The social structure of animal societies can be instrumental to the evolutionand maintenance of animal behaviour. Animal social networks (ASNs) provide aframework with which to visualise, quantify and analyse animals' social structure.The work in this thesis incorporates two areas of ASN research. The first areais the analysis of sparse group-derived data. Observation of group membershipsis a widely used method to uncover social preferences. Here this method is usedto probe the social structure of a population of Trinidadian guppies (Poeciliareticulata). The network is analysed to ascertain if genetic relatedness may playa role in governing social structure. The bright colourings of male fish are alsoanalysed to see if colour influences male-male associations. The guppy studyprovided motivation for an investigation into association indices for group-derived data. Existing indices are evaluated using a simulated dataset and a new index is proposed.The second part of this thesis contributes to a new and exciting trend in ASNsin which complete records of animal associations are obtained enabling temporalnetwork analysis to be used. This is applied to a population of New Caledoniancrows (Corvus moneduloides) which are of interest particularly for their ability tomanufacture and use tools for foraging. Emulations of information flow throughthe network are used to assess the network's information flow potential. A network structure in which information can spread rapidly could indicate that crows can potentially learn tool use skills from their peers.
|Date of Award||1 Aug 2014|
|Supervisor||Richard James (Supervisor)|