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Healy, S. D., & Jones, C. M. (2002). Animal learning and memory: an integration of cognition and ecology. Zoology, 105(4), 321–327.
Abstract: Summary A wonderfully lucid framework for the ways to understand animal behaviour is that represented by the four [`]whys' proposed by Tinbergen (1963). For much of the past three decades, however, these four avenues have been pursued more or less in parallel. Functional questions, for example, have been addressed by behavioural ecologists, mechanistic questions by psychologists and ethologists, ontogenetic questions by developmental biologists and neuroscientists and phylogenetic questions by evolutionary biologists. More recently, the value of integration between these differing views has become apparent. In this brief review, we concentrate especially on current attempts to integrate mechanistic and functional approaches. Most of our understanding of learning and memory in animals comes from the psychological literature, which tends to use only rats or pigeons, and more occasionally primates, as subjects. The underlying psychological assumption is of general processes that are similar across species and contexts rather than a range of specific abilities. However, this does not seem to be entirely true as several learned behaviours have been described that are specific to particular species or contexts. The first conspicuous exception to the generalist assumption was the demonstration of long delay taste aversion learning in rats (Garcia et al., 1955), in which it was shown that a stimulus need not be temporally contiguous with a response for the animal to make an association between food and illness. Subsequently, a number of other examples, such as imprinting and song learning in birds (e.g., Bolhuis and Honey, 1998; Catchpole and Slater, 1995; Horn, 1998), have been thoroughly researched. Even in these cases, however, it has been typical for only a few species to be studied (domestic chicks provide the [`]model' imprinting species and canaries and zebra finches the song learning [`]models'). As a result, a great deal is understood about the neural underpinnings and development of the behaviour, but substantially less is understood about interspecific variation and whether variation in behaviour is correlated with variation in neural processing (see review by Tramontin and Brenowitz, 2000 but see ten Cate and Vos, 1999).
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Bouchard, J. (2002). Is social learning correlated with innovation in birds? An inter-and an interspecific test. Master's thesis, Department of Biology McGili University Montréal, Québec, .
Abstract: This thesis focuses on the relationship between innovation and social learning in the foraging context, across and within bird species, using two different sources of data: anecdotal reports from the literature, and experimental tests in the laboratory and the field. In chapter 1, I review the trends in innovation and social learning in the avian literature, and contrast them with trends in mammals, especially primates. In chapter 2, I use anecdotal reports of feeding innovation and social learning in the literature to assess taxonomic trends and to study the relationship between the two traits at the interspecific level. In chapter 3, I investigate the relationship between innovation and social learning at the intraspecific level in captive feral pigeons (Columba livia). Innovation is estimated from the ability to solve an innovative foraging problem, and social learning is measured as the number of trials required to learn a foraging task from a proficient demonstrator. (Abstract shortened by UMI.)
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Fehr, E., & Gachter, S. (2002). Altruistic punishment in humans. Nature, 415(6868), 137–140.
Abstract: Human cooperation is an evolutionary puzzle. Unlike other creatures, people frequently cooperate with genetically unrelated strangers, often in large groups, with people they will never meet again, and when reputation gains are small or absent. These patterns of cooperation cannot be explained by the nepotistic motives associated with the evolutionary theory of kin selection and the selfish motives associated with signalling theory or the theory of reciprocal altruism. Here we show experimentally that the altruistic punishment of defectors is a key motive for the explanation of cooperation. Altruistic punishment means that individuals punish, although the punishment is costly for them and yields no material gain. We show that cooperation flourishes if altruistic punishment is possible, and breaks down if it is ruled out. The evidence indicates that negative emotions towards defectors are the proximate mechanism behind altruistic punishment. These results suggest that future study of the evolution of human cooperation should include a strong focus on explaining altruistic punishment.
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Soproni, K., Miklósi, Á., Topál, J., & Csányi, V. (2002). Dogs' (Canis familiaris) responsiveness to human pointing gestures. J Comp Psychol, 116(1), 27–34.
Abstract: In a series of 3 experiments, dogs (Canis familiaris) were presented with variations of the human pointing gesture: gestures with reversed direction of movement, cross-pointing, and different arm extensions. Dogs performed at above chance level if they could see the hand (and index finger) protruding from the human body contour. If these minimum requirements were not accessible, dogs still could rely on the body position of the signaler. The direction of movement of the pointing arm did not influence the performance. In summary, these observations suggest that dogs are able to rely on relatively novel gestural forms of the human communicative pointing gesture and that they are able to comprehend to some extent the referential nature of human pointing.
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Katherine Faust, & John Skvoretz. (2002). Comparing Networks Across Space and Time, Size and Species. Socio Meth, 32(1), 267–299.
