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Tipping point detection and early warnings in climate, ecological, and human systems

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Title: Tipping point detection and early warnings in climate, ecological, and human systems
Authors: Dakos, Vasilis, Boulton, Chris A., Buxton, Joshua E., Abrams, Jesse F., Arellano Nava, Beatriz, Armstrong McKay, David I., Bathiany, Sebastian, Blaschke, Lana, Boers, Niklas, Dylewsky, Daniel, López Martínez, Carlos, Parry, Isobel, Ritchie, Paul, van der Bolt, Bregje, van der Laan, Larissa, Weinans, Els, Kéfi, Sonia
Contributors: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. CommSensLab-UPC - Centre de Recerca en Comunicació i Detecció UPC
Publisher Information: European Geosciences Union (EGU)
Publication Year: 2024
Collection: Universitat Politècnica de Catalunya, BarcelonaTech: UPCommons - Global access to UPC knowledge
Subject Terms: Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Teledetecció, Climatic changes -- Mathematical models, Ecology -- Statistical methods, Case-studies, Climate system, Early warning, Ecological systems, Environmental conditions, Human-systems, Tipping points, Literature review, Canvis climàtics -- Models matemàtics, Ecologia -- Mètodes estadístics
Description: Tipping points characterize the situation when a system experiences abrupt, rapid, and sometimes irreversible changes in response to only a gradual change in environmental conditions. Given that such events are in most cases undesirable, numerous approaches have been proposed to identify if a system is approaching a tipping point. Such approaches have been termed early warning signals and represent a set of methods for identifying statistical changes in the underlying behaviour of a system across time or space that would be indicative of an approaching tipping point. Although the idea of early warnings for a class of tipping points is not new, in the last 2 decades, the topic has generated an enormous amount of interest, mainly theoretical. At the same time, the unprecedented amount of data originating from remote sensing systems, field measurements, surveys, and simulated data, coupled with innovative models and cutting-edge computing, has made possible the development of a multitude of tools and approaches for detecting tipping points in a variety of scientific fields. However, we miss a complete picture of where, how, and which early warnings have been used so far in real-world case studies. Here we review the literature of the last 20 years to show how the use of these indicators has spread from ecology and climate to many other disciplines. We document what metrics have been used; their success; and the field, system, and tipping points involved. We find that, despite acknowledged limitations and challenges, in the majority of the case studies we reviewed, the performance of most early warnings was positive in detecting tipping points. Overall, the generality of the approaches employed – the fact that most early warnings can in theory be observed in many dynamical systems – explains the continuous multitude and diversification in their application across scientific domains. ; Chris A. Boulton, Joshua E. Buxton, and David I. Armstrong McKay were supported by the Bezos Earth Fund via the Global Tipping Points ...
Document Type: article in journal/newspaper
File Description: 19 p.; application/pdf
Language: English
Relation: https://esd.copernicus.org/articles/15/1117/2024/; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114623RB-C32/ES/ENFOQUES SINERGICOS PARA UNA NUEVA GENERACION DE PRODUCTOS Y APLICACIONES DE OBSERVACION DE LA TIERRA. PARTE UPC/; https://hdl.handle.net/2117/414956
DOI: 10.5194/esd-15-1117-2024
Availability: https://hdl.handle.net/2117/414956
https://doi.org/10.5194/esd-15-1117-2024
Rights: http://creativecommons.org/licenses/by/4.0/ ; Open Access ; Attribution 4.0 International
Accession Number: edsbas.E01415EE
Database: BASE
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  Data: Tipping point detection and early warnings in climate, ecological, and human systems
