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Dataset Title:  [Juvenile Black sea bass winter growth and lipid accumulation under varying
food and temperature conditions - Experiment 1] - Winter growth and lipid
accumulation in juvenile Black sea bass exposed to varying food and temperature
conditions during lab experiments conducted from September 2021 to April 2022
at UConn Avery Point (Collaborative research: Understanding the effects of
acidification and hypoxia within and across generations in a coastal marine
fish)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_897895_v1)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 Collection_site (unitless) ?          "Mumford Cove"    "Mumford Cove"
 longitude (degrees_east) ?          -72.00195    -72.00195
  < slider >
 latitude (degrees_north) ?          41.32361    41.32361
  < slider >
 Collection_date (unitless) ?          "2021-09-21"    "2021-09-21"
 Sample_date (unitless) ?          "2021-11-05"    "2022-02-11"
 Species (unitless) ?          "Centropristis stri..."    "Centropristis stri..."
 BSB_ID (unitless) ?          "1A"    "H9"
 Group (unitless) ?          "Baseline"    "Experiment 1"
 Temp (degree Celsius) ?          6    19
 Days_W (number of days) ?          42    78
 DD_W (degree-days (°C × days)) ?          468    756
 DD_all (degree-days (°C × days)) ?          777    950
 S_or_M (unitless) ?          "S"    "S"
 wW_ini (grams (g)) ?          3    8
 wW_final (grams (g)) ?          3.9    12.9
 dW_final_g (grams (g)) ?          0.943    3.774
 estdW_ini (grams (g)) ?          0.761    1.995
 DdW (grams (g)) ?          -0.534    1.64
 TL_ini (millimeters (mm)) ?          60    79
 TL_final (millimeters (mm)) ?          62    101
 GR (millimeters per day (mm/d)) ?          -0.01    0.44
 SGR (percent (%) per day) ?          -0.3    1.53
 Cons (percent body wet weight (% body wW)) ?          1.36    7.99
 GE (percent (%)) ?          -14.55    35.54
 dW_final_mg (milligrams (mg)) ?          943    3774
 Lipid (milligrams (mg)) ?          45.4    628.6
 Lean (milligrams (mg)) ?          701.6    3331.3
 Ash (milligrams (mg)) ?          166.0    670.4
 Prop_Lipid (percent (%)) ?          3.9    21.3
 Prop_Lean (percent (%)) ?          62.0    76.2
 Prop_Ash (percent (%)) ?          12.6    22.2
 
