Macaque progressions: passing order during single-file movements reflects the social structure of a wild stump-tailed macaque group.

Inferring the latent structures of social organisations is a central theme in animal ecology. Sophisticated theoretical frameworks underpin the study of various primate social systems. Single-file movements, defined as serially ordered patterns of animals, reflect intra-group social relationships and provide a key to understanding social structures. Here, we analysed automated camera-trapping data on the order of progression of single-file movements in a free-ranging group of stump-tailed macaques to estimate the social structure of the group. The sequence of single file movements showed some regularities, particularly for adult males. Social network analysis identified four community clusters (subgroups) corresponding to the social structures reported for these stumptailed macaques, i.e. males that had copulated more frequently with females were spatially clustered with females, but males that had copulated less frequently were spatially isolated from females. Our results suggest that stumptailed macaques move in regular, socially determined patterns that reflect the spatial positions of adult males and are related to the social organisation of the species.

Agent-based simulation for reconstructing social structure by observing collective movements with special reference to single-file movement.

Understanding social organization is fundamental for the analysis of animal societies. In this study, animal single-file movement data-serialized order movements generated by simple bottom-up rules of collective movements-are informative and effective observations for the reconstruction of animal social structures using agent-based models. For simulation, artificial 2-dimensional spatial distributions were prepared with the simple assumption of clustered structures of a group. Animals in the group are either independent or dependent agents. Independent agents distribute spatially independently each one another, while dependent agents distribute depending on the distribution of independent agents. Artificial agent spatial distributions aim to represent clustered structures of agent locations-a coupling of "core" or "keystone" subjects and "subordinate" or "follower" subjects. Collective movements were simulated following two simple rules, 1) initiators of the movement are randomly chosen, and 2) the next moving agent is always the nearest neighbor of the last moving agents, generating "single-file movement" data. Finally, social networks were visualized, and clustered structures reconstructed using a recent major social network analysis (SNA) algorithm, the Louvain algorithm, for rapid unfolding of communities in large networks. Simulations revealed possible reconstruction of clustered social structures using relatively minor observations of single-file movement, suggesting possible application of single-file movement observations for SNA use in field investigations of wild animals.

Visualization of the Dynamics Effect: Projection of on-the-Fly Trajectories to the Subspace Spanned by the Static Reaction Path Network.

Following our recent work to reduce a dimension of a set of reference structures along the intrinsic reaction coordinate (IRC) by a classical multidimensional scaling (CMDS) approach (J. Chem. Theory Comput. 2018, 14, 4263-4270), we propose the method to project on-the-fly trajectories into a reduced-dimension subspace determined by the IRC network, using the out-of-sample extension of CMDS. The method was applied to the SN2 reaction, OH- + CH3F, in which trajectories show a bifurcating nature around the highly curved region of the IRC path, and to the structural transformation of Au5 cluster in which the global reaction path network consists of five equilibrium structures and 14 IRCs. It was demonstrated that the present analysis can visualize the dynamics effect by showing a dynamic reaction route on the basis of the static reaction paths.

Visualization of the Intrinsic Reaction Coordinate and Global Reaction Route Map by Classical Multidimensional Scaling.

A classical multidimensional scaling (CMDS) method is employed to visualize an intrinsic reaction coordinate (IRC) and a global reaction route map consisting of the equilibrium minima and transition state structures connected by the IRC network. As demonstrations, the method was applied to the IRCs of the intramolecular proton transfer in malonaldehyde and the SN2 reaction of OH- + CH3F → CH3OH + F-, which are both well described by two principal coordinates. Next, the method was applied to the global reaction route map of the Au5 cluster; the resulting map shows appropriate positions of five minima and 14 transition states in a reduced 2- or 3-dimensional coordinate space successfully.