James, R., Croft, D., & Krause, J. (2009). Potential banana skins in animal social network analysis. Behav. Ecol. Sociobiol., 63(7), 989-997.
Abstract: Social network analysis is an increasingly popular tool for the study of the fine-scale and global social structure of animals. It has attracted particular attention by those attempting to unravel social structure in fission–fusion populations. It is clear that the social network approach offers some exciting opportunities for gaining new insights into social systems. However, some of the practices which are currently being used in the animal social networks literature are at worst questionable and at best over-enthusiastic. We highlight some of the areas of method, analysis and interpretation in which greater care may be needed in order to ensure that the biology we extract from our networks is robust. In particular, we suggest that more attention should be given to whether relational data are representative, the potential effect of observational errors and the choice and use of statistical tests. The importance of replication and manipulation must not be forgotten, and the interpretation of results requires care.
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Krause, S., Mattner, L., James, R., Guttridge, T., Corcoran, M., Gruber, S., et al. (2009). Social network analysis and valid Markov chain Monte Carlo tests of null models. Behav. Ecol. Sociobiol., 63(7), 1089-1096.
Abstract: Analyses of animal social networks derived from group-based associations often rely on randomisation methods developed in ecology (Manly, Ecology 76:1109–1115, 1995) and made available to the animal behaviour community through implementation of a pair-wise swapping algorithm by Bejder et al. (Anim Behav 56:719–725, 1998). We report a correctable flaw in this method and point the reader to a wider literature on the subject of null models in the ecology literature. We illustrate the importance of correcting the method using a toy network and use it to make a preliminary analysis of a network of associations among eagle rays.
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Krause, J., Lusseau, D., & James, R. (2009). Animal social networks: an introduction. Behav. Ecol. Sociobiol., 63(7), 967-973.
Abstract: Network analysis has a long history in the mathematical and social sciences and the aim of this introduction is to provide a brief overview of the potential that it holds for the study of animal behaviour. One of the most attractive features of the network paradigm is that it provides a single conceptual framework with which we can study the social organisation of animals at all levels (individual, dyad, group, population) and for all types of interaction (aggressive, cooperative, sexual etc.). Graphical tools allow a visual inspection of networks which often helps inspire ideas for testable hypotheses. Network analysis itself provides a multitude of novel statistical tools that can be used to characterise social patterns in animal populations. Among the important insights that networks have facilitated is that indirect social connections matter. Interactions between individuals generate a social environment at the population level which in turn selects for behavioural strategies at the individual level. A social network is often a perfect means by which to represent heterogeneous relationships in a population. Probing the biological drivers for these heterogeneities, often as a function of time, forms the basis of many of the current uses of network analysis in the behavioural sciences. This special issue on social networks brings together a diverse group of practitioners whose study systems range from social insects over reptiles to birds, cetaceans, ungulates and primates in order to illustrate the wide-ranging applications of network analysis.
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Faria, J. J., Dyer, J. R. G., Tosh, C. R., & Krause, J. (2010). Leadership and social information use in human crowds. Anim. Behav., 79(4), 895–901.
Abstract: One of the big challenges for group-living animals is to find out who in a group has pertinent information (regarding food or predators) at any moment in time, because informed individuals may not be obviously recognizable to other group members. We found that individuals in human groups were capable of identifying those with information, and this identification increased group performance: the speed and accuracy of groups in reaching a target. Using video analysis we found how informed individuals might have been identified by other group members by means of inadvertent social cues (such as starting order, time spent following and group position). Furthermore, we were able to show that at least one of these cues, the group position of informed individuals, was indeed correlated with group performance. Our final experiment confirmed that leadership was even more efficient when the group members were given the identity of the leader. We discuss the effect of information status regarding the presence and identity of leaders on collective animal behaviour.
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Couzin, I. D., & Krause, J. (2003). Self-Organization and Collective Behavior in Vertebrates. In Charles T. Snowdon and Timothy J. Roper J. S. R. Peter J. B. Slater (Ed.), Advances in the Study of Behavior (Vol. 32, pp. 1–75). Academic Press.
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Couzin, I. D., Krause, J., Franks, N. R., & Levin, S. A. (2005). Effective leadership and decision-making in animal groups on the move. Nature, 433(7025), 513–516.
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Croft, D. P., James, R., & Krause, J. (Eds.). (2008). Exploring Animal Social Networks. Princton: Princton University Press.
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Guttridge, T. L., Dijk, S., Stamhuis, E. J., Krause, J., Gruber, S. H., & Brown, C. (2013). Social learning in juvenile lemon sharks, Negaprion brevirostris. Animal Cognition, 16(1), 55–64.
Abstract: Social learning is taxonomically widespread and can provide distinct behavioural advantages, such as in finding food or avoiding predators more efficiently. Although extensively studied in bony fishes, no such empirical evidence exists for cartilaginous fishes. Our aim in this study was to experimentally investigate the social learning capabilities of juvenile lemon sharks, Negaprion brevirostris. We designed a novel food task, where sharks were required to enter a start zone and subsequently make physical contact with a target in order to receive a food reward. Naive sharks were then able to interact with and observe (a) pre-trained sharks, that is, ‘demonstrators’, or (b) sharks with no previous experience, that is, ‘sham demonstrators’. On completion, observer sharks were then isolated and tested individually in a similar task. During the exposure phase observers paired with ‘demonstrator’ sharks performed a greater number of task-related behaviours and made significantly more transitions from the start zone to the target, than observers paired with ‘sham demonstrators’. When tested in isolation, observers previously paired with ‘demonstrator’ sharks completed a greater number of trials and made contact with the target significantly more often than observers previously paired with ‘sham demonstrators’. Such experience also tended to result in faster overall task performance. These results indicate that juvenile lemon sharks, like numerous other animals, are capable of using socially derived information to learn about novel features in their environment. The results likely have important implications for behavioural processes, ecotourism and fisheries.
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Krause, J., James, R., Franks, D. W., & Croft, D. P. (2015). Animal Social Networks. Oxford: Oxford University Press.
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