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Dataset Title:	[AA-CSIA Olson] - Amino acid compound-specific isotope analysis (AA-CSIA) of tissue samples from four distinct trophic groups across the food web in the pelagic eastern tropical Pacific Ocean; samples collected on NOAA cruises from July to December 2006 (CAMEO 2009 - A novel tool for validating trophic position estimates in ecosystem-based fisheries models)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_679447)
Information:	Summary | License | ISO 19115 | Metadata | Background | Files | Make a graph

 

Variable	Optional Constraint #1		Optional Constraint #2		Minimum	Maximum
species (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Dosidicus_gigas"	"Thunnus_obesus"
sample_number (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"Dg1"	"To7"
date_analyzed (unitless)	!= =~ <= >= = < >		!= =~ <= >= = < >		"2011-10-05"	"2012-07-06"
Alanine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		12.5	28.4
Alanine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	1.2
Glycine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-7.9	11.9
Glycine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.4
Threonine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-28.0	-2.3
Threonine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.2	2.5
Serine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-1.3	13.2
Serine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	1.0
Valine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		10.1	24.4
Valine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.9
Leucine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		9.4	25.9
Leucine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.0
Isoleucine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		11.7	36.0
Isoleucine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.7
Proline_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		5.3	24.0
Proline_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.2	1.2
AsparticAcid_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		1.3	28.4
AsparticAcid_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	1.0
Methionine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-0.3	14.5
Methionine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.5
GlutamicAcid_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		13.0	27.9
GlutamicAcid_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	0.8
Phenylalanine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-4.4	10.5
Phenylalanine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.7
Tyrosine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-0.8	15.1
Tyrosine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.1	1.3
Lysine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-1.7	11.1
