Krishna Balasubramaniam

The ‘social microbiome’ conceptualises gut microbial communities as ‘islands’ of host social organisation. Yet, in comparison to broader aspects of social organisation such as animals' group membership and composition, the impact of inter‐individual differences in sociality on microbiome community ecology remains less well studied. Among a wild but human‐provisioned group of long‐tailed macaques ( Macaca fascicularis ), we assessed the relative effects of individuals' sociality, compared to their demographic characteristics, anthropogenic and abiotic environmental factors, and microbe‐microbe associations, on the relative abundance and co‐occurrence of bacterial taxa. Bipartite network analysis showed that bacterial communities among macaques were nested rather than segregated or modular structures. Several ‘core’ bacterial genera were found across all macaques, but other ‘non‐core’ bacteria were found only in a few macaques suggesting that their occurrence/abundance may be influenced by transient environmental factors. Joint Species Distributions Models showed that macaques' sociality, particularly their dominance rank and their connectedness or centrality within their social grooming network, had the strongest impact on taxa abundance, followed by their demographic characteristics, and finally their exposure to both anthropogenic and abiotic environmental factors. Phylogenetically distant taxa were more likely to co‐occur within the same macaque hosts than phylogenetically related taxa. These findings confirm that microbiome communities are strongly influenced by the social status and connectedness of individual hosts. Nevertheless, the finding that some taxa were more prevalent among high‐ranking or well‐connected macaques, while others were more prevalent among low‐ranking or socially peripheral macaques, warrants further investigation into how individual differences in social microbiomes might affect their health and fitness. Future studies, through the collection of behavioural and microbial data on additional macaque groups, may provide further insights into the relative effects of animals' social organisation and social behaviours on microbiomes.

The social organisation of animals likely shapes the composition, diversity and stability of microbiomes, giving rise to the concept of the ‘social microbiome’—microbial communities shared within and across social units, or ‘islands’, ranging from individuals to entire ecosystems. Understanding the connections and their underlying drivers is crucial for revealing how socioecology influences microbiomes and associated health outcomes. However, empirical assessments are still limited, and the relative influence of social organisation compared to intrinsic (biological) and extrinsic (environmental) factors in shaping microbiomes is particularly unclear. Here, we used a long‐term, individual‐based study of Kalahari meerkats ( Suricata suricatta ) to test predictions from the social microbiome concept. We assessed the relative influence of social factors, biological traits and environmental variables on gut microbial communities, while also accounting for the effects of microbial phylogenetic relatedness and within‐host associations or co‐occurrence independent of phylogeny. Meerkat microbiomes exhibited highly ‘nested’ and weakly ‘modular’ structures: individuals with lower diversity hosted amplicon sequence variants (ASVs) that were subsets of the overall community, though some bacterial taxa clustered distinctly among hosts. Microbiomes were more similar within social groups than between them. Group membership strongly influenced the co‐occurrence of many beneficial ASVs, as well as a few potentially harmful ones. This effect was stronger than that of kinship, though closer relatives shared more similar microbiomes within some groups. While a range of social, biological and environmental factors influenced bacterial abundance, group membership, individual age and sampling time since sunrise had the most significant impact. ASV‐ASV co‐occurrence within hosts, independent of phylogeny, also played a major role. In contrast, individual‐level social traits (e.g. dominance, immigration), other environmental (e.g. sampling temperature, rainfall, hours since foraging), demographic (sex) and health‐related factors (body condition, disease status) had weaker effects on bacterial abundance. We show that gut microbiomes are shaped by a combination of factors, highlighting the importance of separating the effects of social organisation from individual social traits, biological factors, environmental influences and microbe–microbe interactions. By identifying drivers of both beneficial and detrimental bacterial co‐occurrence, we provide a foundation for assessing how the social microbiome affects animal health and fitness.

