Evidence map›Paper›PMID 38091288›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2023

Rate-induced tipping in complex high-dimensional ecological networks.

Shirin Panahi, Younghae Do, Alan Hastings, Ying-Cheng Lai

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Shirin PanahiSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287.ORCID 0000-0003-3436-3929
Younghae DoDepartment of Mathematics, Nonlinear Dynamics Mathematical Application Center, Kyungpook National University, Daegu 41566, Republic of Korea.
Alan HastingsDepartment of Environmental Science and Policy, University of California, Davis, CA 95616.ORCID 0000-0002-0717-8026
Ying-Cheng LaiSchool of Electrical, Computer and Energy Engineering, Arizona State University, Tempe, AZ 85287.ORCID 0000-0002-0723-733X

Funding

DOD | USN | ONR | Office of Naval Research Global (ONRG) N00014-21-1-2323National Research Foundation of Korea (NRF) NRF-2022R1A2C3011711National Research Foundation of Korea (NRF) NRF-2022R1A5A1033624
6 · The paper itself

Abstract

In an ecosystem, environmental changes as a result of natural and human processes can cause some key parameters of the system to change with time. Depending on how fast such a parameter changes, a tipping point can occur. Existing works on rate-induced tipping, or R-tipping, offered a theoretical way to study this phenomenon but from a local dynamical point of view, revealing, e.g., the existence of a critical rate for some specific initial condition above which a tipping point will occur. As ecosystems are subject to constant disturbances and can drift away from their equilibrium point, it is necessary to study R-tipping from a global perspective in terms of the initial conditions in the entire relevant phase space region. In particular, we introduce the notion of the probability of R-tipping defined for initial conditions taken from the whole relevant phase space. Using a number of real-world, complex mutualistic networks as a paradigm, we find a scaling law between this probability and the rate of parameter change and provide a geometric theory to explain the law. The real-world implication is that even a slow parameter change can lead to a system collapse with catastrophic consequences. In fact, to mitigate the environmental changes by merely slowing down the parameter drift may not always be effective: Only when the rate of parameter change is reduced to practically zero would the tipping be avoided. Our global dynamics approach offers a more complete and physically meaningful way to understand the important phenomenon of R-tipping.

Indexed as

mutualistic networksnonlinear dynamicsrate-induced tippingscaling lawtipping point

Identifiers

PMID38091288
PMCPMC10743502

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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.