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Dataset Title:	Calcification Rates and Biomass of 4 Coral Species, 2 Temperatures and 2 pCO2 Levels from Experiments at LTER site in Moorea, French Polynesia, 2011 (OA_ Corals project)
Institution:	BCO-DMO   (Dataset ID: bcodmo_dataset_641479)
Range:	longitude = -149.826 to -149.826°E, latitude = -17.4907 to -17.4907°N
Information:	Summary | License | ISO 19115 | Metadata | Background | Subset | Data Access Form | Files

 

Graph Type:  lines linesAndMarkers markers sticks vectors X Axis:  latitude longitude tank calcification biomass Y Axis:  latitude longitude tank calcification biomass Color:  latitude longitude tank calcification biomass   Constraints Optional Constraint #1 Optional Constraint #2 location latitude longitude species pCO2 temp tank treatment calcification biomass     != =~ <= >= = < >     != =~ <= >= = < >     location latitude longitude species pCO2 temp tank treatment calcification biomass     != =~ <= >= = < >     != =~ <= >= = < >     location latitude longitude species pCO2 temp tank treatment calcification biomass     != =~ <= >= = < >     != =~ <= >= = < >     location latitude longitude species pCO2 temp tank treatment calcification biomass     != =~ <= >= = < >     != =~ <= >= = < >     location latitude longitude species pCO2 temp tank treatment calcification biomass     != =~ <= >= = < >     != =~ <= >= = < >       Server-side Functions  distinct() orderBy orderByClosest orderByCount orderByLimit orderByMax orderByMin orderByMinMax orderByMean (" location latitude longitude species pCO2 temp tank treatment calcification biomass location latitude longitude species pCO2 temp tank treatment calcification biomass location latitude longitude species pCO2 temp tank treatment calcification biomass location latitude longitude species pCO2 temp tank treatment calcification biomass ")   Graph Settings Marker Type:  None Plus X Dot Square Filled Square Circle Filled Circle Up Triangle Filled Up Triangle  Size:  3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 Color:  Color Bar:  BlackBlueWhite BlackGreenWhite BlackRedWhite BlackWhite BlueWhiteRed BlueWideWhiteRed LightRainbow Ocean OceanDepth Rainbow Rainbow2 Rainfall ReverseRainbow RedWhiteBlue RedWhiteBlue2 RedWideWhiteBlue Spectrum Topography TopographyDepth WhiteBlueBlack WhiteGreenBlack WhiteRedBlack WhiteBlack YellowRed KT_algae KT_amp KT_balance KT_curl KT_deep KT_delta KT_dense KT_gray KT_haline KT_ice KT_matter KT_oxy KT_phase KT_solar KT_speed KT_tempo KT_thermal KT_turbid  Continuity:  Continuous Discrete  Scale:  Linear Log    Minimum:   Maximum:   N Sections:  2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 Draw land mask:  under over Y Axis Minimum:   Maximum:    Ascending Descending Linear Log   Redraw the Graph (Please be patient. It may take a while to get the data.)   Optional: Then set the File Type: .asc .csv .csvp .csv0 .dataTable .das .dds .dods .esriCsv .fgdc .geoJson .graph .help .html .htmlTable .iso19115 .itx .json .jsonlCSV1 .jsonlCSV .jsonlKVP .mat .nc .ncHeader .ncCF .ncCFHeader .ncCFMA .ncCFMAHeader .nccsv .nccsvMetadata .ncoJson .odvTxt .subset .tsv .tsvp .tsv0 .wav .xhtml .kml .smallPdf .pdf .largePdf .smallPng .png .largePng .transparentPng (File Type information) and or view the URL: (Documentation / Bypass this form )

