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Dataset Title:  Elemental fingerprints of larval, juvenile, and settler Mytilus collected in
the Gulf of Maine between 2015 and 2016
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_752530)
Range: longitude = -71.04074 to -66.97212°E, latitude = 42.31377 to 44.80606°N
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Site {
    String description "Sample location";
    String ioos_category "Unknown";
    String long_name "Site";
    String units "unitless";
  }
  Site_Code {
    String description "Sample location abbreviation";
    String ioos_category "Unknown";
    String long_name "Site Code";
    String units "unitless";
  }
  Age {
    String description "Age (Larvae, Juvenile or Settler)";
    String ioos_category "Time";
    String long_name "Age";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range 42.31377, 44.80606;
    String axis "Y";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "Latitude";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -71.04074, -66.97212;
    String axis "X";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "Longitude";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  Date {
    String description "Sample collection date (UTC) in ISO 8601 format yyyy-MM-dd";
    String ioos_category "Time";
    String long_name "Date";
    String source_name "Date";
    String units "unitless";
  }
  Sample_Number {
    Byte _FillValue 127;
    Byte actual_range 1, 98;
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Indicator to distinguish specific individuals";
    String ioos_category "Statistics";
    String long_name "Sample Number";
    String units "unitless";
  }
  Mg {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 4424754.3;
    String description "Magnesium concentration (umol Mg/mol Ca)";
    String ioos_category "Unknown";
    String long_name "MG";
    String units "dimensionless";
  }
  Mn {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 210708.89;
    String description "Manganese concentration (umol Mn/mol Ca)";
    String ioos_category "Unknown";
    String long_name "MN";
    String units "dimensionless";
  }
  Co {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 1485.83;
    String description "Cobalt concentration (umol Co/mol Ca)";
    String ioos_category "Unknown";
    String long_name "Co";
    String units "dimensionless";
  }
  Sr {
    Float64 _FillValue NaN;
    Float64 actual_range 0.0, 511916.0;
    String description "Strontium concentration (umol Sr/mol Ca)";
    String ioos_category "Unknown";
    String long_name "SR";
    String units "dimensionless";
  }
  Ba {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 3532.25;
    String description "Barium concentration (umol Ba/mol Ca)";
    String ioos_category "Unknown";
    String long_name "Ba";
    String units "dimensionless";
  }
  La {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 256.31;
    String description "Lanthanum concentration (umol La/mol Ca)";
    String ioos_category "Unknown";
    String long_name "La";
    String units "dimensionless";
  }
  Pb {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 2502.05;
    String description "Lead concentration (umol Pb/mol Ca)";
    String ioos_category "Unknown";
    String long_name "PB";
    String units "dimensionless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"We quantified larval fingerprints during spawning at each of the potential
source populations to develop a reference map that will allow us to assign
settled mussels to natal sites based on the elemental fingerprints of their
larval shell. To develop a reference map of elemental signatures, we reared
larvae in situ at each major mussel population (see sample locations data).
After populations spawned in the field (based on our monitoring of gonad
indices in each population) adult mussels from multiple sites were collected,
spawned in the laboratory and the eggs fertilized. Within 24-48 hours (before
shell formation begins) larvae were placed into small chambers and moored in
situ at 3-5m depth. Because spawning varied among the populations, we
staggered our deployment of larvae to coincide with our estimates of spawning
times. After four weeks, larval mussels were removed from in situ chambers,
shells were rinsed in deionized water, dried and prepared for ICPMS. Settlers
were collected from settlement plates deployed at each population.
 
Elemental concentrations were determined from single spot ablation in larval
shells (85% energy, 10 hz, 200 shots, 25 \\u03bcm spot diameter) for both
larvae and settlers. Elemental compositions were quantified by external
calibration (USGS MACS-3) and internal standardization. We quantified
elemental compositions from count per second (cps) measurements of 24Mg, 55Mn,
59Co, 88Sr, 138Ba, 139La, 208Pb and 46Ca using laser ablation inductively
coupled mass spectrometry (213 Nd:YAG laser coupled with Elan DRC II ICPMS) at
the University of Massachusetts, Boston (LA-ICPMS). Elemental abundances were
calculated as analyte cps/ 43Ca cps. We performed a one-point calibration
using gas blank and MACS-3, and ran MACS-1 as a check standard every ten
samples. Analytical accuracy and precision based on repeated check standard
analyses was 96 + 4.4% (mean + sd). Each sample was analyzed in triplicate and
mean concentrations normalized to calcium are reported.
