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  • 1
    facet.materialart.
    Unknown
    Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2012)
    PANGAEA
    In:  Supplement to: Luo, Yawei; Doney, Scott C; Anderson, L A; Benavides, Mar; Berman-Frank, I; Bode, Antonio; Bonnet, S; Boström, Kjärstin H; Böttjer, D; Capone, D G; Carpenter, E J; Chen, Yaw-Lin; Church, Matthew J; Dore, John E; Falcón, Luisa I; Fernández, A; Foster, R A; Furuya, Ken; Gomez, Fernando; Gundersen, Kjell; Hynes, Annette M; Karl, David Michael; Kitajima, Satoshi; Langlois, Rebecca; LaRoche, Julie; Letelier, Ricardo M; Marañón, Emilio; McGillicuddy Jr, Dennis J; Moisander, Pia H; Moore, C Mark; Mouriño-Carballido, Beatriz; Mulholland, Margaret R; Needoba, Joseph A; Orcutt, Karen M; Poulton, Alex J; Rahav, Eyal; Raimbault, Patrick; Rees, Andrew; Riemann, Lasse; Shiozaki, Takuhei; Subramaniam, Ajit; Tyrrell, Toby; Turk-Kubo, Kendra A; Varela, Manuel; Villareal, Tracy A; Webb, Eric A; White, Angelicque E; Wu, Jingfeng; Zehr, Jonathan P (2012): Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth System Science Data, 4, 47-73, https://doi.org/10.5194/essd-4-47-2012
    Details
    Publication Date: 2023-03-27
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. This is a gridded data product about diazotrophic organisms . There are 6 variables. Each variable is gridded on a dimension of 360 (longitude) * 180 (latitude) * 33 (depth) * 12 (month). The first group of 3 variables are: (1) number of biomass observations, (2) biomass, and (3) special nifH-gene-based biomass. The second group of 3 variables is same as the first group except that it only grids non-zero data. We have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling more than 11,000 direct field measurements including 3 sub-databases: (1) nitrogen fixation rates, (2) cyanobacterial diazotroph abundances from cell counts and (3) cyanobacterial diazotroph abundances from qPCR assays targeting nifH genes. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. Data are assigned to 3 groups including Trichodesmium, unicellular diazotrophic cyanobacteria (group A, B and C when applicable) and heterocystous cyanobacteria (Richelia and Calothrix). Total nitrogen fixation rates and diazotrophic biomass are calculated by summing the values from all the groups. Some of nitrogen fixation rates are whole seawater measurements and are used as total nitrogen fixation rates. Both volumetric and depth-integrated values were reported. Depth-integrated values are also calculated for those vertical profiles with values at 3 or more depths.
    Keywords: MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 1.7 MBytes
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 2
    facet.materialart.
    Unknown
    Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2013)
    PANGAEA
    In:  Supplement to: Luo, Yawei; Doney, Scott C; Anderson, L A; Benavides, Mar; Berman-Frank, I; Bode, Antonio; Bonnet, S; Boström, Kjärstin H; Böttjer, D; Capone, D G; Carpenter, E J; Chen, Yaw-Lin; Church, Matthew J; Dore, John E; Falcón, Luisa I; Fernández, A; Foster, R A; Furuya, Ken; Gomez, Fernando; Gundersen, Kjell; Hynes, Annette M; Karl, David Michael; Kitajima, Satoshi; Langlois, Rebecca; LaRoche, Julie; Letelier, Ricardo M; Marañón, Emilio; McGillicuddy Jr, Dennis J; Moisander, Pia H; Moore, C Mark; Mouriño-Carballido, Beatriz; Mulholland, Margaret R; Needoba, Joseph A; Orcutt, Karen M; Poulton, Alex J; Rahav, Eyal; Raimbault, Patrick; Rees, Andrew; Riemann, Lasse; Shiozaki, Takuhei; Subramaniam, Ajit; Tyrrell, Toby; Turk-Kubo, Kendra A; Varela, Manuel; Villareal, Tracy A; Webb, Eric A; White, Angelicque E; Wu, Jingfeng; Zehr, Jonathan P (2012): Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth System Science Data, 4, 47-73, https://doi.org/10.5194/essd-4-47-2012
    Details
    Publication Date: 2023-12-09
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.
