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Dataset Title:  Composition and abundance of macrophyte wrack at six Santa Barbara beaches
quantified during surveys conducted from 2015-2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_815092)
Range: longitude = -119.8857 to -119.7469°E, latitude = 34.4037 to 34.4173°N
Information:  Summary ? | License ? | 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 {
  Site {
    String bcodmo_name "site";
    String description "Unique site name";
    String long_name "Site";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 34.4037, 34.4173;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude of survey site; positive values = North";
    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 -119.8857, -119.7469;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude of surveysite; positive values = East";
    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";
  }
  Year {
    Int16 _FillValue 32767;
    Int16 actual_range 2015, 2017;
    String bcodmo_name "year";
    String description "The year that the survey was done. This year is expressed in YYYY format. Dates reflect measurements taken in local time. For sites in Alaska, local time is Alaska Standard Time except during months when Alaska Daylight time is effective. For all other Pacific Coast sites, local time is Pacific Standard Time except during months when Pacific Daylight Time is effective.";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  }
  Month {
    String bcodmo_name "month";
    String description "The month that the survey was done. Dates reflect measurements taken in local time. For sites in Alaska, local time is Alaska Standard Time except during months when Alaska Daylight time is effective. For all other Pacific Coast sites, local time is Pacific Standard Time except during months when Pacific Daylight Time is effective.";
    String long_name "Month";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/MNTHXXXX/";
    String units "unitless";
  }
  Date {
    String bcodmo_name "date";
    String description "Date of survey; format: YYYY-MM-DD";
    String long_name "Date";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String source_name "Date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  Transect {
    String bcodmo_name "transect";
    String description "A letter representing one of 6 shore normal transects (A-F) within the study beach  The transect letter is determined by the order from the beach access point.";
    String long_name "Transect";
    String units "unitless";
  }
  Start {
    Float32 _FillValue NaN;
    Float32 actual_range -4.0, 54.0;
    String bcodmo_name "sample_descrip";
    String description "start point (meters) of wrack unit on transect";
    String long_name "Start";
    String units "meters (m)";
  }
  End {
    Float32 _FillValue NaN;
    Float32 actual_range -1.3, 56.0;
    String bcodmo_name "sample_descrip";
    String description "end point (meters) of wrack unit on transect";
    String long_name "End";
    String units "meters (m)";
  }
  Length {
    Float32 _FillValue NaN;
    Float32 actual_range 0.01, 8.0;
    String bcodmo_name "length";
    String description "length (meters) of wrack unit (end-start)";
    String long_name "Length";
    String units "meters (m)";
  }
  Type_Code {
    String bcodmo_name "sample_descrip";
    String description "type of wrack or non-sand substrate as code";
    String long_name "Type Code";
    String units "unitless";
  }
  Type {
    String bcodmo_name "sample_descrip";
    String description "type of wrack or non-sand substrate";
    String long_name "Type";
    String units "unitless";
  }
  Depth {
    Byte _FillValue 127;
    Byte actual_range 1, 90;
    String bcodmo_name "sample_descrip";
    Float64 colorBarMaximum 8000.0;
    Float64 colorBarMinimum -8000.0;
    String colorBarPalette "TopographyDepth";
    String description "depth (cm) of wrack";
    String long_name "Depth";
    String standard_name "depth";
    String units "centimeters (cm)";
  }
  Investigator {
    String bcodmo_name "investigator";
    String description "name of investigator";
    String long_name "Investigator";
    String units "unitless";
  }
  Notes {
    String bcodmo_name "comment";
    String description "notes on site or transect";
    String long_name "Notes";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"We quantified composition and abundance of macrophyte wrack of the six study
beaches during each survey from 2015-2017. Wrack composition and cover were
recorded for each of six shore-normal transects of variable length that
extended from the lower edge of terrestrial vegetation or the bluff to the
lowest intertidal level exposed by swash at each location. The transects were
randomly assigned to locations within the first 100 m of shoreline from the
access point using a random number table and a distance measuring wheel. We
used a line-intercept method along each transect tape to quantify wrack cover.
