Increased costs reduce reciprocal helping behaviour of humans in a virtual evacuation experiment

Altruistic behaviour is widespread and highly developed in humans and can also be found in some animal species. It has been suggested that altruistic tendencies can depend on costs, benefits and context. Here, we investigate the changes in the occurrence of helping behaviour in a computer-based experiment that simulates an evacuation from a building exploring the effect of varying the cost to help. Our findings illuminate a number of key mechanistic aspects of human decision-making about whether to help or not. In a novel situation where it is difficult to assess the risks associated with higher costs, we reproduce the finding that increasing costs reduce helping and find that the reduction in the frequency of helping behaviour is gradual rather than a sudden transition for a threshold cost level. Interestingly, younger and male participants were more likely to help. We provide potential explanations for this result relating to the nature of our experiment. Finally, we find no evidence that participants in our experiment plan ahead over two consecutive, inter-dependent helping opportunities when conducting cost-benefit trade-offs in spontaneous decisions. We discuss potential applications of our findings to research into decision-making during evacuations

Copycat dynamics in leaderless animal group navigation

Background: Many animals are known to have improved navigational efficiency when moving together as a social group. One potential mechanism for social group navigation is known as the 'many wrongs principle', where information from many inaccurate compasses is pooled across the group. In order to understand how animal groups may use the many wrongs principle to navigate, it is important to consider how directional information is transferred and shared within the group. Methods: Here we use an individual-based model to explore the information-sharing and copying dynamics of a leaderless animal group navigating towards a target in a virtual environment. We assume that communication and information-sharing is indirect and arises through individuals partially copying the movement direction of their neighbours and weighting this information relative to their individual navigational knowledge. Results: We find that the best group navigation performance occurs when individuals directly copy the direction of movement of a subset of their neighbours while only giving a small (6%) weighting to their individual navigational knowledge. Surprisingly, such a strategy is shown to be highly efficient regardless of the level of individual navigational error. We find there is little relative improvement in navigational efficiency when individuals copy from more than 7 influential neighbours. Conclusions: Our findings suggest that we would expect navigating group-living animals to predominantly copy the movement of others rather than relying on their own navigational knowledge. We discuss our results in the context of individual and group navigation behaviour in animals

Cortisol coregulation in fish

Cortisol coregulation, which is the up- or down-regulation of partners’ physiological stress responses, has been described for individuals with strong attachment bonds, e.g. parents and their children, and romantic relationship partners. Research into moderating effects on cortisol coregulation suggests stronger covariation among distressed partners. Whether cortisol coregulation is unique to humans or can also be found in other species that share universal features of the vertebrate stress response remains unexplored. Using a repeated measures approach and non-invasive waterborne hormone analysis, we test the hypothesis that dyads of three-spined stickleback fish (Gasterosteus aculeatus) coregulate their cortisol levels in shared environments. Dyadic cortisol levels were unrelated when cohabiting (home tank), but significantly covaried when sharing a more stressful (as indicated by higher cortisol levels) environment (open field). Time-lag analysis further revealed that open field cortisol levels were predicted by partner’s cortisol levels prior to the shared experience. To our knowledge, this study provides the first evidence for coregulatory processes on cortisol responses in a non-human animal that lacks strong bonds and social attachment relationships, suggesting a shared evolutionary origin of cortisol coregulation in vertebrates. From an adaptive perspective, cortisol coregulation may serve to reduce risk in challenging, potentially threatening situations

From Social Network (Centralized vs. Decentralized) to Collective Decision-Making (Unshared vs. Shared Consensus)

Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones – star network vs. equal network - led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies

Social preferences and network structure in a population of reef manta rays

Understanding how individual behavior shapes the structure and ecology ofpopulations is key to species conservation and management. Like manyelasmobranchs, manta rays are highly mobile and wide ranging species threatened byanthropogenic impacts. In shallow-water environments these pelagic rays often formgroups, and perform several apparently socially-mediated behaviors. Group structuresmay result from active choices of individual rays to interact, or passive processes.Social behavior is known to affect spatial ecology in other elasmobranchs, but this isthe first study providing quantitative evidence for structured social relationships inmanta rays. To construct social networks, we collected data from more than 500groups of reef manta rays over five years, in the Raja Ampat Regency of West Papua.We used generalized affiliation indices to isolate social preferences from non-socialassociations, the first study on elasmobranchs to use this method. Longer lastingsocial preferences were detected mostly between female rays. We detectedassortment of social relations by phenotype and variation in social strategies, with theoverall social network divided into two main communities. Overall network structurewas characteristic of a dynamic fission-fusion society, with differentiated relationshipslinked to strong fidelity to cleaning station sites. Our results suggest that fine-scaleconservation measures will be useful in protecting social groups of M. alfredi in theirnatural habitats, and that a more complete understanding of the social nature of mantarays will help predict population response

Data from: Distinguishing social from nonsocial navigation in moving animal groups, American Naturalist 179(5): 621-632. doi:10.1086/665005

Many animals, such as migrating shoals of fish, navigate in groups. Knowing the mechanisms involved in animal navigation is important when it comes to explaining navigation accuracy, dispersal patterns, population and evolutionary dynamics and consequently the design of conservation strategies. When navigating towards a common target, animals could interact socially by sharing available information directly or indirectly, or each individual could navigate by itself and aggregations may not disperse because all animals are moving towards the same target. Here, we present an analysis technique that uses individual movement trajectories to determine the extent to which individuals in navigating groups interact socially, given knowledge of their target. The basic idea of our approach is that the movement direction of individuals arises from a combination of responses to the environment and to other individuals. We estimate the relative importance of these responses, distinguishing between social and non-social interactions. We develop and test our method using simulated groups and demonstrate its applicability to empirical data in a case study on groups of guppies moving towards shelter in a tank. Our approach is generic and can be extended to different scenarios of animal group movement