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  Data: <searchLink fieldCode="AR" term="%22Dakos%2C+Vasilis%22">Dakos, Vasilis</searchLink><br /><searchLink fieldCode="AR" term="%22Boulton%2C+Chris+A%2E%22">Boulton, Chris A.</searchLink><br /><searchLink fieldCode="AR" term="%22Buxton%2C+Joshua+E%2E%22">Buxton, Joshua E.</searchLink><br /><searchLink fieldCode="AR" term="%22Abrams%2C+Jesse+F%2E%22">Abrams, Jesse F.</searchLink><br /><searchLink fieldCode="AR" term="%22Arellano+Nava%2C+Beatriz%22">Arellano Nava, Beatriz</searchLink><br /><searchLink fieldCode="AR" term="%22Armstrong+McKay%2C+David+I%2E%22">Armstrong McKay, David I.</searchLink><br /><searchLink fieldCode="AR" term="%22Bathiany%2C+Sebastian%22">Bathiany, Sebastian</searchLink><br /><searchLink fieldCode="AR" term="%22Blaschke%2C+Lana%22">Blaschke, Lana</searchLink><br /><searchLink fieldCode="AR" term="%22Boers%2C+Niklas%22">Boers, Niklas</searchLink><br /><searchLink fieldCode="AR" term="%22Dylewsky%2C+Daniel%22">Dylewsky, Daniel</searchLink><br /><searchLink fieldCode="AR" term="%22López+Martínez%2C+Carlos%22">López Martínez, Carlos</searchLink><br /><searchLink fieldCode="AR" term="%22Parry%2C+Isobel%22">Parry, Isobel</searchLink><br /><searchLink fieldCode="AR" term="%22Ritchie%2C+Paul%22">Ritchie, Paul</searchLink><br /><searchLink fieldCode="AR" term="%22van+der+Bolt%2C+Bregje%22">van der Bolt, Bregje</searchLink><br /><searchLink fieldCode="AR" term="%22van+der+Laan%2C+Larissa%22">van der Laan, Larissa</searchLink><br /><searchLink fieldCode="AR" term="%22Weinans%2C+Els%22">Weinans, Els</searchLink><br /><searchLink fieldCode="AR" term="%22Kéfi%2C+Sonia%22">Kéfi, Sonia</searchLink>
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  Data: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions<br />Universitat Politècnica de Catalunya. CommSensLab-UPC - Centre de Recerca en Comunicació i Detecció UPC
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  Data: Tipping points characterize the situation when a system experiences abrupt, rapid, and sometimes irreversible changes in response to only a gradual change in environmental conditions. Given that such events are in most cases undesirable, numerous approaches have been proposed to identify if a system is approaching a tipping point. Such approaches have been termed early warning signals and represent a set of methods for identifying statistical changes in the underlying behaviour of a system across time or space that would be indicative of an approaching tipping point. Although the idea of early warnings for a class of tipping points is not new, in the last 2 decades, the topic has generated an enormous amount of interest, mainly theoretical. At the same time, the unprecedented amount of data originating from remote sensing systems, field measurements, surveys, and simulated data, coupled with innovative models and cutting-edge computing, has made possible the development of a multitude of tools and approaches for detecting tipping points in a variety of scientific fields. However, we miss a complete picture of where, how, and which early warnings have been used so far in real-world case studies. Here we review the literature of the last 20 years to show how the use of these indicators has spread from ecology and climate to many other disciplines. We document what metrics have been used; their success; and the field, system, and tipping points involved. We find that, despite acknowledged limitations and challenges, in the majority of the case studies we reviewed, the performance of most early warnings was positive in detecting tipping points. Overall, the generality of the approaches employed – the fact that most early warnings can in theory be observed in many dynamical systems – explains the continuous multitude and diversification in their application across scientific domains. ; Chris A. Boulton, Joshua E. Buxton, and David I. Armstrong McKay were supported by the Bezos Earth Fund via the Global Tipping Points ...
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  Data: https://esd.copernicus.org/articles/15/1117/2024/; info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114623RB-C32/ES/ENFOQUES SINERGICOS PARA UNA NUEVA GENERACION DE PRODUCTOS Y APLICACIONES DE OBSERVACION DE LA TIERRA. PARTE UPC/; https://hdl.handle.net/2117/414956
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  Data: https://hdl.handle.net/2117/414956<br />https://doi.org/10.5194/esd-15-1117-2024
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