Factors determining nestedness in complex networks

• Published in: PloS one 2013-09, Vol.8 (9), p.e74025-e74025
• Main Authors: Jonhson, Samuel, Domínguez-García, Virginia, Muñoz, Miguel A
• Format: Article
• Language: English
• Subjects: Algorithms; Biodiversity; Competition; Complex systems; Computer Simulation; Ecological monitoring; Ecology; Ecosystem biology; Ecosystems; Networks; Neural Networks (Computer)
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0074025

Understanding the causes and effects of network structural features is a key task in deciphering complex systems. In this context, the property of network nestedness has aroused a fair amount of interest as regards ecological networks. Indeed, Bastolla et al. introduced a simple measure of network nestedness which opened the door to analytical understanding, allowing them to conclude that biodiversity is strongly enhanced in highly nested mutualistic networks. Here, we suggest a slightly refined version of such a measure of nestedness and study how it is influenced by the most basic structural properties of networks, such as degree distribution and degree-degree correlations (i.e. assortativity). We find that most of the empirically found nestedness stems from heterogeneity in the degree distribution. Once such an influence has been discounted - as a second factor - we find that nestedness is strongly correlated with disassortativity and hence - as random networks have been recently found to be naturally disassortative - they also tend to be naturally nested just as the result of chance.