Tipping points and cascading transitions: methods, principles, and evidence.
- 1School of Systems Science, Beijing Normal University, Beijing 100875, China.
- 2Department of Complexity Science, Potsdam Institute for Climate Impact Research, Potsdam 14412, Germany.
- 3Department of Physics, Humboldt University Berlin, Berlin 10099, Germany.
Abstract
This review synthesizes recent advancements in understanding tipping points and cascading transitions within the Earth system, framing them through the lens of nonlinear dynamics and complexity science. It outlines the fundamental concepts of tipping elements, large-scale subsystems like the Atlantic Meridional Overturning Circulation and the Amazon rainforest, and classifies tipping mechanisms into bifurcation-, noise-, and rate-induced types. The article critically evaluates methods for detecting early-warning signals, particularly those based on critical slowing down, while also acknowledging their limitations and the promise of non-conventional indicators. Furthermore, we explore the significant risk of cascading transitions between interacting tipping elements, often modeled using conceptual network models. This shows that such interactions can substantially increase systemic risk under global warming. The review concludes by outlining key challenges related to data limitations and methodological robustness, and emphasizes the promising role of artificial intelligence and complex network science in advancing prediction and risk assessment of Earth system tipping dynamics.
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BibTeX
@article{fang2026tipping,
title = {{Tipping points and cascading transitions: methods, principles, and evidence.}},
author = {Sheng Fang and Ziyan Wang and Jürgen Kurths and Jingfang Fan},
journal = {National science review},
year = {2026},
month = aug,
doi = {10.1093/nsr/nwag478},
url = {https://europepmc.org/article/MED/42953327},
note = {CC BY},
}
RIS
TY - JOUR
TI - Tipping points and cascading transitions: methods, principles, and evidence.
AU - Sheng Fang
AU - Ziyan Wang
AU - Jürgen Kurths
AU - Jingfang Fan
PY - 2026
DA - 2026/08/07
JO - National science review
DO - 10.1093/nsr/nwag478
UR - https://europepmc.org/article/MED/42953327
AB - This review synthesizes recent advancements in understanding tipping points and cascading transitions within the Earth system, framing them through the lens of nonlinear dynamics and complexity science. It outlines the fundamental concepts of tipping elements, large-scale subsystems like the Atlantic Meridional Overturning Circulation and the Amazon rainforest, and classifies tipping mechanisms into bifurcation-, noise-, and rate-induced types. The article critically evaluates methods for detecting early-warning signals, particularly those based on critical slowing down, while also acknowledging their limitations and the promise of non-conventional indicators. Furthermore, we explore the significant risk of cascading transitions between interacting tipping elements, often modeled using conceptual network models. This shows that such interactions can substantially increase systemic risk under global warming. The review concludes by outlining key challenges related to data limitations and methodological robustness, and emphasizes the promising role of artificial intelligence and complex network science in advancing prediction and risk assessment of Earth system tipping dynamics.
SN - 2095-5138
SN - 2053-714X
ER -