct (56 ± 2%) compared to shallow-diving bottlenose dolphins (range: 30–49%), thus resulting in a greater O₂ storage capacity and longer aerobic diving duration. Contrary to our hypothesis, the specific C_L (sC_L, 0.30 ± 0.12 cmH₂O^-1) was not different between populations. Neither the mass-specific RMR (3.0 ± 1.7 ml O₂ ⋅ min^-1 ⋅ kg^-1) nor V_T (23.0 ± 3.7 ml ⋅ kg^-1) were different from coastal ecotype bottlenose dolphins, both in the wild and under managed care, suggesting that deep-diving dolphins do not have metabolic or respiratory adaptations that differ from the shallow-diving ecotypes. The lack of respiratory adaptations for deep diving further support the recently developed hypothesis that gas management in cetaceans is not entirely passive but governed by alteration in the ventilation-perfusion matching, which allows for selective gas exchange to protect against diving related problems such as decompression sickness.

Combined use of two supervised learning algorithms to model sea turtle behaviours from tri-axial acceleration data

Accelerometers are becoming ever more important sensors in animal-attached technology, providing data that allow determination of body posture and movement and thereby helping to elucidate behaviour in animals that are difficult to observe. We sought to validate the identification of sea turtle behaviours from accelerometer signals by deploying tags on the carapace of a juvenile loggerhead (Caretta caretta), an adult hawksbill (Eretmochelys imbricata) and an adult green turtle (Chelonia mydas) at Aquarium La Rochelle, France. We recorded tri-axial acceleration at 50 Hz for each species for a full day while two fixed cameras recorded their behaviours. We identified behaviours from the acceleration data using two different supervised learning algorithms, Random Forest and Classification And Regression Tree (CART), treating the data from the adult animals as separate from the juvenile data. We achieved a global accuracy of 81.30% for the adult hawksbill and green turtle CART model and 71.63% for the juvenile loggerhead, identifying 10 and 12 different behaviours, respectively. Equivalent figures were 86.96% for the adult hawksbill and green turtle Random Forest model and 79.49% for the juvenile loggerhead, for the same behaviours. The use of Random Forest combined with CART algorithms allowed us to understand the decision rules implicated in behaviour discrimination, and thus remove or group together some 'confused' or under--represented behaviours in order to get the most accurate models. This study is the first to validate accelerometer data to identify turtle behaviours and the approach can now be tested on other captive sea turtle species.

DNA metabarcoding and microscopic analyses of sea turtles biofilms: Complementary to understand turtle behavior

Sea turtles are distributed in tropical and subtropical seas worldwide. They play several ecological roles and are considered important indicators of the health of marine ecosystems. Studying epibiotic diatoms living on turtle shells suggestively has great potential in the study of turtle behavior because diatoms are always there. However, diatom identification at the species level is time consuming, requires well-trained specialists, and there is a high probability of finding new taxa growing on turtle shells, which makes identification tricky. An alternative approach based on DNA barcoding and high throughput sequencing (HTS), metabarcoding, has been developed in recent years to identify species at the community level by using a DNA reference library. The suitabilities of morphological and molecular approaches were compared. Diatom assemblages were sampled from seven juvenile green turtles (Chelonia mydas) from Mayotte Island, France. The structures of the epibiotic diatom assemblages differed between both approaches. This resulted in different clustering of the turtles based on their diatom communities. Metabarcoding allowed better discrimination between turtles based on their epibiotic diatom assemblages and put into evidence the presence of a cryptic diatom diversity. Microscopy, for its part, provided more ecological information of sea turtles based on historical bibliographical data and the abundances of ecological guilds of the diatom species present in the samples. This study shows the complementary nature of these two methods for studying turtle behavior.

High resting metabolic rates with low thermal dependence induce active dives in overwintering Pacific juvenile loggerhead turtles

The metabolic rate and activity of sea turtles generally decreases with decreasing seasonal ambient temperature. Juvenile loggerhead turtles in the Mediterranean Sea made prolonged inactive dives (>400 min), indicating a state of dormancy during the cold winter period. However, seasonal differences in dive duration were not detected in juvenile loggerheads in the western North Pacific, even though the ambient water temperature changed by more than 10°C. Thus, metabolic states might differ among populations, explaining differences in the diving behaviour of juveniles during winter. Here, we test the hypothesis that the active overwintering behaviour of juvenile loggerheads in the western North Pacific is driven by a high resting metabolic rate (RMR) with low thermal dependence. The RMR of juveniles in the western North Pacific (N=13) was 1.4 to 5.7 times higher (Q10=1.8) than that of juveniles in the Mediterranean Sea (Q10=5.4). To validate the high RMR values in the western North Pacific, the difference between core body temperature and ambient water temperature (ΔTb) was estimated from measured RMR and was compared with measured ΔTb. The measured and estimated ΔTb matched each other. In addition, most of the dives conducted by the turtles in the western North Pacific were within the calculated aerobic dive limit (cADL) expected from the measured metabolic rate. Our results indicate that high RMR with low thermal dependence induces active diving during the overwintering periods of juvenile loggerheads in the western North Pacific, supporting the suggestion that metabolic states differ among populations.

