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The modularity of a social group does not affect the transmission speed of a novel, socially learned behaviour, or the formation of local variants

Cite this dataset

Laker, Philippa; Hoppitt, William; Weiss, Michael; Madden, Joah (2021). The modularity of a social group does not affect the transmission speed of a novel, socially learned behaviour, or the formation of local variants [Dataset]. Dryad. https://doi.org/10.5061/dryad.wpzgmsbm4

Abstract

Data set used within the Article "The modularity of a social group does not affect the transmission speed of a novel, socially learned behaviour, or the formation of local variants." 

The structure of a group is critical in determining how a socially learnt behaviour will spread. Predictions from theoretical models indicate that specific parameters of social structure differentially influence social transmission. Modularity describes how the structure of a group or network is divided into distinct subgroups or clusters. Theoretical modelling indicates that the modularity of a network will predict the rate of behavioural spread within a group, with higher modularity slowing the rate of spread and facilitating the establishment of local behavioural variants which can prelude local cultures. Despite prolific modelling approaches, empirical tests via manipulations of group structure remain scarce.

We experimentally manipulated the modularity of populations of domestic fowl chicks, Gallus gallus domesticus, to affect the transmission of a novel foraging behaviour. We compared the spread of behaviour in populations with networks of high or low modularity against a control population where social transmission was prevented.

We found the foraging behaviour to spread socially between individuals when the social transmission was permitted; however, modularity did not increase the speed of behavioural spread nor lead to the initial establishments of shared behavioural variants. This result suggests that factors in the social transmission process additional to the network structure may influence behavioural spread.

 

This dataset includes:

  • The manipulated social networks of our 6 populations of domestic chicks (2 of high modularity, 2 of low modularity and 2 asocial control populations where social transmission was prevented).
  • The order in which chicks learnt the solving behaviour alongside information on individual level variables.
  • The solving techniques used by chicks in all their solves throughout the experiment.
  • The R code use to perform the analyses (Coxph analysis, OADA, testing for assortment)

Methods

File

Title

Short Description

ManuscriptModularity.R

R code for all analysis

R code for all analysis conducted within the manuscript

cumulativeLearningPotential

NetworksChicksModularity

Combined.RData

 

Dynamic OADA networks

R data to load (containing the dynamic OADA networks used in the analysis)

ChicksModularity Number RB doors.txt

 

Data on chicks solving techniques

This data describes every individual’s solving techniques performed across the experiment.

LowCombinedNetsNAs.txt

 

Social networks of Low modularity

Social networks for populations of the low modularity condition

HighCombinedNetsNAs.txt

 

Social networks of High modularity

Social networks for populations of the high modularity condition

Chicks 4&5&7 survival D rem.txt

 

Data for Survival (coxph) analysis

This data describes at which point each individual first acquired the novel solving behaviour, used for the coxph model. (Initial demonstrators removed)

Funding

ERC, Award: 616474