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Dataset Title:  Sea urchin biomass at central and western Aleutian Islands, Alaska from visual
surveys, July 2014
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_755155)
Range: longitude = 173.2486 to 179.35628°E, latitude = 51.40283 to 52.9441°N, time = 2014-07-04 to 2014-07-17
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Subset | 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 {
  island {
    String bcodmo_name "site";
    String description "name of island";
    String long_name "Island";
    String units "unitless";
  site_name {
    Byte _FillValue 127;
    Byte actual_range 1, 46;
    String bcodmo_name "site";
    String description "identity of site";
    String long_name "Site Name";
    String units "unitless";
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 51.40283, 52.9441;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude of study site";
    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 173.2486, 179.35628;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude of study site";
    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";
  depth_feet {
    Float64 _FillValue NaN;
    Float64 actual_range 20.0, 20.0;
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth of benthic survey";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String standard_name "depth";
    String units "feet";
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.404432e+9, 1.4055552e+9;
    String axis "T";
    String bcodmo_name "date";
    String description "calendar date of survey formatted as yyyy-mm-dd";
    String ioos_category "Time";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "date";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String time_precision "1970-01-01";
    String units "seconds since 1970-01-01T00:00:00Z";
  observer {
    String bcodmo_name "person";
    String description "last name of observer";
    String long_name "Observer";
    String units "unitless";
  quadrat_count {
    Byte _FillValue 127;
    Byte actual_range 4, 20;
    String bcodmo_name "num_reps";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "number of 0.25-m^2 quadrats from which estimates were derived";
    String long_name "Quadrat Count";
    String units "quadrats";
  urchin_diameter_mm {
    Byte _FillValue 127;
    Byte actual_range 4, 88;
    String bcodmo_name "diameter";
    String description "diameter of urchin test (body)";
    String long_name "Urchin Diameter Mm";
    String units "millimeters";
  urchin_frequency {
    Byte _FillValue 127;
    Byte actual_range 1, 45;
    String bcodmo_name "count";
    String description "number of urchins collected within a size class";
    String long_name "Urchin Frequency";
    String units "urchins";
  size_biomass_convert {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0245, 254.47224;
    String bcodmo_name "biomass";
    String description "urchin biomass; calculated using known size to dry weight relationship: =EXP(-7.857+(2.992*LN(urchin diameter)))";
    String long_name "Size Biomass Convert";
    String units "grams";
  sum_biomass_class {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0245, 1668.11099;
    String bcodmo_name "biomass";
    String description "total biomass of all urchins collected within a given size class";
    String long_name "Sum Biomass Class";
    String units "grams";
  urchin_biomass_grams {
    Float32 _FillValue NaN;
    Float32 actual_range 0.002, 87.289;
    String bcodmo_name "biomass";
    String description "urchin biomass per 0.25 m^2 per size class; calculated by dividing \"sum.biomass.class\" by \"quadrat.count\"";
    String long_name "Urchin Biomass Grams";
    String units "grams";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"We characterized the ecological status of each island by quantifying the
density, size frequency distribution, and biomass of the sea urchin community
(primarily Strongylocentrotus polyacanthus) at randomly selected sites, using
the same methods that have been employed by us and others over the past 30
years (Estes et al. 2010). Originally, we identified potential study sites by
laying a grid over a map of each island, marking every place a grid line
intersected the coast; these marks were later assigned GPS waypoints. During
the 2014 research cruise, we randomly selected and resampled six sites per
island, or in the Semichi Islands (Alaid, Nizki, and Shemya)\\u2014island
group\\u2014as this level of sampling is sufficient to determine the ecological
status of an island (Estes et al. 2010). We performed identical community
surveys at the sites we studied with respect to algal reef bioerosion (see
associated metadata forms and datasets).
At each site, a diver placed a 0.25-m^2 quadrat at 20 feet depth and counted
all urchins within the quadrat, then collected the urchins in a bag. The diver
then took a random number of kicks along the same depth contour and repeated
this process until 20 quadrats were sampled or 200 urchins were collected,
whichever occurred first. If 200 urchins were collected quickly, additional
density counts were made to yield a better density estimate (n = 4 minimum).
