David P. Hocking

Leopard seals (Hydrurga leptonyx) use suction and filter feeding when hunting small prey underwater

Leopard seals (Hydrurgaleptonyx) are unusual among apex predators in that they feed at both the top and near the bottom of marine food webs; they capture and consume marine amniotes (seals and penguins) as well as krill. This is thought to be achieved with their unusual dentition: rostral caniniform teeth function to grip large prey and tricuspate postcanines function to sieve krill. The use of canine teeth is known, yet until now, the function of the postcanines has never been documented. Here, we present the first direct observations of filter feeding in leopard seals. Suction was used to draw small prey into the mouth followed by expulsion of ingested seawater through the sieve formed by postcanine teeth. Individuals show abrasive wear on canines and incisors, but not postcanines. This suggests that postcanines are not systematically used for piercing prey during macrophagous feeding, confirming that the postcanines primarily serve a sieving function. Rather than being less efficient at feeding as a result of its polarized diet, the leopard seal is well adapted towards two disparate feeding modes.

A behavioural framework for the evolution of feeding in predatory aquatic mammals

Extant aquatic mammals are a key component of aquatic ecosystems. Their morphology, ecological role and behaviour are, to a large extent, shaped by their feeding ecology. Nevertheless, the nature of this crucial aspect of their biology is often oversimplified and, consequently, misinterpreted. Here, we introduce a new framework that categorizes the feeding cycle of predatory aquatic mammals into four distinct functional stages (prey capture, manipulation and processing, water removal and swallowing), and details the feeding behaviours that can be employed at each stage. Based on this comprehensive scheme, we propose that the feeding strategies of living aquatic mammals form an evolutionary sequence that recalls the land-to-water transition of their ancestors. Our new conception helps to explain and predict the origin of particular feeding styles, such as baleen-assisted filter feeding in whales and raptorial ‘pierce’ feeding in pinnipeds, and informs the structure of present and past ecosystems.

Australian Fur Seals (Arctocephalus pusillus doriferus) Use Raptorial Biting and Suction Feeding When Targeting Prey in Different Foraging Scenarios

Foraging behaviours used by two female Australian fur seals (Arctocephalus pusillus doriferus) were documented during controlled feeding trials. During these trials the seals were presented with prey either free-floating in open water or concealed within a mobile ball or a static box feeding device. When targeting free-floating prey both subjects primarily used raptorial biting in combination with suction, which was used to draw prey to within range of the teeth. When targeting prey concealed within either the mobile or static feeding device, the seals were able to use suction to draw out prey items that could not be reached by biting. Suction was followed by lateral water expulsion, where water drawn into the mouth along with the prey item was purged via the sides of the mouth. Vibrissae were used to explore the surface of the feeding devices, especially when locating the openings in which the prey items had been hidden. The mobile ball device was also manipulated by pushing it with the muzzle to knock out concealed prey, which was not possible when using the static feeding device. To knock prey out of this static device one seal used targeted bubble blowing, where a focused stream of bubbles was blown out of the nose into the openings in the device. Once captured in the jaws, prey items were manipulated and re-oriented using further mouth movements or chews so that they could be swallowed head first. While most items were swallowed whole underwater, some were instead taken to the surface and held in the teeth, while being vigorously shaken to break them into smaller pieces before swallowing. The behavioural flexibility displayed by Australian fur seals likely assists in capturing and consuming the extremely wide range of prey types that are targeted in the wild, during both benthic and epipelagic foraging.

Ancient whales did not filter feed with their teeth

The origin of baleen whales (Mysticeti), the largest animals on Earth, is closely tied to their signature filter-feeding strategy. Unlike their modern relatives, archaic whales possessed a well-developed, heterodont adult dentition. How these teeth were used, and what role their function and subsequent loss played in the emergence of filter feeding, is an enduring mystery. In particular, it has been suggested that elaborate tooth crowns may have enabled stem mysticetes to filter with their postcanine teeth in a manner analogous to living crabeater and leopard seals, thereby facilitating the transition to baleen-assisted filtering. Here we show that the teeth of archaic mysticetes are as sharp as those of terrestrial carnivorans, raptorial pinnipeds and archaeocetes, and thus were capable of capturing and processing prey. By contrast, the postcanine teeth of leopard and crabeater seals are markedly blunter, and clearly unsuited to raptorial feeding. Our results suggest that mysticetes never passed through a tooth-based filtration phase, and that the use of teeth and baleen in early whales was not functionally connected. Continued selection for tooth sharpness in archaic mysticetes is best explained by a feeding strategy that included both biting and suction, similar to that of most living pinnipeds and, probably, early toothed whales (Odontoceti).

