Description
Human and nonhuman primates (primates, hereafter) interact with one another in diverse ways. Although the nature of these interactions has been well documented, we still have limited insight as to why humans and primates interact in the patterns we observe. Drawing from life history theory, social network analysis, and human-animal studies, I used an ethnoprimatological approach to examine interactions between humans and a group of moor macaques (Macaca maura) along a provincial road in South Sulawesi, Indonesia. From August 2016-February 2017 I collected behavioral data to investigate how life history and social network factors influence primates’ tendency to interact with humans and how these interactions affect primate social networks. I also documented patterns of primate-directed behavior displayed by humans and conducted semi-structured interviews with area residents and national park staff to assess people’s motivations for interacting with primates. General linear mixed models demonstrate that life history, but not social network factors or individual’s positions within the social network, explains individual’s tendency to be along the road. Specifically, males were more likely than females to be on the road, regardless of age class, associate attributes, or position within the social network. The macaques’ social network was significantly more fragmented along the road as compared to the forest and was characterized by shifts in network roles across context. Interview data suggests that empathy, conceptions of nature, and knowledge of and prior exposure to primates all shape how and why people interact with primates. These findings further our understanding of how the human-primate interface is co-shaped by both species and provides important conservation insights. Specifically, we demonstrate the extent to which interactions with humans disrupt primate social behavior and how humans’ diverse motivations for interacting with primates pose complex conservation challenges, the causes of which cannot be assumed to be understood a priori.
