Gilbert
Melissa
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Melissa
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ArticleDissolved and particulate barium distributions along the US GEOTRACES North Atlantic and East Pacific zonal transects (GA03 and GP16): global implications for the marine barium cycle(American Geophysical Union, 2022-05-23) Rahman, Shaily ; Shiller, Alan M. ; Anderson, Robert F. ; Charette, Matthew A. ; Hayes, Christopher T. ; Gilbert, Melissa ; Grissom, Karen ; Lam, Phoebe J. ; Ohnemus, Daniel C. ; Pavia, Frank ; Twining, Benjamin S. ; Vivancos, Sebastian M.Processes controlling dissolved barium (dBa) were investigated along the GEOTRACES GA03 North Atlantic and GP16 Eastern Tropical Pacific transects, which traversed similar physical and biogeochemical provinces. Dissolved Ba concentrations are lowest in surface waters (∼35–50 nmol kg−1) and increase to 70–80 and 140–150 nmol kg−1 in deep waters of the Atlantic and Pacific transects, respectively. Using water mass mixing models, we estimate conservative mixing that accounts for most of dBa variability in both transects. To examine nonconservative processes, particulate excess Ba (pBaxs) formation and dissolution rates were tracked by normalizing particulate excess 230Th activities. Th-normalized pBaxs fluxes, with barite as the likely phase, have subsurface maxima in the top 1,000 m (∼100–200 μmol m−2 year−1 average) in both basins. Barite precipitation depletes dBa within oxygen minimum zones from concentrations predicted by water mass mixing, whereas inputs from continental margins, particle dissolution in the water column, and benthic diffusive flux raise dBa above predications. Average pBaxs burial efficiencies along GA03 and GP16 are ∼37% and 17%–100%, respectively, and do not seem to be predicated on barite saturation indices in the overlying water column. Using published values, we reevaluate the global freshwater dBa river input as 6.6 ± 3.9 Gmol year−1. Estuarine mixing processes may add another 3–13 Gmol year−1. Dissolved Ba inputs from broad shallow continental margins, previously unaccounted for in global marine summaries, are substantial (∼17 Gmol year−1), exceeding terrestrial freshwater inputs. Revising river and shelf dBa inputs may help bring the marine Ba isotope budget more into balance.
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ArticleThe GEOTRACES Intermediate Data Product 2017(Elsevier, 2018-06-01) Schlitzer, Reiner ; Anderson, Robert F. ; Dodas, Elena Masferrer ; Lohan, Maeve C. ; Geibert, Walter ; Tagliabue, Alessandro ; Bowie, Andrew R. ; Jeandel, Catherine ; Maldonado, Maria T. ; Landing, William M. ; Cockwell, Donna ; Abadie, Cyril ; Abouchami, Wafa ; Achterberg, Eric P. ; Agather, Alison ; Aguliar-Islas, Ana ; van Aken, Hendrik M. ; Andersen, Morten ; Archer, Corey ; Auro, Maureen E. ; Baar, Hein J. W. de ; Baars, Oliver ; Baker, Alex R. ; Bakker, Karel ; Basak, Chandranath ; Baskaran, Mark ; Bates, Nicholas R. ; Bauch, Dorothea ; van Beek, Pieter ; Behrens, Melanie K. ; Black, Erin E. ; Bluhm, Katrin ; Bopp, Laurent ; Bouman, Heather ; Bowman, Katlin ; Bown, Johann ; Boyd, Philip ; Boye, Marie ; Boyle, Edward A. ; Branellec, Pierre ; Bridgestock, Luke ; Brissebrat, Guillaume ; Browning, Thomas A. ; Bruland, Kenneth W. ; Brumsack, Hans-Jürgen ; Brzezinski, Mark A. ; Buck, Clifton S. ; Buck, Kristen N. ; Buesseler, Ken O. ; Bull, Abby ; Butler, Edward ; Cai, Pinghe ; Cámara Mor, Patricia ; Cardinal, Damien ; Carlson, Craig ; Carrasco, Gonzalo ; Casacuberta, Nuria ; Casciotti, Karen L. ; Castrillejo, Maxi ; Chamizo, Elena ; Chance, Rosie ; Charette, Matthew A. ; Chaves, Joaquin E. ; Cheng, Hai ; Chever, Fanny ; Christl, Marcus ; Church, Thomas M. ; Closset, Ivia ; Colman, Albert S. ; Conway, Tim M. ; Cossa, Daniel ; Croot, Peter L. ; Cullen, Jay T. ; Cutter, Gregory A. ; Daniels, Chris ; Dehairs, Frank ; Deng, Feifei ; Dieu, Huong Thi ; Duggan, Brian ; Dulaquais, Gabriel ; Dumousseaud, Cynthia ; Echegoyen-Sanz, Yolanda ; Edwards, R. Lawrence ; Ellwood, Michael J. ; Fahrbach, Eberhard ; Fitzsimmons, Jessica N. ; Flegal, A. Russell ; Fleisher, Martin Q. ; van de Flierdt, Tina ; Frank, Martin ; Friedrich, Jana ; Fripiat, Francois ; Fröllje, Henning ; Galer, Stephen J. G. ; Gamo, Toshitaka ; Ganeshram, Raja S. ; Garcia-Orellana, Jordi ; Garcia Solsona, Ester ; Gault-Ringold, Melanie ; George, Ejin ; Gerringa, Loes J. A. ; Gilbert, Melissa ; Godoy, Jose Marcus ; Goldstein, Steven L. ; Gonzalez, Santiago ; Grissom, Karen ; Hammerschmidt, Chad R. ; Hartman, Alison ; Hassler, Christel ; Hathorne, Ed C. ; Hatta, Mariko ; Hawco, Nicholas J. ; Hayes, Christopher T. ; Heimbürger, Lars-Eric ; Helgoe, Josh ; Heller, Maija Iris ; Henderson, Gideon M. ; Henderson, Paul B. ; van Heuven, Steven ; Ho, Peng ; Horner, Tristan J. ; Hsieh, Yu-Te ; Huang, Kuo-Fang ; Humphreys, Matthew P. ; Isshiki, Kenji ; Jacquot, Jeremy E. ; Janssen, David J. ; Jenkins, William J. ; John, Seth ; Jones, Elizabeth M. ; Jones, Janice L. ; Kadko, David ; Kayser, Rick ; Kenna, Timothy C. ; Khondoker, Roulin ; Kim, Taejin ; Kipp, Lauren ; Klar, Jessica K. ; Klunder, Maarten ; Kretschmer, Sven ; Kumamoto, Yuichiro ; Laan, Patrick ; Labatut, Marie ; Lacan, Francois ; Lam, Phoebe J. ; Lambelet, Myriam ; Lamborg, Carl H. ; le Moigne, Frederique ; Le Roy, Emilie ; Lechtenfeld, Oliver J. ; Lee, Jong-Mi ; Lherminier, Pascale ; Little, Susan ; López-Lora, Mercedes ; Lu, Yanbin ; Masque, Pere ; Mawji, Edward ; McClain, Charles R. ; Measures, Christopher I. ; Mehic, Sanjin ; Menzel Barraqueta, Jan-Lukas ; Merwe, Pier van der ; Middag, Rob ; Mieruch, Sebastian ; Milne, Angela ; Minami, Tomoharu ; Moffett, James W. ; Moncoiffe, Gwenaelle ; Moore, Willard S. ; Morris, Paul J. ; Morton, Peter L. ; Nakaguchi, Yuzuru ; Nakayama, Noriko ; Niedermiller, John ; Nishioka, Jun ; Nishiuchi, Akira ; Noble, Abigail E. ; Obata, Hajime ; Ober, Sven ; Ohnemus, Daniel C. ; van Ooijen, Jan ; O'Sullivan, Jeanette ; Owens, Stephanie A. ; Pahnke, Katharina ; Paul, Maxence ; Pavia, Frank ; Pena, Leopoldo D. ; Peters, Brian ; Planchon, Frederic ; Planquette, Helene ; Pradoux, Catherine ; Puigcorbé, Viena ; Quay, Paul D. ; Queroue, Fabien ; Radic, Amandine ; Rauschenberg, Sara ; Rehkämper, Mark ; Rember, Robert ; Remenyi, Tomas A. ; Resing, Joseph A. ; Rickli, Joerg ; Rigaud, Sylvain ; Rijkenberg, Micha J. A. ; Rintoul, Stephen R. ; Robinson, Laura F. ; Roca-Martí, Montserrat ; Rodellas, Valenti ; Roeske, Tobias ; Rolison, John M. ; Rosenberg, Mark ; Roshan, Saeed ; Rutgers van der Loeff, Michiel M. ; Ryabenko, Evgenia ; Saito, Mak A. ; Salt, Lesley ; Sanial, Virginie ; Sarthou, Geraldine ; Schallenberg, Christina ; Schauer, Ursula ; Scher, Howie ; Schlosser, Christian ; Schnetger, Bernhard ; Scott, Peter M. ; Sedwick, Peter N. ; Semiletov, Igor P. ; Shelley, Rachel U. ; Sherrell, Robert M. ; Shiller, Alan M. ; Sigman, Daniel M. ; Singh, Sunil Kumar ; Slagter, Hans ; Slater, Emma ; Smethie, William M. ; Snaith, Helen ; Sohrin, Yoshiki ; Sohst, Bettina M. ; Sonke, Jeroen E. ; Speich, Sabrina ; Steinfeldt, Reiner ; Stewart, Gillian ; Stichel, Torben ; Stirling, Claudine H. ; Stutsman, Johnny ; Swarr, Gretchen J. ; Swift, James H. ; Thomas, Alexander ; Thorne, Kay ; Till, Claire P. ; Till, Ralph ; Townsend, Ashley T. ; Townsend, Emily ; Tuerena, Robyn ; Twining, Benjamin S. ; Vance, Derek ; Velazquez, Sue ; Venchiarutti, Celia ; Villa-Alfageme, Maria ; Vivancos, Sebastian M. ; Voelker, Antje H. L. ; Wake, Bronwyn ; Warner, Mark J. ; Watson, Ros ; van Weerlee, Evaline ; Weigand, M. Alexandra ; Weinstein, Yishai ; Weiss, Dominik ; Wisotzki, Andreas ; Woodward, E. Malcolm S. ; Wu, Jingfeng ; Wu, Yingzhe ; Wuttig, Kathrin ; Wyatt, Neil ; Xiang, Yang ; Xie, Ruifang C. ; Xue, Zichen ; Yoshikawa, Hisayuki ; Zhang, Jing ; Zhang, Pu ; Zhao, Ye ; Zheng, Linjie ; Zheng, Xin-Yuan ; Zieringer, Moritz ; Zimmer, Louise A. ; Ziveri, Patrizia ; Zunino, Patricia ; Zurbrick, CherylThe GEOTRACES Intermediate Data Product 2017 (IDP2017) is the second publicly available data product of the international GEOTRACES programme, and contains data measured and quality controlled before the end of 2016. The IDP2017 includes data from the Atlantic, Pacific, Arctic, Southern and Indian oceans, with about twice the data volume of the previous IDP2014. For the first time, the IDP2017 contains data for a large suite of biogeochemical parameters as well as aerosol and rain data characterising atmospheric trace element and isotope (TEI) sources. The TEI data in the IDP2017 are quality