10.5061/DRYAD.81K11
Goold, Conor
Norwegian University of Life Sciences
Vas, Judit
Norwegian University of Life Sciences
Olsen, Christine
Norwegian University of Life Sciences
Newberry, Ruth C.
Norwegian University of Life Sciences
Data from: Using network analysis to study behavioural phenotypes: an
example using domestic dogs
Dryad
dataset
2016
phenotypic integration
Play behaviour
Working dogs
Dog behaviour
2016-10-11T13:51:17Z
2016-10-11T13:51:17Z
en
https://doi.org/10.1098/rsos.160268
6740155 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
Phenotypic integration describes the complex interrelationships between
organismal traits, traditionally focusing on morphology. Recently,
research has sought to represent behavioural phenotypes as composed of
quasi-independent latent traits. Concurrently, psychologists have opposed
latent variable interpretations of human behaviour, proposing instead a
network perspective envisaging interrelationships between behaviours as
emerging from causal dependencies. Network analysis could also be applied
to understand integrated behavioural phenotypes in animals. Here, we
assimilate this cross-disciplinary progression of ideas by demonstrating
the use of network analysis on survey data collected on behavioural and
motivational characteristics of police patrol and detection dogs (Canis
lupus familiaris). Networks of conditional independence relationships
illustrated a number of functional connections between descriptors, which
varied between dog types. The most central descriptors denoted desirable
characteristics in both patrol and detection dog networks, with ‘Playful’
being widely correlated and possessing mediating relationships between
descriptors. Bootstrap analyses revealed the stability of network results.
We discuss the results in relation to previous research on dog
personality, and benefits of using network analysis to study behavioural
phenotypes. We conclude that a network perspective offers widespread
opportunities for advancing the understanding of phenotypic integration in
animal behaviour.
rawDataRaw data before any statistical
analysesPatrolDog_GGM_AssociationMatrixAssociation matrix of raw
correlations for patrol dogs shown in the network
figureDetectionDog_GGM_AssociationMatrixAssociation matrix of raw
correlations for detection dogs shown in the network
figurefinalMIdata_averaged_roundedFinal set of multiply imputed data
(averaged over 15 multiply imputed data sets and rounded to be integers)R
script fileR script to run the analyses and reproduce the figures in the
article.Rscript.RSupplementary_MaterialSupplementary Material for the
article, including further details and results of the statistical analyses
not included in the manuscript.