Scholarly Works, Biological Systems Engineering

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https://hdl.handle.net/10919/24302
Research articles, presentations, and other scholarship

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Browsing Scholarly Works, Biological Systems Engineering by Department "Geosciences"

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    Armored kinorhynch-like scalidophoran animals from the early Cambrian
    Zhang, H.; Xiao, S.; Liu, Y.; Yuan, X.; Wan, B.; Muscente, A. D.; Shao, T.; Gong, H.; Cao, G. (2015-11-26)
    Morphology-based phylogenetic analyses support the monophyly of the Scalidophora (Kinorhyncha, Loricifera, Priapulida) and Nematoida (Nematoda, Nematomorpha), together constituting the monophyletic Cycloneuralia that is the sister group of the Panarthropoda. Kinorhynchs are unique among living cycloneuralians in having a segmented body with repeated cuticular plates, longitudinal muscles, dorsoventral muscles, and ganglia. Molecular clock estimates suggest that kinorhynchs may have diverged in the Ediacaran Period. Remarkably, no kinorhynch fossils have been discovered, in sharp contrast to priapulids and loriciferans that are represented by numerous Cambrian fossils. Here we describe several early Cambrian (~535 million years old) kinorhynch-like fossils, including the new species Eokinorhynchus rarus and two unnamed but related forms. E. rarus has characteristic scalidophoran features, including an introvert with pentaradially arranged hollow scalids. Its trunk bears at least 20 annuli each consisting of numerous small rectangular plates, and is armored with five pairs of large and bilaterally placed sclerites. Its trunk annuli are reminiscent of the epidermis segments of kinorhynchs. A phylogenetic analysis resolves E. rarus as a stem-group kinorhynch. Thus, the fossil record confirms that all three scalidophoran phyla diverged no later than the Cambrian Period.
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    Evaluating Geologic Sources of Arsenic in Well Water in Virginia (USA)
    VanDerwerker, Tiffany; Zhang, Lin; Ling, Erin; Benham, Brian L.; Schreiber, Madeline E. (MDPI, 2018-04-18)
    We investigated if geologic factors are linked to elevated arsenic (As) concentrations above 5 μg/L in well water in the state of Virginia, USA. Using geologic unit data mapped within GIS and two datasets of measured As concentrations in well water (one from public wells, the other from private wells), we evaluated occurrences of elevated As (above 5 μg/L) based on geologic unit. We also constructed a logistic regression model to examine statistical relationships between elevated As and geologic units. Two geologic units, including Triassic-aged sedimentary rocks and Triassic-Jurassic intrusives of the Culpeper Basin in north-central Virginia, had higher occurrences of elevated As in well water than other geologic units in Virginia. Model results support these patterns, showing a higher probability for As occurrence above 5 μg/L in well water in these two units. Due to the lack of observations (<5%) having elevated As concentrations in our data set, our model cannot be used to predict As concentrations in other parts of the state. However, our results are useful for identifying areas of Virginia, defined by underlying geology, that are more likely to have elevated As concentrations in well water. Due to the ease of obtaining publicly available data and the accessibility of GIS, this study approach can be applied to other areas with existing datasets of As concentrations in well water and accessible data on geology.