Chemical and biological data from CTD Niskin bottle samples from RVIB Nathaniel B. Palmer NBP1201 in the Ross Sea from 2011-2012 (PRISM-RS project)

Website: https://www.bco-dmo.org/dataset/511219
Data Type: Cruise Results
Version: 2017-05-31

Project
» Processes Regulating Iron Supply at the Mesoscale - Ross Sea (PRISM-RS)

Programs
» Ocean Carbon and Biogeochemistry (OCB)
» Integrated Marine Biogeochemistry and Ecosystem Research -US (IMBER-US)
ContributorsAffiliationRole
McGillicuddy, Dennis J.Woods Hole Oceanographic Institution (WHOI)Principal Investigator
Bibby, ThomasUniversity of SouthamptonCo-Principal Investigator
Dinniman, MichaelOld Dominion University (ODU)Co-Principal Investigator
Greenan, BlairBedford Institute of Oceanography (BIO)Co-Principal Investigator
Hofmann, Eileen E.Old Dominion University (ODU)Co-Principal Investigator
Klinck, John M.Old Dominion University (ODU)Co-Principal Investigator
Sedwick, Peter N.Old Dominion University (ODU)Co-Principal Investigator
Smith, Walker O.Virginia Institute of Marine Science (VIMS)Co-Principal Investigator
Kosnyrev, OlgaWoods Hole Oceanographic Institution (WHOI)Data Manager
Biddle, MathewWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager
Copley, NancyWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager


Coverage

Spatial Extent: N:-72.181833 E:-164.2508 S:-77.7955 W:159.0163
Temporal Extent: 2012-01-06 - 2012-02-05

Dataset Description

CTD data including nutrients, particulates, primary productivity, and trace metals from the Ross Sea collected in January and February, 2012


Methods & Sampling

Hydrographic data and water samples were collected using a rosette sampler fitted with 24 10-L Niskin bottles (General Oceanics), an SBE 911 plus conductivity, temperature, and depth (CTD) sensors (SeaBird Electronics) and a WET Labs C-Star transmissometer (see additional instruments below).  Nitrate and other macronutrient concentrations were measured at sea using standard autoanalyzer techniques. Seawater samples for trace metal analysis were collected with custom-modified 5-L Teflon-lined external-closure Niskin-X samplers (General Oceanics) on a trace-metal clean rosette deployed on a nonmetallic line, and dFe was determined post-cruise following the methods described by Sedwick et al. (2011).

Relevant References:

Sedwick, P. N. et al. Early season depletion of dissolved iron in the Ross Sea polynya: Implications for iron dynamics on the Antarctic continental shelf. Journal of Geophysical Research 116, C12019, doi:10.1029/2010jc006553 (2011).


Data Processing Description

2017-05-31 updates:
replaced version:2015-10-09. The original data is still the same but they expanded to include other parameters and made some data corrections.
1. 2 um Particulate TM data is added.
2. HPLC data is added.
3. Bottle file format in part of columns names location.
4. Several DATA CORRECTIONS were made in a process of merging

2015-10-09 updates:
replaced version:2014-04-11. The values are the same but the parameter names and the order of the columns was changed.

2014-04-11:
Original submission
1. Columns in data source:

2,4,6-9: Station info from CTD data files headers;
10: ISO_DateTime_UTC: added by DMO;
3,5,11-30: Sea-Bird SBE 9 CTD BTL data;
31-36: CTD Bottle Nutrients;
37-41: CTD Bottle biological data - Chlorophyll;
42-44: CTD Bottle biological data - Particulates;
45-47: CTD Bottle biological data - Primary productivity.
48-54: TMCTD stations info;
55-96: TMCTD Metals data

2. nd indicates not available data;

3. Flag -999.999 indicates “bad” data

CTD data was merged with TMCTD data at each station using CTD nominal depth and finding TMCTD data inside some depth interval depending on depth level. Nominal depth and location/time data for both instruments is included in the data.


