Evidence map›Paper›PMID 23575374›Full record

SynthesisThe ISME journal2013

A meta-analysis of changes in bacterial and archaeal communities with time.

Ashley Shade, J Gregory Caporaso, Jo Handelsman, Rob Knight, Noah Fierer

Abstract readMeta-Analysis
In one paragraph

Synthesis in The ISME journal, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 169 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
169citing papers in PubMed, 3 pooled it
–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

169 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  4. Article
  5. Bioenergy Cropping Reduces the Spatiotemporal Scaling of Soil Bacterial Biodiversity.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
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109 more citing papers are in PubMed but not listed here.

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

5 authors.

Ashley ShadeDepartment of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA.
J Gregory Caporaso
Jo Handelsman
Rob Knight
Noah Fierer

Funding

Howard Hughes Medical Institute
6 · The paper itself

Abstract

Ecologists have long studied the temporal dynamics of plant and animal communities with much less attention paid to the temporal dynamics exhibited by microbial communities. As a result, we do not know if overarching temporal trends exist for microbial communities or if changes in microbial communities are generally predictable with time. Using microbial time series assessed via high-throughput sequencing, we conducted a meta-analysis of temporal dynamics in microbial communities, including 76 sites representing air, aquatic, soil, brewery wastewater treatment, human- and plant-associated microbial biomes. We found that temporal variability in both within- and between-community diversity was consistent among microbial communities from similar environments. Community structure changed systematically with time in less than half of the cases, and the highest rates of change were observed within ranges of 1 day to 1 month for all communities examined. Microbial communities exhibited species-time relationships (STRs), which describe the accumulation of new taxa to a community, similar to those observed previously for plant and animal communities, suggesting that STRs are remarkably consistent across a broad range of taxa. These results highlight that a continued integration of microbial ecology into the broader field of ecology will provide new insight into the temporal patterns of microbial and 'macro'-bial communities alike.

Indexed as

Bacterial Physiological PhenomenaBiodiversityEcosystemEnvironmental MicrobiologyAnimalsArchaeaBacteriaHumansRNA, Ribosomal, 16STime FactorsRNA, Ribosomal, 16S

Identifiers

PMID23575374
PMCPMC3721121

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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.