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Dataset Title:  [Primary Production] - Primary productivity measurements from the Hawaii Ocean
Time-Series (HOT) project from October 1988 to December 2019 at station
ALOHA. ([Current] Hawaii Ocean Time-series (HOT): 2018-2023; [Previous] Hawaii
Ocean Time-series (HOT): Sustaining ocean ecosystem and climate observations in
the North Pacific Subtropical Gyre)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_737163)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Subset | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
   or a List of Values ?
   Maximum ?
 
 Cruise (unitless) ?          1    287
 longitude (degrees_east) ?      
   - +  ?
  < slider >
 latitude (degrees_north) ?      
   - +  ?
  < slider >
 PrimProd_filename (unitless) ?          "hot1-12.pp"    "hot89-100.pp"
 Incubation_type (unitless) ?          "I"    "R"
 Date (unitless) ?          203    991215
 Start_time (unitless) ?          400    740
 start_date_time (unitless) ?          "1989-09-22T06:15:00"    "NaN"
 End_time (unitless) ?          1500    3130
 time (End Date Time, UTC) ?          1989-07-29T19:00:00Z    
  < slider >
 time2 (Time, hours) ?          8.5    25.0
 depth (m) ?          0.0    178.0
  < slider >
 Chl_a_mean (miligrams per cubic meter (mg/m3)) ?          0.004    0.5
 Chl_a_sd (miligrams per cubic meter (mg/m3)) ?          0.0    0.139
 Pheo_mean (miligrams per cubic meter (mg/m3)) ?          0.0    0.887
 Pheo_sd (miligrams per cubic meter (mg/m3)) ?          0.0    0.336
 Light_rep1 (miligrams Carbon per cubic meter (mg C/m3)) ?          0.01    29.01
 Light_rep2 (miligrams Carbon per cubic meter (mg C/m3)) ?          0.02    25.02
 Light_rep3 (miligrams Carbon per cubic meter (mg C/m3)) ?          0.0    27.64
 Dark_rep1 (miligrams Carbon per cubic meter (mg C/m3)) ?          0.0    0.88
 Dark_rep2 (miligrams Carbon per cubic meter (mg C/m3)) ?          0.01    0.62
 Dark_rep3 (miligrams Carbon per cubic meter (mg C/m3)) ?          0.0    0.46
 Salt (unitless) ?          34.3871    35.5255
 Prochl (count per mililiter) ?          44    447037
 Hetero (count per mililiter) ?          20127    1262038
 Synecho (count per mililiter) ?          0    21852
 Euk (count per mililiter) ?          0    4238
 Flag (unitless) ?          "2222222222"    "5555555555"
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Cruise {
    Int16 _FillValue 32767;
    Int16 actual_range 1, 287;
    String bcodmo_name "cruise_id";
    String description "Cruise Number";
    String long_name "Cruise";
    String units "unitless";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -158.0, -158.0;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude with East negative";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 22.75, 22.75;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude with South negative";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  PrimProd_filename {
    String bcodmo_name "file_name";
    String description "Original filename of the primary production data from HOT";
    String long_name "Prim Prod Filename";
    String units "unitless";
  }
  Incubation_type {
    String bcodmo_name "treatment";
    String description 
"O - GO-FLO sampled on-deck Incubation; 
I - GO-FLO sampled in-situ Incubation;
R - Rosette sampled in-situ Incubation;
N - External closing niskin sampled in-situ Incubation.";
    String long_name "Incubation Type";
    String units "unitless";
  }
  Date {
    Int32 _FillValue 2147483647;
    Int32 actual_range 203, 991215;
    String bcodmo_name "date";
    String description "Date in YYMMDD format";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  Start_time {
    Int16 _FillValue 32767;
    Int16 actual_range 400, 740;
    String bcodmo_name "time_start";
    String description "Start Time in HHMM format";
    String long_name "Start Time";
    String units "unitless";
  }
  start_date_time {
    String bcodmo_name "ISO_DateTime_UTC";
    String description "start date and time in ISO 8601 format";
    String long_name "Start Date Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String units "unitless";
  }
  End_time {
    Int16 _FillValue 32767;
    Int16 actual_range 1500, 3130;
    String bcodmo_name "time_end";
    String description "End Time in HHMM format";
    String long_name "End Time";
    String units "unitless";
  }
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 6.17742e+8, NaN;
    String axis "T";
    String bcodmo_name "ISO_DateTime_UTC";
    String description "end date and time in ISO 8601 format";
    String ioos_category "Time";
    String long_name "End Date Time";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/DTUT8601/";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  time2 {
    Float32 _FillValue NaN;
    Float32 actual_range 8.5, 25.0;
    String bcodmo_name "duration";
    String description "Incubation Time";
