Evidence map›Paper›PMID 31391302›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2019

A general framework for quantitatively assessing ecological stochasticity.

Daliang Ning, Ye Deng, James M Tiedje, Jizhong Zhou

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 344 papers.

0numbers the graph read from it
0cells of the map it votes in
344citing 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

344 citing papers in PubMed.

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  16. Plant influence shapesMicrobiology spectrum · 2026
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  19. Estivation Strategies of Invasive SnailEcology and evolution · 2026
    Article
  20. Article

284 more citing papers are in PubMed but not listed here.

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.

Daliang NingInstitute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019.ORCID 0000-0002-3368-5988
Ye DengInstitute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019.
James M TiedjeCenter for Microbial Ecology, Michigan State University, East Lansing, MI 48824; tiedjej@msu.edu jzhou@ou.edu.ORCID 0000-0002-8992-6218
Jizhong ZhouInstitute for Environmental Genomics, Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK 73019; tiedjej@msu.edu jzhou@ou.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the community assembly mechanisms controlling biodiversity patterns is a central issue in ecology. Although it is generally accepted that both deterministic and stochastic processes play important roles in community assembly, quantifying their relative importance is challenging. Here we propose a general mathematical framework to quantify ecological stochasticity under different situations in which deterministic factors drive the communities more similar or dissimilar than null expectation. An index, normalized stochasticity ratio (

Indexed as

AlgorithmsEcosystemModels, BiologicalStochastic Processescommunity assemblymicrobial ecologystochasticity

Identifiers

PMID31391302
PMCPMC6708315

What OpenQuestion holds

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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.