http://lod.bco-dmo.org/id/dataset/1001499
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2026-06-23
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
Biogeochemical inventories in the upper water column of the Pacific sector of the coastal Antarctic as measured on the Amundsen Sea Polynya International Research Expedition (ASPIRE) during December 2010 to January 2011
2026-06-23
publication
2026-06-23
revision
Woods Hole Oceanographic Institution (WHOI BCO-DMO)
2026-06-25
publication
https://doi.org/10.26008/1912/bco-dmo.1001499.1
Patricia Lynn Yager
University of Georgia
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Yager, P. L. (2026) Biogeochemical inventories in the upper water column of the Pacific sector of the coastal Antarctic as measured on the Amundsen Sea Polynya International Research Expedition (ASPIRE) during December 2010 to January 2011. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2026-06-23 [if applicable, indicate subset used]. doi:10.26008/1912/bco-dmo.1001499.1 [access date]
ASPIRE Upper Water Column Inventories Dataset Description: Methods and Sampling: <p><strong>Water sampling</strong>:<br />
Hydrographic profiles and discrete water samples were collected from each station using a conventional shipboard conductivity temperature-depth (CTD; Sea-Bird 911+) sensor and a 24 × 10 liter (L) Niskin bottle rosette sampler (General Oceanics). Potential temperature (θ) and salinity (S) were recorded continuously as a function of depth and at the moment of Niskin bottle closure. A few samples (particulate phosphate) reported here were collected similarly using a trace-metal-clean CTD-rosette system (see Sherrell et al., 2015) that was deployed at the same location and depths just before or after the conventional CTD.</p>
<p>Water samples were collected and processed according to standard protocols (Knap et al., 1996; Dickson et al., 2007) for dissolved inorganic carbon (DIC), alkalinity (ALK), nutrients, chlorophyll a (Chl a), particulate and dissolved organic carbon (POC, DOC), particulate and total dissolved nitrogen (PN, TDN), and particulate phosphorus (PP; Planquette and Sherrell, 2012; Planquette et al. 2013). Samples from the same depths and stations were also collected for microbial biomass and activity (see below; Williams et al., 2016). This dataset focuses on samples collected from the upper 100 meters (m) of the water column. Seafloor depths in the area ranged from 300 to 1300 m (Nitsche et al., 2007), although the 13 stations included here were all deeper than 400 m.</p>
<p><strong>Inorganic nutrients, inorganic carbon, and organic matter analysis:</strong><br />
Dissolved inorganic nutrient samples were pre-filtered through 0.45-micrometer (µm) polycarbonate syringe filters, kept refrigerated, and analyzed onboard the ship within 1 day of sampling. Nitrate (NO₃-), nitrite (NO₂-), ammonium (NH₄+), phosphate (HPO₄²-), and silicic acid (Si(OH)₄) were measured using a five-channel Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer in conjunction with a Lachat Instruments XYZ AutoSampler (ASX-500 Series), two Lachat Instruments RP-100 Series peristaltic Reagent Pumps, and Omnion Software, version 3.0.220.02. The nitrate + nitrite analysis uses the basic method of Armstrong et al. (1967), with minor improvements for greater precision and easier operation. Nitrate was first reduced to nitrite using a cadmium reduction column and imidazole buffer as described by Patton (1982). Sulfanilamide and N-(1-Napthyl) ethylenediamine dihydrochloride react with nitrite to form a colored diazo compound. Nitrite analysis was performed on a separate channel, omitting the cadmium reductant. Ammonium was determined using the indophenol blue method modified from ALPKEM RFA methodology (EPA, 1984). Total dissolved inorganic nitrogen (DIN) was calculated by summing NO₃- + NO₂⁻ + NH₄+. The phosphate method was a modification of the molybdenum blue procedure of Bernhardt and Wilhelms (1967), in which phosphate was determined as reduced phosphomolybdic acid employing hydrazine as the reductant. The silicic acid method was based on Armstrong et al. (1967), as adapted by Atlas et al. (1971). Addition of an acidic molybdate reagent forms silicomolybdic acid, which was then reduced by stannous chloride. Detection limits (NO₃- + NO₂- = 0.075 micromoles per liter (µmol/L); NO₂- = 0.009 µmol/L; NH₄+ = 0.040 µmol/L; HPO₄²- = 0.022 µmol/L; and Si(OH)₄ = 1.90 µmol/L) and precision (NO₃- + NO₂- = ± 0.0076 µmol/L; NO₂- = ± 0.0009 µmol/L; NH₄+ = ± 0.0041 µmol/L; HPO₄²- = ± 0.0023 µmol/L; and Si(OH)₄ = ± 0.193 µmol/L) were determined using multiple runs of standards prepared in low nutrient seawater. Samples with negative values following calibration using standard curves were converted to zeros.</p>
