Evidence map›Paper›PMID 31346503›Full record

ArticlePeerJ2019

Microbial regulation of soil carbon properties under nitrogen addition and plant inputs removal.

Ran Wu, Xiaoqin Cheng, Wensong Zhou, Hairong Han

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2019. 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
1.6field-weighted citation impact, top 17% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Ran WuBeijing Key Laboratory of Forest Resources and Ecosystem Processes, Beijing Forestry University, Beijing, China.
Xiaoqin ChengBeijing Key Laboratory of Forest Resources and Ecosystem Processes, Beijing Forestry University, Beijing, China.
Wensong ZhouBeijing Key Laboratory of Forest Resources and Ecosystem Processes, Beijing Forestry University, Beijing, China.
Hairong HanBeijing Key Laboratory of Forest Resources and Ecosystem Processes, Beijing Forestry University, Beijing, China.
Beijing Forestry University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSoil microbial communities and their associated enzyme activities play key roles in carbon cycling in terrestrial ecosystems. Soil microbial communities are sensitive to resource availability, but the mechanisms of microbial regulation have not been thoroughly investigated. Here, we tested the mechanistic relationships between microbial responses and multiple interacting resources.

methodsWe examined soil carbon properties, soil microbial community structure and carbon-related functions under nitrogen addition and plant inputs removal (litter removal (NL), root trench and litter removal (NRL)) in a pure

resultsWe found that nitrogen addition affected the soil microbial community structure, and that microbial biomass increased significantly once 100 kg ha

conclusionsThis study showed that nitrogen addition and plant inputs removal could alter soil enzyme activities and further affect soil carbon turnover via microbial regulation. The increase in soil microbial biomass and the microbial regulation of soil carbon both need to be considered when developing effective sustainable forest management practices for northern China. Moreover, further studies are also needed to exactly understand how the complex interaction between the plant and below-ground processes affects the soil microbial community structure.

Indexed as

Nitrogen additionPlant inputs removalRegulationSoil carbon propertiesSoil enzymeSoil microorganisms

Identifiers

PMID31346503
PMCPMC6642627
OpenAlexW2957290657

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.