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Dataset Title:  [Dendraster_Beh_OA_Expt2017] - Experimental counts and locations within
columns of depth-varying pH to investigate the behavioral effects of ocean
acidification on sand dollar larvae (Dendraster excentricus), July 2017 (RUI:
Will climate change cause 'lazy larvae'? Effects of climate stressors on larval
behavior and dispersal)
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Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_752953)
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 {
  date {
    String bcodmo_name "date_local";
    String description "Date of experiment formatted as yyyy-mm-dd";
    String long_name "Date";
    String source_name "date";
    String time_precision "1970-01-01";
    String units "unitless";
  }
  larvae_stage {
    String bcodmo_name "stage";
    String description "Stage of Dendraster excentricus larvae used in the experiment: 4-arm or 6-arm stage plutei";
    String long_name "Larvae Stage";
    String units "unitless";
  }
  larvae_treatment {
    String bcodmo_name "treatment";
    String description "Indicates the pCO2 treatment condition larvae were reared in from the time of spawning to the time of the experiment. \"acidic\" condition was treatment water maintained at 1500ppm and \"neutral\" condition was treatment water maintained at 400ppm.";
    String long_name "Larvae Treatment";
    String units "unitless";
  }
  column_treatment {
    String bcodmo_name "treatment";
    String description "Identifies the experimental treatment of the water column that larvae were placed into. The first word indicates the pCO2 condition of the water layer at the top of the column and the second word indicates the pCO2 condition of the water layer at the bottom of the column. \"Acidic\" water was bubbled to be 1500ppm and the \"neutral\" water was bubbled to be 400ppm.";
    String long_name "Column Treatment";
    String units "unitless";
  }
  column_name {
    String bcodmo_name "sample";
    String description "code for: (1) the pCO2 treatment of the water in the top of the column (A or N); (2) the pCO2 treatment the larvae were reared within (A or N); (3) the pCO2 treatment of the water in the bottom of the column (A or N); and (4) the replicate number. \"A\"= acidic water that was bubbled to be 1500 pCO2; \"N\" = neutral water that was bubbled to be 400 pCO2";
    String long_name "Column Name";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P02/current/ACYC/";
    String units "unitless";
  }
  count_id {
    String bcodmo_name "replicate";
    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;
    String _Unsigned "false";
    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";
  }
  middepth_cm {
    Float64 _FillValue NaN;
    Float64 actual_range 0.5, 19.5;
    String bcodmo_name "depth";
    String description "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";
  }
  larvae_count {
    Byte _FillValue 127;
    String _Unsigned "false";
    Byte actual_range 0, 108;
    String bcodmo_name "count";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "The number of larvae occupying that area of the water column during the count";
    String long_name "Larvae Count";
    String units "# of larvae";
  }
  proportion_larvae {
    Float32 _FillValue NaN;
    Float32 actual_range 0.0, 0.912;
    String bcodmo_name "relative_abund";
    String description "Proportion of total 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 
"Spawning and fertilization:
 
We collected adult sand dollars (D. excentricus) from Semiahmoo Bay, WA, on
July 7, 2017, and maintained them in 14\\u00b0C continuous flowing seawater at
the Shannon Point Marine Center. On July 12, 2017, 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.
 
Larval Rearing
 
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. Each jar of larvae
received a water change with pre-equilibrated 0.35-m filtered ambient and
acidic seawater and fed the larvae D. tertiolecta (6,000 cells ml-1) daily.
Pre-equilibrated ambient and acidic water was held in tanks within the same
12\\u00b0C incubator as the rearing jars.
 
Experimental Design
 
We conducted two behavioral experiments; one when the larvae were 4-arm
pleutei and one when the larvae were 6-armed pleutei.
 
To 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.
 
Columns were positioned in a randomized order along the table of a walk-in
incubator set to 12\\u00b0C. Once columns were in position and treatments were
established, 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. Larvae were
given 10 minutes in darkness to acclimate before we performed the first count
of vertical positions of larvae in each water column. At 30 minutes of
acclimation, we performed a second count of vertical positions of larvae in
each column. For each larval count, we used a small hand-held flashlight and
counted by eye the number of larvae occupying each centimeter of the water
column beginning at the bottom and moving up to the top. We did these counts
in the dark, so only one column received direct light from our small
flashlight at a time to reduce the influence of light on the larvae\\u2019s
behavior.";
    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 Behavior 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 "2019-01-16T19:36:20Z";
    String date_modified "2019-09-25T19:31:41Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.752953.1";
    String history 
"2024-11-08T05:42:25Z (local files)
2024-11-08T05:42:25Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_752953.das";
    String infoUrl "https://www.bco-dmo.org/dataset/752953";
    String institution "BCO-DMO";
    String keywords "bco, bco-dmo, biological, chemical, column, column_name, column_treatment, count, count_id, data, dataset, date, dmo, erddap, height, height_cm, larvae, larvae_count, larvae_stage, larvae_treatment, management, middepth, middepth_cm, name, oceanography, office, preliminary, proportion, proportion_larvae, stage, time, treatment";
    String license "https://www.bco-dmo.org/dataset/752953/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/752953";
    String param_mapping "{'752953': {'middepth_cm': 'master - depth'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/752953/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 "Data collected from a laboratory water column experiment to investigate the behavioral effects of ocean acidification on sand dollar larvae (Dendraster excentricus).";
    String title "[Dendraster_Beh_OA_Expt2017] - Experimental counts and locations within columns of depth-varying pH to investigate the behavioral effects of ocean acidification on sand dollar larvae (Dendraster excentricus), July 2017 (RUI: Will climate change cause 'lazy larvae'? Effects of climate stressors on larval behavior and dispersal)";
    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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