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Data Files

File
bottle_NBP1201.csv
(Comma Separated Values (.csv), 1.37 MB)
MD5:cdd66c7028497079906b0a6d412fd47b
Primary data file for dataset ID 511219

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Parameters

ParameterDescriptionUnits
stastation number unitless
depth_nnominal depth meters
pressCTD pressure decibars
castCTD cast number unitless
bottleCTD bottle number unitless
dateCTD date yyyymmdd
timeCTD time hhmm
latCTD latitude decimal degrees
lonCTD longitude decimal degrees
ISO_DateTime_UTCDate/Time (UTC) ISO formatted YYYY-MM-DDTHH:MM:SS[xx]Z
salsalinity from primary sensor unitless
sal2salinity from secondary sensor unitless
densitysigma-theta density from primary sensor kilograms/meter^3
density2sigma-theta density from secondary sensor kilograms/meter^3
temptemperature from primary sensor degrees Celsius
temp2temperature from secondary sensor degrees Celsius
condconductivity from primary sensor Siemens/meter
cond2conductivity from secondary sensor Siemens/meter
fluorfluorescence milligrams/m^3
transbeam transmission percent
altaltitude meters
parPAR/Irradiance microEinsteins/centimeter^2/second
cparcorrected Irradiance: CPAR = (100 * ratio multiplier * underwater PAR) / surface PAR where ratio multiplier = scaling factor used for comparing light fields of disparate intensity; input in .con file entry for surface PAR sensor. microEinsteins/centimeter^2/second
sparSPAR/Surface Irradiance microEinsteins/centimeter^2/second
O2_voxygen voltage volts
O2_v2oxygen voltage; secondary sensor volts
potemppotential temperature degrees Celsius
potemp2potential temperature; secondary sensor degrees Celsius
O2_ml_L1dissolved oxygen from CTD sensor milliliters per liter
O2_ml_L2dissolved oxygen from CTD secondary sensor milliliters per liter
bottle_nutsCTD bottle number for nutrient analyses unitless
PO4Phosphate concentration microMolar
NO2nitrited concentration microMolar
NO2_NO3nitrate and nitrite concentration microMolar
NH4ammonium concentration microMolar
SiO4silicate concentration microMolar
Fofluorometric reading of non-adicified chlorophyll sample unitless
Fafluorometric reading of adicified chlorophyll sample unitless
Fo_Faratio of chlorophyll-a to phaeopigment based on fluorometric readings of a non acidified (Fo) and acidified (Fa) samples unitless
chl_achlorophyll micrograms/liter
phaeototal phaeopigment micrograms/liter
Bsibiogenic Silica microMolar
PONparticulate organic Nitrogen microMolar
PICparticulate organic Carbon microMolar
PP_L_hrprimary productivity micrograms C/liter/hour
PP_int_hrintegrated primary productivity per hour micrograms C/square meter/hour
PP_int_dayintegrated primary productivity per day micrograms C/square meter/day
cast_tmctdTrace Metal-CTD cast number unitless
lat_tmctdTrace Metal-CTD latitude decimal degrees
lon_tmctdTrace Metal-CTD longitude decimal degrees
bottle_tmctdTrace Metal-CTD bottle number unitless
depth_tmctdTrace Metal-CTD depth meters
date_tmctdTrace Metal-CTDdate yyyymmdd
time_tmctdTrace Metal-CTD time hhmm
dFedissolved Fe concentration nanoMolar
filter_code_0_4micronfilter code for 0.4 micron filter from TMCTD: 1=IC; 2=IE; 3=IR; 4=IF; 5=IG unitless
filter_id_0_4micronfilter number for 0.4 micron filter from TMCTD unitless
vol_filt_0_4micronvolume filtered for 0.4 micron filter from TMCTD liters
Mg_0_4micronconcentration of Magnesium in 0.4 micron filter from TMCTD nanoMolar
Mg_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Al_0_4micronconcentration of Aluminum in 0.4 micron filter from TMCTD nanoMolar
Al_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Si_0_4micronconcentration of Silica in 0.4 micron filter from TMCTD nanoMolar
Si_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
P_0_4micronconcentration of Phophorous in 0.4 micron filter from TMCTD nanoMolar
