Evidence map›Paper›PMID 27220202›Full record

ArticleEcology2016

Balls, cups, and quasi-potentials: quantifying stability in stochastic systems.

Ben C Nolting, Karen C Abbott

Abstract read
In one paragraph

Article in Ecology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Towards Operationalizing Ecological Resilience for Infrastructure Decision-Making.Risk analysis : an official publication of the Society for Risk Analysis · 2026
    Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
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  9. Kelp-forest dynamics controlled by substrate complexity.Proceedings of the National Academy of Sciences of the United States of America · 2022
    Article
  10. Article
  11. Unifying deterministic and stochastic ecological dynamics via a landscape-flux approach.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Crossing the quasi-threshold manifold of a noise-driven excitable system.Proceedings. Mathematical, physical, and engineering sciences · 2017
    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

2 authors.

Ben C Nolting
Karen C Abbott

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When a system has more than one stable state, how can the stability of these states be compared? This deceptively simple question has important consequences for ecosystems, because systems with alternative stable states can undergo dramatic regime shifts. The probability, frequency, duration, and dynamics of these shifts will all depend on the relative stability of the stable states. Unfortunately, the concept of "stability" in ecology has suffered from substantial confusion and this is particularly problematic for systems where stochastic perturbations can cause shifts between coexisting alternative stable states. A useful way to visualize stable states in stochastic systems is with a ball-in-cup-diagram, in which the state of the system is represented as the position of a ball rolling on a surface, and the random perturbations can push the ball from one basin of attraction to another. The surface is determined by a potential function, which provides a natural stability metric. Systems amenable to this representation, called gradient systems, are quite rare, however. As a result, the potential function is not widely used and other approaches based on linear stability analysis have become standard. Linear stability analysis is designed for local analysis of deterministic systems and, as we show, can produce a highly misleading picture of how the system will behave under continual, stochastic perturbations. In this paper, we show how the potential function can be generalized so that it can be applied broadly, employing a concept from stochastic analysis called the quasi-potential. Using three classic ecological models, we demonstrate that the quasi-potential provides a useful way to quantify stability in stochastic systems. We show that the quasi-potential framework helps clarify long-standing confusion about stability in stochastic ecological systems, and we argue that ecologists should adopt it as a practical tool for analyzing these systems.

Indexed as

EcosystemModels, BiologicalModels, StatisticalStochastic ProcessesEutrophicationLakes

Identifiers

PMID27220202
PMCPMC4850755

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

None linked

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.