The presence and extent (length, depth) of each type of macrophyte, driftwood,
carrion, tar, trash and any other beach-cast wrack was recorded along each
transect tape, yielding total wrack cover by wrack type for each transect.
Data are reported as m2/m of shoreline.";
    String awards_0_award_nid "542227";
    String awards_0_award_number "OCE-1458845";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1458845";
    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 
"Wrack composition and abundance at six Santa Barbara beaches 
  PI: Jenifer Dugan (UCSB) 
  Co-PI: Robert Miller (UCSB) 
  Version date: 15 June 2020";
    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 dataset_current_state "Final and no updates";
    String date_created "2020-06-15T17:40:09Z";
    String date_modified "2020-06-23T13:29:14Z";
    String defaultDataQuery "&time<now";
    String doi "10.26008/1912/bco-dmo.815092.1";
    Float64 Easternmost_Easting -119.7469;
    Float64 geospatial_lat_max 34.4173;
    Float64 geospatial_lat_min 34.4037;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -119.7469;
    Float64 geospatial_lon_min -119.8857;
    String geospatial_lon_units "degrees_east";
    String history 
"2021-10-24T06:23:32Z (local files)
2021-10-24T06:23:32Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_815092.das";
    String infoUrl "https://www.bco-dmo.org/dataset/815092";
    String institution "BCO-DMO";
    String instruments_0_dataset_instrument_nid "815099";
    String instruments_0_description "A tape measure or measuring tape is a flexible ruler. It consists of a ribbon of cloth, plastic, fibre glass, or metal strip with linear-measurement markings. It is a common tool for measuring distance or length.";
    String instruments_0_instrument_name "Measuring Tape";
    String instruments_0_instrument_nid "645010";
    String instruments_0_supplied_name "distance measuring wheel";
    String keywords "bco, bco-dmo, biological, chemical, code, data, dataset, date, depth, dmo, end, erddap, investigator, latitude, length, longitude, management, month, notes, oceanography, office, preliminary, site, start, time, transect, type, Type_Code, year";
    String license "https://www.bco-dmo.org/dataset/815092/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/815092";
    Float64 Northernmost_Northing 34.4173;
    String param_mapping "{'815092': {'Latitude': 'flag - latitude', 'Longitude': 'flag - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/815092/parameters";
    String people_0_affiliation "University of California-Santa Barbara";
    String people_0_affiliation_acronym "UCSB-MSI";
    String people_0_person_name "Jenifer E. Dugan";
    String people_0_person_nid "542219";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "University of California-Santa Barbara";
    String people_1_affiliation_acronym "UCSB-MSI";
    String people_1_person_name "Robert Miller";
    String people_1_person_nid "542220";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Linking Kelp to Beaches";
    String projects_0_acronym "Linking Kelp to Beaches";
    String projects_0_description 
"This project is affiliated with the Santa Barbara Coastal LTER project.
