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

引爆点(物理) 领域(数学) 数据科学 气候变化 计算机科学 多样性(控制论) 集合(抽象数据类型) 预警系统 点(几何) 生态学 地理 环境资源管理 运筹学 环境科学 人工智能 工程类 数学 电信 生物 几何学 纯数学 程序设计语言 电气工程
作者
Vasilis Dakos,Chris A. Boulton,Joshua Buxton,Jesse F. Abrams,Beatriz Arellano Nava,David I. Armstrong McKay,Sebastian Bathiany,Lana Blaschke,Niklas Boers,Daniel Dylewsky,Carlos López-Martínez,Isobel Parry,Paul Ritchie,Bregje van der Bolt,Larissa van der Laan,Els Weinans,Sonia Kéfi
出处
期刊:Earth System Dynamics Discussions [Copernicus Publications]
卷期号:15 (4): 1117-1135 被引量:3
标识
DOI:10.5194/esd-15-1117-2024
摘要

Abstract. 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.
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