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Dataset Title:  [Island grazing history] - Historical reconstruction of sea urchin grazing
events in Aleutian Island ecosystem from grazing scars, 1965-2004 (Ocean
Acidification: Century Scale Impacts to Ecosystem Structure and Function of
Aleutian Kelp Forests)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_755687)
Range: longitude = -178.66258 to 179.38345°E, latitude = 51.40901 to 52.9336°N, time = 2004-08-14 to 2014-07-21
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 {
  time {
    String _CoordinateAxisType "Time";
    Float64 actual_range 1.0924416e+9, 1.4059008e+9;
    String axis "T";
    String bcodmo_name "date";
    String description "date of collection; formatted as yyyy-mm-dd";
    String ioos_category "Time";
    String long_name "Collection Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "collection_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";
  }
  island {
    String bcodmo_name "site";
    String description "name of island";
    String long_name "Island";
    String units "unitless";
  }
  site_name {
    String bcodmo_name "site";
    String description "name of collection site";
    String long_name "Site Name";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 51.40901, 52.9336;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude of collection 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 -178.66258, 179.38346;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude of collection 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 30.0, 33.0;
    String bcodmo_name "depth";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth of sample collection";
    String long_name "Depth";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String standard_name "depth";
    String units "feet";
  }
  replicate {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 5;
    String bcodmo_name "replicate";
    String description "replicate individual alga studied";
    String long_name "Replicate";
    String units "unitless";
  }
  sample_ID {
    String bcodmo_name "sample";
    String description "unique sample identifier";
    String long_name "Sample ID";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  transect {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 1, 3;
    String bcodmo_name "transect";
    String description "replicate transect within individual";
    String long_name "Transect";
    String units "unitless";
  }
  end_period {
    Int16 _FillValue 32767;
    Int16 actual_range 1969, 2004;
    String bcodmo_name "year_end";
    String description "upper bound of 5-year period scored";
    String long_name "End Period";
    String units "year";
  }
  start_period {
    Int16 _FillValue 32767;
    Int16 actual_range 1965, 2000;
    String bcodmo_name "year_start";
    String description "lower bound of 5-year period scored";
    String long_name "Start Period";
    String units "year";
  }
  time_period {
    String bcodmo_name "date_range";
    String description "discrete 5-year time interval scored";
    String long_name "Time Period";
    String units "years";
  }
  growth_increment_um {
    Int16 _FillValue 32767;
    Int16 actual_range 423, 3227;
    String bcodmo_name "growth";
    String description "net algal growth incurred over 5-year period";
    String long_name "Growth Increment Um";
    String units "micrometers";
  }
  grazing_events {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 0, 5;
    String bcodmo_name "number";
    String description "number of grazing events observed within 5-year period";
    String long_name "Grazing Events";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson,.odvTxt";
    String acquisition_description 
"Clathromorphum species produce annual growth increments (hereafter \\\"year
bands\\\") in their skeleton (Adey et al. 2013), which contain elemental and
isotopic signatures that can be used to reconstruct past oceanographic
conditions (e.g., Fietzke et al. 2015). We discovered that such year bands
also archive urchin grazing scars, allowing us to measure the timing and
frequency of past urchin grazing events on C. nereostratum. Wild specimens of
C. nereostratum were thus collected and analyzed in order to reconstruct
grazing events in the ecosystem.
 
At each site studied with respect to bioerosion, we collected C. nereostratum
specimens (n = 10/site) with hammer and chisel, focusing on individuals
without visible signs of grazing on the epithallus. Ship-side, samples were
sectioned with a diamond lapidary saw and examined for quality; high quality
samples were placed in an oven (50\\u00b0C) until dry, then archived for
subsequent analysis. Samples collected from Amchitka were of poor quality.
Hence for Amchitka, we used specimens collected previously (2004) for this
exercise. We also augmented our 2014 collections from Attu with samples
previously collected (2008) from the same locale, because many of the 2014
samples did not meet our criteria for reconstruction (see below).
 
