BCO-DMO ERDDAP
Accessing BCO-DMO data
log in    
Brought to you by BCO-DMO    

ERDDAP > tabledap > Make A Graph ?

Dataset Title:  Porites coral calcification responses to declining \u03a9ar in a CO2
manipulation experiment in Palau versus the calcification responses observed in
ten other studies of massive Porites corals
Subscribe RSS
Institution:  BCO-DMO   (Dataset ID: bcodmo_dataset_705881)
Information:  Summary ? | License ? | ISO 19115 | Metadata | Background (external link) | Data Access Form | Files
 
Graph Type:  ?
X Axis: 
Y Axis: 
Color: 
-1+1
 
Constraints ? Optional
Constraint #1 ?
Optional
Constraint #2 ?
       
       
       
       
       
 
Server-side Functions ?
 distinct() ?
? ("Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.Hover here to see a list of options. Click on an option to select it.")
 
Graph Settings
Marker Type:   Size: 
Color: 
Color Bar:   Continuity:   Scale: 
   Minimum:   Maximum:   N Sections: 
Y Axis Minimum:   Maximum:   
 
(Please be patient. It may take a while to get the data.)
 
Optional:
Then set the File Type: (File Type information)
and
or view the URL:
(Documentation / Bypass this form ? )
    [The graph you specified. Please be patient.]

 

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 {
  reference {
    String bcodmo_name "reference_paper";
    String description "Reference for publication where data first appear";
    String long_name "Reference";
    String units "unitless";
  }
  site {
    String bcodmo_name "site";
    String description "Location of study";
    String long_name "Site";
    String units "unitless";
  }
  study_type {
    String bcodmo_name "brief_desc";
    String description "Type of study (laboratory, field, transplant)";
    String long_name "Study Type";
    String units "unitless";
  }
  omega_AR {
    Float32 _FillValue NaN;
    Float32 actual_range 0.77, 7.56;
    String bcodmo_name "OM_ar";
    String description "Saturation state of aragonite";
    String long_name "Omega AR";
    String units "unitless";
  }
  standardized_calcification_anom {
    Float32 _FillValue NaN;
    Float32 actual_range -2.72, 2.75;
    String bcodmo_name "calcification";
    Float64 colorBarMaximum 10.0;
    Float64 colorBarMinimum -10.0;
    String description "Standardized anomaly of calcification rate, which were calculated for each study by subtracting the measured calcification rate of each coral from the overall calcification mean and dividing by the standard deviation";
    String long_name "Standardized Calcification Anom";
    String units "unitless";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv";
    String acquisition_description 
"Coral collection:\\u00a0Coral plugs were collected in December 2012 from
massive\\u00a0Porites\\u00a0colonies at a naturally low-\\u03a9ar\\u00a0reef site
(7.324 N, 134.493 E; mean \\u03a9ar\\u00a0= 2.3; n = 78) and a naturally
high-\\u03a9ar\\u00a0reef site (7.268 N, 134.522 E; mean \\u03a9ar\\u00a0= 3.7; n
= 75). At each reef site, small skeletal cores (diameter = 3.5 cm) were
removed from massive colonies (one core per colony) at 2-3m depth using
underwater pneumatic drills, and cores were cut with a lapidary table saw to
approximately 1 cm below the tissue layer. The plugs were affixed to nylon
square base screws with marine epoxy, secured to egg crate racks, and returned
to their original reefs to allow the corals to recover from the coring
procedure. All corals survived two months of recovery on the reef and on all
corals living tissue had fully overgrown the sides of the plugs so that no
underlying skeleton was exposed. Corals were recovered in February 2013.
 
\\u00a0
 
CO2 manipulation experiment:\\u00a0Corals from two reefs were cultured at three
CO2 levels for eight weeks in March to May 2013 (n = 10 corals per treatment,
n = 60 corals total). The corals were individually incubated in independently
manipulated plastic cups (volume = 750 ml) to increase statistical power. Cups
were placed within a large, temperature-controlled water bath. The corals were
maintained at mean (\\u00b1 SD) temperatures of 29.4C \\u00b1 0.1C. Light was
provided by LED aquarium lights (Coralife) at average levels of 334 \\u00b1 48
umol photons m-2 s-1 (measured by an underwater quantum sensor, LI-COR) on a
12h:12h light:dark schedule. Corals were fed live Artemia brine shrimp larvae
every other evening by pipetting 1 ml of concentrated brine shrimp in filtered
seawater into each cup. Coral cups were cleaned weekly to prevent algae
overgrowth.
 
