Full text
2,011 characters
· extracted from
oa-doi-fallback
· click to expand
This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.
You must log in to post a comment.
There are no comments or no comments have been made public for this article.
This is a Preprint and has not been peer reviewed. This is version 3 of this Preprint.
Add a Comment
You must log in to post a comment.
Comments
There are no comments or no comments have been made public for this article.
Gene-culture coevolution (GCC) - an ambitious synthesis of biological and social sciences - is often used to explain the evolution of key human traits. Despite the framework’s broad conceptual appeal however, empirical evidence is often perceived as limited to a few key examples like lactase persistence. We argue this apparent gap between theoretical appeal and empirical evidence stems from conceptual ambiguities regarding the scope of relevant gene-culture interactions. Drawing on recent work in animal gene-culture coevolution and human genomics, we propose a ”broad” approach that formally incorporates drift and migration alongside natural selection. This builds upon and subsumes the existing ”narrow” framework focused on selection. Through case studies of skin pigmentation evolution and gift-exchange network influences on genetic variation in Melanesia, we demonstrate how cultural factors shape both adaptive and neutral genetic variation and population structure. This integrative perspective accommodates diverse empirical findings while opening new avenues for research in human evolution.
https://doi.org/10.32942/X2862X
Anthropology, Biological and Physical Anthropology, Ecology and Evolutionary Biology, Evolution, Genetics and Genomics, Genomics, Social and Behavioral Sciences
Gene-culture, gene-culture coevolution, Human genomics, human evolution, biocultural evolution, drift, migration
Published: 2024-09-05 22:09
Last Updated: 2025-04-21 19:30
CC-By Attribution-ShareAlike 4.0 International
Data and Code Availability Statement:
Not applicable
Language:
English
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.