Individual personalities predict social behaviour in wild networks of great tits (Parus major)
Summary (3 min read)
INTRODUCTION
- Understanding the causes and consequence of animal personalities has become one of the great challenges for recent research in evolutionary and behavioural ecology (Wolf et al. 2007; Dall et al. 2012).
- Consistent behavioural differences between individuals have been demonstrated in multiple taxa, with some individuals repeatedly exhibiting more bold, aggressive or exploratory behaviour across a range of contexts (Sih et al. 2004).
- An evenly spaced grid of automated feeding stations fitted with passive integrated transponder (PIT)-tag recording antennae collected ‘snap-shots’ of the composition and distribution of flocks.
Study system
- This population has been the subject of an extensive long-term breeding survey, and there is an ongoing trapping and monitoring effort.
- Almost all individuals in the study area are fitted with both a British Trust for Ornithology metal leg ring, and a plastic leg ring containing a uniquely identifiable PIT tag (proportion PIT-tagged estimated at over 90%, see S2 and Fig. S2).
- While pairs of great tits defend territories over the breeding season, this breaks down into loose fission-fusion groups of unrelated individuals over autumn and winter, with roaming flocks congregating on ephemeral and patchy food sources such as beech mast (seeds of Fagus sylvatica) (Aplin et al. 2012).
Field observations
- Adults and nestling great tits were caught in the breeding season prior to data collection (April to June 2011) and from September to November 2011, when they were aged and sexed based on plumage colour.
- Birds were also assigned as ‘post-breeding’ adults or ‘pre-breeding’ birds (largely juveniles) based on data from previous breeding seasons (2005–2011).
- From 2nd December 2011 until 27th February 2012, sunflower feeders were deployed at 65 locations throughout the study site, each approximately 250 m apart (Fig. S1).
- Each feeding station had two access points each fitted with radio-frequency identification antennae and data logging hardware.
- All feeders automatically opened from dawn to dusk on two consecutive days in every seven, scanning for PIT-tags every 16th of a second.
Behavioural assays
- Assays of exploration behaviour in a novel environment were conducted on wild great tits that were temporarily taken into captivity at the Wytham field station over four winters (October 2009 to October 2012).
- Most data (55%) were collected from late February to early March 2012.
- After assays, birds were released at the site of capture.
- Twelve types of behavioural observation were used to calculate a principal component analysis, including number of flights, flight duration, number of hops, substrates used and area explored (Quinn et al. 2009).
Statistical analysis
- Social associations between individuals were calculated using a Gaussian mixture model that inferred group membership by detecting clusters of visits in spatio-temporal data streams (Farine et al. 2012; Psorakis et al. 2012).
- The authors then tested if the observed pattern of associations were non-random by calculating the number of randomised networks with a higher proportion of associations and mean association strength (Whitehead 2008).
- Social phenotype was measured using three commonly employed individual network measures; degree centrality, betweenness centrality and average association strength.
- To avoid biasing results, all individuals that were observed in fewer than 5 of 13 sampling periods were excluded from analysis.
- Given that each point on the surface is estimated from a large number of dyads, this test permuted the dyadic values between the two groups of data that were used to generate the same points on each of the two surfaces with respect to time lag and relative distance away from either edge of the surface (Pantazis et al. 2004).
Social associations
- Between December 2 2011 and February 27 2012 over 3.3 million visits were recorded from 1017 individual PIT-tagged great tits observed in 26 days of data collection.
- A social network was constructed for the whole winter period taking a ‘gambit of the group’ approach (Franks et al. 2010), inferring group membership from visitation patterns (Farine et al. 2012; Psorakis et al. 2012).
- This remained significant when controlling for the number of spatial movements between data-loggers over the winter (LM: F1,85 = 6.3, P = 0.01), see Table S3.
- Finally, more FE individuals were significantly more likely to move between foraging flocks, with a higher betweenness centrality (LM: F1,86 = 5.2, P = 0.02).
- Network metrics derived at the community-level revealed the same overall relationships between personality and centrality measures (Table S4).
Temporal dynamics
- The authors quantified the temporal stability of social relationships by estimating the lagged association rates of all post-breeding individuals with all other post-breeding individuals over the 3-month sampling period (Whitehead 2008).
- More SE birds had a significantly higher likelihood of re-associating with other individuals, and their probability of re-association was highest with other SE birds, for which associations were maintained at a relatively high rate over time (N = 90; Fig. 2a and b).
- In contrast, more FE birds were much less likely to re-associate, and had lower lagged association rates over the 3 month winter period (Fig. 2c and d).
- Association rates were lowest in FE-FE interactions (Fig. 2c).