Mean pH (total scale)/\\u03a9ar levels for the three treatment conditions were
7.98/3.0, 7.83/2.3, and 7.60/1.5. In each coral cup, carbon system chemistry
was regulated using a combination of flow-through pre-equilibrated water and
bubbling of mixed air/CO2 gas. Incoming seawater (filtered to 0.35 um) from
the reef was aerated and split into three header tanks. In the low-CO2 header
tank, water was bubbled with air. In the mid-CO2 and high-CO2 header tanks,
CO2 levels were regulated by a pH controller (Drs. Foster and Smith) connected
to a solenoid valve that introduced CO2 gas into the header tank through a
column diffuser. Water was siphoned from the three header tanks into each
coral cup at a rate of approximately 375 ml per hour. Each coral cup was also
bubbled with either compressed air (low CO2 treatment) or mixed compressed air
and CO2 gas (mid and high CO2 treatment) controlled by pairs of mass flow
controllers (Aalborg Instruments) at approximately 200 ml per minute. Low
alkalinity levels in the source water to the Palau International Coral Reef
Center (drawn from within the lower-alkalinity Rock Islands) prevented
\\u03a9ar in the low-CO2 condition (\\u03a9ar = 3.0) from reaching values that
were as high as those measured on the barrier reef site (\\u03a9ar = 3.7).
 
To characterize the carbonate chemistry in each cup, total alkalinity (TA),
pH, temperature, and salinity were measured weekly. Spectrophotometric pH
measurements were made with 2 mM m-Cresol purple indicator dye using a
spectrometer with a 100 mm flow cell (Ocean Optics, mean precision = 0.005)
following procedures in Clayton and Byrne (1993) and Dickson et al. (2007) and
using the equation of Liu et al. (2011). Samples for TA were collected in 20
ml glass vials and poisoned with saturated mercuric chloride. Automated gran
titrations for TA were run on duplicate 1 ml samples using a Metrohm Titrando
808 and 730 Sample Changer (mean precision = 4 umol/kg), and TA values were
standardized to certified reference materials obtained from Andrew Dickson
[Scripps Institution of Oceanography (Dickson, 2001)]. Salinity was measured
in each cup using an YSI salinity probe, and temperatures were measured using
an Omega thermocouple (accuracy = 0.1 degree C). Full CO2 system parameters
were calculated from temperature, salinity, TA, and pH using CO2SYS (Lewis and
Wallace, 1998) with the constants of Mehrbach et al. (1973) as refit by
Dickson and Millero (1987).
 
Coral calcification analysis:\\u00a0Calcification rates were measured using
both buoyant weight (Davies, 1989) and alkalinity anomaly (Chisholm and
Gattuso, 1991) techniques. Buoyant weights for each coral were collected at
the beginning of the experiment, after three weeks in experimental CO2
conditions, and then weekly during weeks four to eight. Corals were weighed
using a balance with a weigh-below hook (Sartorius GC803S), which allows for
beneath-balance weighing of coral plugs that remain entirely submerged in
experimental cups maintained at treatment \\u03a9ar levels. Wet weight data
were converted to dry weights using an aragonite density of 2.93 grams per
cubic centimeter\\u00a0and the density of seawater determined using a standard
of known weight and density. Repeated buoyant weight measurements on the same
coral yielded mean precision estimates of \\u00b1 0.03 g.
 
Day/night alkalinity depletion experiments were conducted at the end of the
eight-week experiment. Water flow to each coral cup was stopped during this
time but gas bubbling was continued in order to maintain pH levels. Samples
for TA were collected for each coral cup at the beginning and end of two four-
hour periods (one four-hour period during the day and one at night).
Alkalinity depletion incubations were simultaneously run in control cups
containing only filtered seawater (n=3 per experiment).\\u00a0Because the net
change in TA values in control cups was within analytical precision (mean = 3
umol per kilogram), coral calcification was assumed to be the only process
impacting the alkalinity in the cups, where two moles of alkalinity were
consumed for every one mole of calcium carbonate produced. TA pre and post
incubation was determined following the titration procedure described in
section 2.2 with samples run in triplicate.
 
