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Dataset Title:  Natural abundance of nitrogen and carbon on filters from Cape Flattery, WA
from 2010-2011 (Regenerated Nitrogen project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_489310)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | Files | Make a graph
 
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 site (unitless) ?      
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 latitude (degrees_north) ?      
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 longitude (degrees_east) ?      
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 shore_offshore (text) ?      
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 depth (m) ?      
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 sample (unitless) ?          "170a"    "2B757"
 date (unitless) ?          20100514    20110826
 vol_filt (liters) ?          1.14    3.14
 d15N (parts per thousand vs. VSMOW (Vienna Standard Mean Ocean Water)) ?          3.557    7.138
 N_pcent (percent) ?          0.1398    14.138
 C_pcent (percent) ?          12.006    90.278
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  site {
    String bcodmo_name "site";
    String description "sampling location";
    String long_name "Site";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 48.37, 48.37;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; north is positive";
    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";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -124.57, -124.57;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; east is positive";
    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";
  }
  shore_offshore {
    String bcodmo_name "unknown";
    String description "sampling was close to shore or off-shore";
    String long_name "Shore Offshore";
    String units "text";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 0.0;
    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";
  }
  sample {
    String bcodmo_name "sample";
    String description "sample identification number";
    String long_name "Sample";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  date {
    Int32 _FillValue 2147483647;
    Int32 actual_range 20100514, 20110826;
    String bcodmo_name "date";
    String description "date samples collected in yyyymmdd format";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  }
  vol_filt {
    Float32 _FillValue NaN;
    Float32 actual_range 1.14, 3.14;
    String bcodmo_name "vol_filt";
    String description "volume filtered";
    String long_name "Vol Filt";
    String units "liters";
  }
  d15N {
    Float32 _FillValue NaN;
    Float32 actual_range 3.557, 7.138;
    String bcodmo_name "unknown";
    String description "nitrogen isotopic composition (delta 15N:N14) of the (mostly organic) material trapped on the filter";
    String long_name "D15 N";
    String units "parts per thousand vs. VSMOW (Vienna Standard Mean Ocean Water)";
  }
  N_pcent {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1398, 14.138;
    String bcodmo_name "unknown";
    String description "percent nitrogen";
    String long_name "N Pcent";
    String units "percent";
  }
  C_pcent {
    Float32 _FillValue NaN;
    Float32 actual_range 12.006, 90.278;
    String bcodmo_name "unknown";
    String description "percent carbon";
    String long_name "C Pcent";
    String units "percent";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Laboratory analysis
 
NH4+ and NO3- concentrations were measured at the University of Washington
Marine Chemistry Lab (methods from UNESCO 1994). Concentration values from
2011 were corrected for rain dilution using the change in salinity measured
over the incubation period assuming no addition of NH4+ or NO3- to the pools
from the rainfall.\\u00a0
 
NH4+ isotopic composition was measured according to a modified version of
Zhang et al. (2007) after isotope dilution to less than 500\\u2030 to prevent
isotopic contamination of the natural abundance-level mass spectrometer
system. Briefly, NH4+ is oxidized to nitrite using hypobromite then reduced to
N2O using acetic acid buffered sodium azide before analysis on an isotope
ratio mass spectrometer (IRMS). In modification of the prior method, pre-
existing NO2- was removed prior to hypobromite addition by reaction with
sulfamic acid. To a 20 mL sample volume, 340 \\u00b5L 20 mmol L-1 sulfamic acid
and 10 \\u00b5L 10% HCl was added and allowed to react for 12 hours at room
temperature. A second improvement was the addition of 6 mol L-1 HCl to reduce
the pH of the sample below 7 prior to the addition of an azide-100% acetic
acid reagent. Isotope determinations were made at U. Massachusetts Dartmouth
using a GV IsoPrime IRMS, a custom purge-trap sample preparation system, and a
CTC PAL autosampler. Reproducibility was better than \\u00b1 0.5\\u2030. \\u00a0
 
