Oscillators connected in a network can show collective dynamics by enhancing coherent behaviours through their interactions. In biological systems, understanding synchronization is fundamentally important for conservation and management of various biological systems as synchronized populations are subject to extinction. Typically synchronization in metapopulations has mostly focused on static networks where links offer a permanent connectivity pattern between nodes/habitat patches. However, static environments do not experience large scale disturbances like habitat destruction, fragmentation, ephemeral pools and anthropogenic climate change, whereas dynamic environments experience such disturbances. Habitats are disturbance driven in dynamic landscapes and links between them are best described to form `temporal' networks, where connectivity may change across different time-scales. Hence it is of great importance to study the structure, dynamics and functioning of time-varying networks. In our work by characterizing the evolving connectivity in a biological system, we study how time-varying network influences the synchronized dynamics. We study the time-varying networks in an ecological system using a metacommunity model consisting of N patches connected by dispersal. In each patch, we use the well known Hastings and Powell's [Ecology 72, 896(1991)] tri-trophic food web model.
Results/Conclusions
We determine that time-varying networks strongly influence synchronization behaviour. We observe the effect of an evolving network in various network structures including regular, small-world and random networks using synchrony measure and basin stability. We have also studied the coherent dynamics of the metacommunity in time-varying networks using a clustering approach. In contrast to static networks, the synchronized dynamics of time-varying networks strongly depends on how fast the connectivity evolves over time. Time-varying networks with fast rewiring increase the extinction-risk in the metacommunity by enhancing synchronization. Both the dispersal rate and the average number of connectivity in the time-varying networks strongly influence the number of clusters and its frequency. Our results provide a better understanding of synchronization, and therefore persistence of temporally varying ecological networks.