Abstract: We describe and illustrate methodology for comparing networks from diverse settings. Our empirical base consists of 42 networks from four kinds of species (humans, nonhuman primates, nonprimate mammals, and birds) and covering distinct types of relations such as influence, grooming, and agonistic encounters. The general problem is to determine whether networks are similarly structured despite their surface differences. The methodology we propose is generally applicable to the characterization and comparison of network2013level social structures across multiple settings, such as different organizations, communities, or social groups, and to the examination of sources of variability in network structure. We first fit a p* model (Wasserman and Pattison 1996) to each network to obtain estimates for effects of six structural properties on the probability of the graph. We then calculate predicted tie probabilities for each network, using both its own parameter estimates and the estimates from every other network in the collection. Comparison is based on the similarity between sets of predicted tie probabilities. We then use correspondence analysis to represent the similarities among all 42 networks and interpret the resulting configuration using information about the species and relations involved. Results show that similarities among the networks are due more to the kind of relation than to the kind of animal.
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Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002). Network Motifs: Simple Building Blocks of Complex Networks. Science, 298(5594), 824–827.
Abstract: Complex networks are studied across many fields of science. To uncover their structural design principles, we defined “network motifs,” patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This approach may uncover the basic building blocks of most networks.
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Hemelrijk, C. K. (2002). Understanding Social Behaviour with the Help of Complexity Science (Invited Article). Ethology, 108(8), 655–671.
Abstract: Abstract In the study of complexity, a new kind of explanation has been developed for social behaviour. It shows how patterns of social behaviour can arise as a side-effect of the interaction of individuals with their social or physical environment (e.g. by self-organization). This development may influence our ideas about the direct causation and evolution of social behaviour. Furthermore, it may influence our theories about the integration of different traits. This new method has been made possible by the increase in computing power. It is now applied in many areas of science, such as physics, chemistry, sociology and economics. However, in zoology and anthropology it is still rare. The major aim of this paper is to make this method more generally accepted among behavioural scientists.
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Hemelrijk, C. K. (2002). Self-Organization and Natural Selection in the Evolution of Complex Despotic Societies. Biol Bull, 202(3), 283–288.
Abstract: Differences between related species are usually explained as separate adaptations produced by individual selection. I discuss in this paper how related species, which differ in many respects, may evolve by a combination of individual selection, self-organization, and group-selection, requiring an evolutionary adaptation of only a single trait. In line with the supposed evolution of despotic species of macaques, we take as a starting point an ancestral species that is egalitarian and mildly aggressive. We suppose it to live in an environment with abundant food and we put the case that, if food becomes scarce and more clumped, natural selection at the level of the individual will favor individuals with a more intense aggression (implying, for instance, biting and fierce fighting). Using an individual-centered model, called DomWorld, I show what happens when the intensity of aggression increases. In DomWorld, group life is represented by artificial individuals that live in a homogeneous world. Individuals are extremely simple: all they do is flock together and, upon meeting one another, they may perform dominance interactions in which the effects of winning and losing are self-reinforcing. When the intensity of aggression in the model is increased, a complex feedback between the hierarchy and spatial structure results; via self-organization, this feedback causes the egalitarian society to change into a despotic one. The many differences between the two types of artificial society closely correspond to those between despotic and egalitarian macaques in the real world. Given that, in the model, the organization changes as a side effect of the change of one single trait proper to an egalitarian society, in the real world a despotic society may also have arisen as a side effect of the mutation of a single trait of an egalitarian species. If groups with different intensities of aggression evolve in this way, they will also have different gradients of hierarchy. When food is scarce, groups with the steepest hierarchy may have the best chance to survive, because at least a small number of individuals in such a group may succeed in producing offspring, whereas in egalitarian societies every individual is at risk of being insufficiently fed to reproduce. Therefore, intrademic group selection (selection within an interbreeding group) may have contributed to the evolution of despotic societies. N1 -
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Borgatti, S. P., Everett, M.G., Freeman, L.C. (2002). Ucinet for Windows: Software for Social Network Analysis.
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Silk, J. B. (2002). Kin Selection in Primate Groups. Int. J. Primatol., 23(4), 849–875.
Abstract: Altruism poses a problem for evolutionary biologists because natural selection is not expected to favor behaviors that are beneficial to recipients, but costly to actors. The theory of kin selection, first articulated by Hamilton (1964), provides a solution to the problem. Hamilton's well-known rule (br > c) provides a simple algorithm for the evolution of altruism via kin selection. Because kin recognition is a crucial requirement of kin selection, it is important to know whether and how primates can recognize their relatives. While conventional wisdom has been that primates can recognize maternal kin, but not paternal kin, this view is being challenged by new findings. The ability to recognize kin implies that kin selection may shape altruistic behavior in primate groups. I focus on two cases in which kin selection is tightly woven into the fabric of social life. For female baboons, macaques, and vervets maternal kinship is an important axis of social networks, coalitionary activity, and dominance relationships. Detailed studies of the patterning of altruistic interactions within these species illustrate the extent and limits of nepotism in their social lives. Carefully integrated analyses of behavior, demography, and genetics among red howlers provide an independent example of how kin selection shapes social organization and behavior. In red howlers, kin bonds shape the life histories and reproductive performance of both males and female. The two cases demonstrate that kin selection can be a powerful source of altruistic activity within primate groups. However, to fully assess the role of kin selection in primate groups, we need more information about the effects of kinship on the patterning of behavior across the Primates and accurate information about paternal kin relationships.
Keywords: Biomedical and Life Sciences
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