    Keywords: 33KB20020923; 33RR20030714; A2/19921126; A2/1992-11-27; AMT8/1999-05-05; AMT8/1999-05-06; AMT8/1999-05-07; AMT8/1999-05-08; AMT8/1999-05-10; AMT8/1999-05-12; AMT8/1999-05-13; AMT8/1999-05-18; AMT8/1999-05-20; AMT8/1999-05-21; AMT8/1999-05-23; AMT8/1999-05-25; AMT8/1999-05-26; AMT8/1999-05-28; AMT8/1999-05-29; AT19641122; AT19641123; AT19641202; AT19641203; AT19641208; Atlantic; Barbados; Barbados_1974-07-09_1; Barbados_1974-07-16_1; Barbados_1974-07-23_1; Barbados_1974-07-28_1; Barbados_1974-08-07_1; Barbados_1974-08-11_1; Barbados_1974-08-21_1; Barbados_1974-08-27_1; Barbados_1974-09-03_1; Barbados_1974-09-10_1; Barbados_1974-09-17_1; Barbados_1974-09-24_1; Barbados_1974-10-03_1; Barbados_1974-10-08_1; Barbados_1974-10-15_1; Barbados_1974-10-22_1; Barbados_1974-10-29_1; Barbados_1974-11-05_1; Barbados_1974-11-12_1; Barbados_1974-11-19_1; Barbados_1974-11-29_1; Barbados_1974-12-03_1; Barbados_1974-12-10_1; Barbados_1974-12-17_1; Barbados_1974-12-23_1; Barbados_1974-12-30_1; Barbados_1975-01-07_1; Barbados_1975-01-14_1; Barbados_1975-01-21_1; Barbados_1975-01-31_1; Barbados_1975-02-04_1; Barbados_1975-02-11_1; Barbados_1975-02-15_1; Barbados_1975-03-05_1; Barbados_1975-03-18_1; Barbados_1975-04-01_1; Barbados_1975-04-18_1; Barbados_1975-04-29_1; Barbados_1975-05-13_1; Barbados_1975-05-21_1; Barbados_1975-05-27_1; Barbados_1975-06-10_1; Barbados_1975-06-24_1; Barbados_1975-07-08_1; Barbados_1975-08-05_1; Barbados_1975-08-25_1; Barbados_1975-10-15_1; Barbados_1975-11-17_1; Barbados_1975-12-10_1; Barbados_1976-01-02_1; Barbados_1976-01-19_1; Barbados_1976-02-10_1; Barbados_1976-03-12_1; Barbados_1976-04-15_1; Barbados_1976-05-14_1; BATS1995-05-15; BATS1996-10-10; Bermuda, Atlantic Ocean; Bottle, Niskin; CAIBEX-I; CAIBEX-I_2; CAIBEX-I_3; CAIBEX-I_5; CAIBEX-I_6; CAIBEX-II; CAIBEX-II_01; CAIBEX-II_02; CAIBEX-II_03; CAIBEX-II_04; CAIBEX-II_05; CAIBEX-II_06; CAIBEX-II_07; CAIBEX-II_08; CAIBOX; CAIBOX_01; CAIBOX_02; CAIBOX_03; CAIBOX_04; CAIBOX_05; CAIBOX_06; CAIBOX_07; CAIBOX_08; CAIBOX_09; CAIBOX_10; CAIBOX_11; CAIBOX_12; CAIBOX_13; CAIBOX_14; CAIBOX_15; CAIBOX_16; CAIBOX_17; Calculated; Calothrix, associated species; Calothrix, carbon per cell; Calothrix abundance, cells; China Sea; Chlorophyll total, areal concentration; CTD, Seabird; CTD/Rosette; CTD-R; CTD-RO; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Diazotrophs, total biomass as carbon; East China Sea; ECS1993-11-15_1; ECS1993-11-15_2; ECS1993-11-15_3; ECS1993-11-15_4; ECS1993-11-15_5; ECS1993-11-15_6; ECS1994-03-15_1; ECS1994-03-15_2; ECS1994-03-15_3; ECS1994-03-15_4; ECS1994-03-15_5; ECS1994-05-05_1; ECS1994-05-05_2; ECS1994-07-05_1; ECS1994-07-05_2; ECS1994-07-05_3; ECS1994-07-05_4; ECS1995-03-28_1; ECS1995-03-28_2; ECS1995-04-17_1; ECS1995-04-17_2; ECS1995-04-17_3; ECS1995-04-17_4; ECS1995-04-17_5; ECS1995-10-01_1; ECS1995-10-01_10; ECS1995-10-01_11; ECS1995-10-01_12; ECS1995-10-01_13; ECS1995-10-01_2; ECS1995-10-01_3; ECS1995-10-01_4; ECS1995-10-01_5; ECS1995-10-01_6; ECS1995-10-01_7; ECS1995-10-01_8; ECS1995-10-01_9; ECS1996-01-04; ECS1996-04-26_1; ECS1996-04-26_2; ECS1996-04-26_3; ECS1996-04-26_4; ECS1996-04-26_5; ECS1996-04-26_6; ECS1996-04-26_7; ECS1996-04-26_8; ECS1996-04-26_9; Event label; GOFLO; Go-Flo bottles; Gomez2004-10-26; Gomez2004-10-30; Gomez2004-11-03; Gomez2004-11-07; Gomez2004-11-11; Gomez2004-11-15; Gomez2004-11-19; Gomez2004-11-23; Gomez2004-11-27; Gomez2004-12-01; Gomez2004-12-05; Gomez2004-12-09; HakuhoMaru2002-12-07; HakuhoMaru2002-12-09; HakuhoMaru2002-12-11; HakuhoMaru2002-12-13; HakuhoMaru2002-12-15; HakuhoMaru2002-12-17; HakuhoMaru2002-12-18; Heterocyst, biomass; Indian Ocean; Iron; Latitude of event; Longitude of event; MAREMIP; MARine Ecosystem Model Intercomparison Project; Measured at sea surface; Meville2002-06-24; Meville2002-06-26; Meville2002-06-28; Meville2002-06-30; Meville2002-07-02; Meville2002-07-03; Meville2002-07-04; Meville2002-07-05; Meville2002-07-06; Meville2002-07-07; Meville2002-07-08; Meville2002-07-11; Meville2002-07-12; Mirai2003-01-15; Mirai2003-01-17; Mirai2003-01-18; Mirai2003-01-20; Mirai2003-01-21; Mirai2003-01-23; Mirai2003-01-24; Mirai2003-01-26; Mirai2003-01-28; MP-6; MP-6_01; MP-6_02; MP-6_03; MP-6_04; MP-6_05; MP-6_06; MP-6_07; MP-6_08; MP-6_09; MP-6_10; MP-6_11; MP-6_12; MP-6_13; MP-6_14; MP-6_15; MP-6_16; MP-6_17; MP-6_19; MP-6_20; MP-6_21; MP-6_22; MP-6_23; MP-9; MP-9_01; MP-9_02; MP-9_03; MP-9_04; MP-9_05; MP-9_06; MP-9_08; MP-9_09; MP-9_10; MP-9_11; MP-9_12; MP-9_13; MP-9_14; MP-9_15; MP-9_16; MP-9_17; MP-9_18; MP-9_19; MP-9_20; MP-9_21; MP-9_22; MP-9_23; MP-9_24; MP-9_25; MP-9_27; MULT; Multiple