Shipside, we measured the size (test diameter; mm) of each collected urchin
with calipers. We then calculated its biomass using a known size-weight
relationship (Estes et al. 2010). To estimate total urchin biomass for a site
(grams per 0.25-m^2), we summed the biomass of all urchins collected at the
site and divided that sum by the number of quadrats deployed.";
    String awards_0_award_nid "526658";
    String awards_0_award_number "PLR-1316141";
    String awards_0_data_url "http://nsf.gov/awardsearch/showAward?AWD_ID=1316141";
    String awards_0_funder_name "NSF Arctic Sciences";
    String awards_0_funding_acronym "NSF ARC";
    String awards_0_funding_source_nid "390";
    String awards_0_program_manager "Henrietta N Edmonds";
    String awards_0_program_manager_nid "51517";
    String cdm_data_type "Other";
    String comment 
   Aleutian Islands, AK, July 2014 
   PI's: R. Steneck (UME), J. Estes (UCSCD) 
   version: 2019-01-30";
    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 "2019-02-06T20:40:34Z";
    String date_modified "2019-02-25T18:49:37Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.755155.1";
    Float64 Easternmost_Easting 179.35628;
    Float64 geospatial_lat_max 52.9441;
    Float64 geospatial_lat_min 51.40283;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.35628;
    Float64 geospatial_lon_min 173.2486;
    String geospatial_lon_units "degrees_east";
    String history 
"2023-06-06T23:51:52Z (local files)
2023-06-06T23:51:52Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_755155.das";
    String infoUrl "https://www.bco-dmo.org/dataset/755155";
    String institution "BCO-DMO";
    String keywords "array, array-data, bco, bco-dmo, biological, biomass, chemical, class, comprehensive, convert, count, data, dataset, date, depth, depth_feet, diameter, dmo, erddap, frequency, grams, island, large, latitude, longitude, management, name, observer, oceanography, office, preliminary, quadrat, quadrat_count, site, site_name, size, size_biomass_convert, stewardship, sum, sum_biomass_class, system, time, urchin, urchin_biomass_grams, urchin_diameter_mm, urchin_frequency";
    String license "https://www.bco-dmo.org/dataset/755155/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/755155";
    Float64 Northernmost_Northing 52.9441;
    String param_mapping "{'755155': {'date': 'flag - time', 'depth_feet': 'flag - depth', 'longitude': 'flag - longitude', 'latitude': 'flag - latitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/755155/parameters";
    String people_0_affiliation "University of Maine";
    String people_0_affiliation_acronym "U Maine DMC";
    String people_0_person_name "Robert  S. Steneck";
    String people_0_person_nid "526659";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Cruz";
    String people_1_affiliation_acronym "UC Santa Cruz";
    String people_1_person_name "James Estes";
    String people_1_person_nid "51389";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Bigelow Laboratory for Ocean Sciences";
    String people_2_person_name "Douglas B. Rasher";
    String people_2_person_nid "480721";
    String people_2_role "Co-Principal Investigator";
    String people_2_role_type "originator";
    String people_3_affiliation "Woods Hole Oceanographic Institution";
    String people_3_affiliation_acronym "WHOI BCO-DMO";
    String people_3_person_name "Nancy Copley";
    String people_3_person_nid "50396";
    String people_3_role "BCO-DMO Data Manager";
    String people_3_role_type "related";
    String project "OA Kelp Forest Function";
    String projects_0_acronym "OA Kelp Forest Function";
    String projects_0_description 
"Extracted from the NSF award abstract:
Marine calcifying organisms are most at risk to rapid ocean acidification (OA) in cold-water ecosystems. The investigators propose to determine if a globally unique and widespread calcareous alga in Alaska's Aleutian archipelago, Clathromorphum nereostratum, is threatened with extinction due to the combined effects of OA and food web alterations. C. nereostratum is a slow growing coralline alga that can live to at least 2000 years. It accretes massive 'bioherms' that dominate the regions' rocky substrate both under kelp forests and deforested sea urchin barrens. It develops growth bands (similar to tree rings) in its calcareous skeleton, which effectively record its annual calcification rate over centuries. Pilot data suggest the skeletal density of C. nereostratum began to decline precipitously in the 1990's in some parts of the Aleutian archipelago. The investigators now propose to use high-resolution microscopy and microCT imaging to examine how the growth and skeletal density of C. nereostratum has changed in the past 300 years (i.e., since the industrial revolution) across the western Aleutians. They will compare their records of algal skeletal densities and their variation through time with reconstructions of past climate to infer causes of change. In addition, the investigators will examine whether the alga's defense against grazing by sea urchins is compromised by ongoing ocean acidification. The investigators will survey the extent of C. nereostratum bioerosion occurring at 10 sites spanning the western Aleutians, both inside and outside of kelp forests. At each site they will compare these patterns to observed and monitored ecosystem trophic structure and recent C. nereostratum calcification rates. Field observations will be combined with laboratory experiments to determine if it is a decline in the alga's skeletal density (due to recent OA and warming), an increase in grazing intensity (due to recent trophic-level dysfunction), or their interactive effects that are likely responsible for bioerosion patterns inside vs. outside of forests. By sampling C. nereostratum inside and outside of forests, they will determine if kelp forests locally increase pH via photosynthesis, and thus buffer the effects of OA on coralline calcification. The combination of field observations with laboratory controlled experiments, manipulating CO2 and temperature, will help elucidate drivers of calcification and project how these species interactions will likely change in the near future. The project will provide the first in situ example of how ongoing ocean acidification is affecting the physiology of long-lived, carbonate producing organisms in the subarctic North Pacific. It will also be one of the first studies to document whether OA, ocean warming, and food web changes to ecological processes are interacting in complex ways to reshape the outcome of species interactions in nature.";
    String projects_0_end_date "2016-08";
    String projects_0_name "Ocean Acidification:  Century Scale Impacts to Ecosystem Structure and Function of Aleutian Kelp Forests";
    String projects_0_project_nid "526660";
    String projects_0_start_date "2013-09";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 51.40283;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "depth_feet,observer";
    String summary "Sea urchin biomass at central and western Aleutian Islands, Alaska from visual surveys, July 2014. Estimates were derived from visual surveys, performed via SCUBA.";
    String time_coverage_end "2014-07-17";
    String time_coverage_start "2014-07-04";
    String title "Sea urchin biomass at central and western Aleutian Islands, Alaska from visual surveys, July 2014";
    String version "1";
    Float64 Westernmost_Easting 173.2486;
    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
For example,
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.

ERDDAP, Version 2.02
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