Communities recognition in the Chesapeake Bay ecosystem by dynamical clustering algorithms based on different oscillators systems
Dipartimento di Fisica e Astronomia, Universitá di Catania, and INFN sezione di Catania, via S. Sofia 64, 95123 Catania, Italy
Corresponding author: a firstname.lastname@example.org
Revised: 19 June 2008
Published online: 23 July 2008
We have recently introduced [Phys. Rev. E 75, 045102(R) (2007); AIP Conference Proceedings 965, 2007, p. 323] an efficient method for the detection and identification of modules in complex networks, based on the de-synchronization properties (dynamical clustering) of phase oscillators. In this paper we apply the dynamical clustering tecnique to the identification of communities of marine organisms living in the Chesapeake Bay food web. We show that our algorithm is able to perform a very reliable classification of the real communities existing in this ecosystem by using different kinds of dynamical oscillators. We compare also our results with those of other methods for the detection of community structures in complex networks.
PACS: 89.75.Hc – Networks and genealogical trees / 05.45.Xt – Synchronization; coupled oscillators
© EDP Sciences, Società Italiana di Fisica, Springer-Verlag, 2008