Lysine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.0	0.9
Arginine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-3.2	10.1
Arginine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.3	1.0
Histidine_Avg (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		-3.2	6.3
Histidine_SD (parts per thousand (per mil, ‰))	!= =~ <= >= = < >		!= =~ <= >= = < >		0.2	1.0

 

Server-side Functions

distinct()

orderBy orderByDescending orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean orderBySum (" species sample_number date_analyzed Alanine_Avg Alanine_SD Glycine_Avg Glycine_SD Threonine_Avg Threonine_SD Serine_Avg Serine_SD Valine_Avg Valine_SD Leucine_Avg Leucine_SD Isoleucine_Avg Isoleucine_SD Proline_Avg Proline_SD AsparticAcid_Avg AsparticAcid_SD Methionine_Avg Methionine_SD GlutamicAcid_Avg GlutamicAcid_SD Phenylalanine_Avg Phenylalanine_SD Tyrosine_Avg Tyrosine_SD Lysine_Avg Lysine_SD Arginine_Avg Arginine_SD Histidine_Avg Histidine_SD species sample_number date_analyzed Alanine_Avg Alanine_SD Glycine_Avg Glycine_SD Threonine_Avg Threonine_SD Serine_Avg Serine_SD Valine_Avg Valine_SD Leucine_Avg Leucine_SD Isoleucine_Avg Isoleucine_SD Proline_Avg Proline_SD AsparticAcid_Avg AsparticAcid_SD Methionine_Avg Methionine_SD GlutamicAcid_Avg GlutamicAcid_SD Phenylalanine_Avg Phenylalanine_SD Tyrosine_Avg Tyrosine_SD Lysine_Avg Lysine_SD Arginine_Avg Arginine_SD Histidine_Avg Histidine_SD species sample_number date_analyzed Alanine_Avg Alanine_SD Glycine_Avg Glycine_SD Threonine_Avg Threonine_SD Serine_Avg Serine_SD Valine_Avg Valine_SD Leucine_Avg Leucine_SD Isoleucine_Avg Isoleucine_SD Proline_Avg Proline_SD AsparticAcid_Avg AsparticAcid_SD Methionine_Avg Methionine_SD GlutamicAcid_Avg GlutamicAcid_SD Phenylalanine_Avg Phenylalanine_SD Tyrosine_Avg Tyrosine_SD Lysine_Avg Lysine_SD Arginine_Avg Arginine_SD Histidine_Avg Histidine_SD species sample_number date_analyzed Alanine_Avg Alanine_SD Glycine_Avg Glycine_SD Threonine_Avg Threonine_SD Serine_Avg Serine_SD Valine_Avg Valine_SD Leucine_Avg Leucine_SD Isoleucine_Avg Isoleucine_SD Proline_Avg Proline_SD AsparticAcid_Avg AsparticAcid_SD Methionine_Avg Methionine_SD GlutamicAcid_Avg GlutamicAcid_SD Phenylalanine_Avg Phenylalanine_SD Tyrosine_Avg Tyrosine_SD Lysine_Avg Lysine_SD Arginine_Avg Arginine_SD Histidine_Avg Histidine_SD species sample_number date_analyzed Alanine_Avg Alanine_SD Glycine_Avg Glycine_SD Threonine_Avg Threonine_SD Serine_Avg Serine_SD Valine_Avg Valine_SD Leucine_Avg Leucine_SD Isoleucine_Avg Isoleucine_SD Proline_Avg Proline_SD AsparticAcid_Avg AsparticAcid_SD Methionine_Avg Methionine_SD GlutamicAcid_Avg GlutamicAcid_SD Phenylalanine_Avg Phenylalanine_SD Tyrosine_Avg Tyrosine_SD Lysine_Avg Lysine_SD Arginine_Avg Arginine_SD Histidine_Avg Histidine_SD ")

