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BackgroundEffectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve optimal outcomes for the patients as well as to reduce the risk of overloading the health care system. Currently, severe and nonsevere COVID-19 types are differentiated by only a few features, which do not comprehensively characterize the complicated pathological, physiological, and immunological responses to SARS-CoV-2 infection in the different disease types. In addition, these type-defining features may not be readily testable at the time of diagnosis. ObjectiveIn this study, we aimed to use a machine learning approach to understand COVID-19 more comprehensively, accurately differentiate severe and nonsevere COVID-19 clinical types based on multiple medical features, and provide reliable predictions of the clinical type of the disease. MethodsFor this study, we recruited 214 confirmed patients with nonsevere COVID-19 and 148 patients with severe COVID-19. The clinical characteristics (26 features) and laboratory test results (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest models based on all the features in each modality as well as on the top 5 features in each modality combined were developed and validated to differentiate COVID-19 clinical types. ResultsUsing clinical and laboratory results independently as input, the random forest models achieved >90% and >95% predictive accuracy, respectively. The importance scores of the input features were further evaluated, and the top 5 features from each modality were identified (age, hypertension, cardiovascular disease, gender, and diabetes for the clinical features modality, and dimerized plasmin fragment D, high sensitivity troponin I, absolute neutrophil count, interleukin 6, and lactate dehydrogenase for the laboratory testing modality, in descending order). Using these top 10 multimodal features as the only input instead of all 52 features combined, the random forest model was able to achieve 97% predictive accuracy. ConclusionsOur findings shed light on how the human body reacts to SARS-CoV-2 infection as a unit and provide insights on effectively evaluating the disease severity of patients with COVID-19 based on more common medical features when gold standard features are not available. We suggest that clinical information can be used as an initial screening tool for self-evaluation and triage, while laboratory test results should be applied when accuracy is the priority.

BackgroundEffectively identifying patients with COVID-19 using nonpolymerase chain reaction biomedical data is critical for achieving optimal clinical outcomes. Currently, there is a lack of comprehensive understanding in various biomedical features and appropriate analytical approaches for enabling the early detection and effective diagnosis of patients with COVID-19. ObjectiveWe aimed to combine low-dimensional clinical and lab testing data, as well as high-dimensional computed tomography (CT) imaging data, to accurately differentiate between healthy individuals, patients with COVID-19, and patients with non-COVID viral pneumonia, especially at the early stage of infection. MethodsIn this study, we recruited 214 patients with nonsevere COVID-19, 148 patients with severe COVID-19, 198 noninfected healthy participants, and 129 patients with non-COVID viral pneumonia. The participants’ clinical information (ie, 23 features), lab testing results (ie, 10 features), and CT scans upon admission were acquired and used as 3 input feature modalities. To enable the late fusion of multimodal features, we constructed a deep learning model to extract a 10-feature high-level representation of CT scans. We then developed 3 machine learning models (ie, k-nearest neighbor, random forest, and support vector machine models) based on the combined 43 features from all 3 modalities to differentiate between the following 4 classes: nonsevere, severe, healthy, and viral pneumonia. ResultsMultimodal features provided substantial performance gain from the use of any single feature modality. All 3 machine learning models had high overall prediction accuracy (95.4%-97.7%) and high class-specific prediction accuracy (90.6%-99.9%). ConclusionsCompared to the existing binary classification benchmarks that are often focused on single-feature modality, this study’s hybrid deep learning-machine learning framework provided a novel and effective breakthrough for clinical applications. Our findings, which come from a relatively large sample size, and analytical workflow will supplement and assist with clinical decision support for current COVID-19 diagnostic methods and other clinical applications with high-dimensional multimodal biomedical features.

Variation in reproductive success is the basis of evolution and allows species to respond to the environment, but only when it is based on fixed individual variation that is heritable. Several recent studies suggest that observed variation in reproduction is due to chance, not inherent individual differences. Our aim was to quantify inherent versus neutral variation in fitness of northern elephant seal ( Mirounga angustirostris (Gill, 1866)) females, including both quality and quantity of their offspring. Using 44 years of observations at Año Nuevo in California, we assembled lifetime pup production of 1065 individual females and mass at weaning for 2120 of their pups. Females varied significantly in mean lifetime mass of their pups, with 28% of the variance due to fixed individual differences among mothers. Variation was repeatable over 6 years of a mother’s lifetime and heritable ( h = 0.48). Moreover, pup mass at weaning was associated with future lifetime fitness, since larger pups had a higher chance of surviving to breed. Larger pups, however, did not produce more offspring once breeding, and lifetime pup production was not heritable. Traits related to offspring quality in elephant seals were inherently different among females, but variation in pup production was neutral.