P_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
S_0_4micronconcentration of Sulfur in 0.4 micron filter from TMCTD nanoMolar
S_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Cl_0_4micronconcentration of Chlorine in 0.4 micron filter from TMCTD nanoMolar
Cl_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
K_0_4micronconcentration of Potassium in 0.4 micron filter from TMCTD nanoMolar
K_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Ca_0_4micronconcentration of Calcium in 0.4 micron filter from TMCTD nanoMolar
Ca_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Ti_0_4micronconcentration of Titanium in 0.4 micron filter from TMCTD nanoMolar
Ti_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
V_0_4micronconcentration of Vanadium in 0.4 micron filter from TMCTD nanoMolar
V_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Cr_0_4micronconcentration of Chromium in 0.4 micron filter from TMCTD nanoMolar
Cr_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Mn_0_4micronconcentration of Manganese in 0.4 micron filter from TMCTD nanoMolar
Mn_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Fe_P_0_4micronconcentration of particulate Iron in 0.4 micron filter from TMCTD nanoMolar
Fe_P_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Ni_0_4micronconcentration of Nickel in 0.4 micron filter from TMCTD nanoMolar
Ni_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Cu_0_4micronconcentration of Copper in 0.4 micron filter from TMCTD nanoMolar
Cu_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Zn_0_4micronconcentration of Zinc in 0.4 micron filter from TMCTD nanoMolar
Zn_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Br_0_4micronconcentration of Bromine in 0.4 micron filter from TMCTD nanoMolar
Br_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Sr_0_4micronconcentration of Strontium in 0.4 micron filter from TMCTD nanoMolar
Sr_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
Pb_0_4micronconcentration of Lead in 0.4 micron filter from TMCTD nanoMolar
Pb_3sd_0_4micron3 standard deviations from TMCTD nanoMolar
prim_prodPrimary Productivity micrograms Carbon/Liter/Hour (ug C/L/h)
prim_prod2Integrated Primary Productivity miligrams Carbon/Meter^2/Hour (mg C/m^2/h)
prim_prod3Integrated Primary Productivity miligrams Carbon/Meter^2/Day (mg C/m^2/d)
filter_code_2micronfilter code for 2 micron filter from TMCTD: 6=IM; 7=IN; 8=IO; 9=IP unitless
filter_id_2micronfilter number for 2 micron filter from TMCTD unitless
vol_filt_2micronvolume filtered for 2 micron filter from TMCTD liters (L)
Mg_2micronconcentration of Magnesium in 2 micron filter from TMCTD nanoMolar
Mg_err_2micronerror from TMCTD nanoMolar
Al_2micronconcentration of Aluminum in 2 micron filter from TMCTD nanoMolar
Al_err_2micronerror from TMCTD nanoMolar
Si_2micronconcentration of Silica in 2 micron filter from TMCTD nanoMolar
Si_err_2micronerror from TMCTD nanoMolar
P_2micronconcentration of Phophorous in 2 micron filter from TMCTD nanoMolar
P_err_2micronerror from TMCTD nanoMolar
S_2micronconcentration of Sulfur in 2 micron filter from TMCTD nanoMolar
S_err_2micronerror from TMCTD nanoMolar
Cl_2micronconcentration of Chlorine in 2 micron filter from TMCTD nanoMolar
Cl_err_2micronerror from TMCTD nanoMolar
K_2micronconcentration of Potassium in 2 micron filter from TMCTD nanoMolar
K_err_2micronerror from TMCTD nanoMolar
Ca_2micronconcentration of Calcium in 2 micron filter from TMCTD nanoMolar
Ca_err_2micronerror from TMCTD nanoMolar
Ti_2micronconcentration of Titanium in 2 micron filter from TMCTD nanoMolar
Ti_err_2micronerror from TMCTD nanoMolar
V_2micronconcentration of Vanadium in 2 micron filter from TMCTD nanoMolar
V_err_2micronerror from TMCTD nanoMolar
Cr_2micronconcentration of Chromium in 2 micron filter from TMCTD nanoMolar
Cr_err_2micronerror from TMCTD nanoMolar