Calcification rates for both buoyant weight and alkalinity anomaly
measurements were normalized to coral tissue surface areas. Surface areas were
measured following the general procedure for aluminum foil wrapping, in which
the weight of aluminum foil needed to cover the entire surface of the coral
skeleton is converted to area using a calibration curve (Marsh 1970). However,
skeletons were wrapped with electrical tape instead of aluminum foil because
the use of electric tape provided tighter control and minimization of tape
overlap, which can significantly overestimate surface area. The area of each
coral skeleton occupied by living tissue was wrapped in electrical tape that
was subsequently carefully trimmed to eliminate any overlay.\\u00a0The weight
of tape used to cover the coral tissue for each skeleton were converted to
surface areas using a weight-to-area calibration, where ten pieces of
electrical tape of known area were weighed to build a weight-per-unit area
curve.\\u00a0Replicated electrical tape surface area estimates on ten coral
skeletons produced a mean precision of 0.43 square cm, or ~1% of calculated
surface areas.";
    String awards_0_award_nid "520400";
    String awards_0_award_number "OCE-1220529";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1220529";
    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 
"Comparison of coral calcification response in Palau Porites coral to reponses observed in other studies 
 PI: Anne Cohen (WHOI) 
 Contact: Hannah Barkley (WHOI) 
 Version: 30 June 2017";
    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 "2017-06-23T20:27:40Z";
    String date_modified "2019-08-02T18:44:50Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.705881.2";
    String history 
"2020-08-06T13:21:51Z (local files)
2020-08-06T13:21:51Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_705881.das";
    String infoUrl "https://www.bco-dmo.org/dataset/705881";
    String institution "BCO-DMO";
    String instruments_0_acronym "LI-COR LI-192 PAR";
    String instruments_0_dataset_instrument_description "A LI-COR underwater quantum sensor measured light on a 12h:12h light:dark schedule.";
    String instruments_0_dataset_instrument_nid "705886";
    String instruments_0_description 
"The LI-192 Underwater Quantum Sensor (UWQ) measures underwater or atmospheric Photon Flux Density (PPFD) (Photosynthetically Available Radiation from 360 degrees) using a Silicon Photodiode and glass filters encased in a waterproof housing.  The LI-192 is cosine corrected and features corrosion resistant, rugged construction for use in freshwater or saltwater and pressures up to 800 psi (5500 kPa, 560 meters depth). Typical output is in um s-1 m-2.  The LI-192 uses computer-tailored filter glass to achieve the desired quantum response. Calibration is traceable to NIST.  The LI-192 serial numbers begin with UWQ-XXXXX.  LI-COR has been producing Underwater Quantum Sensors since 1973.  

These LI-192 sensors are typically listed as LI-192SA to designate the 2-pin connector on the base of the housing  and require an Underwater Cable (LI-COR part number 2222UWB) to connect to the pins on the Sensor and connect to a data recording device. 

The LI-192 differs from the LI-193 primarily in sensitivity and angular response.

193:  Sensitivity: Typically 7 uA per 1000 umol s-1 m-2 in water.  Azimuth: < ± 3% error over 360° at 90° from normal axis.  Angular Response: < ± 4% error up to ± 90° from normal axis  

192: Sensitivity: Typically 4 uA per 1000 umol s-1 m-2 in water.  Azimuth: < ± 1% error over 360° at 45° elevation.  Cosine Correction: Optimized for underwater and atmospheric use.

