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Dataset Title:  Blue mussel (Mytilus edulis) settlement data from settlement plates in coastal
eastern Maine from 2014 to 2016 (MuLTI-2 project)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_720217)
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 {
  Station_Code {
    String bcodmo_name "station";
    String description "Station identifier";
    String long_name "Station Code";
    String units "unitless";
  Year {
    Int16 _FillValue 32767;
    Int16 actual_range 2014, 2016;
    String bcodmo_name "year";
    String description "Year of sampling event";
    String long_name "Year";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/YEARXXXX/";
    String units "unitless";
  Sampling_Event {
    String bcodmo_name "event";
    String description "Identifier of sampling deployment";
    String long_name "Sampling Event";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/EVTAGFL/";
    String units "unitless";
  Plate_Number {
    String bcodmo_name "sample_descrip";
    String description "Settlement plate identifier";
    String long_name "Plate Number";
    String units "unitless";
  Date_Deployment_Midpoint {
    String bcodmo_name "date";
    String description "Midpoint date of the deployment in format mm/dd/yy";
    String long_name "Date Deployment Midpoint";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ADATAA01/";
    String units "unitless";
  Deployment_Length {
    Byte _FillValue 127;
    Byte actual_range 2, 68;
    String bcodmo_name "days";
    String description "Number of days in the deployment";
    String long_name "Deployment Length";
    String units "unitless";
  Total_Settlers {
    Int16 _FillValue 32767;
    Int16 actual_range 0, 5172;
    String bcodmo_name "count";
    String description "Total number of settled blue mussels (Mytilus edulis)";
    String long_name "Total Settlers";
    String units "unitless";
  Settler_Density {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 70.6557377;
    String bcodmo_name "density";
    String description "Density of settled blue mussels (Mytilus edulis) during a deployment period";
    String long_name "Settler Density";
    String units "settled mussels per cm^2";
  Daily_Settler_Density {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 4.415983607;
    String bcodmo_name "density";
    String description "Average density of settled blue mussels (Mytilus edulis) per day";
    String long_name "Daily Settler Density";
    String units "settled mussels per cm^2";
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Location:\\u00a0Coastal waters of eastern Maine, from Frenchman Bay to the
Canadian border.\\u00a0Locations and descriptions for station codes used in
this dataset can be found in the dataset:\\u00a0[MuLTI-2 Mussel Station
Sampling and Analytical Methodology:\\u00a0
Three settlement plates were deployed randomly along a 6 m transect in a blue
mussel (Mytilus edulis) bed at each station. Settlement plates were
constructed by gluing 3M Scotch-Brite\\u2122 pad to a 1/8 inch thick and 9.7 cm
diameter piece of PVC (with a 0.95 cm diameter mounting hole) with PVC heavy
cement. Total area of each settlement plate was 73.2 cm^2. Settlement plates
were oriented North in the mussel bed to reduce sun exposure. Following
deployment, settlement plates were collected and replaced, and all newly
settled mussels on each collected plate were counted. Settlement rate was
calculated for each settlement plate at each station for each deployment.
The settlement rate was calculated for each deployment period at each station.";
    String awards_0_award_nid "527111";
    String awards_0_award_number "OCE-1333755";
    String awards_0_data_url "http://nsf.gov/awardsearch/showAward?AWD_ID=1333755";
    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 
    PI: P. Yund 
    data version: 2017-11-30";
    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 "2017-11-30T22:09:07Z";
    String date_modified "2020-01-03T19:41:38Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.720217.1";
    String history 
"2024-07-15T06:15:32Z (local files)
2024-07-15T06:15:32Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_720217.das";
    String infoUrl "https://www.bco-dmo.org/dataset/720217";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, code, daily, Daily_Settler_Density, data, dataset, date, Date_Deployment_Midpoint, day, density, deployment, Deployment_Length, dmo, erddap, event, length, management, midpoint, number, oceanography, office, plate, Plate_Number, preliminary, sampling, Sampling_Event, settler, Settler_Density, settlers, station, Station_Code, total, Total_Settlers, year";
    String license "https://www.bco-dmo.org/dataset/720217/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/720217";
    String param_mapping "{'720217': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/720217/parameters";
    String people_0_affiliation "Downeast Institute for Applied Marine Research and Education";
    String people_0_affiliation_acronym "DEI";
    String people_0_person_name "Dr Philip O. Yund";
    String people_0_person_nid "51154";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Downeast Institute for Applied Marine Research and Education";
    String people_1_affiliation_acronym "DEI";
    String people_1_person_name "Dr Philip O. Yund";
    String people_1_person_nid "51154";
    String people_1_role "Contact";
    String people_1_role_type "related";
    String people_2_affiliation "Woods Hole Oceanographic Institution";
    String people_2_affiliation_acronym "WHOI BCO-DMO";
    String people_2_person_name "Amber York";
    String people_2_person_nid "643627";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "MuLTI-2";
    String projects_0_acronym "MuLTI-2";
    String projects_0_description 
"Acronym \"MuLTI-2\" (Mussel Larval Transport Initiative-2)
Extracted from the NSF award abstract:
Existing larval transport models focus mainly on along-shelf transport and have done little to explicitly incorporate the effects of cross-shelf mixing and transport processes. Yet cross-shelf transits (both outgoing and incoming legs) are critical components of the dispersal paths of coastal invertebrates. This project will explore the role of cross-shelf mixing in the connectivity of blue mussel populations in eastern Maine. Previous work has shown that the Eastern Maine Coastal Current (EMCC) begins to diverge from shore southwest of the Grand Manan Channel and creates a gradient in cross-shelf mixing and larval transport, with cross-shelf mixing being more common on the northeastern end, episodic in the transitional middle area, and then becoming rare in the southwestern half of the region of the Gulf of Maine. As a result, the investigators predict that northeastern populations of mussels are seeded mostly from up-stream sources, while a significant component of self-seeding (local retention) exists in southwestern populations. Larvae settling in the intervening bays are expected to be derived from a mixture of local and up-stream sources. Using a combined empirical and theoretical approach hydrographic, current profile, and larval vertical migration data will be collected and used to develop and validate a high-resolution coastal circulation model coupled to a model of larval behavior. The investigators will model simulations in different years using the empirical data from mussel reproductive output and spawning times. Connectivity predicted from this model will be then tested against independent empirical estimates of connectivity based on trace element fingerprinting for larvae which can be connected to specific natal habitats. Regions of agreement and discrepancy in the model will be identified to guide additional data collection and model refinement. This iterative process will ensure an understanding of both larval transport patterns and processes, and provide estimates of inter-annual variability in connectivity for blue mussel populations in the Gulf of Maine.";
    String projects_0_end_date "2017-08";
    String projects_0_geolocation "Gulf of Maine: Frenchmen Bay (44 28.239 N -68 15.927 W) to Machais Bay (44 39.350 N -67 21.320 W)";
    String projects_0_name "An integrated theoretical and empirical approach to across-shelf mixing and connectivity of mussel populations";
    String projects_0_project_nid "527082";
    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)";
    String standard_name_vocabulary "CF Standard Name Table v55";
    String summary "Blue mussel (Mytilus edulis) settlement data from settlement plates in coastal eastern Maine from 2014 to 2016.";
    String title "Blue mussel (Mytilus edulis) settlement data from settlement plates in coastal eastern Maine from 2014 to 2016 (MuLTI-2 project)";
    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
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.

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