Mn_2micronconcentration of Manganese in 2 micron filter from TMCTD nanoMolar
Mn_err_2micronerror from TMCTD nanoMolar
Fe_P_2micronconcentration of particulate Iron in 2 micron filter from TMCTD nanoMolar
Fe_P_err_2micronerror from TMCTD nanoMolar
Ni_2micronconcentration of Nickel in 2 micron filter from TMCTD nanoMolar
Ni_err_2micronerror from TMCTD nanoMolar
Cu_2micronconcentration of Copper in 2 micron filter from TMCTD nanoMolar
Cu_err_2micronerror from TMCTD nanoMolar
Zn_2micronconcentration of Zinc in 2 micron filter from TMCTD nanoMolar
Zn_err_2micronerror from TMCTD nanoMolar
Br_2micronconcentration of Bromine in 2 micron filter from TMCTD nanoMolar
Br_err_2micronerror from TMCTD nanoMolar
Sr_2micronconcentration of Strontium in 2 micron filter from TMCTD nanoMolar
Sr_err_2micronerror from TMCTD nanoMolar
Pb_2micronconcentration of Lead in 2 micron filter from TMCTD nanoMolar
Pb_err_2micronerror from TMCTD nanoMolar
hplc_sample_numHPLC sample number unitless
hplc_tot_vol_mLHPLC volume filtered seawater mililiters (mL)
hplc_tot_vol_LHPLC volume filtered seawater Liters (L)
hplc_vol_90pcnt_acetonevolume of 90 pcnt acetone microliters (uL)
hplc_vol_CTXvolume of canthaxanthin microliters (uL)
hplc_vol_extract_uLtotal volume extraction (acetone + cantha) (uL) microliters (uL)
hplc_vol_extract_mLVext: total volume extraction (acetone + cantha) mililiters (mL)
hplc_inject_vol_samplefor injection: volume sample microliters (uL)
hplc_buff_volvolume buffer microliter (uL)
hplc_samp_buff_volsample + buffer volume microliter (uL)
hplc_vol_inj_samp_botVinj: vol injected sample + buffer microliter (uL)
hplc_buff_dil_factorB: buffer dilution factor unitless
hplc_chl_c3chlorophyll c3 (RT = 6.200) pick area (Ap) unitless
hplc_periperidinin (partial peak) (see Notes Worksheet) (RT = 9.783) pick area (Ap) unitless
hplc_but1919-butanoyloxyfucoxanthin (RT = 10.850) pick area (Ap) unitless
hplc_fucofucoxanthin (RT = 10.867) pick area (Ap) unitless
hplc_hex1919hex (RT = 11.633) pick area (Ap) unitless
hplc_alloallo (RT 15.3 min) (RT = 15.950) pick area (Ap) unitless
hplc_canthacanthaxanthine (RT = 18.150) pick area (Ap) unitless
hplc_chla_allochla allo pick area (Ap) unitless
hplc_chlachla (RT = 23.316) pick area (Ap) unitless
hplc_chla_epichlorophyll a epimer pick area (Ap) unitless
hplc_chla_sumsum chla pick area (Ap) unitless
hplc_chl_c3_slopeSlope from calibration; total pigment in injected sample; 8945657: chlorophyll c3 micrograms (ug)
hplc_peri_slopeSlope from calibration; total pigment in injected sample; 5631629: peridinin micrograms (ug)
hplc_but19_slopeSlope from calibration; total pigment in injected sample; 8477663: 19-butanoyloxyfucoxanthin micrograms (ug)
hplc_fuco_slopeSlope from calibration; total pigment in injected sample; 8795122: fucoxanthin micrograms (ug)
hplc_hex19_slopeSlope from calibration; total pigment in injected sample; 9134242: 19hex micrograms (ug)
hplc_allo_slopeSlope from calibration; total pigment in injected sample; 10983522: allo micrograms (ug)
hplc_cantha_slopeSlope from calibration; total pigment in injected sample; 8809622: canthaxanthine (red = too low or too high; see Notes worksheet) micrograms (ug)
hplc_chla_slopeSlope from calibration; total pigment in injected sample; 2148822: chla micrograms (ug)
hplc_jeff_chl_c3Jeffrey chlorophyll c3 nanograms/Liter (ng/L)
hplc_jeff_periJeffrey peridinin nanograms/Liter (ng/L)
hplc_jeff_19butJeffrey 19-butanoyloxyfucoxanthin nanograms/Liter (ng/L)
hplc_jeff_fucoJeffrey fucoxanthin nanograms/Liter (ng/L)
hplc_jeff_19hexJeffrey 19hex nanograms/Liter (ng/L)
hplc_jeff_alloJeffrey allo nanograms/Liter (ng/L)
hplc_jeff_canthaJeffrey canthaxanthine nanograms/Liter (ng/L)
hplc_jeff_chlaJeffrey chla nanograms/Liter (ng/L)
hplc_fluor_chl_afluor Chl a micrograms/Liter (ug/L)
hplc_fluor_phaeo_afluor phaeo a micrograms/Liter (ug/L)


