17Social networks are increasingly being used to describe animal social structure, however we 18 still have a limited understanding of the factors that shape networks, and this is particularly so either through sex-biased dispersal or behavioural avoidance (Pusey and Wolf 1996). Increasingly, social networks are being used to explore the structure of social 56 associations within populations and within aggregations (Krause et al. 2007; Sih et al. 2009).
57They provide a framework for quantifying associations among individuals on a dyadic level,
58by representing a population as a series of nodes (representing individuals) connected by 59 edges (representing associations) and are particularly useful for testing hypotheses about the 60 factors influencing social structure (Wey et al. 2008
92Although it has a largely solitary life, each spring, adult lizards form monogamous pair-bonds 93 for up to 10 weeks before they mate, and individual pairs of lizards often re-establish those 94 partnerships in subsequent years (Bull 1988; 1994; Bull et al. 1998; Bull 2000; Bull & 95 Burzacott 2006; Leu et al. 2010a). The use of on-board activity and GPS loggers (Kerr et al.
99Social networks based on frequency of contacts among active lizards have shown that 100 individuals associate with some neighbours and avoid others, and that this social structure 101 remains stable both within a year and over multiple years (Leu et al. 2010a; Godfrey et al. 102 2013). Our current study builds upon this previous research by exploring the genetic 103 relationships between adult lizards in a social network. The aim of the study was to determine 104 whether lizards that were connected in the social network were more (or less) related to each 105 other than if there had been random associations. In any population, individuals that live 106 closer together will have more opportunities to interact than those living further apart. In our 107 analyses we specifically asked whether we could detect an influence of genetic relatedness on 108 network structure after controlling for spatial proximity.
Methods
111The study was conducted from October to December 2010, in a 1.0 x 1.5 km area of Water and Natural Resources.
144Network structure 145 We developed a social network from incidents of spatial proximity of dyads of active lizards.
146These were derived from synchronous GPS locations every 10 min for each of the 60 lizards. with female-female dyads the least related (Fig. 1).
266Association strength was strongly positively correlated with expected associations 267 (derived from the spatial overlap among dyads), although observed association strength was 268 substantially lower than expected association rates (Fig. 2). Association strength was not 269 significantly influenced by genetic relatedness at this spatial scale (Table 2). lizards that had home range centres less than 200 m apart (Fig. 2). For this subset of dyads, 274 association strength was also positively correlated with expected association rates (Fig....
These results suggest the prominent circuits involved in emotion recognition, particularly negative emotions, might be impaired in comorbid depressive symptoms in PD.
White matter alterations in the cingulum, IFOF regions, and corpus callosum might explain faster cognitive deterioration in PD patients with RBD, in terms of visual recognition and visuospatial dysfunction and executive function. Disturbed brain structural tissue markers in CST in PD + RBD patients, could be justified in the light of faster motor progression in these patients.
Pleistocene diversification and biogeographic barriers in southern Australia reflected in the phylogeography of a widespread and common lizard species. Molecular Phylogenetics and Evolution, 133, 107-119.
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