Community-Level Selection Evolves Group Assemblage Phenotypes Inaccessible Through Individual-Level Selection in a Simple Agent-Based Model with Emergent Behavior

61 Pages Posted: 12 Apr 2025

See all articles by C. M. Williams

C. M. Williams

Haverford College

Emma M. Miller

Haverford College

Lauren Ancel Meyers

University of Texas at Austin; Santa Fe Institute

Eric L. Miller

Haverford College

Abstract

How do communities of diverse organisms maintain relative frequencies of members, even as the community evolves, grows, and replicates? How do communities that contain mutually dependent species, such as bacterial biofilms, self-organize and maintain these niches as individuals compete for resources? Are there community-wide characteristics, such as a distinct flavor of cheese caused by a diverse assemblage of microbes, that are only possible through the careful curation and selection of communities by humans? While evidence of selection at levels lower than the individual (such as at the gene-level) are well-documented, the possible outcomes of selection at higher levels (such as communities and community-level properties) are unclear. We used a simple, agent-based simulation to investigate the degree and the predictability of the impacts of community-level selection. In this model, we independently toggled individual-level selection and community-level selection. We found an unexpectedly complex fitness landscape and an emergent behavior — discrete partitioning of individuals into groups — connecting community composition and reproductive success in this simulation. Community-level selection maximized success of communities even with this complex fitness landscape, but the addition of individual-level selection accelerated this process if, and only if, both levels of selection were selecting for complementary properties. Community-level selection also increased the final diversity in the community compared to individual-level selection alone. While our model is simple compared to natural systems, we provide guidance for experimenters curating and selecting communities for diversity or for properties inaccessible by individual species alone.

Keywords: evolution, selection, levels of selection, community-level selection, artificial ecosystem selection

Suggested Citation

Williams, C. M. and Miller, Emma M. and Meyers, Lauren Ancel and Miller, Eric L., Community-Level Selection Evolves Group Assemblage Phenotypes Inaccessible Through Individual-Level Selection in a Simple Agent-Based Model with Emergent Behavior. Available at SSRN: https://ssrn.com/abstract=5215274 or http://dx.doi.org/10.2139/ssrn.5215274

C. M. Williams

Haverford College ( email )

Haverford, PA 19041
United States

Emma M. Miller

Haverford College ( email )

Haverford, PA 19041
United States

Lauren Ancel Meyers

University of Texas at Austin ( email )

2317 Speedway
Austin, TX Texas 78712
United States

Santa Fe Institute ( email )

1399 Hyde Park Road
Santa Fe, NM 87501
United States

Eric L. Miller (Contact Author)

Haverford College ( email )

Haverford, PA 19041
United States

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