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
 s {
  location {
    String bcodmo_name "site";
    String description "location of experiment";
    String long_name "Location";
    String units "unitless";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 _FillValue NaN;
    Float64 actual_range -17.4907, -17.4907;
    String axis "Y";
    String bcodmo_name "latitude";
    Float64 colorBarMaximum 90.0;
    Float64 colorBarMinimum -90.0;
    String description "latitude; north is positive";
    String ioos_category "Location";
    String long_name "Latitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 _FillValue NaN;
    Float64 actual_range -149.826, -149.826;
    String axis "X";
    String bcodmo_name "longitude";
    Float64 colorBarMaximum 180.0;
    Float64 colorBarMinimum -180.0;
    String description "longitude; east is positive";
    String ioos_category "Location";
    String long_name "Longitude";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
    String standard_name "longitude";
    String units "degrees_east";
  }
  species {
    String bcodmo_name "species";
    String description "species used in the study: Ap (Acropora pulchra); Mipl (Millepora platyphylla); MP (massive Porites spp.) ; Pm (Pocillopora meandrina)";
    String long_name "Species";
    String units "unitless";
  }
  pCO2 {
    String bcodmo_name "pCO2";
    String description "tank CO2 concentration levels: ACO2 for ambient (408 micro-atm) and HCO2 for high (913 micro-atm)";
    String long_name "P CO2";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/PCO2C101/";
    String units "unitless";
  }
  temp {
    String bcodmo_name "temperature";
    String description "tank temperature: AT=ambient (28.0 C); HT=high (30.1 C)";
    String long_name "Temperature";
    String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
    String units "unitless";
  }
  tank {
    Byte _FillValue 127;
    Byte actual_range 1, 11;
    String bcodmo_name "tank";
    String description "tank number";
    String long_name "Tank";
    String units "unitless";
  }
  treatment {
    String bcodmo_name "treatment";
    String description "AT-ACO2 = ambient temperature; ambient CO2; AT-HCO2 = ambient temperature-high CO2; HT-ACO2 = high temperature-ambient CO2; HT-HCO2 = high temperature-high CO2";
    String long_name "Treatment";
    String units "unitless";
  }
  calcification {
    Float32 _FillValue NaN;
    Float32 actual_range 0.215, 1.644;
    String bcodmo_name "unknown";
    String description "calcification rate: ACO2 for ambient (408 µatm) and HCO2 for high (913 µatm) CO2 concentration levels";
    String long_name "Calcification";
    String units "cm-2 day-1";
  }
  biomass {
    Float32 _FillValue NaN;
    Float32 actual_range 0.238, 8.622;
    String bcodmo_name "biomass";
    String description "coral biomass";
    String long_name "Biomass";
    String units "mg mg-1";
  }
 }
  NC_GLOBAL {
    String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
    String acquisition_description 
"Calcifying cnidarians were collected from the back reef (~ 4 m depth) on the
north shore of Moorea, French Polynesia, during January and April 2011.
Fragments of Acropora pulchra, Pocillopora meandrina, massive Porites spp.
(15% P. lobata and 85% P. lutea [Edmunds 2009]), and Millepora platyphylla
were used to evaluate the effect of pCO2 and temperature on calcification.
Massive Porites spp. and M. platyphylla were sampled using a pneumatic drill
(McMaster-Carr, part #27755A17) fitted with a 4.1 cm diamond tip hole saw
(McMaster-Carr, part #6930A43). The hole saw was used to remove cores ~ 4 cm
diameter and ~ 3.8 cm long from adult colonies, and the holes were filled with
non-toxic modeling clay (Van Aken Part #10117). To increase the likelihood
that cores were genetically distinct, one core was taken from each colony,
with sampled colonies distributed over 3 km of reef.
 
Freshly collected cores were placed in bags filled with seawater and
transported to the Richard B. Gump South Pacific Research Station where they
were immersed in tanks supplied with a constant flow of seawater from
Cook\\u2019s Bay. Cores were prepared by removing excess skeleton extending >
1.5 cm below the living tissue, and attaching the cores to numbered polyvinyl
chloride (PVC) pipes (4.4 cm diameter and 2.0 cm long) with epoxy (Z Spar,
#A788). To eliminate the possibility of fouling organisms accessing freshly
cut skeleton, bare skeleton was covered in epoxy. A plastic screw was epoxied
to the bottom of each core that was later used to attach them upright in racks
placed in the tanks used for incubations. Following preparation, cores were
returned to ~ 4 m depth in the back reef, where they were left to recover for
6 weeks. Recovery was evaluated from the presence of healthy c 124 oral tissue
covering the formerly damaged edge of the skeleton.
 
Single branches of A. pulchra and P. meandrina were cut from colonies using
bone shears, with each colony sampled once. Sampled colonies were ~ 10 m apart
to increase the likelihood that they were genetically distinct. Branches were
transported to the Richard B. Gump South Pacific Research Station where they
were immersed in flowing seawater. Similar to the methods used for coral
cores, branches of A. pulchra and P. meandrina were attached using epoxy to
pieces of PVC pipe to make nubbins (Birkeland 1976). Care was taken to cover
freshly fractured skeleton with epoxy, and to avoid damaging coral tissue
during preparation. A plastic screw was attached to the base of the nubbins
and used to hold them upright in plastic racks. Prior to beginning the
treatments, coral cores and nubbins were placed in 150 L tanks under ambient
conditions of 28.0\\u00b0C, 370 micro-atm pCO2 and where illuminated with 400 W
metal halide lamps (True 10,000K Hamilton Technology, Gardena, CA to an
irradiance of ~ 600 micro-mol quanta m2 s-1 (measured with a 4p LI-193 quantum
sensor and a LiCor LI-1400 meter) for 5 d to recover from the preparation
procedure. The sampling method limited tissue damage to A. pulchra and P.
meandrina, and therefore a shorter acclimation period was needed in comparison
to massive Porites spp. and M. platyphylla.
 
