Evidence map›Paper›PMID 31506040›Full record

ArticleJournal of the Royal Society, Interface2019

Harnessing tipping points in complex ecological networks.

Junjie Jiang, Alan Hastings, Ying-Cheng Lai

Abstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Rate-induced tipping in complex high-dimensional ecological networks.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  7. Article
  8. The fundamental benefits of multiplexity in ecological networks.Journal of the Royal Society, Interface · 2022
    Article
  9. Article
  10. Tipping point and noise-induced transients in ecological networks.Journal of the Royal Society, Interface · 2020
    Article
  11. Article
  12. 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

3 authors.

Junjie JiangSchool of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA.
Alan HastingsDepartment of Environmental Science and Policy, University of California, One Shields Avenue, Davis, CA 95616, USA.
Ying-Cheng LaiSchool of Electrical, Computer, and Energy Engineering, Arizona State University, Tempe, AZ 85287, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Complex and nonlinear ecological networks can exhibit a tipping point at which a transition to a global extinction state occurs. Using real-world mutualistic networks of pollinators and plants as prototypical systems and taking into account biological constraints, we develop an ecologically feasible strategy to manage/control the tipping point by maintaining the abundance of a particular pollinator species at a constant level, which essentially removes the hysteresis associated with a tipping point. If conditions are changing so as to approach a tipping point, the management strategy we describe can prevent sudden drastic changes. Additionally, if the system has already moved past a tipping point, we show that a full recovery can occur for reasonable parameter changes only if there is active management of abundance, again due essentially to removal of the hysteresis. This recovery point in the aftermath of a tipping point can be predicted by a universal, two-dimensional reduced model.

Indexed as

Models, BiologicalPlantsPollinationSymbiosiscomplex networksecosystem managementmutualistic networksnonlinear dynamicsspecies recoverytipping point

Identifiers

PMID31506040
PMCPMC6769319

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.