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Dataset Title:  Oyster larvae vertical distribution data collected from laboratory water
column experiments on the behavioral effects of ocean acidification on Olympia
oyster larvae (Ostrea lurida), July 2017
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_753058)
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 {
  trial {
    Byte _FillValue 127;
    Byte actual_range 1, 2;
    String bcodmo_name "exp_id";
    String description "Trial number";
    String long_name "Trial";
    String units "unitless";
  }
  date {
    String bcodmo_name "date_local";
    String description "Date of trial formatted as yyyy-mm-dd";
    String long_name "Date";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  column_name {
    String bcodmo_name "sample";
    String description "Identifies the experimental water column treatment and replicate: AN-# = Acidic water at the top and Neutral water at the bottom ; NN-# = Neutral water at the top and Neutral water at the bottom; NA-# = Neutral water at the top and Acid water at the bottom. Acidic water was bubbled to be 400 pCO2 and neutral (ambient) water was bubbled to be 1500 pCO2";
    String long_name "Column Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  count_id {
    Byte _FillValue 127;
    Byte actual_range 1, 2;
    String bcodmo_name "replicate";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "Identifies the count number (1 or 2) per experimental date. The vertical positions of larvae in the columns were counted twice for each experiment; the first count at 10 minutes post-larval introduction into the column and the second count at 30 minutes post-larval introduction into the column.";
    String long_name "Count Id";
    String units "unitless";
  }
  height_cm {
    Byte _FillValue 127;
    Byte actual_range 1, 20;
    String bcodmo_name "height";
    String description "The height above the bottom of the water column where larvae were counted";
    String long_name "Height Cm";
    String units "centimeters (cm)";
  }
  middepth_cm {
    Float64 _FillValue NaN;
    Float64 actual_range 0.5, 19.5;
    String bcodmo_name "depth";
    String description "The middepth of the section of the water column in which larvae were counted";
    String long_name "Middepth Cm";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/DEPH/";
    String units "centimeters (cm)";
  }
  larvae_count {
    Byte _FillValue 127;
    Byte actual_range 0, 63;
    String bcodmo_name "count";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "The number of Olympia oyster larvae occupying that area of the water column during the count";
    String long_name "Larvae Count";
    String units "larvae";
  }
  proportion_larvae {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.738;
    String bcodmo_name "relative_abund";
    String description "Proportion of total Olympia oyster larvae occupying that area of the water column during the count";
    String long_name "Proportion Larvae";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Collection & Larval Rearing
 
\\u00a0We collected adult Olympia oysters (Ostrea lurida) from Fidalgo Bay in
June 2017 and maintained them in a sea table with continuous flowing seawater
heated to 19-20\\u00b0C at the Shannon Point Marine Center. We fed adult
oysters were fed concentrated algae once a day (Shellfish Diet, Reed
Mariculture) and utilized banjo-style filters (60-m) attached to the outflow
pipes of the sea table to catch released O. lurida larvae. We then collected
and reared larvae at 12\\u00b0C in 3-L jars (2 individuals mL-1). Each jar of
larvae received a 50% water change with 0.35-m filtered sea water and were fed
Isochrysis galbana algae (50,000 cells mL-1) daily.
 
\\u00a0Experimental Design
 
\\u00a0To measure the effect of pH conditions on the vertical distribution of
larvae we established three experimental pycnocline treatments within clear
plexiglass water columns (2.5cm x 2.5cm x 30cm): (1) ambient water (400ppm) in
the top layer and acidic water in the bottom layer (1500ppm), (2) ambient
water (400ppm) in both top and bottom layers, and (3) acidic water (1500ppm)
in the top layer and ambient water (400ppm) in the bottom layer. Each water
layer was 60-mL of water and filled the column 10-cm high, so when each
experimental treatment was established it filled the column to 20-cm. We
established the experimental treatments by increasing the density of seawater
in the bottom layer by 0.003-0.005 g ml-1 using PercollTM GE Healthcare
(Podolsky & Emlet 1993). Experimental treatment water was kept at 12\\u00b0C
and pre-equilibrated to the desired pCO2 level and density. We also included
blue food coloring (1 drop per 100-mL) to the dense bottom layer to more
easily visualize the density layers while establishing experimental
treatments. We set-up four replicate columns for each experimental treatment
making twelve columns total per experiment.
 
\\u00a0On the day of each experiment, we incubated the experimental treatment
columns in clear plexiglass water baths connected to a Fisher Scientific
Isotemp recirculating water bath to maintain treatment temperature at
12\\u00b0C throughout the experiment. We carefully injected 150 larvae by
syringe into the bottom 2-cm of each column with no more than 2-mL of their
culture water. Olympia oyster larvae are highly phototactic (personal
observations), so larvae were kept in the dark and we video recorded their
vertical positions under infrared light two times: the first time at 10
minutes of acclimation in the columns and the second time at 30 minutes of
acclimation in the columns. To record, we used an infrared uEye camera
equipped with Edmund Optics VIS-NIR Lens mounted on a motorized stand. We
later counted by eye the number of larvae per centimeter area of each column
from the videos.";
    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 
"Oyster larvae vertical distribution 
   lab expts, July 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 "2019-01-17T13:32:22Z";
    String date_modified "2019-09-25T19:43:40Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.753058.1";
    String history 
"2020-12-05T17:32:24Z (local files)
2020-12-05T17:32:24Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_753058.das";
    String infoUrl "https://www.bco-dmo.org/dataset/753058";
    String institution "BCO-DMO";
    String instruments_0_acronym "in-situ incubator";
    String instruments_0_dataset_instrument_description "Used to maintain treatment temperature during experiment";
    String instruments_0_dataset_instrument_nid "753069";
    String instruments_0_description "A device on shipboard or in the laboratory that holds water samples under controlled conditions of temperature and possibly illumination.";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/82/";
    String instruments_0_instrument_name "In-situ incubator";
    String instruments_0_instrument_nid "494";
    String instruments_0_supplied_name "Fisher Scientific Isotemp Circulating Water Bath";
    String instruments_1_acronym "camera";
    String instruments_1_dataset_instrument_description "uEye camera equipped with Edmund Optics VIS-NIR Lens mounted on a motorized stand";
    String instruments_1_dataset_instrument_nid "753070";
    String instruments_1_description "All types of photographic equipment including stills, video, film and digital systems.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/311/";
    String instruments_1_instrument_name "Camera";
    String instruments_1_instrument_nid "520";
    String instruments_1_supplied_name "uEye video camera";
    String keywords "bco, bco-dmo, biological, chemical, column, column_name, count, count_id, data, dataset, date, dmo, erddap, height, height_cm, larvae, larvae_count, management, middepth, middepth_cm, name, oceanography, office, preliminary, proportion, proportion_larvae, time, trial";
    String license "https://www.bco-dmo.org/dataset/753058/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/753058";
    String param_mapping "{'753058': {'middepth_cm': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/753058/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 "Oyster larvae vertical distribution data collected from a laboratory water column experiments to investigate the behavioral effects of ocean acidification on Olympia oyster larvae (Ostrea lurida), July 2017.";
    String title "Oyster larvae vertical distribution data collected from laboratory water column experiments on the behavioral effects of ocean acidification on Olympia oyster larvae (Ostrea lurida), July 2017";
    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
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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