55 research outputs found

    Mitigation of Shallow Groundwater Nitrate in a Poorly Drained Riparian Area and Adjacent Cropland

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    Riparian ecosystems, through their unique position in the agricultural landscape and ability to influence nutrient cycles, can potentially reduce NO3 loading to surface and ground waters. The purpose of this study was to determine the fate of NO3 in shallow groundwater moving along a lateral flowpath from a grass seed cropping system through an undisturbed mixed-species herbaceous riparian area. Soil A (30–45 cm) and C horizon (135–150 cm) NO3, dissolved oxygen, and nitrous oxide concentrations were significantly higher in the cropping system than the adjacent riparian area. Nitrate concentrations in both horizons of the riparian soil were consistently at or below 0.05 mg NL-1 while cropping system concentrations ranged from 1 to 12 mg N L-1. Chloride data suggested that NO3 dilution occurred from recharge by precipitation. However, a sharp decrease in NO3/Cl ratios as water moved into the riparian area indicated that additional dilution of NO3 concentrations was unlikely. Riparian area A horizon soil water had higher dissolved organic carbon than the cropping system and when the riparian soil became saturated, available electron acceptors (O2, NO3) were rapidly reduced. Dissolved inorganic carbon was significantly higher in the riparian area than the cropping system for both horizons indicating high biological activity. Carbon limitation in the cropping system may have led to microbial respiration using primarily O2 and to a lesser degree NO3. Within 6 m of the riparian/cropping system transition, NO3 was virtually undetectable

    FOAM (functional ontology assignments for metagenomes):a hidden markov model (HMM) database with environmental focus

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    A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. ‘profiles’) were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/

    Back to the future of soil metagenomics

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    JN was funded by a fellowship from the French MENESR.Peer reviewedPeer Reviewe
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