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Dataset Title:  Body characteristic measurements of sand dollar larvae (Dendraster
excentricus) reared in different pCO2 conditions, July 2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_752974)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Variable ?   Optional
Constraint #1 ?
Optional
Constraint #2 ?
   Minimum ?
 
   Maximum ?
 
 Date (unitless) ?          "2017-07-21"    "2017-07-27"
 rearing_condition (unitless) ?          "acidic"    "ambient"
 jar_replicate (unitless) ?          "four"    "two"
 PO_1 (micrometers (um)) ?          222.65    544.02
 PO_2 (micrometers (um)) ?          224.54    519.02
 AL_1 (micrometers (um)) ?          44.53    565.19
 AL_2 (micrometers (um)) ?          243.2    429.39
 Body_ML (micrometers (um)) ?          208.28    447.95
 BW (micrometers (um)) ?          94.39    1992.67
 PD_1 (micrometers (um)) ?          141.68    469.57
 PD_2 (micrometers (um)) ?          183.24    427.82
 Stomach (micrometers (um)) ?          53.67    162.01
 
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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  Date {
    String bcodmo_name "date_local";
    String description "Date larvae were fixed formatted as yyyy-mm-dd";
    String long_name "Date";
    String source_name "Date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  rearing_condition {
    String bcodmo_name "treatment";
    String description "The pH condition of the water larvae were reared in; \"acidic\" water was bubbled to be 1500ppm and \"ambient\" water was bubbled to be 400ppm";
    String long_name "Rearing Condition";
    String units "unitless";
  }
  jar_replicate {
    String bcodmo_name "replicate";
    String description "Jar replicate larvae were sampled from. There were four replicate jars per rearing condition.";
    String long_name "Jar Replicate";
    String units "unitless";
  }
  PO_1 {
    Float32 _FillValue NaN;
    Float32 actual_range 222.65, 544.02;
    String bcodmo_name "length";
    String description "Postoral arm length; one of two";
    String long_name "PO 1";
    String units "micrometers (um)";
  }
  PO_2 {
    Float32 _FillValue NaN;
    Float32 actual_range 224.54, 519.02;
    String bcodmo_name "length";
    String description "Postoral arm length; one of two";
    String long_name "PO 2";
    String units "micrometers (um)";
  }
  AL_1 {
    Float32 _FillValue NaN;
    Float32 actual_range 44.53, 565.19;
    String bcodmo_name "length";
    String description "Anterolateral arm length; one of two";
    String long_name "AL 1";
    String units "micrometers (um)";
  }
  AL_2 {
    Float32 _FillValue NaN;
    Float32 actual_range 243.2, 429.39;
    String bcodmo_name "length";
    String description "Anterolateral arm length; one of two";
    String long_name "AL 2";
    String units "micrometers (um)";
  }
  Body_ML {
    Float32 _FillValue NaN;
    Float32 actual_range 208.28, 447.95;
    String bcodmo_name "length";
    String description "Length of body midline";
    String long_name "Body ML";
    String units "micrometers (um)";
  }
  BW {
    Float32 _FillValue NaN;
    Float32 actual_range 94.39, 1992.67;
    String bcodmo_name "length";
    String description "Length of body width";
    String long_name "BW";
    String units "micrometers (um)";
  }
  PD_1 {
    Float32 _FillValue NaN;
    Float32 actual_range 141.68, 469.57;
    String bcodmo_name "length";
    String description "Posterodorsal arm length; one of two";
    String long_name "PD 1";
    String units "micrometers (um)";
  }
  PD_2 {
    Float32 _FillValue NaN;
    Float32 actual_range 183.24, 427.82;
    String bcodmo_name "length";
    String description "Posterodorsal arm length; one of two";
    String long_name "PD 2";
    String units "micrometers (um)";
  }
  Stomach {
    Float32 _FillValue NaN;
    Float32 actual_range 53.67, 162.01;
    String bcodmo_name "length";
    String description "Longitudinal length of stomach";
    String long_name "Stomach";
    String units "micrometers (um)";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"We collected adult sand dollars (D. excentricus) from Semiahmoo Bay, WA, in
July 2017 and maintained them in 14\\u00b0C continuous flowing seawater at the
Shannon Point Marine Center. We induced twelve individuals to spawn by
injecting 1-mL of 0.5-M KCl into the coelom following methods outlined by
Strathmann (1987).\\u00a0 We then collected and mixed concentrated gametes of
four males and four females for fertilization. We added five drops of sperm to
500-mL of filtered seawater and 5-mL of eggs. We placed the fertilized eggs in
12\\u00b0C incubator and bubbled them with ambient pCO2 condition for 12-hrs
before dividing the embryos into pCO2 treatment conditions before
gastrulation.
 
We reared D. excentricus larvae (2 individuals mL-1) at 12\\u00b0C in eight 3-L
jars that were individually bubbled with CO2 to achieve four replicates of
ambient (400ppm) and acidic (1500ppm) pCO2 conditions. Daily we gave each
larval jar a water change from pre-equilibrated ambient and acidic water and
fed the larvae D. tertiolecta (6,000 cells ml-1).
 
