Publications

Abstract

Background

Which mammals show vocal learning abilities, e.g., can learn new sounds, or learn to use sounds in new contexts? Vocal usage and comprehension learning are submodules of vocal learning. Specifically, vocal usage learning is the ability to learn to use a vocalization in a new context; vocal comprehension learning is the ability to comprehend a vocalization in a new context. Among mammals, harbor seals (Phoca vitulina) are good candidates to investigate vocal learning. Here, we test whether harbor seals are capable of vocal usage and comprehension learning.

Results

We trained two harbor seals to (i) switch contexts from a visual to an auditory cue. In particular, the seals first produced two vocalization types in response to two hand signs; they then transitioned to producing these two vocalization types upon the presentation of two distinct sets of playbacks of their own vocalizations. We then (ii) exposed the seals to a combination of trained and novel vocalization stimuli. In a final experiment, (iii) we broadcasted only novel vocalizations of the two vocalization types to test whether seals could generalize from the trained set of stimuli to only novel items of a given vocal category. Both seals learned all tasks and took ≤ 16 sessions to succeed across all experiments. In particular, the seals showed contextual learning through switching the context from former visual to novel auditory cues, vocal matching and generalization. Finally, by responding to the played-back vocalizations with distinct vocalizations, the animals showed vocal comprehension learning.

Conclusions

It has been suggested that harbor seals are vocal learners; however, to date, these observations had not been confirmed in controlled experiments. Here, through three experiments, we could show that harbor seals are capable of both vocal usage and comprehension learning.

Abstract

Multimodal rhythmic signalling abounds across animal taxa. Studying its mechanisms and functions can highlight adaptive components in highly complex rhythmic behaviours, like dance and music. Pinnipeds, such as the harbour seal, Phoca vitulina, are excellent comparative models to assess rhythmic capacities. Harbour seals engage in rhythmic percussive behaviours which, until now, have not been described in detail. In our study, eight zoo-housed harbour seals (two pups, two juveniles and four adults) were passively monitored by audio and video during their pupping/breeding season. All juvenile and adult animals performed percussive signalling with their fore flippers in agonistic conditions, both on land and in water. Flipper slap sequences produced on the ground or on the seals' bodies were often highly regular in their interval duration, that is, were quasi-isochronous, at a 200–600 beats/min pace. Three animals also showed significant lateralization in slapping. In contrast to slapping on land, display slapping in water, performed only by adult males, showed slower tempo by one order of magnitude, and a rather motivic temporal structure. Our work highlights that percussive communication is a significant part of harbour seals' behavioural repertoire. We hypothesize that its forms of rhythm production may reflect adaptive functions such as regulating internal states and advertising individual traits.

Abstract

Learning can occur via trial and error; however, learning from conspecifics is faster and more efficient. Social animals can easily learn from conspecifics, but how do less social species learn? In particular, birds provide astonishing examples of social learning of vocalizations, while vocal learning from conspecifics is much less understood in mammals. We present a hypothesis aimed at solving an apparent paradox: how can harbor seals (Phoca vitulina) learn their song when their whole lives are marked by loose conspecific social contact? Harbor seal pups are raised individually by their mostly silent mothers. Pups' first few weeks of life show developed vocal plasticity; these weeks are followed by relatively silent years until sexually mature individuals start singing. How can this rather solitary life lead to a learned song? Why do pups display vocal plasticity at a few weeks of age, when this is apparently not needed? Our hypothesis addresses these questions and tries to explain how vocal learning fits into the natural history of harbor seals, and potentially other less social mammals. We suggest that harbor seals learn during a sensitive period within puppyhood, where they are exposed to adult males singing. In particular, we hypothesize that, to make this learning possible, the following happens concurrently: (1) mothers give birth right before male singing starts, (2) pups enter a sensitive learning phase around weaning time, which (3) coincides with their foraging expeditions at sea which, (4) in turn, coincide with the peak singing activity of adult males. In other words, harbor seals show vocal learning as pups so they can acquire elements of their future song from adults, and solitary adults can sing because they have acquired these elements as pups. We review the available evidence and suggest that pups learn adult vocalizations because they are born exactly at the right time to eavesdrop on singing adults. We conclude by advancing empirical predictions and testable hypotheses for future work.

