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Saleh, N., & Chittka, L. (2006). The importance of experience in the interpretation of conspecific chemical signals. Behav. Ecol. Sociobiol., 61(2), 215–220.
Abstract: Abstract Foraging bumblebees scent mark flowers with hydrocarbon secretions. Several studies have found these scent marks act as a repellent to bee foragers. This was thought to minimize the risk of visiting recently depleted flowers. Some studies, however, have found a reverse, attractive effect of scent marks left on flowers. Do bees mark flowers with different scents, or could the same scent be interpreted differently depending on the bees? previous experience with reward levels in flowers? We use a simple experimental design to investigate if the scent marks can become attractive when bees forage on artificial flowers that remain rewarding upon the bees? return after having depleted them. We contrast this with bees trained in the more natural scenario where revisits to recently emptied flowers are unrewarding. The bees association between scent mark and reward value was tested with flowers scent marked from the same source. We find that the bees experience with the level of reward determines how the scent mark is interpreted: the same scent can act as both an attractant and a repellent. How experience and learning influence the interpretation of the meaning of chemical signals deposited by animals for communication has rarely been investigated.
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Ferrari, M. C. O., Capitania-Kwok, T., & Chivers, D. P. (2006). The role of learning in the acquisition of threat-sensitive responses to predator odours. Behav. Ecol. Sociobiol., 60(4), 522–527.
Abstract: The supposition that prey animals respond to a predator with an intensity that matches the risk posed by the predator is known as the threat-sensitive predator avoidance hypothesis. Many studies have provided support for this hypothesis; yet, few studies have attempted to determine how such abilities are acquired by prey species. In this study, we investigated whether fathead minnows (Pimephales promelas) could learn to recognize an unknown predator (northern pike, Esox lucius) in such a way that they could match the intensity of their antipredator response with the threat posed by the predator. We exposed pike-naive minnows to conspecific alarm cues paired with either a high or low concentration of pike odor. The following day, both groups were tested for a response to either high or low concentration of pike odor alone. We found that minnows conditioned with alarm cues paired with a given concentration of pike odor subsequently responded with a higher intensity to higher concentrations of pike odor, and with a lower intensity to lower concentrations of pike odor. These results demonstrate that during a single conditioning trial, minnows learn the identity of the predator in a threat-sensitive manner. Minnows use predator odor concentrations that they experience in subsequent interactions to adjust the intensity of their antipredator behavior. © Springer-Verlag 2006.
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Widdig, A., Streich, W., Nürnberg, P., Croucher, P., Bercovitch, F., & Krawczak, M. (2006). Paternal kin bias in the agonistic interventions of adult female rhesus macaques (Macaca mulatta). Behav. Ecol. Sociobiol., 61(2), 205–214.
Abstract: When agonistic interventions are nepotistic, individuals are expected to side more often with kin but less often against kin in comparison with non-kin. As yet, however, few mammal studies have been in a position to test the validity of this assertion with respect to paternal relatedness. We therefore used molecular genetic kinship testing to assess whether adult female rhesus macaques (Macaca mulatta) from the free-ranging colony of Cayo Santiago (Puerto Rico) bias their interventions in ongoing dyadic aggressive interactions towards maternal and paternal half-sisters compared with unrelated females. It turned out that females supported maternal half-sisters significantly more often than paternal half-sisters or non-kin regardless of the costs associated with such interventions. Similarly, females targeted maternal half-sisters significantly less often than non-kin when this was associated with high costs. Unrelated females provided significantly higher mean rates of both high- and low-cost support to each other than did paternal half-sisters. However, females targeted paternal half-sisters significantly less often than non-kin when targeting was at low cost, suggesting that females refrain from intervening against paternal half-sisters. Our data confirm the general view that coalition formation in female mammals is a function of both the level of maternal relatedness and of the costs of intervention. The patterns of coalition formation among paternal kin were found to be more complex, and may also differ across species, but clear evidence for paternal kin discrimination was observed in female rhesus as predicted by kin selection theory.
Keywords: Biomedical and Life Sciences
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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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Taillon, J., & Côté, S. (2008). Are faecal hormone levels linked to winter progression, diet quality and social rank in young ungulates ? An experiment with white-tailed deer ( Odocoileus virginianus ) fawns. Behav. Ecol. Sociobiol., 62(10), 675–677.
Abstract: Abstract Hormones play a central role in the physiology and behaviour of animals. The recent development of noninvasive techniques has increased information on physical and social states of individuals through hormone measurements. The relationships among hormones, life history traits and behaviours are, however, still poorly known. For the first time, we evaluated natural winter glucocorticoid and testosterone levels in young ungulates in relation to winter progression, diet quality and social rank. Overwinter, levels of glucocorticoid and testosterone decreased, possibly due to the decline of fawns" body mass. The relationships between hormone levels and diet quality were surprising: Fawns fed the control diet presented higher glucocorticoid and lower testosterone levels then fawns fed the poor diet, suggesting that control fawns faced a higher nutritional stress than those on the poor diet. Similarly to other studies on social mammals, we found no relationship between faecal glucocorticoid levels and social rank, suggesting that social stress was similar for dominant and subordinate fawns during winter. Testosterone levels were not correlated to social rank as found previously in groups of individuals forming stable social hierarchies and maintaining stable dominance relationships. The simultaneous suppression of glucocorticoid and testosterone levels suggests for the first time that young ungulates present a hormonal strategy to prevent fast depletion of limited proteins and fat resources during winter.
