ArticleiScience2023
Systematic analysis and optimization of early warning signals for critical transitions using distribution data.
Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed.
- Trend-Conditioned Residual Learning for Early Fault Warning in Nonstationary Multi-Sensor Oil Monitoring.Sensors (Basel, Switzerland) · 2026Article
- Detecting and forecasting tipping points from sample variance alone.PNAS nexus · 2026Article
- Examining the research methods of early warning signals in clinical psychology through a theoretical lens.BMC psychiatry · 2025Review
- Local Predictors of Explosive Synchronization with Ordinal Methods.Entropy (Basel, Switzerland) · 2025Article
- Assessing and comparing early warning signal performance in spatially-structured systems.PloS one · 2025Article
- An early warning indicator trained on stochastic disease-spreading models with different noises.Journal of the Royal Society, Interface · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Abrupt shifts between alternative regimes occur in complex systems, from cell regulation to brain functions to ecosystems. Several model-free early warning signals (EWS) have been proposed to detect impending transitions, but failure or poor performance in some systems have called for better investigation of their generic applicability. Notably, there are still ongoing debates whether such signals can be successfully extracted from data in particular from biological experiments. In this work, we systematically investigate properties and performance of dynamical EWS in different deteriorating conditions, and we propose an optimized combination to trigger warnings as early as possible, eventually verified on experimental data from microbiological populations. Our results explain discrepancies observed in the literature between warning signs extracted from simulated models and from real data, provide guidance for EWS selection based on desired systems and suggest an optimized composite indicator to alert for impending critical transitions using distribution data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.