Evidence map›Paper›PMID 40568985›Full record

ArticleThe ISME journal2025

Quantifying the contribution of the rare biosphere to natural disturbances.

Jianshu Zhao, Genevieve Brandt, Jessica L Gronniger, Zhao Wang, Jiaqian Li, Dana E Hunt, Luis M Rodriguez-R, Janet K Hatt, Konstantinos T Konstantinidis

Abstract read
In one paragraph

Article in The ISME journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

9 authors.

Jianshu ZhaoCenter for Bioinformatics and Computational Genomics, Georgia Institute of Technology, Atlanta, GA 30332, United States.ORCID 0000-0002-2586-3852
Genevieve BrandtSchool of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, United States.
Jessica L GronnigerMarine Laboratory, Duke University, Beaufort, NC 28516, United States.
Zhao WangMarine Laboratory, Duke University, Beaufort, NC 28516, United States.
Jiaqian LiMarine Laboratory, Duke University, Beaufort, NC 28516, United States.
Dana E HuntMarine Laboratory, Duke University, Beaufort, NC 28516, United States.
Luis M Rodriguez-RSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States.
Janet K HattSchool of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332, United States.
Konstantinos T KonstantinidisCenter for Bioinformatics and Computational Genomics, Georgia Institute of Technology, Atlanta, GA 30332, United States.ORCID 0000-0002-0954-4755

Funding

US National Science Foundation ICER 2033934, DEB 2224819US National Science Foundation OCE 1416673 and DEB 1831582
6 · The paper itself

Abstract

Understanding how populations respond to disturbances represents a major goal for microbial ecology. While several hypotheses have been advanced to explain microbial community compositional changes in response to disturbance, appropriate data to test these hypotheses is scarce, due to the challenges in delineating rare vs. abundant taxa and generalists vs. specialists, a prerequisite for testing the theories. Here, we operationally define these two key concepts by employing the patterns of coverage of a (target) genome by a metagenome to identify rare populations, and by borrowing the proportional similarity index from macroecology to identify generalists. We applied these concepts to time-series (field) metagenomes from the Piver's Island Coastal Observatory to establish that coastal microbial communities are resilient to major perturbations such as tropical cyclones and (uncommon) cold or warm temperature events, in part due to the response of rare populations. Therefore, these results provide support for the insurance hypothesis [i.e. the rare biosphere has the buffering capacity to mitigate the effects of disturbance]. Additionally, generalists appear to contribute proportionally more than specialists to community adaptation to perturbations like warming, supporting the disturbance-specialization hypothesis [i.e. disturbance favors generalists]. Several of these findings were also observed in replicated laboratory mesocosms that aimed to simulate disturbances such as a rain-driven washout of microbial cells and a labile organic matter release from a phytoplankton bloom. Taken together, our results advance understanding of the mechanisms governing microbial population dynamics under changing environmental conditions and have implications for ecosystem modeling.

Indexed as

EcosystemMicrobiotaMetagenomedisturbancegeneralists and specialistsmetagenomicsmetagenomics assembled genomes (MAGs)rare biosphereresilience

Identifiers

PMID40568985
PMCPMC12286922

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Registered trials

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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.