Added Value of Sensor-Based Behavioural Monitoring in an Infectious Disease Study with Sheep Infected with Toxoplasma gondii

Sensor technologies are increasingly used to monitor laboratory animal behaviour. The aim of this study was to investigate the added value of using accelerometers and video to monitor the activity and drinking behaviour of three rams from 5 days before to 22 days after inoculation with Toxoplasma gondii. We computed the activity from accelerometer data as the vectorial dynamic body acceleration (VDBA). In addition, we assessed individual drinking behaviour from video, using frame differencing above the drinker to identify drinking bouts, and Aruco markers for individual identification. Four days after inoculation, rams developed fever and activity decreased. The daytime VDBA from days 4 to 10 was 60-80% of that before inoculation. Animal caretakers scored rams as lethargic on days 5 and 6 and, for one ram, also on the morning of day 7. Video analysis showed that each ram decreased its number of visits to the drinker, as well as its time spent at the drinker, by up to 50%. The fever and corresponding sickness behaviours lasted until day 10. Overall, while we recognize the limited conclusiveness due to the small number of animals, the sensor technologies provided continuous, individual, detailed, and objective data and offered additional insights as compared to routine observations. We recommend the wider implementation of such technologies in animal disease trials to refine experiments and guarantee the quality of experimental results.

Automated monitoring of brush use in dairy cattle

Access to brushes allows for natural scratching behaviors in cattle, especially in confined indoor settings. Cattle are motivated to use brushes, but brush use varies with multiple factors including social hierarchy and health. Brush use might serve an indicator of cow health or welfare, but practical application of these measures requires accurate and automated monitoring tools. This study describes a machine learning approach to monitor brush use by dairy cattle. We aimed to capture the daily brush use by integrating data on the rotation of a mechanical brush with data on cow identify derived from either 1) low-frequency radio frequency identification or 2) a computer vision system using fiducial markers. We found that the computer vision system outperformed the RFID system in accuracy, and that the machine learning algorithms enhanced the precision of the brush use estimates. This study presents the first description of a fiducial marker-based computer vision system for monitoring individual cattle behavior in a group setting; this approach could be applied to develop automated measures of other behaviors with the potential to better assess welfare and improve the care for farm animals.

Modelling animal social networks: New solutions and future directions

Research Highlight: Ross, C. T., McElreath, R., & Redhead, D. (2023). Modelling animal network data in R using STRAND. Journal of Animal Ecology. https://doi.org/10.1111/1365-2656.14021. One of the most important insights in ecology over the past decade has been that the social connections among animals affect a wide range of ecological and evolutionary processes. However, despite over 20 years of study effort on this topic, generating knowledge from data on social associations and interactions remains fraught with problems. Redhead et al. present an R package-STRAND-that extends the current animal social network analysis toolbox in two ways. First, they provide a simple R interfaces to implement generative network models, which are an alternative to regression approaches that draw inference by simulating the data-generating process. Second, they implement these models in a Bayesian framework, allowing uncertainty in the observation process to be carried through to hypothesis testing. STRAND therefore fills an important gap for hypothesis testing using network data. However, major challenges remain, and while STRAND represents an important advance, generating robust results continues to require careful study design, considerations in terms of statistical methods and a plurality of approaches.

Group-level differences in social network structure remain repeatable after accounting for environmental drivers

Individuals show consistent between-individual behavioural variation when they interact with conspecifics or heterospecifics. Such patterns might underlie emergent group-specific behavioural patterns and between-group behavioural differences. However, little is known about (i) how social and non-social drivers (external drivers) shape group-level social structures and (ii) whether animal groups show consistent between-group differences in social structure after accounting for external drivers. We used automated tracking to quantify daily social interactions and association networks in 12 colonies of zebra finches (Taeniopygia guttata). We quantified the effects of five external drivers (group size, group composition, ecological factors, physical environments and methodological differences) on daily interaction and association networks and tested whether colonies expressed consistent differences in day-to-day network structure after controlling for these drivers. Overall, we found that external drivers contribute significantly to network structure. However, even after accounting for the contribution of external drivers, there remained significant support for consistent between-group differences in both interaction (repeatability R: up to 0.493) and association (repeatability R: up to 0.736) network structures. Our study demonstrates how group-level differences in social behaviour can be partitioned into different drivers of variation, with consistent contributions from both social and non-social factors.

