Time synchronisation for millisecond-precision on bio-loggers

Time-synchronised data streams from bio-loggers are becoming increasingly important for analysing and interpreting intricate animal behaviour including split-second decision making, group dynamics, and collective responses to environmental conditions. With the increased use of AI-based approaches for behaviour classification, time synchronisation between recording systems is becoming an essential challenge. Current solutions in bio-logging rely on manually removing time errors during post processing, which is complex and typically does not achieve sub-second timing accuracies.We first introduce an error model to quantify time errors, then optimise three wireless methods for automated onboard time (re)synchronisation on bio-loggers (GPS, WiFi, proximity messages). The methods can be combined as required and, when coupled with a state-of-the-art real time clock, facilitate accurate time annotations for all types of bio-logging data without need for post processing. We analyse time accuracy of our optimised methods in stationary tests and in a case study on 99 Egyptian fruit bats (Rousettus aegyptiacus). Based on the results, we offer recommendations for projects that require high time synchrony.During stationary tests, our low power synchronisation methods achieved median time accuracies of 2.72 / 0.43 ms (GPS / WiFi), compared to UTC time, and relative median time accuracies of 5 ms between tags (wireless proximity messages). In our case study with bats, we achieved a median relative time accuracy of 40 ms between tags throughout the entire 10-day duration of tag deployment. Using only one automated resynchronisation per day, permanent UTC time accuracies of ≤ 185 ms can be guaranteed in 95% of cases over a wide temperature range between 0 and 50 °C. Accurate timekeeping required a minimal battery capacity, operating in the nano- to microwatt range.Time measurements on bio-loggers, similar to other forms of sensor-derived data, are prone to errors and so far received little scientific attention. Our combinable methods offer a means to quantify time errors and autonomously correct them at the source (i.e., on bio-loggers). This approach facilitates sub-second comparisons of simultaneously recorded time series data across multiple individuals and off-animal devices such as cameras or weather stations. Through automated resynchronisations on bio-loggers, long-term sub-second accurate timestamps become feasible, even for life-time studies on animals. We contend that our methods have potential to greatly enhance the quality of ecological data, thereby improving scientific conclusions.

"ClusterApp": A Shiny R application to guide cluster studies based on GPS data

The rapid evolution of GPS devices, and therefore, collection of GPS data can be used to investigate a wide variety of topics in wildlife research. The combination of remotely collected GPS data with on-the-ground field investigations is a powerful tool for exploring behavioral ecology. "GPS cluster studies" are aimed at pinpointing and investigating identified clusters in the field. Activity clusters can be based on various parameters (e.g., distance between GPS locations and the number of locations needed to establish a cluster), which are closely related to the set research questions. Variation in methods across years within the same study may result in data collection biases. Therefore, a streamlined method to parametrize, generate interactive maps, and extract activity cluster data using a predefined approach will limit biases, and make field work and data management straightforward for field technicians. We developed the "ClusterApp" Shiny application in the R software to facilitate a step-by-step guide to execute cluster analyses and data management of cluster studies on any species using GPS data. We illustrate the use of the "ClusterApp" with two location datasets constructed by data collected on brown bears (Ursus arctos) and gray wolves (Canis lupus).

Hierarchically embedded scales of movement shape the social networks of vampire bats

Social structure can emerge from hierarchically embedded scales of movement, where movement at one scale is constrained within a larger scale (e.g. among branches, trees, forests). In most studies of animal social networks, some scales of movement are not observed, and the relative importance of the observed scales of movement is unclear. Here, we asked: how does individual variation in movement, at multiple nested spatial scales, influence each individual's social connectedness? Using existing data from common vampire bats (Desmodus rotundus), we created an agent-based model of how three nested scales of movement-among roosts, clusters and grooming partners-each influence a bat's grooming network centrality. In each of 10 simulations, virtual bats lacking social and spatial preferences moved at each scale at empirically derived rates that were either fixed or individually variable and either independent or correlated across scales. We found that numbers of partners groomed per bat were driven more by within-roost movements than by roost switching, highlighting that co-roosting networks do not fully capture bat social structure. Simulations revealed how individual variation in movement at nested spatial scales can cause false discovery and misidentification of preferred social relationships. Our model provides several insights into how nonsocial factors shape social networks.