Description from NSF award abstract:
Primary producers, such as plants and algae, form the basis of most food webs and their productivity and fate fundamentally shape ecosystems. Often, however, food and other resources are delivered to a food web from an outside source, providing a subsidy to the recipient ecosystem. Understanding these types of trophic connections and exchanges between ecosystems is necessary for predicting how food webs may respond to change, whether environmental or anthropogenic. Despite their potential importance, quantitative evaluations of cross-ecosystem material fluxes, variation of these fluxes in time and space, and ecological responses of recipient communities are lacking, particularly for marine ecosystems. By investigating links between a source ecosystem, kelp forests, and a recipient ecosystem, sandy beaches, this project will expand and transform our understanding of cross-ecosystem fluxes in the coastal ocean. Nearshore kelp forests are highly productive marine ecosystems characterized by large seasonal and interannual variations in net primary production (NPP). More than 90% of kelp forest NPP is exported to adjacent ecosystems including the intertidal zone. Lacking attached plants and algae, sandy beach ecosystems near kelp forests depend heavily on imported drift kelp (wrack) to support complex and diverse food webs. Although sandy beaches are a dominant shoreline type along all U.S. coasts, provide habitat and prey for wildlife, including endangered species, and are highly valued by society as recreational and cultural resources that drive vibrant coastal economies, they receive little ecological study compared to other shoreline types. This lack of knowledge hinders the conservation and management of beaches as ecosystems. Perched on the narrow rim between land and sea, beaches are highly vulnerable to climate change, particularly sea level rise, and will be impacted by changes in climate, as will kelp forests. This project integrates biological and physical approaches to achieve an understanding of the fate and transport of exported kelp, and how variability in this resource subsidy shapes the community structure and function of recipient beach ecosystems. Graduate and undergraduate students will be integral members of the research team, receiving scientific training and mentoring in coastal marine ecology and in public outreach and education. The training and participation of local residents and coastal managers in regular shoreline surveys for beached kelp plants will provide an essential research component of the study and enhance public awareness of scientific research, coastal ecology and the role of links between kelp forest and beach ecosystems. The results of this project will provide new insights into the dynamics of connectivity between coastal marine ecosystems that can be applied to their conservation and management.
The project seeks to understand trophic connectivity between a donor ecosystem, kelp forests, and a recipient ecosystem, sandy beaches, with two primary goals:
1) an evaluation of how variation in kelp wrack input affects patterns and processes in beach ecosystems and
2) a quantitative understanding of trophic connectivity through physical transport and input of drift kelp biomass from kelp forests to sandy beaches.
The project will begin with two years of intensive work at a well-studied kelp forest in the Santa Barbara Channel, Mohawk Reef, and along 10 km of adjacent coastline, where the research team will measure intertidal community structure over time in response to variability in kelp inputs. To assess effects of variation in wrack input on ecosystem function, they will also measure kelp consumption and secondary production rates of intertidal consumers on adjacent beaches. They will directly observe fate and transport of kelp using complimentary approaches: 1) tracking kelp plants tagged at Mohawk Reef using drifters with GPS; and 2) tagging large numbers of kelp plants (2000) with \"drift cards\" at Mohawk Reef for recovery by the project team and trained volunteer beachcombers. Ending distributions of recovered drift cards and drifter tracks along the shoreline will then be computed. These data will be used to inform and validate a kelp forest-to-beach kelp transport model based on numerical simulations of coastal surface currents from the Regional Oceanic Modeling System (ROMS). Using predicted kelp beaching rates from this model run regionally, the investigators will then sample community structure and wrack biomass at a larger set of beaches spanning 100 km of the southern California shoreline to test the generality of research findings. This combination of fate and transport observations, beach community surveys and process measurements, and modeling will allow the investigators to characterize temporal variability in kelp subsidy inputs and the consequences of this variability for community structure and function of recipient beach ecosystems.";
    String projects_0_end_date "2019-03";
    String projects_0_geolocation "Santa Barbara Channel, California, USA 34 N, 119 W";
    String projects_0_name "Linking nearshore kelp forest dynamics to sandy beach ecosystems";
    String projects_0_project_nid "542223";
    String projects_0_start_date "2015-04";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 34.4037;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Composition and abundance of macrophyte wrack at six Santa Barbara beaches quantified during surveys conducted from 2015-2017. Wrack composition and cover were recorded for each of six shore-normal transects of variable length that extended from the lower edge of terrestrial vegetation or the bluff to the lowest intertidal level exposed by swash at each location.";
    String title "Composition and abundance of macrophyte wrack at six Santa Barbara beaches quantified during surveys conducted from 2015-2017";
    String version "1";
    Float64 Westernmost_Easting -119.8857;
    String xml_source "osprey2erddap.update_xml() v1.5";
  }
}

 

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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