Observing the unwatchable: Integrating automated sensing, naturalistic observations and animal social network analysis in the age of big data

Collective signalling is shaped by feedbacks between signaller variation, receiver perception and acoustic environment in a simulated communication network

Communication takes place within a network of multiple signallers and receivers. Social network analysis provides tools to quantify how an individual's social positioning affects group dynamics and the subsequent biological consequences. However, network analysis is rarely applied to animal communication, likely due to the logistical difficulties of monitoring natural communication networks. We generated a simulated communication network to investigate how variation in individual communication behaviours generates network effects, and how this communication network's structure feeds back to affect future signalling interactions. We simulated competitive acoustic signalling interactions among chorusing individuals and varied several parameters related to communication and chorus size to examine their effects on calling output and social connections. Larger choruses had higher noise levels, and this reduced network density and altered the relationships between individual traits and communication network position. Hearing sensitivity interacted with chorus size to affect both individuals' positions in the network and the acoustic output of the chorus. Physical proximity to competitors influenced signalling, but a distinctive communication network structure emerged when signal active space was limited. Our model raises novel predictions about communication networks that could be tested experimentally and identifies aspects of information processing in complex environments that remain to be investigated. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

Seabirds show foraging site and route fidelity but demonstrate flexibility in response to local information

BACKGROUND

Fidelity to a given foraging location or route may be beneficial when environmental conditions are predictable but costly if conditions deteriorate or become unpredictable. Understanding the magnitude of fidelity displayed by different species and the processes that drive or erode it is therefore vital for understanding how fidelity may shape the demographic consequences of anthropogenic change. In particular, understanding the information that individuals may use to adjust their fidelity will facilitate improved predictions of how fidelity may change as environments change and the extent to which it will buffer individuals against such changes.

METHODS

We used movement data collected during the breeding season across eight years for common guillemots, Atlantic puffins, razorbills, and black-legged kittiwakes breeding on the Isle of May, Scotland to understand: (1) whether foraging site/route fidelity occurred within and between years, (2) whether the degree of fidelity between trips was predicted by personal foraging effort, and (3) whether different individuals made more similar trips when they overlapped in time at the colony prior to departure and/or when out at sea suggesting the use of the same local environmental cues or information on the decisions made by con- and heterospecifics.

RESULTS

All species exhibited site and route fidelity both within- and between-years, and fidelity between trips in guillemots and razorbills was related to metrics of foraging effort, suggesting they adjust fidelity to their personal foraging experience. We also found evidence that individuals used local environmental cues of prey location or availability and/or information gained by observing conspecifics when choosing foraging routes, particularly in puffins, where trips of individuals that overlapped temporally at the colony or out at sea were more similar.

CONCLUSIONS

The fidelity shown by these seabird species has the potential to put them at greater risk in the face of environmental change by driving individuals to continue using areas being degraded by anthropogenic pressures. However, our results suggest that individuals show some flexibility in their fidelity, which may promote resilience under environmental change. The benefits of this flexibility are likely to depend on numerous factors, including the rapidity and spatial scale of environmental change and the reliability of the information individuals use to choose foraging sites or routes, thus highlighting the need to better understand how organisms combine cues, prior experience, and other sources of information to make movement decisions.

Edge computing in wildlife behavior and ecology

Modern sensor technologies increasingly enrich studies in wildlife behavior and ecology. However, constraints on weight, connectivity, energy and memory availability limit their implementation. With the advent of edge computing, there is increasing potential to mitigate these constraints, and drive major advancements in wildlife studies.

Comparative approaches in social network ecology

Social systems vary enormously across the animal kingdom, with important implications for ecological and evolutionary processes such as infectious disease dynamics, anti-predator defence, and the evolution of cooperation. Comparing social network structures between species offers a promising route to help disentangle the ecological and evolutionary processes that shape this diversity. Comparative analyses of networks like these are challenging and have been used relatively little in ecology, but are becoming increasingly feasible as the number of empirical datasets expands. Here, we provide an overview of multispecies comparative social network studies in ecology and evolution. We identify a range of advancements that these studies have made and key challenges that they face, and we use these to guide methodological and empirical suggestions for future research. Overall, we hope to motivate wider publication and analysis of open social network datasets in animal ecology.

