Evidence map›Paper›PMID 30061665›Full record

ArticleNature communications2018

Asymmetric migration decreases stability but increases resilience in a heterogeneous metapopulation.

Anurag Limdi, Alfonso Pérez-Escudero, Aming Li, Jeff Gore

Abstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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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.

Anurag LimdiPhysics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0002-4891-8254
Alfonso Pérez-EscuderoPhysics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0002-4782-6139
Aming LiPhysics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.ORCID http://orcid.org/0000-0003-4045-8721
Jeff GorePhysics of Living Systems, Department of Physics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. gore@mit.edu.ORCID http://orcid.org/0000-0003-4583-8555

Funding

Early warning indicators of tipping points in biological systemsDP2AG044279 · NIA · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GORE, JEFF · 2012 to 2012
$2.3M
DOD | Defense Advanced Research Projects Agency (DARPA) HR0011-15-C-0091NIA NIH HHS DP2 AG044279
6 · The paper itself

Abstract

Many natural populations are spatially distributed, forming a network of subpopulations linked by migration. Migration patterns are often asymmetric and heterogeneous, with important consequences on the ecology and evolution of the species. Here we investigate experimentally how asymmetric migration and heterogeneous structure affect a simple metapopulation of budding yeast, formed by one strain that produces a public good and a non-producer strain that benefits from it. We study metapopulations with star topology and asymmetric migration, finding that all their subpopulations have a higher fraction of producers than isolated populations. Furthermore, the metapopulations have lower tolerance to challenging environments but higher resilience to transient perturbations. This apparent paradox occurs because tolerance to a constant challenge depends on the weakest subpopulations of the network, while resilience to a transient perturbation depends on the strongest ones.

Indexed as

EcologyCell WallComputer SimulationEcosystemModels, BiologicalMutationSaccharomyces cerevisiaeSucroseTime FactorsSucrose

Identifiers

PMID30061665
PMCPMC6065393

What OpenQuestion holds

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LicenceCC BY
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.