    String long_name "Time";
    String units "hours";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 178.0;
    String axis "Z";
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "Depth";
    String ioos_category "Location";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Chl_a_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.004, 0.5;
    String bcodmo_name "chlorophyll a";
    Float64 colorBarMaximum 30.0;
    Float64 colorBarMinimum 0.03;
    String colorBarScale "Log";
    String description "Chlorophyll a. Mean";
    String long_name "Concentration Of Chlorophyll In Sea Water";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
    String units "miligrams per cubic meter (mg/m3)";
  }
  Chl_a_sd {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.139;
    String bcodmo_name "chlorophyll a";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Chlroropyll a. Standard Deviation";
    String long_name "Chl A Sd";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/CPHLHPP1/";
    String units "miligrams per cubic meter (mg/m3)";
  }
  Pheo_mean {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.887;
    String bcodmo_name "phaeopigment";
    String description "Pheopigments Mean";
    String long_name "Pheo Mean";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHAEFMP1/";
    String units "miligrams per cubic meter (mg/m3)";
  }
  Pheo_sd {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.336;
    String bcodmo_name "phaeopigment";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "Pheopigments Standard Deviation";
    String long_name "Pheo Sd";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PHAEFMP1/";
    String units "miligrams per cubic meter (mg/m3)";
  }
  Light_rep1 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 29.01;
    String bcodmo_name "replicate";
    String description "Light - replicate #1";
    String long_name "Light Rep1";
    String units "miligrams Carbon per cubic meter (mg C/m3)";
  }
  Light_rep2 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.02, 25.02;
    String bcodmo_name "replicate";
    String description "Light - replicate #2";
    String long_name "Light Rep2";
    String units "miligrams Carbon per cubic meter (mg C/m3)";
  }
  Light_rep3 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 27.64;
    String bcodmo_name "replicate";
    String description "Light - replicate #3";
    String long_name "Light Rep3";
    String units "miligrams Carbon per cubic meter (mg C/m3)";
  }
  Dark_rep1 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.88;
    String bcodmo_name "replicate";
    String description "Dark - replicate #1";
    String long_name "Dark Rep1";
    String units "miligrams Carbon per cubic meter (mg C/m3)";
  }
  Dark_rep2 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 0.62;
    String bcodmo_name "replicate";
    String description "Dark - replicate #2";
    String long_name "Dark Rep2";
    String units "miligrams Carbon per cubic meter (mg C/m3)";
  }
  Dark_rep3 {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.46;
    String bcodmo_name "replicate";
    String description "Dark - replicate #3";
    String long_name "Dark Rep3";
    String units "miligrams Carbon per cubic meter (mg C/m3)";
  }
  Salt {
    Float32 _FillValue NaN;
    Float32 actual_range 34.3871, 35.5255;
    String bcodmo_name "sal";
    Float64 colorBarMaximum 37.0;
    Float64 colorBarMinimum 32.0;
    String description "Salinity (PSS-78)";
    String long_name "Sea Water Practical Salinity";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PSALST01/";
    String units "unitless";
  }
  Prochl {
    Int32 _FillValue 2147483647;
    Int32 actual_range 44, 447037;
    String bcodmo_name "abundance";
    String description "Prochlorococcus";
    String long_name "Prochl";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "count per mililiter";
  }
  Hetero {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20127, 1262038;
    String bcodmo_name "abundance";
    String description "Heterotrophic Bacteria";
    String long_name "Hetero";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "count per mililiter";
  }
  Synecho {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 21852;
    String bcodmo_name "abundance";
    String description "Synechococcus";
    String long_name "Synecho";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "count per mililiter";
  }
  Euk {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 4238;
    String bcodmo_name "abundance";
    String description "Eukaryotes";
    String long_name "Euk";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P03/current/B070/";
    String units "count per mililiter";
  }
  Flag {
    String bcodmo_name "flag";
    String description 
"Quality Flags for the bottle, chlorophyll, pheopigments, light incubation, dark incubation, salinity & bacteria values respectively.