Changes of loggerhead turtle (Caretta caretta) dive behavior associated with tropical storm passage during the inter-nesting period

To improve conservation strategies for threatened sea turtles, more knowledge on their ecology, behavior, and how they cope with severe and changing weather conditions is needed. Satellite and animal motion datalogging tags were used to study the inter-nesting behavior of two female loggerhead turtles in the Gulf of Mexico, which regularly has hurricanes and tropical storms during nesting season. We contrast the behavioral patterns and swimming energetics of these two turtles, the first tracked in calm weather and the second tracked before, during and after a tropical storm. Turtle 1 was highly active and swam at the surface or submerged 95% of the time during the entire inter-nesting period, with a high estimated specific oxygen consumption rate (0.95 ml min^-1 kg^-0.83). Turtle 2 was inactive for most of the first 9 days of the inter-nesting period, during which she rested at the bottom (80% of the time) with low estimated oxygen consumption (0.62 ml min^-1 kg^-0.83). Midway through the inter-nesting period, turtle 2 encountered a tropical storm and became highly active (swimming 88% of the time during and 95% after the storm). Her oxygen consumption increased significantly to 0.97 ml min^-1 kg^-0.83 during and 0.98 ml min^-1 kg^-0.83 after the storm. However, despite the tropical storm, turtle 2 returned to the nesting beach, where she successfully re-nested 75 m from her previous nest. Thus, the tropical storm had a minor effect on this female's individual nesting success, even though the storm caused 90% loss nests at Casey Key.

Proxies of energy expenditure for marine mammals: an experimental test of "the time trap"

Direct measures of energy expenditure are difficult to obtain in marine mammals, and accelerometry may be a useful proxy. Recently its utility has been questioned as some analyses derived their measure of activity level by calculating the sum of accelerometry-based values and then comparing this summation to summed (total) energy expenditure (the so-called “time trap”). To test this hypothesis, we measured oxygen consumption of captive fur seals and sea lions wearing accelerometers during submerged swimming and calculated total and rate of energy expenditure. We compared these values with two potential proxies of energy expenditure derived from accelerometry data: flipper strokes and dynamic body acceleration (DBA). Total number of strokes, total DBA, and submergence time all predicted total oxygen consumption \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$({\boldsymbol{sV}}{{\boldsymbol{O}}}_{{\boldsymbol{2}}}$$\end{document}(sVO2 ml kg⁻¹). However, both total DBA and total number of strokes were correlated with submergence time. Neither stroke rate nor mean DBA could predict the rate of oxygen consumption (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$s\mathop{{\boldsymbol{V}}}\limits^{{\boldsymbol{.}}}{{\boldsymbol{O}}}_{{\boldsymbol{2}}}$$\end{document}sV.O2 ml min⁻¹ kg⁻¹). The relationship of total DBA and total strokes with total oxygen consumption is apparently a result of introducing a constant (time) into both sides of the relationship. This experimental evidence supports the conclusion that proxies derived from accelerometers cannot estimate the energy expenditure of marine mammals.

Validating accelerometry estimates of energy expenditure across behaviours using heart rate data in a free-living seabird

Two main techniques have dominated the field of ecological energetics: the heart rate and doubly labelled water methods. Although well established, they are not without their weaknesses, namely expense, intrusiveness and lack of temporal resolution. A new technique has been developed using accelerometers; it uses the overall dynamic body acceleration (ODBA) of an animal as a calibrated proxy for energy expenditure. This method provides high-resolution data without the need for surgery. Significant relationships exist between the rate of oxygen consumption (V̇O2 ) and ODBA in controlled conditions across a number of taxa; however, it is not known whether ODBA represents a robust proxy for energy expenditure consistently in all natural behaviours and there have been specific questions over its validity during diving, in diving endotherms. Here, we simultaneously deployed accelerometers and heart rate loggers in a wild population of European shags (Phalacrocorax aristotelis). Existing calibration relationships were then used to make behaviour-specific estimates of energy expenditure for each of these two techniques. Compared with heart rate-derived estimates, the ODBA method predicts energy expenditure well during flight and diving behaviour, but overestimates the cost of resting behaviour. We then combined these two datasets to generate a new calibration relationship between ODBA and V̇O2  that accounts for this by being informed by heart rate-derived estimates. Across behaviours we found a good relationship between ODBA and V̇O2 Within individual behaviours, we found useable relationships between ODBA and V̇O2  for flight and resting, and a poor relationship during diving. The error associated with these new calibration relationships mostly originates from the previous heart rate calibration rather than the error associated with the ODBA method. The equations provide tools for understanding how energy constrains ecology across the complex behaviour of free-living diving birds.