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.

Automated monitoring of honey bees with barcodes and artificial intelligence reveals two distinct social networks from a single affiliative behavior

Barcode-based tracking of individuals is revolutionizing animal behavior studies, but further progress hinges on whether in addition to determining an individual's location, specific behaviors can be identified and monitored. We achieve this goal using information from the barcodes to identify tightly bounded image regions that potentially show the behavior of interest. These image regions are then analyzed with convolutional neural networks to verify that the behavior occurred. When applied to a challenging test case, detecting social liquid transfer (trophallaxis) in the honey bee hive, this approach yielded a 67% higher sensitivity and an 11% lower error rate than the best detector for honey bee trophallaxis so far. We were furthermore able to automatically detect whether a bee donates or receives liquid, which previously required manual observations. By applying our trophallaxis detector to recordings from three honey bee colonies and performing simulations, we discovered that liquid exchanges among bees generate two distinct social networks with different transmission capabilities. Finally, we demonstrate that our approach generalizes to detecting other specific behaviors. We envision that its broad application will enable automatic, high-resolution behavioral studies that address a broad range of previously intractable questions in evolutionary biology, ethology, neuroscience, and molecular biology.

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.

The social transmission of stress in animal collectives

The stress systems are powerful mediators between the organism's systemic dynamic equilibrium and changes in its environment beyond the level of anticipated fluctuations. Over- or under-activation of the stress systems' responses can impact an animal's health, survival and reproductive success. While physiological stress responses and their influence on behaviour and performance are well understood at the individual level, it remains largely unknown whether-and how-stressed individuals can affect the stress systems of other group members, and consequently their collective behaviour. Stressed individuals could directly signal the presence of a stressor (e.g. via an alarm call or pheromones), or an acute or chronic activation of the stress systems could be perceived by others (as an indirect cue) and spread via social contagion. Such social transmission of stress responses could then amplify the effects of stressors by impacting social interactions, social dynamics and the collective performance of groups. As the neuroendocrine pathways of the stress response are highly conserved among vertebrates, transmission of physiological stress states could be more widespread among non-human animals than previously thought. We therefore suggest that identifying the extent to which stress transmission modulates animal collectives represents an important research avenue.

Machine learning reveals cryptic dialects that explain mate choice in a songbird

Culturally transmitted communication signals - such as human language or bird song - can change over time through cultural drift, and the resulting dialects may consequently enhance the separation of populations. However, the emergence of song dialects has been considered unlikely when songs are highly individual-specific, as in the zebra finch (Taeniopygia guttata). Here we show that machine learning can nevertheless distinguish the songs from multiple captive zebra finch populations with remarkable precision, and that 'cryptic song dialects' predict strong assortative mating in this species. We examine mating patterns across three consecutive generations using captive populations that have evolved in isolation for about 100 generations. We cross-fostered eggs within and between these populations and used an automated barcode tracking system to quantify social interactions. We find that females preferentially pair with males whose song resembles that of the females' adolescent peers. Our study shows evidence that in zebra finches, a model species for song learning, individuals are sensitive to differences in song that have hitherto remained unnoticed by researchers.

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.

Permutation tests for hypothesis testing with animal social network data: Problems and potential solutions

Permutation tests are widely used to test null hypotheses with animal social network data, but suffer from high rates of type I and II error when the permutations do not properly simulate the intended null hypothesis.Two common types of permutations each have limitations. Pre-network (or datastream) permutations can be used to control 'nuisance effects' like spatial, temporal or sampling biases, but only when the null hypothesis assumes random social structure. Node (or node-label) permutation tests can test null hypotheses that include nonrandom social structure, but only when nuisance effects do not shape the observed network.We demonstrate one possible solution addressing these limitations: using pre-network permutations to adjust the values for each node or edge before conducting a node permutation test. We conduct a range of simulations to estimate error rates caused by confounding effects of social or non-social structure in the raw data.Regressions on simulated datasets suggest that this 'double permutation' approach is less likely to produce elevated error rates relative to using only node permutations, pre-network permutations or node permutations with simple covariates, which all exhibit elevated type I errors under at least one set of simulated conditions. For example, in scenarios where type I error rates from pre-network permutation tests exceed 30%, the error rates from double permutation remain at 5%.The double permutation procedure provides one potential solution to issues arising from elevated type I and type II error rates when testing null hypotheses with social network data. We also discuss alternative approaches that can provide robust inference, including fitting mixed effects models, restricted node permutations, testing multiple null hypotheses and splitting large datasets to generate replicated networks. Finally, we highlight ways that uncertainty can be explicitly considered and carried through the analysis.