Biologists are increasingly interested in the ecological and evolutionary factors that influence microbial communities. Yet compared to bacterial communities, our understanding of viral community ecology remains limited. Here, we investigated the factors influencing viral community composition and structure among wild rhesus macaques ( Macaca mulatta ) in human‐modified environments in Bangladesh, focusing on assemblages of picobirnaviruses (PbVs) as a model system. We found that anthropogenic factors—particularly human and livestock densities—were the strongest predictors of viral community composition. Host social organisation played a secondary role, shaping viral communities at the group and site levels. Virus–virus associations influenced co‐occurrence patterns primarily within individual hosts, but their effect became less evident at broader scales. In contrast, individual host traits (age, sex and physiological stress) and viral phylogenetic relationships had minimal effects on viral co‐occurrence. Notably, anthropogenic factors had opposing effects on different PbV taxa: While some viruses were more prevalent in areas with higher human and livestock densities, others were less common, possibly due to their association with wildlife or natural environments. This suggests that macaques may acquire certain PbVs from anthropogenic sources while experiencing reduced exposure to others in human‐modified landscapes. Together, these findings reveal the dominant role of environmental and social factors in shaping viral communities and highlight the hierarchical nature of virus community assembly—with different ecological processes operating at individual, group and site scales.

The threat of disease transmission at the intersection of human‐wildlife interfaces underscores the urgent need for detailed studies on the transmission of human‐borne pathogens across species, especially among nonhuman primates in urban areas. This research focuses on the social and demographic determinants of Mycobacterium tuberculosis complex (MTBC) infection in free‐ranging long‐tailed macaques (Macaca fascicularis) in Thailand. Behavioral observations and noninvasive biological specimens (freshly defecated feces and rope‐baited oral samples) were collected from 98 long‐tailed macaques living in Wat Khao Thamon, southern Thailand, between August 2021 and February 2022. We detected the MTBC antigen using IS6110 nested‐PCR method in 11 out of 98 monkeys (11.22%). Logistic GLMs revealed that the risk of MTBC acquisition was higher among macaques with frequent human‐macaque interactions, whereas increased social grooming of conspecifics showed a nonsignificant trend toward reducing the risk. Our findings suggest that anthropogenic exposure increases the risk of MTBC infection among macaques, but this risk may be mitigated (socially buffered) by increased within‐group affiliative interactions. More generally, the potential for increased disease prevalence in wildlife with frequent human interactions or reduced social buffering highlights the need to consider animal socio‐demography when developing strategies to understand and prevent the transmission of diseases between humans and wildlife.

Biologists are increasingly interested in the ecological and evolutionary factors that influence microbial communities. Yet compared to bacterial communities, our understanding of viral community ecology remains limited. Here, we investigated the factors influencing viral community composition and structure among wild rhesus macaques (Macaca mulatta) in human-modified environments in Bangladesh, focusing on assemblages of picobirnaviruses (PbVs) as a model system. We found that anthropogenic factors—particularly human and livestock densities—were the strongest predictors of viral community composition. Host social structure played a secondary role, shaping viral communities at the group and site levels. Virus-virus associations influenced co-occurrence patterns primarily within individual hosts but their effect became less evident at broader scales. In contrast, individual host traits (age, sex, and physiological stress) and viral phylogenetic relationships had minimal effects on viral co-occurrence. Notably, anthropogenic factors had opposing effects on different PbV taxa: while some viruses were more prevalent in areas with higher human and livestock densities, others were less common, possibly due to their association with wildlife or natural environments. This suggests that macaques may acquire certain PbVs from anthropogenic sources while experiencing reduced exposure to others in human-modified landscapes. Together, these findings reveal the dominant role of environmental and social factors in shaping viral communities, and highlight the hierarchical nature of virus community assembly – with different ecological processes operating at individual, group, and site scales.