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. Our goal is to advance and bridge these two areas of inquiry and highlight the potential for their creative integration. To achieve this goal, we organise our review around the following themes: (1) identifying the promise of integrating collective behaviour and sensory ecology; (2) defining and exploring the concept of a 'sensory collective'; (3) considering the potential for sensory collectives to shape the evolution of sensory systems; (4) exploring examples from diverse taxa to illustrate neural circuits involved in sensing and collective behaviour; and (5) suggesting the need for creative conceptual and methodological advances to quantify 'sensescapes'. In the final section, (6) applications to biological conservation, we argue that these topics are timely, given the ongoing anthropogenic changes to sensory stimuli (e.g. via light, sound, and chemical pollution) which are anticipated to impact animal collectives and group-level behaviour and, in turn, ecosystem composition and function. Our synthesis seeks to provide a forward-looking perspective on how sensory ecologists and collective behaviourists can both learn from and inspire one another to advance our understanding of animal behaviour, ecology, adaptation, and evolution.

Differential provisioning roles, prey size, and prey abundance shape the dynamic feeding behavior of gray wolves

The demands of raising dependent young can influence the feeding behaviors of social carnivores, especially for individuals that are primarily responsible for provisioning young. We investigated how the feeding and provisioning behavior of a social carnivore, gray wolves (Canis lupus), are connected and shaped by extrinsic and intrinsic factors, and whether and how these patterns changed throughout the pup-rearing season (April-August). We found breeding wolves had shorter handling times of prey, lower probability of returning to kills, and greater probability of returning to homesites after kills compared to subordinate individuals. However, the feeding and provisioning behaviors of breeding individuals changed considerably over the pup-rearing season. Wolves had longer handling times and returned to provision pups directly after kills less frequently as annual prey abundance decreased. These patterns indicate that adult wolves prioritize meeting their own energetic demands over those of their pups when prey abundance decreases. We suggest that differential provisioning of offspring based on prey abundance is a behavioral mechanism by which group size adjusts to available resources via changes in neonate survival.

Bullying as an advertisement of social dominance in common waxbills

Bullying consists of preferentially attacking individuals lowest in the dominance hierarchy, and its functions are unclear because the most subordinate individuals do not pose social challenges to the aggressor. Instead, conflict is expected mostly between individuals of similar dominance rank or socially distant (i.e. weakly associated), among whom dominance relationships may not be well established. A possible function of bullying is that it may be used as a low-risk strategy of showing-off dominance to relevant third parties. To study this hypothesis, we monitored aggressions during feeding, the composition of audiences, dominance hierarchy and social network of common waxbills (Estrilda astrild) in an open-air mesocosm, and tested (i) whether their aggressions show a pattern of bullying, and (ii) whether audience effects influence aggressiveness. Waxbills showed bullying, most often attacking the lowest ranking individuals rather than socially distant individuals or those of similar dominance rank, and aggressions increased when the audience included socially distant individuals, indicating a signalling function of bullying. Showing-off dominance in the presence of socially distant individuals may be a strategy to manage dominance hierarchies, avoiding direct fights with potentially dangerous opponents in the audience. We suggest that bullying is a safe manner of managing dominance hierarchies, by signalling dominance status to potential opponents.

Cow characteristics associated with the variation in number of contacts between dairy cows

In modern freestall barns where large groups of cows are housed together, the behavior displayed by herd mates can influence the welfare and production of other individuals. Therefore, understanding social interactions in groups of dairy cows is important to enhance herd management and optimize the outcomes of both animal health and welfare in the future. Many factors can affect the number of social contacts in a group. This study aimed to identify which characteristics of a cow are associated with the number of contacts it has with other group members in 2 different functional areas (feeding and resting area) to increase our understanding of the social behavior of dairy cows. Inside 2 herds housed in freestall barns with around 200 lactating cows each, cow positions were recorded with an ultra-wideband real-time location system collecting all cows' positions every second over 2 wk. Using the positioning data of the cows, we quantified the number of contacts between them, assuming that cows spending time in proximity to one another (within a distance of 2.5 m for at least 10 min per day) were interacting socially. We documented in which barn areas these interactions occurred and used linear mixed models to investigate if lactation stage, parity, breed, pregnancy status, estrus, udder health, and claw health affect the number of contacts. We found variation in the number of contacts a cow had between individuals in both functional areas. Cows in later lactation had more contacts in the feeding area than cows in early lactation. Furthermore, in one herd, higher parity cows had fewer contacts in the feeding area than first parity cows, and in the other herd, cows in third parity or higher had more contacts in the resting area. This study indicates that cow characteristics such as parity and days in milk are associated with the number of contacts a cow has daily to its herd mates and provides useful information for further research on social interactions of dairy cows.