Many animals and plants have species-typical annual cycles, but individuals vary in their timing of life-history events. Individual variation in fur replacement (moult) timing is poorly understood in mammals due to the challenge of repeated observations and longitudinal sampling. We examined factors that influence variation in moult duration and timing among elephant seals (Mirounga angustirostris). We quantified the onset and progression of fur loss in 1178 individuals. We found that an exceptionally rapid visible moult (7 days, the shortest of any mammals or birds), and a wide range of moult start dates (spanning 6-10× the event duration) facilitated high asynchrony across individuals (only 20% of individuals in the population moulting at the same time). Some of the variation was due to reproductive state, as reproductively mature females that skipped a breeding season moulted a week earlier than reproductive females. Moreover, individual variation in timing and duration within age-sex categories far outweighed (76-80%) variation among age-sex categories. Individuals arriving at the end of the moult season spent 50% less time on the beach, which allowed them to catch up in their annual cycles and reduce population-level variance during breeding. These findings underscore the importance of individual variation in annual cycles.

Populations and species are threatened by human pressure, but their fate is variable. Some depleted populations, such as that of the northern elephant seal (Mirounga angustirostris), recover rapidly even when the surviving population was small. The northern elephant seal was hunted extensively and taken by collectors between the early 1800s and 1892, suffering an extreme population bottleneck as a consequence. Recovery was rapid and now there are over 200,000 individuals. We sequenced 260 modern and 8 historical northern elephant seal nuclear genomes to assess the impact of the population bottleneck on individual northern elephant seals and to better understand their recovery. Here we show that inbreeding, an increase in the frequency of alleles compromised by lost function, and allele frequency distortion, reduced the fitness of breeding males and females, as well as the performance of adult females on foraging migrations. We provide a detailed investigation of the impact of a severe bottleneck on fitness at the genomic level and report on the role of specific gene systems.

Understanding the ontogeny of diving behaviour in marine megafauna is crucial owing to its influence on foraging success, energy budgets, and mortality. We compared the ontogeny of diving behaviour in two closely related species-northern elephant seals (Mirounga angustirostris, n = 4) and southern elephant seals (Mirounga leonina, n = 9)-to shed light on the ecological processes underlying migration. Although both species have similar sizes and behaviours as adults, we discovered that juvenile northern elephant seals have superior diving development, reaching 260 m diving depth in just 30 days, while southern elephant seals require 160 days. Similarly, northern elephant seals achieve dive durations of approximately 11 min on their first day of migration, while southern elephant seals take 125 days. The faster physiological maturation of northern elephant seals could be related to longer offspring dependency and post-weaning fast durations, allowing them to develop their endogenous oxygen stores. Comparison across both species suggests that weaned seal pups face a trade-off between leaving early with higher energy stores but poorer physiological abilities or leaving later with improved physiology but reduced fat stores. This trade-off might be influenced by their evolutionary history, which shapes their migration behaviours in changing environments over time.

Sleep is a crucial part of the daily activity patterns of mammals. However, in marine species that spend months or entire lifetimes at sea, the location, timing, and duration of sleep may be constrained. To understand how marine mammals satisfy their daily sleep requirements while at sea, we monitored electroencephalographic activity in wild northern elephant seals (Mirounga angustirostris) diving in Monterey Bay, California. Brain-wave patterns showed that seals took short (less than 20 minutes) naps while diving (maximum depth 377 meters; 104 sleeping dives). Linking these patterns to accelerometry and the time-depth profiles of 334 free-ranging seals (514,406 sleeping dives) revealed a North Pacific sleepscape in which seals averaged only 2 hours of sleep per day for 7 months, rivaling the record for the least sleep among all mammals, which is currently held by the African elephant (about 2 hours per day).