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  species {
    String bcodmo_name "species";
    String description "Name of the species";
    String long_name "Species";
    String units "unitless";
  }
  sample_number {
    String bcodmo_name "sample";
    String description "Sample identification number";
    String long_name "Sample Number";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  date_analyzed {
    String bcodmo_name "date";
    String description "Date on which AA-CSIA analysis of corresponding sample was begun; formatted as yyyy-mm-dd";
    String long_name "Date Analyzed";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date_analyzed";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  Alanine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 12.5, 28.4;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Alanine";
    String long_name "Alanine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Alanine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.2;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Alanine";
    String long_name "Alanine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Glycine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -7.9, 11.9;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Glycine";
    String long_name "Glycine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Glycine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.4;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Glycine";
    String long_name "Glycine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Threonine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -28.0, -2.3;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Threonine";
    String long_name "Threonine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Threonine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 2.5;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Threonine";
    String long_name "Threonine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Serine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -1.3, 13.2;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Serine";
    String long_name "Serine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Serine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.0;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Serine";
    String long_name "Serine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Valine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 10.1, 24.4;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Valine";
    String long_name "Valine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Valine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.9;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Valine";
    String long_name "Valine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Leucine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 9.4, 25.9;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Leucine";
    String long_name "Leucine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Leucine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.0;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Leucine";
    String long_name "Leucine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Isoleucine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 11.7, 36.0;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Isoleucine";
    String long_name "Isoleucine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Isoleucine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.7;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Isoleucine";
    String long_name "Isoleucine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Proline_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 5.3, 24.0;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Proline";
    String long_name "Proline Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Proline_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 1.2;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Proline";
    String long_name "Proline SD";
    String units "parts per thousand (per mil, ‰)";
  }
  AsparticAcid_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 1.3, 28.4;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Aspartic Acid";
    String long_name "Aspartic Acid Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  AsparticAcid_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1.0;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Aspartic Acid";
    String long_name "Aspartic Acid SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Methionine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -0.3, 14.5;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Methionine";
    String long_name "Methionine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Methionine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.5;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Methionine";
    String long_name "Methionine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  GlutamicAcid_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range 13.0, 27.9;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Glutamic Acid";
    String long_name "Glutamic Acid Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  GlutamicAcid_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 0.8;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Glutamic Acid";
    String long_name "Glutamic Acid SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Phenylalanine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -4.4, 10.5;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Phenylalanine";
    String long_name "Phenylalanine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Phenylalanine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.7;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Phenylalanine";
    String long_name "Phenylalanine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Tyrosine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -0.8, 15.1;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Tyrosine";
    String long_name "Tyrosine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Tyrosine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.1, 1.3;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Tyrosine";
    String long_name "Tyrosine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Lysine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -1.7, 11.1;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Lysine";
    String long_name "Lysine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Lysine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.9;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Lycine";
    String long_name "Lysine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Arginine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -3.2, 10.1;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Arginine";
    String long_name "Arginine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Arginine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.3, 1.0;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Arginine";
    String long_name "Arginine SD";
    String units "parts per thousand (per mil, ‰)";
  }
  Histidine_Avg {
    Float32 _FillValue NaN;
    Float32 actual_range -3.2, 6.3;
    String bcodmo_name "d15N_bio";
    String description "mean d15N value of Histidine";
    String long_name "Histidine Avg";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/IRBO/";
    String units "parts per thousand (per mil, ‰)";
  }
  Histidine_SD {
    Float32 _FillValue NaN;
    Float32 actual_range 0.2, 1.0;
    String bcodmo_name "standard deviation";
    Float64 colorBarMaximum 50.0;
    Float64 colorBarMinimum 0.0;
    String description "standard deviation of d15N values of Histidine";
    String long_name "Histidine SD";
    String units "parts per thousand (per mil, ‰)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Sampling Methodology:\\u00a0Zooplankton, small mesopelagic fishes, and squids
were collected from July 28 to December 8, 2006 during the National Oceanic
and Atmospheric Administration\\u2019s (NOAA's) Stenella Abundance Research
(STAR) surveys (Gerrodette et al. 2008). We defined our study area to include
a subset of sample locations from the STAR surveys based on the presence of
both east-west and north-south productivity gradients across the region, with
greater surface chlorophyll a concentrations at the eastern end of the study
area and along the equator, according to published oceanographic data.
Zooplankton samples were collected with a cylindrical-conical bongo net (333
um mesh), fished to 200 m approximately two hours after sunset, and the
samples were frozen within one hour of collection. Specimens of euphausiid
crustaceans, Euphausia distinguenda (Ed) and E. tenera (Et) were sorted from
the thawed zooplankton samples in the laboratory. Specimens of mesopelagic
myctophid fishes Myctophum nitidulum (Mn) and Symbolophorus reversus (Sr) were
collected by dipnet at night. Specimens of the squids Dosidicus gigas (Dg) and
Sthenoteuthis oualaniensis (So) also were collected at night, using handlines
and jigs. (See Olson et al. 2010, Philbrick et al. 2001 for detailed methods).
 