Filters and algal samples were dried at 60\\u00b0C for 48 h and elemental and
isotopic analyses were made at the University of Chicago and at Yale
University. Samples were run using a Costech 4010 Elemental Analyzer
combustion system coupled to a Thermo DeltaV Plus IRMS via a Thermo Conflo IV
interface (University of Chicago), or using the same Elemental Analyzer
coupled to a Thermo DeltaXP Advantage IRMS via a Thermo Conflo III interface
(Yale University). \\u00a0Reproducibility was better than \\u00b1 0.1\\u2030.";
    String awards_0_award_nid "474676";
    String awards_0_award_number "OCE-0928232";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0928232";
    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 awards_1_award_nid "474685";
    String awards_1_award_number "OCE-0928015";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0928015";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "David L. Garrison";
    String awards_1_program_manager_nid "50534";
    String awards_2_award_nid "474686";
    String awards_2_award_number "OCE-0928152";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=0928152";
    String awards_2_funder_name "NSF Division of Ocean Sciences";
    String awards_2_funding_acronym "NSF OCE";
    String awards_2_funding_source_nid "355";
    String awards_2_program_manager "David L. Garrison";
    String awards_2_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"nitrogen & carbon natural abundance 
  
   S. Pather (UMass-SMAST) 
  
  version: 2014-11-04   [added site column] 
   replaces version: 24 January 2014";
    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 "2014-01-31T13:31:43Z";
    String date_modified "2016-08-20T03:10:46Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/6420";
    Float64 Easternmost_Easting -124.57;
    Float64 geospatial_lat_max 48.37;
    Float64 geospatial_lat_min 48.37;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -124.57;
    Float64 geospatial_lon_min -124.57;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 0.0;
    Float64 geospatial_vertical_min 0.0;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-03-28T09:00:37Z (local files)
2024-03-28T09:00:37Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_489310.html";
    String infoUrl "https://www.bco-dmo.org/dataset/489310";
    String institution "BCO-DMO";
    String instruments_0_acronym "IR Mass Spec";
    String instruments_0_dataset_instrument_description "GV IsoPrime IRMS: Isotope determinations were made at U. Massachusetts Dartmouth using a GV IsoPrime IRMS, a custom purge-trap sample preparation system, and a CTC PAL autosampler. Reproducibility was better than ± 0.5‰.";
    String instruments_0_dataset_instrument_nid "489316";
    String instruments_0_description "The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_0_instrument_name "Isotope-ratio Mass Spectrometer";
    String instruments_0_instrument_nid "469";
    String instruments_0_supplied_name "IR Mass Spec";
    String instruments_1_acronym "Nutrient Autoanalyzer";
    String instruments_1_dataset_instrument_description 
"The nutrient autoanalyzer at UWashington was used to determine the nutrient concentrations in the water. Analyses and calibration follow the protocols of the WOCE Hydrographic Program using a Technicon AAII system.
For more information, see http://www.ocean.washington.edu/story/Marine+Chemistry+Laboratory";
    String instruments_1_dataset_instrument_nid "489317";
    String instruments_1_description "Nutrient Autoanalyzer is a generic term used when specific type, make and model were not specified.  In general, a Nutrient Autoanalyzer is an automated flow-thru system for doing nutrient analysis (nitrate, ammonium, orthophosphate, and silicate) on seawater samples.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB04/";
    String instruments_1_instrument_name "Nutrient Autoanalyzer";
    String instruments_1_instrument_nid "558";
    String instruments_1_supplied_name "Nutrient Autoanalyzer";
    String instruments_2_acronym "CHN_EA";
    String instruments_2_dataset_instrument_description 
"Samples were run using a Costech 4010 Elemental Analyzer combustion system coupled to a Thermo DeltaV Plus IRMS via a Thermo Conflo IV interface (University of Chicago), or using the same Elemental Analyzer coupled to a Thermo DeltaXP Advantage IRMS via a Thermo Conflo III interface (Yale University). Reproducibility was better than ± 0.1‰.
These instruments were used to look at the mass composition and isotopic signatures of the algal and filter material.";
    String instruments_2_dataset_instrument_nid "489488";
    String instruments_2_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.";
    String instruments_2_instrument_name "CHN Elemental Analyzer";
    String instruments_2_instrument_nid "625";
    String instruments_2_supplied_name "CHN_EA";
    String keywords "bco, bco-dmo, biological, C_pcent, chemical, d15, d15N, data, dataset, date, depth, dmo, erddap, filt, latitude, longitude, management, N_pcent, oceanography, office, offshore, pcent, preliminary, sample, shore, shore_offshore, site, vol, vol_filt";
