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Contribution Details

Type Journal Article
Scope Discipline-based scholarship
Title Nestedness in complex networks: Observation, emergence, and implications
Organization Unit
  • Manuel Mariani
  • Zhuo-Ming Ren
  • Jordi Bascompte
  • Claudio Tessone
Item Subtype Original Work
Refereed Yes
Status Published in final form
  • English
Journal Title Physics Reports
Publisher Elsevier
Geographical Reach international
ISSN 0370-1573
Volume 813
Page Range 1 - 90
Date 2019
Abstract Text The observed architecture of ecological and socio-economic networks differssignificantly from that of random networks. From a network science standpoint, non-random structural patterns observed in real networks call for an explanation of their emergence and an understanding of their potential systemic consequences. This article focuses on one of these patterns: nestedness. Given a network of interacting nodes, nestedness can be described as the tendency for nodes to interact with subsets of the interaction partners of better-connected nodes. Known since more than 80 years in biogeography, nestedness has been found in systems as diverse as ecological mutualistic systems, world trade, inter-organizational relations, among many others. This review article focuses on three main pillars: the existing methodologies to observe nestedness in networks; the main theoretical mechanisms conceived to explain the emergence of nestedness in ecological and socio-economic networks; the implications of a nested topology of interactions for the stability and feasibility of a given interacting system. We survey results from variegated disciplines, including statistical physics, graph theory, ecology, and theoretical economics. Nestedness was found to emerge both in bipartite networks and, more recently, in unipartite ones; this review is the first comprehensive attempt to unify both streams of studies, usually disconnected from each other. We believe that the truly interdisciplinary endeavor – while rooted in a complex systems perspective – may inspire new models and algorithms whose realm of application will undoubtedly transcend disciplinary boundaries.
Digital Object Identifier 10.1016/j.physrep.2019.04.001
Other Identification Number merlin-id:17846
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