Sharing from the Same Bowl: Resource Partitioning between Sympatric Macaque Species in the Western Himalaya, India

Comparative ecological and behavioral study of Macaca assamensis and M. mulatta in Shivapuri Nagarjun National Park, Nepal

Resource partitioning reduces the competition between different species within the same habitat, promoting their coexistence. To understand how such species co-adapt to reduce conflicts, we examined the behavior of two primates, Assamese macaque (Macaca assamensis) and rhesus macaque (Macaca mulatta), from April 2017 to March 2018 in Sivapuri Nagarjun National Park (SNNP), Kathmandu Valley, Nepal. We performed 1580 and 1261 scan sessions on wild multi-male/multi-female groups of Assamese and rhesus macaques, respectively, at 15-min sampling intervals. Assamese macaques consumed fewer plant species (38 species) than rhesus macaques (88 species). Overlapping food sources between the macaque species resulted in a Pianka index of 0.5. Assamese macaques consumed more items of tree, climber, and vine species, whereas rhesus macaques fed on more shrub, herb, and grass species. The proportions of plant parts consumed by the two species differed-more leaves, fruits and cones were used by Assamese macaques than rhesus macaques, whereas more flowers, seeds, and pods were consumed by rhesus macaques than Assamese macaques. Assamese macaques had a smaller home range (0.55 km²) than rhesus macaques (4.23 km²), and Assamese macaques had a shorter daily moving distance (1.6 km) than rhesus macaques (4.0 km). Although feeding time did not differ between the two macaque species, less time was devoted to social activities by Assamese macaques (16.0%) than by rhesus macaques (33.7%). Assamese macaques were generally arboreal, with 94.0% of their activities in trees, whereas rhesus macaques were largely terrestrial, with 58.5% of their activities on the ground. These differences in food selection, home-range size, ranging and activity patterns, and habitat use suggest that Assamese and rhesus macaques reduce resource competition through resource partitioning to coexist in a landscape matrix.