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  • 1
    facet.materialart.
    Unknown
    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
    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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  • 2
    facet.materialart.
    Unknown
    PANGAEA
    In:  Supplement to: Hauck, Judith; Völker, Christoph; Wolf-Gladrow, Dieter A; Laufkötter, Charlotte; Vogt, Meike; Aumont, Olivier; Bopp, Laurent; Buitenhuis, Erik Theodoor; Doney, Scott C; Dunne, John; Gruber, Nicolas; Hashioka, Taketo; John, Jasmin; Le Quéré, Corinne; Lima, Ivan D; Nakano, Hideyuki; Séférian, Roland; Totterdell, Ian J (2015): On the Southern Ocean CO2 uptake and the role of the biological carbon pump in the 21st century. Global Biogeochemical Cycles, 29(9), 1451-1470, https://doi.org/10.1002/2015GB005140
    Publication Date: 2023-01-13
    Description: We use a suite of eight ocean biogeochemical/ecological general circulation models from the MAREMIP and CMIP5 archives to explore the relative roles of changes in winds (positive trend of Southern Annular Mode, SAM) and in warming- and freshening-driven trends of upper ocean stratification in altering export production and CO2 uptake in the Southern Ocean at the end of the 21st century. The investigated models simulate a broad range of responses to climate change, with no agreement ona dominance of either the SAM or the warming signal south of 44° S. In the southernmost zone, i.e., south of 58° S, they concur on an increase of biological export production, while between 44 and 58° S the models lack consensus on the sign of change in export. Yet, in both regions, the models show an enhanced CO2 uptake during spring and summer. This is due to a larger CO 2 (aq) drawdown by the same amount of summer export production at a higher Revelle factor at the end of the 21st century. This strongly increases the importance of the biological carbon pump in the entire Southern Ocean. In the temperate zone, between 30 and 44° S all models show a predominance of the warming signal and a nutrient-driven reduction of export production. As a consequence, the share of the regions south of 44° S to the total uptake of the Southern Ocean south of 30° S is projected to increase at the end of the 21st century from 47 to 66% with a commensurable decrease to the north. Despite this major reorganization of the meridional distribution of the major regions of uptake, the total uptake increases largely in line with the rising atmospheric CO2. Simulations with the MITgcm-REcoM2 model show that this is mostly driven by the strong increase of atmospheric CO2, with the climate-driven changes of natural CO2 exchange offsetting that trend only to a limited degree (~10%) and with negligible impact of climate effects on anthropogenic CO2 uptake when integrated over a full annual cycle south of 30° S.
    Keywords: File content; Uniform resource locator/link to file; Uniform resource locator/link to image
    Type: Dataset
    Format: text/tab-separated-values, 27 data points
    Location Call Number Expected Availability
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  • 3
    facet.materialart.
    Unknown
    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
    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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  • 4
    facet.materialart.
    Unknown
    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
    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
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  • 5
    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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  • 6
    facet.materialart.
    Unknown
    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
    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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  • 7
    Electronic Resource
    Electronic Resource
    [s.l.] : Nature Publishing Group
    Nature 444 (2006), S. 695-696 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Oranges in Florida, wildfires in Indonesia, plankton in the North Pacific — what links these seemingly disparate items is that they are all affected by year-to-year fluctuations in global-scale climate. On page 752 of this issue, Behrenfeld et al. describe how such fluctuations, ...
    Type of Medium: Electronic Resource
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  • 8
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] Today's surface ocean is saturated with respect to calcium carbonate, but increasing atmospheric carbon dioxide concentrations are reducing ocean pH and carbonate ion concentrations, and thus the level of calcium carbonate saturation. Experimental evidence suggests that if these trends ...
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    [s.l.] : Macmillan Magazines Ltd.
    Nature 389 (1997), S. 905-906 
    ISSN: 1476-4687
    Source: Nature Archives 1869 - 2009
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Notes: [Auszug] The loss of photosynthetically generated carbon from the ocean's surface waters is a central mechanism in the global carbon cycle. Analyses of the results from three independent techniques give us the best estimate yet of the scale of this ‘export’ process. The vast, ...
    Type of Medium: Electronic Resource
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  • 10
    Electronic Resource
    Electronic Resource
    Palo Alto, Calif. : Annual Reviews
    Annual Review of Environment and Resources 28 (2003), S. 521-558 
    ISSN: 1543-5938
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
    Topics: Energy, Environment Protection, Nuclear Power Engineering
    Notes: Agriculture and industrial development have led to inadvertent changes in the natural carbon cycle. As a consequence, concentrations of carbon dioxide and other greenhouse gases have increased in the atmosphere and may lead to changes in climate. The current challenge facing society is to develop options for future management of the carbon cycle. A variety of approaches has been suggested: direct reduction of emissions, deliberate manipulation of the natural carbon cycle to enhance sequestration, and capture and isolation of carbon from fossil fuel use. Policy development to date has laid out some of the general principles to which carbon management should adhere. These are summarized as: how much carbon is stored, by what means, and for how long. To successfully manage carbon for climate purposes requires increased understanding of carbon cycle dynamics and improvement in the scientific capabilities available for measurement as well as for policy needs. The specific needs for scientific information to underpin carbon cycle management decisions are not yet broadly known. A stronger dialogue between decision makers and scientists must be developed to foster improved application of scientific knowledge to decisions. This review focuses on the current knowledge of the carbon cycle, carbon measurement capabilities (with an emphasis on the continental scale) and the relevance of carbon cycle science to carbon sequestration goals.
    Type of Medium: Electronic Resource
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