10 research outputs found

    Analyses of three‐dimensional species associations reveal departures from neutrality in a tropical forest

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    The study of community spatial structure is central to understanding diversity patterns over space and species co-occurrence at local scales. Although most analytical approaches consider horizontal and vertical dimensions separately, in this study we introduce a three-dimensional spatial analysis that simultaneously includes horizontal and vertical species associations. Using tree census data (2000–2016) and allometries from the Luquillo forest plot in Puerto Rico, we show that spatial organization becomes less random over time as the forest recovered from land-use legacy effects and hurricane disturbance. Tree species vertical segregation is predominant in the forest with almost all species that co-occur in the horizontal plane avoiding each other in the vertical dimension. Horizontal segregation is less common than vertical, whereas three-dimensional aggregation (a proxy for direct tree competition) is the least frequent type of spatial association. Furthermore, dominant species are involved in more non-random spatial associations, implying that species co-occurrence is facilitated by species segregation in space. This novel three-dimensional analysis allowed us to identify and quantify tree species spatial distributions, how interspecific competition was reduced through forest structure, and how it changed over time after disturbance, in ways not detectable from two-dimensional analyses alone

    Data from: Negative biotic interactions drive predictions of distributions for species from a grassland community

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    Understanding the factors that determine species’ geographic distributions is important for addressing a wide range of biological questions, including where species will be able to maintain populations following environmental change. New methods for modelling species distributions include the effects of biotic interactions alongside more commonly used abiotic variables such as temperature and precipitation; however, it is not clear which types of interspecific relationship contribute to shaping species distributions and should therefore be prioritised in models. Even if some interactions are known to be influential at local spatial scales, there is no guarantee they will have similar impacts at macroecological scales. Here we apply a novel method based on information theory to determine which types of interspecific relationship drive species distributions. Our results show that negative biotic interactions such as competition have the greatest effect on model predictions for species from a California grassland community. This knowledge will help focus data collection and improve model predictions for identifying at-risk species. Furthermore, our methodological approach is applicable to any kind of species distribution model that can be specified with and without interspecific relationships

    Isolation and characterization of diverse microbial representatives from the human skin microbiome

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    Abstract Background The skin micro-environment varies across the body, but all sites are host to microorganisms that can impact skin health. Some of these organisms are true commensals which colonize a unique niche on the skin, while open exposure of the skin to the environment also results in the transient presence of diverse microbes with unknown influences on skin health. Culture-based studies of skin microbiota suggest that skin microbes can affect skin properties, immune responses, pathogen growth, and wound healing. Results In this work, we greatly expanded the diversity of available commensal organisms by collecting \u3e 800 organisms from 3 body sites of 17 individuals. Our collection includes \u3e 30 bacterial genera and 14 fungal genera, with Staphylococcus and Micrococcus as the most prevalent isolates. We characterized a subset of skin isolates for the utilization of carbon compounds found on the skin surface. We observed that members of the skin microbiota have the capacity to metabolize amino acids, steroids, lipids, and sugars, as well as compounds originating from personal care products. Conclusions This collection is a resource that will support skin microbiome research with the potential for discovery of novel small molecules, development of novel therapeutics, and insight into the metabolic activities of the skin microbiota. We believe this unique resource will inform skin microbiome management to benefit skin health. Video abstract

    Isolation and characterization of diverse microbial representatives from the human skin microbiome

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    Abstract Background The skin micro-environment varies across the body, but all sites are host to microorganisms that can impact skin health. Some of these organisms are true commensals which colonize a unique niche on the skin, while open exposure of the skin to the environment also results in the transient presence of diverse microbes with unknown influences on skin health. Culture-based studies of skin microbiota suggest that skin microbes can affect skin properties, immune responses, pathogen growth, and wound healing. Results In this work, we greatly expanded the diversity of available commensal organisms by collecting \u3e 800 organisms from 3 body sites of 17 individuals. Our collection includes \u3e 30 bacterial genera and 14 fungal genera, with Staphylococcus and Micrococcus as the most prevalent isolates. We characterized a subset of skin isolates for the utilization of carbon compounds found on the skin surface. We observed that members of the skin microbiota have the capacity to metabolize amino acids, steroids, lipids, and sugars, as well as compounds originating from personal care products. Conclusions This collection is a resource that will support skin microbiome research with the potential for discovery of novel small molecules, development of novel therapeutics, and insight into the metabolic activities of the skin microbiota. We believe this unique resource will inform skin microbiome management to benefit skin health. Video abstract

    Network motifs involving both competition and facilitation predict biodiversity in alpine plant communities

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    Biological diversity depends on multiple, cooccurring ecological interactions. However, most studies focus on one interaction type at a time, leaving community ecologists unsure of how positive and negative associations among species combine to influence biodiversity patterns. Using surveys of plant populations in alpine communities worldwide, we explore patterns of positive and negative associations among triads of species (modules) and their relationship to local biodiversity. Three modules, each incorporating both positive and negative associations, were overrepresented, thus acting as "network motifs." Furthermore, the overrepresentation of these network motifs is positively linked to species diversity globally. A theoretical model illustrates that these network motifs, based on competition between facilitated species or facilitation between inferior competitors, increase local persistence. Our findings suggest that the interplay of competition and facilitation is crucial for maintaining biodiversity.ISSN:0027-8424ISSN:1091-649

    Biotic interactions between saproxylic insect species

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    Biotic interactions between saproxylic insect specie
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