Evidence map›Paper›PMID 25147550›Full record

ArticleFrontiers in microbiology2014

Potential drivers of microbial community structure and function in Arctic spring snow.

Lorrie Maccario, Timothy M Vogel, Catherine Larose

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 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

3 authors.

Lorrie MaccarioCNRS UMR 5005, Environmental Microbial Genomics, Laboratoire Ampère, École Centrale de Lyon, Université de Lyon Ecully, France.
Timothy M VogelCNRS UMR 5005, Environmental Microbial Genomics, Laboratoire Ampère, École Centrale de Lyon, Université de Lyon Ecully, France.
Catherine LaroseCNRS UMR 5005, Environmental Microbial Genomics, Laboratoire Ampère, École Centrale de Lyon, Université de Lyon Ecully, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Arctic seasonal snowpack can extend at times over a third of the Earth's land surface. This chemically dynamic environment interacts constantly with different environmental compartments such as atmosphere, soil and meltwater, and thus, strongly influences the entire biosphere. However, the microbial community associated with this habitat remains poorly understood. Our objective was to investigate the functional capacities, diversity and dynamics of the microorganisms in snow and to test the hypothesis that their functional signature reflects the snow environment. We applied a metagenomic approach to nine snow samples taken over 2 months during the spring season. Fungi, Bacteroidetes, and Proteobacteria were predominant in metagenomic datasets and changes in community structure were apparent throughout the field season. Functional data that strongly correlated with chemical parameters like mercury or nitrogen species supported that this variation could be explained by fluctuations in environmental conditions. Through inter-environmental comparisons we examined potential drivers of snowpack microbial community functioning. Known cold adaptations were detected in all compared environments without any apparent differences in their relative abundance, implying that adaptive mechanisms related to environmental factors other than temperature may play a role in defining the snow microbial community. Photochemical reactions and oxidative stress seem to be decisive parameters in structuring microbial communities inside Arctic snowpacks.

Indexed as

Arcticcryospheremetagenomicmicrobial adaptationsnowpack

Identifiers

PMID25147550
PMCPMC4124603

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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.