    String license "https://www.bco-dmo.org/dataset/489310/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/489310";
    Float64 Northernmost_Northing 48.37;
    String param_mapping "{'489310': {'lat': 'master - latitude', 'depth': 'master - depth', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/489310/parameters";
    String people_0_affiliation "University of Massachusetts Dartmouth";
    String people_0_affiliation_acronym "UMASSD-SMAST";
    String people_0_person_name "Ms Santhiska Pather";
    String people_0_person_nid "488866";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Massachusetts Dartmouth";
    String people_1_affiliation_acronym "UMASSD-SMAST";
    String people_1_person_name "Mark A. Altabet";
    String people_1_person_nid "50571";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Chicago";
    String people_2_person_name "Dr Catherine Pfister";
    String people_2_person_nid "474679";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Yale University";
    String people_3_person_name "Dr David Post";
    String people_3_person_nid "474683";
    String people_3_role "Co-Principal Investigator";
    String people_3_role_type "originator";
    String people_4_affiliation "University of Massachusetts Dartmouth";
    String people_4_affiliation_acronym "UMASSD-SMAST";
    String people_4_person_name "Ms Santhiska Pather";
    String people_4_person_nid "488866";
    String people_4_role "Student";
    String people_4_role_type "related";
    String people_5_affiliation "Woods Hole Oceanographic Institution";
    String people_5_affiliation_acronym "WHOI BCO-DMO";
    String people_5_person_name "Nancy Copley";
    String people_5_person_nid "50396";
    String people_5_role "BCO-DMO Data Manager";
    String people_5_role_type "related";
    String project "Regenerated Nitrogen";
    String projects_0_acronym "Regenerated Nitrogen";
    String projects_0_description 
"We described patterns of nitrogen isotopes that change over spatial gradients of animal abundance, with isotopic enrichment patterns consistent with a role for animal excretion (Pfister et al, ms). We have quantified the microbes associated with intertidal mussels with metagenomics (Pfister et al. 2010 and 16S rRNA sequencing of the v4 region (Pfister et al, submitted). We used a novel experimental approach in which stable isotope tracers were added to exposed tidepools utilizing them as temporary mesocosms to quantify N transformation rates (Pather et al.,L&O). Large tracer signals were observed over the typical 4-5 hr experimental period in both the dilution of the isotope label in its added form (NH4+ or NO3-) and the appearance of the label in products (e.g. NO2-) The primary advantage was that all members of community participated in the experiment allowing us to recognize the complexity of nitrogen cycling in this system. This funding also supported long-term global change research on Tatoosh Island (Wootton & Pfister 2012 ).   
Project Summary From Original Proposal
A fundamental and persistent question in a multitude of ecosystems is the extent to which new versus regenerated nutrients support ecosystem productivity. In coastal marine systems, nitrate derived from upwelling (=new nitrogen) and ammonium regeneration in coastal waters and sediments (=regenerated nitrogen) are major nitrogen sources that fuel coastal ocean productivity. Because inorganic nitrogen availability clearly regulates production in a large number of areas, understanding nitrogen supply is essential. In open coast regions away from river mouths, nitrate inputs are determined by large-scale physical processes promoting upwelling of deep, nutrient-rich water including wind direction and intensity. In contrast, regenerated nitrogen (mainly ammonium) is generally the result of local animal and microbial processes. Along marine rocky shores, where upwelling is typically used as a proxy for productivity, we know very little about the dynamics of regenerated nutrients and their potential contribution to productivity at larger scales; only upwelling is typically used as a proxy for productivity. Associations of the abundant California mussel, Mytilus californianus, with water nutrients, algal productivity, stable isotope signatures, and microbial genetics indicate potentially strong regeneration of nitrogen by these animals and suggests an important secondary role of nitrifying microbes affiliated with these animals.
We propose collaborative work to quantify the relative contribution of regenerated nitrogen on rocky shores through censuses and experiments across a gradient of mussel abundance. We will use stable nitrogen and oxygen isotopes of ammonium, nitrite, and nitrate to disentangle the contribution of different biological processes versus upwelling to the nitrogen supply and uptake of rocky shore regions. This includes both natural abundance and tracer addition studies.
 