Familiarity, age, weaning and health status impact social proximity networks in dairy calves

Social network analysis in dairy calves has not been widely studied, with previous studies limited by the short study duration, and low number of animals and replicates. In this study, we investigated social proximity interactions of 79 Holstein-Friesian calves from 5 cohorts for up to 76 days. Networks were computed using 4-day aggregated associations obtained from ultrawideband location sensor technology, at 1 Hz sampling rate. The effect of age, familiarity, health, and weaning status on the social proximity networks of dairy calves was assessed. Networks were poorly correlated (non-stable) between the different 4-day periods, in the majority of them calves associated heterogeneously, and individuals assorted based on previous familiarity for the whole duration of the study. Age significantly increased association strength, social time and eigenvector centrality and significantly decreased closeness and coefficient of variation in association (CV). Sick calves had a significantly lower strength, social time, centrality and CV, and significantly higher closeness compared to the healthy calves. During and after weaning, calves had significantly lower closeness and CV, and significantly higher association strength, social time, and eigenvector centrality. These results indicate that age, familiarity, weaning, and sickness have a significant impact on the variation of social proximity interaction of calves.

Leveraging big data to uncover the eco-evolutionary factors shaping behavioural development

Mapping the eco-evolutionary factors shaping the development of animals' behavioural phenotypes remains a great challenge. Recent advances in 'big behavioural data' research-the high-resolution tracking of individuals and the harnessing of that data with powerful analytical tools-have vastly improved our ability to measure and model developing behavioural phenotypes. Applied to the study of behavioural ontogeny, the unfolding of whole behavioural repertoires can be mapped in unprecedented detail with relative ease. This overcomes long-standing experimental bottlenecks and heralds a surge of studies that more finely define and explore behavioural-experiential trajectories across development. In this review, we first provide a brief guide to state-of-the-art approaches that allow the collection and analysis of high-resolution behavioural data across development. We then outline how such approaches can be used to address key issues regarding the ecological and evolutionary factors shaping behavioural development: developmental feedbacks between behaviour and underlying states, early life effects and behavioural transitions, and information integration across development.

Behavioural ecology at the spatial-social interface

Spatial and social behaviour are fundamental aspects of an animal's biology, and their social and spatial environments are indelibly linked through mutual causes and shared consequences. We define the 'spatial-social interface' as intersection of social and spatial aspects of individuals' phenotypes and environments. Behavioural variation at the spatial-social interface has implications for ecological and evolutionary processes including pathogen transmission, population dynamics, and the evolution of social systems. We link spatial and social processes through a foundation of shared theory, vocabulary, and methods. We provide examples and future directions for the integration of spatial and social behaviour and environments. We introduce key concepts and approaches that either implicitly or explicitly integrate social and spatial processes, for example, graph theory, density-dependent habitat selection, and niche specialization. Finally, we discuss how movement ecology helps link the spatial-social interface. Our review integrates social and spatial behavioural ecology and identifies testable hypotheses at the spatial-social interface.

Patterns of extra-territorial nest-box visits in a songbird suggest a role in extrapair mating

Many animals make visits outside of their territory during the breeding period, but these are typically infrequent and difficult to observe. As a consequence, comprehensive data on extra-territorial movements at the population-level are scarce and the function of this behavior remains poorly understood. Using an automated nest-box visit tracking system in a wild blue tit population over six breeding seasons, we recorded all extra-territorial nest-box visits (n = 22 137) related to 1195 individual breeding attempts (761 unique individuals). Sixty-two percent of breeders made at least one extra-territorial visit between the onset of nest building and the day of fledging of their offspring, and individuals visited another nest-box on average on 11% of the days during this period. Visit behavior differed clearly between the sexes, with males making over three times as many extra-territorial forays as females. There was a strong overall seasonal decline in visit behavior, but this was sex dependent, with females showing a strong reduction in the number of extra-territorial visits before the onset of egg laying and males showing a strong and sudden reduction on the day their offspring hatched. The likelihood of visiting a particular nest-box declined sharply with the distance to that box, and blue tits almost exclusively visited direct neighbors. Individuals were more likely to have extrapair offspring with an individual whose box they visited, but they were not more likely to disperse to a box they had visited. Thus, our results are inconsistent with the hypothesis that extra-territorial nest-box visits serve to inform dispersal decisions, but suggest that such visits are linked to extrapair mating opportunities.

