11 research outputs found

    The Biology, Development, and Host Distribution of Epifoliar Fungi in the Mangrove Ferns (Acrostichum aureum) of Mo'orea, French Polynesia

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    Epifoliar fungi are understudied, despite high prevalence across plant tissue. In this study, conducted on the island of Mo’orea, French Polynesia, an epifoliar fungus found on a high diversity of native leaves was identified and characterized. The rate of development was tracked and the characteristics of colonization were determined on mangrove ferns. Environmental conditions did not affect distribution, but did affect the growth rate of the fungal fruiting body. Host distribution was also surveyed and the fungi primarily occurred on naturalized plants. The potential use of this fungus as a bioindicator of plant and habitat health will be discussed

    Universal gut microbial relationships in the gut microbiome of wild baboons

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    Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships is essential to learn how ecology scales up to affect microbiome assembly, dynamics, and host health. However, whether bacterial relationships are generalizable across hosts or personalized to individual hosts is debated. Here, we apply a robust, multinomial logistic-normal modeling framework to extensive time series data (5534 samples from 56 baboon hosts over 13 years) to infer thousands of correlations in bacterial abundance in individual baboons and test the degree to which bacterial abundance correlations are ‘universal’. We also compare these patterns to two human data sets. We find that, most bacterial correlations are weak, negative, and universal across hosts, such that shared correlation patterns dominate over host-specific correlations by almost twofold. Further, taxon pairs that had inconsistent correlation signs (either positive or negative) in different hosts always had weak correlations within hosts. From the host perspective, host pairs with the most similar bacterial correlation patterns also had similar microbiome taxonomic compositions and tended to be genetic relatives. Compared to humans, universality in baboons was similar to that in human infants, and stronger than one data set from human adults. Bacterial families that showed universal correlations in human infants were often universal in baboons. Together, our work contributes new tools for analyzing the universality of bacterial associations across hosts, with implications for microbiome personalization, community assembly, and stability, and for designing microbiome interventions to improve host health.</p

    Universal gut microbial relationships in the gut microbiome of wild baboons

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    Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships is essential to learn how ecology scales up to affect microbiome assembly, dynamics, and host health. However, whether bacterial relationships are generalizable across hosts or personalized to individual hosts is debated. Here, we apply a robust, multinomial logistic-normal modeling framework to extensive time series data (5534 samples from 56 baboon hosts over 13 years) to infer thousands of correlations in bacterial abundance in individual baboons and test the degree to which bacterial abundance correlations are ‘universal’. We also compare these patterns to two human data sets. We find that, most bacterial correlations are weak, negative, and universal across hosts, such that shared correlation patterns dominate over host-specific correlations by almost twofold. Further, taxon pairs that had inconsistent correlation signs (either positive or negative) in different hosts always had weak correlations within hosts. From the host perspective, host pairs with the most similar bacterial correlation patterns also had similar microbiome taxonomic compositions and tended to be genetic relatives. Compared to humans, universality in baboons was similar to that in human infants, and stronger than one data set from human adults. Bacterial families that showed universal correlations in human infants were often universal in baboons. Together, our work contributes new tools for analyzing the universality of bacterial associations across hosts, with implications for microbiome personalization, community assembly, and stability, and for designing microbiome interventions to improve host health.</p

    A comparison of dominance rank metrics reveals multiple competitive landscapes in an animal society

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    Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes and reproductive performance. Studies of how dominance rank predicts these traits typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here, we compare the ability of two dominance rank metrics-simple ordinal rank and proportional or 'standardized' rank-to predict 20 traits in a wild baboon population in Amboseli, Kenya. We propose that simple ordinal rank best predicts traits when competition is density-dependent, whereas proportional rank best predicts traits when competition is density-independent. We found that for 75% of traits (15/20), one rank metric performed better than the other. Strikingly, all male traits were best predicted by simple ordinal rank, whereas female traits were evenly split between proportional and simple ordinal rank. Hence, male and female traits are shaped by different competitive processes: males are largely driven by density-dependent resource access (e.g. access to oestrous females), whereas females are shaped by both density-independent (e.g. distributed food resources) and density-dependent resource access. This method of comparing how different rank metrics predict traits can be used to distinguish between different competitive processes operating in animal societies

    A comparison of dominance rank metrics reveals multiple competitive landscapes in an animal society

