%0 Journal Article
%A Smolla, Marco
%A Akçay, Erol
%+ Department of Human Behavior Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Max Planck Society
%T Pathways to cultural adaptation: the coevolution of cumulative culture and social networks : 
%G eng
%U https://hdl.handle.net/21.11116/0000-000D-AFD0-3
%R 10.1017/ehs.2023.21
%7 2023-08-25
%D 2023
%* Review method: peer-reviewed
%X Humans have adapted to an immense array of environments by accumulating culturally transmitted knowledge and skills. Adaptive culture can accumulate either via more distinct cultural traits or via improvements of existing cultural traits. The kind of culture that accumulates depends on, and coevolves with, the social structure of societies. Here, we show that the coevolution of learning networks and cumulative culture results in two distinct pathways to cultural adaptation: highly connected populations with high proficiency but low trait diversity versus sparsely connected populations with low proficiency but higher trait diversity. Importantly, we show there is a conflict between group-level payoffs, which are maximised in highly connected groups that attain high proficiency, and individual level selection, which favours disconnection. This conflict emerges from the interaction of social learning with population structure and causes populations to cycle between the two cultural and network states. The same conflict creates a paradox where increasing innovation rates lowers group payoffs. Finally, we explore how populations navigate these two pathways in environments where payoffs differ among traits and can change over time, showing that high proficiency is favoured when payoffs are stable and vary strongly between traits, while frequent changes in trait payoffs favour more trait diversity. Our results illustrate the complex interplay between networks, learning, and the environment, and so inform our understanding of human social evolution
%K cumulative cultural evolution, social networks, social learning, heterogeneous environments, agent-based model

%J Evolutionary Human Sciences
%V 5
%& 1
%P 1 - 20
%] e26
%@ 2513-843X