investigations; MW19950822_21; NA1975-05-25; NA19750526; NA19750527; NA19750528; NA1975-05-29; NA19750530; NA19750531; NA1975-06-01; NA1975-06-02; NA1975-06-03; NA1975-06-04; NA1975-06-05; NA1975-06-06; NewHorizon2003-08-22; NewHorizon2003-08-25; NewHorizon2003-08-26; NewHorizon2003-08-27; NewHorizon2003-08-28; NewHorizon2003-08-30; NewHorizon2003-08-31; NewHorizon2003-09-01; NewHorizon2003-09-03; NewHorizon2003-09-04; NewHorizon2003-09-05; NewHorizon2003-09-07; NewHorizon2003-09-08; NewHorizon2003-09-09; NewHorizon2003-09-11; NewHorizon2003-09-12; NewHorizon2003-09-13; NewHorizon2003-09-14; NIS; Nitrate; North Atlantic; Northeast Atlantic; North Pacific; North Pacific Ocean; Northwest Pacific; NPO1969-08-28; NPO1969-09-01; NPO1969-09-05; NPO1969-09-09; NPO1969-09-11; NPO1969-09-14; NPO1969-09-17; NPO1969-09-19; NPO1969-09-23; NPO1969-09-27; NPO1969-10-01; NPO1969-10-05; NPO1969-10-10; NWP2002-10-21_1; NWP2002-10-21_2; NWP2002-10-21_3; NWP2002-10-21_4; NWP2002-10-21_5; NWP2004-02-11; NWP2004-02-22; NWP2004-05-05; NWP2004-06-26; NWP2004-06-30; NWP2004-07-04; NWP2004-08-07; NWP2004-11-06; NWP2005-03-31; NWP2005-04-22; NWP2005-04-23; NWP2005-04-24; NWP2005-04-25_1; NWP2005-04-25_2; NWP2005-04-26; NWP2005-04-27; NWP2005-04-28; NWP2005-04-29; NWP2005-04-30_1; NWP2005-04-30_2; NWP2005-05-01; NWP2005-08-10; NWP2005-08-15; NWP2005-11-10; NWP2005-12-26; NWP2006-07-03; NWP2006-10-21; NWP2006-12-20; NWP2006-12-25; NWP2007-01-15; OR-I/414_1; OR-I/414_2; OR-I/448; OR-II/034; OR-II/111_1; OR-II/111_2; OR-II/149_1; OR-II/149_2; Phosphate; Richelia, associated species; Richelia, carbon per cell; Richelia abundance, cells; Roger A. Revelle; RV Kilo Moana; Salinity; Sample comment; Sample method; Sargasso Sea; SargassoSea_1973-09-17; SargassoSea_1973-09-19; SargassoSea_1973-09-20; SargassoSea_1973-09-21; SargassoSea_1973-09-28; SargassoSea_1973-09-29; SargassoSea_1973-10-01; SargassoSea_1973-10-02; SargassoSea_1973-10-03; SargassoSea_1974-02-06; SargassoSea_1974-02-08; SargassoSea_1974-02-11; SargassoSea_1974-02-12; SargassoSea_1974-02-13; SargassoSea_1974-02-14; SargassoSea_1974-02-16; SargassoSea_1974-02-17; SargassoSea_1974-02-18; SargassoSea_1974-02-19; SargassoSea_1974-02-20; SargassoSea_1974-02-21; SargassoSea_1974-02-22; SargassoSea_1974-02-26; SargassoSea_1974-02-27; SargassoSea_1974-03-01; SargassoSea_1974-03-02; SargassoSea_1974-03-03; SargassoSea_1974-03-04; SargassoSea_1974-03-05; SargassoSea_1974-08-08; SargassoSea_1974-08-09; SargassoSea_1974-08-10_1; SargassoSea_1974-08-10_2; SargassoSea_1974-08-11; SargassoSea_1974-08-12; SargassoSea_1974-08-13; SargassoSea_1974-08-14; SargassoSea_1974-08-15; SargassoSea_1974-08-16; SargassoSea_1974-08-17; SargassoSea_1974-08-18; SargassoSea_1974-08-19; SargassoSea_1974-08-20; SargassoSea_1974-08-21; Sarmiento de Gamboa; SCS2000-07-04; SCS2000-07-08; SCS2000-07-12; SCS2000-10-05; SCS2000-10-06; SCS2000-10-07; SCS2000-10-08; SCS2000-10-09; SCS2000-10-10; SCS2000-10-11; SCS2000-10-12; SCS2001-03-21; SCS2001-03-22; SCS2001-03-23; SCS2001-03-24; SCS2001-03-25; SCS2001-03-26; SCS2001-03-27; SCS2001-03-28; SCS2001-03-29; SCS2001-03-30; SCS2001-06-28; SCS2001-06-30; SCS2001-07-02; SCS2001-07-04; SCS2001-07-06; SCS2001-10-23; SCS2001-10-25; SCS2001-10-27; SCS2001-10-29; SCS2001-10-31; SCS2002-03-04; SCS2002-03-05; SCS2002-03-06; SCS2002-03-07; SCS2002-03-08; SCS2002-03-09; SCS2002-03-10;
    Type: Dataset
    Format: text/tab-separated-values, 8546 data points
    Location Call Number Expected Availability
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    DATA PANGAEA
  • 3
    facet.materialart.
    Unknown
    Global distributions of diazotrophs nitrogen fixation rates - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2013)
    PANGAEA
    In:  Supplement to: Luo, Yawei; Doney, Scott C; Anderson, L A; Benavides, Mar; Berman-Frank, I; Bode, Antonio; Bonnet, S; Boström, Kjärstin H; Böttjer, D; Capone, D G; Carpenter, E J; Chen, Yaw-Lin; Church, Matthew J; Dore, John E; Falcón, Luisa I; Fernández, A; Foster, R A; Furuya, Ken; Gomez, Fernando; Gundersen, Kjell; Hynes, Annette M; Karl, David Michael; Kitajima, Satoshi; Langlois, Rebecca; LaRoche, Julie; Letelier, Ricardo M; Marañón, Emilio; McGillicuddy Jr, Dennis J; Moisander, Pia H; Moore, C Mark; Mouriño-Carballido, Beatriz; Mulholland, Margaret R; Needoba, Joseph A; Orcutt, Karen M; Poulton, Alex J; Rahav, Eyal; Raimbault, Patrick; Rees, Andrew; Riemann, Lasse; Shiozaki, Takuhei; Subramaniam, Ajit; Tyrrell, Toby; Turk-Kubo, Kendra A; Varela, Manuel; Villareal, Tracy A; Webb, Eric A; White, Angelicque E; Wu, Jingfeng; Zehr, Jonathan P (2012): Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth System Science Data, 4, 47-73, https://doi.org/10.5194/essd-4-47-2012
    Details
    Publication Date: 2023-12-18
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs nitrogen fixation rates, computed from a collection of source data sets.