    No full text
    Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes and reproductive performance. Studies of how dominance rank predicts these traits typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here, we compare the ability of two dominance rank metrics—simple ordinal rank and proportional or ‘standardized’ rank—to predict 20 traits in a wild baboon population in Amboseli, Kenya. We propose that simple ordinal rank best predicts traits when competition is density-dependent, whereas proportional rank best predicts traits when competition is density-independent. We found that for 75% of traits (15/20), one rank metric performed better than the other. Strikingly, all male traits were best predicted by simple ordinal rank, whereas female traits were evenly split between proportional and simple ordinal rank. Hence, male and female traits are shaped by different competitive processes: males are largely driven by density-dependent resource access (e.g. access to oestrous females), whereas females are shaped by both density-independent (e.g. distributed food resources) and density-dependent resource access. This method of comparing how different rank metrics predict traits can be used to distinguish between different competitive processes operating in animal societies

    Universal gut microbial relationships in the gut microbiome of wild baboons

    Get PDF
    Ecological relationships between bacteria mediate the services that gut microbiomes provide to their hosts. Knowing the overall direction and strength of these relationships is essential to learn how ecology scales up to affect microbiome assembly, dynamics, and host health. However, whether bacterial relationships are generalizable across hosts or personalized to individual hosts is debated. Here, we apply a robust, multinomial logistic-normal modeling framework to extensive time series data (5534 samples from 56 baboon hosts over 13 years) to infer thousands of correlations in bacterial abundance in individual baboons and test the degree to which bacterial abundance correlations are ‘universal’. We also compare these patterns to two human data sets. We find that, most bacterial correlations are weak, negative, and universal across hosts, such that shared correlation patterns dominate over host-specific correlations by almost twofold. Further, taxon pairs that had inconsistent correlation signs (either positive or negative) in different hosts always had weak correlations within hosts. From the host perspective, host pairs with the most similar bacterial correlation patterns also had similar microbiome taxonomic compositions and tended to be genetic relatives. Compared to humans, universality in baboons was similar to that in human infants, and stronger than one data set from human adults. Bacterial families that showed universal correlations in human infants were often universal in baboons. Together, our work contributes new tools for analyzing the universality of bacterial associations across hosts, with implications for microbiome personalization, community assembly, and stability, and for designing microbiome interventions to improve host health

    Comparing proportional and ordinal dominance ranks reveals multiple competitive landscapes in an animal society

    No full text
    Across group-living animals, linear dominance hierarchies lead to disparities in access to resources, health outcomes, and reproductive performance. Studies of how dominance rank affects these outcomes typically employ one of several dominance rank metrics without examining the assumptions each metric makes about its underlying competitive processes. Here we compare the ability of two dominance rank metrics—ordinal rank and proportional or ‘standardized’ rank—to predict 20 distinct traits in a well-studied wild baboon population in Amboseli, Kenya. We propose that ordinal rank best predicts outcomes when competition is density-dependent, while proportional rank best predicts outcomes when competition is density-independent. We found that for 75% (15/20) of the traits, one of the two rank metrics performed better than the other. Strikingly, all male traits were better predicted by ordinal than by proportional rank, while female traits were evenly split between being better predicted by proportional or ordinal rank. Hence, male and female traits are shaped by different competitive regimes: males’ competitive environments are largely driven by density-dependent resource access (e.g., access to estrus females), while females’ competitive environments are shaped by both density-independent resource access (e.g. distributed food resources) and density-dependent resource access. However, traits related to competition for social and mating partners are an exception to this sex-biased pattern: these traits were better predicted by ordinal rank than by proportional rank for both sexes. We argue that this method of comparing how different rank metrics predict traits of interest can be used as a way to distinguish between different competitive processes operating in animal societies

    Twenty Important Research Questions in Microbial Exposure and Social Equity

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    Social and political policy, human activities, and environmental change affect the ways in which microbial communities assemble and interact with people. These factors determine how different social groups are exposed to beneficial and/ or harmful microorganisms, meaning microbial exposure has an important socioecological justice context. Therefore, greater consideration of microbial exposure and social equity in research, planning, and policy is imperative. Here, we identify 20 research questions considered fundamentally important to promoting equitable exposure to beneficial microorganisms, along with safeguarding resilient societies and ecosystems. The 20 research questions we identified span seven broad themes, including the following: (i) sociocultural interactions; (ii) Indigenous community health and well-being; (iii) humans, urban ecosystems, and environmental processes; (iv) human psychology and mental health; (v) microbiomes and infectious diseases; (vi) human health and food security; and (vii) microbiome-related planning, policy, and outreach. Our goal was to summarize this growing field and to stimulate impactful research avenues while providing focus for funders and policymakers
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