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Dataset Title:  [Winam Gulf Metagenomic Time Series] - Metagenomic Time Series of Winam Gulf,
Lake Victoria from 2022-2023 (ASI Lake Victoria project) (IRES Track II:
Advanced studies institute on water quality and harmful algal blooms in Lake
Victoria)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_931936_v1)
Range: longitude = 34.03812 to 36.425°E, latitude = -0.7586 to -0.0623°N, depth = 0.25 to 1.0m
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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Things You Can Do With Your Graphs

Well, you can do anything you want with your graphs, of course. But some things you might not have considered are:

The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Library_ID {
    String long_name "Library_id";
    String units "unitless";
  }
  Site_Name {
    String long_name "Site_name";
    String units "unitless";
  }
  Replicate_id {
    String long_name "Replicate_id";
    String units "unitless";
  }
  SampleID {
    String long_name "Sampleid";
    String units "unitless";
  }
  StudyID {
    String long_name "Studyid";
    String units "unitless";
  }
  Sample_type {
    String long_name "Sample_type";
    String units "unitless";
  }
  Lake_or_river {
    String long_name "Lake_or_river";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float32 actual_range -0.7586, -0.0623;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float32 actual_range 34.03812, 36.425;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Collection_date {
    String long_name "Collection_date";
    String units "unitless";
  }
  Env_broad_scale {
    String long_name "Env_broad_scale";
    String units "unitless";
  }
  Site_depth {
    Float32 actual_range 0.61, 44.3;
    String long_name "Site_depth";
    String units "meters (m)";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float32 actual_range 0.25, 1.0;
    String axis "Z";
    String ioos_category "Location";
    String long_name "Sampling_depth";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  Preservation {
    String long_name "Preservation";
    String units "unitless";
  }
  Filter_size {
    Float32 actual_range 0.2, 0.2;
    String long_name "Filter_size";
    String units "um";
  }
  pH {
    Float32 actual_range 6.7, 9.0;
    String long_name "Ph";
    String units "unitless";
  }
  Temp {
    Float32 actual_range 24.8, 29.7;
    String long_name "Temp";
    String units "degrees C";
  }
  Nitrate {
    Float32 actual_range 0.8406, 1320.0;
    String long_name "Nitrate";
    String units "ug / L";
  }
  Diss_oxygen {
    Float32 actual_range 4.26, 11.6;
    String long_name "Diss_oxygen";
    String units "mg / L";
  }
  Conductivity {
    Float32 actual_range 85.0, 180.0;
    String long_name "Conductivity";
    String units "uS / cm";
  }
  Secchi {
    Float32 actual_range 0.35, 2.5;
    String long_name "Secchi";
    String units "meters";
  }
  Turbidity {
    Float32 actual_range 5.0, 48.1;
    String long_name "Turbidity";
    String units "NTU";
  }
  Microcystin {
    Float32 actual_range 0.03, 1.34;
    String long_name "Microcystin";
    String units "ug / L";
  }
  TN_TP_ratio {
    Float32 actual_range 3.603306, 35.52465;
    String long_name "Tn_tp_ratio";
    String units "unitless";
  }
  Chlorophyll_a {
    Float32 actual_range 24.61, 151.07;
    String long_name "Chlorophyll_a";
    String units "ug / L";
  }
  Total_phosphorus {
    Float32 actual_range 39.55, 303.0;
    String long_name "Total_phosphorus";
    String units "ug / L";
  }
  Dissolved_phosphorus {
    Float32 actual_range 0.43358, 2309.743;
    String long_name "Dissolved_phosphorus";
    String units "ug / L";
  }
  Soluble_reactive_phosphorus {
    Float32 actual_range 4.1525, 85.4;
    String long_name "Soluble_reactive_phosphorus";
    String units "ug / L";
  }
  Ammonia {
    Float32 actual_range 3.49976, 355.0994;
    String long_name "Ammonia";
    String units "ug / L";
  }
  Nitrate_Nitrite {
    Float32 actual_range 0.067, 22.229;
    String long_name "Nitrate_nitrite";
    String units "umol / L";
  }
  Nitrite {
    Float32 actual_range 0.007, 1.09;
    String long_name "Nitrite";
    String units "umol / L";
  }
  Silicate {
    Float32 actual_range 20.096, 1090.099;
    String long_name "Silicate";
    String units "umol / L";
  }
  Total_nitrogen {
    Int32 actual_range 265, 3500;
    String long_name "Total_nitrogen";
    String units "umol / L";
  }
  Total_dissolved_nitrogen {
    Float32 actual_range 204.75, 2335.0;
