Human population expansion into wildlife habitats has increased interest in the behavioural ecology of human-wildlife interactions. To date, however, the socioecological factors that determine whether, when or where wild animals take risks by interacting with humans and anthropogenic factors still remains unclear. We adopt a comparative approach to address this gap, using social network analysis (SNA). SNA, increasingly implemented to determine human impact on wildlife ecology, can be a powerful tool to understand how animal socioecology influences the spatiotemporal distribution of human-wildlife interactions. For 10 groups of rhesus, long-tailed and bonnet macaques (Macaca spp.) living in anthropogenically impacted environments in Asia, we collected data on human-macaque interactions, animal demographics, and macaque-macaque agonistic and affiliative social interactions. We constructed 'human co-interaction networks' based on associations between macaques that interacted with humans within the same time and spatial locations, and social networks based on macaque-macaque allogrooming behaviour, affiliative behaviours of short duration (agonistic support, lip-smacking, silent bare-teeth displays and non-sexual mounting) and proximity. Pre-network permutation tests revealed that, within all macaque groups, specific individuals jointly took risks by repeatedly, consistently co-interacting with humans within and across time and space. GLMMs revealed that macaques' tendencies to co-interact with humans was positively predicted by their tendencies to engage in short-duration affiliative interactions and tolerance of conspecifics, although the latter varied across species (bonnets>rhesus>long-tailed). Male macaques were more likely to co-interact with humans than females. Neither macaques' grooming relationships nor their dominance ranks predicted their tendencies to co-interact with humans. Our findings suggest that, in challenging anthropogenic environments, less (compared to more) time-consuming forms of affiliation, and additionally greater social tolerance in less ecologically flexible species with a shorter history of exposure to humans, may be key to animals' joint propensities to take risks to gain access to resources. For males, greater exploratory tendencies and less energetically demanding long-term life-history strategies (compared to females) may also influence such joint risk-taking. From conservation and public health perspectives, wildlife connectedness within such co-interaction networks may inform interventions to mitigate zoonosis, and move human-wildlife interactions from conflict towards coexistence.
In primates, living in an anthropogenic environment can significantly improve an individual's fitness, which is likely attributed to access to anthropogenic food resources. However, in non-professionally provisioned groups, few studies have examined whether individual attributes, such as dominance rank and sex, affect primates' ability to access anthropogenic food. Here, we investigated whether rank and sex explain individual differences in the proportion of anthropogenic food consumed by macaques. We observed 319 individuals living in nine urban groups across three macaque species. We used proportion of anthropogenic food in the diet as a proxy of access to those food resources. Males and high-ranking individuals in both sexes had significantly higher proportions of anthropogenic food in their diets than other individuals. We speculate that unequal access to anthropogenic food resources further increases within-group competition, and may limit fitness benefits in an anthropogenic environment to certain individuals.
Despite increasing conflict at human-wildlife interfaces, there exists little research on how the attributes and behavior of individual wild animals may influence human-wildlife interactions. Adopting a comparative approach, we examined the impact of animals' life-history and social attributes on interactions between humans and (peri)urban macaques in Asia. For 10 groups of rhesus, long-tailed, and bonnet macaques, we collected social behavior, spatial data, and human-interaction data for 11-20 months on pre-identified individuals. Mixed-model analysis revealed that, across all species, males and spatially peripheral individuals interacted with humans the most, and that high-ranking individuals initiated more interactions with humans than low-rankers. Among bonnet macaques, but not rhesus or long-tailed macaques, individuals who were more well-connected in their grooming network interacted more frequently with humans than less well-connected individuals. From an evolutionary perspective, our results suggest that individuals incurring lower costs related to their life-history (males) and resource-access (high rank; strong social connections within a socially tolerant macaque species), but also higher costs on account of compromising the advantages of being in the core of their group (spatial periphery), are the most likely to take risks by interacting with humans in anthropogenic environments. From a conservation perspective, evaluating individual behavior will better inform efforts to minimize conflict-related costs and zoonotic-risk.
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.