(www.licor.com)";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0120/";
    String instruments_0_instrument_name "LI-COR LI-192 PAR Sensor";
    String instruments_0_instrument_nid "475";
    String instruments_0_supplied_name "LI-COR underwater quantum sensor LI-192";
    String instruments_1_acronym "Manual Biota Sampler";
    String instruments_1_dataset_instrument_description "At each reef site, small skeletal cores (diameter = 3.5 cm) were removed from massive colonies (one core per colony) at 2–3mdepth using underwater pneumatic drills.";
    String instruments_1_dataset_instrument_nid "705885";
    String instruments_1_description "Manual Biota Sampler indicates that a sample was collected in situ by a person, possibly using a hand-held collection device such as a jar, a net or their hands.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/90/";
    String instruments_1_instrument_name "Manual Biota Sampler";
    String instruments_1_instrument_nid "565";
    String instruments_1_supplied_name "pneumatic drill";
    String instruments_2_acronym "Automatic titrator";
    String instruments_2_dataset_instrument_description "Automated gran titrations for TA were run on duplicate 1 ml samples using a Metrohm Titrando 808 and 730 Sample Changer.";
    String instruments_2_dataset_instrument_nid "705889";
    String instruments_2_description "Instruments that incrementally add quantified aliquots of a reagent to a sample until the end-point of a chemical reaction is reached.";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB12/";
    String instruments_2_instrument_name "Automatic titrator";
    String instruments_2_instrument_nid "682";
    String instruments_2_supplied_name "Metrohm Titrando 808 and 730 Sample Changer";
    String instruments_3_acronym "Spectrophotometer";
    String instruments_3_dataset_instrument_description "Spectrophotometric pH measurements were made with 2 mM m-Cresol purple indicator dye using a spectrometer with a 100 mm flow cell (Ocean Optics, mean precision = 0.005).";
    String instruments_3_dataset_instrument_nid "705888";
    String instruments_3_description "An instrument used to measure the relative absorption of electromagnetic radiation of different wavelengths in the near infra-red, visible and ultraviolet wavebands by samples.";
    String instruments_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB20/";
    String instruments_3_instrument_name "Spectrophotometer";
    String instruments_3_instrument_nid "707";
    String instruments_3_supplied_name "Ocean Optics pH spectrophotometer";
    String instruments_4_acronym "MFC";
    String instruments_4_dataset_instrument_description "Each coral cup was also bubbled with either compressed air or mixed compressed air and CO2 gas controlled by pairs of mass flow controllers (Aalborg Instruments).";
    String instruments_4_dataset_instrument_nid "705887";
    String instruments_4_description "Mass Flow Controller (MFC) - A device used to measure and control the flow of fluids and gases";
    String instruments_4_instrument_name "Mass Flow Controller";
    String instruments_4_instrument_nid "712";
    String instruments_4_supplied_name "Aalborg Instruments mass flow controllers GFCS-010554 and GFCS-011067";
    String instruments_5_acronym "Scale";
    String instruments_5_dataset_instrument_description "Corals were weighed using a balance with a weigh-below hook (Sartorius GC803S).";
    String instruments_5_dataset_instrument_nid "705890";
    String instruments_5_description "An instrument used to measure weight or mass.";
    String instruments_5_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB13/";
    String instruments_5_instrument_name "Scale";
    String instruments_5_instrument_nid "714";
    String instruments_5_supplied_name "Sartorius GC803S scale
";
    String keywords "anomaly, bco, bco-dmo, biological, calcification, chemical, data, dataset, dmo, erddap, management, oceanography, office, omega, omega_AR, preliminary, reference, site, standardized, standardized_calcification_anom, study, study_type, type";
    String license "https://www.bco-dmo.org/dataset/705881/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/705881";
    String param_mapping "{'705881': {}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/705881/parameters";
    String people_0_affiliation "Woods Hole Oceanographic Institution";
    String people_0_affiliation_acronym "WHOI";
    String people_0_person_name "Anne L Cohen";
    String people_0_person_nid "51428";
    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";
    String people_1_person_name "Hannah Barkley";
    String people_1_person_nid "560803";
    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 "Shannon Rauch";
    String people_2_person_nid "51498";
    String people_2_role "BCO-DMO Data Manager";
    String people_2_role_type "related";
    String project "Coral Reef Ecosystem OA Impact";
    String projects_0_acronym "Coral Reef Ecosystem OA Impact";
    String projects_0_description 
"text copied from the NSF award abstract: 