Exploiting animal personality to reduce chronic stress in captive fish populations

Chronic stress is a major source of welfare problems in many captive populations, including fishes. While we have long known that chronic stress effects arise from maladaptive expression of acute stress response pathways, predicting where and when problems will arise is difficult. Here we highlight how insights from animal personality research could be useful in this regard. Since behavior is the first line of organismal defense when challenged by a stressor, assays of shy-bold type personality variation can provide information about individual stress response that is expected to predict susceptibility to chronic stress. Moreover, recent demonstrations that among-individual differences in stress-related physiology and behaviors are underpinned by genetic factors means that selection on behavioral biomarkers could offer a route to genetic improvement of welfare outcomes in captive fish stocks. Here we review the evidence in support of this proposition, identify remaining empirical gaps in our understanding, and set out appropriate criteria to guide development of biomarkers. The article is largely prospective: fundamental research into fish personality shows how behavioral biomarkers could be used to achieve welfare gains in captive fish populations. However, translating potential to actual gains will require an interdisciplinary approach that integrates the expertise and viewpoints of researchers working across animal behavior, genetics, and welfare science.

Socially transferred materials: why and how to study them

When biological material is transferred from one individual's body to another, as in ejaculate, eggs, and milk, secondary donor-produced molecules are often transferred along with the main cargo, and influence the physiology and fitness of the receiver. Both social and solitary animals exhibit such social transfers at certain life stages. The secondary, bioactive, and transfer-supporting components in socially transferred materials have evolved convergently to the point where they are used in applications across taxa and type of transfer. The composition of these materials is typically highly dynamic and context dependent, and their components drive the physiological and behavioral evolution of many taxa. Our establishment of the concept of socially transferred materials unifies this multidisciplinary topic and will benefit both theory and applications.

Community structure of the solitary giant pandas is maintained by indirect social connections

BACKGROUND

Indirect interactions between individual solitary mammals, such as the giant panda, are often overlooked because of their nature, yet are important for maintaining the necessary sociality in solitary species.

METHODS AND RESULTS

Here, we determined the genetic identity of all giant panda individuals in a local population and matched these identities with their associations to determine social network of this solitary animal. Total thirty-five giant panda individuals were found in our field survey, and we constructed genetic and social networks for thirty-three individuals who successfully obtained genetic, age and sex information. The results showed that sex had great impact on both social network and genetic network, and age may have the potential to influence the social network of the giant pandas. Adult males, mostly in the central of the social network, which appeared significantly larger network connections than adult females. Due to the female-biased dispersal pattern of wild giant pandas, male-male pairs showed higher relatedness than female-female ones and multi-generational patrilinear assemblages are expected in the study area.

CONCLUSIONS

The relatedness of individuals has an influence on the formation of community social structure of giant pandas, and indirect interactions among solitary giant pandas potentially function to reduce competition for resources and inbreeding.

Ultra-light photosensor collars to monitor Arctic lemming activity

Background

Studying the anti-predatory behavior of mammals represents an important challenge, especially for fossorial small mammals that hide in burrows. In the Arctic, such behaviors are critical to the survival of lemmings considering that predation risks are high every summer. Because detailed information about how lemmings use burrows as hideouts is still lacking, we developed a 1.59 g photosensitive collar to record any event of a small mammal moving between a dark area (e.g., burrow) and a bright area (e.g., outside the burrow). Tests of how collars affected lemming behavior were conducted in captivity in Cambridge Bay, Nunavut, Canada, in November 2019 and field tests were conducted on Bylot Island, Nunavut, Canada, in August 2021.

Results

The device was made of two chemical batteries and a printed circuit board (PCB) equipped with a photosensor and a real-time clock that recorded amplitude transient thresholds of light (lux) continuously. In accordance with ethical use of such devices, we verified that no abnormal loss of body mass was observed in captive or free-ranging lemmings, and no difference in recapture rates were observed between those with and without a collar, though we could not test this for periods longer than 108 h. Measurements of light intensities revealed consistent patterns with high lux levels at mid-day and lowest during the night. Lemmings showed clearly defined behavioral patterns alternating between periods outside and inside burrows. Despite 24-h daylight in the middle of the summer, August nighttime (i.e., 11 PM to 4 AM) lux levels were insufficient for amplitude transient thresholds to be reached.

Conclusion

By taking advantage of the long periods of daylight in the Arctic, such technology is very promising as it sets new bases for passive recording of behavioral parameters and builds on the prospect of further miniaturization of batteries and PCBs.

Evaluation of the Students’ Learning Status in the Foreign Language Classroom Based on Machine Vision

In order to improve the effectiveness of the evaluation of student’s learning status in foreign language classrooms, this paper applies machine vision to classroom teaching. Through an in-depth analysis of the relative motion relationship between the end marker points of classroom feature recognition and the center point of the machine vision system window, this paper first proposes an autonomous tracking motion algorithm of the machine vision system window based on the preset field of view parameters. Moreover, this paper realizes the motion function of the window to track the marker points autonomously, completes the simulation analysis through two sets of planned trajectories and two sets of master hands to collect the actual trajectories, and verifies the correctness and feasibility of the algorithm. The research study shows that the algorithm based on machine vision proposed in this paper can effectively judge the real-time state of students in the foreign language classroom.