Quality Indicators:
Flag: Meaning
1: unquality controlled
2: good data
3: suspect (i.e.  questionable) data
4: bad data
5: missing value
9: variable not measured during this cast";
    String long_name "Flag";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Photosynthetic production of organic matter was measured by the 14C tracer
method. All incubations from 1990 through mid-2000 were conducted in situ at
eight depths (5, 25, 45, 75, 100, 125, 150 and 175m) over one daylight period
using a free-drifting array as described by Winn et al. (1991). Starting
HOT-119 (October 2000), we collected samples from only the upper six depths &
modeled the lower two depths based on the monthly climatology. During 2015,
all incubations were conducted in situ on a free floating, surface tethered
array. Integrated carbon assimilation rates were calculated using the
trapezoid rule with the shallowest value extended to 0 meters and the deepest
extrapolated to a value of zero at 200 meters.
 
The information below has been copied from the HOT\\u00a0Field & Laboratory
Protocols page, found
at\\u00a0[http://hahana.soest.hawaii.edu/hot/protocols/protocols.html#](\\\\\"http://hahana.soest.hawaii.edu/hot/protocols/protocols.html#\\\\\")
(last visited on 2018-05-21).
 
SUMMARY: The 14C-radiotracer method is used to measure the assimilation of
dissolved inorganic carbon (DIC) by phytoplankton as an estimate of the rate
of photosynthetic production of organic matter in the euphotic zone.
 
1\\. Principle  
 The 14C method, originally proposed by Steeman-Nielsen (1952), is used to
estimate the uptake of dissolved inorganic carbon (DIC) by planktonic algae in
the water column. The method is based on the fact that the biological uptake
of14C-labeled DIC is proportional to the biological uptake of 12C-DIC. If one
knows the initial concentration of DIC in a water sample, the amount of 14C-
DIC added, the 14C retained in particulate organic matter (14C-POC) at the end
of the incubation and the metabolic discrimination between the two isotopes of
carbon (i.e., 5% discrimination against the heavier 14C isotope), then it is
possible to estimate the total uptake of carbon from the following
relationship:  
 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0
\\u00a0 \\u00a0 \\u00a0 \\u00a0 DIC * 14C-POC * 1.05  
 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 C uptake\\u00a0
=\\u00a0 \\u00a0--------------------  
 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0
\\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 \\u00a0 14C-DIC added\\u00a0  
 Due to the potentially toxic effects of trace metals on phytoplankton
metabolism in oligotrophic waters, the following procedure is used to minimize
the contact between water samples and possible sources of contamination.  
 2. Cleaning  
 2.1.  
 HCl (Baker Instra-Analyzed) solution (1M) is prepared with high purity
hydrochloric acid and freshly-prepared glass distilled deionized water (DDW).  
 2.2.  
 500 ml polycarbonate bottles are rinsed twice with 1M HCl (Baker Instra-
Analyzed) and left overnight filled with the same acid solution. The acid is
removed by rinsing the bottles three times with DDW before air drying.  
 2.3.  
 Go-Flo bottles, fitted with teflon-coated springs, are rinsed three times
with 1M HCl and DDW before use.  
 2.4.  
 Pipette tips used in the preparation of the isotope stock and in the
inoculation of samples are rinsed three times with concentrated HCl (Baker
Instra-Analyzed), three times with DDW and once with the sodium carbonate
solution (Chapter 14, section 3.2) and stored in a clean polyethylene glove
until used.  
 3. Isotope Stock  
 3.1.  
 The preparation of the isotope stock is performed wearing polyethylene
gloves. A 25 ml acid-washed teflon bottle and a 50 ml acid-washed
polypropylene centifuge tube are rinsed three times with DDW.  
 3.2.  
 0.032 g of anhydrous Na2CO3 (ALDRICH 20,442-0, 99.999% purity) are dissolved
in 50 ml DDW in the centrifuge tube to provide a solution of 6 mmol Na2CO3 per
liter.  
 3.3.  
 3.5 ml of NaH-14CO3 (53 mCi mmol-1; Research Products Inc.) are mixed with
16.5 ml of the above prepared Na2CO3 solution in the teflon bottle.  
 3.4.  
 The new stock activity is checked by counting triplicate 10 \\u00b5l samples
with 1 ml \\u03b2-phenethylamine in 10 ml Aquasol-II.  
 3.5.  