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Instruments

Dataset-specific Instrument Name
Niskin bottle
Generic Instrument Name
Niskin bottle
Dataset-specific Description
Rosette fitted with 24 10-L General Oceanics Niskin bottles
Generic Instrument Description
A Niskin bottle (a next generation water sampler based on the Nansen bottle) is a cylindrical, non-metallic water collection device with stoppers at both ends. The bottles can be attached individually on a hydrowire or deployed in 12, 24, or 36 bottle Rosette systems mounted on a frame and combined with a CTD. Niskin bottles are used to collect discrete water samples for a range of measurements including pigments, nutrients, plankton, etc.

Dataset-specific Instrument Name
Altimeter
Generic Instrument Name
Altimeter
Generic Instrument Description
An instrument that measures height above a fixed surface. The data can be used to map ocean-surface topography and generate gridded surface height fields.

Dataset-specific Instrument Name
LI-COR Biospherical PAR
Generic Instrument Name
LI-COR Biospherical PAR Sensor
Generic Instrument Description
The LI-COR Biospherical PAR Sensor is used to measure Photosynthetically Available Radiation (PAR) in the water column. This instrument designation is used when specific make and model are not known.

Dataset-specific Instrument Name
Transmissometer
Generic Instrument Name
Transmissometer
Dataset-specific Description
Chelsea/Seatech transmissometer
Generic Instrument Description
A transmissometer measures the beam attenuation coefficient of the lightsource over the instrument's path-length. This instrument designation is used when specific manufacturer, make and model are not known.

Dataset-specific Instrument Name
HPLC
Generic Instrument Name
High-Performance Liquid Chromatograph
Dataset-specific Description
High Performance Liquid Chromatograph
Generic Instrument Description
A High-performance liquid chromatograph (HPLC) is a type of liquid chromatography used to separate compounds that are dissolved in solution. HPLC instruments consist of a reservoir of the mobile phase, a pump, an injector, a separation column, and a detector. Compounds are separated by high pressure pumping of the sample mixture onto a column packed with microspheres coated with the stationary phase. The different components in the mixture pass through the column at different rates due to differences in their partitioning behavior between the mobile liquid phase and the stationary phase.

