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Dataset Title:  Physical description of marine lakes: surface area, distance to ocean, tidal
efficiency, depth, and stratification
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_768110)
Information:  Summary ? | License ? | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 lake (unitless) ?          "Big Crocodile Lake"    "Ulong Lake"
 lake_code (unitless) ?          "BCM"    "ULU"
 volume_m3 (meters^3) ?          12038    1458890
 surface_area_m2 (meters^2) ?          980    79636
 distance_to_ocean_min_m (meters) ?          24    501
 distance_to_ocean_mean_m (meters) ?          48    542
 distance_to_ocean_median_m (meters) ?          52    540
 tidal_lag_time_minutes (minutes) ?          0    190
 tidal_efficiency (unitless) ?          0.17    0.99
 mean_transect_length_m (meters) ?          1.167925    49.855
 depth (Max Actual Depth M, m) ?          0.91    22.56
  < slider >
 perimeter_m (meters) ?          118.6785825    1898.121669
 habitable_surface_area_cylinder (meters^2) ?          352.2554619    68121.25011
 habitable_surface_area_frustum (meters^2) ?          316.1651968    61157.96127
 stratified (unitless) ?          0    1
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")

File type: (more info)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  lake {
    String bcodmo_name "site";
    String description "common name for lake";
    String long_name "Lake";
    String units "unitless";
  }
  lake_code {
    String bcodmo_name "site";
    String description "3-letter code for sampled lake name";
    String long_name "Lake Code";
    String units "unitless";
  }
  volume_m3 {
    Int32 _FillValue 2147483647;
    Int32 actual_range 12038, 1458890;
    String bcodmo_name "volume";
    String description "estimated volume of the lake (m3)";
    String long_name "Volume M3";
    String units "meters^3";
  }
  surface_area_m2 {
    Int32 _FillValue 2147483647;
    Int32 actual_range 980, 79636;
    String bcodmo_name "surface_area";
    String description "Surface area of the lake  (m2).";
    String long_name "Surface Area M2";
    String units "meters^2";
  }
  distance_to_ocean_min_m {
    Int16 _FillValue 32767;
    Int16 actual_range 24, 501;
    String bcodmo_name "unknown";
    String description "Minimum distance from a lake’s edge to the surrounding lagoon (m)";
    String long_name "Distance To Ocean Min M";
    String units "meters";
  }
  distance_to_ocean_mean_m {
    Int16 _FillValue 32767;
    Int16 actual_range 48, 542;
    String bcodmo_name "unknown";
    String description "Mean distance from a lake’s edge to the surrounding lagoon (m).";
    String long_name "Distance To Ocean Mean M";
    String units "meters";
  }
  distance_to_ocean_median_m {
    Int16 _FillValue 32767;
    Int16 actual_range 52, 540;
    String bcodmo_name "unknown";
    String description "Median distance from a lake’s edge to the surrounding lagoon (m).";
    String long_name "Distance To Ocean Median M";
    String units "meters";
  }
  tidal_lag_time_minutes {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 190;
    String bcodmo_name "unknown";
    String description "the time between high tide in the adjacent ocean and high tide in the lake";
    String long_name "Tidal Lag Time Minutes";
    String units "minutes";
  }
  tidal_efficiency {
    Float32 _FillValue NaN;
    Float32 actual_range 0.17, 0.99;
    String bcodmo_name "unknown";
    String description "the ratio between amplitude of ocean tide and lake tide.";
    String long_name "Tidal Efficiency";
    String units "unitless";
  }
  mean_transect_length_m {
    Float64 _FillValue NaN;
    Float64 actual_range 1.167925, 49.855;
    String bcodmo_name "len_track";
    String description "average of distance_trans for the lake from https://www.bco-dmo.org/dataset/541181";
    String long_name "Mean Transect Length M";
    String units "meters";
  }
  depth {
    String _CoordinateAxisType "Height";
    String _CoordinateZisPositive "down";
    Float64 _FillValue NaN;
    Float64 actual_range 0.91, 22.56;
    String axis "Z";
    String bcodmo_name "depth";
    String description "maximum depth_m for the lake from https://www.bco-dmo.org/dataset/541181";
    String ioos_category "Location";
    String long_name "Max Actual Depth M";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String positive "down";
    String standard_name "depth";
    String units "m";
  }
  perimeter_m {
    Float64 _FillValue NaN;
    Float64 actual_range 118.6785825, 1898.121669;
    String bcodmo_name "unknown";
    String description "circumference of lake (m).";
    String long_name "Perimeter M";
    String units "meters";
  }
  habitable_surface_area_cylinder {
    Float64 _FillValue NaN;
    Float64 actual_range 352.2554619, 68121.25011;
    String bcodmo_name "surface_area";
    String description "An estimate of the area of the benthic zone above the chemocline; based on the model of lake shape as a cylinder.";
    String long_name "Habitable Surface Area Cylinder";
    String units "meters^2";
  }
  habitable_surface_area_frustum {
    Float64 _FillValue NaN;
    Float64 actual_range 316.1651968, 61157.96127;
    String bcodmo_name "surface_area";
    String description "An estimate of the area of the benthic zone above the chemocline; based on the model of lake shape as a truncated cone.";
    String long_name "Habitable Surface Area Frustum";
    String units "meters^2";
  }
  stratified {
    Byte _FillValue 127;
    Byte actual_range 0, 1;
    String bcodmo_name "unknown";
    String description "whether a lake is vertically stratified (1) or holomictic (0)";
    String long_name "Stratified";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Lake Bathymetry Mapping
 
