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Boogert, N.J.; Reader, S.M.; Hoppitt, W.; Laland, K.N. |
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Title |
The origin and spread of innovations in starlings |
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Journal Article |
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Year |
2008 |
Publication |
Animal Behaviour |
Abbreviated Journal |
Anim. Behav. |
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75 |
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4 |
Pages |
1509-1518 |
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Keywords |
diffusion dynamics; dominance; foraging; group; innovation; neophobia; social learning; social network; starling; Sturnus vulgaris |
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Abstract |
There are numerous reports of novel learned behaviour patterns in animal populations, yet the factors influencing the invention and spread of these innovations remain poorly understood. Here we investigated to what extent the pattern of spread of innovations in captive groups of starlings, Sturnus vulgaris, could be predicted by knowledge of individual and social group variables, including association patterns, social rank orders, measures of neophobia and asocial learning performance. We presented small groups of starlings with a series of novel extractive foraging tasks and recorded the latency for each bird to contact and solve each task, as well as the orders of contacting and solving. We then explored which variables best predicted the observed diffusion patterns. Object neophobia and social rank measures characterized who was the first of the group to contact the novel foraging tasks, and the subsequent spread of contacting tasks was associated with latency to feed in a novel environment. Asocial learning performance, measured in isolation, predicted who was the first solver of the novel foraging tasks in each group. Association patterns did not predict the spread of solving. Contact latency and solving duration were negatively correlated, consistent with social learning underlying the spread of solving. Our findings indicate that we can improve our understanding of the diffusion dynamics of innovations in animal groups by investigating group-dependent and individual variables in combination. We introduce novel methods for exploring predictors of the origin and spread of behavioural innovations that could be widely applied. |
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0003-3472 |
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Equine Behaviour @ team @ |
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6036 |
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Briard, L.; Dorn, C.; Petit, O. |
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Title |
Personality and Affinities Play a Key Role in the Organisation of Collective Movements in a Group of Domestic Horses |
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Journal Article |
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Year |
2015 |
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Ethology |
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Ethology |
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121 |
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9 |
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888-902 |
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decision-making; equids; hierarchy; leadership; social network |
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Understanding how groups of individuals with different motives come to daily decisions about the exploitation of their environment is a key question in animal behaviour. While interindividual differences are often seen only as a threat to group cohesion, growing evidence shows that they may to some extent facilitate effective collective action. Recent studies suggest that personality differences influence how individuals are attracted to conspecifics and affect their behaviour as an initiator or a follower. However, most of the existing studies are limited to a few taxa, mainly social fish and arthropods. Horses are social herbivores that live in long-lasting groups and show identifiable personality differences between individuals. We studied a group of 38 individuals living in a 30-ha hilly pasture. Over 200 h, we sought to identify how far individual differences such as personality and affinity distribution affect the dynamic of their collective movements. First, we report that individuals distribute their relationships according to similar personality and hierarchical rank. This is the first study that demonstrates a positive assortment between unrelated individuals according to personality in a mammal species. Second, we measured individual propensity to initiate and found that bold individuals initiated more often than shy individuals. However, their success in terms of number of followers and joining duration did not depend on their individual characteristics. Moreover, joining process is influenced by social network, with preferred partners following each other and bolder individuals being located more often at the front of the movement. Our results illustrate the importance of taking into account interindividual behavioural differences in studies of social behaviours. |
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1439-0310 |
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Equine Behaviour @ team @ |
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6153 |
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Hasenjager, M.J.; Dugatkin, L.A. |
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Social Network Analysis in Behavioral Ecology |
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Animal personalities; Animal social networks; Collective behavior; Cooperation; Dynamic networks; Emergent properties; Network theory; Social behavior; Social learning; Social structure |
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Abstract In recent years, behavioral ecologists have embraced social network analysis (SNA) in order to explore the structure of animal societies and the functional consequences of that structure. We provide a conceptual introduction to the field that focuses on historical developments, as well as on novel insights generated by recent work. First, we discuss major advances in the analysis of nonhuman societies, culminating in the use of SNA by behavioral ecologists. Next, we discuss how network-based approaches have enhanced our understanding of social structure and behavior over the past decade, focusing on: (1) information transmission, (2) collective behaviors, (3) animal personality, and (4) cooperation. These behaviors and phenomena possess several features—e.g., indirect effects, emergent properties—that network analysis is well equipped to handle. Finally, we highlight recent developments in SNA that are allowing behavioral ecologists to address increasingly sophisticated questions regarding the structure and function of animal sociality. |
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Academic Press |
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Advances in the Study of Behavior |
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Equine Behaviour @ team @ Hasenjager |
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5863 |
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Author |
Newman, M.E.J. |
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Title |
The Structure and Function of Complex Networks |
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2003 |
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SIAM Review |
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SIAM Rev. |
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45 |
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2 |
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167-256 |
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networks; graph theory; complex systems; computer networks; social networks; random graphs; percolation theory |
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Inspired by empirical studies of networked systems such as the Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us understand or predict the behavior of these systems. Here we review developments in this field, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks. |
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Siam |
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Equine Behaviour @ team @ |
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5214 |
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