 
Location:  
 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 awards_0_award_nid "527081";
    String awards_0_award_number "OCE-1334022";
    String awards_0_data_url "http://nsf.gov/awardsearch/showAward?AWD_ID=1334022";
    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 "Dr David  L. Garrison";
    String awards_0_program_manager_nid "50534";
    String awards_1_award_nid "542418";
    String awards_1_award_number "OCE-1458154";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1458154";
    String awards_1_funder_name "NSF Division of Ocean Sciences";
    String awards_1_funding_acronym "NSF OCE";
    String awards_1_funding_source_nid "355";
    String awards_1_program_manager "Dr David  L. Garrison";
    String awards_1_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Mytilus fingerprints 
  PI: Ron Etter 
  Data Version 1: 2019-04-04";
    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 2.2d  13 Jun 2019";
    String date_created "2019-01-04T21:23:49Z";
    String date_modified "2019-04-19T15:47:35Z";
    String defaultDataQuery "&time";
    String doi "10.1575/1912/bco-dmo.752530.1";
    Float64 Easternmost_Easting -66.97212;
    Float64 geospatial_lat_max 44.80606;
    Float64 geospatial_lat_min 42.31377;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -66.97212;
    Float64 geospatial_lon_min -71.04074;
    String geospatial_lon_units "degrees_east";
    String history 
"2019-11-17T02:35:47Z (local files)
2019-11-17T02:35:47Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_752530.das";
    String infoUrl "https://www.bco-dmo.org/dataset/752530";
    String institution "BCO-DMO";
    String instruments_0_acronym "Mass Spec";
    String instruments_0_dataset_instrument_description "Teledyne Cetac 213 G2+ laser coupled with a Perkin Elmer NexION 2000C mass spectrometer with autosampler and cross-flow nebulizer.";
    String instruments_0_dataset_instrument_nid "763563";
    String instruments_0_description "General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB16/";
    String instruments_0_instrument_name "Mass Spectrometer";
    String instruments_0_instrument_nid "685";
    String instruments_0_supplied_name "Perkin Elmer NexION 2000C";
    String instruments_1_dataset_instrument_description "Teledyne Cetac 213 G2+ laser coupled with a Perkin Elmer NexION 2000C mass spectrometer with autosampler and cross-flow nebulizer";
    String instruments_1_dataset_instrument_nid "763564";
    String instruments_1_description "A device that generates an intense beam of coherent monochromatic light (or other electromagnetic radiation) by stimulated emission of photons from excited atoms or molecules.�";
    String instruments_1_instrument_name "Laser";
    String instruments_1_instrument_nid "564857";
    String instruments_1_supplied_name "Teledyne Cetac 213 G2+";
    String keywords "age, bco, bco-dmo, biological, chemical, code, data, dataset, date, dmo, erddap, latitude, longitude, management, number, oceanography, office, preliminary, sample, Sample_Number, site, Site_Code, statistics, time";
    String license 
"The data may be used and redistributed for free but is not intended
for legal use, since it may contain inaccuracies. Neither the data
Contributor, ERD, NOAA, nor the United States Government, nor any
of their employees or contractors, makes any warranty, express or
implied, including warranties of merchantability and fitness for a
particular purpose, or assumes any legal liability for the accuracy,
completeness, or usefulness, of this information.";
    String metadata_source "https://www.bco-dmo.org/api/dataset/752530";
    Float64 Northernmost_Northing 44.80606;
    String param_mapping "{'752530': {'Latitude': 'master - latitude', 'Longitude': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/752530/parameters";
    String people_0_affiliation "University of Massachusetts Boston";
    String people_0_affiliation_acronym "UMB";
    String people_0_person_name "Dr Ron J Etter";
    String people_0_person_nid "51359";
    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 "Amber York";
    String people_1_person_nid "643627";
    String people_1_role "BCO-DMO Data Manager";
    String people_1_role_type "related";
    String project "An integrated theoretical and empirical approach to across-shelf mixing and connectivity of mussel populations, Intertidal community assembly and dynamics: Integrating broad-scale regional variation in environmental forcing and benthic-pelagic coupling";
    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 projects_1_acronym "GOMEPRO";
    String projects_1_description 
