Seasonal changes in the structure of rhesus macaque social networks

Abstract

Social structure emerges from the patterning of interactions between individuals and plays a critical role in shaping some of the main characteristics of animal populations. The topological features of social structure, such as the extent to which individuals interact in clusters, can influence many biologically important factors, including the persistence of cooperation, and the rate of spread of disease. Yet the extent to which social structure topology fluctuates over relatively short periods of time in relation to social, demographic or environmental events remains unclear. Here, we use social network analysis to examine seasonal changes in the topology of social structures that emerge from socio-positive associations in adult female rhesus macaques (Macaca mulatta). Behavioral data for two different association types (grooming, spatial proximity) were collected for females in two free-ranging groups during two seasons: the mating and birth seasons. Stronger dyadic bonds resulted in social structures that were more tightly connected (i.e. of greater density) in the mating season compared to the birth season. Social structures were also more centralized around a subset of individuals, and were more clustered in the mating season than the birth season, although the latter differences were mostly driven by differences in density alone. Our results suggest a degree of temporal variation in the topological features of social structure in this population. Such variation may feed back on interactions, hence affecting the behaviors of individuals, and may therefore be important to take into account in studies of animal behavior.

Machine vision methods for analyzing social interactions

“…Much information about an animal's social life can be learned from observing who it interacts with (Brent et al, 2013). Social interactions can be extracted from trajectories by either identifying regions of interest (ROIs) within an arena and defining an interaction as two animals simultaneously in the same ROI (Shemesh et al, 2013), or by using thresholds on proximity, heading direction and behavior duration (Schneider et al, 2012).…”

Degrees of freedom in social bonds of crested macaque females

“…In this study, we aim to investigate these degrees of freedom and the interplay between the 140 structure and the value of social bonds in wild female crested macaques (M. nigra), which express a 141 tolerant social style (Petit, MacLarnon, Platt, & Semple, 2013). Previous studies on the same population showed that female 150 crested macaques form highly diverse affiliative social networks (Duboscq et al, 2013).…”

Social network dynamics: the importance of distinguishing between heterogeneous and homogeneous changes

“…Similar issues can also arise in studies on the influence of seasonal changes on social 388 networks (e.g. Henzi et al 2009; Brent et al 2013) or in studies of natural knockouts where knockouts effects could be conflated with seasonal effects (Barrett et al 2012). …”

“…In addition, we show that one commonly used test for the analysis of changes in social network structures, the bootstrap test (e.g. Lusseau et al 2008; Henzi et al 2009; Brent et al 2013), fails to distinguish between homogeneous and heterogeneous changes. We then show that an appropriate randomization test can be used instead of, or in addition to, the bootstrap, to infer whether heterogeneous changes occurred.…”

“…While most studies of social networks in animal behavior have focused on describing static network structures there is an increasing interest in studying how social networks change over time and what determines the stability of social networks (Wittemyer et al 2005; Flack et al 2006; Hansen et al 2009; Ansmann et al 2012; Blonder et al 2012; Cantor et al 2012; Foster et al 2012; Brent et al 2013; Gero et al 2013; Hobson et al 2013; Boogert et al 2014; Pinter Wollman et al 2014; Wilson et al 2014). Indeed, inferring changes in social network structures has the potential to provide crucial insights into how social dynamics change over time, for instance, in response to seasonal changes (Wittemyer et al 2005 ; Henzi et al 2009; Brent et al 2013) or in response to disturbances such as the removal of important individuals (Flack et al 2006; Barrett et al 2012). …”