Evidence map›Paper›PMID 27935587›Full record

ArticleThe ISME journal2017

A family of interaction-adjusted indices of community similarity.

Thomas Sebastian Benedikt Schmidt, João Frederico Matias Rodrigues, Christian von Mering

Abstract read
In one paragraph

Article in The ISME journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

23 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

3 authors.

Thomas Sebastian Benedikt SchmidtInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zürich, Switzerland.ORCID 0000-0001-8587-4177
João Frederico Matias RodriguesInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zürich, Switzerland.
Christian von MeringInstitute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zürich, Switzerland.ORCID 0000-0001-7734-9102

Funding

European Research Council 242870
6 · The paper itself

Abstract

Interactions between taxa are essential drivers of ecological community structure and dynamics, but they are not taken into account by traditional indices of β diversity. In this study, we propose a novel family of indices that quantify community similarity in the context of taxa interaction networks. Using publicly available datasets, we assessed the performance of two specific indices that are Taxa INteraction-Adjusted (TINA, based on taxa co-occurrence networks), and Phylogenetic INteraction-Adjusted (PINA, based on phylogenetic similarities). TINA and PINA outperformed traditional indices when partitioning human-associated microbial communities according to habitat, even for extremely downsampled datasets, and when organising ocean micro-eukaryotic plankton diversity according to geographical and physicochemical gradients. We argue that interaction-adjusted indices capture novel aspects of diversity outside the scope of traditional approaches, highlighting the biological significance of ecological association networks in the interpretation of community similarity.

Indexed as

BiotaBacteriaComputational BiologyHumansModels, BiologicalOceans and SeasPhylogenySoil MicrobiologyWater Microbiology

Identifiers

PMID27935587
PMCPMC5322292

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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.