A simple tool for linking photo-identification with multimedia data to track mammal behaviour

Identifying individual animals is critical to describe demographic and behavioural patterns, and to investigate the ecological and evolutionary underpinnings of these patterns. The traditional non-invasive method of individual identification in mammals—comparison of photographed natural marks—has been improved by coupling other sampling methods, such as recording overhead video, audio and other multimedia data. However, aligning, linking and syncing these multimedia data streams are persistent challenges. Here, we provide computational tools to streamline the integration of multiple techniques to identify individual free-ranging mammals when tracking their behaviour in the wild. We developed an open-source R package for organizing multimedia data and for simplifying their processing a posteriori—“MAMMals: Managing Animal MultiMedia: Align, Link, Sync”. The package contains functions to (i) align and link the individual data from photographs to videos, audio recordings and other text data sources (e.g. GPS locations) from which metadata can be accessed; and (ii) synchronize and extract the useful multimedia (e.g. videos with audios) containing photo-identified individuals. To illustrate how these tools can facilitate linking photo-identification and video behavioural sampling in situ, we simultaneously collected photos and videos of bottlenose dolphins using off-the-shelf cameras and drones, then merged these data to track the foraging behaviour of individuals and groups. We hope our simple tools encourage future work that extend and generalize the links between multiple sampling platforms of free-ranging mammals, thereby improving the raw material needed for generating new insights in mammalian population and behavioural ecology.

Casting the Net Widely for Change in Animal Welfare: The Plight of Birds in Zoos, Ex Situ Conservation, and Conservation Fieldwork

Simple Summary

Animal welfare measures have been designed to improve the health and environmental conditions of animals living under human control, for whatever reason. Welfare regulations have evolved also in line with new research insights into the cognitive, affective, and physiological domain of birds, as this paper discusses. This paper casts a critical eye on areas that Animal Welfare regulations have not reached at all, have not gone far enough, or are not regulated or supervised. It identifies the plight of birds living in captivity or being studied in the field, which either by neglect, ignorance, or design are subject to practices and procedures that may not meet basic welfare standards. The paper discusses some profound contradictions in the way we think about birds and their plight in today’s world: marked for extinction on one hand and highly admired as pets on the other; damaging fieldwork on one hand and the aims of conservation on the other. It highlights some common and distressing examples of poor welfare in birds. It also offers some solutions involving simple legislative changes and ways to eliminate some unacceptably low ethical standards in the handling and management of birds.

Abstract

This paper discusses paradoxes in our relationship to and treatment of birds in captive and conservation contexts. The paper identifies modern and new challenges that arise from declining bird numbers worldwide. Such challenges have partly changed zoos into providers of insurance populations specifically for species at risk of extinction. They have also accelerated fieldwork projects, but by using advanced technological tools and in increasing numbers, contradictorily, they may cause serious harm to the very birds studied for conservation purposes. In practice, very few avian species have any notable protection or guarantee of good treatment. The paper first deals with shortcomings of identifying problematic avian behavior in captive birds. It then brings together specific cases of field studies and captive breeding for conservation in which major welfare deficits are identified. Indeed, the paper argues that avian welfare is now an urgent task. This is not just because of declining bird numbers but because of investment in new technologies in field studies that may have introduced additional stressors and put at risk bird survival. While the paper documents a substantial number of peer-reviewed papers criticizing practices counter to modern welfare standards, they have by and large not led to changes in some practices. Some solutions are suggested that could be readily implemented and, to my knowledge, have never been considered under a welfare model before.

