Evidence map›Paper›PMID 38040724›Full record

ArticleNature communications2023

Early warning signals have limited applicability to empirical lake data.

Duncan A O'Brien, Smita Deb, Gideon Gal, Stephen J Thackeray, Partha S Dutta, Shin-Ichiro S Matsuzaki, Linda May, Christopher F Clements

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Early warning signals for loss of control in complex systems.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  3. Early Warning Signals in Ecological Time-Series.Entropy (Basel, Switzerland) · 2026
    Review
  4. Article
  5. Review
  6. Generalized Mechanism Model for Ecosystem Hysteresis.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
  7. Review
  8. Article
  9. Article
  10. Revealing unseen dynamical regimes of ecosystems from population time-series data.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Duncan A O'BrienSchool of Biological Sciences, University of Bristol, Bristol, BS8 1TQ, UK. duncan.a.obrien@gmail.com.ORCID 0000-0002-3420-5210
Smita DebDepartment of Mathematics, Indian Institute of Technology Ropar, Rupnagar, Punjab, 140001, India.
Gideon GalKinneret Limnological Laboratory, Israel Oceanographic & Limnological Research, PO Box 447, Migdal, Israel.ORCID 0000-0002-6962-4001
Stephen J ThackerayLake Ecosystems Group, UK Centre for Ecology & Hydrology, Bailrigg, Lancaster, UK.ORCID 0000-0003-3274-2706
Partha S DuttaDepartment of Mathematics, Indian Institute of Technology Ropar, Rupnagar, Punjab, 140001, India.ORCID 0000-0001-6067-1023
Shin-Ichiro S MatsuzakiBiodiversity Division, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-8506, Japan.ORCID 0000-0003-2744-1343
Linda MayUK Centre for Ecology & Hydrology, Bush Estate, Penicuik, Midlothian, EH26 OQB, UK.ORCID 0000-0003-3385-9973
Christopher F ClementsSchool of Biological Sciences, University of Bristol, Bristol, BS8 1TQ, UK.ORCID 0000-0001-5677-5401

Funding

RCUK | Natural Environment Research Council (NERC) NE/R011524/1RCUK | Natural Environment Research Council (NERC) NE/R016429/1
6 · The paper itself

Abstract

Research aimed at identifying indicators of persistent abrupt shifts in ecological communities, a.k.a regime shifts, has led to the development of a suite of early warning signals (EWSs). As these often perform inaccurately when applied to real-world observational data, it remains unclear whether critical transitions are the dominant mechanism of regime shifts and, if so, which EWS methods can predict them. Here, using multi-trophic planktonic data on multiple lakes from around the world, we classify both lake dynamics and the reliability of classic and second generation EWSs methods to predict whole-ecosystem change. We find few instances of critical transitions, with different trophic levels often expressing different forms of abrupt change. The ability to predict this change is highly processing dependant, with most indicators not performing better than chance, multivariate EWSs being weakly superior to univariate, and a recent machine learning model performing poorly. Our results suggest that predictive ecology should start to move away from the concept of critical transitions, developing methods suitable for predicting resilience loss not limited to the strict bounds of bifurcation theory.

Indexed as

EcosystemLakesEcologyModels, BiologicalReproducibility of Results

Identifiers

PMID38040724
PMCPMC10692136

What OpenQuestion holds

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Registered trials

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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.