<p>Samples for DIC were preserved with mercuric chloride and sealed (Dickson et al., 2007), and then stored cool and dark until analysis using the SOMMA at UGA ( Johnson et al., 1993; Cooley and Yager, 2006). Accuracy was confirmed with Certified Reference Material from University of California, San Diego (CRM; Dickson et al., 2003) and precision was determined to be better than ± 1 micromoles per kilogram (µmol/kg) using duplicate samples from surface and 200 m depths. Alkalinity measurements were made on the same samples (following DIC analysis) using a programmable open-cell potentiometric titration system (Dickson et al., 2003; Cooley and Yager, 2006). Accuracy was established by acid-calibration using multiple daily runs of CRM. Precision was determined to be ± 5 µmol/kg using replicate samples run on multiple days.</p>
<p>Samples for particulate organic carbon (POC) and nitrogen (PN) were collected by cleanly filtering 100–600 milliliters (mL) of seawater onto a 25-millimeter (mm) diameter, combusted GF/F filter (nominal pore size of 0.7 µm) which was then folded sample side in and frozen at -80 degrees Celsius (°C). Samples were processed at Rutgers University and analyzed using a Carlo-Erba CHN analyzer (Hedges and Stern, 1984). Precision, based on replicate filtered volumes from the same Niskin bottle, was ± 5% for most samples, but was occasionally higher. Samples for particulate phosphate (PP) were collected separately from the same depths and locations as part of a trace metal suite and analyzed separately using a Thermo-Finnigan Element I HR-ICP-MS (Sherrell et al., 2015; Planquette and Sherrell, 2012; Planquette et al., 2013). Precision was ± 5%.</p>
<p>Samples for DOC and TDN were collected cleanly from the filtrate of the POC/PN samples and stored frozen until processed at the Georgia Institute of Technology by Shimadzu TOC-5000 analyzer with an associated TNM-1 Total Nitrogen Measuring Unit. Precision was ± 4%. Residual dissolved organic nitrogen (DON) was calculated by subtracting DIN from TDN. This approach involves taking the difference between two relatively large numbers, thus precision of relatively small DON concentrations is strongly affected by the precision of the DIN and TDN analyses.</p>
<p><strong>Organismal abundance and biomass analysis:</strong><br />
Water column Chl <em>a</em> concentration (used as a proxy for algal biomass) was measured onboard ship using acetone extraction and a spectrofluorometer (Alderkamp et al., 2015). Shipboard values were calibrated against a second set of samples collected similarly, flash-frozen in liquid N₂, stored at -80°C, and analyzed at Mote Marine Lab using HPLC (Wright et al., 1991; see Alderkamp et al., 2015). CHEMTAX (Mackey et al., 1996; Wright et al., 1996; 2010) was applied to determine the relative abundance of phytoplankton classes based on pigment analysis (see Alderkamp et al., 2015).</p>
<p>Bacterial abundance samples were collected in triplicate, preserved using 1% paraformaldehyde, and deep frozen (-80 °C) until they were counted at The University of Georgia with flow cytometry and SYBR Green I nucleic acid staining (Marie et al., 1997). Abundance was calibrated with polystyrene beads, and values were crosschecked using DAPI and epifluorescence microscopy (Porter and Feig, 1980). Abundance was converted to bacterial carbon (BAC) using a conversion factor (25 femtograms C per cell (fg C cell-1); Simon and Azam, 1989). Precision was ± 3%.</p>
<p>Microzooplankton abundance and biovolume were determined at select depths and stations using microscopy (Goswami, 2004). Samples were gently siphoned through silicon tubes into 300 mL amber colored glass bottles, fixed in acidic Lugol’s solution (2% final concentration), and kept cool and dark until analysis. Biovolume calculations followed the HELCOM (2014) manual on appropriate geometrical shapes when making length-width measurements for each individual species. Biovolumes were corrected for shrinkage due to preservation (vol × 1.33; Stoecker et al., 1994). Heterotrophic/mixotrophic microplankton cell volumes were converted to cell carbon (Menden-Deuer and Lessard, 2000) for loricate and aloricate ciliates (CIL), and dinoflagellates (DINO).</p>
<p>Heterotrophic nanoflagellates (HNAN) were counted by flow cytometry (Christaki et al., 2011). Each sample was stained with SYBR Green, at final concentration of 1:10000 and a minimum staining time of 10 minutes in the dark. The flow rate was ∼250 microliters per minute (µL/min). Both green and red fluorescence were used to discriminate between autotrophs and heterotrophs. Data acquisition was 5–10 minutes depending on concentration of the sample (or depth). Samples with &gt; 1200 events per second were diluted to allow a correct measurement. The detected abundance was checked against counts of DAPI filters. HNAN biomass was converted from abundance data assuming 3.5 cubic micrometer (µm³) per cell biovolume (Vaqué et al., 2002) and 220 femtograms C per cubic micrometer (fg C/µm³) (Børsheim and Bratbak, 1987).</p>
<p>Mesozooplankton biovolume and abundance were determined as described by Wilson et al. (2015) and converted to biomass (micromoles C per liter (µmol C/L)) for both daytime and nighttime tows using conversion factors from the literature (Gallienne et al., 2001; Forest et al., 2012; Trudnowska et al., 2014). The maximum value of day or night tows is reported here.</p>
<p><strong>Biological rate measurements:</strong><br />