Raspberry Pi nest cameras: An affordable tool for remote behavioral and conservation monitoring of bird nests

Bespoke (custom-built) Raspberry Pi cameras are increasingly popular research tools in the fields of behavioral ecology and conservation, because of their comparative flexibility in programmable settings, ability to be paired with other sensors, and because they are typically cheaper than commercially built models.Here, we describe a novel, Raspberry Pi-based camera system that is fully portable and yet weatherproof-especially to humidity and salt spray. The camera was paired with a passive infrared sensor, to create a movement-triggered camera capable of recording videos over a 24-hr period. We describe an example deployment involving "retro-fitting" these cameras into artificial nest boxes on Praia Islet, Azores archipelago, Portugal, to monitor the behaviors and interspecific interactions of two sympatric species of storm-petrel (Monteiro's storm-petrel Hydrobates monteiroi and Madeiran storm-petrel Hydrobates castro) during their respective breeding seasons.Of the 138 deployments, 70% of all deployments were deemed to be "Successful" (Successful was defined as continuous footage being recorded for more than one hour without an interruption), which equated to 87% of the individual 30-s videos. The bespoke cameras proved to be easily portable between 54 different nests and reasonably weatherproof (~14% of deployments classed as "Partial" or "Failure" deployments were specifically due to the weather/humidity), and we make further trouble-shooting suggestions to mitigate additional weather-related failures.Here, we have shown that this system is fully portable and capable of coping with salt spray and humidity, and consequently, the camera-build methods and scripts could be applied easily to many different species that also utilize cavities, burrows, and artificial nests, and can potentially be adapted for other wildlife monitoring situations to provide novel insights into species-specific daily cycles of behaviors and interspecies interactions.

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.

Population turnover facilitates cultural selection for efficiency in birds

Culture, defined as socially transmitted information and behaviors that are shared in groups and persist over time, is increasingly accepted to occur across a wide range of taxa and behavioral domains.¹ While persistent, cultural traits are not necessarily static, and their distribution can change in frequency and type in response to selective pressures, analogous to that of genetic alleles. This has led to the treatment of culture as an evolutionary process, with cultural evolutionary theory arguing that culture exhibits the three fundamental components of Darwinian evolution: variation, competition, and inheritance.^2-5 Selection for more efficient behaviors over alternatives is a crucial component of cumulative cultural evolution,⁶ yet our understanding of how and when such cultural selection occurs in non-human animals is limited. We performed a cultural diffusion experiment using 18 captive populations of wild-caught great tits (Parus major) to ask whether more efficient foraging traditions are selected for, and whether this process is affected by a fundamental demographic process-population turnover. Our results showed that gradual replacement of individuals with naive immigrants greatly increased the probability that a more efficient behavior invaded a population's cultural repertoire and outcompeted an established inefficient behavior. Fine-scale, automated behavioral tracking revealed that turnover did not increase innovation rates, but instead acted on adoption rates, as immigrants disproportionately sampled novel, efficient behaviors relative to available social information. These results provide strong evidence for cultural selection for efficiency in animals, and highlight the mechanism that links population turnover to this process.

"Micropersonality" traits and their implications for behavioral and movement ecology research

Many animal personality traits have implicit movement-based definitions and can directly or indirectly influence ecological and evolutionary processes. It has therefore been proposed that animal movement studies could benefit from acknowledging and studying consistent interindividual differences (personality), and, conversely, animal personality studies could adopt a more quantitative representation of movement patterns.Using high-resolution tracking data of three-spined stickleback fish (Gasterosteus aculeatus), we examined the repeatability of four movement parameters commonly used in the analysis of discrete time series movement data (time stationary, step length, turning angle, burst frequency) and four behavioral parameters commonly used in animal personality studies (distance travelled, space use, time in free water, and time near objects).Fish showed repeatable interindividual differences in both movement and behavioral parameters when observed in a simple environment with two, three, or five shelters present. Moreover, individuals that spent less time stationary, took more direct paths, and less commonly burst travelled (movement parameters), were found to travel farther, explored more of the tank, and spent more time in open water (behavioral parameters).Our case study indicates that the two approaches-quantifying movement and behavioral parameters-are broadly equivalent, and we suggest that movement parameters can be viewed as "micropersonality" traits that give rise to broad-scale consistent interindividual differences in behavior. This finding has implications for both personality and movement ecology research areas. For example, the study of movement parameters may provide a robust way to analyze individual personalities in species that are difficult or impossible to study using standardized behavioral assays.