    Keywords: 33KB20020923; 33RR20030714; Alis; ALOHA2000-07-26; ALOHA2000-11-30; ALOHA2001-03-21; ALOHA2001-06-14; ALOHA2004-11-28; ALOHA2005-02-02; ALOHA2005-03-05; ALOHA2005-06-15; ALOHA2005-07-16; ALOHA2005-08-14; ALOHA2005-09-09; ALOHA2005-10-08; ALOHA2005-11-16; ALOHA2005-12-13; ALOHA2006-01-25; ALOHA2006-02-15; ALOHA2006-03-10; ALOHA2006-04-01; ALOHA2006-05-26; ALOHA2006-06-13; ALOHA2006-07-12; ALOHA2006-08-08; ALOHA2006-09-15; ALOHA2006-10-19; ALOHA2006-11-08; ALOHA2006-12-09; ALOHA2007-02-06; ALOHA2007-03-20; ALOHA2007-05-03; ALOHA2007-06-09; ALOHA2007-07-07; ALOHA2007-08-02; ALOHA2007-09-02; ALOHA2007-12-20; ALOHA2008-01-28; ALOHA2008-02-23; ALOHA2008-05-27; ALOHA2008-06-25; ALOHA2008-07-26; ALOHA2008-08-17; ALOHA2008-10-11; ALOHA2008-12-01; ALOHA2009-01-21; ALOHA2009-02-18; ALOHA2009-04-29; ALOHA2009-05-28; ALOHA2009-07-04; ALOHA2009-07-25; ALOHA2009-09-26; ALOHA2009-11-05; ALOHA2010-04-08; ALOHA2010-05-20; ALOHA2010-06-10; ALOHA2010-07-10; ALOHA2010-08-09; ALOHA2010-09-05; ALOHA2010-10-05; AMT17/01; AMT17/02; AMT17/03; AMT17/04; AMT17/05; AMT17/06; AMT17/07; AMT17/08; AMT17/09; AMT17/10; Arabian Sea; AT19641122; AT19641123; AT19641202; AT19641203; Atalante20080627; Atalante20080628; Atalante20080704; Atalante20080705; Atalante20080709/1; Atalante20080710; Atalante20080712; Atalante20080713; Atalante20080714; Atlantic; BIOSOPE_EGY; BIOSOPE_GYR; BIOSOPE_HLNC; BIOSOPE_MAR; BIOSOPE_UPW; BIOSOPE04-10-28; BIOSOPE04-10-30; BIOSOPE04-11-03; BIOSOPE04-11-04; BIOSOPE04-11-06; BIOSOPE04-11-07; BIOSOPE04-11-08; BIOSOPE04-11-10; BIOSOPE04-11-12; BIOSOPE04-11-20; BIOSOPE04-11-21; BIOSOPE04-11-23; BIOSOPE04-11-24; BIOSOPE04-11-28; BIOSOPE04-12-01; BIOSOPE04-12-02; BIOSOPE04-12-03; BIOSOPE04-12-04; BIOSOPE04-12-05; Bottle, Niskin; CAIBEX-I; CAIBEX-I_1; CAIBEX-I_2; CAIBEX-I_3; CAIBEX-I_4; CAIBEX-I_5; CAIBEX-I_6; CAIBEX-I_7; CAIBEX-II; CAIBEX-II_01; CAIBEX-II_02; CAIBEX-II_03; CAIBEX-II_04; CAIBEX-II_05; CAIBEX-II_06; CAIBEX-II_07; CAIBEX-II_08; CAIBOX; CAIBOX_01; CAIBOX_02; CAIBOX_03; CAIBOX_04; CAIBOX_05; CAIBOX_06; CAIBOX_07; CAIBOX_08; CAIBOX_09; CAIBOX_10; CAIBOX_11; CAIBOX_12; CAIBOX_13; CAIBOX_14; CAIBOX_15; CAIBOX_16; CAIBOX_17; Calculated; Cape Verde; CATO-I/9; Chlorophyll total, areal concentration; CLIMAX_VII/1973-08-18; CLIMAX_VII/1973-08-27; CLIMAX_VII/1973-08-29; CLIMAX_VII/1973-08-31; CLIMAX_VII/1973-09-02; CLIMAX_VII/1973-09-04; CLIMAX_VII/1973-09-07; CLIMAX_VII/1973-09-09; Cook25_7; CTD/Rosette; CTD-RO; D325_Stn-A-01; D325_Stn-C-01; D325_Stn-D-07; D325_Stn-E-01; D325_Stn-F-07; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Diapalis-3; Diapalis-3_1; Diapalis-3_2; Diapalis-3_3; Diapalis-3_4; Diapalis-4; Diapalis-4_1; Diapalis-4_2; Diapalis-4_3; Diapalis-4_4; Diapalis-5; Diapalis-5_1; Diapalis-5_3; Diapalis-5_4; Diapalis-5_5; Diapalis-6; Diapalis-6_1; Diapalis-6_2; Diapalis-6_3; Diapalis-6_4; Diapalis-6_5; Diapalis-6_6; Diapalis-7; Diapalis-7_1; Diapalis-7_2; Diapalis-7_3; Diapalis-7_4; Diapalis-7_6; Diapalis-7_7; Diapalis-9; Diapalis-9_1; Diapalis-9_2; Diapalis-9_3; Diapalis-9_4; Diapalis-9_5; DIAPAZON_Diapalis-3; DIAPAZON_Diapalis-4; DIAPAZON_Diapalis-5; DIAPAZON_Diapalis-6; DIAPAZON_Diapalis-7; DIAPAZON_Diapalis-9; DYFAMED2003-03-26; DYFAMED2003-03-30; DYFAMED2004-01-25; DYFAMED2004-02-24; DYFAMED2004-04-25; DYFAMED2004-05-27; DYFAMED2004-07-01; DYFAMED2004-07-31; DYFAMED2004-08-31; DYFAMED2004-09-18; DYFAMED2004-10-14; Equatorial Pacific; Event label; GoA_StnA2010-03-18; GOFLO; Go-Flo bottles; Gulf of Aqaba; Gundersen_1; Gundersen_2; Hawaiian Islands, North Central Pacific; Hesperides_03a; Hesperides_05a; Hesperides_06a; Hesperides_07a; Hesperides_08a; Hesperides_12a; Hesperides_13a; Hesperides_14a; Hesperides_17a; Hesperides_18a; Hesperides_19a; Hesperides_20a; Hesperides_21a; Hesperides_23a; Hesperides_24a; Hesperides_25a; Hesperides_26a; Hesperides_27a; Hesperides_28a; Hesperides_29a; Hesperides_30a; Hesperides_31a; Hesperides_32a; Hesperides_33a; Hesperides_34a; Hesperides_36a; Hesperides_37a; Hesperides_38a; Hesperides_39a; Hesperides_40a; Hesperides_41a; Hesperides_42a; Heterocyst, nitrogen fixation