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  • 1
    Publication Date: 2021-02-08
    Description: Sulfate-driven anaerobic oxidation of methane (SD-AOM) plays a critical role in regulating the global methane budget. Determination of the diagnostic triple isotope exponent 33 e (= ln33 a/ln34 a) for SDAOM can help to identify and quantify microbial sulfate reduction via SD-AOM in the environment. The history of Earth's surface red ox conditions can also be examined through the measurement of triple sulfur isotope compositions in sedimentary rocks. Due to difficulties in both culturing anaerobic methanotrophs and sampling pore-water sulfate in SD-AOM-dominated environments. however. the 33 e values for the processes of SD-AOM have not been constrained. We propose that a set of modern cold-seep associated barite samples with low ll8 18 0j !l834S values bear a record of residual pore-water sulfate during SDAOM. and therefore the triple sulfur isotope composition of these barites can be used to deduce 33 e values. We applied a 1-D diagenetic reaction-transport model to fit !l 33S and 8134S results from modern cold seep barites collected from five sites in the Gulf of Mexico. Based on revealed negative correlations (R2 = 0.77) between !l33 S and 8134S values we calculated an upper-limit 33 e value of 0.5100 to 0.5112 (±0.0005) given a 1000ln34 a value of -30%0 to -10%0. This 33 e value is distinctively lower than that of organoclastic sulfate reduction ( OSR) in marine environments where the diagnostic isotope fractionation ( 1000 ln34 a) is typically more negative than that of SD-AOM. In addition. cold seep barite data display a negative !l 33 S-81 34S correlation whereas pore-water sulfates of all OSR-dominated settings show a positive one. Therefore. the diagnostic triple-sulfur isotope exponent and associated negative !l 33S-8134S correlation may allow for the identification of SD-AOM in sedimentary records.
    Type: Article , PeerReviewed
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  • 2
    Publication Date: 2024-02-07
    Description: Geochemical analyses of trace elements in the ocean water column have suggested that pelagic clay‐rich sediments are a major source of various elements to bottom‐waters. However, corresponding high‐quality measurements of trace element concentrations in porewaters of pelagic clay‐rich sediments are scarce, making it difficult to evaluate the contributions from benthic processes to global oceanic cycles of trace elements. To bridge this gap, we analyzed porewater and bulk sediment concentrations of vanadium, chromium, cobalt, nickel, copper, arsenic, molybdenum, barium and uranium, as well as concentrations of the major oxidants nitrate, manganese, iron, and sulfate in the top 30 cm of cores collected along a transect from Hawaii to Alaska. The data show large increases in porewater concentrations of vanadium, manganese, cobalt, nickel, copper, and arsenic within the top cm of the sediment, consistent with the release of these elements from remineralized organic matter. The sediments are a sink for sulfate, uranium, and molybdenum, even though conditions within the sampled top 30 cm remain aerobic. Porewater chromium concentrations generally increase with depth due to release from sediment particles. Extrapolated to the global aerial extent of pelagic clay sediment, the benthic fluxes in mol yr −1 are Ba 3.9 ± 3.6 × 10 9 , Mn 3.4 ± 3.5 × 10 8 , Co 2.6 ± 1.3 × 10 7 , Ni 9.6 ± 8.6 × 10 8 , Cu 4.6 ± 2.4 × 10 9 , Cr 1.7 ± 1.1 × 10 8 , As 6.1 ± 7.0 × 10 8 , V 6.0 ± 2.5 × 10 9 . With the exception of vanadium, calculated fluxes across the sediment–water interface are consistent with the variability in bottom‐water concentrations and ocean residence time of the studied elements.
