Evidence map›Paper›PMID 41727183›Full record

ReviewiScience2026

Marine synthetic ecology: From microbial communities to ecosystems.

Ruilin Su, Xiaoli Yu, Mingyang Niu, Kun Wu, Hongbin Liu, Qingyun Yan, Zhili He

Abstract readReview
In one paragraph

Review in iScience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ruilin SuMarine Synthetic Ecology Research Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
Xiaoli YuMarine Synthetic Ecology Research Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
Mingyang NiuMarine Synthetic Ecology Research Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
Kun WuMarine Synthetic Ecology Research Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
Hongbin LiuDepartment of Ocean Science, Hong Kong University of Science and Technology, Hong Kong 999077, China.
Qingyun YanMarine Synthetic Ecology Research Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
Zhili HeMarine Synthetic Ecology Research Center, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marine ecosystems are vital for global ecological functions and human health but face escalating threats from both anthropogenic activities and global climate change. Marine microorganisms, comprising over two-thirds of the marine biomass, play essential roles in biogeochemical cycling of elements and food webs. Synthetic ecology aims to understand ecological theories and provide nature-based solutions to emerging ecological and environmental problems. Here, we first propose a framework, the resource-design-verification-evolution-application (RDVEA) model for marine synthetic ecology studies, aiming to understand marine ecological theories, design and construct marine-specific synthetic communities, and optimize their functionality toward marine environmental applications. Synthetic ecosystems may target food web interactions, greenhouse gas mitigation, and carbon sequestration enhancement in the future marine environment.

Indexed as

ecologyenvironmental sciencemicrobiology

Identifiers

PMID41727183
PMCPMC12918165

What OpenQuestion holds

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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.