Evidence map›Paper›PMID 40301372›Full record

ArticleNature communications2025

The powerbend distribution provides a unified model for the species abundance distribution across animals, plants and microbes.

Yingnan Gao, Ahmed Abdullah, Martin Wu

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Yingnan GaoDepartment of Biology, University of Virginia, Charlottesville, VA, USA.ORCID http://orcid.org/0000-0002-0960-4519
Ahmed AbdullahDepartment of Biology, University of Virginia, Charlottesville, VA, USA.ORCID http://orcid.org/0000-0001-5550-9574
Martin WuDepartment of Biology, University of Virginia, Charlottesville, VA, USA. mw4yv@virginia.edu.ORCID http://orcid.org/0000-0003-3093-4077

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Remarkably, almost every ecological community investigated to date is composed of many rare species and a few abundant species. While the precise nature of this species abundance distribution is believed to reflect fundamental ecological principles underlying community assembly, ecologists have yet to identify a single model that comprehensively explains all species abundance distributions. Recent studies using large datasets have suggested that the logseries distribution best describes animal and plant communities, while the Poisson lognormal distribution is the best model for microbes, thereby challenging the notion of a unifying species abundance distribution model across the tree of life. Here, using a large dataset of ~30,000 globally distributed communities spanning animals, plants and microbes from diverse environments, we show that the powerbend distribution, predicted by a maximum information entropy-based theory of ecology, emerges as a unifying model that accurately captures species abundance distributions of all life forms, habitats and abundance scales. Our findings challenge the notion of pure neutrality, suggesting instead that community assembly is driven by a combination of random fluctuations and deterministic mechanisms shaped by interspecific trait variation.

Indexed as

Models, BiologicalPlantsAnimalsBiodiversityEcosystem

Identifiers

PMID40301372
PMCPMC12041394

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.