"Rocky intertidal habitats in the Gulf of Maine (GoM) provide a model system to examine the structure and dynamics of natural communities. Throughout the Gulf of Maine, the same species are often found in these habitats but community structure, dynamics and productivity differ markedly among 3 distinct regions (southern, central and northern GoM). Past influential work, conducted primarily in the southern and central GoM, focused on the local processes driving intertidal community structure but produced very different conceptual models of how these communities are structured. This project examines whether regional differences in rocky shore community processes are driven by differences in recruitment that are shaped by regional variation in temperature and food availability and nearshore coastal oceanography. This project will improve the understanding of how large-scale environmental forces interact with local processes to control the distribution of species and the structure and dynamics of these communities. Understanding the interaction between processes operating at different scales is fundamentally important to developing more reliable models that can be used to predict community dynamics. In addition, data resulting from this project will have important implications for regional dynamics in commercially important species and for ecosystem and fisheries management within the GoM.
The overarching hypothesis of this project is that regional differences in community-level processes are driven by very different patterns of population connectivity and recruitment in a few key species, and that these differences are ultimately caused by regional variation in temperature and food availability and mediated by physical larval transport processes. Hence, the project will test the following hypotheses with manipulative field experiments, field sampling, connectivity estimates, and integrative modeling:
1) Locally-dispersing species dominate dynamics in regions with a net export of planktonic larvae (Northern GoM), while species with planktonic larvae dominate the dynamics in regions with high settlement and extensive connectivity among populations (Southern GoM).
2) Settlement density of species with planktonic larvae increases from northern to southern regions in accord with regional variation in food availability.
3) Population connectivity varies greatly among regions, with regions differing in the degree to which they are self-seeded or serve as larval sources vs. sinks; self-seeding leads to relatively localized population dynamics in the middle portion of the GoM.
4) Patterns of population connectivity are driven by physical transport processes and can be represented by coupling basic larval behavior models with circulation models.
At 18 different sites in the GoM across ~ 600 km, surveys will evaluate variation in recruitment, food availability and secondary productivity and experiments will assess community processes in wave-exposed and sheltered habitats. We will use hydrographic, current profile, and larval vertical distribution surveys to collect data for coupled larval/circulation models. Population connectivity will be both modeled and empirically evaluated (for one species) using elemental fingerprinting. A spatially explicit metacommunity model will integrate across all project components and test the relative importance of regional and local processes in controlling community organization and dynamics.";
    String projects_1_end_date "2019-01";
    String projects_1_geolocation "Rocky intertidal shores and nearshore coastal waters throughout the Gulf of Maine";
    String projects_1_name "Intertidal community assembly and dynamics: Integrating broad-scale regional variation in environmental forcing and benthic-pelagic coupling";
    String projects_1_project_nid "542407";
    String projects_1_start_date "2015-02";
    String publisher_name "Amber York";
    String publisher_role "BCO-DMO Data Manager(s)";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 42.31377;
    String standard_name_vocabulary "CF Standard Name Table v29";
    String summary "Elemental fingerprints of larval, juvenile, and settler Mytilus collected in the Gulf of Maine between 2015 and 2016.";
    String title "Elemental fingerprints of larval, juvenile, and settler Mytilus collected in the Gulf of Maine between 2015 and 2016";
    String version "1";
    Float64 Westernmost_Easting -71.04074;
    String xml_source "osprey2erddap.update_xml() v1.5-beta";
  }
}

 

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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