Three species of tuna, yellowfin (Ta.; Thunnus albacares), skipjack (Kp.;
Katsuwonus pelamis), and bigeye (To.; Thunnus obesus) tunas, were sampled
year-round during 2003-2005 by observers of the Inter-American Tropical Tuna
Commission onboard purse-seine fishing vessels. Samples of dorsal white muscle
were taken from each fish adjacent to the second dorsal fin. Fish of uniform
size were used for analysis: skipjack tuna 450-550 mm, yellowfin tuna 500-700
mm, and bigeye tuna 450-550 mm. All samples were stored frozen until further
processing in the laboratory.
 
Analytical Methodology:\\u00a0 Methods are described in Hetherington et al.
(2016). Briefly: Amino acid (AA) compound-specific isotope analysis (AA-CSIA)
was conducted on a subset of 48 of the samples used for isotopic analysis of
bulk muscle tissue or whole animals. The basis for sample selection was to
represent the range of variability in bulk \\u03b415N values and the range of
sample locations along the transect. The d15N values of individual AAs were
measured using an isotope ratio mass spectrometer (IRMS) (Delta PlusXP, Delta
V Plus or MAT 253) interfaced with a gas chromatograph (Trace GC) through a
GC-C III combustion furnace (980 degrees C), reduction furnace (650 degrees
C), and liquid-N cold trap. All samples were analyzed in triplicate and the
measured AA-d15N values were normalized to known d15N values of two coinjected
internal reference compounds (norleucine and aminoadipic acid with d15N
reference values of 19.06 \\u2030 and -5.8 \\u2030, respectively).";
    String awards_0_award_nid "616068";
    String awards_0_award_number "OCE-1040810";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1040810";
    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 
"AA-CSIA 
 PIs: Robert J. Olson (Inter-American Tropical Tuna Commission) & Brian N. Popp (University of Hawaii) 
 Co-PI: Jeffrey C. Drazen (University of Hawaii) 
 Version: 30 January 2017";
    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 "2017-01-30T21:34:34Z";
    String date_modified "2019-08-05T16:38:23Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.679447.1";
    String history 
"2024-11-08T05:38:42Z (local files)
2024-11-08T05:38:42Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_679447.html";
    String infoUrl "https://www.bco-dmo.org/dataset/679447";
    String institution "BCO-DMO";
    String instruments_0_acronym "Bongo Net";
    String instruments_0_dataset_instrument_description "Zooplankton samples were collected with a cylindrical-conical bongo net (333 um mesh), fished to 200 m approximately two hours after sunset.";
    String instruments_0_dataset_instrument_nid "679629";
    String instruments_0_description "A Bongo Net consists of paired plankton nets, typically with a 60 cm diameter mouth opening and varying mesh sizes, 10 to 1000 micron. The Bongo Frame was designed by the National Marine Fisheries Service for use in the MARMAP program. It consists of two cylindrical collars connected with a yoke so that replicate samples are collected at the same time. Variations in models are designed for either vertical hauls (OI-2500 = NMFS Pairovet-Style, MARMAP Bongo, CalVET) or both oblique and vertical hauls (Aquatic Research). The OI-1200 has an opening and closing mechanism that allows discrete \"known-depth\" sampling. This model is large enough to filter water at the rate of 47.5 m3/minute when towing at a speed of two knots. More information: Ocean Instruments, Aquatic Research, Sea-Gear";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/NETT0009/";
    String instruments_0_instrument_name "Bongo Net";
    String instruments_0_instrument_nid "410";
    String instruments_0_supplied_name "cylindrical-conical bongo net";
    String instruments_1_acronym "IR Mass Spec";
    String instruments_1_dataset_instrument_description "The d15N values of individual AAs were measured using an isotope ratio mass spectrometer (IRMS) (Delta PlusXP, Delta V Plus or MAT 253) interfaced with a gas chromatograph (Trace GC) through a GC-C III combustion furnace (980 degrees C), reduction furnace (650 degrees C), and liquid-N cold trap.";
    String instruments_1_dataset_instrument_nid "679635";
    String instruments_1_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_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_1_instrument_name "Isotope-ratio Mass Spectrometer";
    String instruments_1_instrument_nid "469";
    String instruments_1_supplied_name "isotope ratio mass spectrometer (IRMS)";
    String instruments_2_acronym "Gas Chromatograph";
    String instruments_2_dataset_instrument_description "The d15N values of individual AAs were measured using an isotope ratio mass spectrometer (IRMS) (Delta PlusXP, Delta V Plus or MAT 253) interfaced with a gas chromatograph (Trace GC) through a GC-C III combustion furnace (980 degrees C), reduction furnace (650 degrees C), and liquid-N cold trap.";
