149 research outputs found

    Phenotypic Plasticity of Leaf Shape along a Temperature Gradient in Acer rubrum

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    Both phenotypic plasticity and genetic determination can be important for understanding how plants respond to environmental change. However, little is known about the plastic response of leaf teeth and leaf dissection to temperature. This gap is critical because these leaf traits are commonly used to reconstruct paleoclimate from fossils, and such studies tacitly assume that traits measured from fossils reflect the environment at the time of their deposition, even during periods of rapid climate change. We measured leaf size and shape in Acer rubrum derived from four seed sources with a broad temperature range and grown for two years in two gardens with contrasting climates (Rhode Island and Florida). Leaves in the Rhode Island garden have more teeth and are more highly dissected than leaves in Florida from the same seed source. Plasticity in these variables accounts for at least 6–19 % of the total variance, while genetic differences among ecotypes probably account for at most 69–87 %. This study highlights the role of phenotypic plasticity in leaf-climate relationships. We suggest that variables related to tooth count and leaf dissection in A. rubrum can respond quickly to climate change, which increases confidence in paleoclimate methods that use these variables

    Predicting soil carbon loss with warming

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    Journal ArticleThis is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.ARISING FROM: T. W. Crowther et al. Nature 540, 104–108 (2016); doi:10.1038/nature2015

    Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

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    A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

    Integrating natural gradients, experiments, and statistical modeling in a distributed network experiment: An example from the WaRM Network

    Get PDF
    A growing body of work examines the direct and indirect effects of climate change on ecosystems, typically by using manipulative experiments at a single site or performing meta-analyses across many independent experiments. However, results from single-site studies tend to have limited generality. Although meta-analytic approaches can help overcome this by exploring trends across sites, the inherent limitations in combining disparate datasets from independent approaches remain a major challenge. In this paper, we present a globally distributed experimental network that can be used to disentangle the direct and indirect effects of climate change. We discuss how natural gradients, experimental approaches, and statistical techniques can be combined to best inform predictions about responses to climate change, and we present a globally distributed experiment that utilizes natural environmental gradients to better understand long-term community and ecosystem responses to environmental change. The warming and (species) removal in mountains (WaRM) network employs experimental warming and plant species removals at high- and low-elevation sites in a factorial design to examine the combined and relative effects of climatic warming and the loss of dominant species on community structure and ecosystem function, both above- and belowground. The experimental design of the network allows for increasingly common statistical approaches to further elucidate the direct and indirect effects of warming. We argue that combining ecological observations and experiments along gradients is a powerful approach to make stronger predictions of how ecosystems will function in a warming world as species are lost, or gained, in local communities

    Clostridium septicum growth from a total knee arthroplasty associated with intestinal malignancy: a case report

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    BACKGROUND: Previous reports of infection with Clostridium septicum have identified an unexpected association with concurrent malignancy. The reported rate of associated malignancy has been found to be as high as 81 percent. The purpose of this case report was to present a case of a total knee arthroplasty infected with C. septicum and the subsequent finding of an occult colonic malignancy. CASE PRESENTATION: A 74 year-old man underwent uneventful bilateral total knee arthroplasties. Two weeks post-operatively, he presented with acute swelling, redness and pain of the left knee. Aspiration of the knee was sent for cell count and culture. The cell count demonstrated 39,000 white blood cells per cubic millimeter with 71% of white blood cells identified as neutrophils. Synovial fluid cultures identified the presence of C. septicum, Enterobacter and coagulase negative Staphylococcus. After urgent irrigation and debridement and polyethylene exchange of the affected knee, the patient was placed on intravenous Penicillin G for a period of six weeks. Two weeks into his course of antibiotics, the patient developed hematochezia and was found to have an obstructive colonic malignancy. The patient underwent hemi-colectomy and has since made a complete recovery of both his malignancy and total knee arthroplasty infection. CONCLUSION: Recognition of the association between C. septicum and malignancy is especially important considering the large predicted increase in total joint arthroplasty procedures over the coming decades. In addition to the standard treatment for infection after total joint arthroplasty, identification of Clostridium septicum should initiate a search for associated occult malignancy

    Climate Change Alters Seedling Emergence and Establishment in an Old-Field Ecosystem

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    Background: Ecological succession drives large-scale changes in ecosystem composition over time, but the mechanisms whereby climatic change might alter succession remain unresolved. Here, we asked if the effects of atmospheric and climatic change would alter tree seedling emergence and establishment in an old-field ecosystem, recognizing that small shifts in rates of seedling emergence and establishment of different species may have long-term repercussions on the transition of fields to forests in the future. Methodology/Principal Findings: We introduced seeds from three early successional tree species into constructed old-field plant communities that had been subjected for 4 years to altered temperature, precipitation, and atmospheric CO 2 regimes in an experimental facility. Our experiment revealed that different combinations of atmospheric CO2 concentration, air temperature, and soil moisture altered seedling emergence and establishment. Treatments directly and indirectly affected soil moisture, which was the best predictor of seedling establishment, though treatment effects differed among species. Conclusions: The observed impacts, coupled with variations in the timing of seed arrival, are demonstrated as predictors o

    Linking Symptom Inventories using Semantic Textual Similarity

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    An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment
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