- The effect was synergistic, with the most ephemeral relationships being between pairs of more proactive (FE) birds (Fig. 2c), and the most stable between pairs of more reactive (SE) birds (Fig. 2a; Table S5).
Social structure
- The authors tested whether individuals of similar personality were more likely to be observed together, influencing the composition of groups and emergent social structure.
- Preliminary analysis did, however, reveal contrasting results for mixing patterns among males and females, and the sexes were analysed separately.
- (a) Social network where colour represents personality score ranging from most reactive (SE) phenotypes in blue to most proactive (FE) phenotypes in red; the range of the colour distribution has been slightly exaggerated at the ends of the distribution to emphasise more extreme phenotypes.
- Grey nodes are individuals of unknown phenotype.
- To test whether personality phenotypes were non-randomly distributed between groups, the authors calculated the kurtosis of the distribution of mean phenotype of each group.
DISCUSSION
- Using standard behavioural assays and automated monitoring of foraging flocks, the authors show that individual-level differences in behaviour predict the frequency, stability and distribution of social associ- © 2013 John Wiley & Sons Ltd/CNRS ations in a wild songbird.
- In particular, the authors demonstrate that individual-level variation in exploration behaviour (a proxy for the reactive-proactive axis) is associated with both social phenotype and patterns of group organisation in adult great tits.
- Given this, there must be potentially high payoffs associated with the alternative social behaviour observed in more proactive (FE) individuals.
- This relationship is likely to interact with ecological processes, with important implications for transmission of information and disease, and for individual variation in the acquisition of resources (Aplin et al. 2012).
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Citations
648 citations
Cites background from "Individual personalities predict so..."
...2013), how individual variation in social behaviour can drive population structure (Aplin et al. 2013; Jacoby et al. 2014; Snijders et al. 2014) and how socially transmitted quantities, such as information or disease, flow through individuals in a population (Boogert et al....
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...A good example of thresholding individuals based on properties of the data is Aplin et al. (2013) who removed individuals with fewer than 100 observations as these exhibited a clear relationship between number of observations and the binary degree....
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...Connor, Heithaus & Barre 2001; Wittemyer, DouglasHamilton & Getz 2005); (ii) studies of the causes and consequences of individual variation in network position – where ‘network position’ refers to the structural properties that arise as a consequence of an individual’s phenotype or patterns of sociality (e.g. McDonald 2007; Pike et al. 2008; Oh & Badyaev 2010; Aplin et al. 2013); (iii) studies of social processes and the implications of network structure for dynamics of information (e....
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...The lagged association rate is useful for describing and modelling the temporal scales over which social behaviour processes operate, or for comparing how these differ between different classes of individuals (e.g. Aplin et al. 2013)....
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...…properties that arise as a consequence of an individual’s phenotype or patterns of sociality (e.g. McDonald 2007; Pike et al. 2008; Oh & Badyaev 2010; Aplin et al. 2013); (iii) studies of social processes and the implications of network structure for dynamics of information (e.g. Boogert et al.…...
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541 citations
312 citations
Cites background from "Individual personalities predict so..."
...For example, a hypothesis might be that individuals with bold personalities have higher binary degree (more associates) in the social network (e.g. Aplin et al. 2013)....
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291 citations
References
272,030 citations
"Individual personalities predict so..." refers methods in this paper
...All network analyses were conducted in R Core Team (2012), using the sna and igraph packages (Csardi & Nepusz 2006; Butts 2008)....
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15,738 citations
"Individual personalities predict so..." refers result in this paper
...However, we found no evidence for heterophily in our social network, but rather positive network assortment (i.e. homophily) among males, similar to that often observed in human personality research (McPherson et al. 2001)....
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...homophily) among males, similar to that often observed in human personality research (McPherson et al. 2001)....
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8,850 citations
"Individual personalities predict so..." refers methods in this paper
...Network assortment was calculated independently for males and females using Newman’s assortative mixing by scalar properties (Newman 2003) in the igraph package (Csardi & Nepusz 2006), with personality scores used as a continuous measure....
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...All network analyses were conducted in R Core Team (2012), using the sna and igraph packages (Csardi & Nepusz 2006; Butts 2008)....
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6,366 citations
5,439 citations
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Frequently Asked Questions (2)
Q2. What have the authors stated for future works in "Individual personalities predict social behaviour in wild networks of great tits (parus major)" ?
Further research should aim to further understand the mechanisms driving emergent population structure, and attempt to establish the directionality of the relationship between social behaviour and personality traits such as exploration behaviour ( Wilson et al. 2013 ). A future challenge will be to advance the understanding of the ecology and evolution of personality by quantifying the role of personality in social networks across fluctuating spatial and temporal gradients.