Advances in understanding bat infection dynamics across biological scales

Over the past two decades, research on bat-associated microbes such as viruses, bacteria and fungi has dramatically increased. Here, we synthesize themes from a conference symposium focused on advances in the research of bats and their microbes, including physiological, immunological, ecological and epidemiological research that has improved our understanding of bat infection dynamics at multiple biological scales. We first present metrics for measuring individual bat responses to infection and challenges associated with using these metrics. We next discuss infection dynamics within bat populations of the same species, before introducing complexities that arise in multi-species communities of bats, humans and/or livestock. Finally, we outline critical gaps and opportunities for future interdisciplinary work on topics involving bats and their microbes.

The role of social attraction and social avoidance in shaping modular networks

How interactions between individuals contribute to the emergence of complex societies is a major question in behavioural ecology. Nonetheless, little remains known about the type of immediate social structure (i.e. social network) that emerges from relationships that maximize beneficial interactions (e.g. social attraction towards informed individuals) and minimize costly relationships (e.g. social avoidance of infected group mates). We developed an agent-based model where individuals vary in the degree to which individuals signal benefits versus costs to others and, on this basis, choose with whom to interact depending on simple rules of social attraction (e.g. access to the highest benefits) and social avoidance (e.g. avoiding the highest costs). Our main findings demonstrate that the accumulation of individual decisions to avoid interactions with highly costly individuals, but that are to some extent homogeneously beneficial, leads to more modular networks. On the contrary, individuals favouring interactions with highly beneficial individuals, but that are to some extent homogeneously costly, lead to less modular networks. Interestingly, statistical models also indicate that when individuals have multiple potentially beneficial partners to interact with, and no interaction cost exists, this also leads to more modular networks. Yet, the degree of modularity is contingent upon the variability in benefit levels held by individuals. We discuss the emergence of modularity in the systems and their consequences for understanding social trade-offs.

Let's stick together: Infection enhances preferences for social grouping in a songbird species

Acute infections can alter foraging and movement behaviors relevant to sociality and pathogen spread. However, few studies have directly examined how acute infections caused by directly transmitted pathogens influence host social preferences. While infected hosts often express sickness behaviors (e.g., lethargy) that can reduce social associations with conspecifics, enhanced sociality during infection might be favored in some systems if social grouping improves host survival of infection. Directly assaying social preferences of infected hosts is needed to elucidate potential changes in social preferences that may act as a form of behavioral tolerance (defined as using behavior to minimize fitness costs of infection). We tested how infection alters sociality in juvenile house finches (Haemorhous mexicanus), which are both highly gregarious and particularly susceptible to infection by the bacterial pathogen Mycoplasma gallisepticum (MG). We inoculated 33 wild-caught but captive-held juvenile house finches with MG or media (sham control). At peak infection, birds were given a choice assay to assess preference for associating near a flock versus an empty cage. We then repeated this assay after all birds had recovered from infection. Infected birds were significantly more likely than controls to spend time associating with, and specifically foraging near, the flock. However, after infected birds had recovered from MG infection, there were no significant differences in the amount of time birds in each treatment spent with the flock. These results indicate augmented social preferences during active infection, potentially as a form of behavioral tolerance. Notably, infected birds showed strong social preferences regardless of variation in disease severity or pathogen loads, with 14/19 harboring high loads (5-6 log10 copies of MG) at the time of the assay. Overall, our results show that infection with a directly transmitted pathogen can augment social preferences, with important implications for MG spread in natural populations.

Bat behavioral immune responses in social contexts: current knowledge and future directions

Animals often mount complex immune responses to infections. Aside from cellular and molecular defense mechanisms, animals can alter their behavior in response to infection by avoiding, resisting, or tolerating negative effects of pathogens. These behaviors are often connected to cellular and molecular immune responses. For instance, sickness behaviors are a set of behavioral changes triggered by the host inflammatory response (e.g., cytokines) and could aid in resisting or tolerating infection, as well as affect transmission dynamics if sick animals socially withdraw or are being avoided by others. To fully understand the group and population level transmission dynamics and consequences of pathogen infections in bats, it is not only important to consider cellular and molecular defense mechanisms, but also behavioral mechanisms, and how both interact. Although there has been increasing interest in bat immune responses due to their ability to successfully cope with viral infections, few studies have explored behavioral anti-pathogen defense mechanisms. My main objective is to explore the interaction of cellular and molecular defense mechanisms, and behavioral alterations that results from infection in bats, and to outline current knowledge and future research avenues in this field.

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.

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.

