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Nowak, M. A., & Sigmund, K. (1992). Tit for tat in heterogeneous populations. Nature, 355, 250–253.
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Maynard Smith, J., & Price, G. R. (1973). The Logic of Animal Conflict. Nature, 246, 15–18.
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Hamilton, W. D. (1970). Selfish and Spiteful Behaviour in an Evolutionary Model. Nature, 228, 1218–1220.
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Reeve, H. K. (1992). Queen activation of lazy workers in colonies of the eusocial naked mole-rat. Nature, 358, 147–149.
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Watts, D. J., & Strogatz, S. H. (1998). Collective dynamics of /`small-world/' networks. Nature, 393(6684), 440–442.
Abstract: Networks of coupled dynamical systems have been used to model biological oscillators Josephson junction arrays excitable media, neural networks spatial games11, genetic control networks12 and many other self-organizing systems. Ordinarily, the connection topology is assumed to be either completely regular or completely random. But many biological, technological and social networks lie somewhere between these two extremes. Here we explore simple models of networks that can be tuned through this middle ground: regular networks 'rewired' to introduce increasing amounts of disorder. We find that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs. We call them 'small-world' networks, by analogy with the small-world phenomenon (popularly known as six degrees of separation). The neural network of the worm Caenorhabditis elegans, the power grid of the western United States, and the collaboration graph of film actors are shown to be small-world networks. Models of dynamical systems with small-world coupling display enhanced signal-propagation speed, computational power, and synchronizability. In particular, infectious diseases spread more easily in small-world networks than in regular lattices.
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Conradt, L., & Roper, T. J. (2003). Group decision-making in animals. Nature, 421(6919), 155–158.
Abstract: Groups of animals often need to make communal decisions, for example about which activities to perform, when to perform them and which direction to travel in; however, little is known about how they do so. Here, we model the fitness consequences of two possible decision-making mechanisms: 'despotism' and 'democracy'. We show that under most conditions, the costs to subordinate group members, and to the group as a whole, are considerably higher for despotic than for democratic decisions. Even when the despot is the most experienced group member, it only pays other members to accept its decision when group size is small and the difference in information is large. Democratic decisions are more beneficial primarily because they tend to produce less extreme decisions, rather than because each individual has an influence on the decision per se. Our model suggests that democracy should be widespread and makes quantitative, testable predictions about group decision-making in non-humans.
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Rands, S. A., Cowlishaw, G., Pettifor, R. A., Rowcliffe, J. M., & Johnstone, R. A. (2003). Spontaneous emergence of leaders and followers in foraging pairs. Nature, 423(6938), 432–434.
Abstract: Animals that forage socially often stand to gain from coordination of their behaviour. Yet it is not known how group members reach a consensus on the timing of foraging bouts. Here we demonstrate a simple process by which this may occur. We develop a state-dependent, dynamic game model of foraging by a pair of animals, in which each individual chooses between resting or foraging during a series of consecutive periods, so as to maximize its own individual chances of survival. We find that, if there is an advantage to foraging together, the equilibrium behaviour of both individuals becomes highly synchronized. As a result of this synchronization, differences in the energetic reserves of the two players spontaneously develop, leading them to adopt different behavioural roles. The individual with lower reserves emerges as the 'pace-maker' who determines when the pair should forage, providing a straightforward resolution to the problem of group coordination. Moreover, the strategy that gives rise to this behaviour can be implemented by a simple 'rule of thumb' that requires no detailed knowledge of the state of other individuals.
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Potts, W. K., Manning, C. J., & Wakeland, E. K. (1991). Mating patterns in seminatural populations of mice influenced by MHC genotype. Nature, 352(6336), 619–621.
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Barton, N. (1998). Evolutionary biology: The geometry of adaptation. Nature, 395(6704), 751–752.
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Moon, C., Baldridge, M. T., Wallace, M. A., Burnham, C. - A. D., Virgin, H. W., & Stappenbeck, T. S. (2015). Vertically transmitted faecal IgA levels determine extra-chromosomal phenotypic variation. Nature, 521(7550), 90–93.
Abstract: The proliferation of genetically modified mouse models has exposed phenotypic variation between investigators and institutions that has been challenging to control1-5. In many cases, the microbiota is the presumed culprit of the variation. Current solutions to account for phenotypic variability include littermate and maternal controls or defined microbial consortia in gnotobiotic mice6,7. In conventionally raised mice, the microbiome is transmitted from the dam2,8,9. Here we show that microbially–driven dichotomous fecal IgA levels in WT mice within the same facility mimic the effects of chromosomal mutations. We observed in multiple facilities that vertically-transmissible bacteria in IgA-Low mice dominantly lowered fecal IgA levels in IgA-High mice after cohousing or fecal transplantation. In response to injury, IgA-Low mice showed increased damage that was transferable by fecal transplantation and driven by fecal IgA differences. We found that bacteria from IgA-Low mice degraded the secretory component (SC) of SIgA as well as IgA itself. These data indicate that phenotypic comparisons between mice must take into account the non-chromosomal hereditary variation between different breeders. We propose fecal IgA as one marker of microbial variability and conclude that cohousing and/or fecal transplantation enables analysis of progeny from different dams.
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