    Type: Article , PeerReviewed
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  • 3
    Publication Date: 2023-01-30
    Keywords: ABN1314-103 ice core; Age; AGE; Age-depth model (ALC01112018); Ant_ABN-1314; Antarctica; Calculated from density and age-depth model; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; density; Density, ice; Depth, bottom/max; DEPTH, ice/snow; Depth, top/min; East Antarctica; IC; Ice core; Ice corer; nitrate; nitrogen isotope ratio (δ15N); Physical measurement; Sample ID; surface mass balance; Surface mass balance; Time in years
    Type: Dataset
    Format: text/tab-separated-values, 774 data points
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  • 4
    Publication Date: 2023-01-30
    Description: Nitrate concentration and isotopic (δ15NNO3) data, ice density, and surface mass balance estimates from the ABN1314-103 ice core. This 103 m long core was drilled beginning on 07 January 2014 as one of three ice cores at Aurora Basin North, Antarctica (-71.17, 111.37, 2679 m.a.s.l), in the 2013-2014 field season. The age-depth model for ABN1314-103 was matched through ion profiles from an annually-resolved model (ALC01112018) originally developed for one of the other ABN cores through seasonal ion and water isotope cycles and constrained by volcanic horizons. Each 1 m segment of the core was weighed and measured for ice density calculations, and then sampled for nitrate at 0.33 m resolution. Nitrate concentrations were taken on melted ice aliquots with ion chromatography, while isotopic analysis was achieved through bacterial denitrification and MAT 253 mass spectrometry after concentrating with anionic resin. Using the density data and the age-depth model's dates for the top and bottom of each 1 m core segment, we reconstructed a history of surface mass balance changes as recorded in ABN1314-103. Additionally, we also estimated the effect of upstream topographic changes on the ice core's surface mass balance record through a ground penetrating radar transect that extended 11.5 km against the direction of glacial ice flow. The modern SMB changes along this upstream transect were linked to ABN1314-103 core depths by through the local horizontal ice flow rate (16.2 m a-1) and the core's age-depth model, and included here for comparative analysis. See Akers et al., 2022 for more analytical details.
    Keywords: Antarctica; density; Ice core; nitrate; nitrogen isotope ratio (δ15N); surface mass balance
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 5
    Publication Date: 2023-02-13
    Keywords: ABN1314-103 ice core; Age; AGE; Age-depth model (ALC01112018); Ant_ABN-1314; Antarctica; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; Colorimetry and/or ion chromatography; density; Depth, bottom/max; DEPTH, ice/snow; Depth, top/min; East Antarctica; Ground-penetrating radar (GPR); IC; Ice core; Ice corer; Mass spectrometer, Finnigan, MAT 253; nitrate; Nitrate; nitrogen isotope ratio (δ15N); Physical measurement; Sample ID; surface mass balance; Surface mass balance; Time in years; δ15N; δ15N, standard error
    Type: Dataset
    Format: text/tab-separated-values, 3207 data points
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  • 6
    Publication Date: 2023-07-19
    Description: Geographic information, surface mass balance (SMB) data, and sub-photic zone (〉0.3 m) nitrate concentration and nitrogen isotopic composition (δ15NNO3) for 135 sites across East Antarctica. This database was used to examine and define the relationship between δ15NNO3 and SMB in Antarctica as part of the SCADI (Snow Core Accumulation from Delta-15N Isotopes) and EAIIST (East Antarctic International Ice Sheet Traverse) projects. Of these 135 sites, 92 are newly reported here while the other site data were previously published and are cited accordingly. Snow bearing nitrate was sampled from snow pits and firn/ice cores at different dates depending on the original scientific campaign, but predominately between 2010 and 2020, with the earliest sampling occurring in 2004. Nitrate was later extracted from the snow, concentrated, and analyzed for δ15NNO3. Surface mass balance data comes from a combination of previous ground-based observations (e.g., stakes, ice core data) and the output from Modèle Atmosphérique Régional version 3.6.4 with European Centre for Medium-Range Weather Forecasts “Interim” re-analysis data (ERA-interim) data, adjusted for observed model SMB biases. Elevation data were extracted from the Reference Elevation Model of Antarctica (REMA, https://doi.org/10.5194/tc-13-665-2019).