rate; Iron; KiloMoana20060609/1; KiloMoana20060609/2; KiloMoana20060821; KiloMoana20060826; KiloMoana20060922; KiloMoana20060923; KiloMoana20060925; KiloMoana20060927; KiloMoana20060930; KiloMoana20061009; Latitude of event; LB2008-09-12; LB2008-09-16; Levantine Basin; Ligurian Sea, Mediterranean; Longitude of event; MAREMIP; MARine Ecosystem Model Intercomparison Project; Measured at sea surface; Mediterranean Sea; Mooring (long time); MOORY; MP-6; MP-6_01; MP-6_02; MP-6_03; MP-6_04; MP-6_05; MP-6_06; MP-6_07; MP-6_08; MP-6_09; MP-6_10; MP-6_11; MP-6_12; MP-6_13; MP-6_14; MP-6_15; MP-6_16; MP-6_18; MP-6_19; MP-6_20; MP-6_21; MP-6_22; MP-6_23; MP-9; MP-9_01; MP-9_02; MP-9_03; MP-9_04; MP-9_05; MP-9_06; MP-9_07; MP-9_09; MP-9_10; MP-9_11; MP-9_12; MP-9_13; MP-9_14; MP-9_15; MP-9_16; MP-9_17; MP-9_18; MP-9_19; MP-9_20; MP-9_21; MP-9_22; MP-9_23; MP-9_24; MP-9_25; MP-9_26; MP-9_27; MR07-01/02; MR07-01/03; MR07-01/04; MR07-01/05; MR07-01/06; MR07-01/07; MR07-01/08; MR07-01/09; MR07-01/10; MR07-01/11; Mulholland_2006-07-01; Mulholland_2006-07-02; Mulholland_2006-07-03; Mulholland_2006-07-04; Mulholland_2006-07-05; Mulholland_2006-07-06; Mulholland_2006-07-07; Mulholland_2006-07-08; Mulholland_2006-07-09; Mulholland_2006-07-10; Mulholland_2006-07-11; Mulholland_2006-07-12; Mulholland_2006-07-13; Mulholland_2006-07-14; Mulholland_2006-10-25; Mulholland_2006-10-26; Mulholland_2006-10-27; Mulholland_2006-10-28; Mulholland_2006-10-29; Mulholland_2006-10-30; Mulholland_2006-10-31; Mulholland_2006-11-01; Mulholland_2006-11-02; Mulholland_2006-11-03; Mulholland_2006-11-04; Mulholland_2006-11-05; Mulholland_2006-11-06; Mulholland_2006-11-07; Mulholland_2006-11-08; Mulholland_2006-11-09; Mulholland_2008-05-03_1; Mulholland_2008-05-04_1; Mulholland_2008-05-05_1; Mulholland_2008-05-05_2; Mulholland_2008-05-06_1; Mulholland_2008-05-07_1; Mulholland_2008-05-10_1; Mulholland_2008-05-11_1; Mulholland_2008-05-12_1; Mulholland_2008-05-13_1; Mulholland_2008-05-14_1; Mulholland_2008-05-15_1; Mulholland_2008-05-16_1; Mulholland_2008-05-17_1; Mulholland_2008-05-18_1; Mulholland_2008-05-19_1; Mulholland_2008-05-20_1; Mulholland_2008-05-21_1; Mulholland_2008-05-22_1; Mulholland_2008-05-24_1; Mulholland_2009-08-17_1; Mulholland_2009-08-18_1; Mulholland_2009-08-18_2; Mulholland_2009-08-19_1; Mulholland_2009-08-19_2; Mulholland_2009-08-20_1; Mulholland_2009-08-20_3; Mulholland_2009-08-21_1; Mulholland_2009-08-21_3; Mulholland_2009-08-22_1; Mulholland_2009-08-22_3; Mulholland_2009-08-23; Mulholland_2009-08-24_1; Mulholland_2009-08-24_3; Mulholland_2009-08-25_3; Mulholland_2009-08-26_3; Mulholland_2009-08-27_2; Mulholland_2009-08-27_3; Mulholland_2009-11-04_2; Mulholland_2009-11-05_1; Mulholland_2009-11-08_1; Mulholland_2009-11-09_3; Mulholland_2009-11-10_3; Mulholland_2009-11-11_1; Mulholland_2009-11-18_1; Mulholland_2009-11-18_3; NA19750526; NA19750527; NA19750528; NA19750530; NA19750531; NIS; Nitrate; Nitrogen fixation rate, integrated per day; Nitrogen fixation rate, whole seawater; North Atlantic; Northeast Atlantic; North Pacific; Pacific; Phosphate; PUMP; Rahav_2009-07-13_1; Rahav_2009-07-14_1; Rahav_2009-07-16_1; Rahav_2009-12-07_1; Rees2004-03-05/01; Rees2004-04-05; Rees2004-05-16; Rees2004-05-19/01; Rees2004-05-21/01; Rees2004-07-05/01; Rees2004-09-05/01; Roger A. Revelle; RV Kilo Moana; Salinity; Sample comment; Sample method; Sargasso Sea; SargassoSea_1973-09-17; SargassoSea_1973-09-19; SargassoSea_1973-09-20; SargassoSea_1973-09-21; SargassoSea_1973-09-28; SargassoSea_1973-09-29; SargassoSea_1973-10-01; SargassoSea_1973-10-02; SargassoSea_1973-10-03; SargassoSea_1974-02-06; SargassoSea_1974-02-08; SargassoSea_1974-02-11; SargassoSea_1974-02-13; SargassoSea_1974-02-14; SargassoSea_1974-02-16; SargassoSea_1974-02-17; SargassoSea_1974-02-18; SargassoSea_1974-02-19; SargassoSea_1974-02-20; SargassoSea_1974-02-21; SargassoSea_1974-02-26;
    Type: Dataset
    Format: text/tab-separated-values, 5926 data points
    Location Call Number Expected Availability
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  • 4
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    Unknown
    Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2013)
    PANGAEA
    Details
    Publication Date: 2024-03-30
