Evidence map›Paper›PMID 36425041›Full record

ArticleFrontiers in microbiology2022

Litter mixing promoted decomposition rate through increasing diversities of phyllosphere microbial communities.

Jiaying Liu, Changjun Ding, Weixi Zhang, Yawei Wei, Yongbin Zhou, Wenxu Zhu

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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

6 authors.

Jiaying LiuCollege of Forestry, Shenyang Agriculture University, Shenyang, China.
Changjun DingState Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China.
Weixi ZhangState Key Laboratory of Tree Genetics and Breeding, Research Institute of Forestry, Chinese Academy of Forestry, Beijing, China.
Yawei WeiCollege of Forestry, Shenyang Agriculture University, Shenyang, China.
Yongbin ZhouCollege of Forestry, Shenyang Agriculture University, Shenyang, China.
Wenxu ZhuCollege of Forestry, Shenyang Agriculture University, Shenyang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Decomposition of forest litter is an essential process for returning nutrients to the soil, which is crucial for preserving soil fertility and fostering the regular biological cycle and nutrient balance of the forest ecosystem. About 70% of the land-based forest litter is made up primarily of leaf litter. However, research on the complex effects and key determinants of leaf litter decomposition is still lacking. In this study, we examined the characteristics of nutrient release and microbial diversity structure during the decomposition of three types of litter in arid and semi-arid regions using 16S rRNA and ITS sequencing technology as well as nutrient content determination. It was revealed that the nutrient content and rate of decomposition of mixed litters were significantly different from those of single species. Following litter mixing, the richness and diversity of the microbial community on leaves significantly increased. It was determined that there was a significant correlation between bacterial diversity and content (Total N, Total P, N/P, and C/P). This study provided a theoretical framework for investigating the decomposition mechanism of mixed litters by revealing the microbial mechanism of mixed decomposition of litters from the microbial community and nutrient levels.

Indexed as

litter leafmicrobial communitymixed decompositionPinus sylvestris var. mongolicaPopulus × canadensis Moench

Identifiers

PMID36425041
PMCPMC9678933

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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.