    String instruments_2_dataset_instrument_nid "679637";
    String instruments_2_description "Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB02/";
    String instruments_2_instrument_name "Gas Chromatograph";
    String instruments_2_instrument_nid "661";
    String instruments_2_supplied_name "gas chromatograph (Trace GC)";
    String instruments_3_acronym "Purse-seine";
    String instruments_3_dataset_instrument_description "Three species of tuna, yellowfin (Ta.; Thunnus albacares), skipjack (Kp.; Katsuwonus pelamis), and bigeye (To.; Thunnus obesus) tunas, were sampled year-round during 2003-2005 by observers of the Inter-American Tropical Tuna Commission onboard purse-seine fishing vessels.";
    String instruments_3_dataset_instrument_nid "679633";
    String instruments_3_description "A purse seine is a large wall of netting deployed in a circle around an entire school of fish. The seine has floats along the top line with a lead line of chain along the bottom. Once a school of fish is located, a skiff pulls the seine into the water as the vessel encircles the school with the net. A cable running along the bottom is then pulled in, \"pursing\" the net closed on the bottom, preventing fish from escaping by swimming downward. The catch is harvested by bringing the net alongside the vessel and brailing the fish aboard.";
    String instruments_3_instrument_name "Purse-seine Fishing Gear";
    String instruments_3_instrument_nid "675173";
    String instruments_3_supplied_name "purse-seine fishing";
    String instruments_4_acronym "Hand Net";
    String instruments_4_dataset_instrument_description "Specimens of mesopelagic myctophid fishes Myctophum nitidulum (Mn) and Symbolophorus reversus (Sr) were collected by dipnet at night.";
    String instruments_4_dataset_instrument_nid "682471";
    String instruments_4_description "A hand net (also called a scoop net or dip net) is a net or mesh basket held open by a hoop. They are used for scooping fish near the surface of the water.";
    String instruments_4_instrument_name "Hand Net";
    String instruments_4_instrument_nid "682469";
    String instruments_4_supplied_name "dipnet";
    String instruments_5_acronym "Handline and Jig";
    String instruments_5_dataset_instrument_description "Specimens of the squids Dosidicus gigas (Dg) and Sthenoteuthis oualaniensis (So) also were collected at night, using handlines and jigs.";
    String instruments_5_dataset_instrument_nid "682473";
    String instruments_5_description "Handline fishing, or handlining, is a fishing technique where a single fishing line is held in the hands. A handline is a relatively large diameter line that can be pulled by hand, and it has a jig attached at the end. Handlines are frequently used for catching fish or squid that are schooling near the surface, thus a long haul by hand is not necessary.";
    String instruments_5_instrument_name "Handline and Jig";
    String instruments_5_instrument_nid "682472";
    String instruments_5_supplied_name "handlines and jigs";
    String keywords "acid, alanine, Alanine_Avg, Alanine_SD, analyzed, arginine, Arginine_Avg, Arginine_SD, aspartic, AsparticAcid_Avg, AsparticAcid_SD, average, bco, bco-dmo, biological, chemical, data, dataset, date, dmo, erddap, glutamic, GlutamicAcid_Avg, GlutamicAcid_SD, glycine, Glycine_Avg, Glycine_SD, histidine, Histidine_Avg, Histidine_SD, isoleucine, Isoleucine_Avg, Isoleucine_SD, leucine, Leucine_Avg, Leucine_SD, lysine, Lysine_Avg, Lysine_SD, management, methionine, Methionine_Avg, Methionine_SD, number, oceanography, office, phenylalanine, Phenylalanine_Avg, Phenylalanine_SD, preliminary, proline, Proline_Avg, Proline_SD, sample, sample_number, serine, Serine_Avg, Serine_SD, species, threonine, Threonine_Avg, Threonine_SD, time, tyrosine, Tyrosine_Avg, Tyrosine_SD, valine, Valine_Avg, Valine_SD";
    String license "https://www.bco-dmo.org/dataset/679447/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/679447";
    String param_mapping "{'679447': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/679447/parameters";
    String people_0_affiliation "Inter-American Tropical Tuna Commission";
    String people_0_affiliation_acronym "IATTC";
    String people_0_person_name "Robert Olson";
    String people_0_person_nid "50553";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of Hawaii";
    String people_1_person_name "Brian N. Popp";
    String people_1_person_nid "51093";
    String people_1_role "Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "University of Hawaii";
    String people_2_person_name "Jeffrey C. Drazen";
    String people_2_person_nid "491313";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Inter-American Tropical Tuna Commission";
    String people_3_affiliation_acronym "IATTC";