The bathymetry of the lakes was recorded with a purpose-built lightweight,
low-power echosounder unit with integrated GPS and AHRS (attitude and heading
reference system), towed behind a kayak. (Data courtesy of Herwig Stibor,
Thomas Stieglitz.)
 
Lake Bathymetry Analysis
 
Raw bathymetry data were down-sampled to include one sample every 2\\u00a0m
distance along the survey track. Data were visually inspected and false
soundings removed. In some lakes, GPS reception was partially compromised
along the steep shorelines. Where required to not compromise data density, the
survey track was reconstructed from field notes and AHRS data (less than 5% of
data where applicable). During the bathymetry surveys, tidal water level was
not recorded. Therefore, tidal water level variations were corrected for by
modeling tidal water level in each lake. The water level for each lake was
correlated with tidal water level measured at a reference station at CRRF or
predicted tide (x-tide database), by determining tidal lag time and tidal
efficiency (see below) from data previously collected concurrently in the
respective lake and at this reference station. Subsequently, bathymetry data
was reduced to a grid with 2m resolution by kriging of a further down-sampled
subset of data using every third data point. Lake-specific variograms were
applied, and contour lines and total lake volumes were calculated in a GIS.
(Data courtesy of Thomas Stieglitz.)
 
Distance from lake to ocean & lake surface area
 
Lake shorelines and island coastlines were manually extracted from satellite
data (Microsoft Bing). The nearest, mean and median distance of each lake to
the respective island\\u2019s coastline as well as lake surface area was
calculated in a GIS. The perimeter was measured in meters using the
\\u2018Measure Line\\u2019 tool in QGIS 3.4.
 
Habitable surface area for benthic organisms was estimated either as (1) a
multiple of the perimeter and depth of the chemocline, i.e. assuming a
cylindrical model for the lake, or (2) as the area of a frustum, i.e. a
truncated cone, using the perimeter of the lake at the surface, the average
length of transects, and the average angle of the transect from the vertical
(estimated using the sine of maximum depth / transect length).
 
Tidal lag time and tidal efficiency were calculated from concurrently measured
tidal water level in a lake and the adjacent ocean. The tidal lag time \\u2014
the time between high tide in the adjacent ocean and high tide in the lake
\\u2014 was determined by least-square fit between lake and ocean tide measured
using HOBO 30-foot depth Titanium water level data loggers (Part #
U20-001-01-Ti).\\u00a0 Tidal efficiency was calculated as the ratio between
amplitude of ocean tide and lake tide (e.g. Ayers, JF and Vacher, HL,
1986.\\u00a0 Hydrogeology of an Atoll Island: A Conceptual Model from a
Detailed Study of a Micronesian Example. Groundwater 24(2) 185-198.). Larger
tidal lag time and smaller tidal efficiency respectively indicate a less
efficient hydrological connection between ocean and lake.
 
