Evidence map›Paper›PMID 37884812›Full record

ArticleJournal of mathematical biology2023

Mathematical bounds on Shannon entropy given the abundance of the ith most abundant taxon.

Maike L Morrison, Noah A Rosenberg

Abstract read
In one paragraph

Article in Journal of mathematical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Mathematical bounds on rTheoretical population biology · 2025
    Article
  4. Article
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

2 authors.

Maike L MorrisonDepartment of Biology, Stanford University, Stanford, CA, 94305, USA. maikem@stanford.edu.ORCID 0000-0003-0430-1401
Noah A RosenbergDepartment of Biology, Stanford University, Stanford, CA, 94305, USA.ORCID 0000-0002-1829-8664

Funding

Population genetics for large-scale sequencing studies of diverse populationsR01HG005855 · NHGRI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Noah Rosenberg, Paul A Scheet · 2010 to 2026
$5.8M
NHGRI NIH HHS R01 HG005855
6 · The paper itself

Abstract

The measurement of diversity is a central component of studies in ecology and evolution, with broad uses spanning multiple biological scales. Studies of diversity conducted in population genetics and ecology make use of analogous concepts and even employ equivalent mathematical formulas. For the Shannon entropy statistic, recent developments in the mathematics of diversity in population genetics have produced mathematical constraints on the statistic in relation to the frequency of the most frequent allele. These results have characterized the ways in which standard measures depend on the highest-frequency class in a discrete probability distribution. Here, we extend mathematical constraints on the Shannon entropy in relation to entries in specific positions in a vector of species abundances, listed in decreasing order. We illustrate the new mathematical results using abundance data from examples involving coral reefs and sponge microbiomes. The new results update the understanding of the relationship of a standard measure to the abundance vectors from which it is calculated, potentially contributing to improved interpretation of numerical measurements of biodiversity.

Indexed as

EcologyGenetics, PopulationBiodiversityMathematicsProbabilityBiodiversityDiversity indicesMajorizationShannon entropySpecies richness

Identifiers

PMID37884812
PMCPMC10603011

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.