Social network community structure and the contact-mediated sharing of commensal E. coli among captive rhesus macaques (Macaca mulatta)

Flocking dynamics mediated by weighted social networks

We study the effects of animal social networks with a weighted pattern of interactions on the flocking transition exhibited by models of self-organized collective motion. We consider variations of traditional models of collective motion in which interactions between individuals are mediated by static complex weighted networks, representing patterns of social interactions. For a model representing dynamics on a one-dimensional substrate, application of a heterogeneous mean-field theory provides a phase diagram as function of the heterogeneity of the network connections and the correlations between weights and degree. In this diagram we observe two phases, one corresponding to the presence of a transition and other to a transition suppressed in an always ordered system, already observed in the nonweighted case. Interestingly, a third phase, with no transition in an always disordered state, is also obtained. These predictions, numerically recovered in computer simulations, are also fulfilled for the more realistic Vicsek model, with movement in a two-dimensional space. Additionally, we observe at finite network sizes the presence of a maximum threshold for particular weight configurations, indicating that it is possible to tune weights to achieve a maximum resilience to noise effects. Simulations in real weighted animal social networks show that, in general, the presence of weights diminishes the value of the flocking threshold, thus increasing the fragility of the flocking state. The shift in the threshold is observed to depend on the heterogeneity of the weight pattern.

Impact of joint interactions with humans and social interactions with conspecifics on the risk of zooanthroponotic outbreaks among wildlife populations

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 (Macaca spp.) 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.

Monkey's Social Roles Predict Their Affective Reactivity

Accumulating evidence demonstrates that the number of social connections an individual has predicts health and wellbeing outcomes in people and nonhuman animals. In this report, we investigate the relationship between features of an individuals' role within his social network and affective reactivity to ostensibly threatening stimuli, using a highly translatable animal model - rhesus monkeys. Features of the social network were quantified via observations of one large (0.5 acre) cage that included 83 adult monkeys. The affective reactivity profiles of twenty adult male monkeys were subsequently evaluated in two classic laboratory-based tasks of negative affective reactivity (human intruder and object responsiveness). Rhesus monkeys who had greater social status, characterized by age, higher rank, more close social partners, and who themselves have more close social partners, and who played a more central social role in their affiliative network were less reactive on both tasks. While links between social roles and social status and psychological processes have been demonstrated, these data provide new insights about the link between social status and affective processes in a tractable animal model of human health and disease.

Social networks research in ex situ populations: Patterns, trends, and future directions for conservation-focused behavioral research

Social networks research using non-human animals has grown over the past decade, utilizing a wide range of species to answer an array of pure and applied questions. Network approaches have relevance to conservation, evaluating social influences on fecundity, health, fitness and longevity. While the application of network approaches to in situ populations with conservation concern appears in published literature, the degree to which ex situ and zoo-housed populations are the focus of "social networks for conservation research" is limited. Captive environments provide scientists with an ability to understand the social behavior of species that may be hard to observe consistently in the wild. This paper evaluates the scope of network research involving ex situ populations, analyzing output from 2010 to 2019 to determine trends in questions and subjects using ex situ populations. We show that only 8.2% of ex situ social network analysis (SNA) implications are of conservation-focus, apparent in papers relating to birds, carnivores, bats, primates, reptiles, and ungulates. Husbandry and welfare questions predominate in ex situ network research, but over half of these papers have nonpractical application (basic science). The chance of a citation for a basic science paper was 95.4% more than for a conservation-based paper. For taxonomic groups, primate-focused papers had the most citations. The focus of ex situ conservation-based networks research may be driven by the needs of conservation programs (e.g., population recovery outcomes) or by a need to evaluate the efficacy of ex situ conservation goals. We evaluate our findings considering the IUCN's One Plan Approach to conservation to show how in situ and ex situ network research is applicable to global conservation efforts. We have identified that there is a lack of application and evaluation of SNA to wildlife conservation. We highlight future areas of research in zoos and hope to stimulate discussion and collaboration between relevant parties.

