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      Bayesian nitrate source apportionment to individual groundwater wells in the Central Valley by use of elemental and isotopic tracers : BAYESIAN NITRATE SOURCE APPORTIONMENT

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          A bacterial method for the nitrogen isotopic analysis of nitrate in seawater and freshwater.

          We report a new method for measurement of the isotopic composition of nitrate (NO3-) at the natural-abundance level in both seawater and freshwater. The method is based on the isotopic analysis of nitrous oxide (N20) generated from nitrate by denitrifying bacteria that lack N2O-reductase activity. The isotopic composition of both nitrogen and oxygen from nitrate are accessible in this way. In this first of two companion manuscripts, we describe the basic protocol and results for the nitrogen isotopes. The precision of the method is better than 0.2/1000 (1 SD) at concentrations of nitrate down to 1 microM, and the nitrogen isotopic differences among various standards and samples are accurately reproduced. For samples with 1 microM nitrate or more, the blank of the method is less than 10% of the signal size, and various approaches may reduce it further.
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            Uncertainty in source partitioning using stable isotopes.

            Stable isotope analyses are often used to quantify the contribution of multiple sources to a mixture, such as proportions of food sources in an animal's diet, or C3 and C4 plant inputs to soil organic carbon. Linear mixing models can be used to partition two sources with a single isotopic signature (e.g., δ(13)C) or three sources with a second isotopic signature (e.g., δ(15)N). Although variability of source and mixture signatures is often reported, confidence interval calculations for source proportions typically use only the mixture variability. We provide examples showing that omission of source variability can lead to underestimation of the variability of source proportion estimates. For both two- and three-source mixing models, we present formulas for calculating variances, standard errors (SE), and confidence intervals for source proportion estimates that account for the observed variability in the isotopic signatures for the sources as well as the mixture. We then performed sensitivity analyses to assess the relative importance of: (1) the isotopic signature difference between the sources, (2) isotopic signature standard deviations (SD) in the source and mixture populations, (3) sample size, (4) analytical SD, and (5) the evenness of the source proportions, for determining the variability (SE) of source proportion estimates. The proportion SEs varied inversely with the signature difference between sources, so doubling the source difference from 2‰ to 4‰ reduced the SEs by half. Source and mixture signature SDs had a substantial linear effect on source proportion SEs. However, the population variability of the sources and the mixture are fixed and the sampling error component can be changed only by increasing sample size. Source proportion SEs varied inversely with the square root of sample size, so an increase from 1 to 4 samples per population cut the SE in half. Analytical SD had little effect over the range examined since it was generally substantially smaller than the population SDs. Proportion SEs were minimized when sources were evenly divided, but increased only slightly as the proportions varied. The variance formulas provided will enable quantification of the precision of source proportion estimates. Graphs are provided to allow rapid assessment of possible combinations of source differences and source and mixture population SDs that will allow source proportion estimates with desired precision. In addition, an Excel spreadsheet to perform the calculations for the source proportions and their variances, SEs, and 95% confidence intervals for the two-source and three-source mixing models can be accessed at http://www.epa.gov/wed/pages/models.htm.
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              Measurement of the oxygen isotopic composition of nitrate in seawater and freshwater using the denitrifier method.

              We report a novel method for measurement of the oxygen isotopic composition (18O/16O) of nitrate (NO3-) from both seawater and freshwater. The denitrifier method, based on the isotope ratio analysis of nitrous oxide generated from sample nitrate by cultured denitrifying bacteria, has been described elsewhere for its use in nitrogen isotope ratio (15N/14N) analysis of nitrate. (1) Here, we address the additional issues associated with 18O/16O analysis of nitrate by this approach, which include (1) the oxygen isotopic difference between the nitrate sample and the N20 analyte due to isotopic fractionation associated with the loss of oxygen atoms from nitrate and (2) the exchange of oxygen atoms with water during the conversion of nitrate to N2O. Experiments with 18O-labeled water indicate that water exchange contributes less than 10%, and frequently less than 3%, of the oxygen atoms in the N20 product for Pseudomonas aureofaciens. In addition, both oxygen isotope fractionation and oxygen atom exchange are consistent within a given batch of analyses. The analysis of appropriate isotopic reference materials can thus be used to correct the measured 18O/16O ratios of samples for both effects. This is the first method tested for 18O/16O analysis of nitrate in seawater. Benefits of this method, relative to published freshwater methods, include higher sensitivity (tested down to 10 nmol and 1 microM NO3-), lack of interference by other solutes, and ease of sample preparation.
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                Author and article information

                Journal
                Water Resources Research
                Water Resour. Res.
                Wiley
                00431397
                July 2016
                July 2016
                July 31 2016
                : 52
                : 7
                : 5577-5597
                Affiliations
                [1 ]Department of Land, Air, and Water Resources; University of California; Davis California USA
                [2 ]Department of Anthropology; University of California; Davis California USA
                [3 ]Lawrence Livermore National Laboratory; Livermore California USA
                [4 ]United States Geological Survey; Menlo Park California USA
                [5 ]Department of Earth and Planetary Sciences; University of California; Davis California USA
                Article
                10.1002/2015WR018523
                3faaab22-f0be-4de7-9b0e-bc5041ba297e
                © 2016

                http://doi.wiley.com/10.1002/tdm_license_1.1

                http://creativecommons.org/licenses/by-nc-nd/4.0/


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