Much of our understanding of the impact of ocean acidification on coral reef calcification comes from laboratory manipulation experiments in which reef organisms are removed from their natural habitat and reared under conditions of calcium carbonate saturation (Omega) predicted for the tropical oceans at the end of this century. By comparison, there is a paucity of in situ data describing the sensitivity of coral reef ecosystems to changes in calcium carbonate saturation. Yet emerging evidence suggests there may be critical differences between the calcification response of organisms in culture and the net calcification response of a coral reef ecosystem, to the same degree of change in calcium carbonate saturation. In the majority of cases, the sensitivity of net reef calcification to changing calcium carbonate saturation is more severe than laboratory manipulation experiments predict. Clearly, accurate predictions of the response of coral reef ecosystems to 21st century ocean acidification will depend on a robust characterization of ecosystem-scale responses and an understanding of the fundamental processes that shape them. Using existing data, the investigators show that the sensitivity of coral reef ecosystem calcification to Delta calcium carbonate saturation conforms to the empirical rate equation R=k(Aragonite saturation state -1)n, which also describes the relationship between the rate of net abiogenic CaCO3 precipitation (R) and the degree of Aragonite supersaturation (Aragonite saturation state-1). By implication, the net ecosystem calcification (NEC) response to ocean acidification is governed by fundamental laws of physical chemistry and is potentially predictable across space and time. When viewed this way, the existing, albeit sparse, dataset of NEC reveals distinct patterns that, if verified, have important implications for how different coral reef ecosystems will respond to 21st century ocean acidification. The investigators have outlined a research program designed to build on this proposition. The project expands the currently sparse dataset of ecosystem-scale observations at four strategically placed reef sites: 2 sites in the Republic of Palau, Caroline Islands, Micronesia, western Pacific Ocean; a third at Dongsha Atoll, Pratas Islands, South China Sea; and the fourth at Kingman Reef, US Northern Line Islands, 6 deg. 23 N, 162 deg. 25 W.  The four selected sites will allow investigators to test the following hypotheses: (1) The sensitivity (\"n\" in the rate equation) of coral reef ecosystem calcification to Delta Aragonite saturation state decreases with decreasing Aragonite saturation state. By implication, the rate at which reef calcification declines will slow as ocean acidification progresses over the course of this century. (2) The energetic status of the calcifying community is a key determinant of absolute rates of net ecosystem calcification (\"k\" in the rate equation), which, combined with n, defines the Aragonite saturation state value at which NEC approaches zero. By implication, the shift from net calcification to net dissolution will be delayed in healthy, energetically replete coral reef ecosystems and accelerated in perturbed, energetically depleted ecosystems. and (3) The calcification response of individual colonies of dominant reef calcifiers (corals and algae) is weaker than the measured ecosystem-scale response to the same change in Aragonite saturation state. By implication, processes not adequately captured in laboratory experiments, such as bioerosion and dissolution, will play an important role in the coral reef response to ocean acidification.
Broader Impacts: Ocean acidification threatens the livelihoods of 500 million people worldwide who depend on coral reefs to provide habitable and agricultural land, food, building materials, coastal protection and income from tourism. Yet data emerging from ocean acidification (OA) studies point to critical gaps in our knowledge of reef ecosystem-scale responses to OA that currently limit our ability to predict the timing and severity of its impact on different reefs in different parts of the world. Using existing data generated by the investigators and others, this project will address a series of related hypotheses, which, if verified by the research, will have an immediate, direct impact on predictions of coral reef resilience in a high CO2 world. This project brings together expertise in coral reef biogeochemistry, chemical oceanography and physical oceanography to focus on a problem that has enormous societal, economic and conservation relevance. In addition to sharing the resultant data via BCO-DMO, project data will also be contributed to the Ocean Acidification International Coordination Centre (OA-ICC) data collection hosted at the PANGAEA Open Access library (http://www.pangaea.de).";
    String projects_0_end_date "2015-08";
    String projects_0_geolocation "Republic of Palau, Caroline Islands, Micronesia, western Pacific Ocean; Dongsha Atoll, Pratas Islands, South China Sea; Kingman Reef, US Northern Line Islands, 6 deg. 23 N, 162 deg. 25 W";
    String projects_0_name "Toward Predicting the Impact of Ocean Acidification on Net Calcification by a Broad Range of Coral Reef Ecosystems: Identifying Patterns and Underlying Causes";
    String projects_0_project_nid "520413";
    String projects_0_start_date "2012-09";
    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 "Porites coral calcification responses to declining \\u03a9ar in a CO2 manipulation experiment in Palau versus the calcification responses observed in ten other studies of massive Porites corals.";
    String title "Porites coral calcification responses to declining \\u03a9ar in a CO2 manipulation experiment in Palau versus the calcification responses observed in ten other studies of massive Porites corals";
    String version "2";
    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.


 
ERDDAP, Version 2.02
Disclaimers | Privacy Policy | Contact