Weddell seals (Leptonychotes weddellii) are important predators in the Southern Ocean and are among the best-studied pinnipeds on Earth, yet much still needs to be learned about their year-round movements and foraging behaviour. Using biologgers, we tagged 62 post-moult Weddell seals in McMurdo Sound and vicinity between 2010 and 2012. Generalized additive mixed models were used to (i) explain and predict the probability of seal presence and foraging behaviour from eight environmental variables, and (ii) examine foraging behaviour in relation to dive metrics. Foraging probability was highest in winter and lowest in summer, and foraging occurred mostly in the water column or just above the bottom; across all seasons, seals preferentially exploited the shallow banks and deeper troughs of the Ross Sea, the latter providing a pathway for Circumpolar Deep Water to flow onto the shelf. In addition, the probability of Weddell seal occurrence and foraging increased with increasing bathymetric slope and where water depth was typically less than 600 m. Although the probability of occurrence was higher closer to the shelf break, foraging was higher in areas closer to shore and over banks. This study highlights the importance of overwinter foraging for recouping body mass lost during the previous summer.

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

Many marine animals migrate between foraging areas and reproductive sites, often timing the return migration with extreme precision. In theory, the decision to return should reflect energy acquisition at foraging areas, energetic costs associated with transit, and timing arrival for successful reproduction. For long-distance migrations to be successful, animals must integrate 'map' information to assess where they are relative to their reproductive site as well as 'calendar' information to know when to initiate the return migration given their distance from home1. Elephant seals, Mirounga angustirostris, migrate thousands of kilometers from reproductive sites to open ocean foraging areas (Figure 1A), yet return within a narrow window of time to specific beaches2. Each year, pregnant female elephant seals undertake a ∼240-day, 10,000 km foraging migration across the Northeast Pacific Ocean before returning to their breeding beaches, where they give birth 5 days after arriving2. We found that the seals' abilities to adjust the timing of their return migration is based on the perception of space and time, which further elucidates the mechanisms behind their astonishing navigational feats3.

All organisms face resource limitations that will ultimately restrict population growth, but the controlling mechanisms vary across ecosystems, taxa, and reproductive strategies. Using four decades of data, we examine how variation in the environment and population density affect reproductive outcomes in a capital-breeding carnivore, the northern elephant seal (Mirounga angustirostris). This species provides a unique opportunity to examine the relative importance of resource acquisition and density-dependence on breeding success. Capital breeders accrue resources over large temporal and spatial scales for use during an abbreviated reproductive period. This strategy may have evolved, in part, to confer resilience to short-term environmental variability. We observed density-dependent effects on weaning mass, and maternal age (experience) was more important than oceanographic conditions or maternal mass in determining offspring weaning mass. Together these findings show that the mechanisms controlling reproductive output are conserved across terrestrial and marine systems and vary with population dynamics, an important consideration when assessing the effect of extrinsic changes, such as climate change, on a population.

Small mesopelagic fishes dominate the world's total fish biomass, yet their ecological importance as prey for large marine animals is poorly understood. To reveal the little-known ecosystem dynamics, we identified prey, measured feeding events, and quantified the daily energy balance of 48 deep-diving elephant seals throughout their oceanic migrations by leveraging innovative technologies: animal-borne smart accelerometers and video cameras. Seals only attained positive energy balance after feeding 1000 to 2000 times per day on small fishes, which required continuous deep diving (80 to 100% of each day). Interspecies allometry suggests that female elephant seals have exceptional diving abilities relative to their body size, enabling them to exploit a unique foraging niche on small but abundant mesopelagic fish. This unique foraging niche requires extreme round-the-clock deep diving, limiting the behavioral plasticity of elephant seals to a changing mesopelagic ecosystem.

Seasonal resource pulses can have enormous impacts on species interactions. In marine ecosystems, air-breathing predators often drive their prey to deeper waters. However, it is unclear how ephemeral resource pulses such as near-surface phytoplankton blooms alter the vertical trade-off between predation avoidance and resource availability in consumers, and how these changes cascade to the diving behaviour of top predators. We integrated data on Weddell seal diving behaviour, diet stable isotopes, feeding success and mass gain to examine shifts in vertical foraging throughout ice break-out and the resulting phytoplankton bloom each year. We also tested hypotheses about the likely location of phytoplankton bloom origination (advected or produced in situ where seals foraged) based on sea ice break-out phenology and advection rates from several locations within 150 km of the seal colony. In early summer, seals foraged at deeper depths resulting in lower feeding rates and mass gain. As sea ice extent decreased throughout the summer, seals foraged at shallower depths and benefited from more efficient energy intake. Changes in diving depth were not due to seasonal shifts in seal diets or horizontal space use and instead may reflect a change in the vertical distribution of prey. Correspondence between the timing of seal shallowing and the resource pulse was variable from year to year and could not be readily explained by our existing understanding of the ocean and ice dynamics. Phytoplankton advection occurred faster than ice break-out, and seal dive shallowing occurred substantially earlier than local break-out. While there remains much to be learned about the marine ecosystem, it appears that an increase in prey abundance and accessibility via shallower distributions during the resource pulse could synchronize life-history phenology across trophic levels in this high-latitude ecosystem.