 Triplicate 10 \\u00b5l stock samples are also acidified with 1 ml of 2 M HCl,
mixed intermittently for 1-2 hours and counted in 10 ml Aquasol-II to confirm
that there is no 14C-organic carbon contamination. The acidification is done
under the hood. The acidified dpm should be <0.001% of the total dpm of the
14C preparation.  
 4. Incubation Systems  
 Typically we measure primary production using in situ incubation techniques.  
 4.1.  
 A free-floating array equipped with VHF radio and strobe light is used for
the in situ incubations. Incubation bottles are attached to a horizontal
polycarbonate spreader bar which is then attached to the 200 m, 1/2\\\"
polypropylene in situ line at the depths corresponding to the sample
collections.  
 4.2.  
 Generally eight incubation depths are selected (5-175 m, approximately).  
 5. Sampling  
 5.1.  
 Approximately 3 hours before local sunrise, seawater samples are collected
with acid- washed, 12-liter Go-Flo bottles using Kevlar line, metal-free
sheave, teflon messengers and a stainless steel bottom weight. A dedicated
hydrowinch is used for the primary productivity sampling procedures in a
further effort to reduce/eliminate all sources of trace metal contamination.  
 5.2.  
 Under low light conditions, water samples are transferred to the incubation
bottles (500 ml polycarbonate bottles) and stored in the dark. Polyethylene
gloves are worn during sample collection and inoculation procedures. No
drawing tubes are used.  
 6. Isotope Addition and Sample Incubation  
 6.1.  
 Three light bottles, three dark bottles and 1 time-zero control (see Chapter
14, section 8) are collected at each depth for in situ incubation. In situ
dark bottles are deployed in specially- designed, double-layered cloth bags
with VelcroR closures.  
 6.2.  
 After all water samples have been drawn from the appropriate Go-Flo bottles,
250 \\u00b5l of the 14C-sodium carbonate stock solution is added to each sample
using a specially-cleaned pipette tip. The samples are deployed before dawn on
a free-floating, drifter buoy array.  
 6.3.  
 At local sunset, the free-floating array is recovered and all in situ
bottles are immediately placed in the dark and processed as soon as possible.
The time of recovery is recorded.  
 7. Filtration  
 7.1.  
 Filtration of the samples is done under low light conditions and begins as
soon as the incubation bottles are recovered from the in situ array.  
 7.2.  
 200 \\u00b5l are removed and placed into a second LSC vial containing 0.5 ml
of \\u03b2-phenethylamine. This sample is used for the determination of total
radioactivity in each sample.  
 7.3.  
 The remainder is filtered through a 25 mm diameter GF/F filters. The filters
are placed into prelabelled, clean glass liquid scintillation counting vials
(LSC vials) and stored at -20 \\u00b0C.  
 8. 14C Sample Processing  
 8.1.  
 One ml of 2 M HCl is added to each sample vial (under the hood). Vials are
covered with their respective caps and shaken in a vortex mixer for at least 1
hour with venting at 20 minute intervals. To vent, the vials are removed from
the shaker, and the cap opened (under the hood). After shaking is completed,
the vials are left open to vent under the hood for an additional 24 hours.  
 8.2.  
 Ten ml of Aquasol-II are added per vial (including vials for total 14C
radioactivity) and the samples are counted in a liquid scintillation counter.
