Evidence map›Paper›PMID 40771677›Full record

ArticleFrontiers in microbiology2025

Successional patterns of microbial communities across various stages of leaf litter decomposition in poplar plantations.

Shuang Hu, Bao-Teng Wang, Taihua Li, Su Bu, Chun-Zhi Jin, Long Jin, Hong-Hua Ruan, Kee-Sun Shin, Feng-Jie Jin

Abstract read
In one paragraph

Article in Frontiers in microbiology, 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. Article
  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.

Shuang HuCollege of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.
Bao-Teng WangCollege of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.
Taihua LiCollege of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.
Su BuCollege of Life Science, Nanjing Forestry University, Nanjing, China.
Chun-Zhi JinKorea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea.
Long JinCollege of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.
Hong-Hua RuanCollege of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.
Kee-Sun ShinKorea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea.
Feng-Jie JinCollege of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Litter decomposition drives nutrient cycling in terrestrial ecosystems, yet the dynamics of phyllosphere microbial communities during this process remain poorly understood. Poplar leaf litter decomposition is particularly critical due to its widespread plantation use. While prior studies highlight the roles of microbes in decomposition, stage-specific community succession patterns and their driving factors are underexplored. We hypothesize that microbial structure and function correlate with litter nutrient dynamics. This work advances mechanistic insights into poplar litter decomposition and informs sustainable plantation management. Methods: Poplar leaf litter was sampled periodically during a 342-day decomposition period. DNA was extracted for 16S rRNA gene (bacteria) and ITS region (fungi) high-throughput sequencing. Microbial diversity, composition, and co-occurrence networks were analyzed using QIIME2 and Gephi. Litter quality was measured via elemental analysis and spectrophotometry. Canonical Correlation Analysis (CCA) was used to assess relationships between microbial communities and environmental factors. Results: The microbial community structure and composition exhibited significant differences at both the class and genus levels throughout the entire decomposition process. Specifically, the dominant fungal taxa, Dothideomycetes, was partially replaced by Sordariomycetes, Tremellomycetes and Leotiomycetes as degradation progressed. Meanwhile, Actinobacteria, Alphaproteobacteria, and Gammaproteobacteria dominated the bacterial communities throughout the entire degradation period, while the abundance of Gammaproteobacteria decreased at later stage and Actinobacteria peaked at t4 stage. Co-correlation networks revealed that the bacterial community had a higher average clustering coefficient and shorter average path lengths compared to fungi, suggesting greater functional diversity and resilience against external disturbances. With the decomposition of leaf litter, the total N content increased gradually, while other nutrients (C, P, K, cellulose and hemicellulose) decreased progressively. Litter characteristics had significant effects on microbial community structure: C/N, TK and residual hemicellulose (RH) were the primary driving factors affecting fungal community structure, whereas bacterial community structure was influenced by TK, RH, residual cellulose (RC) and lignin contents. Conclusion: Overall, the decomposition of poplar litter is a complex process accompanied by dynamic succession of phyllosphere microbial communities. These results provide insights into the decomposition mechanisms of poplar leaf litter and offer a scientific basis for enhancing nutrient conversion efficiency and productivity of poplar plantations.

Indexed as

chemical propertylitter decompositionmicrobial communityphyllospheric microorganismspoplar litter

Identifiers

PMID40771677
PMCPMC12325270

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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.