Relevant References:
2010. Pfister, C. A., F. Meyer, D. A. Antonopoulos. Metagenomic profiling of a microbial assemblage associated with the California mussel, Mytilus californianus: a node in networks of carbon and nitrogen cycling. PLoS ONE 5(5): e10518. doi:10.1371/ journal.pone.0010518. Metagenome data associated with this paper are uploaded to MGRAST server at http://metagenomics.anl.gov/
2012. Wootton, J. T. & C. A. Pfister. Carbon system measurements and potential climatic drivers at a site of rapidly declining ocean pH. PLoS ONE 7(12): e53396. doi:10.1371/ journal.pone.0053396. Data associated with this paper are uploaded to the World Ocean DataBase, https://www.nodc.noaa.gov
in press. Pather, S., C. A. Pfister, M. Altabet, D. M. Post. Ammonium cycling in the rocky intertidal: remineralization, removal and retention. Limnology and Oceanography
in review (1/2014). Pfister, C. A., M. Altabet, D. Post. Animal Regeneration and microbial retention of nitrogen along coastal rocky shores.";
    String projects_0_end_date "2013-08";
    String projects_0_geolocation "coastal northeast Pacific Ocean";
    String projects_0_name "The Role of Regenerated Nitrogen for Rocky Shore Productivity";
    String projects_0_project_nid "474677";
    String projects_0_project_website "http://pfisterlab.uchicago.edu";
    String projects_0_start_date "2009-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 48.37;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "site,latitude,longitude,shore_offshore,depth";
    String summary 
"We evaluated the role of mussels by adding 15N-labeled NH4+ to an assemblage
of tidepools where they were either present at natural abundance levels, or
absent through manual removal. \\u00a0The role of phototrophs was separately
examined by conducting these experiments both during the day and at night.
\\u00a0The tidal height of pools varied between 1.2 to 1.5 m above Mean Lower
Low Water (MLLW). Tidepools were thus isolated from each other as well as the
nearshore environment during the low tide period when experiments were
conducted. Each experiment included 4 to 5 mussel removal (MR) tidepools
(since 2002) and 4 to 5 mussel control (MC) tidepools with natural mussel
densities. \\u00a0In June 2010, we performed daytime NH4+ tracer experiments
and in August 2010 nighttime experiments using the same tidepools. The
following year (July 2011) these experiments were repeated with the addition
of bottle incubations (see below) to evaluate the effects of suspended
tidepool components and extended sampling for 6 days after the initial 15N
addition to test for long-term retention of NH4+. \\u00a0During the 2011
experiments, unforeseen rain reduced the salinity in some pools by up to 51%,
and we have attempted to correct for the expected dilution of NH4+ in our
tidepool rate calculations.
 
Because isotope enrichment levels were relatively low, we used the
conventional delta notation instead of atom% to describe variations in 15N
enrichment (where delta-15NH4+ = {(15N:14N sample \\u00f7 15N:14N standard)
-1}\\u00d71000\\u2030, where the standard is atmospheric N2. \\u00a0Tracer
labeled ammonium chloride (15NH4Cl) was added to the pools to approximate a
1000\\u2030 enrichment in 2010 (doubling the 15N-NH4+ concentration) and a
2000\\u2030 enrichment in 2011(tripling the 15N-NH4+ concentration). 15N
natural abundance is only 0.365% and these tracer additions thus had a
negligible effect on the overall NH4+ concentrations increasing them by only
~0.4% and ~0.8%, respectively. Tidepool volumes were estimated
spectrophotometrically using varying concentrations of food dye (Pfister
1995). Together with estimates of NH4+ concentration (from 2009 data), we
estimated the tracer addition required to achieve the targeted 15N
enrichments. However, the actual initial enrichments varied substantially,
684.4 - 2406.4\\u2030 in 2010 and 781.4 - 3880.2\\u2030 in 2011, likely due to
error in tidepool volume estimation and natural variations in initial NH4+
concentrations. Fortunately, we sampled immediately following each tracer
addition allowing for the determination of the true initial 15N enrichment.
\\u00a0
 
