Evidence map›Paper›PMID 35814650›Full record

ArticleFrontiers in microbiology2022

Variations in Soil Nutrient Dynamics and Bacterial Communities After the Conversion of Forests to Long-Term Tea Monoculture Systems.

Heng Gui, Lichao Fan, Donghui Wang, Peng Yan, Xin Li, Yinghua Pang, Liping Zhang, Kazem Zamanian, Lingling Shi, Jianchu Xu and 1 more

Open access · goldAbstract 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 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
2.4field-weighted citation impact, top 12% of its field
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

11 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
  2. Linking topography, soil physicochemical traits and bacterial community dynamics in a managed tea landscape.International microbiology : the official journal of the Spanish Society for Microbiology · 2026
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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

11 authors at 5 institutions in 2 countries.

Heng GuiTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Lichao FanTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Donghui WangTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Peng YanTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Xin LiTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Yinghua PangBureau of Agriculture and Rural Affairs of the Yuhang District, Hangzhou, China.
Liping ZhangTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Kazem ZamanianDepartment of Soil Science of Temperate Ecosystems, University of Göttingen, Göttingen, Germany.
Lingling ShiDepartment of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
Jianchu XuDepartment of Economic Plants and Biotechnology, Yunnan Key Laboratory for Wild Plant Resources, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, China.
Wenyan HanTea Research Institute, Chinese Academy of Agricultural Sciences, Hangzhou, China.
Tea Research Institute · CNKunming Institute of Botany · CNChinese Academy of Agricultural Sciences · CNMinistry of Agriculture and Rural Affairs · CNUniversity of Göttingen · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The soil microbial community is a key indicator to evaluate the soil health and productivities in agricultural ecosystems. Monoculture and conversions of forests to tea plantations have been widely applied in tea plantation globally, but long-term monoculture of tea plantation could lead to soil degradation and yield decline. Understanding how long-term monoculture systems influence the soil health and ecosystem functions in tea plantation is of great importance for soil environment management. In this study, through the comparison of three independent tea plantations across eastern China composed of varying stand ages (from 3 to 90 years after conversion from forest), we found that long-term tea monoculture led to significant increases in soil total organic carbon (TOC) and microbial nitrogen (MBN). Additionally, the structure, function, and co-occurrence network of soil bacterial communities were investigated by pyrosequencing 16S rRNA genes. The pyrosequencing analysis revealed that the structures and functions of soil bacterial communities were significantly affected by different stand ages, but sampling sites and land-use conversion (from forest to tea plantation) had stronger effects than stand age on the diversity and structure of soil bacterial communities. Soil bacterial diversity can be improved with increasing stand ages in tea plantation. Further RDA analysis revealed that the C and N availability improvement in tea plantation soils led to the variation of structure and function in soil bacterial communities. Moreover, co-occurrence network analysis of soil bacterial communities also demonstrated that interactions among soil bacteria taxa were strengthened with increasing stand age. Our findings suggest that long-term monoculture with proper managements could be beneficial to soil ecosystems by increasing the C and N content and strengthening bacterial associations in tea plantations. Overall, this study provides a comprehensive understanding of the impact of land-use change and long-term monoculture stand age on soil environments in tea plantation.

Indexed as

co-occurrence networkmonoculture systemnutrient availabilitypyrosequencingtea production

Identifiers

PMID35814650
PMCPMC9263701
OpenAlexW4283390134

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.