Like landscapes of fear, animals are hypothesized to strategically use lightscapes based on intrinsic motivations. However, longitudinal evidence of state-dependent risk aversion has been difficult to obtain in wild animals. Using high-resolution biologgers, we continuously measured body condition, time partitioning, three-dimensional movement, and risk exposure of 71 elephant seals throughout their 7-month foraging migrations (N = 16,000 seal days). As body condition improved from 21 to 32% fat and daylength declined from 16 to 10 hours, seals rested progressively earlier with respect to sunrise, sacrificing valuable nocturnal foraging hours to rest in the safety of darkness. Seals in superior body condition prioritized safety over energy conservation by resting >100 meters deeper where it was 300× darker. Together, these results provide empirical evidence that marine mammals actively use the three-dimensional lightscape to optimize risk-reward trade-offs based on ecological and physiological factors.

Repeated counts of animal abundance can reveal changes in local ecosystem health and inform conservation strategies. Unmanned aircraft systems (UAS), also known as drones, are commonly used to photograph animals in remote locations; however, counting animals in images is a laborious task. Crowd-sourcing can reduce the time required to conduct these censuses considerably, but must first be validated against expert counts to measure sources of error. Our objectives were to assess the accuracy and precision of citizen science counts and make recommendations for future citizen science projects. We uploaded drone imagery from Año Nuevo Island (California, USA) to a curated Zooniverse website that instructed citizen scientists to count seals and sea lions. Across 212 days, over 1,500 volunteers counted animals in 90,000 photographs. We quantified the error associated with several descriptive statistics to extract a single citizen science count per photograph from the 15 repeat counts and then compared the resulting citizen science counts to expert counts. Although proportional error was relatively low (9% for sea lions and 5% for seals during the breeding seasons) and improved with repeat sampling, the 12+ volunteers required to reduce error was prohibitively slow, taking on average 6 weeks to estimate animals from a single drone flight covering 25 acres, despite strong public outreach efforts. The single best algorithm was 'Median without the lowest two values', demonstrating that citizen scientists tended to under-estimate the number of animals present. Citizen scientists accurately counted adult seals, but accuracy was lower when sea lions were present during the summer and could be confused for seals. We underscore the importance of validation efforts and careful project design for researchers hoping to combine citizen science with imagery from drones, occupied aircraft, and/or remote cameras.

Objective: Human immunodeficiency virus (HIV) is a notable public health problem among young adults. The present study examined college students' knowledge of HIV and pre-exposure prophylaxis (PrEP) in relation to their sexual health behaviors. Participants and Method: Participants included 1516 students who completed questionnaires on actual and perceived HIV knowledge, perceived PrEP knowledge, and sexual health behaviors. Results: While knowledge of HIV was high, knowledge of PrEP was low. Approximately 73% of the sample reported not using condoms at all times, and 41% reported never having been tested for HIV. Women, students at public schools, upper-year students, and students with higher HIV and PrEP knowledge were more likely to get tested for HIV than their counterparts. Knowledge of HIV and PrEP did not relate to condom use. Conclusion: These results suggest the need for increased education about PrEP and strategies to help students translate knowledge about HIV to recommended sexual health behaviors.

BACKGROUND: State-space models are important tools for quality control and analysis of error-prone animal movement data. The near real-time (within 24 h) capability of the Argos satellite system can aid dynamic ocean management of human activities by informing when animals enter wind farms, shipping lanes, and other intensive use zones. This capability also facilitates the use of ocean observations from animal-borne sensors in operational ocean forecasting models. Such near real-time data provision requires rapid, reliable quality control to deal with error-prone Argos locations. METHODS: We formulate a continuous-time state-space model to filter the three types of Argos location data (Least-Squares, Kalman filter, and Kalman smoother), accounting for irregular timing of observations. Our model is deliberately simple to ensure speed and reliability for automated, near real-time quality control of Argos location data. We validate the model by fitting to Argos locations collected from 61 individuals across 7 marine vertebrates and compare model-estimated locations to contemporaneous GPS locations. We then test assumptions that Argos Kalman filter/smoother error ellipses are unbiased, and that Argos Kalman smoother location accuracy cannot be improved by subsequent state-space modelling. RESULTS: Estimation accuracy varied among species with Root Mean Squared Errors usually