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates
    Keywords: MAREDAT_Diazotrophs_Collection; MAREMIP; MARine Ecosystem Model Intercomparison Project
    Type: Dataset
    Format: application/zip, 94 datasets
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  • 5
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    Unknown
    Global distributions of diazotrophs Gamma-A nifH genes abundance - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types (2013)
    PANGAEA
    In:  Supplement to: Luo, Yawei; Doney, Scott C; Anderson, L A; Benavides, Mar; Berman-Frank, I; Bode, Antonio; Bonnet, S; Boström, Kjärstin H; Böttjer, D; Capone, D G; Carpenter, E J; Chen, Yaw-Lin; Church, Matthew J; Dore, John E; Falcón, Luisa I; Fernández, A; Foster, R A; Furuya, Ken; Gomez, Fernando; Gundersen, Kjell; Hynes, Annette M; Karl, David Michael; Kitajima, Satoshi; Langlois, Rebecca; LaRoche, Julie; Letelier, Ricardo M; Marañón, Emilio; McGillicuddy Jr, Dennis J; Moisander, Pia H; Moore, C Mark; Mouriño-Carballido, Beatriz; Mulholland, Margaret R; Needoba, Joseph A; Orcutt, Karen M; Poulton, Alex J; Rahav, Eyal; Raimbault, Patrick; Rees, Andrew; Riemann, Lasse; Shiozaki, Takuhei; Subramaniam, Ajit; Tyrrell, Toby; Turk-Kubo, Kendra A; Varela, Manuel; Villareal, Tracy A; Webb, Eric A; White, Angelicque E; Wu, Jingfeng; Zehr, Jonathan P (2012): Database of diazotrophs in global ocean: abundance, biomass and nitrogen fixation rates. Earth System Science Data, 4, 47-73, https://doi.org/10.5194/essd-4-47-2012
    Details
    Publication Date: 2024-03-30
    Description: The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs Gamma-A nifH genes abundance, computed from a collection of source data sets.
    Keywords: 06MT60_5; 06MT60_5/158; 06MT60_5/159; 06MT60_5/161; 06MT60_5/173; 06MT60_5/180; 06MT60_5/181; 06MT60_5/184; 06MT60_5/187; 06MT60_5/188; 06MT60_5/189; 06MT60_5/190; 06MT60_5/192; 06MT60_5/199; ALOHA2002-12-13; ALOHA2002-12-14; ALOHA2005-07-16; ALOHA2005-07-26_01; ALOHA2005-07-26_02; ALOHA2005-07-26_03; ALOHA2005-07-26_04; ALOHA2005-07-26_05; ALOHA2005-07-26_06; ALOHA2005-07-26_07; ALOHA2005-07-26_08; ALOHA2005-08-13; Arabian Sea; Bottle, Niskin; Calculated; Calothrix, abundance expressed in number of nifH gene copies; Calothrix, associated species; Calothrix, biological trait, ratio expressed in mass of carbon per amount of nifH gene copies; CD132; CD132 _AMBITION; CD132_AMBITION/1; CD132_AMBITION/2; CD132_AMBITION/3; CD132_AMBITION/4; CD132/1; CD132/2; CD132/3; CD132/4; Charles Darwin; China Sea; Chlorophyll a; CTD, Seabird; CTD/Rosette; CTD-R; CTD-RO; Date/Time of event; Depth, bottom/max; Depth, top/min; DEPTH, water; Diazotrophs, total biomass as carbon; Eastern equatorial Atlantic; EEA2007-06-14_Stn8; EEA2007-06-15_Stn9; Event label; Foster2008-07-12; Foster2008-07-14; Foster2008-07-15; Foster2008-07-18; Hawaiian Islands, North Central Pacific; Heterocyst, biomass; In situ pump; Iron; ISP; Latitude of event; Longitude of event; M55_30a; M55_36a; M55_38a; M55_44a; M55_45; M55_48a; M55/1; M60/5; M60/5_158; M60/5_159; M60/5_161; M60/5_163a; M60/5_173; M60/5_180; M60/5_181; M60/5_184; M60/5_187; M60/5_188; M60/5_189; M60/5_190; M60/5_192; M60/5_199; MAREMIP; MARine Ecosystem Model Intercomparison Project; Measured at sea surface; Meteor (1986); NIS; Nitrate; North Atlantic sub-tropical gyre; North Pacific; Phosphate; Proteobacteria, abundance expressed in number of nifH gene copies; Richelia, abundance expressed in number of nifH gene copies; Richelia, associated species; Richelia, biological trait, ratio expressed in mass of carbon per amount of nifH gene copies; Salinity; Sample comment; Sample method; SCS2009-08-10; SCS2009-08-15; SCS2009-08-20; SCS2009-08-25; SO187/2; SO187/2_33-1; SO187/2_44-1; SO187/2_45-1-1a; SO187/2_45-4; SO187/2_46-1; SO187/2_48-1; SO187/2_53-1a; SO187/2_54-2; Sonne; South China Sea; South Pacific