Effects of the social environment on vertebrate fitness and health in nature: Moving beyond the stress axis

Social interactions are a ubiquitous feature of the lives of vertebrate species. These may be cooperative or competitive, and shape the dynamics of social systems, with profound effects on individual behavior, physiology, fitness, and health. On one hand, a wealth of studies on humans, laboratory animal models, and captive species have focused on understanding the relationships between social interactions and individual health within the context of disease and pathology. On the other, ecological studies are attempting an understanding of how social interactions shape individual phenotypes in the wild, and the consequences this entails in terms of adaptation. Whereas numerous studies in wild vertebrates have focused on the relationships between social environments and the stress axis, much remains to be done in understanding how socially-related activation of the stress axis coordinates other key physiological functions related to health. Here, we review the state of our current knowledge on the effects that social interactions may have on other markers of vertebrate fitness and health. Building upon complementary findings from the biomedical and ecological fields, we identify 6 key physiological functions (cellular metabolism, oxidative stress, cellular senescence, immunity, brain function, and the regulation of biological rhythms) which are intimately related to the stress axis, and likely directly affected by social interactions. Our goal is a holistic understanding of how social environments affect vertebrate fitness and health in the wild. Whereas both social interactions and social environments are recognized as important sources of phenotypic variation, their consequences on vertebrate fitness, and the adaptive nature of social-stress-induced phenotypes, remain unclear. Social flexibility, or the ability of an animal to change its social behavior with resulting changes in social systems in response to fluctuating environments, has emerged as a critical underlying factor that may buffer the beneficial and detrimental effects of social environments on vertebrate fitness and health.

Frontiers in quantifying wildlife behavioural responses to chemical pollution

Animal behaviour is remarkably sensitive to disruption by chemical pollution, with widespread implications for ecological and evolutionary processes in contaminated wildlife populations. However, conventional approaches applied to study the impacts of chemical pollutants on wildlife behaviour seldom address the complexity of natural environments in which contamination occurs. The aim of this review is to guide the rapidly developing field of behavioural ecotoxicology towards increased environmental realism, ecological complexity, and mechanistic understanding. We identify research areas in ecology that to date have been largely overlooked within behavioural ecotoxicology but which promise to yield valuable insights, including within- and among-individual variation, social networks and collective behaviour, and multi-stressor interactions. Further, we feature methodological and technological innovations that enable the collection of data on pollutant-induced behavioural changes at an unprecedented resolution and scale in the laboratory and the field. In an era of rapid environmental change, there is an urgent need to advance our understanding of the real-world impacts of chemical pollution on wildlife behaviour. This review therefore provides a roadmap of the major outstanding questions in behavioural ecotoxicology and highlights the need for increased cross-talk with other disciplines in order to find the answers.

Conceptualizing the 3D niche and vertical space use

Spatial partitioning in ecological communities has predominantly been described in two dimensions, yet habitat is complex and 3D. Complex space use mediates community structure and interaction strength by expanding spatial, temporal, and dietary dimensions. Vertical stratification of resources provides opportunities for novel specializations, creating a 3D niche. Competition and predation are mediated by 3D space use, as individuals use the vertical axis to access prey, flee predators, or avoid competitors. The 3D niche is important for long-term conservation strategies as species must navigate tradeoffs in habitat use between strata-specific threats and suboptimal habitat patches. Ultimately, elucidating the 3D niche has implications for protected area management and corridor design that directly influence species persistence and ecosystem function in a rapidly changing world.

Predicting the impacts of chemical pollutants on animal groups

Chemical pollution is among the fastest-growing agents of global change. Synthetic chemicals with diverse modes-of-action are being detected in the tissues of wildlife and pervade entire food webs. Although such pollutants can elicit a range of sublethal effects on individual organisms, research on how chemical pollutants affect animal groups is severely lacking. Here we synthesise research from two related, but largely segregated fields - ecotoxicology and behavioural ecology - to examine pathways by which chemical contaminants could disrupt processes that govern the emergence, self-organisation, and collective function of animal groups. Our review provides a roadmap for prioritising the study of chemical pollutants within the context of sociality and highlights important methodological advancements for future research.