Each C. nereostratum specimen (n = 5/island) was mounted to a glass slide,
sectioned parallel to the growth axis with a diamond lapidary saw, and
polished to 3 microns resolution following established methods (Hetzinger et
al. 2009). Each section was then imaged with a camera coupled to a reflected
light microscope (GeoTS, Olympus Inc.), which obtains a mosaic of overlapping
images and stitches them together to produce a single high-resolution image of
the cross-section. This photomosaic was used to carefully identify, age, and
count grazing scars that occurred along a transect oriented parallel to the
alga's growth axis in the plane of the section. We scored multiple (n = 2-3)
transects per sample, given that grazing events do not span the entirety of a
year band. The origin of each transect was randomly plotted, then moved to the
nearest location on the epithallus that was living and that displayed a flat
or convex shape. The transect was then plotted through sequentially older year
bands, so long as it: (i) did not cross a fusion between two individual algae;
(ii) spanned at least 30 years of growth; and (iii) intercepted year bands
that were clearly visible. If any of these criteria were violated, the
transect was relocated.
 
Along each transect, we aged and measured the growth (vertical extension) of
year bands in 5-year intervals, repeating this process so long as dating could
be rigorously performed and end-dates aligned for all transects within a
sample. Within each 5-year interval, we assessed the annual frequency of
grazing scars - which manifest as a jagged interruption of the growth margin
coupled with serial pitting of the reproductive conceptacles - found 5 mm to
either side of the transect. Straight growth lines that lacked conceptacles or
the occasional empty conceptacle within an otherwise clean growth band was not
considered evidence of grazing. In instances where one side of the transect
entered an area that violated the above criteria (e.g., passed under an area
that had a concave epithallial surface), we analyzed only one side of the
transect (10 mm). With this methodology remains the possibility that urchin
grazing may have removed entire years of growth, thus obscuring our estimates
of grazing frequency and the timing of each grazing event. To address this
issue, we compared (double blind) our age models for a subset of samples from
Alaid and Ogliuga to ages produced using Uranium series dating (Fietzke et al.
2005). Our age estimates were very similar to those produced by Uranium series
dating, indicating we did not lose entire years to grazing.
 
We selected the year 1965 as the cutoff for our reconstruction because
ecological records are scant prior to this period (Estes et al. 2010). For C.
nereostratum samples collected in 2014, we excluded the 10 most recent years
of growth (2014-2005) from our analyses due to a known bias in our collection
method; since we collected non-grazed specimens from the wild and retained
only the highest quality samples, we biased ourselves against finding evidence
of grazing in recent years. For samples collected in 2004 and 2008, such a
bias was not evident, at least for those records that met our criteria and
were used in the study. For the three 2008 samples used, we excluded the first
four years to align chronologies with all other specimens.";
    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 
"Historical reconstruction of sea urchin grazing events in the Aleutian Islands, 1965-2004 
   PI's: Steneck (Umaine), J.Estes (UCSC), D. Rasher (BLOS) 
   version: 2019-02-013";
    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 "2019-02-13T20:13:05Z";
    String date_modified "2019-02-25T20:18:35Z";
    String defaultDataQuery "&amp;time&lt;now";
    String doi "10.1575/1912/bco-dmo.755687.1";
    Float64 Easternmost_Easting 179.38346;
    Float64 geospatial_lat_max 52.9336;
    Float64 geospatial_lat_min 51.40901;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max 179.38346;
    Float64 geospatial_lon_min -178.66258;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-11-08T05:45:41Z (local files)
2024-11-08T05:45:41Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_755687.das";
    String infoUrl "https://www.bco-dmo.org/dataset/755687";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, collection, data, dataset, date, depth, depth_feet, dmo, end, end_period, erddap, events, grazing, grazing_events, growth, growth_increment_um, increment, island, latitude, longitude, management, name, oceanography, office, period, preliminary, replicate, sample, sample_ID, site, site_name, start, start_period, time, time_period, transect";
    String license "https://www.bco-dmo.org/dataset/755687/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/755687";
    Float64 Northernmost_Northing 52.9336;
    String param_mapping "{'755687': {'collection_date': 'flag - time', 'depth_feet': 'flag - depth', 'longitude': 'flag - longitude', 'latitude': 'flag - latitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/755687/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 51.40901;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Historical reconstruction of sea urchin grazing events in the ecosystem, achieved via enumerating the annual frequency of grazing scars that are archived in the calcified matrix of Clathromorphum nereostratum. Intact colonies of C. nereostratum were collected via SCUBA. Reconstructions were performed on polished and imaged sample cross-sections.";
    String time_coverage_end "2014-07-21";
    String time_coverage_start "2004-08-14";
    String title "[Island grazing history] - Historical reconstruction of sea urchin grazing events in Aleutian Island ecosystem from grazing scars, 1965-2004 (Ocean Acidification:  Century Scale Impacts to Ecosystem Structure and Function of Aleutian Kelp Forests)";
    String version "1";
    Float64 Westernmost_Easting -178.66258;
    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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