Samples are counted again after 2 and 4 weeks, before discarding. Counts have
shown a consistent increase during the first two weeks and become stable
between the second and the fourth week. This is probably the result of sample
hydrolysis or diffusion of radioactivity from the GF/F filter matrix, thereby
reducing the extent of self-absorption. Only the 4-week count is used for 14C
calculations. Counts per min (CPM) are converted to disintegration per min
(DPM) using the channels ratio program supplied by the the manufacturer
(Packard Instrument Co.)";
    String awards_0_award_nid "54915";
    String awards_0_award_number "OCE-0926766";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0926766";
    String awards_0_funder_name "NSF Division of Ocean Sciences";
    String awards_0_funding_acronym "NSF OCE";
    String awards_0_funding_source_nid "355";
    String awards_0_program_manager "David L. Garrison";
    String awards_0_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"version: 2018-05-18 
  
    Primary Production data 
    from monthly HOT cruises to deep-water Station ALOHA";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_type "institution";
    String creator_url "https://www.bco-dmo.org/";
    String data_source "extract_data_as_tsv version 2.3  19 Dec 2019";
    String date_created "2018-05-18T17:03:33Z";
    String date_modified "2019-12-10T19:24:43Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.737163.1";
    Float64 Easternmost_Easting -158.0;
    Float64 geospatial_lat_max 22.75;
    Float64 geospatial_lat_min 22.75;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -158.0;
    Float64 geospatial_lon_min -158.0;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 178.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-11-23T17:26:10Z (local files)
2024-11-23T17:26:10Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_737163.html";
    String infoUrl "https://www.bco-dmo.org/dataset/737163";
    String institution "BCO-DMO";
    String instruments_0_acronym "GO-FLO";
    String instruments_0_dataset_instrument_description "Go-Flo bottles";
    String instruments_0_dataset_instrument_nid "737174";
    String instruments_0_description "GO-FLO bottle cast used to collect water samples for pigment, nutrient, plankton, etc. The GO-FLO sampling bottle is specially designed to avoid sample contamination at the surface, internal spring contamination, loss of sample on deck (internal seals), and exchange of water from different depths.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/30/";
    String instruments_0_instrument_name "GO-FLO Bottle";
    String instruments_0_instrument_nid "411";
    String instruments_0_supplied_name "Go-Flo bottles";
    String instruments_1_acronym "Niskin bottle";
    String instruments_1_dataset_instrument_description "External closing niskin sampled in-situ Incubation.";
    String instruments_1_dataset_instrument_nid "737212";
    String instruments_1_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.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0412/";
    String instruments_1_instrument_name "Niskin bottle";
    String instruments_1_instrument_nid "413";
    String instruments_1_supplied_name "External closing niskin";
    String instruments_2_acronym "LSC";
    String instruments_2_dataset_instrument_description "liquid scintillation counter (Packard model 4640; United Technologies Inc.)";
    String instruments_2_dataset_instrument_nid "737175";
    String instruments_2_description "Liquid scintillation counting is an analytical technique which is defined by the incorporation of the radiolabeled analyte into uniform distribution with a liquid chemical medium capable of converting the kinetic energy of nuclear emissions into light energy. Although the liquid scintillation counter is a sophisticated laboratory counting system used the quantify the activity of particulate emitting (ß and a) radioactive samples, it can also detect the auger electrons emitted from 51Cr and 125I samples.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB21/";
    String instruments_2_instrument_name "Liquid Scintillation Counter";
    String instruments_2_instrument_nid "624";
    String instruments_2_supplied_name "liquid scintillation counter";
    String instruments_3_dataset_instrument_description "temperature- and light-controlled deck incubation system (NORDA/USM incubation system)";
    String instruments_3_dataset_instrument_nid "737173";
    String instruments_3_description "A device mounted on a ship that holds water samples under conditions of controlled temperature or controlled temperature and illumination.";
    String instruments_3_instrument_name "Shipboard Incubator";
    String instruments_3_instrument_nid "629001";
    String instruments_3_supplied_name "NORDA/USM incubation system";
    String keywords "bco, bco-dmo, biological, chemical, chemistry, chl, Chl_a_mean, Chl_a_sd, chlorophyll, concentration, concentration_of_chlorophyll_in_sea_water, cruise, dark, Dark_rep1, Dark_rep2, Dark_rep3, data, dataset, date, density, depth, dmo, earth, Earth Science > Oceans > Ocean Chemistry > Chlorophyll, Earth Science > Oceans > Salinity/Density > Salinity, end, end_date_time, End_time, erddap, euk, filename, flag, hetero, incubation, Incubation_type, latitude, light, Light_rep1, Light_rep2, Light_rep3, longitude, management, mean, ocean, oceanography, oceans, office, pheo, Pheo_mean, Pheo_sd, practical, preliminary, prim, PrimProd_filename, prochl, prod, rep1, rep2, rep3, salinity, Salt, science, sea, sea_water_practical_salinity, seawater, start, start_date_time, Start_time, synecho, time, time2, type, water";
    String keywords_vocabulary "GCMD Science Keywords";
    String license "https://www.bco-dmo.org/dataset/737163/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/737163";
    Float64 Northernmost_Northing 22.75;
    String param_mapping "{'737163': {'lat': 'flag - latitude', 'Depth': 'flag - depth', 'lon': 'flag - longitude', 'end_date_time': 'flag - time'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/737163/parameters";
    String people_0_affiliation "University of Hawaii at Manoa";
    String people_0_affiliation_acronym "SOEST";
    String people_0_person_name "David M. Karl";
    String people_0_person_nid "50750";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Hawaii at Manoa";
    String people_1_affiliation_acronym "SOEST";
    String people_1_person_name "Lance  A Fujieki";
    String people_1_person_nid "51683";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Mathew Biddle";
    String people_2_person_nid "708682";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "HOT";
    String projects_0_acronym "HOT";
    String projects_0_description 
"Systematic, long-term observations are essential for evaluating natural variability of Earth’s climate and ecosystems and their responses to anthropogenic disturbances.  Since October 1988, the Hawaii Ocean Time-series (HOT) program has investigated temporal dynamics in biology, physics, and chemistry at Stn. ALOHA (22°45' N, 158°W), a deep ocean field site in the oligotrophic North Pacific Subtropical Gyre (NPSG). HOT conducts near monthly ship-based sampling and makes continuous observations from moored instruments to document and study NPSG climate and ecosystem variability over semi-diurnal to decadal time scales. HOT was founded to understand the processes controlling the time-varying fluxes of carbon and associated biogenic elements in the ocean and to document changes in the physical structure of the water column. To achieve these broad objectives, the program has several specific goals:
Quantify time-varying (seasonal to decadal) changes in reservoirs and fluxes of carbon (C) and associated bioelements (nitrogen, oxygen, phosphorus, and silicon).