Sex, not social behavior, predicts fecal glucocorticoid metabolite concentrations in a facultatively social rodent, the highland tuco-tuco (Ctenomys opimus)

Social relationships may influence circulating glucocorticoid levels, particularly in group-living species in which individuals regularly engage in interactions with conspecifics. The effects of such interactions appear to vary, with greater social contact being associated with increased glucocorticoid concentrations in some species but decreased concentrations in others. These distinct responses raise intriguing questions regarding relationships among social behavior, individual phenotypes, and glucocorticoid physiology. To explore such relationships in a free-living mammal with a dynamic social organization, we quantified variation in baseline glucocorticoids in a population of highland tuco-tucos (Ctenomys opimus) from Jujuy Province, Argentina. These subterranean rodents are facultatively social, with lone and group-living individuals regularly occurring within the same population. To assess potential endocrine correlates of this behavioral variability, we examined differences in baseline fecal glucocorticoid metabolite (fGCm) concentrations as a function of social group size and composition as well as several metrics of social behavior derived from social network analyses. Despite marked variability in social relationships among the 37 (12 male, 25 female) free-living tuco-tucos sampled, none of the measures of social behavior examined were significant predictors of variation in fGCm concentrations. In contrast, individual variation in glucocorticoid metabolites was best explained by sex, with males having higher fGCm concentrations than females. These analyses provide the first characterization of the glucocorticoid physiology of highland tuco-tucos and underscore the potential importance of intrinsic phenotypic factors (e.g., sex) in shaping glucocorticoid variation in free-living mammals.

Songbird parents coordinate offspring provisioning at fine spatio-temporal scales

For parents, rearing offspring together is far from a purely cooperative exercise, as a conflict of interest (‘sexual conflict’) exists over their optimum level of care. Recent theory emphasizes that sexual conflict can be evolutionarily resolved, and complete parental cooperation can occur, if parents directly respond (‘negotiate’) to each other and coordinate their level of care. Despite numerous experiments showing that parents are responsive to each other, we still lack empirical evidence of the behavioural mechanisms by which this negotiation occurs.

In this study, we investigated the spatio‐temporal coordination of parental provisioning behaviour as a possible mechanism of negotiation over parental care.

We deployed an automated radiotracking technology to track the provisioning activity of wild great tit Parus major pairs during chick rearing. Our analyses represent the first detailed spatial and temporal description of foraging coordination in songbird parents in a natural context.

We demonstrate that the foraging behaviour of the two parents is highly coordinated in space and time, with parents changing their foraging locations in conjunction with their partners' movements.

Therefore, foraging coordination could be a mechanism by which parents directly monitor and respond to each other's level of investment.

Behavioral Neuroscience in the Era of Genomics: Tools and Lessons for Analyzing High-Dimensional Datasets

Behavioral neuroscience underwent a technology-driven revolution with the emergence of machine-vision and machine-learning technologies. These technological advances facilitated the generation of high-resolution, high-throughput capture and analysis of complex behaviors. Therefore, behavioral neuroscience is becoming a data-rich field. While behavioral researchers use advanced computational tools to analyze the resulting datasets, the search for robust and standardized analysis tools is still ongoing. At the same time, the field of genomics exploded with a plethora of technologies which enabled the generation of massive datasets. This growth of genomics data drove the emergence of powerful computational approaches to analyze these data. Here, we discuss the composition of a large behavioral dataset, and the differences and similarities between behavioral and genomics data. We then give examples of genomics-related tools that might be of use for behavioral analysis and discuss concepts that might emerge when considering the two fields together.

Social networks and the conservation of fish

Despite our critical dependence on aquatic wildlife, we lack a complete understanding of the drivers of population stability and structure for most fish species. Social network analysis has been increasingly used to investigate animal societies as it explicitly links individual decision-making to population-level processes and demography. While the study of social structure is of great ecological interest, it is also potentially important for species of economic value or of conservation concern. To date however, there has been little focus on how social processes are likely to influence the conservation of fish populations. Here we identify applications for how a social network approach can help address broad fish conservation themes such as population structure, biological invasions or fisheries management. We discuss the burgeoning opportunities offered and challenges still faced by current technologies to integrate social network approaches within fish conservation.

Indirect Genetic Effects: A Cross-disciplinary Perspective on Empirical Studies

Indirect genetic effects (IGE) occur when an individual's phenotype is influenced by genetic variation in conspecifics. Opportunities for IGE are ubiquitous, and, when present, IGE have profound implications for behavioral, evolutionary, agricultural, and biomedical genetics. Despite their importance, the empirical study of IGE lags behind the development of theory. In large part, this lag can be attributed to the fact that measuring IGE, and deconvoluting them from the direct genetic effects of an individual's own genotype, is subject to many potential pitfalls. In this Perspective, we describe current challenges that empiricists across all disciplines will encounter in measuring and understanding IGE. Using ideas and examples spanning evolutionary, agricultural, and biomedical genetics, we also describe potential solutions to these challenges, focusing on opportunities provided by recent advances in genomic, monitoring, and phenotyping technologies. We hope that this cross-disciplinary assessment will advance the goal of understanding the pervasive effects of conspecific interactions in biology.