Correlations of metabolic rate and body acceleration in three species of coastal sharks under contrasting temperature regimes

The ability to produce estimates of the metabolic rate of free-ranging animals is fundamental to the study of their ecology. However, measuring the energy expenditure of animals in the field has proved difficult, especially for aquatic taxa. Accelerometry presents a means of translating metabolic rates measured in the laboratory to individuals studied in the field, pending appropriate laboratory calibrations. Such calibrations have only been performed on a few fish species to date, and only one where the effects of temperature were accounted for. Here, we present calibrations between activity, measured as overall dynamic body acceleration (ODBA), and metabolic rate, measured through respirometry, for nurse sharks (Ginglymostoma cirratum), lemon sharks (Negaprion brevirostris) and blacktip sharks (Carcharhinus limbatus). Calibrations were made at a range of volitional swimming speeds and experimental temperatures. Linear mixed models were used to determine a predictive equation for metabolic rate based on measured ODBA values, with the optimal model using ODBA in combination with activity state and temperature to predict metabolic rate in lemon and nurse sharks, and ODBA and temperature to predict metabolic rate in blacktip sharks. This study lays the groundwork for calculating the metabolic rate of these species in the wild using acceleration data.

Physiological constraints and energetic costs of diving behaviour in marine mammals: a review of studies using trained Steller sea lions diving in the open ocean

Marine mammals are characterized as having physiological specializations that maximize the use of oxygen stores to prolong time spent under water. However, it has been difficult to undertake the requisite controlled studies to determine the physiological limitations and trade-offs that marine mammals face while diving in the wild under varying environmental and nutritional conditions. For the past decade, Steller sea lions (Eumetopias jubatus) trained to swim and dive in the open ocean away from the physical confines of pools participated in studies that investigated the interactions between diving behaviour, energetic costs, physiological constraints, and prey availability. Many of these studies measured the cost of diving to understand how it varies with behaviour and environmental and physiological conditions. Collectively, these studies show that the type of diving (dive bouts or single dives), the level of underwater activity, the depth and duration of dives, and the nutritional status and physical condition of the animal affect the cost of diving and foraging. They show that dive depth, dive and surface duration, and the type of dive result in physiological adjustments (heart rate, gas exchange) that may be independent of energy expenditure. They also demonstrate that changes in prey abundance and nutritional status cause sea lions to alter the balance between time spent at the surface acquiring oxygen (and offloading CO₂ and other metabolic by-products) and time spent at depth acquiring prey. These new insights into the physiological basis of diving behaviour further our understanding of the potential scope for behavioural responses of marine mammals to environmental changes, the energetic significance of these adjustments, and the consequences of approaching physiological limits.

Counting calories in cormorants: dynamic body acceleration predicts daily energy expenditure measured in pelagic cormorants

The integral of the dynamic component of acceleration over time has been proposed as a measure of energy expenditure in wild animals. We tested that idea by attaching accelerometers to the tails of free-ranging pelagic cormorants (Phalacrocorax pelagicus) and simultaneously estimating energy expenditure using doubly labelled water. Two different formulations of dynamic body acceleration, [vectorial and overall DBA (VeDBA and ODBA)], correlated with mass-specific energy expenditure (both R(2)=0.91). VeDBA models combining and separately parameterizing flying, diving, activity on land and surface swimming were consistently considered more parsimonious than time budget models and showed less variability in model fit. Additionally, we observed evidence for the presence of hypometabolic processes (i.e. reduced heart rate and body temperature; shunting of blood away from non-essential organs) that suppressed metabolism in cormorants while diving, which was the most metabolically important activity. We concluded that a combination of VeDBA and physiological processes accurately measured energy expenditure for cormorants.