Dataset-specific Instrument Name
SBE-43 DO
Generic Instrument Name
Sea-Bird SBE 43 Dissolved Oxygen Sensor
Generic Instrument Description
The Sea-Bird SBE 43 dissolved oxygen sensor is a redesign of the Clark polarographic membrane type of dissolved oxygen sensors. more information from Sea-Bird Electronics

Dataset-specific Instrument Name
CTD SBE 911plus
Generic Instrument Name
CTD Sea-Bird SBE 911plus
Generic Instrument Description
The Sea-Bird SBE 911 plus is a type of CTD instrument package for continuous measurement of conductivity, temperature and pressure. The SBE 911 plus includes the SBE 9plus Underwater Unit and the SBE 11plus Deck Unit (for real-time readout using conductive wire) for deployment from a vessel. The combination of the SBE 9 plus and SBE 11 plus is called a SBE 911 plus. The SBE 9 plus uses Sea-Bird's standard modular temperature and conductivity sensors (SBE 3 plus and SBE 4). The SBE 9 plus CTD can be configured with up to eight auxiliary sensors to measure other parameters including dissolved oxygen, pH, turbidity, fluorescence, light (PAR), light transmission, etc.). more information from Sea-Bird Electronics

Dataset-specific Instrument Name
ECO AFL/FL
Generic Instrument Name
Wet Labs ECO-AFL/FL Fluorometer
Generic Instrument Description
The Environmental Characterization Optics (ECO) series of single channel fluorometers delivers both high resolution and wide ranges across the entire line of parameters using 14 bit digital processing. The ECO series excels in biological monitoring and dye trace studies. The potted optics block results in long term stability of the instrument and the optional anti-biofouling technology delivers truly long term field measurements. more information from Wet Labs

Dataset-specific Instrument Name
Niskin-1010X
Generic Instrument Name
Niskin-1010X
Dataset-specific Description
Custom-modified 5-L Teflon-lined external-closure Niskin-X samplers (General Oceanics) on a trace-metal clean rosette deployed on a nonmetallic line.
Generic Instrument Description
The Model 1010X NISKIN-X External Spring Niskin Water Sampler is a Niskin water sample bottle with the stainless steel closure springs mounted externally. The external closure mechanism is designed to support applications such as trace metal analysis where the inside of the sampler must be totally free of contaminants. The 1010X Niskin bottle, manufactured by General Oceanics Inc., is available in a variety of sizes (sample volume). It can be activated by the GO Devil Messenger (1000-MG) if individually or serially attached to a hydrocable or can be deployed as part of a Rosette multibottle array. The bottles can be teflon-lined and are available as GO-FLO bottles to further avoid sample contamination. (more from General Oceanics)


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Deployments

NBP1201

Website
Platform
RVIB Nathaniel B. Palmer
Report
Start Date
2011-12-24
End Date
2012-02-11
Description
From McMurdo Station to Punta Arenas, Chile More information: http://gcmd.gsfc.nasa.gov/KeywordSearch/Metadata.do?Portal=amd&KeywordPa...


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Project Information

Processes Regulating Iron Supply at the Mesoscale - Ross Sea (PRISM-RS)


Coverage: Ross Sea continental shelf; Southern Ocean


The NSF proposal title was "Impact of Mesoscale Processes on Iron Supply and Phytoplankton Dynamics in the Ross Sea"

The Ross Sea continental shelf is one of the most productive areas in the Southern Ocean, and may comprise a significant, but unaccounted for, oceanic CO2 sink, largely driven by phytoplankton production. The processes that control the magnitude of primary production in this region are not well understood, but data suggest that iron limitation is a factor. Field observations and model simulations indicate four potential sources of dissolved iron to surface waters of the Ross Sea: (1) circumpolar deep water intruding from the shelf edge; (2) sediments on shallow banks and nearshore areas; (3) melting sea ice around the perimeter of the polynya; and (4) glacial meltwater from the Ross Ice Shelf. The principal investigators hypothesize that hydrodynamic transport via mesoscale currents, fronts, and eddies facilitate the supply of dissolved iron from these four sources to the surface waters of the Ross Sea polynya. These hypotheses will be tested through a combination of in situ observations and numerical modeling, complemented by satellite remote sensing. In situ observations will be obtained during a month-long cruise in the austral summer. The field data will be incorporated into model simulations, which allow quantification of the relative contributions of the various hypothesized iron supply mechanisms, and assessment of their impact on primary production. The research will provide new insights and a mechanistic understanding of the complex oceanographic phenomena that regulate iron supply, primary production, and biogeochemical cycling. The research will thus form the basis for predictions about how this system may change in a warming climate. The research will contribute to the goals of the international research programs ICED (Integrated Climate and Ecosystem Dynamics) and GEOTRACES (Biogeochemical cycling and trace elements in the marine environment).