Foreword to the Special Issue on ‘The rapidly expanding role of drones as a tool for wildlife research’

Drones have emerged as a popular wildlife research tool, but their use for many species and environments remains untested and research is needed on validation of sampling approaches that are optimised for unpiloted aircraft. Here, we present a foreword to a special issue that features studies pushing the taxonomic and innovation boundaries of drone research and thus helps address these knowledge and application gaps. We then conclude by highlighting future drone research ideas that are likely to push biology and conservation in exciting new directions.

Automatic mapping of multiplexed social receptive fields by deep learning and GPU-accelerated 3D videography

Social interactions powerfully impact the brain and the body, but high-resolution descriptions of these important physical interactions and their neural correlates are lacking. Currently, most studies rely on labor-intensive methods such as manual annotation. Scalable and objective tracking methods are required to understand the neural circuits underlying social behavior. Here we describe a hardware/software system and analysis pipeline that combines 3D videography, deep learning, physical modeling, and GPU-accelerated robust optimization, with automatic analysis of neuronal receptive fields recorded in interacting mice. Our system ("3DDD Social Mouse Tracker") is capable of fully automatic multi-animal tracking with minimal errors (including in complete darkness) during complex, spontaneous social encounters, together with simultaneous electrophysiological recordings. We capture posture dynamics of multiple unmarked mice with high spatiotemporal precision (~2 mm, 60 frames/s). A statistical model that relates 3D behavior and neural activity reveals multiplexed 'social receptive fields' of neurons in barrel cortex. Our approach could be broadly useful for neurobehavioral studies of multiple animals interacting in complex low-light environments.

Quantifying song behavior in a free-living, light-weight, mobile bird using accelerometers

To acquire a fundamental understanding of animal communication, continuous observations in a natural setting and at an individual level are required. Whereas the use of animal-borne acoustic recorders in vocal studies remains challenging, light-weight accelerometers can potentially register individuals' vocal output when this coincides with body vibrations. We collected one-dimensional accelerometer data using light-weight tags on a free-living, crepuscular bird species, the European Nightjar (Caprimulgus europaeus). We developed a classification model to identify four behaviors (rest, sing, fly, and leap) from accelerometer data and, for the purpose of this study, validated the classification of song behavior. Male nightjars produce a distinctive "churring" song while they rest on a stationary song post. We expected churring to be associated with body vibrations (i.e., medium-amplitude body acceleration), which we assumed would be easy to distinguish from resting (i.e., low-amplitude body acceleration). We validated the classification of song behavior using simultaneous GPS tracking data (i.e., information on individuals' movement and proximity to audio recorders) and vocal recordings from stationary audio recorders at known song posts of one tracked individual. Song activity was detected by the classification model with an accuracy of 92%. Beyond a threshold of 20 m from the audio recorders, only 8% of the classified song bouts were recorded. The duration of the detected song activity (i.e., acceleration data) was highly correlated with the duration of the simultaneously recorded song bouts (correlation coefficient = 0.87, N = 10, S = 21.7, p = .001). We show that accelerometer-based identification of vocalizations could serve as a promising tool to study communication in free-living, small-sized birds and demonstrate possible limitations of audio recorders to investigate individual-based variation in song behavior.

Detecting Animal Contacts-A Deep Learning-Based Pig Detection and Tracking Approach for the Quantification of Social Contacts

The identification of social interactions is of fundamental importance for animal behavioral studies, addressing numerous problems like investigating the influence of social hierarchical structures or the drivers of agonistic behavioral disorders. However, the majority of previous studies often rely on manual determination of the number and types of social encounters by direct observation which requires a large amount of personnel and economical efforts. To overcome this limitation and increase research efficiency and, thus, contribute to animal welfare in the long term, we propose in this study a framework for the automated identification of social contacts. In this framework, we apply a convolutional neural network (CNN) to detect the location and orientation of pigs within a video and track their movement trajectories over a period of time using a Kalman filter (KF) algorithm. Based on the tracking information, we automatically identify social contacts in the form of head–head and head–tail contacts. Moreover, by using the individual animal IDs, we construct a network of social contacts as the final output. We evaluated the performance of our framework based on two distinct test sets for pig detection and tracking. Consequently, we achieved a Sensitivity, Precision, and F1-score of 94.2%, 95.4%, and 95.1%, respectively, and a MOTA score of 94.4%. The findings of this study demonstrate the effectiveness of our keypoint-based tracking-by-detection strategy and can be applied to enhance animal monitoring systems.