Phytoplankton net primary production (NPP) rates were determined for 6 light depths in the upper 100 m using standard ¹⁴C-bicarbonate incubations (Steeman-Nielsen, 1952; Knap et al., 1996) in on-deck incubators with light-filtering screens to match in situ light levels. Bacterial production (BP) rates were determined using ³H-leucine incorporation as described by Williams et al. (2016). Microbial community respiration (MCR) rates were determined for near-surface and subsurface depths by changes in CO₂ concentrations over 48 hours in dark incubations, as described in Williams et al. (2016).</p>
Funding provided by NSF Antarctic Sciences (NSF ANT) Award Number: ANT-0839069 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0839069
Funding provided by NSF Antarctic Sciences (NSF ANT) Award Number: ANT-0944727 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0944727
Funding provided by NSF Antarctic Sciences (NSF ANT) Award Number: ANT-0839012 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0839012
Funding provided by NSF Antarctic Sciences (NSF ANT) Award Number: ANT-0838995 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0838995
Funding provided by NSF Antarctic Sciences (NSF ANT) Award Number: ANT-0838975 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=0838975
Funding provided by Swedish Research Council () Award Number: 2008-6430
Funding provided by Swedish Research Council () Award Number: 2008-6429
completed
Patricia Lynn Yager
University of Georgia
706-542-6824
Department of Marine Sciences 166 Marine Sciences Building
Athens
GA
30602-3636
USA
pyager@uga.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Station
Event
Cast
Date
Year_Day
Lat
Lon
ASP_num
Depth
Poten_Temp
Salinity
DIC
DIN
DIP
POC
PON
Part_P
SiO4
DOC
DON
Chl_a
Bacterial_biomass
Nanoflagellate_biomass
Ciliate_biomass
Dinoflagellate_biomass
Max_Macrozooplankton_biomass
Primary_Production
Community_Respiration
Bacterial_Production
Carlo-Erba CHN analyzer
Sea-Bird 911+
flow cytometry and SYBR Green I nucleic acid staining
epifluorescence microscopy
On-deck incubators
Lachat Instruments XYZ AutoSampler (ASX-500 Series)
Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer
Niskin bottle rosette sampler (General Oceanics)
Shimadzu TOC-5000 analyzer
TNM-1 Total Nitrogen Measuring Unit
SOMMA
Spectrofluorometer
Thermo-Finnigan Element I HR-ICP-MS
theme
None, User defined
station
event
cast
date
year day (Day of Year, or day of year and decimal time)
latitude
longitude
bottle
depth
potential temperature
salinity
dissolved inorganic Carbon
Dissolved Inorganic Nitrogen
Dissolved Inorganic Phosphate
particulate organic Carbon (POC)
particulate organic Nitrogen
phosphate
Silicate (reactive silica)
dissolved organic Carbon
Dissolved Organic Nitrogen
chlorophyll a
biomass_C
primary production
respiration rate
Bacterial production in the water column
featureType
BCO-DMO Standard Parameters
CHN Elemental Analyzer
CTD Sea-Bird SBE 911plus
Flow Cytometer
Fluorescence Microscope
In-situ incubator
Laboratory Autosampler
Lachat QuikChem 8000 flow injection analyzer and Ion Chromatography (IC) system
Niskin bottle
Shimadzu TOC 5000A total organic carbon analyzer
Shimadzu Total Nitrogen Monoxide 1
Single Operator Multi-parameter Metabolic Analyzer
Spectrometer
Thermo Finnigan (Thermo Fisher Scientific) Element I inductively coupled plasma mass spectrometer
instrument
BCO-DMO Standard Instruments
NBP1005
service
Deployment Activity
Amundsen Sea, South Pacific Sector of Antarctica, Southern Ocean 73 S 115 W
place
Locations
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Amundsen Sea Polynya International Research Expedition
http://AntarcticASPIRE.org/
Amundsen Sea Polynya International Research Expedition
<p>The Amundsen Sea Polynya is areally the most productive Antarctic polynya, exhibits higher chlorophyll levels during peak bloom and greater interannual variability than the better-studied Ross Sea Polynya ecosystem. Polynyas may be the key to understanding the future of polar regions as their extent is expected to increase with anthropogenic warming. The project will examine 1) sources of iron to the Amundsen Sea Polynya as a function of climate forcing, 2) phytoplankton community structure in relation to iron supply and mixed-layer depths, 3) the efficiency of the biological pump of carbon to depth and 4) the net flux of carbon as a function of climate and micronutrient forcing. The research also will compare results for the Amundsen Sea to existing data synthesis and modeling efforts for the Palmer LTER and Ross Sea. The project will 1) build close scientific collaborations between US and Swedish researchers; 2) investigate climate change implications with broad societal relevance; 3) train new researchers; 4) encourage participation in research science by underrepresented groups, and 5) involve broad dissemination of results via scientific literature and public outreach, including close interactions with NSF-supported PolarTrec and COSEE K-12 teachers.</p>