Ocean; SPO2003-03-17; SPO2003-03-18; SPO2003-03-19; SPO2003-03-20; SPO2003-03-21; SPO2003-03-22-1; SPO2003-03-22-2; SPO2003-03-24; SPO2003-03-25; SPO2003-03-28; SPO2003-03-29; SPO2003-03-30; SPO2003-03-31; SPO2003-04-02; SPO2003-04-03; SPO2003-04-05; SPO2003-04-06; SPO2003-04-07; SPO2003-04-08; SPO2003-04-09; SPO2003-04-10; SPO2003-04-12; SPO2003-04-13; SW2006-06-22; SW2006-06-23; SW2006-06-27; SW2006-06-28; SW2006-06-29; SW2006-06-30; SW2006-07-01; SW2006-07-03; SW2006-07-04; SW2006-07-06; SW2006-07-07; SW2006-07-12; SW2006-07-13; SW2006-07-14_1; SW2006-07-14_2; SW2006-07-15; SW2006-07-17; SW2006-07-19; SW2006-07-20; SW2006-07-21; Temperature, water; Trichodesmium, abundance expressed in number of nifH gene copies; Trichodesmium, biological trait, ratio expressed in mass of carbon per amount of nifH gene copies; Trichodesmium, biomass as carbon; Tropical Atlantic; Unicellular cyanobacteria, biomass; Unicellular cyanobacteria-A, abundance expressed in number of nifH gene copies; Unicellular cyanobacteria-B, abundance expressed in number of nifH gene copies; Unicellular cyanobacteria-B, biological trait, ratio expressed in mass of carbon per amount of nifH gene copies; Unicellular cyanobacteria-C, abundance expressed in number of nifH gene copies; Unicellular cyanobacteria-C, biological trait, ratio expressed in mass of carbon per amount of nifH gene copies; Uniform resource locator/link to source data file; VIETNAM; Water sample; WesternFlyer2005-10-25; Western tropical north Atlantic; WS; WTNA2003-04-24_01; WTNA2003-04-26; WTNA2003-05-01; WTNA2003-05-04; WTNA2003-05-11; WTNA2003-05-12; WTNA2003-05-13; WTNA2003-05-14; WTNA2003-05-18; WTNA2003-05-20
    Type: Dataset
    Format: text/tab-separated-values, 2032 data points
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  • 6
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    Unknown
    Diazotroph diversity in the sea ice, melt ponds and surface waters of the Eurasian Basin of the Central Arctic Ocean (2016)
    In:  EPIC3Frontiers in Microbiology, 7, pp. 1884
    Details
    Publication Date: 2016-11-23
    Description: The Eurasian basin of the Central Arctic Ocean is nitrogen limited, but little is known about the presence and role of nitrogen-fixing bacteria. Recent studies have indicated the occurrence of diazotrophs in Arctic coastal waters potentially of riverine origin. Here, we investigated the presence of diazotrophs in ice and surface waters of the Central Arctic Ocean in the summer of 2012. We identified diverse communities of putative diazotrophs through targeted analysis of the nifH gene, which encodes the iron protein of the nitrogenase enzyme. We amplified 529 nifH sequences from 26 samples of Arctic melt ponds, sea ice and surface waters. These sequences resolved into 43 clusters at 92% amino acid sequence identity, most of which were non-cyanobacterial phylotypes from sea ice and water samples. One cyanobacterial phylotype related to Nodularia sp. was retrieved from sea ice, suggesting that this important functional group is rare in the Central Arctic Ocean. The diazotrophic community in sea-ice environments appear distinct from other cold-adapted diazotrophic communities, such as those present in the coastal Canadian Arctic, the Arctic tundra and glacial Antarctic lakes. Molecular fingerprinting of nifH and the intergenic spacer region of the rRNA operon revealed differences between the communities from river-influenced Laptev Sea waters and those from ice-related environments pointing towards a marine origin for sea-ice diazotrophs. Our results provide the first record of diazotrophs in the Central Arctic and suggest that microbial nitrogen fixation may occur north of 77ºN. To assess the significance of nitrogen fixation for the nitrogen budget of the Arctic Ocean and to identify the active nitrogen fixers, further biogeochemical and molecular biological studies are needed.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , peerRev , info:eu-repo/semantics/article
    Format: application/pdf
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  • 7
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    Distinct siderophores contribute to iron cycling in the mesopelagic at Station ALOHA (2018)
    Frontiers Media
    Details
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Frontiers in Marine Science 5 (2018): 61, doi:10.3389/fmars.2018.00061.