Identify processes controlling air-sea C exchange, rates of C transformation through the planktonic food web, and fluxes of C into the ocean’s interior.
Develop a climatology of hydrographic and biogeochemical dynamics from which to form a multi-decadal baseline from which to decipher natural and anthropogenic influences on the NPSG ecosystem. 
Provide scientific and logistical support to ancillary programs that benefit from the temporal context, interdisciplinary science, and regular access to the open sea afforded by HOT program occupation of Sta. ALOHA, including projects implementing, testing, and validating new methodologies, models, and transformative ocean sampling technologies.
Over the past 24+ years, time-series research at Station ALOHA has provided an unprecedented view of temporal variability in NPSG climate and ecosystem processes.  Foremost among HOT accomplishments are an increased understanding of the sensitivity of bioelemental cycling to large scale ocean-climate interactions, improved quantification of reservoirs and time varying fluxes of carbon, identification of the importance of the hydrological cycle and its influence on upper ocean biogeochemistry, and the creation of long-term data sets from which the oceanic response to anthropogenic perturbation of elemental cycles may be gauged. 
A defining characteristic of the NPSG is the perennially oligotrophic nature of the upper ocean waters.  This biogeochemically reactive layer of the ocean is where air-sea exchange of climate reactive gases occurs, solar radiation fuels rapid biological transformation of nutrient elements, and diverse assemblages of planktonic organisms comprise the majority of living biomass and sustain productivity.  The prevailing Ekman convergence and weak seasonality in surface light flux, combined with relatively mild subtropical weather and persistent stratification, result in a nutrient depleted upper ocean habitat.  The resulting dearth of bioessential nutrients limits plankton standing stocks and maintains a deep (175 m) euphotic zone.  Despite the oligotrophic state of the NPSG, estimates of net organic matter production at Sta. ALOHA are estimated to range ~1.4 and 4.2 mol C m2 yr1.  Such respectable rates of productivity have highlighted the need to identify processes supplying growth limiting nutrients to the upper ocean.  Over the lifetime of HOT numerous ancillary science projects have leveraged HOT science and infrastructure to examine possible sources of nutrients supporting plankton productivity.  Both physical (mixing, upwelling) and biotic (N2 fixation, vertical migration) processes supply nutrients to the upper ocean in this region, and HOT has been instrumental in demonstrating that these processes are sensitive to variability in ocean climate.
Station ALOHA - site selection and infrastructure
Station ALOHA is a deep water (~4800 m) location approximately 100 km north of the Hawaiian Island of Oahu.  Thus, the region is far enough from land to be free of coastal ocean dynamics and terrestrial inputs, but close enough to a major port (Honolulu) to make relatively short duration (45 m depth), below depths of detection by Earth-orbiting satellites.  The emerging data emphasize the value of in situ measurements for validating remote and autonomous detection of plankton biomass and productivity and demonstrate that detection of potential secular-scale changes in productivity against the backdrop of significant interannual and decadal fluctuations demands a sustained sampling effort.     
