Revealing the hidden structure of dynamic ecological networks - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Royal Society Open Science Année : 2017

Revealing the hidden structure of dynamic ecological networks

Résumé

Recent technological advances and long-term data studies provide interaction data that can be modelled through dynamic networks, i.e a sequence of different snapshots of an evolving ecological network. Most often time is the parameter along which these networks evolve but any other one-dimensional gradient (temperature, altitude, depth, humidity, . . . ) could be considered. Here we propose a statistical tool to analyse the underlying structure of these networks and follow its evolution dynamics (either in time or any other one-dimensional factor). It consists in extracting the main features of these networks and summarise them into a high-level view. We analyse a dynamic animal contact network and a seasonal food web and in both cases we show that our approach allows for the identification of a backbone organisation as well as interesting temporal variations at the individual level. Our method, implemented into the R package dynsbm, can handle the largest ecological datasets and is a versatile and promising tool for ecologists that study dynamic interactions.
Fichier principal
Vignette du fichier
mee_miele.pdf (307.24 Ko) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01426652 , version 1 (05-01-2017)

Identifiants

Citer

Vincent Miele, Catherine Matias. Revealing the hidden structure of dynamic ecological networks. Royal Society Open Science, 2017, 4, pp.170251. ⟨10.1098/rsos.170251⟩. ⟨hal-01426652⟩
277 Consultations
156 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More