    Description: The distribution of dissolved iron (Fe), total organic Fe-binding ligands, and siderophores were measured between the surface and 400 m at Station ALOHA, a long term ecological study site in the North Pacific Subtropical Gyre. Dissolved Fe concentrations were low throughout the water column and strong organic Fe-binding ligands exceeded dissolved Fe at all depths; varying from 0.9 nmol L−1 in the surface to 1.6 nmol L−1 below 150 m. Although Fe does not appear to limit microbial production, we nevertheless found siderophores at nearly all depths, indicating some populations of microbes were responding to Fe stress. Ferrioxamine siderophores were most abundant in the upper water column, with concentrations between 0.1 and 2 pmol L−1, while a suite of amphibactins were found below 200 m with concentrations between 0.8 and 11 pmol L−1. The distinct vertical distribution of ferrioxamines and amphibactins may indicate disparate strategies for acquiring Fe from dust in the upper water column and recycled organic matter in the lower water column. Amphibactins were found to have conditional stability constants (log KcondFeL1,Fe′) ranging from 12.0 to 12.5, while ferrioxamines had much stronger conditional stability constants ranging from 14.0 to 14.4, within the range of observed L1 ligands by voltammetry. We used our data to calculate equilibrium Fe speciation at Station ALOHA to compare the relative concentration of inorganic and siderophore complexed Fe. The results indicate that the concentration of Fe bound to siderophores was up to two orders of magnitude higher than inorganic Fe, suggesting that even if less bioavailable, siderophores were nevertheless a viable pathway for Fe acquisition by microbes at our study site. Finally, we observed rapid production of ferrioxamine E by particle-associated bacteria during incubation of freshly collected sinking organic matter. Fe-limitation may therefore be a factor in regulating carbon metabolism and nutrient regeneration in the mesopelagic.
    Description: This work was funded by the Woods Hole Oceanographic Postdoctoral Fellowship for RaB, the Simons Foundation (Award 329108), and the National Science Foundation (OCE-1356747).
    Keywords: Iron ; Siderophores ; Station ALOHA ; Organic ligands ; Iron limitation
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 8
    facet.materialart.
    Unknown
    Distinct siderophores contribute to iron cycling in the mesopelagic at station ALOHA (2019)
    Frontiers Media
    Details
    Publication Date: 2019-02-19
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Bundy, R. M., Boiteau, R. M., McLean, C., Turk-Kubo, K. A., Mcllvin, M. R., Saito, M. A., Van Mooy, B. A. S., & Repeta, D. J.. Distinct siderophores contribute to iron cycling in the mesopelagic at station ALOHA. Frontiers in Marine Science, 5, (2018): 61. doi:10.3389/fmars.2018.00061.
    Description: The distribution of dissolved iron (Fe), total organic Fe-binding ligands, and siderophores were measured between the surface and 400 m at Station ALOHA, a long term ecological study site in the North Pacific Subtropical Gyre. Dissolved Fe concentrations were low throughout the water column and strong organic Fe-binding ligands exceeded dissolved Fe at all depths; varying from 0.9 nmol L−1 in the surface to 1.6 nmol L−1 below 150 m. Although Fe does not appear to limit microbial production, we nevertheless found siderophores at nearly all depths, indicating some populations of microbes were responding to Fe stress. Ferrioxamine siderophores were most abundant in the upper water column, with concentrations between 0.1 and 2 pmol L−1, while a suite of amphibactins were found below 200 m with concentrations between 0.8 and 11 pmol L−1. The distinct vertical distribution of ferrioxamines and amphibactins may indicate disparate strategies for acquiring Fe from dust in the upper water column and recycled organic matter in the lower water column. Amphibactins were found to have conditional stability constants (log KcondFeL1,Fe′) ranging from 12.0 to 12.5, while ferrioxamines had much stronger conditional stability constants ranging from 14.0 to 14.4, within the range of observed L1 ligands by voltammetry. We used our data to calculate equilibrium Fe speciation at Station ALOHA to compare the relative concentration of inorganic and siderophore complexed Fe. The results indicate that the concentration of Fe bound to siderophores was up to two orders of magnitude higher than inorganic Fe, suggesting that even if less bioavailable, siderophores were nevertheless a viable pathway for Fe acquisition by microbes at our study site. Finally, we observed rapid production of ferrioxamine E by particle-associated bacteria during incubation of freshly collected sinking organic matter. Fe-limitation may therefore be a factor in regulating carbon metabolism and nutrient regeneration in the mesopelagic.
    Description: We thank Chief Scientists Tara Clemente and Sam Wilson for leading the SCOPE Diel cruises. We also thank the Captain and crew of the R/V Ka'imikai-O-Kanaloa, as well as Paul Henderson in the Woods Hole Oceanographic Nutrient Analytical Facility for nutrient analyses. This work was funded by the Woods Hole Oceanographic Postdoctoral Fellowship for RaB, the Simons Foundation (Award 329108), and the National Science Foundation (OCE-1356747). We also thank two reviewers for helpful comments on the manuscript.
    Keywords: iron ; siderophores ; Station ALOHA ; organic ligands ; iron limitation
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 9
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    Unknown
    Symbiotic unicellular cyanobacteria fix nitrogen in the Arctic Ocean (2018)
    National Academy of Sciences
    Details
    Publication Date: 2018-12-11
    Description: Biological dinitrogen (N2) fixation is an important source of nitrogen (N) in low-latitude open oceans. The unusual N2-fixing unicellular cyanobacteria (UCYN-A)/haptophyte symbiosis has been found in an increasing number of unexpected environments, including northern waters of the Danish Straight and Bering and Chukchi Seas. We used nanoscale secondary ion mass spectrometry (nanoSIMS) to measure 15N2 uptake into UCYN-A/haptophyte symbiosis and found that UCYN-A strains identical to low-latitude strains are fixing N2 in the Bering and Chukchi Seas, at rates comparable to subtropical waters. These results show definitively that cyanobacterial N2 fixation is not constrained to subtropical waters, challenging paradigms and models of global N2 fixation. The Arctic is particularly sensitive to climate change, and N2 fixation may increase in Arctic waters under future climate scenarios.
    Print ISSN: 0027-8424
    Electronic ISSN: 1091-6490
    Topics: Biology , Medicine , Natural Sciences in General
    Published by National Academy of Sciences
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    Phytoplankton transcriptomic and physiological responses to fixed nitrogen in the California current system (2020)
    Public Library of Science
    Details
    Publication Date: 2020-04-20
    Electronic ISSN: 1932-6203
    Topics: Medicine , Natural Sciences in General
    Published by Public Library of Science
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