Careful long-term measurements at Stn. ALOHA also highlight a well-resolved, though relatively weak, seasonal climatology in upper ocean primary productivity.  Measurements of 14C-primary production document a ~3-fold increase during the summer months (Karl et al., 2012) that coincides with increases in plankton biomass (Landry et al., 2001; Sheridan and Landry, 2004).  Moreover, phytoplankton blooms, often large enough to be detected by ocean color satellites, are a recurrent summertime feature of these waters (White et al., 2007; Dore et al., 2008; Fong et al., 2008). Analyses of ~13-years (1992-2004) of particulate C, N, P, and biogenic Si fluxes collected from bottom-moored deep-ocean (2800 m and 4000 m) sediment traps provide clues to processes underlying these seasonal changes.  Unlike the gradual summertime increase in sinking particle flux observed in the upper ocean (150 m) traps, the deep sea particle flux record depicts a sharply defined summer maximum that accounts for ~20% of the annual POC flux to the deep sea, and appears driven by rapidly sinking diatom biomass (Karl et al., 2012).  Analyses of the 15N isotopic signatures associated with sinking particles at Sta. ALOHA, together with genetic analyses of N2 fixing microorganisms, implicates upper ocean N2 fixation as a major control on the magnitude and efficiency of the biological carbon pump in this ecosystem (Dore et al., 2002; Church et al., 2009; Karl et al., 2012).
Motivating Questions
Science results from HOT continue to raise new, important questions about linkages between ocean climate and biogeochemistry that remain at the core of contemporary oceanography.  Answers have begun to emerge from the existing suite of core program measurements; however, sustained sampling is needed to improve our understanding of contemporary ecosystem behavior and our ability to make informed projections of future changes to this ecosystem. HOT continues to focus on providing answers to some of the questions below:
How sensitive are rates of primary production and organic matter export to short- and long-term climate variability?
What processes regulate nutrient supply to the upper ocean and how sensitive are these processes to climate forcing? 
What processes control the magnitude of air-sea carbon exchange and over what time scales do these processes vary?
Is the strength of the NPSG CO2 sink changing in time?
To what extent does advection (including eddies) contribute to the mixed layer salinity budget over annual to decadal time scales and what are the implications for upper ocean biogeochemistry?
How do variations in plankton community structure influence productivity and material export? 
What processes trigger the formation and demise of phytoplankton blooms in a persistently stratified ocean ecosystem?
References";
    String projects_0_end_date "2014-12";
    String projects_0_geolocation "North Pacific Subtropical Gyre; 22 deg 45 min N, 158 deg W";
    String projects_0_name "Hawaii Ocean Time-series (HOT): Sustaining ocean ecosystem and climate observations in the North Pacific Subtropical Gyre";
    String projects_0_project_nid "2101";
    String projects_0_project_website "http://hahana.soest.hawaii.edu/hot/hot_jgofs.html";
    String projects_0_start_date "1988-07";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 22.75;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "longitude,latitude";
    String summary "Primary productivity measurements from the Hawaii Ocean Time-Series (HOT). Photosynthetic production of organic matter was measured by the 14C tracer method. All incubations from 1990 through mid-2000 were conducted in situ at eight depths (5, 25, 45, 75, 100, 125, 150 and 175m) over one daylight period using a free-drifting array as described by Winn et al. (1991). Starting HOT-119 (October 2000), we collected samples from only the upper six depths & modeled the lower two depths based on the monthly climatology. During 2015, all incubations were conducted in situ on a free floating, surface tethered array. Integrated carbon assimilation rates were calculated using the trapezoid rule with the shallowest value extended to 0 meters and the deepest extrapolated to a value of zero at 200 meters.";
    String time_coverage_start "1989-07-29T19:00:00Z";
    String title "[Primary Production] - Primary productivity measurements from the Hawaii Ocean Time-Series (HOT) project from October 1988 to December 2019 at station ALOHA. ([Current] Hawaii Ocean Time-series (HOT): 2018-2023;  [Previous] Hawaii Ocean Time-series (HOT): Sustaining ocean ecosystem and climate observations in the North Pacific Subtropical Gyre)";
    String version "1";
    Float64 Westernmost_Easting -158.0;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

Using tabledap to Request Data and Graphs from Tabular Datasets

tabledap lets you request a data subset, a graph, or a map from a tabular dataset (for example, buoy data), via a specially formed URL. tabledap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its selection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names, followed by a collection of constraints (e.g., variable<value), each preceded by '&' (which is interpreted as "AND").

For details, see the tabledap Documentation.


 
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