Social effects of rabies infection in male vampire bats (Desmodus rotundus)

Rabies virus (RABV) transmitted by the common vampire bat (Desmodus rotundus) poses a threat to agricultural development and public health throughout the Neotropics. The ecology and evolution of rabies host-pathogen dynamics are influenced by two infection-induced behavioural changes. RABV-infected hosts often exhibit increased aggression which facilitates transmission, and rabies also leads to reduced activity and paralysis prior to death. Although several studies document rabies-induced behavioural changes in rodents and other dead-end hosts, surprisingly few studies have measured these changes in vampire bats, the key natural reservoir throughout Latin America. Taking advantage of an experiment designed to test an oral rabies vaccine in captive male vampire bats, we quantify for the first time, to our knowledge, how rabies affects allogrooming and aggressive behaviours in this species. Compared to non-rabid vampire bats, rabid individuals reduced their allogrooming prior to death, but we did not detect increases in aggression among bats. To put our results in context, we review what is known and what remains unclear about behavioural changes of rabid vampire bats (resumen en español, electronic supplementary material, S1).

Social networks respond to a disease challenge in calves

Changes in network position and behavioral interactions have been linked with infectious disease in social animals. Here, we investigate the effects of an experimental disease challenge on social network centrality of group-housed Holstein bull dairy calves. Within group-housed pens (6/group) calves were randomly assigned to either a previously developed challenge model, involving inoculation with Mannheimia haemolytia (n = 12 calves; 3 calves/group) or a control involving only saline (n = 12 calves; 3 calves/group). Continuous behavioral data were recorded from video on pre-treatment baseline day and for 24 h following inoculation to describe social lying frequency and duration and all active social contact between calves. Mixed-model analysis revealed that changes in network position were related to the challenge. Compared to controls, challenged calves had reduced centrality and connectedness, baseline to challenge day. On challenge day, challenged calves were less central in the directed social contact networks (lower degree, strength and eigenvector centrality), and initiated contact (higher out-degree) with more penmates, compared to healthy calves. This finding suggests that giving rather than receiving affiliative social contact may be more beneficial for challenged calves. This is the first study demonstrating that changes in social network position coincide with an experimental challenge of a respiratory pathogen in calves.

Networks, cultures, and institutions: Toward a social immunology

This paper calls for increased attention to the ways in which immune function – including its behavioral aspects – are responsive to social contexts at multiple levels. Psychoneuroimmunology has demonstrated that the quantity and quality of social connections can affect immune responses, while newer research is finding that sickness temporarily affects these same social networks and that some aspects of culture can potentially “get under the skin” to affect inflammatory responses. Social immunology, the research framework proposed here, unifies these findings and also considers the effects of structural factors – that is, a society's economic, political, and environmental landscape – on exposure to pathogens and subsequent immune responses. As the COVID-19 pandemic has highlighted, a holistic understanding of the effects of social contexts on the patterning of morbidity and mortality is critically important. Social immunology provides such a framework and can highlight important risk factors related to impaired immune function.

Social convergence of gut microbiomes in vampire bats

The 'social microbiome' can fundamentally shape the costs and benefits of group-living, but understanding social transmission of microbes in free-living animals is challenging due to confounding effects of kinship and shared environments (e.g. highly associated individuals often share the same spaces, food and water). Here, we report evidence for convergence towards a social microbiome among introduced common vampire bats, Desmodus rotundus, a highly social species in which adults feed only on blood, and engage in both mouth-to-body allogrooming and mouth-to-mouth regurgitated food sharing. Shotgun sequencing of samples from six zoos in the USA, 15 wild-caught bats from a colony in Belize and 31 bats from three colonies in Panama showed that faecal microbiomes were more similar within colonies than between colonies. To assess microbial transmission, we created an experimentally merged group of the Panama bats from the three distant sites by housing these bats together for four months. In this merged colony, we found evidence that dyadic gut microbiome similarity increased with both clustering and oral contact, leading to microbiome convergence among introduced bats. Our findings demonstrate that social interactions shape microbiome similarity even when controlling for past social history, kinship, environment and diet.