Gaps to Address in Ecological Studies of Temperament and Physiology

Ecology is a diverse field with many researchers interested in drivers and consequences of variability within populations. Two aspects of variability that have been addressed are behavioral and physiological. While these have been shown to separately influence ecological outcomes such as survival, reproductive success and fitness, combined they could better predict within-population variability in survival and fitness. Recently there has been a focus on potential fitness outcomes of consistent behavioral traits that are referred to as personality or temperament (e.g. boldness, sociability, exploration, etc.). Given this recent focus, it is an optimal time to identify areas to supplement in this field, particularly in determining the relationship between temperament and physiological traits. To maximize progress, in this perspective paper we propose that the following two areas be addressed: (1) increased diversity of species, and (2) increased number of physiological processes studied, with an eye toward using more representative and relatively consistent measures across studies. We first highlight information that has been gleaned from species that are frequently studied to determine how animal personality relates to physiology and/or survival/fitness. We then shine a spotlight on important taxa that have been understudied and that can contribute meaningful, complementary information to this area of research. And last, we propose a brief array of physiological processes to relate to temperament, and that can significantly impact fitness, and that may be accessible in field studies.

Animal movement in a pastoralist population in the Maasai Mara Ecosystem in Kenya and implications for pathogen spread and control

Livestock movements are important drivers for infectious disease transmission. However, paucity of such data in pastoralist communities in rangeland ecosystems limits our understanding of their dynamics and hampers disease surveillance and control. The aim of this study was to investigate animal movement networks in a pastoralist community in Kenya, and assess network-based strategies for disease control. We used network analysis to characterize five types of between-village animal movement networks. We then evaluated implications of these networks for disease spread and control by quantifying topological changes in the network associated with targeted and random removal of nodes. To construct these networks, data were collected using standardized questionnaires (N = 165 households) from communities living within the Maasai Mara Ecosystem in southwestern Kenya. Our analyses show that the Maasai Mara National Reserve (MMNR), a protected wildlife area, was critical for maintaining village connectivity in the agistment network (dry season grazing), with MMNR-adjacent villages being highly utilized during the dry season. In terms of disease dynamics, the network-based basic reproduction number, R₀, was sufficient to allow disease invasion in all the five networks, and removal of villages based on degree or betweenness was not efficient in reducing R₀. However, we show that villages with high degree or betweenness may play an important role in maintaining network connectivity, which may not be captured by assessment of R₀ alone. Such villages may function as potential "firebreaks." For example, targeted removal of highly connected village nodes was more effective at fragmenting each network than random removal of nodes, indicating that network-based targeting of interventions such as vaccination could potentially disrupt transmission pathways in the ecosystem. In conclusion, this work shows that animal movements have the potential to shape patterns of disease transmission in this ecosystem, with targeted interventions being a practical and efficient measure for disease control.

Bacterial dispersal and drift drive microbiome diversity patterns within a population of feral hindgut fermenters

Studies of microbiome variation in wildlife often emphasize host physiology and diet as proximate selective pressures acting on host-associated microbiota. In contrast, microbial dispersal and ecological drift are more rarely considered. Using amplicon sequencing, we characterized the bacterial microbiome of adult female (n = 86) Sable Island horses (Nova Scotia, Canada) as part of a detailed individual-based study of this feral population. Using data on sampling date, horse location, age, parental status, and local habitat variables, we contrasted the ability of spatiotemporal, life history, and environmental factors to explain microbiome diversity among Sable Island horses. We extended inferences made from these analyses with both phylogeny-informed and phylogeny-independent null modelling approaches to identify deviations from stochastic expectations. Phylogeny-informed diversity measures were correlated with spatial and local habitat variables, but null modelling results suggested that heterogeneity in ecological drift, rather than differential selective pressures acting on the microbiome, was responsible for these correlations. Conversely, phylogeny-independent diversity measures were best explained by host spatial and social structure, suggesting that taxonomic composition of the microbiome was shaped most strongly by bacterial dispersal. Parental status was important but correlated with measures of β-dispersion rather than β-diversity (mares without foals had lower alpha diversity and more variable microbiomes than mares with foals). Our results suggest that between host microbiome variation within the Sable Island horse population is driven more strongly by bacterial dispersal and ecological drift than by differential selective pressures. These results emphasize the need to consider alternative ecological processes in the study of microbiomes.

