In group-living animals, social interactions influence various traits including circadian activity. Maternal care, in particular, can have a strong effect on the circadian activity of parents or nurses across taxa. In social insects, nestmates are known to have diverse activity rhythms; however, what kind of social environment is crucial in shaping an individual's rhythm is largely unknown. Here, we show that the focal brood types being taken care of (i.e. egg, larva and pupa) have significant effects on individual activity/ rest rhythm, using the monomorphic ant Diacamma ( putative species indicum). When isolated from a colony, nurses exhibited a clear circadian rhythm. However, when paired with eggs or larvae, they exhibited around-the-clock activity with no apparent rhythm. In contrast, a clear activity rhythm emerged when nurses were paired with a pupa, requiring little care. Such brood-type-specific changes in circadian activity are considered to arise from the difference in caretaking demands. Our finding may contribute to the understanding of the organization of a colony in the context of behavioural variability under different microenvironments.

Constructing biological communities is a major challenge in both basic and applied sciences. Although model synthetic communities with a few species have been constructed, designing systems consisting of tens or hundreds of species remains one of the most difficult goals in ecology and microbiology. By utilizing high-throughput sequencing data of interspecific association networks, we here propose a framework for exploring "functional core" species that have great impacts on whole community processes and functions. The framework allows us to score each species within a large community based on three criteria: namely, topological positions, functional portfolios, and functional balance within a target network. The criteria are measures of each species' roles in maximizing functional benefits at the community or ecosystem level. When species with potentially large contributions to ecosystem-level functions are screened, the framework also helps us design "functional core microbiomes" by focusing on properties of species groups (modules) within a network. When embedded into agroecosystems or human gut, such functional core microbiomes are expected to organize whole microbiome processes and functions. An application to a plantassociated microbiome dataset actually highlighted potential functional core microbes that were known to control rhizosphere microbiomes by suppressing pathogens. Meanwhile, an example of application in mouse gut microbiomes called attention to poorly investigated bacterial species, whose potential roles within gut microbiomes deserve future experimental studies. The framework for gaining "bird's-eye" views of functional cores within networks is applicable not only to agricultural and medical data but also to datasets produced in food processing, brewing, waste water purification, and biofuel production.

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