    String long_name "Total_dissolved_nitrogen";
    String units "ug / L";
  }
  Weather {
    String long_name "Weather";
    String units "unitless";
  }
  Wave_height {
    Float32 actual_range 0.0, 0.5;
    String long_name "Wave_height";
    String units "meters";
  }
  Wind_speed {
    Float32 actual_range 0.0, 7.0;
    String long_name "Wind_speed";
    String units "knots";
  }
  Salinity {
    Float32 actual_range 0.04, 0.08;
    String long_name "Salinity";
    String units "g / kg";
  }
  Atmospheric_temperature {
    Float32 actual_range 18.0, 28.0;
    String long_name "Atmospheric_temperature";
    String units "degrees C";
  }
  Particulate_cylindrospermopsin {
    Float32 actual_range 2.312, 2.312;
    String long_name "Particulate_cylindrospermopsin";
    String units "ng / mL";
  }
  ORP {
    Float32 actual_range -168.3, 516.0;
    String long_name "Orp";
    String units "mV";
  }
  Algal_Torch_cyano_sonde {
    Int32 actual_range 1300000, 249000000;
    String long_name "Algal_torch_cyano_sonde";
    String units "cells / L";
  }
  Algal_Torch_sonde_total_cells {
    Int32 actual_range 4940000, 375000000;
    String long_name "Algal_torch_sonde_total_cells";
    String units "cells / L";
  }
  Algal_Torch_percentage_cells_cyano {
    Float32 actual_range 2.954545, 88.96247;
    String long_name "Algal_torch_percentage_cells_cyano";
    String units "unitless";
  }
  Site_Description {
    String long_name "Site_description";
    String units "unitless";
  }
  Station_observations {
    String long_name "Station_observations";
    String units "unitless";
  }
  Site_Classification {
    String long_name "Site_classification";
    String units "unitless";
  }
  Notes {
    String long_name "Notes";
    String units "unitless";
  }
 }
  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.931936.1";
    Float64 Easternmost_Easting 36.425;
    Float64 geospatial_lat_max -0.0623;
    Float64 geospatial_lat_min -0.7586;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 36.425;
    Float64 geospatial_lon_min 34.03812;
    String geospatial_lon_units "degrees_east";
    Float64 geospatial_vertical_max 1.0;
    Float64 geospatial_vertical_min 0.25;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2024-09-21T05:57:02Z (local files)
2024-09-21T05:57:02Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_931936_v1.das";
    String infoUrl "https://www.bco-dmo.org/dataset/931936";
    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 -0.0623;
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -0.7586;
    String summary 
"Compared to the other \"Great Lakes\" (Laurentian Great Lakes of North America and Lake Baikal of Russia) the African Great Lakes have remained widely unstudied. This serves as a substantial research gap within the limnological literature given the African Great Lakes contribute approximately 25% of all global, accessible freshwater.  Lake Victoria of the African Great Lakes is notable for its large size - serving as the second largest freshwater lake in the world by surface area. Yet, Lake Victoria is also known for the prolific year-long cyanobacterial blooms that occur throughout her waters such as the Winam Gulf. These blooms are fueled by intense agricultural and anthropogenic development much like other freshwater harmful algal blooms. However, unlike other freshwater blooms such as those occurring in Lake Erie and Lake Taihhu - these cyanobacterial blooms have remained widely uncharacterized (especially using molecular techniques). 

The central study area is the Winam Gulf of Lake Victoria, Kenya. This is a relatively shallow, hypereutrophic system that has various rivers serving as nutrient loading sources (such as the Sondu River). This dataset also contains opportunistic samples collected from a variety of riverine systems and Lakes Simbi and Naivasha. 

Here, we present the biological, chemical and physical data corresponding to a two year metagenomic time series of the Winam Gulf, Lake Victoria. We further present the physiochemical data of eight outgroup samples including adjacent riverine systems and Lakes Simbi and Naivasha.";
    String title "[Winam Gulf Metagenomic Time Series] - Metagenomic Time Series of Winam Gulf, Lake Victoria from 2022-2023 (ASI Lake Victoria project) (IRES Track II: Advanced studies institute on water quality and harmful algal blooms in Lake Victoria)";
    Float64 Westernmost_Easting 34.03812;
  }
}

 

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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