Computerized assessment of dominance hierarchy in baboons (Papio papio)

Dominance hierarchies are an important aspect of Primate social life, and there is an increasing need to develop new systems to collect social information automatically. The main goal of this research was to explore the possibility to infer the dominance hierarchy of a group of Guinea baboons (Papio papio) from the analysis of their spontaneous interactions with freely accessible automated learning devices for monkeys (ALDM, Fagot & Bonté Behavior Research Methods, 42, 507-516, 2010). Experiment 1 compared the dominance hierarchy obtained from conventional observations of agonistic behaviours to the one inferred from the analysis of automatically recorded supplanting behaviours within the ALDM workstations. The comparison, applied to three different datasets, shows that the dominance hierarchies obtained with the two methods are highly congruent (all rs ≥ 0.75). Experiment 2 investigated the experimental potential of inferring dominance hierarchy from ALDM testing. ALDM data previously published in Goujon and Fagot (Behavioural Brain Research, 247, 101-109, 2013) were re-analysed for that purpose. Results indicate that supplanting events within the workstations lead to a transient improvement of cognitive performance for the baboon supplanting its partners and that this improvement depends on the difference in rank between the two baboons. This study therefore opens new perspectives for cognitive studies conducted in a social context.

TRex, a fast multi-animal tracking system with markerless identification, and 2D estimation of posture and visual fields

Automated visual tracking of animals is rapidly becoming an indispensable tool for the study of behavior. It offers a quantitative methodology by which organisms’ sensing and decision-making can be studied in a wide range of ecological contexts. Despite this, existing solutions tend to be challenging to deploy in practice, especially when considering long and/or high-resolution video-streams. Here, we present TRex, a fast and easy-to-use solution for tracking a large number of individuals simultaneously using background-subtraction with real-time (60 Hz) tracking performance for up to approximately 256 individuals and estimates 2D visual-fields, outlines, and head/rear of bilateral animals, both in open and closed-loop contexts. Additionally, TRex offers highly accurate, deep-learning-based visual identification of up to approximately 100 unmarked individuals, where it is between 2.5 and 46.7 times faster, and requires 2–10 times less memory, than comparable software (with relative performance increasing for more organisms/longer videos) and provides interactive data-exploration within an intuitive, platform-independent graphical user-interface.

Drivers of alloparental provisioning of fledglings in a colonially breeding bird

Reproduction is costly. Despite this, evidence suggests that parents sometimes feed unrelated offspring. Several hypotheses could explain this puzzling phenomenon. Adults could feed unrelated offspring that are 1) of their close social associates to facilitate these juveniles’ integration into their social network (the social inheritance hypothesis), 2) potential extrapair offspring, 3) at a similar developmental stage as their own, 4) coercing feeding by begging, or 5) less-developed (to enhance their survival, which could benefit the adult or its offspring; the group augmentation hypothesis). Colonial breeders are ideal for investigating the relative importance of these hypotheses because offspring are often kept in crèches where adults can exhibit allofeeding. Using automated monitoring of replicated captive zebra finch (Taeniopygia guttata) colonies, we found that while parents selectively fed their own offspring, they also consistently fed unrelated offspring (32.48% of feeding events). Social relationships among adults prior to breeding did not predict allofeeding, nor was allofeeding directed toward potential genetic offspring. Instead, adults with more-developed offspring preferentially fed less-developed non-offspring over non-offspring at a similar developmental stage as their own offspring, and this tendency was not explained by differences in begging behavior. Our study suggests that allofeeding is consistent with group augmentation, potentially benefiting adults through colony maintenance or increased offspring survival.