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Program Information

Ocean Carbon and Biogeochemistry (OCB)


Coverage: Global


The Ocean Carbon and Biogeochemistry (OCB) program focuses on the ocean's role as a component of the global Earth system, bringing together research in geochemistry, ocean physics, and ecology that inform on and advance our understanding of ocean biogeochemistry. The overall program goals are to promote, plan, and coordinate collaborative, multidisciplinary research opportunities within the U.S. research community and with international partners. Important OCB-related activities currently include: the Ocean Carbon and Climate Change (OCCC) and the North American Carbon Program (NACP); U.S. contributions to IMBER, SOLAS, CARBOOCEAN; and numerous U.S. single-investigator and medium-size research projects funded by U.S. federal agencies including NASA, NOAA, and NSF.

The scientific mission of OCB is to study the evolving role of the ocean in the global carbon cycle, in the face of environmental variability and change through studies of marine biogeochemical cycles and associated ecosystems.

The overarching OCB science themes include improved understanding and prediction of: 1) oceanic uptake and release of atmospheric CO2 and other greenhouse gases and 2) environmental sensitivities of biogeochemical cycles, marine ecosystems, and interactions between the two.

The OCB Research Priorities (updated January 2012) include: ocean acidification; terrestrial/coastal carbon fluxes and exchanges; climate sensitivities of and change in ecosystem structure and associated impacts on biogeochemical cycles; mesopelagic ecological and biogeochemical interactions; benthic-pelagic feedbacks on biogeochemical cycles; ocean carbon uptake and storage; and expanding low-oxygen conditions in the coastal and open oceans.


Integrated Marine Biogeochemistry and Ecosystem Research -US (IMBER-US)


Coverage: global


The BCO-DMO database includes data from IMBER endorsed projects lead by US funded investigators. There is no dedicated US IMBER project or data management office. Those functions are provided by US-OCB and BCO-DMO respectively.

The information in this program description pertains to the Internationally coordinated IMBER research program. The projects contributing data to the BCO-DMO database are those funded by US NSF only. The full IMBER data catalog is hosted at the Global Change Master Directory (GCMD). 

IMBER Data Portal: The IMBER project has chosen to create a metadata portal hosted by the NASA's Global Change Master Directory (GCMD). The GCMD IMBER data catalog provides an overview of all IMBER endorsed and related projects and links to datasets, and can be found at URL http://gcmd.nasa.gov/portals/imber/.

IMBER research will seek to identify the mechanisms by which marine life influences marine biogeochemical cycles, and how these, in turn, influence marine ecosystems. Central to the IMBER goal is the development of a predictive understanding of how marine biogeochemical cycles and ecosystems respond to complex forcings, such as large-scale climatic variations, changing physical dynamics, carbon cycle chemistry and nutrient fluxes, and the impacts of marine harvesting. Changes in marine biogeochemical cycles and ecosystems due to global change will also have consequences for the broader Earth System. An even greater challenge will be drawing together the natural and social science communities to study some of the key impacts and feedbacks between the marine and human systems.

To address the IMBER goal, four scientific themes, each including several issues, have been identified for the IMBER project: Theme 1 - Interactions between Biogeochemical Cycles and Marine Food Webs; Theme 2 - Sensitivity to Global Change: How will key marine biogeochemical cycles, ecosystems and their interactions, respond to global change?; Theme 3 - Feedback to the Earth System: What are the roles of the ocean biogeochemistry and ecosystems in regulating climate?; and Theme 4 - Responses of Society: What are the relationships between marine biogeochemical cycles, ecosystems, and the human system?



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Funding

Funding SourceAward
NSF Antarctic Sciences (NSF ANT)

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