<p>This project brings together experienced US and Swedish investigators (trace metal and carbon chemists, phytoplankton physiologists, microbial and zooplankton ecologists, and physical oceanographers) to investigate climate controls on carbon dioxide uptake by one of the most productive ecosystems in the Antarctic.</p>
<p>The Amundsen Sea Polynya is the most productive Antarctic polynya per square meter, and exhibits higher chlorophyll levels during peak bloom and greater interannual variability than the better-studied Ross Sea polynya ecosystem to the west.</p>
<p>Polynyas, or recurring areas of seasonally open water surrounded by ice, are foci for energy and material transfer between the atmosphere, polar surface ocean and deep sea. Most help take up large amounts of carbon dioxide from the atmosphere.</p>
<p>These polar ecosystems are characterized by high biological productivity and intense biogeochemical cycling - a bit like an oasis. Polynyas may be the key to understanding the future of polar regions since their extent is expected to increase with anthropogenic warming. On the other hand, if seasonal sea ice disappears completely, the unique nature of polynyas may also be lost.</p>
<p>Regional reductions or growth in sea-ice over the past decade have been extensive and are coupled to climate-sensitive global cycles such as ENSO and the Southern Annular Mode. Without many historical measurements, this regional and interannual variability is our best present-day indication for what controls or “forces” these critical polar ecosystems and their sensitivity to future change.</p>
<p>Variability in the productivity of Antarctic polynyas is high for reasons the science community do not currently understand. The supply of trace metals such as iron is thought to determine phytoplankton community structure and production in the Southern Ocean, particularly in conjunction with mixed-layer depth controls on light limitation. A key question is whether interannual variability is driven by these two climate-sensitive factors, and whether we can expect climate-sensitive shifts in ecosystem function and carbon flux in the future. Understanding critical feedbacks between climate and the marine biosphere becomes increasingly urgent as we project rates of change into the future.</p>
<p><a href="http://home.elementascience.org/special-features/aspire-the-amundsen-sea-polynya-international-research-expedition/" target="_blank">Special ASPIRE journal feature in ELEMENTA</a></p>
ASPIRE
largerWorkCitation
project
eng; USA
oceans
Amundsen Sea, South Pacific Sector of Antarctica, Southern Ocean 73 S 115 W
-118.32
-112
-73.96
-71.86
2010-12-15
2011-01-08
Amundsen Sea, South Pacific Sector of Antarctica, Southern Ocean 73 S 115 W
0
BCO-DMO catalogue of parameters from Biogeochemical inventories in the upper water column of the Pacific sector of the coastal Antarctic as measured on the Amundsen Sea Polynya International Research Expedition (ASPIRE) during December 2010 to January 2011
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/1001555.rdf
Name: Station
Units: unitless
Description: <p>Station number</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001556.rdf
Name: Event
Units: unitless
Description: <p>Event number</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001557.rdf
Name: Cast
Units: unitless
Description: <p>Cast number</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001558.rdf
Name: Date
Units: unitless
Description: <p>Date sampled</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001559.rdf
Name: Year_Day
Units: unitless
Description: <p>Year Day sampled</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001560.rdf
Name: Lat
Units: decimal degrees
Description: <p>Latitude</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001562.rdf
Name: Lon
Units: decimal degrees
Description: <p>Longitude</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001564.rdf
Name: ASP_num
Units: unitless
Description: <p>Unique Niskin bottle identifier</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001565.rdf
Name: Depth
Units: meters (m)
Description: <p>Water depth</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001567.rdf
Name: Poten_Temp
Units: degrees C
Description: <p>Potential temperature</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001568.rdf
Name: Salinity
Units: unitless
Description: <p>Practical salinity</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001569.rdf
Name: DIC
Units: micromoles C per liter (µmol C per L)
Description: <p>Dissolved inorganic carbon</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001570.rdf
Name: DIN
Units: micromoles N per liter (µmol N per L)
Description: <p>Dissolved inorganic nitrogen</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001571.rdf
Name: DIP
Units: micromoles P per liter (µmol P per L)
Description: <p>Dissolved inorganic phosphorus</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001572.rdf
Name: POC
Units: micromoles C per liter (µmol C per L)
Description: <p>Particulate organic carbon</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001573.rdf
Name: PON
Units: micromoles N per liter (µmol N per L)
Description: <p>Particulate organic nitrogen</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001574.rdf