Experimental conditions and maintenance
 
Treatments were created in 8 tanks (Aqua Logic, San Diego), each holding 150 L
of seawater and regulated independently for temperature, light, and pCO2.
Tanks were operated as closed146 circuit systems with filtered seawater (50
micro-m) from Cook\\u2019s Bay, with circulation provided by a pump (Rio 8HF,
2,082 L h-1). Light was supplied 147 by 400 W metal halide lamps (True 10,000K
Hamilton Technology, Gardena, CA) at ~ 560 micro-mol quanta m-2s-1 (measured
with a 4p LI-193 quantum sensor and a LiCor LI-1400 meter) in the range of
photosynthetically active radiation (PAR, 400-700 nm). Lights were operated on
a 12hr light-12hr dark photoperiod, beginning at 06:00 hrs and ending at 18:00
hrs. Temperatures were maintained at 28.0\\u00b0C, which corresponded to the
ambient seawater temperature in the back reef when the study was conducted,
and 30.1\\u00b0C which is close to the maximum temperature in this habitat
(Putnam and Edmunds 2011). pCO2 treatments contrasted ambient conditions (~
408 micro-atm) and 913 micro-atm pCO2, with the elevated value expected to
occur within 100 y under the \\\"stabilization without overshoot\\\"
representative concentration pathway (RCP 6.0) (van Vuuren et al. 2011). pCO2
treatments were created by bubbling ambient air or a mixture of ambient air
and pure CO2 that was blended continually and monitored using an infrared gas
analyzer (IRGA model S151, Qubit Systems). A solenoid-controlled, gas
regulation system (Model A352, Qubit Systems, Ontario, Canada) regulated the
flow of CO2 and air, with pCO2 logged on a PC running LabPro software (Vemier
Software and Technology). Ambient air and the elevated pCO2 mixture were
supplied at ~ 10-15 L min-1 to treatment tanks using pumps (Gast pump
DOA-P704-AA, see Edmunds 2011).
 
The temperatures and pCO2 levels created four treatments with two tanks
treatment-1: ambient temperature-ambient pCO2 (AT-ACO2), ambient temperature-
high pCO2 (AT-HCO2), high temperature-ambient pCO2 (HT-ACO2) and high
temperature-high pCO2 (HT-HCO2). Treatment conditions were monitored daily,
with temperature measured at 08:00, 12:00 and 18:00 hrs using a digital
thermometer (Fisher Scientific model #150778, \\u00b1 0.05 \\u00b0C), and light
intensities at 12:00 hrs using a Li-Cor LI-193 sensor attached t 170 o a
LI-1400 meter. Seawater within each tank was replaced at 200 ml/min with
filtered seawater (50 micro-m) pumped from Cook\\u2019s Bay.";
    String awards_0_award_nid "54987";
    String awards_0_award_number "OCE-0417412";
    String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=0417412";
    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 awards_1_award_nid "55110";
    String awards_1_award_number "OCE-1041270";
    String awards_1_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1041270";
    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 "David L. Garrison";
    String awards_1_program_manager_nid "50534";
    String awards_2_award_nid "520630";
    String awards_2_award_number "OCE-1026851";
    String awards_2_data_url "http://www.nsf.gov/awardsearch/showAward?AWD_ID=1026851";
    String awards_2_funder_name "NSF Division of Ocean Sciences";
    String awards_2_funding_acronym "NSF OCE";
    String awards_2_funding_source_nid "355";
    String awards_2_program_manager "David L. Garrison";
    String awards_2_program_manager_nid "50534";
    String cdm_data_type "Other";
    String comment 
"Calcification and biomass 
     LTER-Moorea, 2011 
   P. Edmunds, D. Brown (CSU-Northridge) 
    
