TIPPEN

Tipping Points in Ecological Networks

 Coordinatore AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS 

 Organization address address: CALLE SERRANO 117
city: MADRID
postcode: 28006

contact info
Titolo: Mr.
Nome: Alberto
Cognome: Sereno Alvarez
Email: send email
Telefono: 34915668852
Fax: 34915668913

 Nazionalità Coordinatore Spain [ES]
 Totale costo 168˙896 €
 EC contributo 168˙896 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2011-IEF
 Funding Scheme MC-IEF
 Anno di inizio 2013
 Periodo (anno-mese-giorno) 2013-04-01   -   2015-03-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS

 Organization address address: CALLE SERRANO 117
city: MADRID
postcode: 28006

contact info
Titolo: Mr.
Nome: Alberto
Cognome: Sereno Alvarez
Email: send email
Telefono: 34915668852
Fax: 34915668913

ES (MADRID) coordinator 168˙896.40

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

warning    transitions    critical    signals    ecosystems    simple    tipping    models   

 Obiettivo del progetto (Objective)

'Ecosystems occasionally respond abruptly to small changes in external conditions. Such abrupt responses can represent critical transitions that occur at tipping points where the ecosystem shifts to an alternative regime. Despite the often profound consequences of tipping events, our ability to predict them is still limited. To meet this challenge, generic early-warning signals for critical transitions have recently been proposed. These signals are generic, because they may in principle work irrespectively of the specific mechanism responsible for the tipping, making their potential field of application very broad. However, they have so-far been mostly analyzed in simple models that neglect the high spatial and structural complexity that characterizes most ecosystems. The proposed project aims to help bridging this gap between complex reality and simple models by 1) analyzing how critical transitions arise in spatially and structurally complex ecological networks, and 2) investigating how this kind of critical transitions might be detected by generic early-warning signals. The anticipated results will be of more than academic interest, as the complex webs of interactions in nature are under increasing pressure and there is an urgent need to understand how we may estimate the risk of systemic collapses.'

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