Name: Part_P
Units: micromoles P per liter (µmol P per L)
Description: <p>Particulate phosphate</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001575.rdf
Name: SiO4
Units: micromoles Si per liter (µmol Si per L)
Description: <p>Silicate</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001576.rdf
Name: DOC
Units: micromoles C per liter (µmol C per L)
Description: <p>Dissolved organic carbon</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001577.rdf
Name: DON
Units: micromoles N per liter (µmol N per L)
Description: <p>Dissolved organic nitrogen</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001578.rdf
Name: Chl_a
Units: micrograms chl a per liter (µg chl a per L)
Description: <p>Chlorophyll a</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001579.rdf
Name: Bacterial_biomass
Units: micromoles C per liter (µmol C per L)
Description: <p>Bacterial biomass</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001580.rdf
Name: Nanoflagellate_biomass
Units: micromoles C per liter (µmol C per L)
Description: <p>Nanoflagellate biomass</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001581.rdf
Name: Ciliate_biomass
Units: micromoles C per liter (µmol C per L)
Description: <p>Ciliate biomass</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001582.rdf
Name: Dinoflagellate_biomass
Units: micromoles C per liter (µmol C per L)
Description: <p>Dinoflagellate biomass</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001583.rdf
Name: Max_Macrozooplankton_biomass
Units: micromoles C per liter (µmol C per L)
Description: <p>Macrozooplankton biomass</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001584.rdf
Name: Primary_Production
Units: micromoles C per liter per day (µmol C per L per day)
Description: <p>Primary Production</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001585.rdf
Name: Community_Respiration
Units: micromoles C per liter per day (µmol C per L per day)
Description: <p>Community Respiration</p>
http://lod.bco-dmo.org/id/dataset-parameter/1001586.rdf
Name: Bacterial_Production
Units: micromoles C per liter per day (µmol C per L per day)
Description: <p>Bacterial Production</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
https://doi.org/10.26008/1912/bco-dmo.1001499.1
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dataset
<p><strong>Water sampling</strong>:<br />
Hydrographic profiles and discrete water samples were collected from each station using a conventional shipboard conductivity temperature-depth (CTD; Sea-Bird 911+) sensor and a 24 × 10 liter (L) Niskin bottle rosette sampler (General Oceanics). Potential temperature (θ) and salinity (S) were recorded continuously as a function of depth and at the moment of Niskin bottle closure. A few samples (particulate phosphate) reported here were collected similarly using a trace-metal-clean CTD-rosette system (see Sherrell et al., 2015) that was deployed at the same location and depths just before or after the conventional CTD.</p>
<p>Water samples were collected and processed according to standard protocols (Knap et al., 1996; Dickson et al., 2007) for dissolved inorganic carbon (DIC), alkalinity (ALK), nutrients, chlorophyll a (Chl a), particulate and dissolved organic carbon (POC, DOC), particulate and total dissolved nitrogen (PN, TDN), and particulate phosphorus (PP; Planquette and Sherrell, 2012; Planquette et al. 2013). Samples from the same depths and stations were also collected for microbial biomass and activity (see below; Williams et al., 2016). This dataset focuses on samples collected from the upper 100 meters (m) of the water column. Seafloor depths in the area ranged from 300 to 1300 m (Nitsche et al., 2007), although the 13 stations included here were all deeper than 400 m.</p>
<p><strong>Inorganic nutrients, inorganic carbon, and organic matter analysis:</strong><br />
Dissolved inorganic nutrient samples were pre-filtered through 0.45-micrometer (µm) polycarbonate syringe filters, kept refrigerated, and analyzed onboard the ship within 1 day of sampling. Nitrate (NO₃-), nitrite (NO₂-), ammonium (NH₄+), phosphate (HPO₄²-), and silicic acid (Si(OH)₄) were measured using a five-channel Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer in conjunction with a Lachat Instruments XYZ AutoSampler (ASX-500 Series), two Lachat Instruments RP-100 Series peristaltic Reagent Pumps, and Omnion Software, version 3.0.220.02. The nitrate + nitrite analysis uses the basic method of Armstrong et al. (1967), with minor improvements for greater precision and easier operation. Nitrate was first reduced to nitrite using a cadmium reduction column and imidazole buffer as described by Patton (1982). Sulfanilamide and N-(1-Napthyl) ethylenediamine dihydrochloride react with nitrite to form a colored diazo compound. Nitrite analysis was performed on a separate channel, omitting the cadmium reductant. Ammonium was determined using the indophenol blue method modified from ALPKEM RFA methodology (EPA, 1984). Total dissolved inorganic nitrogen (DIN) was calculated by summing NO₃- + NO₂⁻ + NH₄+. The phosphate method was a modification of the