Flexibility in the social structure of male chimpanzees (Pan troglodytes schweinfurthii) in the Budongo Forest, Uganda

Individuals of social species experience competitive costs and social benefits of group living. Substantial flexibility in humans' social structure and the combination of different types of social structure with fission-fusion dynamics allow us to live in extremely large groups-overcoming some of the costs of group living while capitalizing on the benefits. Non-human species also show a range of social strategies to deal with this trade-off. Chimpanzees are an archetypical fission-fusion species, using dynamic changes in day-to-day association to moderate the costs of within-group competition. Using 4 years of association data from two neighbouring communities of East African chimpanzees (Pan troglodytes schweinfurthii), we describe an unexplored level of flexibility in chimpanzee social structure. We show that males from the larger Waibira community (N = 24-31) exhibited additional structural levels of semi-stable core-periphery society, while males from the smaller Sonso community (N = 10-13) did not. This novel core-periphery pattern adds to previous results describing alternative modular social structure in other large communities of chimpanzees. Our data support the hypothesis that chimpanzees can incorporate a range of strategies in addition to fission-fusion to overcome costs of social living, and that their social structures may be closer to that of modern humans than previously described.

Predictions of primate-parasite coextinction

Future biodiversity loss threatens the integrity of complex ecological associations, including among hosts and parasites. Almost half of primate species are threatened with extinction, and the loss of threatened hosts could negatively impact parasite associations and ecosystem functions. If endangered hosts are highly connected in host-parasite networks, then future host extinctions will also drive parasite extinctions, destabilizing ecological networks. If threatened hosts are not highly connected, however, then network structure should not be greatly affected by the loss of threatened hosts. Networks with high connectance, modularity, nestedness and robustness are more resilient to perturbations such as the loss of interactions than sparse, nonmodular and non-nested networks. We analysed the interaction network involving 213 primates and 763 parasites and removed threatened primates (114 species) to simulate the effects of extinction. Our analyses revealed that connections to 23% of primate parasites (176 species) may be lost if threatened primates go extinct. In addition, measures of network structure were affected, but in varying ways because threatened hosts have fewer parasite interactions than non-threatened hosts. These results reveal that host extinctions will perturb the host-parasite network and potentially lead to secondary extinctions of parasites. The ecological consequences of these extinctions remain unclear. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.

Effects of host extinction and vector preferences on vector-borne disease risk in phylogenetically structured host-hector communities

Anthropogenic disturbance impacts the phylogenetic composition and diversity of ecological communities. While changes in diversity are known to dramatically change species interactions and alter disease dynamics, the effects of phylogenetic changes in host and vector communities on disease have been relatively poorly studied. Using a theoretical model, we investigated how phylogeny and extinction influence network structural characteristics relevant to disease transmission in disturbed environments. We modelled a multi-host, multi-vector community as a bipartite ecological network, where nodes represent host and vector species and edges represent connections among them through vector feeding, and we simulated vector preferences and threat status on host and parasite phylogenies. We then simulated loss of hosts, including phylogenetically clustered losses, to investigate how extinction influences network structure. We compared effects of phylogeny and extinction to those of host specificity, which we predicted to strongly increase network modularity and reduce disease prevalence. The simulations revealed that extinction often increased modularity, with higher modularity as species loss increased, although not as much as increasing host specificity did. These results suggest that extinction itself, all else being equal, may reduce disease prevalence in disturbed communities. However, in real communities, systematic patterns in species loss (e.g. favoring high competence species) or changes in abundance may counteract these effects. Unexpectedly, we found that effects of phylogenetic signal in host and vector traits were relatively weak, and only important when phylogenetic signal of host and vector traits were similar, or when these traits both varied.

Spatial and temporal variation in proximity networks of commercial dairy cattle in Great Britain

The nature of contacts between hosts can be important in facilitating or impeding the spread of pathogens within a population. Networks constructed from contacts between hosts allow examination of how individual variation might influence the spread of infections. Studying the contact networks of livestock species managed under different conditions can additionally provide insight into their influence on these contact structures. We collected high-resolution proximity and GPS location data from nine groups of domestic cattle (mean group size = 85) in seven dairy herds employing a range of grazing and housing regimes. Networks were constructed from cattle contacts (defined by proximity) aggregated by different temporal windows (2 h, 24 h, and approximately 1 week) and by location within the farm. Networks of contacts aggregated over the whole study were highly saturated but dividing contacts by space and time revealed substantial variation in cattle interactions. Cows showed statistically significant variation in the frequency of their contacts and in the number of cows with which they were in contact. When cows were in buildings, compared to being on pasture, contact durations were longer and cows contacted more other cows. A small number of cows showed evidence of consistent relationships but the majority of cattle did not. In one group where management allowed free access to all farm areas, cows showed asynchronous space use and, while at pasture, contacted fewer other cows and showed substantially greater between-individual variation in contacts than other groups. We highlight the degree to which variations in management (e.g. grazing access, milking routine) substantially alter cattle contact patterns, with potentially major implications for infection transmission and social interactions. In particular, where individual cows have free choice of their environment, the resulting contact networks may have a less-risky structure that could reduce the likelihood of direct transmission of infections.

A Guide for Choosing Community Detection Algorithms in Social Network Studies: The Question Alignment Approach

INTRODUCTION

Community detection, the process of identifying subgroups of highly connected individuals within a network, is an aspect of social network analysis that is relevant but potentially underutilized in prevention research. Guidance on using community detection methods stresses aligning methods with specific research questions but lacks clear operationalization. The Question Alignment approach was developed to help address this gap and promote the high-quality use of community detection methods.

METHODS

A total of 6 community detection methods are discussed: Walktrap, Edge-Betweenness, Infomap, Louvain, Label Propagation, and Spinglass. The Question Alignment approach is described and demonstrated using real-world data collected in 2013. This hypothetical case study was conducted in 2019 and focused on targeting a hand hygiene intervention to high-risk communities to prevent influenza transmission.

RESULTS

Community detection using the Walktrap method best fit the hypothetical case study. The communities derived using the Walktrap method were quite different from communities derived through the other 5 methods in both the number of communities and individuals within communities. There was evidence to support that the Question Alignment approach can help researchers produce more useful community detection results. Compared to other methods of selecting high-risk groups, the Walktrap produced the most communities that met the hypothetical intervention requirements.

CONCLUSIONS

As prevention research incorporating social networks increases, researchers can use the Question Alignment approach to produce more theoretically meaningful results and potentially more useful results for practice. Future research should focus on assessing whether the Question Alignment approach translates into improved intervention results.

Behavioural ecology and infectious disease: implications for conservation of biodiversity

Behaviour underpins interactions among conspecifics and between species, with consequences for the transmission of disease-causing parasites. Because many parasites lead to declines in population size and increased risk of extinction for threatened species, understanding the link between host behaviour and disease transmission is particularly important for conservation management. Here, we consider the intersection of behaviour, ecology and parasite transmission, broadly encompassing micro- and macroparasites. We focus on behaviours that have direct impacts on transmission, as well as the behaviours that result from infection. Given the important role of parasites in host survival and reproduction, the effects of behaviour on parasitism can scale up to population-level processes, thus affecting species conservation. Understanding how conservation and infectious disease control strategies actually affect transmission potential can therefore often only be understood through a behavioural lens. We highlight how behavioural perspectives of disease ecology apply to conservation by reviewing the different ways that behavioural ecology influences parasite transmission and conservation goals. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'.

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.