Acceleration-triggered animal-borne videos show a dominance of fish in the diet of female northern elephant seals

The spatiotemporal context of individual specialization in resource use and environmental associations

1. Individual niche specialization is widespread in natural populations and has key implications for higher levels of biological organization. This phenomenon, however, has been primarily quantified in resource niche axes, overlooking individual variation in environmental associations (i.e. abiotic conditions organisms experience). 2. Here, we explore what we can learn from a multidimensional perspective of individual niche specialization that integrates resource use and environmental associations into a common framework. 3. By combining predictions from theory and simple simulations, we illustrate how (i) multidimensional intraspecific niche variation and (ii) the spatiotemporal context of interactions between conspecifics scale up to shape emergent patterns of the population niche. 4. Contemplating individual specialization as a multidimensional, unifying concept across biotic and abiotic niche axes is a fundamental step towards bringing this concept closer to the n-dimensional niche envisioned by Hutchinson.

Life in the Midwater: The Ecology of Deep Pelagic Animals

The water column of the deep ocean is dark, cold, low in food, and under crushing pressures, yet it is full of diverse life. Due to its enormous volume, this mesopelagic zone is home to some of the most abundant animals on the planet. Rather than struggling to survive, they thrive-owing to a broad set of adaptations for feeding, behavior, and physiology. Our understanding of these adaptations is constrained by the tools available for exploring the deep sea, but this tool kit is expanding along with technological advances. Each time we apply a new method to the depths, we gain surprising insights about genetics, ecology, behavior, physiology, diversity, and the dynamics of change. These discoveries show structure within the seemingly uniform habitat, limits to the seemingly inexhaustible resources, and vulnerability in the seemingly impervious environment. To understand midwater ecology, we need to reimagine the rules that govern terrestrial ecosystems. By spending more time at depth-with whatever tools are available-we can fill the knowledge gaps and better link ecology to the environment throughout the water column.

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.

Contrasting offspring dependence periods and diving development rates in two closely related marine mammal species

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.

Linking vertical movements of large pelagic predators with distribution patterns of biomass in the open ocean

Many predator species make regular excursions from near-surface waters to the twilight (200 to 1,000 m) and midnight (1,000 to 3,000 m) zones of the deep pelagic ocean. While the occurrence of significant vertical movements into the deep ocean has evolved independently across taxonomic groups, the functional role(s) and ecological significance of these movements remain poorly understood. Here, we integrate results from satellite tagging efforts with model predictions of deep prey layers in the North Atlantic Ocean to determine whether prey distributions are correlated with vertical habitat use across 12 species of predators. Using 3D movement data for 344 individuals who traversed nearly 1.5 million km of pelagic ocean in [Formula: see text]42,000 d, we found that nearly every tagged predator frequented the twilight zone and many made regular trips to the midnight zone. Using a predictive model, we found clear alignment of predator depth use with the expected location of deep pelagic prey for at least half of the predator species. We compared high-resolution predator data with shipboard acoustics and selected representative matches that highlight the opportunities and challenges in the analysis and synthesis of these data. While not all observed behavior was consistent with estimated prey availability at depth, our results suggest that deep pelagic biomass likely has high ecological value for a suite of commercially important predators in the open ocean. Careful consideration of the disruption to ecosystem services provided by pelagic food webs is needed before the potential costs and benefits of proceeding with extractive activities in the deep ocean can be evaluated.

