Interaction network based early-warning indicators of vegetation transitions

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/26550

dc.contributor	Universitat Politècnica de Catalunya. Departament de Física i Enginyeria Nuclear
dc.contributor	Universitat Politècnica de Catalunya. DONLL - Dinàmica no Lineal, Òptica no Lineal i Làsers
dc.contributor.author	Tirabassi, Giulio
dc.contributor.author	Viebahn, Jan P.
dc.contributor.author	Dakos, Vasilis
dc.contributor.author	Dijkstra, Hendrik
dc.contributor.author	Masoller Alonso, Cristina
dc.contributor.author	Rietkerk, Max
dc.contributor.author	Dekker, Stefan C.
dc.date	2014-09-01
dc.identifier.citation	Tirabassi, G. [et al.]. Interaction network based early-warning indicators of vegetation transitions. "Ecological complexity", 01 Setembre 2014, vol. 19, p. 148-157.
dc.identifier.citation	1476-945X
dc.identifier.citation	10.1016/j.ecocom.2014.06.004
dc.identifier.uri	http://hdl.handle.net/2117/26550
dc.language.iso	eng
dc.relation	http://www.sciencedirect.com/science/article/pii/S1476945X14000695
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Desenvolupament humà i sostenible
dc.subject	Desertification
dc.subject	Resilience (Ecology)
dc.subject	Desertification
dc.subject	Early-warning indicators
dc.subject	Networks
dc.subject	Catastrophic transitions
dc.subject	Catastrophic shifts
dc.subject	Ecosystems
dc.subject	Signals
dc.subject	Resilience
dc.subject	Desertització
dc.subject	Ecologia
dc.title	Interaction network based early-warning indicators of vegetation transitions
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/article
dc.description.abstract	Changes in vegetation patterns in semi-arid regions can precede the abrupt transition to bare soil. Here, complex network techniques are used to develop novel early-warning indicators for these desertification transitions. These indicators are applied to results from a local positive feedback vegetation model and are compared to classical indicators, such as the autocorrelation and variance of biomass time series. A quantitative measure is also introduced to evaluate the quality of the early-warning indicators. Based on this measure, the network-based indicators are superior to the classical ones, being more sensitive to the presence of the transition point.
dc.description.abstract	Peer Reviewed

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