Evidence map›Paper›PMID 37396368›Full record

ArticleFrontiers in microbiology2023

Microbial mats as model to decipher climate change effect on microbial communities through a mesocosm study.

C Mazière, R Duran, C Dupuy, C Cravo-Laureau

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2023. 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
  3. 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

4 authors.

C MazièreUniversité de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IPREM UMR 525-Bât. IBEAS, BP1155, Pau, France.
R DuranUniversité de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IPREM UMR 525-Bât. IBEAS, BP1155, Pau, France.
C DupuyLa Rochelle Université, CNRS, UMR 7266 LIENSs (Littoral Environnement et Sociétés)-2, rue Olympe de Gouges, Bât. ILE, La Rochelle, France.
C Cravo-LaureauUniversité de Pau et des Pays de l'Adour, E2S UPPA, CNRS, IPREM UMR 525-Bât. IBEAS, BP1155, Pau, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marine environments are expected to be one of the most affected ecosystems by climate change, notably with increasing ocean temperature and ocean acidification. In marine environments, microbial communities provide important ecosystem services ensuring biogeochemical cycles. They are threatened by the modification of environmental parameters induced by climate change that, in turn, affect their activities. Microbial mats, ensuring important ecosystem services in coastal areas, are well-organized communities of diverse microorganisms representing accurate microbial models. It is hypothesized that their microbial diversity and metabolic versatility will reveal various adaptation strategies in response to climate change. Thus, understanding how climate change affects microbial mats will provide valuable information on microbial behaviour and functioning in changed environment. Experimental ecology, based on mesocosm approaches, provides the opportunity to control physical-chemical parameters, as close as possible to those observed in the environment. The exposure of microbial mats to physical-chemical conditions mimicking the climate change predictions will help to decipher the modification of the microbial community structure and function in response to it. Here, we present how to expose microbial mats, following a mesocosm approach, to study the impact of climate change on microbial community.

Indexed as

experimental ecologyglobal changemesocosmsmicrobial matocean acidificationocean warming

Identifiers

PMID37396368
PMCPMC10308941

What OpenQuestion holds

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LicenceCC BY
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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.