molybdenum blue procedure of Bernhardt and Wilhelms (1967), in which phosphate was determined as reduced phosphomolybdic acid employing hydrazine as the reductant. The silicic acid method was based on Armstrong et al. (1967), as adapted by Atlas et al. (1971). Addition of an acidic molybdate reagent forms silicomolybdic acid, which was then reduced by stannous chloride. Detection limits (NO₃- + NO₂- = 0.075 micromoles per liter (µmol/L); NO₂- = 0.009 µmol/L; NH₄+ = 0.040 µmol/L; HPO₄²- = 0.022 µmol/L; and Si(OH)₄ = 1.90 µmol/L) and precision (NO₃- + NO₂- = ± 0.0076 µmol/L; NO₂- = ± 0.0009 µmol/L; NH₄+ = ± 0.0041 µmol/L; HPO₄²- = ± 0.0023 µmol/L; and Si(OH)₄ = ± 0.193 µmol/L) were determined using multiple runs of standards prepared in low nutrient seawater. Samples with negative values following calibration using standard curves were converted to zeros.</p>
<p>Samples for DIC were preserved with mercuric chloride and sealed (Dickson et al., 2007), and then stored cool and dark until analysis using the SOMMA at UGA ( Johnson et al., 1993; Cooley and Yager, 2006). Accuracy was confirmed with Certified Reference Material from University of California, San Diego (CRM; Dickson et al., 2003) and precision was determined to be better than ± 1 micromoles per kilogram (µmol/kg) using duplicate samples from surface and 200 m depths. Alkalinity measurements were made on the same samples (following DIC analysis) using a programmable open-cell potentiometric titration system (Dickson et al., 2003; Cooley and Yager, 2006). Accuracy was established by acid-calibration using multiple daily runs of CRM. Precision was determined to be ± 5 µmol/kg using replicate samples run on multiple days.</p>
<p>Samples for particulate organic carbon (POC) and nitrogen (PN) were collected by cleanly filtering 100–600 milliliters (mL) of seawater onto a 25-millimeter (mm) diameter, combusted GF/F filter (nominal pore size of 0.7 µm) which was then folded sample side in and frozen at -80 degrees Celsius (°C). Samples were processed at Rutgers University and analyzed using a Carlo-Erba CHN analyzer (Hedges and Stern, 1984). Precision, based on replicate filtered volumes from the same Niskin bottle, was ± 5% for most samples, but was occasionally higher. Samples for particulate phosphate (PP) were collected separately from the same depths and locations as part of a trace metal suite and analyzed separately using a Thermo-Finnigan Element I HR-ICP-MS (Sherrell et al., 2015; Planquette and Sherrell, 2012; Planquette et al., 2013). Precision was ± 5%.</p>
<p>Samples for DOC and TDN were collected cleanly from the filtrate of the POC/PN samples and stored frozen until processed at the Georgia Institute of Technology by Shimadzu TOC-5000 analyzer with an associated TNM-1 Total Nitrogen Measuring Unit. Precision was ± 4%. Residual dissolved organic nitrogen (DON) was calculated by subtracting DIN from TDN. This approach involves taking the difference between two relatively large numbers, thus precision of relatively small DON concentrations is strongly affected by the precision of the DIN and TDN analyses.</p>
<p><strong>Organismal abundance and biomass analysis:</strong><br />
Water column Chl <em>a</em> concentration (used as a proxy for algal biomass) was measured onboard ship using acetone extraction and a spectrofluorometer (Alderkamp et al., 2015). Shipboard values were calibrated against a second set of samples collected similarly, flash-frozen in liquid N₂, stored at -80°C, and analyzed at Mote Marine Lab using HPLC (Wright et al., 1991; see Alderkamp et al., 2015). CHEMTAX (Mackey et al., 1996; Wright et al., 1996; 2010) was applied to determine the relative abundance of phytoplankton classes based on pigment analysis (see Alderkamp et al., 2015).</p>
<p>Bacterial abundance samples were collected in triplicate, preserved using 1% paraformaldehyde, and deep frozen (-80 °C) until they were counted at The University of Georgia with flow cytometry and SYBR Green I nucleic acid staining (Marie et al., 1997). Abundance was calibrated with polystyrene beads, and values were crosschecked using DAPI and epifluorescence microscopy (Porter and Feig, 1980). Abundance was converted to bacterial carbon (BAC) using a conversion factor (25 femtograms C per cell (fg C cell-1); Simon and Azam, 1989). Precision was ± 3%.</p>
<p>Microzooplankton abundance and biovolume were determined at select depths and stations using microscopy (Goswami, 2004). Samples were gently siphoned through silicon tubes into 300 mL amber colored glass bottles, fixed in acidic Lugol’s solution (2% final concentration), and kept cool and dark until analysis. Biovolume calculations followed the HELCOM (2014) manual on appropriate geometrical shapes when making length-width measurements for each individual species. Biovolumes were corrected for shrinkage due to preservation (vol × 1.33; Stoecker et al., 1994). Heterotrophic/mixotrophic microplankton cell volumes were converted to cell carbon (Menden-Deuer and Lessard, 2000) for loricate and aloricate ciliates (CIL), and dinoflagellates (DINO).</p>
