Evidence map›Paper›PMID 38818334›Full record

ArticlemLife2023

Ecosystem Microbiome Science.

Yong-Guan Zhu, Dong Zhu, Matthias C Rillig, Yunfeng Yang, Haiyan Chu, Qing-Lin Chen, Josep Penuelas, Hui-Ling Cui, Michael Gillings

Abstract read
In one paragraph

Article in mLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
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  9. mLife · 2025
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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.

Yong-Guan ZhuKey Laboratory of Urban Environment and Health, Institute of Urban Environment Chinese Academy of Sciences Xiamen China.ORCID 0000-0003-3861-8482
Dong ZhuState Key Laboratory of Urban and Regional Ecology, Research Centre for Eco-environmental Sciences Chinese Academy of Sciences Beijing China.
Matthias C RilligInstitute of Biology Freie Universität Berlin Berlin Germany.
Yunfeng YangState Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment Tsinghua University Beijing China.ORCID 0000-0001-8274-6196
Haiyan ChuState Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science Chinese Academy of Sciences Nanjing China.
Qing-Lin ChenFaculty of Veterinary and Agricultural Sciences The University of Melbourne Melbourne Victoria Australia.
Josep PenuelasCSIC, Global Ecology Unit CREAF-CSIC-UAB Bellaterra Catalonia Spain.
Hui-Ling CuiState Key Laboratory of Urban and Regional Ecology, Research Centre for Eco-environmental Sciences Chinese Academy of Sciences Beijing China.
Michael GillingsARC Centre of Excellence for Synthetic Biology, and Department of Biological Sciences Macquarie University Sydney New South Wales Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The microbiome contributes to multiple ecosystem functions and services through its interactions with a complex environment and other organisms. To date, however, most microbiome studies have been carried out on individual hosts or particular environmental compartments. This greatly limits a comprehensive understanding of the processes and functions performed by the microbiome and its dynamics at an ecosystem level. We propose that the theory and tools of ecosystem ecology be used to investigate the connectivity of microorganisms and their interactions with the biotic and abiotic environment within entire ecosystems and to examine their contributions to ecosystem services. Impacts of natural and anthropogenic stressors on ecosystems will likely cause cascading effects on the microbiome and lead to unpredictable outcomes, such as outbreaks of emerging infectious diseases or changes in mutualistic interactions. Despite enormous advances in microbial ecology, we are yet to study microbiomes of ecosystems as a whole. Doing so would establish a new framework for microbiome study: Ecosystem Microbiome Science. The advent and application of molecular and genomic technologies, together with data science and modeling, will accelerate progress in this field.

Indexed as

dynamicsecosystemglobal changeinteractionsmicrobiome

Identifiers

PMID38818334
PMCPMC10989922

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.