Primate Infectious Disease Ecology: Insights and Future Directions at the Human-Macaque Interface

Global population expansion has increased interactions and conflicts between humans and nonhuman primates over shared ecological space and resources. Such ecological overlap, along with our shared evolutionary histories, makes human-nonhuman primate interfaces hot spots for the acquisition and transmission of parasites. In this chapter, we bring to light the importance of human-macaque interfaces in particular as hot spots for infectious disease ecological and epidemiological assessments. We first outline the significance and broader objectives behind research related to the subfield of primate infectious disease ecology and epidemiology. We then reveal how members of the genus Macaca, being among the most socioecologically flexible and invasive of all primate taxa, live under varying degrees of overlap with humans in anthropogenic landscapes. Thus, human-macaque interfaces may favor the bidirectional exchange of parasites. We then review studies that have isolated various types of parasites at human-macaque interfaces, using information from the Global Mammal Parasite Database (GMPD: http://www.mammalparasites.org/). Finally, we elaborate on avenues through which the implementation of both novel conceptual frameworks (e.g., Coupled Systems, One Health) and quantitative network-based approaches (e.g., social and bipartite networks, agent-based modeling) may potentially address some of the critical gaps in our current knowledge of infectious disease ecology at human-primate interfaces.

Leveraging non-human primates for exploring the social transmission of microbes

Host social interactions can provide multiple complex pathways for microbial transmission. Here, we suggest non-human primates as models to study the social transmission of commensal or mutualistic microbes due to their high sociality, wide range of group compositions and dominance structures, and diverse group interactions. Microbial sharing from social interactions can positively impact host health by promoting microbial diversity and influencing immunity. Microbes may also drive their own transmission by shaping host behavior, which could lead to fitness benefits for both microbes and hosts. Variation in patterns of social interactions at both the individual and group scale make non-human primates an ideal system to explore the relationship between social behavior, microbial sharing, and their impact on host health and evolution.

Commensal bacterial sharing does not predict host social associations in kangaroos

Social network analysis has been postulated as a tool to study potential pathogen transmission in wildlife but is resource-intensive to quantify. Networks based on bacterial genotypes have been proposed as a cost-effective method for estimating social or transmission network based on the assumption that individuals in close contact will share commensal bacteria. However, the use of network analysis to study wild populations requires critical evaluation of the assumptions and parameters these models are founded on. We test (a) whether networks of commensal bacterial sharing are related to hosts' social associations and hence could act as a proxy for estimating transmission networks, (b) how the parameters chosen to define host associations and delineate bacterial genotypes impact inference and (c) whether these relationships change across time. We use stochastic simulations to evaluate how uncertainty in parameter choice affects network structure. We focused on a well-studied population of eastern grey kangaroos (Macropus giganteus), from Sundown National Park, Australia. Using natural markings, each individual was identified and its associations with other kangaroos recorded through direct field observations over 2 years to construct social networks. Faecal samples were collected, Escherichia coli was cultured and genotyped using BOX-PCR, and bacterial networks were constructed. Two individuals were connected in the bacterial network if they shared at least one E. coli genotype. We determined the capacity of bacterial networks to predict the observed social network structure in each year. We found little support for a relationship between social association and dyadic commensal bacterial similarity. Thresholds to determine host associations and similarity cut-off values used to define E. coli genotypes had important ramifications for inferring links between individuals. In fact, we found that inferences can show opposite patterns based on the chosen thresholds. Moreover, no similarity in overall bacterial network structure was detected between years. Although empirical disease transmission data are often unavailable in wildlife populations, both bacterial networks and social networks have limitations in representing the mode of transmission of a pathogen. Our results suggest that caution is needed when designing such studies and interpreting results.