Thinking small: Next-generation sensor networks close the size gap in vertebrate biologging

Recent advances in animal tracking technology have ushered in a new era in biologging. However, the considerable size of many sophisticated biologging devices restricts their application to larger animals, whereas older techniques often still represent the state-of-the-art for studying small vertebrates. In industrial applications, low-power wireless sensor networks (WSNs) fulfill requirements similar to those needed to monitor animal behavior at high resolution and at low tag mass. We developed a wireless biologging network (WBN), which enables simultaneous direct proximity sensing, high-resolution tracking, and long-range remote data download at tag masses of 1 to 2 g. Deployments to study wild bats created social networks and flight trajectories of unprecedented quality. Our developments highlight the vast capabilities of WBNs and their potential to close an important gap in biologging: fully automated tracking and proximity sensing of small animals, even in closed habitats, at high spatial and temporal resolution.

Development of New Food-Sharing Relationships in Vampire Bats

Some nonhuman animals form adaptive long-term cooperative relationships with nonkin that seem analogous in form and function to human friendship [1-4]. However, it remains unclear how these bonds initially form, especially when they entail investments of time and energy. Theory suggests individuals can reduce the risk of exploitation by initially spreading out smaller cooperative investments across time [e.g., 5] or partners [6], then gradually escalating investments in more cooperative partnerships [7]. Despite its intuitive appeal, this raising-the-stakes model [7] has gained surprisingly scarce empirical support. Although human strangers do "raise the stakes" when making bids in cooperation games [8], there has been no clear evidence for raising the stakes during formation of social bonds in nature. Existing studies are limited to cooperative interactions with severe power asymmetries (e.g., the cleaner-client fish mutualism [9]) or snapshots of a single behavior within established relationships (grooming in primates [10-13]). Raising the stakes during relationship formation might involve escalating to more costly behaviors. For example, individuals could "test the waters" by first clustering for warmth (no cost), then conditionally grooming (low cost), and eventually providing coalitionary support (high cost). Detecting such a pattern requires introducing random strangers and measuring the emergence of natural helping behaviors that vary in costs. We performed this test by tracking the emergence of social grooming and regurgitated food donations among previously unfamiliar captive vampire bats (Desmodus rotundus) over 15 months. We found compelling evidence that vampire bats selectively escalate low-cost grooming before developing higher-cost food-sharing relationships.

Winter associations predict social and extra-pair mating patterns in a wild songbird

Despite decades of research, our understanding of the underlying causes of within-population variation in patterns of extra-pair paternity (EPP) remains limited. Previous studies have shown that extra-pair mating decisions are linked to both individual traits and ecological factors. Here, we examine whether social associations among individuals prior to breeding also shape mating patterns, specifically the occurrence of EPP, in a small songbird, the blue tit. We test whether associations during the non-breeding period predict (1) future social pairs, (2) breeding proximity (i.e. the distance between breeding individuals) and (3) the likelihood that individuals have extra-pair young together. Individuals that were more strongly associated (those that foraged more often together) during winter tended to nest closer together. This, by itself, predicts EPP patterns, because most extra-pair sires are close neighbours. However, even after controlling for spatial effects, female-male dyads with stronger social associations prior to breeding were more likely to have extra-pair young. Our findings reveal a carry-over from social associations into future mating decisions. Quantifying the long-term social environment of individuals and studying its dynamics is a promising approach to enhance our understanding of the process of (extra-)pair formation.

Early-life social environment predicts social network position in wild zebra finches

Early-life experience can fundamentally shape individual life-history trajectories. Previous research has suggested that exposure to stress during development causes differences in social behaviour later in life. In captivity, juvenile zebra finches exposed to elevated corticosterone levels were less socially choosy and more central in their social networks when compared to untreated siblings. These differences extended to other aspects of social life, with 'stress-exposed' juveniles switching social learning strategies and juvenile males less faithfully learning their father's song. However, while this body of research suggests that the impacts of early-life stress could be profound, it remains unknown whether such effects are strong enough to be expressed under natural conditions. Here, we collected data on social associations of zebra finches in the Australian desert after experimentally manipulating brood sizes. Juveniles from enlarged broods experienced heightened sibling competition, and we predicted that they would express similar patterns of social associations to stress-treated birds in the captive study by having more, but less differentiated, relationships. We show striking support for the suggested consequences of developmental stress on social network positions, with our data from the wild replicating the same results in 9 out of 10 predictions previously tested in captivity. Chicks raised in enlarged broods foraged with greater numbers of conspecifics but were less 'choosy' and more central in the social network. Our results confirm that the natural range of variation in early-life experience can be sufficient to predict individuals' social trajectories and support theory highlighting the potential importance of developmental conditions on behaviour.

