Innovation and geographic spread of a complex foraging culture in an urban parrot

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Abstract

The emergence, spread, and establishment of innovations within cultures can promote adaptive responses to anthropogenic change. We describe a putative case of the development of a cultural adaptation to urban environments: opening of household waste bins by wild sulphur-crested cockatoos. A spatial network analysis of community science reports revealed the geographic spread of bin opening from three suburbs to 44 in Sydney, Australia, by means of social learning. Analysis of 160 direct observations revealed individual styles and site-specific differences. We describe a full pathway from the spread of innovation to emergence of geographic variation, evidencing foraging cultures in parrots and indicating the existence of cultural complexity in parrots. Bin opening is directly linked to human-provided opportunities, highlighting the potential for culture to facilitate behavioral responses to anthropogenic change.

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Is Open Access

Constructing, conducting and interpreting animal social network analysis

Damien R. Farine, Hal Whitehead (2015)

Summary Animal social networks are descriptions of social structure which, aside from their intrinsic interest for understanding sociality, can have significant bearing across many fields of biology. Network analysis provides a flexible toolbox for testing a broad range of hypotheses, and for describing the social system of species or populations in a quantitative and comparable manner. However, it requires careful consideration of underlying assumptions, in particular differentiating real from observed networks and controlling for inherent biases that are common in social data. We provide a practical guide for using this framework to analyse animal social systems and test hypotheses. First, we discuss key considerations when defining nodes and edges, and when designing methods for collecting data. We discuss different approaches for inferring social networks from these data and displaying them. We then provide an overview of methods for quantifying properties of nodes and networks, as well as for testing hypotheses concerning network structure and network processes. Finally, we provide information about assessing the power and accuracy of an observed network. Alongside this manuscript, we provide appendices containing background information on common programming routines and worked examples of how to perform network analysis using the r programming language. We conclude by discussing some of the major current challenges in social network analysis and interesting future directions. In particular, we highlight the under‐exploited potential of experimental manipulations on social networks to address research questions.