Server-side Functions ?
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Collection_site {
    String long_name "Collection_site";
    String units "unitless";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range -72.00195, -72.00195;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range 41.32361, 41.32361;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  Collection_date {
    String long_name "Collection_date";
    String units "unitless";
  }
  Sample_date {
    String long_name "Sample_date";
    String units "unitless";
  }
  Species {
    String long_name "Species";
    String units "unitless";
  }
  BSB_ID {
    String long_name "Bsb_id";
    String units "unitless";
  }
  Group {
    String long_name "Group";
    String units "unitless";
  }
  Temp {
    Int32 actual_range 6, 19;
    String long_name "Temp";
    String units "degree Celsius";
  }
  Days_W {
    Int32 actual_range 42, 78;
    String long_name "Days_w";
    String units "number of days";
  }
  DD_W {
    Int32 actual_range 468, 756;
    String long_name "Dd_w";
    String units "degree-days (°C × days)";
  }
  DD_all {
    Int32 actual_range 777, 950;
    String long_name "Dd_all";
    String units "degree-days (°C × days)";
  }
  S_or_M {
    String long_name "S_or_m";
    String units "unitless";
  }
  wW_ini {
    Int32 actual_range 3, 8;
    String long_name "Ww_ini";
    String units "grams (g)";
  }
  wW_final {
    Float32 actual_range 3.9, 12.9;
    String long_name "Ww_final";
    String units "grams (g)";
  }
  dW_final_g {
    Float32 actual_range 0.943, 3.774;
    String long_name "Dw_final_g";
    String units "grams (g)";
  }
  estdW_ini {
    Float32 actual_range 0.761, 1.995;
    String long_name "Estdw_ini";
    String units "grams (g)";
  }
  DdW {
    Float32 actual_range -0.534, 1.64;
    String long_name "Ddw";
    String units "grams (g)";
  }
  TL_ini {
    Int32 actual_range 60, 79;
    String long_name "Tl_ini";
    String units "millimeters (mm)";
  }
  TL_final {
    Int32 actual_range 62, 101;
    String long_name "Tl_final";
    String units "millimeters (mm)";
  }
  GR {
    Float32 actual_range -0.01, 0.44;
    String long_name "Gr";
    String units "millimeters per day (mm/d)";
  }
  SGR {
    Float32 actual_range -0.3, 1.53;
    String long_name "Sgr";
    String units "percent (%) per day";
  }
  Cons {
    Float32 actual_range 1.36, 7.99;
    String long_name "Cons";
    String units "percent body wet weight (% body wW)";
  }
  GE {
    Float32 actual_range -14.55, 35.54;
    String long_name "Ge";
    String units "percent (%)";
  }
  dW_final_mg {
    Int32 actual_range 943, 3774;
    String long_name "Dw_final_mg";
    String units "milligrams (mg)";
  }
  Lipid {
    Float32 actual_range 45.4, 628.6;
    String long_name "Lipid";
    String units "milligrams (mg)";
  }
  Lean {
    Float32 actual_range 701.6, 3331.3;
    String long_name "Lean";
    String units "milligrams (mg)";
  }
  Ash {
    Float32 actual_range 166.0, 670.4;
    String long_name "Ash";
    String units "milligrams (mg)";
  }
  Prop_Lipid {
    Float32 actual_range 3.9, 21.3;
    String long_name "Prop_lipid";
    String units "percent (%)";
  }
  Prop_Lean {
    Float32 actual_range 62.0, 76.2;
    String long_name "Prop_lean";
    String units "percent (%)";
  }
  Prop_Ash {
    Float32 actual_range 12.6, 22.2;
    String long_name "Prop_ash";
    String units "percent (%)";
  }
 }
  NC_GLOBAL {
    String cdm_data_type "Other";
    String Conventions "COARDS, CF-1.6, ACDD-1.3";
    String creator_email "info@bco-dmo.org";
    String creator_name "BCO-DMO";
    String creator_url "https://www.bco-dmo.org/";
    String doi "10.26008/1912/bco-dmo.897895.1";
    Float64 Easternmost_Easting -72.00195;
    Float64 geospatial_lat_max 41.32361;
    Float64 geospatial_lat_min 41.32361;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -72.00195;
    Float64 geospatial_lon_min -72.00195;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T06:10:26Z (local files)
2024-11-08T06:10:26Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_897895_v1.html";
    String infoUrl "https://www.bco-dmo.org/dataset/897895";
    String institution "BCO-DMO";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    Float64 Northernmost_Northing 41.32361;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 41.32361;
    String summary 
"The northern stock of Black sea bass (BSB, Centropristis striata) has greatly expanded over the past decade, potentially due to warming Northwest Atlantic shelf waters affecting overwintering especially in juveniles. To gather better empirical data we quantified winter growth and lipid accumulation in BSB juveniles from Long Island Sound using two complementing experiments. The data from Experiment 1 are presented here.

Experiment 1 measured individual length growth (GR), weight-specific growth (SGR), growth efficiency, and lipid content at constant food and three static temperatures: 6°, 12°, and 19° Celsius (C). Average GR (SGR) decreased from 0.24 millimeters per day (mm d-1) at 19°C (0.89% d-1) to 0.15 mm d-1 at 12°C (0.54% d-1) to 0.04 mm d-1 at 6°C (0.17% d-1). Even at the coldest temperature, most juveniles sustained positive GRs and SGRs; hence, the species' true thermal growth minimum may be below 6°C. However, lipid accumulation was greatest at 12°C, which is close to what overwintering juveniles likely encounter offshore.

The data from Experiment 2 are presented in a related dataset (https://www.bco-dmo.org/dataset/898012). In both experiments, juveniles disproportionally accumulated lipid over lean mass, with lipid proportions tripling in Exp2 from 4% at 65 mm to 12% at 120 mm.";
    String title "[Juvenile Black sea bass winter growth and lipid accumulation under varying food and temperature conditions - Experiment 1] - Winter growth and lipid accumulation in juvenile Black sea bass exposed to varying food and temperature conditions during lab experiments conducted from September 2021 to April 2022 at UConn Avery Point (Collaborative research: Understanding the effects of acidification and hypoxia within and across generations in a coastal marine fish)";
    Float64 Westernmost_Easting -72.00195;
  }
}

 

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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