Evidence map›Paper›PMID 41267624›Full record

ArticleEnvironmental microbiology reports2025

Eutrophication Reshapes Microbial Communities and Life-History Strategies in the Riverine Ecosystems.

Haizhou Li, Jing Fu, Xiangyu Fan, Zhiwei He, Yuekai Wang, Shanshan Yang, Jiawang Wu, Li Wu, Jin Zhou

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Environmental microbiology reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

9 authors.

Haizhou LiEast China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China.
Jing FuEast China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China.
Xiangyu FanDepartment of Molecular and Cellular Biology, University of California, Davis, California, USA.
Zhiwei HeState Key Laboratory of Marine Geology, Tongji University, Shanghai, China.
Yuekai WangEast China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China.
Shanshan YangCollege of Marine Science and Technology, China University of Geosciences, Wuhan, China.
Jiawang WuSchool of Marine Sciences, Sun Yat-Sen University, Guangzhou, China.
Li WuLaboratory for Coastal Ocean Variation and Disaster Prediction, College of Ocean and Meteorology, Guangdong Ocean University, Zhanjiang, China.
Jin ZhouEast China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Shanghai, China.

Funding

Central Public-Interest Scientific Institution Basal Research Fund, Chinese Academy of Fishery Sciences 2024QT03Key Program of National Natural Science Foundation of China 91428207National Key Basic Research Program of China (2012CB417300)Youth Program of National Natural Science Foundation of China 32100081
6 · The paper itself

Abstract

Rivers are increasingly affected by human activities, leading to widespread eutrophication. However, the responses of riverine microbiomes to eutrophication remain poorly understood. In this study, we compared microbiomes between eutrophic urban rivers (UR) and relatively undisturbed natural rivers (NR) to elucidate how eutrophication influences community structures, assembly processes, functions and life-history strategies. Amplicon and metagenomic sequencing revealed that eutrophication substantially enhanced microbial abundance and diversity in riverine ecosystems, with UR harbouring a higher proportion of fast-growing, nitrogen-transforming and antibiotic-resistant taxa. Neutral and null model analyses further revealed that, while stochastic processes predominantly shaped communities in NR, deterministic environmental selection exerted stronger control under eutrophic conditions in UR. Correspondingly, microbial communities in UR exhibited higher 16S rRNA gene copy numbers (median 4.69 vs. 4.28), stronger codon usage bias (0.0209 vs. 0.0204), greater predicted growth rates (0.2664 vs. 0.1567 h

Indexed as

BacteriaEutrophicationMicrobiotaRiversEcosystemMetagenomicsPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16Secological modellife‐history strategiesmicrobiomesriverurbanisation

Identifiers

PMID41267624
PMCPMC12635496

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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.