controlled by careful assessment of intercalibration results and multi-laboratory data comparisons at crossover stations. The IDP2017 consists of two parts: (1) a compilation of digital data for more than 450 TEIs as well as standard hydrographic parameters, and (2) the eGEOTRACES Electronic Atlas providing an on-line atlas that includes more than 590 section plots and 130 animated 3D scenes. The digital data are provided in several formats, including ASCII, Excel spreadsheet, netCDF, and Ocean Data View collection. Users can download the full data packages or make their own custom selections with a new on-line data extraction service. In addition to the actual data values, the IDP2017 also contains data quality flags and 1-σ data error values where available. Quality flags and error values are useful for data filtering and for statistical analysis. Metadata about data originators, analytical methods and original publications related to the data are linked in an easily accessible way. The eGEOTRACES Electronic Atlas is the visual representation of the IDP2017 as section plots and rotating 3D scenes. The basin-wide 3D scenes combine data from many cruises and provide quick overviews of large-scale tracer distributions. These 3D scenes provide geographical and bathymetric context that is crucial for the interpretation and assessment of tracer plumes near ocean margins or along ridges. The IDP2017 is the result of a truly international effort involving 326 researchers from 25 countries. This publication provides the critical reference for unpublished data, as well as for studies that make use of a large cross-section of data from the IDP2017. This article is part of a special issue entitled: Conway GEOTRACES - edited by Tim M. Conway, Tristan Horner, Yves Plancherel, and Aridane G. González.
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ArticleBarium in seawater: dissolved distribution, relationship to silicon, and barite saturation state determined using machine learning(Copernicus Publications, 2023-09-13) Mete, Oyku Z. ; Subhas, Adam V. ; Kim, Heather H. ; Dunlea, Ann G. ; Whitmore, Laura M. ; Shiller, Alan M. ; Gilbert, Melissa ; Leavitt, William D. ; Horner, Tristan J.Barium is widely used as a proxy for dissolved silicon and particulate organic carbon fluxes in seawater. However, these proxy applications are limited by insufficient knowledge of the dissolved distribution of Ba ([Ba]). For example, there is significant spatial variability in the barium–silicon relationship, and ocean chemistry may influence sedimentary Ba preservation. To help address these issues, we developed 4095 models for predicting [Ba] using Gaussian process regression machine learning. These models were trained to predict [Ba] from standard oceanographic observations using GEOTRACES data from the Arctic, Atlantic, Pacific, and Southern oceans. Trained models were then validated by comparing predictions against withheld [Ba] data from the Indian Ocean. We find that a model trained using depth, temperature, and salinity, as well as dissolved dioxygen, phosphate, nitrate, and silicate, can accurately predict [Ba] in the Indian Ocean with a mean absolute percentage deviation of 6.0 %. We use this model to simulate [Ba] on a global basis using these same seven predictors in the World Ocean Atlas. The resulting [Ba] distribution constrains the Ba budget of the ocean to 122(±7) × 1012 mol and reveals oceanographically consistent variability in the barium–silicon relationship. We then calculate the saturation state of seawater with respect to barite. This calculation reveals systematic spatial and vertical variations in marine barite saturation and shows that the ocean below 1000 m is at equilibrium with respect to barite. We describe a number of possible applications for our model outputs, ranging from use in mechanistic biogeochemical models to paleoproxy calibration. Our approach demonstrates the utility of machine learning in accurately simulating the distributions of tracers in the sea and provides a framework that could be extended to other trace elements. Our model, the data used in training and validation, and global outputs are available in Horner and Mete (2023, https://doi.org/10.26008/1912/bco-dmo.885506.2).