Pinnipeds spend large portions of their lives at sea, submerged, or hauled-out on land, often on remote off-shore islands. This fundamentally limits access by researchers to critical parts of pinniped life history and has spurred the development and implementation of a variety of externally attached telemetry devices (ETDs) to collect information about movement patterns, physiology and ecology of marine animals when they cannot be directly observed. ETDs are less invasive and easier to apply than implanted internal devices, making them more widely used. However, ETDs have limited retention times and their use may result in negative short- and long-term consequences including capture myopathy, impacts to energetics, behavior, and entanglement risk. We identify 15 best practice recommendations for the use of ETDs with pinnipeds that address experimental justification, animal capture, tag design, tag attachment, effects assessments, preparation, and reporting. Continued improvement of best practices is critical within the framework of the Three Rs (Reduction, Refinement, Replacement); these best practice recommendations provide current guidance to mitigate known potential negative outcomes for individuals and local populations. These recommendations were developed specifically for pinnipeds; however, they may also be applicable to studies of other marine taxa. We conclude with four desired future directions for the use of ETDs in technology development, validation studies, experimental designs and data sharing.

Purpose: Using the framework of Adult Learning Theory, this study worked to uncover the composition of rural landowners' information sources and learner characteristics that impact information-seeking behavior among maple syrup producers in Wisconsin. Design: Regression models were used to analyze data from a survey targeted at Wisconsin maple syrup producers (N = 677). Findings: Maple syrup producers mostly learn through interactions with peers and underutilize expert resources, but opinion leaders and early adopters of new technologies are more likely to seek information through both formal and informal knowledge networks than maple producers who are not influencers in their community. Extrinsic motivation was associated with maple producers' tendency to engage in optimal knowledge acquisition, whereas intrinsic motivation was not. Practical implications: Professionals can optimize resources to design outreach programs and develop marketing strategies by targeting landowners based on their learner characteristics. Theoretical implications: Our research contributes to the adult learning literature and advances the theoretical understanding of micro-Agricultural Knowledge and Innovation Systems by investigating the influence of different types of learning motivations on optimal knowledge acquisition. Originality/Value: This study identified landowner characteristics related to optimal knowledge acquisition and is the first to highlight the roles of family legacy and social norms as motivators that drive maple producers to acquire new skills and knowledge. [ABSTRACT FROM AUTHOR]

How animal movement decisions interact with the distribution of resources to shape individual performance is a key question in ecology. However, links between spatial and behavioural ecology and fitness consequences are poorly understood because the outcomes of individual resource selection decisions, such as energy intake, are rarely measured. In the open ocean, mesoscale features (approx. 10-100 km) such as fronts and eddies can aggregate prey and thereby drive the distribution of foraging vertebrates through bottom-up biophysical coupling. These productive features are known to attract predators, yet their role in facilitating energy transfer to top-level consumers is opaque. We investigated the use of mesoscale features by migrating northern elephant seals and quantified the corresponding energetic gains from the seals' foraging patterns at a daily resolution. Migrating elephant seals modified their diving behaviour and selected for mesoscale features when foraging. Daily energy gain increased significantly with increasing mesoscale activity, indicating that the physical environment can influence predator fitness at fine temporal scales. Results show that areas of high mesoscale activity not only attract top predators as foraging hotspots, but also lead to increased energy transfer across trophic levels. Our study provides evidence that the physical environment is an important factor in controlling energy flow to top predators by setting the stage for variation in resource availability. Such understanding is critical for assessing how changes in the environment and resource distribution will affect individual fitness and food web dynamics.

