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Memorias de investigación
Research Publications in journals:
Effects of topology on robustness in ecological bipartite networks
Year:2012
Research Areas
  • Physics chemical and mathematical
Information
Abstract
High robustness of complex ecological systems in the face of species extinction has been hypothesized based on the redundancy in species. We explored how differences in network topology may affect robustness. Ecological bipartite networks used to be small, asymmetric and sparse matrices. We created synthetic networks to study the influence of the properties of network dimensions asymmetry, connectance and type of degree distribution on network robustness. We used two extinction strategies: node extinction and link extinction, and three extinction sequences differing in the order of species removal (least-to-most connected, random, most-to-least connected). We assessed robustness to extinction of simulated networks, which differed in one of the three topological features. Simulated networks indicated that robustness decreases when (a) extinction involved those nodes belonging to the most species-rich guild and (b) networks had lower connectance. We also compared simulated networks with different degree- distribution networks, and they showed important differences in robustness depending on the extinction scenario. In the link extinction strategy, the robustness of synthetic networks was clearly determined by the asymmetry in the network dimensions, while the variation in connectance produced negligible differences.
International
Si
JCR
Si
Title
Networks And Heterogeneous Media
ISBN
1556-1801
Impact factor JCR
0,658
Impact info
Volume
7
10.3934/nhm.2012.7.429
Journal number
3
From page
429
To page
440
Month
SEPTIEMBRE
Ranking
Participants
  • Autor: Juan Manuel Pastor Ruiz (UPM)
  • Autor: Silvia Santamaria (Universidad Rey Juan Carlos)
  • Autor: Marcos Méndez (Universidad Rey Juan Carlos)
  • Autor: Javier Ricardo Galeano Prieto (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Sistemas Complejos
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