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Mirabet, V., Fréon, P., & Lett, C. (2008). Factors affecting information transfer from knowledgeable to naive individuals in groups. Behav. Ecol. Sociobiol., 63(2), 159-171.
Abstract: There is evidence that individuals in animal groups benefit from the presence of knowledgeable group members in different ways. Experiments and computer simulations have shown that a few individuals within a group can lead others, for a precise task and at a specific moment. As a group travels, different individuals possessing a particular knowledge may act as temporary leaders, so that the group will, as a whole, follow their behaviour. In this paper, we use a model to study different factors influencing group response to temporary leadership. The model is based on four individual behaviours. Three of those, attraction, repulsion, and alignment, are shared by all individuals. The last one, attraction toward the source of a stimulus, concerns only a fraction of the group members. We explore the influence of group size, proportion of stimulated individuals, number of influential neighbours, and intensity of the attraction to the source of the stimulus, on the proportion of the group reaching this source. Special attention is given to the simulation of large group size, close to those observed in nature. Groups of 100, 400 and 900 individuals are currently simulated, and up to 8,000 in one experiment. We show that more stimulated individuals and a larger group size both induce the arrival of a larger fraction of the group. The number of influential neighbours and the intensity of the stimulus have a non-linear influence on the proportion of the group arrival, displaying first a positive relationship and then, above a given threshold, a negative one. We conclude that an intermediate level of group cohesion provides optimal transfer information from knowledgeable to naive individuals.
Keywords: Biomedical and Life Sciences
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Sih, A., Hanser, S., & McHugh, K. (2009). Social network theory: new insights and issues for behavioral ecologists. Behav. Ecol. Sociobiol., 63(7), 975–988.
Abstract: Abstract Until recently, few studies have used social network theory (SNT) and metrics to examine how social network structure (SNS) might influence social behavior and social dynamics in non-human animals. Here, we present an overview of why and how the social network approach might be useful for behavioral ecology. We first note four important aspects of SNS that are commonly observed, but relatively rarely quantified: (1) that within a social group, differences among individuals in their social experiences and connections affect individual and group outcomes; (2) that indirect connections can be important (e.g., partners of your partners matter); (3) that individuals differ in their importance in the social network (some can be considered keystone individuals); and (4) that social network traits often carry over across contexts (e.g., SN position in male–male competition can influence later male mating success). We then discuss how these four points, and the social network approach in general, can yield new insights and questions for a broad range of issues in behavioral ecology including: mate choice, alternative mating tactics, male–male competition, cooperation, reciprocal altruism, eavesdropping, kin selection, dominance hierarchies, social learning, information flow, social foraging, and cooperative antipredator behavior. Finally, we suggest future directions including: (1) integrating behavioral syndromes and SNT; (2) comparing space use and SNS; (3) adaptive partner choice and SNS; (4) the dynamics and stability (or instability) of social networks, and (5) group selection shaping SNS.
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Whitehead, H. (2009). SOCPROG programs: analysing animal social structures. Behav. Ecol. Sociobiol., 63(5), 765–778.
Abstract: Abstract SOCPROG is a set of programs which analyses data on animal associations. Data usually come from observations of the social behaviour of individually identifiable animals. Associations among animals, sampling periods, restrictions on the data and association indices can be defined very flexibly. SOCPROG can analyse data sets including 1,000 or more individuals. Association matrices are displayed using sociograms, principal coordinates analysis, multidimensional scaling and cluster analyses. Permutation tests, Mantel and related tests and matrix correlation methods examine hypotheses about preferred associations among individuals and classes of individual. Weighted network statistics are calculated and can be tested against null hypotheses. Temporal analyses include displays of lagged association rates (rates of reassociation following an association). Models can be fitted to lagged association rates. Multiple association measures, including measures produced by other programs such as genetic or range use data, may be analysed using Mantel tests and principal components analysis. SOCPROG also performs mark-recapture population analyses and movement analyses. SOCPROG is written in the programming language MATLAB and may be downloaded free from the World Wide Web.
Keywords: Social analysis – Software – Association
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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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Eagle, N., & Pentland, A. (2009). Eigenbehaviors: identifying structure in routine. Behav. Ecol. Sociobiol., 63(7), 1057-1066.
Abstract: Longitudinal behavioral data generally contains a significant amount of structure. In this work, we identify the structure inherent in daily behavior with models that can accurately analyze, predict, and cluster multimodal data from individuals and communities within the social network of a population. We represent this behavioral structure by the principal components of the complete behavioral dataset, a set of characteristic vectors we have termed eigenbehaviors. In our model, an individual’s behavior over a specific day can be approximated by a weighted sum of his or her primary eigenbehaviors. When these weights are calculated halfway through a day, they can be used to predict the day’s remaining behaviors with 79% accuracy for our test subjects. Additionally, we demonstrate the potential for this dimensionality reduction technique to infer community affiliations within the subjects’ social network by clustering individuals into a behavior space spanned by a set of their aggregate eigenbehaviors. These behavior spaces make it possible to determine the behavioral similarity between both individuals and groups, enabling 96% classification accuracy of community affiliations within the population-level social network. Additionally, the distance between individuals in the behavior space can be used as an estimate for relational ties such as friendship, suggesting strong behavioral homophily amongst the subjects. This approach capitalizes on the large amount of rich data previously captured during the Reality Mining study from mobile phones continuously logging location, proximate phones, and communication of 100 subjects at MIT over the course of 9 months. As wearable sensors continue to generate these types of rich, longitudinal datasets, dimensionality reduction techniques such as eigenbehaviors will play an increasingly important role in behavioral research.
Keywords: Biomedical and Life Sciences
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