DOI: 10.5061/dryad.3tx95x6fw
title: Social network centrality predicts dietary decisions in wild great tits

description: Foraging in groups provides many benefits but also carries costs, such as
 competition. Social individuals can potentially alleviate competition by
 broadening their dietary niches through incorporating new foods. However,
 individuals have less information about the nutritional quality, and
 safety, of novel foods compared to familiar-foods. Individuals
 experiencing the most competitive social environments might be expected to
 be most likely to respond by incorporating novel foods, but it has
 previously been challenging to test directly how sociality relates to
 dietary decisions in natural populations. Here, we present RFID-tracked
 wild great tits (Parus major) with novel food, and use social network
 analysis to test how sociality predicts individuals’ foraging choices. We
 show that socially-central individuals with more social links have a
 higher propensity to use novel food compared to socially-peripheral
 individuals, and that this relationship is unrelated to aversion to novel
 feeders, number of feeding observations, and demographic factors. We
 demonstrate how our findings indicate sociable individuals can offset the
 costs of highly competitive social environments by foraging more broadly.
 Finally, we discuss how competition may drive behavioural change in
 natural populations, and the implications for understanding the causes and
 consequences of social strategies and dietary decisions.
description: ReadMe Data Description For Sociality and Diet Objects (note this
 description is also included in the .RData file) contains 2 Primary
 objects: Object 1 = 'inds.data': This is
 general information on all the individuals take took place in the groups,
 along with info on their foraging activities, and their social network
 positions in all 3 aspects of the network. The following columns need some
 further description. recs.tot is total records, recs.pre is records before
 exp began, recs.exp is records over the experimental period,
 recs.novel1.out is number of records when the first novel feeder was out,
 recs.novel2.out is same but when second novel feeder was out (note that
 this '1' and '2' theme carries on with the columns),
 recs.exp.novelfood.1 is the number of recs ON THE FIRST EXPERIMENTAL
 FEEDER (i.e. recs on the novel food feeder) when the first novel feeder
 was out, recs.exp.novelfood.2 is the number of recs ON THE SECOND
 EXPERIMENTAL FEEDER (i.e. recs on the novel food feeder) when the second
 novel feeder was out, the next set of columns give info about the number
 of days the bird visited the feeder at the different time points etc etc,
 site.exppart.ninds is the number of individuals present in this local
 network, site.exppart.ninds is the number of flocking events this local
 network was derived from, locations is the locations this bird was
 recorded at during this network , the rest of the columns are metrics for
 the individual within that local network such as ngroups is the nubmer of
 groups the ind was observed in for this local network, avggroup is their
 average group size, deg is their unweighted network degree, wdeg is their
 weighted network degree (or 'strength'), avedge is the average
 strength of their non-zero bonds within the network, wevc is their
 eigenvector centrality. Object 2 =
 'recs.data': This is raw data in terms of the datastream from
 the RFID detections of great tits at the feeders, the columns are
 described in the column headings. Please contact
 joshua.firth@zoo.ox.ac.uk with any questions.