Affiliation and disease risk: social networks mediate gut microbial transmission among rhesus macaques

In social animals, affiliative behaviours bring many benefits, but also costs such as disease risk. The ways in which affiliation may affect the risk of infectious agent transmission remain unclear. Moreover, studies linking variation in affiliative interactions to infectious agent incidence/diversity have speculated that disease transmission may have occurred, rather than revealing that transmission did occur. We address these gaps using the phylogenetics of commensal gut Escherichia coli to determine whether affiliative grooming and huddling social networks mediated microbial transmission among rhesus macaques. We collected behavioural and microbial data from adult macaques across a 12-week period that was split into two 6-week phases to better detect dyadic transmission. We reconstructed undirected social networks from affiliative interactions and reconstructed microbial transmission networks from the pairwise phylogenetic similarity of E. coli pulsotypes from macaques within and across adjacent sampling events. Macaque E. coli pulsotypes were more phylogenetically similar to each other than to environmental isolates, which established a premise for socially mediated transmission. Dyadic grooming and huddling frequencies strongly influenced the likelihood of E. coli transmission during the second data collection phase, but not the first. Macaques that were more central/well connected in both their grooming and huddling networks were also more central in the E. coli transmission networks. Our results confirmed that affiliative grooming and huddling behaviours mediate the transmission of gut microbes among rhesus macaques, particularly among females and high-ranking individuals. The detectability of socially mediated E. coli transmission maybe partially masked by environmental acquisition in males, or by high frequencies of interactions in captivity. Predicting the potential transmission pathways of gastrointestinal parasites and pathogens, our findings add to current knowledge of the coevolutionary relationships between affiliative behaviour and health and may be used to identify 'superspreader' individuals as potential targets for disease control strategies.

Social stability influences the association between adrenal responsiveness and hair cortisol concentrations in rhesus macaques

Hair cortisol concentrations are increasingly being used in both humans and nonhuman animals as a biomarker of chronic stress. However, many details regarding how hair cortisol concentrations relate to the dynamic activity and regulation of the HPA axis are still unknown. The current study explores 1) how the regulation of the HPA axis in infancy relates to hair cortisol concentrations (HCC) in infancy 2) whether this relationship persists into adulthood under conditions of social stability, and 3) how social instability impacts these relationships. All subjects were rhesus monkeys housed in large social groups at the California National Primate Research Center, and all had participated in a 25-hr. long BioBehavioral Assessment (BBA) at 3-4 months of age when four plasma samples were taken to assess HPA regulation, in particular cortisol responses to 1) 2-hour social separation and relocation, 2) sustained challenge, 3) dexamethasone and 4) ACTH administration. In Study 1, hair samples were collected at the end of the BBA testing from 25 infant rhesus monkeys from 2 different stable social groups. In Study 2, hair samples were obtained at three timepoints from 108 adults from 3 different stable social groups (1 in the Spring/Summer and 2 in the Fall/Winter) to examine the temporal stability of the relationship between HCC and HPA axis regulation. In Study 3, subjects included 31 infants and 33 adults from a single social group experiencing social instability following the same procedures as in Studies 1 and 2. Generalized linear models were used to determine if infants' HPA axis activity and regulation predicted HCC in infancy (Study 1), in adulthood with animals living in stable social conditions (Study 2) or in animals living in an unstable social group (Study 3). Results indicated that for both infants and adults living in stable social groups, HCC are associated with the adrenal response to ACTH in infancy. Samples collected in the winter also had higher HCC than those collected in summer. In the unstable social group, adult hair cortisol levels were higher than in the stable social groups. Additionally, there were no consistent relationships between HCC and infant HPA axis regulation among adults or infants living in a group experiencing social instability. These results suggest that the aspects of the HPA axis that drive HCC may differ depending on context. Under stable, non-stressed conditions there seems to be a trait-like association between adrenal responsivity and HCC in infancy and adulthood. However, this association may be reduced or eliminated under conditions of social stress.