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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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Chase, I. D., Tovey, C., Spangler-Martin, D., & Manfredonia, M. (2002). Individual differences versus social dynamics in the formation of animal dominance hierarchies. Proc. Natl. Acad. Sci. U.S.A., 99(8), 5744–5749.
Abstract: Linear hierarchies, the classical pecking-order structures, are formed readily in both nature and the laboratory in a great range of species including humans. However, the probability of getting linear structures by chance alone is quite low. In this paper we investigate the two hypotheses that are proposed most often to explain linear hierarchies: they are predetermined by differences in the attributes of animals, or they are produced by the dynamics of social interaction, i.e., they are self-organizing. We evaluate these hypotheses using cichlid fish as model animals, and although differences in attributes play a significant part, we find that social interaction is necessary for high proportions of groups with linear hierarchies. Our results suggest that dominance hierarchy formation is a much richer and more complex phenomenon than previously thought, and we explore the implications of these results for evolutionary biology, the social sciences, and the use of animal models in understanding human social organization.
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Seyfarth, R. M., & Cheney, D. L. (2002). What are big brains for? Proc. Natl. Acad. Sci. U.S.A., 99(7), 4141–4142.
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Jansen, T., Forster, P., Levine, M. A., Oelke, H., Hurles, M., Renfrew, C., et al. (2002). Mitochondrial DNA and the origins of the domestic horse. Proc. Natl. Acad. Sci. U.S.A., 99(16), 10905–10910.
Abstract: The place and date of the domestication of the horse has long been a matter for debate among archaeologists. To determine whether horses were domesticated from one or several ancestral horse populations, we sequenced the mitochondrial D-loop for 318 horses from 25 oriental and European breeds, including American mustangs. Adding these sequences to previously published data, the total comes to 652, the largest currently available database. From these sequences, a phylogenetic network was constructed that showed that most of the 93 different mitochondrial (mt)DNA types grouped into 17 distinct phylogenetic clusters. Several of the clusters correspond to breeds and/or geographic areas, notably cluster A2, which is specific to Przewalski's horses, cluster C1, which is distinctive for northern European ponies, and cluster D1, which is well represented in Iberian and northwest African breeds. A consideration of the horse mtDNA mutation rate together with the archaeological timeframe for domestication requires at least 77 successfully breeding mares recruited from the wild. The extensive genetic diversity of these 77 ancestral mares leads us to conclude that several distinct horse populations were involved in the domestication of the horse.
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Reader, S. M., & Laland, K. N. (2002). Social intelligence, innovation, and enhanced brain size in primates. Proc. Natl. Acad. Sci. U.S.A., 99(7), 4436–4441.
Abstract: Despite considerable current interest in the evolution of intelligence, the intuitively appealing notion that brain volume and “intelligence” are linked remains untested. Here, we use ecologically relevant measures of cognitive ability, the reported incidence of behavioral innovation, social learning, and tool use, to show that brain size and cognitive capacity are indeed correlated. A comparative analysis of 533 instances of innovation, 445 observations of social learning, and 607 episodes of tool use established that social learning, innovation, and tool use frequencies are positively correlated with species' relative and absolute “executive” brain volumes, after controlling for phylogeny and research effort. Moreover, innovation and social learning frequencies covary across species, in conflict with the view that there is an evolutionary tradeoff between reliance on individual experience and social cues. These findings provide an empirical link between behavioral innovation, social learning capacities, and brain size in mammals. The ability to learn from others, invent new behaviors, and use tools may have played pivotal roles in primate brain evolution.
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Broom, M. (2002). A unified model of dominance hierarchy formation and maintenance. J. Theor. Biol., 219(1), 63–72.
Abstract: In many different species it is common for animals to spend large portions of their lives in groups. Such groups need to divide available resources amongst the individuals they contain and this is often achieved by means of a dominance hierarchy. Sometimes hierarchies are stable over a long period of time and new individuals slot into pre-determined positions, but there are many situations where this is not so and a hierarchy is formed out of a group of individuals meeting for the first time. There are several different models both of the formation of such dominance hierarchies and of already existing hierarchies. These models often treat the two phases as entirely separate, whereas in reality, if there is a genuine formation phase to the hierarchy, behaviour in this phase will be governed by the rewards available, which in turn depends upon how the hierarchy operates once it has been formed. This paper describes a method of unifying models of these two distinct phases, assuming that the hierarchy formed is stable. In particular a framework is introduced which allows a variety of different models of each of the two parts to be used in conjunction with each other, thus enabling a wide range of situations to be modelled. Some examples are given to show how this works in practice.