We measured morphological characteristics of larvae from each rearing jar when
larvae were in the 4- and 6-arm stages following diagrams in Chan et al.
(2011) and Reitzel et al. (2004). Larvae were relaxed in 7% magnesium
chloride, fixed in 3% formalin, imaged using a stereomicroscope equipped with
a camera (Leica MC170 HD and Leica Application Suite, Leica, Wetzlar,
Germany), and measured with ImageJ software. 4-arm larvae were fixed on
7/24/17 and 6-arm larvae were fixed on 7/28/18. The following morphological
characteristics were measured: length of postoral arms (PO), anterolateral
arms (AL), length of body midline, body width, and longitudinal length of
stomach.
 
This dataset includes unprocessed data.";
    String awards_0_award_nid "684166";
    String awards_0_award_number "OCE-1538626";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1538626";
    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 "Michael E. Sieracki";
    String awards_0_program_manager_nid "50446";
    String cdm_data_type "Other";
    String comment 
"Dendraster Characters_OA Expt, 2017 
   S. Arellano, B. Olson, S. Yang (WWU) 
   version: 2019-01-14";
    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 "2019-01-16T20:14:50Z";
    String date_modified "2019-09-25T19:39:12Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.752974.1";
    String history 
"2020-07-06T05:43:17Z (local files)
2020-07-06T05:43:17Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_752974.html";
    String infoUrl "https://www.bco-dmo.org/dataset/752974";
    String institution "BCO-DMO";
    String keywords "AL_1, AL_2, bco, bco-dmo, biological, body, Body_ML, chemical, condition, data, dataset, date, dmo, erddap, jar, jar_replicate, management, oceanography, office, PD_1, PD_2, PO_1, PO_2, preliminary, rearing, rearing_condition, replicate, stomach, time";
    String license "https://www.bco-dmo.org/dataset/752974/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/752974";
    String param_mapping "{'752974': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/752974/parameters";
    String people_0_affiliation "Western Washington University";
    String people_0_affiliation_acronym "WWU";
    String people_0_person_name "Shawn M Arellano";
    String people_0_person_nid "684169";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "Western Washington University";
    String people_1_affiliation_acronym "WWU";
    String people_1_person_name "Dr Brady  M. Olson";
    String people_1_person_nid "51528";
    String people_1_role "Co-Principal Investigator";
    String people_1_role_type "originator";
    String people_2_affiliation "Western Washington University";
    String people_2_affiliation_acronym "WWU";
    String people_2_person_name "Dr Sylvia Yang";
    String people_2_person_nid "684172";
    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 "Climate stressors on larvae";
    String projects_0_acronym "Climate stressors on larvae";
    String projects_0_description 
"In the face of climate change, future distribution of animals will depend not only on whether they adjust to new conditions in their current habitat, but also on whether a species can spread to suitable locations in a changing habitat landscape. In the ocean, where most species have tiny drifting larval stages, dispersal between habitats is impacted by more than just ocean currents alone; the swimming behavior of larvae, the flow environment the larvae encounter, and the length of time the larvae spend in the water column all interact to impact the distance and direction of larval dispersal. The effects of climate change, especially ocean acidification, are already evident in shellfish species along the Pacific coast, where hatchery managers have noticed shellfish cultures with 'lazy larvae syndrome.' Under conditions of increased acidification, these 'lazy larvae' simply stop swimming; yet, larval swimming behavior is rarely incorporated into studies of ocean acidification. Furthermore, how ocean warming interacts with the effects of acidification on larvae and their swimming behaviors remains unexplored; indeed, warming could reverse 'lazy larvae syndrome.' This project uses a combination of manipulative laboratory experiments, computer modeling, and a real case study to examine whether the impacts of ocean warming and acidification on individual larvae may affect the distribution and restoration of populations of native oysters in the Salish Sea. The project will tightly couple research with undergraduate education at Western Washington University, a primarily undergraduate university, by employing student researchers, incorporating materials into undergraduate courses, and pairing marine science student interns with art student interns to develop art projects aimed at communicating the effects of climate change to public audiences
As studies of the effects of climate stress in the marine environment progress, impacts on individual-level performance must be placed in a larger ecological context. While future climate-induced circulation changes certainly will affect larval dispersal, the effects of climate-change stressors on individual larval traits alone may have equally important impacts, significantly altering larval transport and, ultimately, species distribution. This study will experimentally examine the relationship between combined climate stressors (warming and acidification) on planktonic larval duration, morphology, and swimming behavior; create models to generate testable hypotheses about the effects of these factors on larval dispersal that can be applied across systems; and, finally, use a bio-physically coupled larval transport model to examine whether climate-impacted larvae may affect the distribution and restoration of populations of native oysters in the Salish Sea.";
    String projects_0_end_date "2018-08";
    String projects_0_geolocation "Coastal Pacific, USA";
    String projects_0_name "RUI: Will climate change cause 'lazy larvae'? Effects of climate stressors on larval behavior and dispersal";
    String projects_0_project_nid "684167";
    String projects_0_start_date "2015-09";
    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 "This dataset includes body characteristic measurements of sand dollar larvae (Dendraster excentricus) reared in different pCO2 conditions as part of a laboratory experiment to investigate the behavioral effects of ocean acidification on this species in July 2017.";
    String title "Body characteristic measurements of sand dollar larvae (Dendraster excentricus) reared in different pCO2 conditions, July 2017";
    String version "1";
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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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