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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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    DATA PANGAEA
  • 4
    facet.materialart.
    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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    DATA PANGAEA
  • 5
    facet.materialart.
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    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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    SeaFlow data v1, high-resolution abundance, size and biomass of small phytoplankton in the North Pacific (2019)
    Springer Nature
    Details
    Publication Date: 2019-11-22
    Electronic ISSN: 2052-4463
    Topics: Nature of Science, Research, Systems of Higher Education, Museum Science
    Published by Springer Nature
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    PAPER CURRENT
  • 7
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    Unknown
    An individual-based model for the analysis of Prochlorococcus diel cycle behavior (2015)
    Elsevier
    Details
    Publication Date: 2015-04-01
    Print ISSN: 0304-3800
    Electronic ISSN: 1872-7026
    Topics: Biology
    Published by Elsevier
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  • 8
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    Unknown
    Assessing cell cycle-based methods of measuring Prochlorococcus division rates using an individual-based model (2015)
    Wiley
    Details
    Publication Date: 2015-07-17
    Electronic ISSN: 1541-5856
    Topics: Biology , Geosciences
    Published by Wiley on behalf of Association for the Sciences of Limnology and Oceanography.
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  • 9
    facet.materialart.
    Unknown
    Cross-basin comparison of phosphorus stress and nitrogen fixation in Trichodesmium (2009)
    Wiley
    Details
    Publication Date: 2009-06-12
    Print ISSN: 0024-3590
    Electronic ISSN: 1939-5590
    Topics: Biology , Geosciences , Physics
    Published by Wiley on behalf of Association for the Sciences of Limnology and Oceanography.
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  • 10
    facet.materialart.
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    Kīlauea lava fuels phytoplankton bloom in the North Pacific Ocean (2019)
    American Association for the Advancement of Science
    Details
    Publication Date: 2019-09-05
    Description: From June to August 2018, the eruption of Kīlauea volcano on the island of Hawai‘i injected millions of cubic meters of molten lava into the nutrient-poor waters of the North Pacific Subtropical Gyre. The lava-impacted seawater was characterized by high concentrations of metals and nutrients that stimulated phytoplankton growth, resulting in an extensive plume of chlorophyll a that was detectable by satellite. Chemical and molecular evidence revealed that this biological response hinged on unexpectedly high concentrations of nitrate, despite the negligible quantities of nitrogen in basaltic lava. We hypothesize that the high nitrate was caused by buoyant plumes of nutrient-rich deep waters created by the substantial input of lava into the ocean. This large-scale ocean fertilization was therefore a unique perturbation event that revealed how marine ecosystems respond to exogenous inputs of nutrients.
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science
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