SensorDrop: A system to remotely detach individual sensors from wildlife tracking collars

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

TDFCAM: A method for estimating stable isotope trophic discrimination in wild populations

Stable isotope mixing models (SIMMs) are widely used for characterizing wild animal diets. Such models rely upon using accurate trophic discrimination factors (TDFs) to account for the digestion, incorporation, and assimilation of food. Existing methods to calculate TDFs rely on controlled feeding trials that are time-consuming, often impractical for the study taxon, and may not reflect natural variability of TDFs present in wild populations.We present TDF_CAM as an alternative approach to estimating TDFs in wild populations, by using high-precision diet estimates from a secondary methodological source-in this case nest cameras-in lieu of controlled feeding trials, and provide a framework for how and when it should be applied.In this study, we evaluate the TDF_CAM approach in three datasets gathered on wild raptor nestlings (gyrfalcons Falco rusticolus; peregrine falcons Falco perigrinus; common buzzards Buteo buteo) comprising contemporaneous δ¹³C & δ¹⁵N stable isotope data and high-quality nest camera dietary data. We formulate Bayesian SIMMs (BSIMMs) incorporating TDFs from TDF_CAM and analyze their agreement with nest camera data, comparing model performance with those based on other relevant TDFs. Additionally, we perform sensitivity analyses to characterize TDF_CAM variability, and identify ecological and physiological factors contributing to that variability in wild populations.Across species and tissue types, BSIMMs incorporating a TDF_CAM outperformed any other TDF tested, producing reliable population-level estimates of diet composition. We demonstrate that applying this approach even with a relatively low sample size (n < 10 individuals) produced more accurate estimates of trophic discrimination than a controlled feeding study conducted on the same species. Between-individual variability in TDF_CAM estimates for ∆¹³C & ∆¹⁵ N increased with analytical imprecision in the source dietary data (nest cameras) but was also explained by natural variables in the study population (e.g., nestling nutritional/growth status and dietary composition).TDF_CAM is an effective method of estimating trophic discrimination in wild animal populations. Here, we use nest cameras as source dietary data, but this approach is applicable to any high-accuracy method of measuring diet, so long as diet can be monitored over an interval contemporaneous with a tissue's isotopic turnover rate.

Prey encounters and spatial memory influence use of foraging patches in a marine central place forager

Given the patchiness and long-term predictability of marine resources, memory of high-quality foraging grounds is expected to provide fitness advantages for central place foragers. However, it remains challenging to characterize how marine predators integrate memory with recent prey encounters to adjust fine-scale movement and use of foraging patches. Here, we used two months of movement data from harbour seals (Phoca vitulina) to quantify the repeatability in foraging patches as a proxy for memory. We then integrated these data into analyses of fine-scale movement and underwater behaviour to test how both spatial memory and prey encounter rates influenced the seals' area-restricted search (ARS) behaviour. Specifically, we used one month's GPS data from 29 individuals to build spatial memory maps of searched areas and archived accelerometery data from a subset of five individuals to detect prey catch attempts, a proxy for prey encounters. Individuals were highly consistent in the areas they visited over two consecutive months. Hidden Markov models showed that both spatial memory and prey encounters increased the probability of seals initiating ARS. These results provide evidence that predators use memory to adjust their fine-scale movement, and this ability should be accounted for in movement models.

The Functional and Ecological Significance of Deep Diving by Large Marine Predators

Many large marine predators make excursions from surface waters to the deep ocean below 200 m. Moreover, the ability to access meso- and bathypelagic habitats has evolved independently across marine mammals, reptiles, birds, teleost fishes, and elasmobranchs. Theoretical and empirical evidence suggests a number of plausible functional hypotheses for deep-diving behavior. Developing ways to test among these hypotheses will, however, require new ways to quantify animal behavior and biophysical oceanographic processes at coherent spatiotemporal scales. Current knowledge gaps include quantifying ecological links between surface waters and mesopelagic habitats and the value of ecosystem services provided by biomass in the ocean twilight zone. Growing pressure for ocean twilight zone fisheries creates an urgent need to understand the importance of the deep pelagic ocean to large marine predators.

