Evidence map›Paper›PMID 35484221›Full record

ArticleNature ecology & evolution2022

Complexity-stability trade-off in empirical microbial ecosystems.

Yogev Yonatan, Guy Amit, Jonathan Friedman, Amir Bashan

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In one paragraph

Article in Nature ecology & evolution, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yogev Yonatan *Physics Department, Bar-Ilan University, Ramat-Gan, Israel.
Guy Amit *Physics Department, Bar-Ilan University, Ramat-Gan, Israel.ORCID http://orcid.org/0000-0001-8840-8809
Jonathan FriedmanDepartment of Plant Pathology and Microbiology, The Hebrew University of Jerusalem, Rehovot, Israel.ORCID http://orcid.org/0000-0001-8476-8030
Amir BashanPhysics Department, Bar-Ilan University, Ramat-Gan, Israel. amir.bashan@biu.ac.il.ORCID http://orcid.org/0000-0002-4502-3850

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

May's stability theory, which holds that large ecosystems can be stable up to a critical level of complexity, a product of the number of resident species and the intensity of their interactions, has been a central paradigm in theoretical ecology. So far, however, empirically demonstrating this theory in real ecological systems has been a long-standing challenge with inconsistent results. Especially, it is unknown whether this theory is pertinent in the rich and complex communities of natural microbiomes, mainly due to the challenge of reliably reconstructing such large ecological interaction networks. Here we introduce a computational framework for estimating an ecosystem's complexity without relying on a priori knowledge of its underlying interaction network. By applying this method to human-associated microbial communities from different body sites and sponge-associated microbial communities from different geographical locations, we found that in both cases the communities display a pronounced trade-off between the number of species and their effective connectance. These results suggest that natural microbiomes are shaped by stability constraints, which limit their complexity.

Indexed as

MicrobiotaModels, BiologicalHumans

Identifiers

What OpenQuestion holds

Textmetadata
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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.