@misc{10481/31118,
year = {2013},
url = {http://hdl.handle.net/10481/31118},
abstract = {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.},
organization = {This work was supported by Junta de Andalucia projects FQM-01505 and P09-FQM4682, and by Spanish MEC-FEDER project FIS2009-08451. S.J. is grateful for financial support from the European Commision under the Marie Curie Intra-European Fellowship Programme PIEF-GA-2010-276454.},
publisher = {Public Library of Science (PLOS)},
keywords = {Biodiversity},
keywords = {Calculators},
keywords = {Community ecology},
keywords = {Complex systems},
keywords = {Ecosystems},
keywords = {Scale-free networks},
keywords = {Theoretical ecology},
keywords = {Topology},
title = {Factors Determining Nestedness in Complex Networks},
author = {Johnson, Samuel and Domínguez-García, Virginia and Muñoz Martínez, Miguel Ángel},
}