Immune challenges increase network centrality in a queenless ant

Social animals display a wide range of behavioural defences against infectious diseases, some of which increase social contacts with infectious individuals (e.g. mutual grooming), while others decrease them (e.g. social exclusion). These defences often rely on the detection of infectious individuals, but this can be achieved in several ways that are difficult to differentiate. Here, we combine non-pathogenic immune challenges with automated tracking in colonies of the clonal raider ant to ask whether ants can detect the immune status of their social partners and to quantify their behavioural responses to this perceived infection risk. We first show that a key behavioural response elicited by live pathogens (allogrooming) can be qualitatively recapitulated by immune challenges alone. Automated scoring of interactions between all colony members reveals that this behavioural response increases the network centrality of immune-challenged individuals through a general increase in physical contacts. These results show that ants can detect the immune status of their nest-mates and respond with a general 'caring' strategy, rather than avoidance, towards social partners that are perceived to be infectious. Finally, we find no evidence that changes in cuticular hydrocarbon profiles drive these behavioural effects.

Sick bats stay home alone: fruit bats practice social distancing when faced with an immunological challenge

Along with its many advantages, social roosting imposes a major risk of pathogen transmission. How social animals reduce this risk is poorly documented. We used lipopolysaccharide challenge to imitate bacterial infection in both a captive and a free‐living colony of an extremely social, long‐lived mammal—the Egyptian fruit bat. We monitored behavioral and physiological responses using an arsenal of methods, including onboard GPS to track foraging, acceleration sensors to monitor movement, infrared video to record social behavior, and blood samples to measure immune markers. Sick‐like (immune‐challenged) bats exhibited an increased immune response, as well as classic illness symptoms, including fever, weight loss, anorexia, and lethargy. Notably, the bats also exhibited behaviors that would reduce pathogen transfer. They perched alone and appeared to voluntarily isolate themselves from the group by leaving the social cluster, which is extremely atypical for this species. The sick‐like individuals in the open colony ceased foraging outdoors for at least two nights, thus reducing transmission to neighboring colonies. Together, these sickness behaviors demonstrate a strong, integrative immune response that promotes recovery of infected individuals while reducing pathogen transmission inside and outside the roost, including spillover events to other species, such as humans.

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.

Bidirectional interactions between host social behaviour and parasites arise through ecological and evolutionary processes

An animal's social behaviour both influences and changes in response to its parasites. Here we consider these bidirectional links between host social behaviours and parasite infection, both those that occur from ecological vs evolutionary processes. First, we review how social behaviours of individuals and groups influence ecological patterns of parasite transmission. We then discuss how parasite infection, in turn, can alter host social interactions by changing the behaviour of both infected and uninfected individuals. Together, these ecological feedbacks between social behaviour and parasite infection can result in important epidemiological consequences. Next, we consider the ways in which host social behaviours evolve in response to parasites, highlighting constraints that arise from the need for hosts to maintain benefits of sociality while minimizing fitness costs of parasites. Finally, we consider how host social behaviours shape the population genetic structure of parasites and the evolution of key parasite traits, such as virulence. Overall, these bidirectional relationships between host social behaviours and parasites are an important yet often underappreciated component of population-level disease dynamics and host-parasite coevolution.

Tracking sickness effects on social encounters via continuous proximity sensing in wild vampire bats

Sickness behaviors can slow the spread of pathogens across a social network. We conducted a field experiment to investigate how sickness behavior affects individual connectedness over time using a dynamic social network created from high-resolution proximity data. After capturing adult female vampire bats (Desmodus rotundus) from a roost, we created “sick” bats by injecting a random half of bats with the immune-challenging substance, lipopolysaccharide, while the control group received saline injections. Over the next 3 days, we used proximity sensors to continuously track dyadic associations between 16 “sick” bats and 15 control bats under natural conditions. Compared to control bats, “sick” bats associated with fewer bats, spent less time near others, and were less socially connected to more well-connected individuals (sick bats had on average a lower degree, strength, and eigenvector centrality). High-resolution proximity data allow researchers to flexibly define network connections (association rates) based on how a particular pathogen is transmitted (e.g., contact duration of >1 vs. >60 min, contact proximity of <1 vs. <10 m). Therefore, we inspected how different ways of measuring association rates changed the observed effect of LPS. How researchers define association rates influences the magnitude and detectability of sickness effects on network centrality. When animals are sick, they often encounter fewer individuals. We tracked this unintentional “social distancing” effect hour-by-hour in a wild colony of vampire bats. Using bat-borne proximity sensors, we compared changes in the social network connectedness of immune-challenged “sick” bats versus “control” bats over time. “Sick” bats had fewer encounters with others and spent less time near others. Associations changed dramatically by time of day, and different measures of association influenced the sickness effect estimates.