Evidence map›Paper›PMID 29891000›Full record

ArticleMicrobiome2018

Direct and indirect effects of a pH gradient bring insights into the mechanisms driving prokaryotic community structures.

Daniel R Lammel, Gabriel Barth, Otso Ovaskainen, Leonardo M Cruz, Josileia A Zanatta, Masahiro Ryo, Emanuel M de Souza, Fábio O Pedrosa

Open access · goldAbstract read
In one paragraph

Article in Microbiome, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed
13.4field-weighted citation impact, top 1% 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

51 citing papers in PubMed, 197 citations in OpenAlex.

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  19. Lineage-specific evolution ofApplied and environmental microbiology · 2024
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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

8 authors at 5 institutions in 4 countries.

Daniel R LammelDepartment of Biochemistry and Molecular Biology, Universidade Federal do Paraná (UFPR), Curitiba, Brazil.ORCID 0000-0002-1977-2831
Gabriel BarthABC Research Foundation, Castro, Brazil.
Otso OvaskainenDepartment of Biosciences, University of Helsinki, PO Box 65, 00014, Helsinki, Finland.
Leonardo M CruzDepartment of Biochemistry and Molecular Biology, Universidade Federal do Paraná (UFPR), Curitiba, Brazil.
Josileia A ZanattaEMBRAPA Forests, Colombo, Brazil.
Masahiro RyoFreie Universität Berlin and Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany.
Emanuel M de SouzaDepartment of Biochemistry and Molecular Biology, Universidade Federal do Paraná (UFPR), Curitiba, Brazil.
Fábio O PedrosaDepartment of Biochemistry and Molecular Biology, Universidade Federal do Paraná (UFPR), Curitiba, Brazil. fpedrosa@ufpr.br.
Universidade Federal do Paraná · BRBerlin Brandenburg Institute of Advanced Biodiversity Research · DEBrazilian Agricultural Research Corporation · BRFundação do ABC · BRUniversity of Helsinki · FI

Funding

Academy of Finland 1273253/284601/273253Norges Forskningsråd 223257
6 · The paper itself

Abstract

backgroundpH is frequently reported as the main driver for prokaryotic community structure in soils. However, pH changes are also linked to "spillover effects" on other chemical parameters (e.g., availability of Al, Fe, Mn, Zn, and Cu) and plant growth, but these indirect effects on the microbial communities are rarely investigated. Usually, pH also co-varies with some confounding factors, such as land use, soil management (e.g., tillage and chemical inputs), plant cover, and/or edapho-climatic conditions. So, a more comprehensive analysis of the direct and indirect effects of pH brings a better understanding of the mechanisms driving prokaryotic (archaeal and bacterial) community structures.

resultsWe evaluated an agricultural soil pH gradient (from 4 to 6, the typical range for tropical farms), in a liming gradient with confounding factors minimized, investigating relationships between prokaryotic communities (16S rRNA) and physical-chemical parameters (indirect effects). Correlations, hierarchical modeling of species communities (HMSC), and random forest (RF) modeling indicated that both direct and indirect effects of the pH gradient affected the prokaryotic communities. Some OTUs were more affected by the pH changes (e.g., some Actinobacteria), while others were more affected by the indirect pH effects (e.g., some Proteobacteria). HMSC detected a phylogenetic signal related to the effects. Both HMSC and RF indicated that the main indirect effect was the pH changes on the availability of some elements (e.g., Al, Fe, and Cu), and secondarily, effects on plant growth and nutrient cycling also affected the OTUs. Additionally, we found that some of the OTUs that responded to pH also correlated with CO

conclusionsOur results indicate that there are two distinct pH-related mechanisms driving prokaryotic community structures, the direct effect and "spillover effects" of pH (indirect effects). Moreover, the indirect effects are highly relevant for some OTUs and consequently for the community structure; therefore, it is a mechanism that should be further investigated in microbial ecology.

Indexed as

ArchaeaBacteriaBase SequenceBrazilEcological and Environmental PhenomenaGreenhouse GasesHigh-Throughput Nucleotide SequencingHydrogen-Ion ConcentrationProton-Motive ForceRNA, Ribosomal, 16SSoilSoil MicrobiologyGreenhouse GasesRNA, Ribosomal, 16SSoil16S rRNAArchaeaBacteriaIllumina sequencingMicrobial ecologypHSoil chemistrySub-tropical soil

Identifiers

PMID29891000
PMCPMC5996553
OpenAlexW2807871022

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.