Evidence map›Paper›PMID 30280033›Full record

ArticlePeerJ2018

High-throughput metabarcoding reveals the effect of physicochemical soil properties on soil and litter biodiversity and community turnover across Amazonia.

Camila D Ritter, Alexander Zizka, Fabian Roger, Hanna Tuomisto, Christopher Barnes, R Henrik Nilsson, Alexandre Antonelli

Open access · goldAbstract read
In one paragraph

Article in PeerJ, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
3.5field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 27 citations in OpenAlex.

  1. Review
  2. Ciliate diversity in rodrigo de freitas lagoon (Rio de Janeiro, Brazil) from an integrative standpoint.Brazilian journal of microbiology : [publication of the Brazilian Society for 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

7 authors at 5 institutions in 4 countries.

Camila D RitterGothenburg Global Biodiversity Centre, Göteborg, Sweden.
Alexander ZizkaGothenburg Global Biodiversity Centre, Göteborg, Sweden.
Fabian RogerCentre for Environmental and Climate Research, Lund University, Lund, Sweden.
Hanna TuomistoDepartment of Biology, University of Turku, Turku, Finland.
Christopher BarnesNatural History Museum of Denmark, University of Copenhagen, Denmark, Copenhagen, Denmark.
R Henrik Nilsson *Gothenburg Global Biodiversity Centre, Göteborg, Sweden.
Alexandre Antonelli *Gothenburg Global Biodiversity Centre, Göteborg, Sweden.
Göteborgs Stads · SEUniversity of Gothenburg · SELund University · SENatural History Museum Aarhus · DKUniversity of Turku · FI

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKnowledge on the globally outstanding Amazonian biodiversity and its environmental determinants stems almost exclusively from aboveground organisms, notably plants. In contrast, the environmental factors and habitat preferences that drive diversity patterns for micro-organisms in the ground remain elusive, despite the fact that micro-organisms constitute the overwhelming majority of life forms in any given location, in terms of both diversity and abundance. Here we address how the diversity and community turnover of operational taxonomic units (OTU) of organisms in soil and litter respond to soil physicochemical properties; whether OTU diversities and community composition in soil and litter are correlated with each other; and whether they respond in a similar way to soil properties.

methodsWe used recently inferred OTUs from high-throughput metabarcoding of the 16S (prokaryotes) and 18S (eukaryotes) genes to estimate OTU diversity (OTU richness and effective number of OTUs) and community composition for prokaryotes and eukaryotes in soil and litter across four localities in Brazilian Amazonia. All analyses were run separately for prokaryote and eukaryote OTUs, and for each group using both presence-absence and abundance data. Combining these with novel data on soil chemical and physical properties, we identify abiotic correlates of soil and litter organism diversity and community structure using regression, ordination, and variance partitioning analysis.

resultsSoil organic carbon content was the strongest factor explaining OTU diversity (negative correlation) and pH was the strongest factor explaining community turnover for prokaryotes and eukaryotes in both soil and litter. We found significant effects also for other soil variables, including both chemical and physical properties. The correlation between OTU diversity in litter and in soil was non-significant for eukaryotes and weak for prokaryotes. The community compositions of both prokaryotes and eukaryotes were more separated among habitat types (terra-firme, várzea, igapó and campina) than between substrates (soil and litter). DISCUSSION: In spite of the limited sampling (four localities, 39 plots), our results provide a broad-scale view of the physical and chemical correlations of soil and litter biodiversity in a longitudinal transect across the world's largest rainforest. Our methods help to understand links between soil properties, OTU diversity patterns, and community composition and turnover. The lack of strong correlation between OTU diversity in litter and in soil suggests independence of diversity drives of these substrates and highlights the importance of including both measures in biodiversity assessments. Massive sequencing of soil and litter samples holds the potential to complement traditional biological inventories in advancing our understanding of the factors affecting tropical diversity.

Indexed as

BrazilEukaryotesOperational Taxonomic Units (OTUs)ProkaryotesRainforestSoil microorganisms

Identifiers

PMID30280033
PMCPMC6161700
OpenAlexW2885114920

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.