Lusseau, D., & Conradt, L. (2009). The emergence of unshared consensus decisions in bottlenose dolphins. Behav. Ecol. Sociobiol., 63(7), 1067–1077.
Abstract: Abstract Unshared consensus decision-making processes, in which one or a small number of individuals make the decision for the rest of a group, are rarely documented. However, this mechanism can be beneficial for all group members when one individual has greater knowledge about the benefits of the decision than other group members. Such decisions are reached during certain activity shifts within the population of bottlenose dolphins residing in Doubtful Sound, New Zealand. Behavioral signals are performed by one individual and seem to precipitate shifts in the behavior of the entire group: males perform side flops and initiate traveling bouts while females perform upside-down lobtails and terminate traveling bouts. However, these signals are not observed at all activity shifts. We find that, while side flops were performed by males that have greater knowledge than other male group members, this was not the case for females performing upside-down lobtails. The reason for this could have been that a generally high knowledge about the optimal timing of travel terminations rendered it less important which individual female made the decision.
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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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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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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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Krama, T. [1], & Krams, I. [2]. (2005). Cost of mobbing call to breeding pied flycatcher, Ficedula hypoleuca. Behav. Ecol., 16, 37–40.
Abstract: Mobbing signals advertise the location of a stalking predator to all prey in an area and recruit them into the inspection aggregation. Such behavior usually causes the predator to move to another area. However, mobbing calls could be eavesdropped by other predators. Because the predation cost of mobbing calls is poorly known, we investigated whether the vocalizations of the mobbing pied flycatcher, Ficedula hypoleuca, a small hole nesting passerine, increase the risk of nest predation. We used mobbing calls of pied flycatchers to examine if they could lure predators such as the marten, Martes martes. This predator usually hunts by night and may locate its mobbing prey while resting nearby during the day. Within each of 56 experimental plots, from the top of one nest-box we played back mobbing sounds of pied flycatchers, whereas blank tapes were played from the top of another nest-box. The trials with mobbing calls were carried out before sunset. We put pieces of recently abandoned nests of pied flycatchers and a quail, Coturnix coturnix, egg into each of the nest-boxes. Nest-boxes with playbacks of mobbing calls were depredated by martens significantly more than were nest-boxes with blank tapes. The results of the present study indicate that repeated conspicuous mobbing calls may carry a significant cost for birds during the breeding season.
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Kirkpatrick, J. F., & Turner, J. W. (1991). Changes in herd stallions among feral horse bands and the absence of forced copulation and induced abortion. Behav. Ecol. Sociobiol., 29(3), 217–219.
Abstract: Forced copulation and induced abortion were investigated in a herd of feral horses inhabiting a coastal barrier island. Eight mares were diagnosed pregnant in August and October 1989 by means of urinary and fecal steroid metabolites, prior to documented changes in herd stallions. These mares were observed for harassment and forced copulation by the new stallions and for the presence of foals during the spring and summer of 1990. No incidents of harassment or attempts at forced copulation were witnessed and seven of the eight mares produced foals in 1990. These data indicate that forced copulation and induced abortion are not common events among all feral horse herds and suggest reinvestigation of this hypothesized phenomenon.
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Kavaliers, M., Colwell, D. D., & Choleris, E. (2005). Kinship, familiarity and social status modulate social learning about “micropredators” (biting flies) in deer mice. Behav. Ecol. Sociobiol., 58(1), 60–71.
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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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Hildenbrandt, H., Carere, C., & Hemelrijk, C. K. (2010). Self-organized aerial displays of thousands of starlings: a model. Behav. Ecol., 21(6), 1349–1359.
Abstract: Through combining theoretical models and empirical data, complexity science has increased our understanding of social behavior of animals, in particular of social insects, primates, and fish. What are missing are studies of collective behavior of huge swarms of birds. Recently detailed empirical data have been collected of the swarming maneuvers of large flocks of thousands of starlings (Sturnus vulgaris) at their communal sleeping site (roost). Their flocking maneuvers are of dazzling complexity in their changes in density and flock shape, but the processes underlying them are still a mystery. Recent models show that flocking may arise by self-organization from rules of co-ordination with nearby neighbors, but patterns in these models come nowhere near the complexity of those of the real starlings. The question of this paper, therefore, is whether such complex patterns can emerge by self-organization. In our computer model, called StarDisplay, we combine the usual rules of co-ordination based on separation, attraction, and alignment with specifics of starling behavior: 1) simplified aerodynamics of flight, especially rolling during turning, 2) movement above a “roosting area” (sleeping site), and 3) the low fixed number of interaction neighbors (i.e., the topological range). Our model generates patterns that resemble remarkably not only qualitative but also quantitative empirical data collected in Rome through video recordings and position measurements by stereo photography. Our results provide new insights into the mechanisms underlying complex flocking maneuvers of starlings and other birds.
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