Recumbency as an Equine Welfare Indicator in Geriatric Horses and Horses with Chronic Orthopaedic Disease

Recumbency is a prerequisite for horses achieving rapid eye movement (REM) sleep and completing a full sleep cycle. An inability to lie down due to environmental insecurities or pain results in REM sleep deficiency, which can cause substantial impairment of welfare and health. Therefore, the present study used wearable automated sensor technology on 83 horses housed in an animal sanctuary to measure and compare the recumbency, locomotion, and standing time budgets of geriatric horses with and without chronic lameness to younger adult sound and lame horses. Recumbency times ranged from 0 to 319 min per day with an overall mean of 67.4 (±61.9) minutes; the time budget for locomotion was 19.1% (±11.2% s.d.) and for standing 75.6% (±13.1 s.d.). Interestingly, neither age nor lameness due to chronic orthopedic disease had a significant influence on recumbency times in this study. Eight horses showed symptoms of REM deficit. These horses had significantly shorter lying times (7.99 ± 11.4 min) and smaller locomotion time budgets than the other horses enrolled in this study (73.8 ± 61.8 min), indicating a general compromise of well-being. Thus, wearable sensor technology can be used to identify horses with low recumbency times at risk for REM sleep deficiency and to assess and monitor equine welfare objectively.

Social evolution in mammals

[Figure: see text].

Animal culture research should include avian nest construction

Material culture—that is, group-shared and socially learned object-related behaviour(s)—is a widespread and diverse phenomenon in humans. For decades, researchers have sought to confirm the existence of material culture in non-human animals; however, the main study systems of interest—namely, tool making and/or using non-human primates and corvids—cannot provide such confirmatory evidence: because long-standing ethical and logistical constraints handicap the collection of necessary experimental data. Synthesizing evidence across decades and disciplines, here, I present a novel framework for (mechanistic, developmental, behavioural, and comparative) study on animal material culture: avian nest construction.

Body language signals for rodent social communication

Integration of social cues to initiate adaptive emotional and behavioral responses is a fundamental aspect of animal and human behavior. In humans, social communication includes prominent nonverbal components, such as social touch, gestures and facial expressions. Comparative studies investigating the neural basis of social communication in rodents has historically been centered on olfactory signals and vocalizations, with relatively less focus on non-verbal social cues. Here, we outline two exciting research directions: First, we will review recent observations pointing to a role of social facial expressions in rodents. Second, we will review observations that point to a role of 'non-canonical' rodent body language: body posture signals beyond stereotyped displays in aggressive and sexual behavior. In both sections, we will outline how social neuroscience can build on recent advances in machine learning, robotics and micro-engineering to push these research directions forward towards a holistic systems neurobiology of rodent body language.

Infectious diseases and social distancing in nature

Spread of contagious pathogens critically depends on the number and types of contacts between infectious and susceptible hosts. Changes in social behavior by susceptible, exposed, or sick individuals thus have far-reaching downstream consequences for infectious disease spread. Although "social distancing" is now an all too familiar strategy for managing COVID-19, nonhuman animals also exhibit pathogen-induced changes in social interactions. Here, we synthesize the effects of infectious pathogens on social interactions in animals (including humans), review what is known about underlying mechanisms, and consider implications for evolution and epidemiology.

New dimensions for animal communication networks: space and time

Communication is a social process and usually occurs in a network of signalers and receivers. While social network analysis has received enormous recent attention from animal behaviorists, there have been relatively few attempts to apply these techniques to communication networks. Communication networks have the potential to offer novel insights into social network studies, and yet are especially challenging subjects, largely because of their unique spatiotemporal characteristics. Namely, signals propagate through the environment, often dissociating from the body of the signaler, to influence receiver behavior. The speed of signal propagation and the signal's active space will affect the congruence of communication networks and other types of social network; in extreme cases the signal may persist and only first be detected long after the signaler has left the area. Other signals move more rapidly and over greater distances than the signaler could possibly move to reach receivers. We discuss the spatial and temporal consequences of signaling in networks and highlight the distinction between the physical location of the signaler and the spread of influence of its signals, the effects of signal modality and receiver sensitivity on communication network properties, the potential for feedbacks between network layers, and approaches to analyzing spatial and temporal change in communication networks in conjunction with other network layers.