Dive behaviour can predict metabolic expenditure in Steller sea lions

Quantification of costs associated with foraging contributes to understanding the energetic impact that changes in prey availability have on the energy balance of an animal and the fitness of populations. However, estimating the costs of foraging is difficult for breath-hold divers, such as Steller sea lions, that feed underwater. We developed models parameterized with data from free-diving captive Steller sea lions to estimate the costs incurred by wild animals while foraging. We measured diving metabolic rate of trained sea lions performing four types of dives to 10 and 40 m in the open ocean and estimated the separate costs of different dive components: surface time; bottom time; and transiting to and from depth. We found that the sea lions' diving metabolic rates were higher while transiting (20.5 ± 13.0 ml O2 min(-1) kg(-1)) than while swimming at depth (13.5 ± 4.1 ml O2 min(-1) kg(-1)), and both were higher than metabolism at the surface (9.2 ± 1.6 ml O2 min(-1) kg(-1)). These values were incorporated into an energetic model that accurately predicted oxygen consumption for dives only (within 9.5%) and dive cycles (within 7.7%), although it consistently overestimated costs by 5.9% for dives and 21.8% for dive cycles. Differences in the costs of individual components of dives also explained differences in the efficiency of different dive strategies. Single dives were energetically less costly than bout dives; however, sea lions were more efficient at replenishing oxygen stores after bout dives and could therefore spend a greater portion of their time foraging than when undertaking single dives. The metabolic rates we measured for the different behavioural components of diving can be applied to time-depth recordings from wild Steller sea lions to estimate the energy expended while foraging. In turn, this can be used to understand how changes in prey availability affect energy balance and the health of individuals in declining populations.

Surfacers change their dive tactics depending on the aim of the dive: evidence from simultaneous measurements of breaths and energy expenditure

Air-breathing divers are assumed to have evolved to apportion their time between surface and underwater periods to maximize the benefit gained from diving activities. However, whether they change their time allocation depending on the aim of the dive is still unknown. This may be particularly crucial for 'surfacers' because they dive for various purposes in addition to foraging. In this study, we counted breath events at the surface and estimated oxygen consumption during resting, foraging and other dives in 11 green turtles (Chelonia mydas) in the wild. Breath events were counted by a head-mounted acceleration logger or direct observation based on an animal-borne video logger, and oxygen consumption was estimated by measuring overall dynamic body acceleration. Our results indicate that green turtles maximized their submerged time, following this with five to seven breaths to replenish oxygen for resting dives. However, they changed their dive tactic during foraging and other dives; they surfaced without depleting their estimated stores of oxygen, followed by only a few breaths for effective foraging and locomotion. These dichotomous surfacing tactics would be the result of behavioural modifications by turtles depending on the aim of each dive.

Validating the relationship between 3-dimensional body acceleration and oxygen consumption in trained Steller sea lions

We tested the ability of overall dynamic body acceleration (ODBA) to predict the rate of oxygen consumption ([Formula: see text]) in freely diving Steller sea lions (Eumetopias jubatus) while resting at the surface and diving. The trained sea lions executed three dive types-single dives, bouts of multiple long dives with 4-6 dives per bout, or bouts of multiple short dives with 10-12 dives per bout-to depths of 40 m, resulting in a range of activity and oxygen consumption levels. Average metabolic rate (AMR) over the dive cycle or dive bout calculated was calculated from [Formula: see text]. We found that ODBA could statistically predict AMR when data from all dive types were combined, but that dive type was a significant model factor. However, there were no significant linear relationships between AMR and ODBA when data for each dive type were analyzed separately. The potential relationships between AMR and ODBA were not improved by including dive duration, food consumed, proportion of dive cycle spent submerged, or number of dives per bout. It is not clear whether the lack of predictive power within dive type was due to low statistical power, or whether it reflected a true absence of a relationship between ODBA and AMR. The average percent error for predicting AMR from ODBA was 7-11 %, and standard error of the estimated AMR was 5-32 %. Overall, the extensive range of dive behaviors and physiological conditions we tested indicated that ODBA was not suitable for estimating AMR in the field due to considerable error and the inconclusive effects of dive type.

Accelerometry predicts daily energy expenditure in a bird with high activity levels

Animal ecology is shaped by energy costs, yet it is difficult to measure fine-scale energy expenditure in the wild. Because metabolism is often closely correlated with mechanical work, accelerometers have the potential to provide detailed information on energy expenditure of wild animals over fine temporal scales. Nonetheless, accelerometry needs to be validated on wild animals, especially across different locomotory modes. We merged data collected on 20 thick-billed murres (Uria lomvia) from miniature accelerometers with measurements of daily energy expenditure over 24 h using doubly labelled water. Across three different locomotory modes (swimming, flying and movement on land), dynamic body acceleration was a good predictor of daily energy expenditure as measured independently by doubly labelled water (R(2) = 0.73). The most parsimonious model suggested that different equations were needed to predict energy expenditure from accelerometry for flying than for surface swimming or activity on land (R(2) = 0.81). Our results demonstrate that accelerometers can provide an accurate integrated measure of energy expenditure in wild animals using many different locomotory modes.