Characterizing habitat suitability for a marine predator requires an understanding of the environmental heterogeneity and variability over the range in which a population moves during a particular life cycle. Female California sea lions (Zalophus californianus) are central-place foragers and are particularly constrained while provisioning their young. During this time, habitat selection is a function of prey availability and proximity to the rookery, which has important implications for reproductive and population success. We explore how lactating females may select habitat and respond to environmental variability over broad spatial and temporal scales within the California Current System. We combine near-real-time remotely sensed satellite oceanography, animal tracking data (n = 72) from November to February over multiple years (2003-2009) and Generalized Additive Mixed Models (GAMMs) to determine the probability of sea lion occurrence based on environmental covariates. Results indicate that sea lion presence is associated with cool (

Little is known about the foraging behavior of top predators in the deep mesopelagic ocean. Elephant seals dive to the deep biota-poor oxygen minimum zone (OMZ) (>800 m depth) despite high diving costs in terms of energy and time, but how they successfully forage in the OMZ remains largely unknown. Assessment of their feeding rate is the key to understanding their foraging behavior, but this has been challenging. Here, we assessed the feeding rate of 14 female northern elephant seals determined by jaw motion events (JME) and dive cycle time to examine how feeding rates varied with dive depth, particularly in the OMZ. We also obtained video footage from seal-mounted videos to understand their feeding in the OMZ. While the diel vertical migration pattern was apparent for most depths of the JME, some very deep dives, beyond the normal diel depth ranges, occurred episodically during daylight hours. The midmesopelagic zone was the main foraging zone for all seals. Larger seals tended to show smaller numbers of JME and lower feeding rates than smaller seals during migration, suggesting that larger seals tended to feed on larger prey to satisfy their metabolic needs. Larger seals also dived frequently to the deep OMZ, possibly because of a greater diving ability than smaller seals, suggesting their dependency on food in the deeper depth zones. Video observations showed that seals encountered the rarely reported ragfish (Icosteus aenigmaticus) in the depths of the OMZ, which failed to show an escape response from the seals, suggesting that low oxygen concentrations might reduce prey mobility. Less mobile prey in OMZ would enhance the efficiency of foraging in this zone, especially for large seals that can dive deeper and longer. We suggest that the OMZ plays an important role in structuring the mesopelagic ecosystem and for the survival and evolution of elephant seals.

Hauling out is an essential component of pinniped life-history. Haul-out behaviour may be affected by biological (e.g. sex, age and condition) and physical factors (e.g. food availability and environmental conditions), and identifying these factors may help explain the spatio-temporal distribution and habitat use of pinnipeds. The aim of this study is to describe observed winter haul-out patterns of adult Weddell seals in the Weddell Sea and investigate the role of potential predictors to gain insight into the way these animals interact with the physical environment in this region. We examined the haul-out behaviour in relation to available biological (i.e., diving effort, sex) and physical information (i.e., sun angle). Thirty-three satellite telemetry tags were deployed on adult Weddell seals in the southern Weddell Sea during February 2007, 2009 and 2011, following their annual moult recording information on the behavioural mode of the animal: at surface, hauled out or diving. At the end of the austral summer Weddell seals spent, on average, more than 40% of their time hauled out on the ice. Under constant light conditions, it appears that physiological factors drive sex differences in the timing and duration of haul-out behaviour, with females spending on average more time hauled out than males during daylight hours. This time spent hauled-out declined to around 15% in both sexes by the beginning of autumn and remained at this level with a clear nocturnal haul-out pattern during the winter. The time spent diving increased during this period, indicating an increase in foraging effort during the winter months, and led to a common haul-out pattern in both sexes over winter. We found a positive relationship between haul-out duration and the percentage of time spent diving prior to a haul-out in both sexes, with the exception of female daytime haul-outs early in the year.

Foraging theory predicts that breath-hold divers adjust the time spent foraging at depth relative to the energetic cost of swimming, which varies with buoyancy (body density). However, the buoyancy of diving animals varies as a function of their body condition, and the effects of these changes on swimming costs and foraging behaviour have been poorly examined. A novel animal-borne accelerometer was developed that recorded the number of flipper strokes, which allowed us to monitor the number of strokes per metre swam (hereafter, referred to as strokes-per-metre) by female northern elephant seals over their months-long, oceanic foraging migrations. As negatively buoyant seals increased their fat stores and buoyancy, the strokes-per-metre increased slightly in the buoyancy-aided direction (descending), but decreased significantly in the buoyancy-hindered direction (ascending), with associated changes in swim speed and gliding duration. Overall, the round-trip strokes-per-metre decreased and reached a minimum value when seals achieved neutral buoyancy. Consistent with foraging theory, seals stayed longer at foraging depths when their round-trip strokes-per-metre was less. Therefore, neutrally buoyant divers gained an energetic advantage via reduced swimming costs, which resulted in an increase in time spent foraging at depth, suggesting a foraging benefit of being fat.