Dynamics of communities in two fission-fusion species, Grevy's zebra and onager Chayant Tantipathananandh 1, Tanya Y. Berger-Wolf 1, Siva R. Sundaresan 2, Ilya R. Fischhoff 2, and Daniel I. Rubenstein 2 1 Dept. of Computer Science, University of Illinois at Chicago, USA 2 Dept. of Ecology and Evolutionary Biology, Princeton University, USA Introduction We consider the problem of identifying communities in populations with changing social affiliations over time. Ours is the first community identification method that does not aggregate information over time but takes the dynamic nature of interactions explicitly into consideration, accounting for a fluid and changing community structure. Here we apply our method to two equid species: Grevy's zebra (Equus grevyi) and onagers (Equus hemionus khur). The two populations are of similar fission-fusion species with territorial males and harem females. However, there are ecological differences which have been expected to result in different social patterns between the two species. The results of applying our method not only confirm the ecological insight but quantify it and provide visual supporting evidence of the difference. In particular, Grevy's zebra have a more cohesive social structure, which suggests a preference of individual company. In contrast, the social groups in onagers are more happenstance, which suggests that group formation is a byproduct of other ecological factors, such as congregation at a waterhole or seeking strength in numbers against predation OnagersGrevy’s zebras A recurring community A persistent community Fleeting small communities, otherwise isolated individuals. Dynamic Community Identification Method We assume that social individuals need to maintain the following properties: Individual Conservatism They rarely change community affiliations Group Loyalty They tend to stay near by other individuals from the same community to socialize They tend to be unseen at the same time Deviations from these assumptions are possible and ideally need to be at minimum to maintain socialization. Finding dynamic community that minimizes these deviations is NP-complete. Example Analysis Figure 2. Each color represents one community. Color of a group indicates which community the group represents (which may or may not be dominating color within group). Color of individuals indicate its affiliation at the moment. Green individual in blue group Green individual absent from green group Affiliation Change: Green-blue-green A small community References Sundaresan, S. R., Fischhoff, I. R., Dushoff, J. & Rubenstein, D. I Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager. Oecologia, 151, Tantipathananandh, C., Berger-Wolf T., Kempe, D A Framework For Identifying Communities in Dynamic Social Networks. Proceedings of the 13th ACM SIGKDD, fission fusion fission fusion fission Observation We assume that the input is obtained as a sequence of population snapshots. Day 3 Day 1 Groups of individuals in each snapshot are defined by spatial proximity time T1 T2 T3 T4 T5 T1 T2 T3 T4 T Observed Individuals Unseen Individuals Static Networks Dynamic Networks Entire group was unseen The recurring community (see below)