<p>Heterotrophic nanoflagellates (HNAN) were counted by flow cytometry (Christaki et al., 2011). Each sample was stained with SYBR Green, at final concentration of 1:10000 and a minimum staining time of 10 minutes in the dark. The flow rate was ∼250 microliters per minute (µL/min). Both green and red fluorescence were used to discriminate between autotrophs and heterotrophs. Data acquisition was 5–10 minutes depending on concentration of the sample (or depth). Samples with &gt; 1200 events per second were diluted to allow a correct measurement. The detected abundance was checked against counts of DAPI filters. HNAN biomass was converted from abundance data assuming 3.5 cubic micrometer (µm³) per cell biovolume (Vaqué et al., 2002) and 220 femtograms C per cubic micrometer (fg C/µm³) (Børsheim and Bratbak, 1987).</p>
<p>Mesozooplankton biovolume and abundance were determined as described by Wilson et al. (2015) and converted to biomass (micromoles C per liter (µmol C/L)) for both daytime and nighttime tows using conversion factors from the literature (Gallienne et al., 2001; Forest et al., 2012; Trudnowska et al., 2014). The maximum value of day or night tows is reported here.</p>
<p><strong>Biological rate measurements:</strong><br />
Phytoplankton net primary production (NPP) rates were determined for 6 light depths in the upper 100 m using standard ¹⁴C-bicarbonate incubations (Steeman-Nielsen, 1952; Knap et al., 1996) in on-deck incubators with light-filtering screens to match in situ light levels. Bacterial production (BP) rates were determined using ³H-leucine incorporation as described by Williams et al. (2016). Microbial community respiration (MCR) rates were determined for near-surface and subsurface depths by changes in CO₂ concentrations over 48 hours in dark incubations, as described in Williams et al. (2016).</p>
Specified by the Principal Investigator(s)
- Loaded original file "Yager_et_al_2016_ASPIRE_Carbon_Budget_Data.csv" into the BCO-DMO system.
- Treated "NaN" as a missing data value (missing data are empty/blank in the final CSV file).
- Renamed columns to comply with BCO-DMO naming conventions.
- Converted "Date" column from MM/DD/YY format to ISO 8601 date format (YYYY-MM-DD).
- Saved the final file as "1001499_v1_aspire_upper_water_column_inventories.csv".
Specified by BCO-DMO Data Managers
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
Carlo-Erba CHN analyzer
Carlo-Erba CHN analyzer
PI Supplied Instrument Name: Carlo-Erba CHN analyzer Instrument Name: CHN Elemental Analyzer Instrument Short Name:CHN_EA Instrument Description: A CHN Elemental Analyzer is used for the determination of carbon, hydrogen, and nitrogen content in organic and other types of materials, including solids, liquids, volatile, and viscous samples.
Sea-Bird 911+
Sea-Bird 911+
PI Supplied Instrument Name: Sea-Bird 911+ Instrument Name: CTD Sea-Bird SBE 911plus Instrument Short Name:CTD SBE 911plus 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 Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0058/
flow cytometry and SYBR Green I nucleic acid staining
flow cytometry and SYBR Green I nucleic acid staining
PI Supplied Instrument Name: flow cytometry and SYBR Green I nucleic acid staining Instrument Name: Flow Cytometer Instrument Short Name:Flow Cytometer Instrument Description: Flow cytometers (FC or FCM) are automated instruments that quantitate properties of single cells, one cell at a time. They can measure cell size, cell granularity, the amounts of cell components such as total DNA, newly synthesized DNA, gene expression as the amount messenger RNA for a particular gene, amounts of specific surface receptors, amounts of intracellular proteins, or transient signalling events in living cells.
(from: http://www.bio.umass.edu/micro/immunology/facs542/facswhat.htm) Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB37/
epifluorescence microscopy
epifluorescence microscopy
PI Supplied Instrument Name: epifluorescence microscopy Instrument Name: Fluorescence Microscope Instrument Short Name: Instrument Description: Instruments that generate enlarged images of samples using the phenomena of fluorescence and phosphorescence instead of, or in addition to, reflection and absorption of visible light. Includes conventional and inverted instruments. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/LAB06/
On-deck incubators
On-deck incubators
PI Supplied Instrument Name: On-deck incubators Instrument Name: In-situ incubator Instrument Short Name:in-situ incubator Instrument Description: A device on a ship or in the laboratory that holds water samples under controlled conditions of temperature and possibly illumination. Community Standard Description: http://vocab.nerc.ac.uk/collection/L05/current/82/
Lachat Instruments XYZ AutoSampler (ASX-500 Series)
Lachat Instruments XYZ AutoSampler (ASX-500 Series)
PI Supplied Instrument Name: Lachat Instruments XYZ AutoSampler (ASX-500 Series) Instrument Name: Laboratory Autosampler Instrument Short Name: Instrument Description: Laboratory apparatus that automatically introduces one or more samples with a predetermined volume or mass into an analytical instrument.
Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer
Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer
PI Supplied Instrument Name: Lachat Instruments QuikChem FIA+ 8000s series autoanalyzer Instrument Name: Lachat QuikChem 8000 flow injection analyzer and Ion Chromatography (IC) system Instrument Short Name: Instrument Description: The Lachat QuikChem 8000 can operate flow injection analysis and ion chromatography simultaneously and independently on the same instrument platform. Instrument includes sampler, dilutor, sampling pump, electronics unit, and data station. Analysis takes 20-60 seconds, with a sample throughput of 60-120 samples per hour. Measurements are in the range of parts per trillion to parts per hundred.
Niskin bottle rosette sampler (General Oceanics)
Niskin bottle rosette sampler (General Oceanics)
PI Supplied Instrument Name: Niskin bottle rosette sampler (General Oceanics) Instrument Name: Niskin bottle Instrument Short Name:Niskin bottle 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. Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/
Shimadzu TOC-5000 analyzer
Shimadzu TOC-5000 analyzer
PI Supplied Instrument Name: Shimadzu TOC-5000 analyzer Instrument Name: Shimadzu TOC 5000A total organic carbon analyzer Instrument Short Name:Shimadzu TOC-5000(A) Instrument Description: The Shimadzu TOC-5000(A) Series instruments are capable of performing analysis on any high sensitivity applications such as pharmaceutical grade, semiconductor grade, steam power, and ultrapure waters, as well as less sensitive application such as drinking water and particulate analysis such as wastewater and industrial effluents, sea water, brines, ground water, and surface water.
Shimadzu TOC-5000(A) Series instruments meet USP 23 (Fifth Supplement 643) for Pure Water (PW) and Water For Injection (WFI), Standard Methods 5310B, EPA 415.1, EPA 9060A, ASTM D2579, EPA Drinking Water ICR (D/DBP), and DIN Specifications
TNM-1 Total Nitrogen Measuring Unit
TNM-1 Total Nitrogen Measuring Unit
PI Supplied Instrument Name: TNM-1 Total Nitrogen Measuring Unit Instrument Name: Shimadzu Total Nitrogen Monoxide 1 Instrument Short Name:Shimadzu TNM-1 Instrument Description: The TNM-1 is a chemiluminescence analyzer for measurement of total nitrogen. Measurements are in range 0 to 4000 mg/L, with accuracy of CV 3 percent (max) and a measurement time of 4 minutes
SOMMA
SOMMA
PI Supplied Instrument Name: SOMMA Instrument Name: Single Operator Multi-parameter Metabolic Analyzer Instrument Short Name:SOMMA Instrument Description: Single Operator Multi-parameter Metabolic Analyzer (SOMMA) which was manufactured at the University of Rhode Island and standardized at the Brookhaven National Laboratory.
Spectrofluorometer
Spectrofluorometer
PI Supplied Instrument Name: Spectrofluorometer Instrument Name: Spectrometer Instrument Short Name:Spectrometer Instrument Description: A spectrometer is an optical instrument used to measure properties of light over a specific portion of the electromagnetic spectrum. Community Standard Description: http://vocab.nerc.ac.uk/collection/L22/current/TOOL0460/
Thermo-Finnigan Element I HR-ICP-MS
Thermo-Finnigan Element I HR-ICP-MS
PI Supplied Instrument Name: Thermo-Finnigan Element I HR-ICP-MS Instrument Name: Thermo Finnigan (Thermo Fisher Scientific) Element I inductively coupled plasma mass spectrometer Instrument Short Name:Element I ICP-MS Instrument Description: The Thermo Finnigan Element I is a double focusing, sector field inductively coupled plasma mass spectrometer. It uses a demountable Meinhard nebulizer for sample introduction and a magnetic sector as a mass filter. It has a scanning rate at full mass range of under 60 ms. Short term precision is 2 %. Its sensitivity is 20 Mcps/ppm at R=300 and 1 Mcps/ppm at R=3000, with a detection limit under 0.1 ng/L for In at R=300.
Cruise: NBP1005
NBP1005
Community Standard Description
International Council for the Exploration of the Sea
RVIB Nathaniel B. Palmer
vessel
NBP1005
Patricia Lynn Yager
University of Georgia
Community Standard Description
International Council for the Exploration of the Sea
RVIB Nathaniel B. Palmer
vessel