Evidence map›Paper›PMID 39116044›Full record

ArticlePLoS biology2024

Diatom abundance in the polar oceans is predicted by genome size.

Wade R Roberts, Adam M Siepielski, Andrew J Alverson

Abstract read
In one paragraph

Article in PLoS biology, 2024. 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
–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

9 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.

Wade R RobertsDepartment of Biological Sciences, University of Arkansas, Fayetteville, Arkansas, United States of America.ORCID 0000-0002-5100-7558
Adam M SiepielskiDepartment of Biological Sciences, University of Arkansas, Fayetteville, Arkansas, United States of America.
Andrew J AlversonDepartment of Biological Sciences, University of Arkansas, Fayetteville, Arkansas, United States of America.

Funding

National Science Foundation DEB 1651087
6 · The paper itself

Abstract

A principal goal in ecology is to identify the determinants of species abundances in nature. Body size has emerged as a fundamental and repeatable predictor of abundance, with smaller organisms occurring in greater numbers than larger ones. A biogeographic component, known as Bergmann's rule, describes the preponderance, across taxonomic groups, of larger-bodied organisms in colder areas. Although undeniably important, the extent to which body size is the key trait underlying these patterns is unclear. We explored these questions in diatoms, unicellular algae of global importance for their roles in carbon fixation and energy flow through marine food webs. Using a phylogenomic dataset from a single lineage with worldwide distribution, we found that body size (cell volume) was strongly correlated with genome size, which varied by 50-fold across species and was driven by differences in the amount of repetitive DNA. However, directional models identified temperature and genome size, not cell size, as having the greatest influence on maximum population growth rate. A global metabarcoding dataset further identified genome size as a strong predictor of species abundance in the ocean, but only in colder regions at high and low latitudes where diatoms with large genomes dominated, a pattern consistent with Bergmann's rule. Although species abundances are shaped by myriad interacting abiotic and biotic factors, genome size alone was a remarkably strong predictor of abundance. Taken together, these results highlight the cascading cellular and ecological consequences of macroevolutionary changes in an emergent trait, genome size, one of the most fundamental and irreducible properties of an organism.

Indexed as

DiatomsGenome SizeOceans and SeasPhylogenyBody SizeTemperature

Identifiers

PMID39116044
PMCPMC11309476

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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.