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Croft, D. P., James, R., & Krause, J. (2008). Comparing Networks. In Exploring Animal Social Networks (pp. 141–162). Princeton, NY: Princton University Press.
Abstract: Social network analysis is used widely in the social sciences to study interactions among people, groups, and organizations, yet until now there has been no book that shows behavioral biologists how to apply it to their work on animal populations. Exploring Animal Social Networks provides a practical guide for researchers, undergraduates, and graduate students in ecology, evolutionary biology, animal behavior, and zoology.
Existing methods for studying animal social structure focus either on one animal and its interactions or on the average properties of a whole population. This book enables researchers to probe animal social structure at all levels, from the individual to the population. No prior knowledge of network theory is assumed. The authors give a step-by-step introduction to the different procedures and offer ideas for designing studies, collecting data, and interpreting results. They examine some of today's most sophisticated statistical tools for social network analysis and show how they can be used to study social interactions in animals, including cetaceans, ungulates, primates, insects, and fish. Drawing from an array of techniques, the authors explore how network structures influence individual behavior and how this in turn influences, and is influenced by, behavior at the population level. Throughout, the authors use two software packages--UCINET and NETDRAW--to illustrate how these powerful analytical tools can be applied to different animal social organizations.
Darren P. Croft is lecturer in animal behavior at the University of Wales, Bangor. Richard James is senior lecturer in physics at the University of Bath. Jens Krause is professor of behavioral ecology at the University of Leeds.
Reviews:
“Exploring Animal Social Networks shows behavioral biologists how to apply social network theory to animal populations. In doing so, Croft, James, and Krause illustrate the connections between an animal's individual behaviors and how these, in turn, influence and are influenced by behavior at the population level. . . . Valuable for readers interested in using quantitative analyses to study animal social behaviors.”--Choice
“[T]his volume provides an engaging, accessible, and timely introduction to the use of network theory methods for examining the social behavior of animals.”--Noa Pinter-Wollman, Quarterly Review of Biology
“The book is a useful 'handbook' providing detailed, stepwise procedures sufficient to allow the reader to address a broad range of questions about social interactions. . . . The book includes numerous examples of the kind of research questions one might ask, and, thus, it allows the reader to find the analysis that best fits the data set to be analyzed. Thus, even readers with minimal prior knowledge of social network analysis will be able to apply this approach. And if further assistance is needed, the authors provide numerous references to specific procedures that have been used by others.”--Thomas R. Zentall, PsycCRITIQUES
Endorsements:
“An important and timely addition to the literature. This book should be readily accessible to researchers who are interested in animal social organization but who have little or no experience in conducting network analysis. The book is well-written in an engaging style and contains a good number of examples drawn from a range of taxonomic groups.”--Paul R. Moorcroft, Harvard University
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Table of Contents:
Preface vii
Chapter 1: Introduction to Social Networks 1
Chapter 2: Data Collection 19
Chapter 3: Visual Exploration 42
Chapter 4: Node-Based Measures 64
Chapter 5: Statistical Tests of Node-Based Measures 88
Chapter 6: Searching for Substructures 117
Chapter 7: Comparing Networks 141
Chapter 8: Conclusions 163
Glossary of Frequently Used Terms 173
References 175
Index 187
Subject Area:
* Biological Sciences
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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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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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Krause, J., James, R., Franks, D. W., & Croft, D. P. (2015). Animal Social Networks. Oxford: Oxford University Press.
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Gaunitz, C., Fages, A., Hanghøj, K., Albrechtsen, A., Khan, N., Schubert, M., et al. (2018). Ancient genomes revisit the ancestry of domestic and Przewalski's horses. Science, 360(6384), 111–114.
Abstract: The Eneolithic Botai culture of the Central Asian steppes provides the earliest archaeological evidence for horse husbandry, ~5,500 ya, but the exact nature of early horse domestication remains controversial. We generated 42 ancient horse genomes, including 20 from Botai. Compared to 46 published ancient and modern horse genomes, our data indicate that Przewalski's horses are the feral descendants of horses herded at Botai and not truly wild horses. All domestic horses dated from ~4,000 ya to present only show ~2.7% of Botai-related ancestry. This indicates that a massive genomic turnover underpins the expansion of the horse stock that gave rise to modern domesticates, which coincides with large-scale human population expansions during the Early Bronze Age.
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Conradt, L., Krause, J., Couzin, I. D., & Roper, T. J. (2009). “Leading According to Need” in Self-Organizing Groups. Am Nat, 173(3), 304–312.
Abstract: Self‐organizing‐system approaches have shed significant light on the mechanisms underlying synchronized movements by large groups of animals, such as shoals of fish, flocks of birds, or herds of ungulates. However, these approaches rarely consider conflicts of interest between group members, although there is reason to suppose that such conflicts are commonplace. Here, we demonstrate that, where conflicts exist, individual members of self‐organizing groups can, in principle, increase their influence on group movement destination by strategically changing simple behavioral parameters (namely, movement speed, assertiveness, and social attraction range). However, they do so at the expense of an increased risk of group fragmentation and a decrease in movement efficiency. We argue that the resulting trade‐offs faced by each group member render it likely that group movements are led by those members for which reaching a particular destination is most crucial or group cohesion is least important. We term this phenomenon leading according to “need” or “social indifference,” respectively. Both kinds of leading can occur in the absence of knowledge of or communication about the needs of other group members and without the assumption of altruistic cooperation. We discuss our findings in the light of observations on fish and other vertebrates.
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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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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., Bumann, D., & Todt, D. (1992). Relationship between the position preference and nutritional state of individuals in schools of juvenile roach (Rutilus rutilus). Behav. Ecol. Sociobiol., 30(3), 177–180.
Abstract: Position preferences of well-fed and food-deprived juvenile roach were investigated in schools of 2 and 4 fish in the laboratory. Food-deprived fish appeared significantly more often in the front position than their well-fed conspecifics. For fish at the same hunger level, individuals at the front of the school had the highest feeding rate. These results represent the first evidence for a relationship between the nutritional state of individual fish and their positions in a school and suggest a functional advantage of the preference.
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Krause, J., Croft, D., & James, R. (2007). Social network theory in the behavioural sciences: potential applications. Behav. Ecol. Sociobiol., 62(1), 15–27.
Abstract: Abstract Social network theory has made major contributions to our understanding of human social organisation but has found relatively little application in the field of animal behaviour. In this review, we identify several broad research areas where the networks approach could greatly enhance our understanding of social patterns and processes in animals. The network theory provides a quantitative framework that can be used to characterise social structure both at the level of the individual and the population. These novel quantitative variables may provide a new tool in addressing key questions in behavioural ecology particularly in relation to the evolution of social organisation and the impact of social structure on evolutionary processes. For example, network measures could be used to compare social networks of different species or populations making full use of the comparative approach. However, the networks approach can in principle go beyond identifying structural patterns and also can help with the understanding of processes within animal populations such as disease transmission and information transfer. Finally, understanding the pattern of interactions in the network (i.e. who is connected to whom) can also shed some light on the evolution of behavioural strategies.
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