    Keywords: ABN1314-103 ice core; Ant_ABN-1314; Ant_ABN-DL1; Ant_ABN-DL2; Ant_ABN-P4; Ant_ABN-P5; Ant_AGO5; Ant_asuma.2016.1; Ant_asuma.2016.2; Ant_CHIC-01; Ant_CHIC-04; Ant_CHIC-05; Ant_CHIC-07; Ant_CHIC-10; Ant_CHIC-11; Ant_CHIC-13; Ant_CHIC-15; Ant_CHIC-18; Ant_CHIC-20; Ant_cph.d17; Ant_cph.d24; Ant_cph.d5; Ant_cph1516; Ant_DA2005; Ant_DC04; Ant_DC07-1; Ant_DC07-2; Ant_DC07-3; Ant_dc14; Ant_dc2010pits; Ant_DF1; Ant_DF2; Ant_dml.pit.a; Ant_dml.pit.b; Ant_eaiist.stop01; Ant_eaiist.stop02; Ant_eaiist.stop03; Ant_eaiist.stop04; Ant_eaiist.stop05; Ant_eaiist.stop06; Ant_eaiist.stop07; Ant_eaiist.stop08a; Ant_eaiist.stop08b; Ant_eaiist.stop09; Ant_eaiist.stop10; Ant_eaiist.stop11; Ant_eaiist.stop12; Ant_eaiist.stop13a; Ant_eaiist.stop13b; Ant_eaiist.stop14; Ant_eaiist.stop19; Ant_eaiist.stop20; Ant_eaiist.stop21; Ant_eaiist.stop22; Ant_eaiist.stop23; Ant_eaiist.stop24; Ant_eaiist.stop25; Ant_eaiist.stop26; Ant_Fuji_Pass; Ant_H108; Ant_H128; Ant_H42; Ant_H68; Ant_H88; Ant_IM0; Ant_IV; Ant_MD590; Ant_NDF; Ant_NMD304; Ant_Paleo; Ant_Plateau_S; Ant_posteaiist.asuma01; Ant_posteaiist.asuma02; Ant_posteaiist.asuma03; Ant_posteaiist.asuma04; Ant_posteaiist.asuma05; Ant_posteaiist.asuma06; Ant_posteaiist.asuma07; Ant_posteaiist.asuma08; Ant_posteaiist.asuma09; Ant_posteaiist.asuma10; Ant_posteaiist.asuma11; Ant_posteaiist.samba; Ant_posteaiist.stop27; Ant_posteaiist.stop28; Ant_posteaiist.stop29; Ant_posteaiist.stop30; Ant_posteaiist.stop31; Ant_posteaiist.stop32; Ant_posteaiist.stop33; Ant_posteaiist.stop34; Ant_posteaiist.stop35; Ant_posteaiist.stop36; Ant_posteaiist.stop37; Ant_posteaiist.stop38; Ant_preeaiist.01; Ant_preeaiist.02; Ant_preeaiist.03; Ant_preeaiist.04; Ant_preeaiist.05; Ant_preeaiist.06; Ant_preeaiist.07; Ant_preeaiist.08; Ant_preeaiist.09; Ant_preeaiist.10; Ant_preeaiist.11; Ant_preeaiist.12; Ant_preeaiist.13; Ant_preeaiist.14; Ant_preeaiist.15; Ant_preeaiist.16; Ant_preeaiist.17; Ant_preeaiist.18; Ant_S1; Ant_S2; Ant_S3; Ant_S30-JARE; Ant_S4; Ant_S80core; Ant_S80pit; Ant_V09-1; Ant_V09-2; Ant_VI; Ant_VIII; Ant_X; Ant_XII; Ant_XIV; Ant_XVI; Ant_XVIII; Ant_Z2; Ant_ZtoA-P1; Ant_ZtoA-P2; Ant_ZtoA-P3; Ant_ZtoA-P4; Ant_ZtoA-P5; Ant_ZtoA-P7; Antarctica; Bias-adjusted MAR output; Campaign; Category; Chemical and physical analysis in snow/firn for accumulation studies in Adelie L; CHICTABA; Colorimetry and/or ion chromatography; Comment; East Antarctica; ELEVATION; Event label; Extracted from REMA; GPS in field; IC; Ice core; Ice corer; isotope; LATITUDE; LONGITUDE; MAR output; Mass spectrometer, Finnigan, MAT 253; nitrate; Nitrate; nitrogen isotope ratio (δ15N); Physical measurement and observations; Reference/source; Site; SNOW; Snow/ice sample; Snow pits/firn core/ice core; surface mass balance; Surface mass balance; Transect; Type; δ15N
    Type: Dataset
    Format: text/tab-separated-values, 1904 data points
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  • 7
    Publication Date: 2024-01-19
    Description: This dataset includes the analyses of major elements (except Si), trace, and rare earth element concentrations of marine sediment samples collected with a multi-corer during CDisK-IV cruise. Samples were prepared and analyzed by Peter W. Crockford and Ann G. Dunlea at Woods Hole Oceanographic Institution (WHOI). In trace-metal clean labs, samples were cooked in a heated acid cocktail (HNO3, HCl, HF) with later additions of H2O2 before being dried down and brought back up with HNO3 and H2O2 and diluted. Sample solutions were analyzed on a Thermo Fischer Scientific iCAP inductively coupled plasma mass spectrometer (ICP-MS) in the WHOI Plasma Facility. Precision was determined by digesting two samples three times each. The average relative standard deviation of the two sets of triplicate analyses determined precision to be ~3%. The evaporation of HF causes loss of Si, so those concentrations are not reported.