    String people_3_person_name "Robert Olson";
    String people_3_person_nid "50553";
    String people_3_role "Contact";
    String people_3_role_type "related";
    String people_4_affiliation "Woods Hole Oceanographic Institution";
    String people_4_affiliation_acronym "WHOI BCO-DMO";
    String people_4_person_name "Shannon Rauch";
    String people_4_person_nid "51498";
    String people_4_role "BCO-DMO Data Manager";
    String people_4_role_type "related";
    String project "CAMEO_Trophic_Position";
    String projects_0_acronym "CAMEO_Trophic_Position";
    String projects_0_description 
"(From NSF Award Abstract)
Evidence increasingly demonstrates that selective removal of marine life can induce restructuring of marine food webs. Trophic structure is the central component of mass balance models, widely used tools to evaluate fisheries in an ecosystem context. Food web structure is commonly determined by stomach contents or by bulk tissue stable isotope analyses, both of which are limited in terms of resolution and versatility. The investigators will refine a tool, Amino Acid Compound-Specific Isotopic Analyses (AA-CSIA), which can be broadly applicable for quantifying the time-integrated trophic position (TP) of consumers. Differences in source and trophic nitrogen isotopic composition for specific amino acids will provide an unambiguous and integrated measure of fractional trophic TP across multiple phyla, regardless of an animal's physiological condition or of the biogeochemical cycling at the base of the food web. AA-CSIA will allow testing of the efficacy of trophic position estimates derived from ecosystem-based models and promote the evolution of these models into decision-support tools.
This project has three goals: 1. To validate the application of AA-CSIA across multiple marine phyla under differing physiological conditions. 2. To compare the application of AA-CSIA across systems with contrasting biogeochemical cycling regimes. 3. To develop the use of AA-CSIA TP estimates for validating trophic models of exploited ecosystems. The investigators will test and refine the approach using a combination of laboratory feeding experiments and field studies across regions with differing biogeochemical cycling regimes. They will determine the applicability of the AA-CSIA approach in a variety of marine organisms assessed in controlled studies. Subsequently, ecosystem components will be sampled from the eastern tropical Pacific, coastal California and the subtropical Pacific gyre. They will also test the effects of sample preservation on the isotopic composition of individual AA to determine whether the approach can be used on archived samples. This tool will allow testing of the efficacy of ecosystem-based models currently used to gain insight into the ecological effects of fisheries removals and improve the reliability of future models required to manage marine resources. In addition to the goal of developing AA-CSIA for use as a TP indicator, the information obtained through this project will provide important species-specific biological data on the feeding behavior of marine organisms that could have implications for their resilience to anthropogenic pressures and climate change.";
    String projects_0_end_date "2014-07";
    String projects_0_geolocation "Subtropical North Pacific Ocean";
    String projects_0_name "CAMEO 2009 - A novel tool for validating trophic position estimates in ecosystem-based fisheries models";
    String projects_0_project_nid "491309";
    String projects_0_project_website "http://cameo.noaa.gov/pres_bpopp.html";
    String projects_0_start_date "2010-08";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Amino acid compound-specific isotope analysis (AA-CSIA) of tissue samples from four distinct trophic groups across the food web in the pelagic eastern tropical Pacific Ocean; samples collected on NOAA cruises from July to December 2006.";
    String title "[AA-CSIA Olson] - Amino acid compound-specific isotope analysis (AA-CSIA) of tissue samples from four distinct trophic groups across the food web in the pelagic eastern tropical Pacific Ocean; samples collected on NOAA cruises from July to December 2006 (CAMEO 2009 - A novel tool for validating trophic position estimates in ecosystem-based fisheries models)";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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 Data Access Protocol (DAP) and its selection constraints.

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.

• (easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
• (easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
• (not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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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