Future trends in measuring physiology in free-living animals

Thus far, ecophysiology research has predominantly been conducted within controlled laboratory-based environments, owing to a mismatch between the recording technologies available for physiological monitoring in wild animals and the suite of behaviours and environments they need to withstand, without unduly affecting subjects. While it is possible to record some physiological variables for free-living animals using animal-attached logging devices, including inertial-measurement, heart-rate and temperature loggers, the field is still in its infancy. In this opinion piece, we review the most important future research directions for advancing the field of 'physiologging' in wild animals, including the technological development that we anticipate will be required, and the fiscal and ethical challenges that must be overcome. Non-invasive, multi-sensor miniature devices are ubiquitous in the world of human health and fitness monitoring, creating invaluable opportunities for animal and human physiologging to drive synergistic advances. We argue that by capitalizing on the research efforts and advancements made in the development of human wearables, it will be possible to design the non-invasive loggers needed by ecophysiologists to collect accurate physiological data from free-ranging animals ethically and with an absolute minimum of impact. In turn, findings have the capacity to foster transformative advances in human health monitoring. Thus, we invite biomedical engineers and researchers to collaborate with the animal-tagging community to drive forward the advancements necessary to realize the full potential of both fields. This article is part of the theme issue 'Measuring physiology in free-living animals (Part II)'.

Basking shark sub-surface behaviour revealed by animal-towed cameras

While biologging tags have answered a wealth of ecological questions, the drivers and consequences of movement and activity often remain difficult to ascertain, particularly marine vertebrates which are difficult to observe directly. Basking sharks, the second largest shark species in the world, aggregate in the summer in key foraging sites but despite advances in biologging technologies, little is known about their breeding ecology and sub-surface behaviour. Advances in camera technologies holds potential for filling in these knowledge gaps by providing environmental context and validating behaviours recorded with conventional telemetry. Six basking sharks were tagged at their feeding site in the Sea of Hebrides, Scotland, with towed cameras combined with time-depth recorders and satellite telemetry. Cameras recorded a cumulative 123 hours of video data over an average 64-hour deployment and confirmed the position of the sharks within the water column. Feeding events only occurred within a metre depth and made up ¾ of the time spent swimming near the surface. Sharks maintained similar tail beat frequencies regardless of whether feeding, swimming near the surface or the seabed, where they spent surprisingly up to 88% of daylight hours. This study reported the first complete breaching event and the first sub-surface putative courtship display, with nose-to-tail chasing, parallel swimming as well as the first observation of grouping behaviour near the seabed. Social groups of sharks are thought to be very short term and sporadic, and may play a role in finding breeding partners, particularly in solitary sharks which may use aggregations as an opportunity to breed. In situ observation of basking sharks at their seasonal aggregation site through animal borne cameras revealed unprecedented insight into the social and environmental context of basking shark behaviour which were previously limited to surface observations.

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.

Forced into an ecological corner: Round-the-clock deep foraging on small prey by elephant seals

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.

Lightscapes of fear: How mesopredators balance starvation and predation in the open ocean

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.

Machine learning enables improved runtime and precision for bio-loggers on seabirds

Unravelling the secrets of wild animals is one of the biggest challenges in ecology, with bio-logging (i.e., the use of animal-borne loggers or bio-loggers) playing a pivotal role in tackling this challenge. Bio-logging allows us to observe many aspects of animals’ lives, including their behaviours, physiology, social interactions, and external environment. However, bio-loggers have short runtimes when collecting data from resource-intensive (high-cost) sensors. This study proposes using AI on board video-loggers in order to use low-cost sensors (e.g., accelerometers) to automatically detect and record complex target behaviours that are of interest, reserving their devices’ limited resources for just those moments. We demonstrate our method on bio-loggers attached to seabirds including gulls and shearwaters, where it captured target videos with 15 times the precision of a baseline periodic-sampling method. Our work will provide motivation for more widespread adoption of AI in bio-loggers, helping us to shed light onto until now hidden aspects of animals’ lives.

Joseph Korpela et al. demonstrate the use of machine-learning assisted bio-loggers on black-tailed gulls and streaked shearwaters. As video recording is only activated through variations in movement detected by low-cost accelerometers, this method represents improvements to runtime and precision over existing bio-logging technology.