Super machine learning: improving accuracy and reducing variance of behaviour classification from accelerometry

BackgroundSemi-automating the analyses of accelerometry data makes it possible to synthesize large data sets. However, when constructing activity budgets from accelerometry data, there are many methods to extract, analyse and report data and results. For instance, machine learning is a robust approach to classifying data. We used a new method, super learning, that combines base learners (different machine learning methods) in an optimal manner to achieve overall improved accuracy. Other facets of super learning include the number of behavioural categories to predict, the number of epochs (sample window size) used to split data for training and testing and the parameters on which to train the models.ResultsThe super learner accurately classified behaviour categories with higher accuracy and lower variance than comparative models. For all models tested, using four behaviours, in comparison with six, achieved higher rates of accuracy. The number of epochs chosen also affected the accuracy with smaller epochs (7 and 13) performing better than longer epochs (25 and 75).ConclusionsCorrect model selection, training and testing are imperative to creating reliable and valid classification models. To do so means model fitting must use a wide array of selection criteria. We evaluated a number of these including model, number of behaviours to classify and epoch length and then used a parameter grid search to implement the models. We found that all criteria tested contributed to the models’ overall accuracies. Fewer behaviour categories and shorter epoch length improved the performance of all models tested. The super learner classified behaviours with higher accuracy and lower variance than other models tested. However, when using this model, users need to consider the additional human and computational time required for implementation. Machine learning is a powerful method for classifying the behaviour of animals from accelerometers. Care and consideration of the modelling parameters evaluated in this study are essential when using this type of statistical analysis.

Seeing It All: Evaluating Supervised Machine Learning Methods for the Classification of Diverse Otariid Behaviours

Constructing activity budgets for marine animals when they are at sea and cannot be directly observed is challenging, but recent advances in bio-logging technology offer solutions to this problem. Accelerometers can potentially identify a wide range of behaviours for animals based on unique patterns of acceleration. However, when analysing data derived from accelerometers, there are many statistical techniques available which when applied to different data sets produce different classification accuracies. We investigated a selection of supervised machine learning methods for interpreting behavioural data from captive otariids (fur seals and sea lions). We conducted controlled experiments with 12 seals, where their behaviours were filmed while they were wearing 3-axis accelerometers. From video we identified 26 behaviours that could be grouped into one of four categories (foraging, resting, travelling and grooming) representing key behaviour states for wild seals. We used data from 10 seals to train four predictive classification models: stochastic gradient boosting (GBM), random forests, support vector machine using four different kernels and a baseline model: penalised logistic regression. We then took the best parameters from each model and cross-validated the results on the two seals unseen so far. We also investigated the influence of feature statistics (describing some characteristic of the seal), testing the models both with and without these. Cross-validation accuracies were lower than training accuracy, but the SVM with a polynomial kernel was still able to classify seal behaviour with high accuracy (>70%). Adding feature statistics improved accuracies across all models tested. Most categories of behaviour -resting, grooming and feeding—were all predicted with reasonable accuracy (52–81%) by the SVM while travelling was poorly categorised (31–41%). These results show that model selection is important when classifying behaviour and that by using animal characteristics we can strengthen the overall accuracy.

Foraging-Based Enrichment Promotes More Varied Behaviour in Captive Australian Fur Seals (Arctocephalus pusillus doriferus).

During wild foraging, Australian fur seals (Arctocephalus pusillus doriferus) encounter many different types of prey in a wide range of scenarios, yet in captive environments they are typically provided with a narrower range of opportunities to display their full repertoire of behaviours. This study aimed to quantitatively explore the effect of foraging-based enrichment on the behaviour and activity patterns displayed by two captive Australian fur seals at Melbourne Zoo, Australia. Food was presented as a scatter in open water, in a free-floating ball device, or in a static box device, with each treatment separated by control trials with no enrichment. Both subjects spent more time interacting with the ball and static box devices than the scatter feed. The total time spent pattern swimming was reduced in the enrichment treatments compared to the controls, while the time spent performing random swimming behaviours increased. There was also a significant increase in the total number of bouts of behaviour performed in all three enrichment treatments compared to controls. Each enrichment method also promoted a different suit of foraging behaviours. Hence, rather than choosing one method, the most effective way to increase the diversity of foraging behaviours, while also increasing variation in general activity patterns, is to provide seals with a wide range of foraging scenarios where food is encountered in different ways.

