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Group composition of individual personalities alters social network structure in experimental populations of forked fungus beetles

Citation

Cook, Phoebe et al. (2022), Group composition of individual personalities alters social network structure in experimental populations of forked fungus beetles, Dryad, Dataset, https://doi.org/10.5061/dryad.0rxwdbs24

Abstract

Social network structure is a critical group character that mediates the flow of information, pathogens, and resources among individuals in a population, yet little is known about what shapes social structures. In this study, we experimentally tested whether social network structure depends on the personalities of group members. Replicate groups of forked fungus beetles (Bolitotherus cornutus) were engineered to include only members previously assessed as either more social or less social. We found that individuals behaved consistently across social contexts, exhibiting repeatable numbers of interactions and numbers of partners. At the group level, networks composed of more social individuals had higher interaction rates, higher tie density, higher global clustering, and shorter average shortest paths than those composed of less social individuals. We highlight group composition of personalities as a source of variance in group traits and a potential mechanism by which networks could evolve.

Methods

These data describe patterns of interaction among 20 mesocosm populations of Bolitotherus cornutus -- 10 initial populations in which individual phenotypes were scored, and 10 populations (5 each of the "high" or "low" sociality treatments) in which both individual and group phenotypes were scored. Social interactions were defined as individuals being in close proximity (within 5cm) of one another, and were collected through scan sampling 3x a day for 8 days in each session. Behavioral datasets were error-checked to remove all unidentifiable or dead beetles and all impossible or partially recorded interactions. Weighted social networks were created using the the simple ratio index. Weighted clustering and shortest path lengths were calculated in the R package tnet.

Funding

National Science Foundation, Award: DGE-1842490

National Science Foundation, Award: IOS-1355029

National Science Foundation, Award: IOS-1355003

National Science Foundation, Award: DEB-1911485

National Science Foundation, Award: DBI-1461169

University of Virginia