| Autor: |
Dakos, Vasilis, Boulton, Chris A., Buxton, Josh E., Abrams, Jesse F., McKay, David I. Armstrong, 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 |
| Předmět: |
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| Zdroj: |
EGUsphere; 8/7/2023, p1-35, 35p |
| Abstrakt: |
Tipping points characterize the situation when a system experiences abrupt, rapid and sometimes irreversible changes. Given that such changes are in most cases undesirable, numerous approaches have been proposed to identify if a system is close to a tipping point. Such approaches have been termed early-warning signals and represent a set of methods for identifying statistical changes in the underlying behavior 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 two decades, the topic 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. Yet, 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 as well as the field, system and tipping point 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 on any dynamical system – explains the continuous multitude and diversification in their application across scientific domains. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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