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Reproductive division of labour is a hallmark of eusocial insects. However, its stability can often be hampered by the potential for reproduction by otherwise sterile nest-mates. Dominance hierarchy has a crucial role in some species in regulating which individuals reproduce. Compared with those in vertebrates, the dominance hierarchies in eusocial insects tend to involve many more individuals, and should require additional selective forces unique to them. Here, we provide an overview of a series of studies on dominance hierarchies in eusocial insects. Although reported from diverse eusocial taxa, dominance hierarchies have been extensively studied in paper wasps and ponerine ants. Starting from molecular physiological attributes of individuals, we describe how the emergence of dominance hierarchies can be understood as a kind of self-organizing process through individual memory and local behavioural interactions. The resulting global structures can be captured by using network analyses. Lastly, we argue the adaptive significance of dominance hierarchies from the standpoint of sterile subordinates. Kin selection, underpinned by relatedness between nest-mates, is key to the subordinates' acceptance of their positions in the hierarchies. This article is part of the theme issue 'The centennial of the pecking order: current state and future prospects for the study of dominance hierarchies'.

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BV (bacterial vaginosis) influences 20%-40% of women but its etiology is still poorly understood. An open question about the BV is which of the hundreds of bacteria found in the human vaginal microbiome (HVM) are the major force driving the vaginal microbiota dysbiosis. Here, we recast the question of microbial causality of BV by asking if there are any prevalent 'signatures' (network motifs) in the vaginal microbiome networks associated with it? We apply a new framework [species dominance network analysis by Ma & Ellison (2019): Ecological Monographs) to detect critical structures in HVM networks associated with BV risks and etiology. We reanalyzed the 16 s-rRNA gene sequencing datasets of a mixed-cohort of 25 BV patients and healthy women. In these datasets, we detected 15 trio-motifs that occurred exclusively in BV patients. We failed to find any of these 15 trio-motifs in three additional cohorts of 1535 healthy women. Most member-species of the 15 trio motifs are BV-associated anaerobic bacteria (BVAB), Ravel's community-state type indicators, or the most dominant species; virtually all species interactions in these trios are high-salience skeletons, suggesting that those trios are strongly connected 'cults' associated with the occurrence of BV. The presence of the trio motifs unique to BV may act as indicators for its personalized diagnosis and could help elucidate a more mechanistic interpretation of its risks and etiology. We caution that scarcity of large longitudinal datasets of HVM also limited further verifications of our findings, and these findings require further clinical tests to launch their applications.

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Although Lactobacillus dominance is one of the commonest characteristics of many healthy vaginal microbiomes, a significant proportion of healthy women lack an appreciable amount of Lactobacillus in their microbiome. Indeed, the vaginal microbiomes of many BV (bacterial vaginosis) patients lack the dominance by Lactobacillus. One would wonder what are special with those healthy non-Lactobacillus dominated vaginal microbiomes (nLDVM)? Here we re-analyzed the vaginal microbiome datasets of 1107 postpartum women in rural Malawi Doyle et al. (2018) using species dominance network (SDN) analysis. We discovered that: (i) The DN of the nLDVM is predominantly mutualistic, where most competitive (negative) relationships were from bacterial vaginosis-associated bacteria (BVAB), >60% occurred between BVAB and non-BVAB genera. Gardnerella was inhibited by a mutualistic combination of 23 genera, and Lactobacillus by 15 genera. These may be possible mechanisms by which the microbiome maintains high diversity but avoids dominance by Gardnerella or Lactobacillus. Gardnerella and Lactobacillus were only cooperated with a few genera, but they were positively connected with each other. The suppressed Lactobacillus species positively associated with Gardnerella was Lactobacillus iners, indicating that L. iners might act as an "enemy" in the Lactobacillus-poor vaginal microbiome, and inhibition of Gardnerella and L. iners might be a self-protective mechanism to maintain stability and health of this microbiome. (ii) We identified skeletons of the DNs and separate pathways consisting of high salience skeletons. Finegoldia species and Staphylococcus epidermidis were the hubs of the skeleton network. The roles that they play in the nLDVM deserve more attention of future studies.

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Hierarchical organization is widespread in the societies of humans and other animals, both in social structure and in decision-making contexts. In the case of collective motion, the majority of case studies report that dominant individuals lead group movements, in agreement with the common conflation of the terms "dominance" and "leadership." From a theoretical perspective, if social relationships influence interactions during collective motion, then social structure could also affect leadership in large, swarm-like groups, such as fish shoals and bird flocks. Here we use computer-vision-based methods and miniature GPS tracking to study, respectively, social dominance and in-flight leader-follower relations in pigeons. In both types of behavior we find hierarchically structured networks of directed interactions. However, instead of being conflated, dominance and leadership hierarchies are completely independent of each other. Although dominance is an important aspect of variation among pigeons, correlated with aggression and access to food, our results imply that the stable leadership hierarchies in the air must be based on a different set of individual competences. In addition to confirming the existence of independent and context-specific hierarchies in pigeons, we succeed in setting out a robust, scalable method for the automated analysis of dominance relationships, and thus of social structure, applicable to many species. Our results, as well as our methods, will help to incorporate the broader context of animal social organization into the study of collective behavior.

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