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Viscido, S. V., Miller, M., & Wethey, D. S. (2002). The dilemma of the selfish herd: the search for a realistic movement rule. J. Theor. Biol., 217(2), 183–194.
Abstract: The selfish herd hypothesis predicts that aggregations form because individuals move toward one another to minimize their own predation risk. The “dilemma of the selfish herd” is that movement rules that are easy for individuals to follow, fail to produce true aggregations, while rules that produce aggregations require individual behavior so complex that one may doubt most animals can follow them. If natural selection at the individual level is responsible for herding behavior, a solution to the dilemma must exist. Using computer simulations, we examined four different movement rules. Relative predation risk was different for all four movement rules (p<0.05). We defined three criteria for measuring the quality of a movement rule. A good movement rule should (a) be statistically likely to benefit an individual that follows it, (b) be something we can imagine most animals are capable of following, and (c) result in a centrally compact flock. The local crowded horizon rule, which allowed individuals to take the positions of many flock-mates into account, but decreased the influence of flock-mates with distance, best satisfied these criteria. The local crowded horizon rule was very sensitive to the animal's perceptive ability. Therefore, the animal's ability to detect its neighbors is an important factor in the dynamics of group formation.
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Couzin, I. D., Krause, J., James, R., Ruxton, G. D., & Franks, N. R. (2002). Collective Memory and Spatial Sorting in Animal Groups. J. Theor. Biol., 218(1), 1–11.
Abstract: We present a self-organizing model of group formation in three-dimensional space, and use it to investigate the spatial dynamics of animal groups such as fish schools and bird flocks. We reveal the existence of major group-level behavioural transitions related to minor changes in individual-level interactions. Further, we present the first evidence for collective memory in such animal groups (where the previous history of group structure influences the collective behaviour exhibited as individual interactions change) during the transition of a group from one type of collective behaviour to another. The model is then used to show how differences among individuals influence group structure, and how individuals employing simple, local rules of thumb, can accurately change their spatial position within a group (e.g. to move to the centre, the front, or the periphery) in the absence of information on their current position within the group as a whole. These results are considered in the context of the evolution and ecological importance of animal groups.
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Zentall, T. R., Galizio, M., & Critchfied, T. S. (2002). Categorization, concept learning, and behavior analysis: an introduction. J Exp Anal Behav, 78(3), 237–248.
Abstract: Categorization and concept learning encompass some of the most important aspects of behavior, but historically they have not been central topics in the experimental analysis of behavior. To introduce this special issue of the Journal of the Experimental Analysis of Behavior (JEAB), we define key terms; distinguish between the study of concepts and the study of concept learning; describe three types of concept learning characterized by the stimulus classes they yield; and briefly identify several other themes (e.g., quantitative modeling and ties to language) that appear in the literature. As the special issue demonstrates, a surprising amount and diversity of work is being conducted that either represents a behavior-analytic perspective or can inform or constructively challenge this perspective.
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Zentall, T. R. (2002). A cognitive behaviorist approach to the study of animal behavior. J Gen Psychol, 129(4), 328–363.
Abstract: Traditional psychological approaches to animal learning and behavior have involved either the atheoretical behaviorist approach proposed by B. F. Skinner (1938), in which input-output relations are described in response to environmental manipulations, or the theoretical behaviorist approach offered by C. L Hull (1943), in which associations mediated by several hypothetical constructs and intervening variables are formed between stimuli and responses. Recently, the application of a cognitive behaviorist approach to animal learning and behavior has been found to have considerable value as a research tool. This perspective has grown out of E. C. Tolman's cognitive approach to learning in which behavior is mediated by mechanisms that are not directly observable but can be inferred from the results of critical experiments. In the present article, the author presents several examples of the successful application of the cognitive behaviorist approach. In each case, the experiments have been designed to distinguish between more traditional mechanisms and those mediated by hypothesized internal representations. These examples were selected because the evidence suggests that some form of active cognitive organization is needed to account for the behavioral results.
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