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Sih, A.; Hanser, S.; McHugh, K. |
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Social network theory: new insights and issues for behavioral ecologists |
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2009 |
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Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
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7 |
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975-988 |
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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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Equine Behaviour @ team @ |
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4990 |
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Whitehead, H. |
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Title |
SOCPROG programs: analysing animal social structures |
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Year |
2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
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5 |
Pages |
765-778 |
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Social analysis – Software – Association |
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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. |
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Equine Behaviour @ team @ |
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5026 |
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Lusseau, D.; Conradt, L. |
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Title |
The emergence of unshared consensus decisions in bottlenose dolphins |
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2009 |
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Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
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7 |
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1067-1077 |
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Behavioral ecology – Decision-making process – Bottlenose dolphin – Group living |
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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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Equine Behaviour @ team @ |
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5109 |
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Author |
Eagle, N.; Pentland, A. |
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Title |
Eigenbehaviors: identifying structure in routine |
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Year |
2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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Volume |
63 |
Issue |
7 |
Pages |
1057-1066-1066 |
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Biomedical and Life Sciences |
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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. |
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Springer Berlin / Heidelberg |
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0340-5443 |
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Equine Behaviour @ team @ |
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5189 |
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Fischhoff, I.; Dushoff, J.; Sundaresan, S.; Cordingley, J.; Rubenstein, D. |
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Title |
Reproductive status influences group size and persistence of bonds in male plains zebra (Equus burchelli) |
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Journal Article |
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2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
Issue |
7 |
Pages |
1035-1043-1043 |
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Biomedical and Life Sciences |
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Animal groups arise from individuals’ choices about the number, characteristics, and identity of associates. Individuals make these choices to gain benefits from their associations. As the needs of an individual change with its phenotype, so too we expect the nature of its associations to vary. In this paper, we investigate how the social priorities of male plains zebra (Equus burchelli) depend on reproductive state. An adult male is either a bachelor, and lacking mating access, or a stallion defending a harem. Multiple harems and bachelor males aggregate in larger herds. Herds frequently split and merge, affording males opportunities to change associates. Over a 4-year period, we sampled the herd associations in a population of 500–700 zebras. To isolate the effects of reproductive state on male social behavior, we account for potential confounding factors: changes in population size, grouping tendencies, and sampling intensity. We develop a generally applicable permutation procedure, which allows us to test the null hypothesis that social behavior is independent of male status. Averaging over all individuals in the population, we find that a typical bachelor is found in herds containing significantly more adults, bachelors, and stallions than the herds of a typical stallion. Further, bachelors’ bonds with each other are more persistent over time than those among stallions. These results suggest that bachelors form cohesive cliques, in which we may expect cooperative behaviors to develop. Stallion–stallion associations are more diffuse, and less conducive to long-term cooperation. |
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Springer Berlin / Heidelberg |
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0340-5443 |
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Equine Behaviour @ team @ |
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5193 |
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Author |
Franks, D.; James, R.; Noble, J.; Ruxton, G. |
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Title |
A foundation for developing a methodology for social network sampling |
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Journal Article |
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Year |
2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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Volume |
63 |
Issue |
7 |
Pages |
1079-1088-1088 |
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Biomedical and Life Sciences |
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Researchers are increasingly turning to network theory to understand the social nature of animal populations. We present a computational framework that is the first step in a series of works that will allow us to develop a quantitative methodology of social network sampling to aid ecologists in their social network data collection. To develop our methodology, we need to be able to generate networks from which to sample. Ideally, we need to perform a systematic study of sampling protocols on different known network structures, as network structure might affect the robustness of any particular sampling methodology. Thus, we present a computational tool for generating network structures that have user-defined distributions for network properties and for key measures of interest to ecologists. The user defines the values of these measures and the tool will generate appropriate network randomizations with those properties. This tool will be used as a framework for developing a sampling methodology, although we do not present a full methodology here. We describe the method used by the tool, demonstrate its effectiveness, and discuss how the tool can now be utilized. We provide a proof-of-concept example (using the assortativity measure) of how such networks can be used, along with a simulated egocentric sampling regime, to test the level of equivalence of the sampled network to the actual network. |
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Springer Berlin / Heidelberg |
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0340-5443 |
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Equine Behaviour @ team @ |
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5194 |
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Author |
Henzi, S.; Lusseau, D.; Weingrill, T.; van Schaik, C.; Barrett, L. |
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Title |
Cyclicity in the structure of female baboon social networks |
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2009 |
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Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
Issue |
7 |
Pages |
1015-1021-1021 |
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Biomedical and Life Sciences |
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There is an established and very influential view that primate societies have identifiable, persistent social organizations. It assumes that association patterns reflect long-term strategic interests that are not qualitatively perturbed by short-term environmental variability. We used data from two baboon troops in markedly different habitats over three consecutive seasons to test this assumption. Our results demonstrate pronounced cyclicity in the extent to which females maintained differentiated relationships. When food was plentiful, the companionships identified by social network analysis in the food-scarce season disappeared and were replaced by casual acquaintanceships more representative of mere gregariousness. Data from the fourth, food-scarce, season at one site indicated that few companions were re-united. It is likely that this reflected stochastic variation in individual circumstances. These results suggest that attention could profitably be paid to the effects of short-term local contingencies on social dynamics, and has implications for current theories of primate cognitive evolution. |
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Springer Berlin / Heidelberg |
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0340-5443 |
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Equine Behaviour @ team @ |
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5203 |
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Author |
James, R.; Croft, D.; Krause, J. |
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Title |
Potential banana skins in animal social network analysis |
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Journal Article |
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2009 |
Publication |
Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
Issue |
7 |
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989-997-997 |
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Biomedical and Life Sciences |
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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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Springer Berlin / Heidelberg |
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0340-5443 |
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Equine Behaviour @ team @ |
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5206 |
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Krause, S.; Mattner, L.; James, R.; Guttridge, T.; Corcoran, M.; Gruber, S.; Krause, J. |
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Social network analysis and valid Markov chain Monte Carlo tests of null models |
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Journal Article |
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2009 |
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Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
Issue |
7 |
Pages |
1089-1096-1096 |
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Biomedical and Life Sciences |
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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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Springer Berlin / Heidelberg |
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Equine Behaviour @ team @ |
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5208 |
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Krause, J.; Lusseau, D.; James, R. |
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Animal social networks: an introduction |
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2009 |
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Behavioral Ecology and Sociobiology |
Abbreviated Journal |
Behav. Ecol. Sociobiol. |
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63 |
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7 |
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967-973-973 |
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Biomedical and Life Sciences |
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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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Springer Berlin / Heidelberg |
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Equine Behaviour @ team @ |
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5209 |
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