Prior to tracer addition at ebb tide, 100 mL of tidepool water was syringe-
filtered (Whatman GF/F) into separate HDPE bottles for natural abundance
15NH4+ and concentration determination. \\u00a0To each pool, tracer 15NH4+ was
then added and distributed by stirring with a stick. Water samples were
immediately collected for measuring initial 15N enrichment and subsequently at
2, 4, and 6 hour intervals to determine isotope and concentration time
courses. All water samples were frozen until analysis. Tidepool oxygen, pH,
and temperature (Hach HQ4D) were also collected at ~ 2 h intervals throughout
the experiment.
 
In 2011 we also assessed the contribution of the suspended microbial community
to NH4+ cycling by enclosing tidepool water in a 250 mL transparent
polycarbonate incubation bottle. Following tracer addition, the bottle was
filled, then left to float in the tidepool for the duration of the experiment.
Samples from bottles were filtered as described both immediately after
containment and at the end of the experiment (~6 h later).
 
We assessed macroalgal contribution to NH4+ removal by transplanting two
tidepool-dwelling algae species. \\u00a0Prionitis sternbergii were sampled 2
weeks prior to the experiment for baseline natural abundance 15N values and
transplanted into the pools with Z-Spar Epoxy (Pfister 2007). On the day of
the experiment, the red-alga, Corallina vancouveriensis from a single source
patch, was also sampled for 15N natural abundance, inserted into pieces of
Styrofoam, and floated in each pool.
 
At the end of each experiment (~6 h sampling point), we sampled tidepool
particulate organic material (POM) by filtering through combusted GF/F filters
until they clogged (~ 600 mL), comparing these samples with POM similarly
sampled from the immediate nearshore. \\u00a0Floating Corallina spp. samples
were collected into clean Eppendorf tubes, and similar sized pieces of
Prionitis spp. were collected from each pool into clean foil packets.\\u00a0  
 We evaluated the extent of longer-term 15N tracer retention in 2011 by
sampling tidepool water, POM and transplanted Prionitis 1, 3, and 6 days
following tracer addition. We sampled at ebb tide and at again at slack water
just prior to high tide on the first day after tracer addition (that is, 24 h
later) and at slack water prior to high tide on Day 3 and 6.\\u00a0
 
Relevant References:
 
2014\\. Pather, S., C. A. Pfister, M. Altabet, D. M. Post. Ammonium cycling in
the rocky intertidal: remineralization, removal and retention. Limnology and
Oceanography
59:361-372.\\u00a0[http://aslo.org/lo/toc/vol_59/issue_2/0361.htm](\\\\http://aslo.org/lo/toc/vol_59/issue_2/0361.html\\\\)
 
DOI for this dataset:\\u00a0The role of regenerated nitrogen for rocky shore
productivity, Cape Flattery, Washington, 2010 &
2011.\\u00a0Handle:\\u00a0[http://hdl.handle.net/1912/6420](\\\\http://hdl.handle.net/1912/6420\\\\).\\u00a0DOI:10.1575/1912/6420
 
Related Datasets:  
[ammonium removal by seaweeds](\\\\https://www.bco-dmo.org/dataset/489420\\\\)  
[filter tracer content](\\\\https://www.bco-dmo.org/dataset/489283\\\\)  
[tidepool ammonium and mussels](\\\\https://www.bco-dmo.org/dataset/488860\\\\)  
[tidepool incubation ammonium](\\\\https://www.bco-dmo.org/dataset/489085\\\\)";
    String title "Natural abundance of nitrogen and carbon on filters from Cape Flattery, WA from 2010-2011 (Regenerated Nitrogen project)";
    String version "1";
    Float64 Westernmost_Easting -124.57;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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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