There is a vast and ever‐accumulating amount of behavioural data on individually recognised animals, an incredible resource to shed light on the ecological and evolutionary drivers of variation in animal behaviour. Yet, the full potential of such data lies in comparative research across taxa with distinct life histories and ecologies. Substantial challenges impede systematic comparisons, one of which is the lack of persistent, accessible and standardised databases. Big‐team approaches to building standardised databases offer a solution to facilitating reliable cross‐species comparisons. By sharing both data and expertise among researchers, these approaches ensure that valuable data, which might otherwise go unused, become easier to discover, repurpose and synthesise. Additionally, such large‐scale collaborations promote a culture of sharing within the research community, incentivising researchers to contribute their data by ensuring their interests are considered through clear sharing guidelines. Active communication with the data contributors during the standardisation process also helps avoid misinterpretation of the data, ultimately improving the reliability of comparative databases. Here, we introduce MacaqueNet, a global collaboration of over 100 researchers (https://macaquenet.github.io/) aimed at unlocking the wealth of cross‐species data for research on macaque social behaviour. The MacaqueNet database encompasses data from 1981 to the present on 61 populations across 14 species and is the first publicly searchable and standardised database on affiliative and agonistic animal social behaviour. We describe the establishment of MacaqueNet, from the steps we took to start a large‐scale collective, to the creation of a cross‐species collaborative database and the implementation of data entry and retrieval protocols. We share MacaqueNet's component resources: an R package for data standardisation, website code, the relational database structure, a glossary and data sharing terms of use. With all these components openly accessible, MacaqueNet can act as a fully replicable template for future endeavours establishing large‐scale collaborative comparative databases.

Ecologists are increasingly interested in the deterministic factors that influence microbial communities. Yet in comparison to other microbes, our understanding of viral community ecology is limited. Here we investigated the factors influencing the community ecology of picobirnaviruses among wild rhesus macaques (Macaca mulatta) in Bangladesh. Using co-occurrence networks and species distribution models, we found that macaques’ social organisation and anthropogenic factors (human and livestock densities) had the greatest impact on picobirnavirus communities. Virus phylogenetic relationships, host demographics (sex, age), and host physiological stress (cortisol levels) had less of an impact. We also found a few significant biotic virus-virus associations that impacted community composition, more so at lower host social organisational levels (individual macaques within groups) compared to higher levels (macaque groups within sites). These findings advance our understanding of the deterministic factors shaping viral communities, and contribute to changing perceptions of viruses as embedded components of human-natural ecosystems.

The fearful ape hypothesis proposes that heightened fearfulness in humans is adaptive. However, despite its attractive anthropocentric narrative, the evidence presented for greater fearfulness in humans versus other apes is not sufficient to support this claim. Conceptualization, context, and comparison are strongly lacking in Grossmann's proposal, but are key to understanding variation in the fear response among individuals and species.

Pandemics caused by pathogens that originate in wildlife highlight the importance of understanding the behavioral ecology of disease outbreaks at human–wildlife interfaces. Specifically, the relative effects of human–wildlife and wildlife-wildlife interactions on disease outbreaks among wildlife populations in urban and peri-urban environments remain unclear. We used social network analysis and epidemiological Susceptible-Infected-Recovered models to simulate zooanthroponotic outbreaks, through wild animals’ joint propensities to co-interact with humans, and their social grooming of conspecifics. On 10 groups of macaques (Macacaspp.) in peri-urban environments in Asia, we collected behavioral data using event sampling of human–macaque interactions within the same time and space, and focal sampling of macaques’ social interactions with conspecifics and overall anthropogenic exposure. Model-predicted outbreak sizes were related to structural features of macaques’ networks. For all three species, and for both anthropogenic (co-interactions) and social (grooming) contexts, outbreak sizes were positively correlated to the network centrality of first-infected macaques. Across host species and contexts, the above effects were stronger through macaques’ human co-interaction networks than through their grooming networks, particularly for rhesus and bonnet macaques. Long-tailed macaques appeared to show intraspecific variation in these effects. Our findings suggest that among wildlife in anthropogenically-impacted environments, the structure of their aggregations around anthropogenic factors makes them more vulnerable to zooanthroponotic outbreaks than their social structure. The global features of these networks that influence disease outbreaks, and their underlying socio-ecological covariates, need further investigation. Animals that consistently interact with both humans and their conspecifics are important targets for disease control.