Error-checking: Estimates of basic dimensions (depth, distance, length,
surface area) were double-checked manually for a subset of measurements by a
second person using using Google Earth.\\u00a0";
    String awards_0_award_nid "55103";
    String awards_0_award_number "OCE-1241255";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1241255";
    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 
"Lake physical 
   Palau marine lake physical descriptions 
   M. Dawson (UC-Merced) 
   version date: 2019-05-13";
    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 "2019-05-16T12:47:21Z";
    String date_modified "2019-07-08T12:59:48Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.768110.1";
    Float64 geospatial_vertical_max 22.56;
    Float64 geospatial_vertical_min 0.91;
    String geospatial_vertical_positive "down";
    String geospatial_vertical_units "m";
    String history 
"2021-12-05T02:23:50Z (local files)
2021-12-05T02:23:50Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_768110.html";
    String infoUrl "https://www.bco-dmo.org/dataset/768110";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_description "Used to determine tidal lag time, the time between high tide in the adjacent ocean and high tide in the lake.";
    String instruments_0_dataset_instrument_nid "768137";
    String instruments_0_description "Electronic devices that record data over time or in relation to location either with a built-in instrument or sensor or via external instruments and sensors.";
    String instruments_0_instrument_name "Data Logger";
    String instruments_0_instrument_nid "731353";
    String instruments_0_supplied_name "HOBO 30-foot depth Titanium water level data loggers (Part # U20-001-01-Ti)";
    String keywords "actual, area, bco, bco-dmo, biological, chemical, code, cylinder, data, dataset, depth, distance, distance_to_ocean_mean_m, distance_to_ocean_median_m, distance_to_ocean_min_m, dmo, efficiency, erddap, frustum, habitable, habitable_surface_area_cylinder, habitable_surface_area_frustum, lag, lake, lake_code, length, management, max, max_actual_depth_m, mean, mean_transect_length_m, median, min, minutes, ocean, oceanography, office, perimeter, perimeter_m, preliminary, stratified, surface, surface_area_m2, tidal, tidal_efficiency, tidal_lag_time_minutes, time, transect, volume, volume_m3";
    String license "https://www.bco-dmo.org/dataset/768110/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/768110";
    String param_mapping "{'768110': {'max_actual_depth_m': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/768110/parameters";
    String people_0_affiliation "University of California-Merced";
    String people_0_affiliation_acronym "UC Merced";
    String people_0_person_name "Michael N Dawson";
    String people_0_person_nid "51577";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Woods Hole Oceanographic Institution";
    String people_1_affiliation_acronym "WHOI BCO-DMO";
    String people_1_person_name "Nancy Copley";
    String people_1_person_nid "50396";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "PaPaPro";
    String projects_0_acronym "PaPaPro";
    String projects_0_description 
"This project will survey the taxonomic, genetic, and functional diversity of the organisms found in marine lakes, and investigate the processes that cause gains and losses in this biodiversity. Marine lakes formed as melting ice sheets raised sea level after the last glacial maximum and flooded hundreds of inland valleys around the world. Inoculated with marine life from the surrounding sea and then isolated to varying degrees for the next 6,000 to 15,000 years, these marine lakes provide multiple, independent examples of how environments and interactions between species can drive extinction and speciation. Researchers will survey the microbes, algae, invertebrates, and fishes present in 40 marine lakes in Palau and Papua, and study how diversity has changed over time by retrieving the remains of organisms preserved in sediments on the lake bottoms. The project will test whether the number of species, the diversity of functional roles played by organisms, and the genetic diversity within species increase and decrease in parallel; whether certain species can greatly curtail diversity by changing the environment; whether the size of a lake determines its biodiversity; and whether the processes that control diversity in marine organisms are similar to those that operate on land.
Because biodiversity underlies the ecosystem services on which society depends, society has a great interest in understanding the processes that generate and retain biodiversity in nature. This project will also help conserve areas of economic importance. Marine lakes in the study region are important for tourism, and researchers will work closely with governmental and non-governmental conservation and education groups and with diving and tourism businesses to raise awareness of the value and threats to marine lakes in Indonesia and Palau.";
    String projects_0_end_date "2017-12";
    String projects_0_geolocation "Western Pacific; Palau; Indonesia (West Papua)";
    String projects_0_name "Do Parallel Patterns Arise from Parallel Processes?";
    String projects_0_project_nid "2238";
    String projects_0_project_website "http://marinelakes.ucmerced.edu/";
    String projects_0_start_date "2013-01";
    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 "Physical description of marine lakes including surface area, distance to ocean, tidal efficiency, depth, and stratification.";
    String title "Physical description of marine lakes: surface area, distance to ocean, tidal efficiency, depth, and stratification";
    String version "1";
    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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