Pathogen transmission modes determine contact network structure, altering other pathogen characteristics

MacaqueNet: Advancing comparative behavioural research through large-scale collaboration

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.

Epidemiological Consequences of Individual Centrality on Wild Chimpanzees

Disease outbreaks are one of the key threats to great apes and other wildlife. Because the spread of some pathogens (e.g., respiratory viruses, sexually transmitted diseases, ectoparasites) are mediated by social interactions, there is a growing interest in understanding how social networks predict the chain of pathogen transmission. In this study, we built a party network from wild chimpanzees (Pan troglodytes), and used agent-based modeling to test: (i) whether individual attributes (sex, age) predict individual centrality (i.e., whether it is more or less socially connected); (ii) whether individual centrality affects an individual's role in the chain of pathogen transmission; and, (iii) whether the basic reproduction number (R0) and infectious period modulate the influence of centrality on pathogen transmission. We show that sex and age predict individual centrality, with older males presenting many (degree centrality) and strong (strength centrality) relationships. As expected, males are more central than females within their network, and their centrality determines their probability of getting infected during simulated outbreaks. We then demonstrate that direct measures of social interaction (strength centrality), as well as eigenvector centrality, strongly predict disease dynamics in the chimpanzee community. Finally, we show that this predictive power depends on the pathogen's R0 and infectious period: individual centrality was most predictive in simulations with the most transmissible pathogens and long-lasting diseases. These findings highlight the importance of considering animal social networks when investigating disease outbreaks.

Social interactions do not affect mycoplasma infection in griffon vultures

Uncovering the ways in which pathogens spread has important implications for population health and management. Pathogen transmission is influenced by various factors, including patterns of social interactions and shared use of space. We aim to understand how the social behaviour of griffon vultures (Gyps fulvus), a species of conservation interest, influences the presence or absence of mycoplasma, a group of bacteria known to cause respiratory diseases in birds. We investigated how direct and indirect social interactions of griffon vultures in the wild, in different social situations, impacted the mycoplasma infection status. We inferred interactions from high-resolution global positioning system (GPS) tracking data. Specifically, we assessed how social behaviour affects infection status when vultures share feeding and roosting locations, either at the same time (direct interactions) or subsequently, when space use is asynchronous (indirect interactions). We did not detect a significant effect of any social situation and type of interaction on infection status. However, we observed a high population prevalence of mycoplasma, suggesting that other factors might be more important than social interactions in determining the transmission of this bacteria in the Israeli vulture population. Uncovering the mechanisms that underlie infection status in wildlife is crucial for maintaining viable populations, designing containment management actions and gaining insights into the ecological mechanisms that drive infectious disease dynamics.

The contribution of movement to social network structure and spreading dynamics under simple and complex transmission

The structure of social networks fundamentally influences spreading dynamics. In general, the more contact between individuals, the more opportunity there is for the transmission of information or disease to take place. Yet, contact between individuals, and any resulting transmission events, are determined by a combination of spatial (where individuals choose to move) and social rules (who they choose to interact with or learn from). Here, we examine the effect of the social-spatial interface on spreading dynamics using a simulation model. We quantify the relative effects of different movement rules (localized, semi-localized, nomadic and resource-based movement) and social transmission rules (simple transmission, anti-conformity, proportional, conformity and threshold rules) to both the structure of social networks and spread of a novel behaviour. Localized movement created weakly connected sparse networks, nomadic movement created weakly connected dense networks, and resource-based movement generated strongly connected modular networks. The resulting rate of spreading varied with different combinations of movement and transmission rules, but-importantly-the relative rankings of transmission rules changed when running simulations on static versus dynamic representations of networks. Our results emphasize that individual-level social and spatial behaviours influence emergent network structure, and are of particular consequence for the spread of information under complex transmission rules.This article is part of the theme issue 'The spatial-social interface: a theoretical and empirical integration'.

Social and environmental transmission spread different sets of gut microbes in wild mice

Gut microbes shape many aspects of organismal biology, yet how these key bacteria transmit among hosts in natural populations remains poorly understood. Recent work in mammals has emphasized either transmission through social contacts or indirect transmission through environmental contact, but the relative importance of different routes has not been directly assessed. Here we used a novel radio-frequency identification-based tracking system to collect long-term high-resolution data on social relationships, space use and microhabitat in a wild population of mice (Apodemus sylvaticus), while regularly characterizing their gut microbiota with 16S ribosomal RNA profiling. Through probabilistic modelling of the resulting data, we identify positive and statistically distinct signals of social and environmental transmission, captured by social networks and overlap in home ranges, respectively. Strikingly, microorganisms with distinct biological attributes drove these different transmission signals. While the social network effect on microbiota was driven by anaerobic bacteria, the effect of shared space was most influenced by aerotolerant spore-forming bacteria. These findings support the prediction that social contact is important for the transfer of microorganisms with low oxygen tolerance, while those that can tolerate oxygen or form spores may be able to transmit indirectly through the environment. Overall, these results suggest social and environmental transmission routes can spread biologically distinct members of the mammalian gut microbiota.

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.

Ornaments indicate parasite load only if they are dynamic or parasites are contagious

Choosing to mate with an infected partner has several potential fitness costs, including disease transmission and infection-induced reductions in fecundity and parental care. By instead choosing a mate with no, or few, parasites, animals avoid these costs and may also obtain resistance genes for offspring. Within a population, then, the quality of sexually selected ornaments on which mate choice is based should correlate negatively with the number of parasites with which a host is infected ("parasite load"). However, the hundreds of tests of this prediction yield positive, negative, or no correlation between parasite load and ornament quality. Here, we use phylogenetically controlled meta-analysis of 424 correlations from 142 studies on a wide range of host and parasite taxa to evaluate explanations for this ambiguity. We found that ornament quality is weakly negatively correlated with parasite load overall, but the relationship is more strongly negative among ornaments that can dynamically change in quality, such as behavioral displays and skin pigmentation, and thus can accurately reflect current parasite load. The relationship was also more strongly negative among parasites that can transmit during sex. Thus, the direct benefit of avoiding parasite transmission may be a key driver of parasite-mediated sexual selection. No other moderators, including methodological details and whether males exhibit parental care, explained the substantial heterogeneity in our data set. We hope to stimulate research that more inclusively considers the many and varied ways in which parasites, sexual selection, and epidemiology intersect.