Bioacoustic fundamental frequency estimation: a cross-species dataset and deep learning baseline.

The fundamental frequency (F0) is a key parameter for characterising structures in vertebrate vocalisations, for instance defining vocal repertoires and their variations at different biological scales ( population dialects, individual signatures). However, the task is too laborious to perform manually, and its automation is complex. Despite significant advancements in the fields of speech and music for automatic F0 estimation, similar progress in bioacoustics has been limited.

From biologging to conservation: Tracking individual performance in changing environments.

Under an accelerating biodiversity crisis, increased urbanization, habitat fragmentation, and climate change require new approaches to assess conservation impact. We argue that animal biologging is a cost-effective method for monitoring biodiversity at its source, including tracked animals and the habitats they occupy. Biologging, or animal-mounted sensors to record data, can act as a reporting, measurement, and verification system, and deliver direct insights into environments of selection.

Behavioral sequences across multiple animal species in the wild share common structural features.

Animal behavior can be decomposed into a sequence of discrete activity bouts over time. Analyzing the statistical structure of such behavioral sequences can provide insights into the drivers of behavioral decisions. Laboratory studies, predominantly in invertebrates, have suggested that behavioral sequences exhibit multiple timescales and long-range memory, but whether these results can be generalized to other taxa and to animals in natural settings remains unclear.

Multidimensional social influence drives leadership and composition-dependent success in octopus-fish hunting groups.

Collective behaviour, social interactions and leadership in animal groups are often driven by individual differences. However, most studies focus on same-species groups, in which individual variation is relatively low. Multispecies groups, however, entail interactions among highly divergent phenotypes, ranging from simple exploitative actions to complex coordinated networks.

The sociality of sleep in animal groups.

Group-living animals sleep together, yet most research treats sleep as an individual process. Here, we argue that social interactions during the sleep period contribute in important, but largely overlooked, ways to animal groups' social dynamics, while patterns of social interaction and the structure of social connections within animal groups play important, but poorly understood, roles in shaping sleep behavior. Leveraging field-appropriate methods, such as direct and video-based observation, and increasingly common on-animal motion sensors (e.

Exposure to calls before hatching affects the post-hatching behaviour of domestic chickens.

The soundscape experienced by animals early in life can affect their behaviour later in life. For birds, sounds experienced in the egg can influence how individuals learn to respond to specific calls post-hatching. However, how early acoustic experiences affect subsequent social behaviour remains unknown.

Mapping vocal interactions in space and time differentiates signal broadcast versus signal exchange in meerkat groups.

Animal vocal communication research traditionally focuses on acoustic and contextual features of calls, yet substantial information is also contained in response selectivity and timing during vocalization events. By examining the spatiotemporal structure of vocal interactions, we can distinguish between 'broadcast' and 'exchange' signalling modes, with the former potentially serving to transmit signallers' general state and the latter reflecting more interactive signalling behaviour. Here, we tracked the movements and vocalizations of wild meerkat () groups simultaneously using collars to explore this distinction.

Accelerometer-based predictions of behaviour elucidate factors affecting the daily activity patterns of spotted hyenas.

Animal activity patterns are highly variable and influenced by internal and external factors, including social processes. Quantifying activity patterns in natural settings can be challenging, as it is difficult to monitor animals over long time periods. Here, we developed and validated a machine-learning-based classifier to identify behavioural states from accelerometer data of wild spotted hyenas , social carnivores that live in large fission-fusion societies.

Sensory collectives in natural systems.

Groups of animals inhabit vastly different sensory worlds, or umwelten, which shape fundamental aspects of their behaviour. Yet the sensory ecology of species is rarely incorporated into the emerging field of collective behaviour, which studies the movements, population-level behaviours, and emergent properties of animal groups. Here, we review the contributions of sensory ecology and collective behaviour to understanding how animals move and interact within the context of their social and physical environments.

Correction to: 'Fission-fusion dynamics in sheep: the influence of resource distribution and temporal activity patterns' (2023) by Della Libera .

[This corrects the article DOI: 10.1098/10.1098/rsos.

Fission-fusion dynamics in sheep: the influence of resource distribution and temporal activity patterns.

Fission-fusion events, i.e. changes to the size and composition of animal social groups, are a mechanism to adjust the social environment in response to short-term changes in the cost-benefit ratio of group living.

Humans strategically avoid connecting to others who agree and avert the emergence of network polarization in a coordination task.

Clusters of like-minded individuals can impede consensus in group decision-making. We implemented an online color coordination task to investigate whether control over communication links creates clusters impeding group consensus. In 244 6-member networks, individuals were incentivized to reach a consensus by agreeing on a color, but had conflicting incentives for which color to choose.

Link updating strategies influence consensus decisions as a function of the direction of communication.

Consensus decision-making in social groups strongly depends on communication links that determine to whom individuals send, and from whom they receive, information. Here, we ask how consensus decisions are affected by strategic updating of links and how this effect varies with the direction of communication. We quantified the coevolution of link and opinion dynamics in a large population with binary opinions using mean-field numerical simulations of two voter-like models of opinion dynamics: an incoming model (IM) (where individuals choose who to receive opinions from) and an outgoing model (OM) (where individuals choose who to send opinions to).

Directional speakers as a tool for animal vocal communication studies.