Reply to comment by Kienle et al. 2017

Kienle et al . [1] suggest amendments to our framework for feeding in predatory aquatic mammals [2]. Below we reply to their suggestions and demonstrate that they are fundamentally flawed from both a mechanical (feeding cycle, strategies) and an evolutionary perspective. They do, however, inspire an important addition to the range and structuring of capture behaviours encoded in our framework. Feeding cycle . Our framework groups feeding behaviours with similar functions, such as capture and processing, and thus clarifies how different species perform similar tasks during feeding. Kienle et al . [1] suggest that these groupings should be broken up, with capture, ‘external’ processing and manipulation behaviours instead being clustered into a single ‘ingestion’ stage. We question the biological justification for lumping behaviours as disparate as chasing, killing and dismembering. Capturing prey is unrelated to, and need not be followed by, processing. By contrast, ‘external’ and intraoral processing behaviours are functionally akin, with both aiming to dismember prey to start the digestive process. Lumping capture and processing furthermore deviates from the most recent conceptualization of the tetrapod feeding cycle by Schwenk & Rubega [3], which, contra [1], both explicitly includes a separate capture/subjugation stage (p. 12) and specifically associates ‘external’ with intraoral processing (p. 21). Besides the inclusion of water removal, our model differs from [3] only in not recognizing a separate ‘ingestion’ stage. This is because we view ingestion as a moment in time—namely, when food enters the mouth [4]—that can occur during multiple stages, and be achieved and reversed several times during feeding. By contrast, capture, manipulation and processing reflect periods of time over which specific behaviours are performed. Feeding strategies . Kienle et al. [1] criticize our use of a semi-aquatic …

Clawed forelimbs allow northern seals to eat like their ancient ancestors

Streamlined flippers are often considered the defining feature of seals and sea lions, whose very name ‘pinniped’ comes from the Latin pinna and pedis, meaning ‘fin-footed’. Yet not all pinniped limbs are alike. Whereas otariids (fur seals and sea lions) possess stiff streamlined forelimb flippers, phocine seals (northern true seals) have retained a webbed yet mobile paw bearing sharp claws. Here, we show that captive and wild phocines routinely use these claws to secure prey during processing, enabling seals to tear large fish by stretching them between their teeth and forelimbs. ‘Hold and tear’ processing relies on the primitive forelimb anatomy displayed by phocines, which is also found in the early fossil pinniped Enaliarctos. Phocine forelimb anatomy and behaviour therefore provide a glimpse into how the earliest seals likely fed, and indicate what behaviours may have assisted pinnipeds along their journey from terrestrial to aquatic feeding.

Using accelerometers to develop time-energy budgets of wild fur seals from captive surrogates

Background Accurate time-energy budgets summarise an animal’s energy expenditure in a given environment, and are potentially a sensitive indicator of how an animal responds to changing resources. Deriving accurate time-energy budgets requires an estimate of time spent in different activities and of the energetic cost of that activity. Bio-loggers (e.g., accelerometers) may provide a solution for monitoring animals such as fur seals that make long-duration foraging trips. Using low resolution to record behaviour may aid in the transmission of data, negating the need to recover the device. Methods This study used controlled captive experiments and previous energetic research to derive time-energy budgets of juvenile Australian fur seals (Arctocephalus pusillus) equipped with tri-axial accelerometers. First, captive fur seals and sea lions were equipped with accelerometers recording at high (20 Hz) and low (1 Hz) resolutions, and their behaviour recorded. Using this data, machine learning models were trained to recognise four states—foraging, grooming, travelling and resting. Next, the energetic cost of each behaviour, as a function of location (land or water), season and digestive state (pre- or post-prandial) was estimated. Then, diving and movement data were collected from nine wild juvenile fur seals wearing accelerometers recording at high- and low- resolutions. Models developed from captive seals were applied to accelerometry data from wild juvenile Australian fur seals and, finally, their time-energy budgets were reconstructed. Results Behaviour classification models built with low resolution (1 Hz) data correctly classified captive seal behaviours with very high accuracy (up to 90%) and recorded without interruption. Therefore, time-energy budgets of wild fur seals were constructed with these data. The reconstructed time-energy budgets revealed that juvenile fur seals expended the same amount of energy as adults of similar species. No significant differences in daily energy expenditure (DEE) were found across sex or season (winter or summer), but fur seals rested more when their energy expenditure was expected to be higher. Juvenile fur seals used behavioural compensatory techniques to conserve energy during activities that were expected to have high energetic outputs (such as diving). Discussion As low resolution accelerometry (1 Hz) was able to classify behaviour with very high accuracy, future studies may be able to transmit more data at a lower rate, reducing the need for tag recovery. Reconstructed time-energy budgets demonstrated that juvenile fur seals appear to expend the same amount of energy as their adult counterparts. Through pairing estimates of energy expenditure with behaviour this study demonstrates the potential to understand how fur seals expend energy, and where and how behavioural compensations are made to retain constant energy expenditure over a short (dive) and long (season) period.