    Keywords: Aluminium; Antimony; Barium; Caesium; Calcium; CDISK4-1; CDISK4-2; CDISK4-3; CDISK4-4; CDISK4-5; CDISK-IV; Cerium; Chromium; Cobalt; Copper; Depth, bathymetric; Depth, sediment, experiment, bottom/maximum; Depth, sediment, experiment, top/minimum; Dysprosium; Erbium; Europium; Event label; Gadolinium; Hafnium; Holmium; Iron; Lanthanum; Lead; Lithium; Lutetium; Magnesium; major and trace element data; Manganese; marine sediment; Molybdenum; MUC; MultiCorer; Neodymium; Nickel; North Pacific; pelagic clay; Phosphorus; Potassium; Pristane; Red Clay; Rubidium; RV Kilo Moana; Samarium; Scandium; Sodium; Station label; Strontium; Terbium; Thallium; Thorium; Thulium; Tin; Titanium; Uranium; Vanadium; Ytterbium; Yttrium; Zinc
    Type: Dataset
    Format: text/tab-separated-values, 1690 data points
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  • 8
    Publication Date: 2022-10-26
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Farrell, U. C., Samawi, R., Anjanappa, S., Klykov, R., Adeboye, O. O., Agic, H., Ahm, A.-S. C., Boag, T. H., Bowyer, F., Brocks, J. J., Brunoir, T. N., Canfield, D. E., Chen, X., Cheng, M., Clarkson, M. O., Cole, D. B., Cordie, D. R., Crockford, P. W., Cui, H., Dahl, T. W., Mouro, L. D., Dewing, K., Dornbos, S. Q., Drabon, N., Dumoulin, J. A., Emmings, J. F., Endriga, C. R., Fraser, T. A., Gaines, R. R., Gaschnig, R. M., Gibson, T. M., Gilleaudeau, G. J., Gill, B. C., Goldberg, K., Guilbaud, R., Halverson, G. P., Hammarlund, E. U., Hantsoo, K. G., Henderson, M. A., Hodgskiss, M. S. W., Horner, Tristan J., Husson, J. M., Johnson, B., Kabanov, P., Brenhin K. C., Kimmig, J., Kipp, M. A., Knoll, A. H., Kreitsmann, T., Kunzmann, M., Kurzweil, F., LeRoy, M. A., Li, C., Lipp, A. G., Loydell, D. K., Lu, X., Macdonald, F. A., Magnall, J. M., Mänd, K., Mehra, A., Melchin, M. J., Miller, A. J., Mills, N. T., Mwinde, C. N., O'Connell, B., Och, L. M., Ossa Ossa, F., Pagès, A., Paiste, K., Partin, C. A., Peters, S. E., Petrov, P., Playter, T. L., Plaza-Torres, S., Porter, Susannah M., Poulton, S. W., Pruss, S. B., Richoz, S., Ritzer, S. R., Rooney, A. D., Sahoo, S. K., Schoepfer, S. D., Sclafani, J. A., Shen, Y., Shorttle, O., Slotznick, S. P., Smith, E. F., Spinks, S., Stockey, R. G., Strauss, J. V., Stüeken, E. E., Tecklenburg, S., Thomson, D., Tosca, N. J., Uhlein, G. J., Vizcaíno, M. N., Wang, H., White, T., Wilby, P. R., Woltz, C. R., Wood, R. A., Xiang, L., Yurchenko, I. A., Zhang, T., Planavsky, N. J., Lau, K. V., Johnston, D. T., Sperling, E. A., The Sedimentary Geochemistry and Paleoenvironments Project. Geobiology. 00, (2021): 1– 12,https://doi.org/10.1111/gbi.12462.
