DOI: 10.5281/zenodo.16930532
title: Code and Data for: Experimental evidence reveals alternative pathways to cultural inheritance in juvenile great tits, Parus major

description: Authors: Sonja Wild, Gustavo Alarcón-Nieto, Lucy Aplin




This repository contains all data and R code necessary to replicate analyses and all figures.

 




1) Accompanying R codes are available on github:


Parental_behav.R: this is the code for analysing behavioural similarities among parents and their offspring - i.e. does parental solving behaviour during dependence predict whether or not offspring learn to solve the puzzle box or not.

NBDA_solving.R: This details the network-based diffusion analysis detailing the pathways of social transmission of knowledge about the puzzle box for juvenile birds during transition to independence.

Side_choice_regressions.R: This is the code analysis which factors predict side choices (right and left) of juvenile birds i) on their first solving day when entirely inexperienced, and ii) across all experimental days to assess whether parental behaviour, social information and/or personal experience predict side choices.



Breeders 2021.txt: contains information on individual birds' PIT tags, sex and species

demonstrators.RDA: a list of birds that were knowledgeable in solving the puzzle box from a previous experiment prior to May 14 2021.

fledge.dates.txt: contains the date on which fledglings left their nest boxes

fledgling_parents_strategies.csv: input data set for analysis on whether parental behavior predicts solving in juvneiles (see parental_behav.R for details on columns)

Guett acquisition date.RDA and Mill acquisition date.RDA contain information on the date and time when birds learned to solve the puzzle at the different experimental locations (used for NBDA analyses). Acquisition is considered to have happened on the third solve.

Guett.gmm & Mill.gmm: output objects of gmmevents function from package asnipe on visitation data streams at network feeders. These group arrivals into clusters forming flocks, which can then be used to create social networks based on co-occurrence in flocks.

Guett.networks and Mill.networks: These contain 8 social networks each calculated using the gmm objects above. These are based on weekly measures (8 weeks) and are used as dynamics networks in NBDA.

Guett puzzle data and Mill puzzle data: contain information on arrival, departure, solving times and sides, and identity of birds at the 7 experimental locations collected automatically.

side choice input.RDA: input data used to assess side choices (left/right) by juveniles both on their first solving day and across all experimental days (see code Side_choice_regression for details)

AIC.table.csv: contains AICc values and relative support by AICc weights for all NBDA models

constraintsVectMatrix: is a matrix detailing which models are run for the NBDA

Guett and Mill.nbda.data.objects: one input object for each of the 7 experimental locations. This is generated by a custom function in the NBDA code, but can be loaded directly.

model_conflicting.RData: contains the model output of the analysis on whether parental solving behaviour influences side choices on first solving day (delayed production)

model_first_day.RData: model output of factors predicting side choices (left/right) on juveniles' first solving day

model_parent_predict.RData: contains the model output of the analysis on behavioural similarities between parents and their offspring

model_soc_vs_asoc.RData: contains model output of predictors of side choices of juveniles across all experimental days (social information and persoanl experience)

tadaAICtable.RData: model output of NBDA analyses.