Audio playbacks are a common experimental tool in vocal communication research. However, low directionality of sound makes it hard to control the audience exposed to the stimuli. Parametric speakers offer a solution for transmitting directional audible signals by using ultrasonic carrier waves.

The role of position in consensus dynamics of polarizable networks.

Communication constraints often complicate group decision-making. In this experiment, we investigate how the network position of opinionated group members determines both the speed and the outcome of group consensus in 7-member communication networks susceptible to polarization. To this end, we implemented an online version of a color coordination task within experimentally controlled communication networks.

Disentangling influence over group speed and direction reveals multiple patterns of influence in moving meerkat groups.

Animals that travel together in groups must constantly come to consensus about both the direction and speed of movement, often simultaneously. Contributions to collective decisions may vary among group members, yet inferring who has influence over group decisions is challenging, largely due to the multifaceted nature of influence. Here we collected high-resolution GPS data from five habituated meerkat groups in their natural habitat during foraging and developed a method to quantify individual influence over both group direction and speed.

Long-distance vocalizations of spotted hyenas contain individual, but not group, signatures.

In animal societies, identity signals are common, mediate interactions within groups, and allow individuals to discriminate group-mates from out-group competitors. However, individual recognition becomes increasingly challenging as group size increases and as signals must be transmitted over greater distances. Group vocal signatures may evolve when successful in-group/out-group distinctions are at the crux of fitness-relevant decisions, but group signatures alone are insufficient when differentiated within-group relationships are important for decision-making.

A practical guide for generating unsupervised, spectrogram-based latent space representations of animal vocalizations.

The manual detection, analysis and classification of animal vocalizations in acoustic recordings is laborious and requires expert knowledge. Hence, there is a need for objective, generalizable methods that detect underlying patterns in these data, categorize sounds into distinct groups and quantify similarities between them. Among all computational methods that have been proposed to accomplish this, neighbourhood-based dimensionality reduction of spectrograms to produce a latent space representation of calls stands out for its conceptual simplicity and effectiveness.

Confirmation and variability of the Allee effect incell populations, possible role of chemical signaling within cell clusters.

In studies of the unicellular eukaryote, many have anecdotally observed that cell dilution below a certain 'threshold density' causes cells to undergo a period of slow growth (lag). However, little is documented about the slow growth phase and the reason for different growth dynamics below and above this threshold density. In this paper, we extend and correct our earlier work to report an extensive set of experiments, including the use of new cell counting technology, that set this slow-to-fast growth transition on a much firmer biological basis.

Vocal Turn-Taking in Meerkat Group Calling Sessions.

Coordination is a fundamental aspect of social living, underlying processes ranging from the maintenance of group cohesion to the avoidance of competition. Coordination can manifest as synchronization, where individuals perform the same action at the same time but can also take the form of anti-synchronization or turn-taking. Turn-taking has mainly been studied in the context of the development of language [1] due to the fact that it is a universal feature in all languages and has been found to appear early in infancy [2, 3].

Inferring influence and leadership in moving animal groups.

Collective decision-making is a daily occurrence in the lives of many group-living animals, and can have critical consequences for the fitness of individuals. Understanding how decisions are reached, including who has influence and the mechanisms by which information and preferences are integrated, has posed a fundamental challenge. Here, we provide a methodological framework for studying influence and leadership in groups.

Challenges and solutions for studying collective animal behaviour in the wild.

Mobile animal groups provide some of the most compelling examples of self-organization in the natural world. While field observations of songbird flocks wheeling in the sky or anchovy schools fleeing from predators have inspired considerable interest in the mechanics of collective motion, the challenge of simultaneously monitoring multiple animals in the field has historically limited our capacity to study collective behaviour of wild animal groups with precision. However, recent technological advancements now present exciting opportunities to overcome many of these limitations.

Habitat and social factors shape individual decisions and emergent group structure during baboon collective movement.

For group-living animals traveling through heterogeneous landscapes, collective movement can be influenced by both habitat structure and social interactions. Yet research in collective behavior has largely neglected habitat influences on movement. Here we integrate simultaneous, high-resolution, tracking of wild baboons within a troop with a 3-dimensional reconstruction of their habitat to identify key drivers of baboon movement.

Both Nearest Neighbours and Long-term Affiliates Predict Individual Locations During Collective Movement in Wild Baboons.

In many animal societies, groups of individuals form stable social units that are shaped by well-delineated dominance hierarchies and a range of affiliative relationships. How do socially complex groups maintain cohesion and achieve collective movement? Using high-resolution GPS tracking of members of a wild baboon troop, we test whether collective movement in stable social groups is governed by interactions among local neighbours (commonly found in groups with largely anonymous memberships), social affiliates, and/or by individuals paying attention to global group structure. We construct candidate movement prediction models and evaluate their ability to predict the future trajectory of focal individuals.

Estimating uncertainty and reliability of social network data using Bayesian inference.

Social network analysis provides a useful lens through which to view the structure of animal societies, and as a result its use is increasingly widespread. One challenge that many studies of animal social networks face is dealing with limited sample sizes, which introduces the potential for a high level of uncertainty in estimating the rates of association or interaction between individuals. We present a method based on Bayesian inference to incorporate uncertainty into network analyses.