Testing the Sexual and Social Benefits of Cooperation in Animals

Theoretical models show that sexual and social selection can stabilise cooperation. However, field tests of these mechanisms have been difficult to conduct and the results are mixed. We discuss the conceptual and practical difficulties associated with testing the role of social and sexual selection on cooperation and argue that there are alternative ways of examining these hypotheses. Specifically, approaches based on the classic theories of sexual selection and signalling, and recent developments in the field of behavioural syndromes, provide mechanisms to insure the reliability of cooperation. In addition, methodological developments (social networks and microtracking) and long-term datasets, allow measuring partner choice in a cooperation context and the resulting fitness benefits for both the cooperators and the individuals that associate with them.

Experimental disturbances reveal group-level costs of social instability

In group-living species, social stability is an important trait associated with the evolution of complex behaviours such as cooperation. While the drivers of stability in small groups are relatively well studied, little is known about the potential impacts of unstable states on animal societies. Temporary changes in group composition, such as a social group splitting and recombining (i.e. a disturbance event), can result in individuals having to re-establish their social relationships, thus taking time away from other tasks such as foraging or vigilance. Here, we experimentally split socially stable groups of captive zebra finches (Taeniopygia guttata), and quantified the effects of repeated disturbance events on (1) group foraging efficiency, and (2) co-feeding associations when subgroups were recombined. We found that the efficiency of groups to deplete a rich, but ephemeral, resource patch decreased after just a single short disturbance event. Automated tracking of individuals showed that repeated disturbances reduced efficiency by causing social relationships to become more differentiated and weaker, resulting in fewer individuals simultaneously accessing the patch. Our experiment highlights how short-term disturbances can severely disrupt social structure and group functionality, revealing potential costs associated with group instability that can have consequences for the evolution of animal societies.

Stress hormones, social associations and song learning in zebra finches

The use of information provided by others is a common short-cut adopted to inform decision-making. However, instead of indiscriminately copying others, animals are often selective in what, when and whom they copy. How do they decide which 'social learning strategy' to use? Previous research indicates that stress hormone exposure in early life may be important: while juvenile zebra finches copied their parents' behaviour when solving novel foraging tasks, those exposed to elevated levels of corticosterone (CORT) during development copied only unrelated adults. Here, we tested whether this switch in social learning strategy generalizes to vocal learning. In zebra finches, juvenile males often copy their father's song; would CORT-treated juveniles in free-flying aviaries switch to copying songs of other males? We found that CORT-treated juveniles copied their father's song less accurately as compared to control juveniles. We hypothesized that this could be due to having weaker social foraging associations with their fathers, and found that sons that spent less time foraging with their fathers produced less similar songs. Our findings are in line with a novel hypothesis linking early-life stress and social learning: early-life CORT exposure may affect social learning indirectly as a result of the way it shapes social affiliations.This article is part of the theme issue 'Causes and consequences of individual differences in cognitive abilities'.

Advances from the nexus of animal behaviour and pathogen transmission: new directions and opportunities using contact networks

Contact network models have enabled significant advances in understanding the influence of behaviour on parasite and pathogen transmission. They are an important tool that links variation in individual behaviour, to epidemiological consequences at the population level. Here, in our introduction to this special issue, we highlight the importance of applying network approaches to disease ecological and epidemiological questions, and how this has provided a much deeper understanding of these research areas. Recent advances in tracking host behaviour (bio-logging: e.g., GPS tracking, barcoding) and tracking pathogens (high-resolution sequencing), as well as methodological advances (multi-layer networks, computational techniques) started producing exciting new insights into disease transmission through contact networks. We discuss some of the exciting directions that the field is taking, some of the challenges, and importantly the opportunities that lie ahead. For instance, we suggest to integrate multiple transmission pathways, multiple pathogens, and in some systems, multiple host species, into the next generation of network models. Corresponding opportunities exist in utilising molecular techniques, such as high-resolution sequencing, to establish causality in network connectivity and disease outcomes. Such novel developments and the continued integration of network tools offers a more complete understanding of pathogen transmission processes, their underlying mechanisms and their evolutionary consequences.