    Description: Geobiology explores how Earth's system has changed over the course of geologic history and how living organisms on this planet are impacted by or are indeed causing these changes. For decades, geologists, paleontologists, and geochemists have generated data to investigate these topics. Foundational efforts in sedimentary geochemistry utilized spreadsheets for data storage and analysis, suitable for several thousand samples, but not practical or scalable for larger, more complex datasets. As results have accumulated, researchers have increasingly gravitated toward larger compilations and statistical tools. New data frameworks have become necessary to handle larger sample sets and encourage more sophisticated or even standardized statistical analyses. In this paper, we describe the Sedimentary Geochemistry and Paleoenvironments Project (SGP; Figure 1), which is an open, community-oriented, database-driven research consortium. The goals of SGP are to (1) create a relational database tailored to the needs of the deep-time (millions to billions of years) sedimentary geochemical research community, including assembling and curating published and associated unpublished data; (2) create a website where data can be retrieved in a flexible way; and (3) build a collaborative consortium where researchers are incentivized to contribute data by giving them priority access and the opportunity to work on exciting questions in group papers. Finally, and more idealistically, the goal was to establish a culture of modern data management and data analysis in sedimentary geochemistry. Relative to many other fields, the main emphasis in our field has been on instrument measurement of sedimentary geochemical data rather than data analysis (compared with fields like ecology, for instance, where the post-experiment ANOVA (analysis of variance) is customary). Thus, the longer-term goal was to build a collaborative environment where geobiologists and geologists can work and learn together to assess changes in geochemical signatures through Earth history.
    Description: We thank the donors of The American Chemical Society Petroleum Research Fund for partial support of SGP website development (61017-ND2). EAS is funded by National Science Foundation grant (NSF) EAR-1922966. BGS authors (JE, PW) publish with permission of the Executive Director of the British Geological Survey, UKRI.
    Keywords: Consortium ; Database ; Earth history ; Geochemistry ; Website
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 9
    Publication Date: 2022-05-26
    Description: © The Author(s), 2017. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Communications 8 (2017): 1342, doi:10.1038/s41467-017-01229-5.
    Description: Geochemical analyses of sedimentary barites (barium sulfates) in the geological record have yielded fundamental insights into the chemistry of the Archean environment and evolutionary origin of microbial metabolisms. However, the question of how barites were able to precipitate from a contemporary ocean that contained only trace amounts of sulfate remains controversial. Here we report dissolved and particulate multi-element and barium-isotopic data from Lake Superior that evidence pelagic barite precipitation at micromolar ambient sulfate. These pelagic barites likely precipitate within particle-associated microenvironments supplied with additional barium and sulfate ions derived from heterotrophic remineralization of organic matter. If active during the Archean, pelagic precipitation and subsequent sedimentation may account for the genesis of enigmatic barite deposits. Indeed, barium-isotopic analyses of barites from the Paleoarchean Dresser Formation are consistent with a pelagic mechanism of precipitation, which altogether offers a new paradigm for interpreting the temporal occurrence of barites in the geological record.
    Description: This research was made possible with support from the National Science Foundation Division of Ocean Sciences (OCE-PRF 1421196, OCE-1430015, and OCE-1443577), The Andrew W. Mellon Foundation Endowed Fund for Innovative Research, and the Agouron Institute Geobiology Postdoctoral Fellowship Program.
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 10
    Publication Date: 2022-05-26
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Communications 9 (2018): 305, doi:10.1038/s41467-017-02701-y.
    Description: Correction to: Nature Communications https://doi.org/10.1038/s41467-017-01229-5, Article published online 07 November 2017
    Repository Name: Woods Hole Open Access Server
    Type: Article
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