Abstract

Objective

Researchers in animal cognition, psychophysics, and experimental psychology need to randomise the presentation order of trials in experimental sessions. In many paradigms, for each trial, one of two responses can be correct, and the trials need to be ordered such that the participant’s responses are a fair assessment of their performance. Specifically, in some cases, especially for low numbers of trials, randomised trial orders need to be excluded if they contain simple patterns which a participant could accidentally match and so succeed at the task without learning.
Results

We present and distribute a simple Python software package and tool to produce pseudorandom sequences following the Gellermann series. This series has been proposed to pre-empt simple heuristics and avoid inflated performance rates via false positive responses. Our tool allows users to choose the sequence length and outputs a .csv file with newly and randomly generated sequences. This allows behavioural researchers to produce, in a few seconds, a pseudorandom sequence for their specific experiment. PyGellermann is available at https://github.com/YannickJadoul/PyGellermann.

Abstract

Most bioacoustics software is used to analyse the already collected acoustics data in batch, i.e., after the data-collecting phase of a scientific study. However, experiments based on animal training require immediate and precise reactions from the experimenter, and thus do not easily dovetail with a typical bioacoustics workflow. Bridging this methodological gap, we have developed a custom application to live-monitor the vocal development of harbour seals in a behavioural experiment. In each trial, the application records and automatically detects an animal's call, and immediately measures duration and acoustic measures such as intensity, fundamental frequency, or formant frequencies. It then displays a spectrogram of the recording and the acoustic measurements, allowing the experimenter to instantly evaluate whether or not to reinforce the animal's vocalisation. From a technical perspective, the rapid and easy development of this custom software was made possible by combining multiple open-source software projects. Here, we integrated the acoustic analyses from Parselmouth, a Python library for Praat, together with PyAudio and Matplotlib's recording and plotting functionality, into a custom graphical user interface created with PyQt. This flexible recombination of different open-source Python libraries allows the whole program to be written in a mere couple of hundred lines of code

Abstract

Understanding cetacean distribution is essential for conservation planning and decision-making, particularly in regions subject to rapid environmental changes. Nevertheless, information on their spatiotemporal distribution is commonly limited, especially from remote areas. Species distribution models (SDMs) are powerful tools, relating species occurrences to environmental variables to predict the species' potential distribution. This study aims at using presence-only SDMs (MaxEnt) to identify suitable habitats for fin whales (Balaenoptera physalus) on their Nordic and Barents Seas feeding grounds. We used spatial-block cross-validation to tune MaxEnt parameters and evaluate model performance using spatially independent testing data. We considered spatial sampling bias correction using four methods. Important environmental variables were distance to shore and sea ice edge, variability of sea surface temperature and sea surface salinity, and depth. Suitable fin whale habitats were predicted along the west coast of Svalbard, between Svalbard and the eastern Norwegian Sea, coastal areas off Iceland and southern East Greenland, and along the Knipovich Ridge to Jan Mayen. Results support that presence-only SDMs are effective tools to predict cetacean habitat suitability, particularly in remote areas like the Arctic Ocean. SDMs constitute a cost-effective method for targeting future surveys and identifying top priority sites for conservation measures.

Abstract

Object categorization is an important cognitive adaptation, quickly providing an animal with relevant and potentially life-saving information. It can be defined as the process whereby objects that are not the same, are nonetheless grouped together according to some defining feature(s) and responded to as if they were the same. In this way, knowledge about one object, behavior or situation can be extrapolated onto another without much cost and effort. Many vertebrates including humans, monkeys, birds and teleosts have been shown to be able to categorize, with abilities varying between species and tasks. This study assessed object categorization skills in the gray bamboo shark Chiloscyllium griseum. Sharks learned to distinguish between the two categories, 'fish' versus 'snail' independently of image features and image type, i.e., black and white drawings, photographs, comics or negative images. Transfer tests indicated that sharks predominantly focused on and categorized the positive stimulus, while disregarding the negative stimulus.