This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.3389/fevo.2026.1752597. This is version 2 of this Preprint.
Abundant empirical evidence of multilevel selection revealed by a bibliometric review
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Abstract
Natural selection is based on the concept of differential reproduction between entities, often characterized as a struggle between individual organisms. However, natural selection can act at all levels of biological organization, thus being termed “multilevel selection” (MLS). A common misconception is that selection across levels of biological organization lacks empirical support. To address this, we conducted a bibliometric review of 2,950 Web of Science/Scopus-indexed scientific articles, to document the range of taxa and research topics where MLS has been used to understand natural selection across levels. The 280 studies providing empirical support for selection at more than one level spanned a vast range of organisms, from viruses to humans to eusocial insects. They included research done both in natural populations (100) and in laboratory experiments (180). While 90.4% of studies focused on selection among organismal groups (e.g., demes, colonies, aggregates), another 9.6% explored selection across other levels (genetic elements, nuclei, cells, or multispecies communities). We classified studies by topic including artificial selection, breeding through group selection, indirect genetic effects, and contextual analysis, among others. Contrary to common notions, we found solid empirical support for the utility and importance of MLS in explaining natural selection and evolution.
DOI
https://doi.org/10.32942/X25S84
Subjects
Life Sciences
Keywords
animal and plant breeding, artificial selection, contextual analysis, Epistasis, group selection, units of selection
Dates
Published: 2025-07-31 23:04
Last Updated: 2026-02-21 02:20
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License
CC-By Attribution-NonCommercial-NoDerivatives 4.0 International
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Conflict of interest statement:
The authors declare no conflict of interest.
Data and Code Availability Statement:
The database used for this Review is available at Zenodo: https://doi.org/10.5281/zenodo.16633276
Language:
English
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