   version: 2016-04-04 
   These data were published in Brown & Edmunds (2016) Marine Biology, Fig. 1";
    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 "2016-03-29T20:37:33Z";
    String date_modified "2016-04-13T23:48:22Z";
    String defaultDataQuery "&time<now";
    String doi "10.1575/1912/bco-dmo.641945";
    Float64 Easternmost_Easting -149.826;
    Float64 geospatial_lat_max -17.4907;
    Float64 geospatial_lat_min -17.4907;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -149.826;
    Float64 geospatial_lon_min -149.826;
    String geospatial_lon_units "degrees_east";
    String history 
"2024-04-18T01:49:20Z (local files)
2024-04-18T01:49:20Z https://erddap.bco-dmo.org/tabledap/bcodmo_dataset_641479.das";
    String infoUrl "https://www.bco-dmo.org/dataset/641479";
    String institution "BCO-DMO";
    String instruments_0_acronym "LI-COR LI-193 PAR";
    String instruments_0_dataset_instrument_description "4p LI-193 quantum sensor";
    String instruments_0_dataset_instrument_nid "641489";
    String instruments_0_description "The LI-193 Underwater Spherical Quantum Sensor uses a Silicon Photodiode and glass filters encased in a waterproof housing to measure PAR (in the 400 to 700 nm waveband) in aquatic environments. Typical output is in micromol s-1 m-2.  The LI-193 Sensor gives an added dimension to underwater PAR measurements as it measures photon flux from all directions. This measurement is referred to as Photosynthetic Photon Flux Fluence Rate (PPFFR) or Quantum Scalar Irradiance. This is important, for example, when studying phytoplankton, which utilize radiation from all directions for photosynthesis. LI-COR began producing Spherical Quantum Sensors in 1979; serial numbers for the LI-193 begin with SPQA-XXXXX (licor.com).";
    String instruments_0_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L22/current/TOOL0458/";
    String instruments_0_instrument_name "LI-COR LI-193 PAR Sensor";
    String instruments_0_instrument_nid "432";
    String instruments_1_acronym "in-situ incubator";
    String instruments_1_dataset_instrument_description "150 L tanks";
    String instruments_1_dataset_instrument_nid "641490";
    String instruments_1_description "A device on shipboard or in the laboratory that holds water samples under controlled conditions of temperature and possibly illumination.";
    String instruments_1_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/82/";
    String instruments_1_instrument_name "In-situ incubator";
    String instruments_1_instrument_nid "494";
    String instruments_2_acronym "Water Temp Sensor";
    String instruments_2_dataset_instrument_nid "641491";
    String instruments_2_description "General term for an instrument that measures the temperature of the water with which it is in contact (thermometer).";
    String instruments_2_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/134/";
    String instruments_2_instrument_name "Water Temperature Sensor";
    String instruments_2_instrument_nid "647";
    String instruments_3_acronym "Automatic titrator";
    String instruments_3_dataset_instrument_description "Open cell potentiometric titrator (Model T50, Mettler-Toledo, Columbus, OH) fitted with a DG115-SC pH probe (Mettler-Toledo, Columbus, OH)";
    String instruments_3_dataset_instrument_nid "641492";
    String instruments_3_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_3_instrument_external_identifier "https://vocab.nerc.ac.uk/collection/L05/current/LAB12/";
    String instruments_3_instrument_name "Automatic titrator";
    String instruments_3_instrument_nid "682";
    String instruments_4_acronym "Light Meter";
    String instruments_4_dataset_instrument_description "LiCor LI-1400 meter";
    String instruments_4_dataset_instrument_nid "641488";
    String instruments_4_description "Light meters are instruments that measure light intensity. Common units of measure for light intensity are umol/m2/s or uE/m2/s (micromoles per meter squared per second or microEinsteins per meter squared per second). (example: LI-COR 250A)";
    String instruments_4_instrument_name "Light Meter";
    String instruments_4_instrument_nid "703";
    String instruments_5_acronym "Conductivity Meter";
    String instruments_5_dataset_instrument_description "YSI 3100 conductivity meter";
    String instruments_5_dataset_instrument_nid "641493";
    String instruments_5_description "Conductivity Meter - An electrical conductivity meter (EC meter) measures the electrical conductivity in a solution. Commonly used in hydroponics, aquaculture and freshwater systems to monitor the amount of nutrients, salts or impurities in the water.";
    String instruments_5_instrument_name "Conductivity Meter";
    String instruments_5_instrument_nid "719";
    String instruments_6_acronym "sonicator";
    String instruments_6_dataset_instrument_description "Ultrasonic dismembrator (Fisher model 216 15-338-550; fitted with a 3.2 mm diameter probe, Fisher 15-338-67)";
    String instruments_6_dataset_instrument_nid "641494";
    String instruments_6_description "Instrument that applies sound energy to agitate particles in a sample.";
    String instruments_6_instrument_name "ultrasonic cell disrupter";
    String instruments_6_instrument_nid "528691";
    String keywords "bco, bco-dmo, biological, biomass, calcification, carbon, carbon dioxide, chemical, co2, data, dataset, dioxide, dmo, erddap, latitude, longitude, management, oceanography, office, pCO2, preliminary, species, tank, temperature, treatment";
    String license "https://www.bco-dmo.org/dataset/641479/license";
    String metadata_source "https://www.bco-dmo.org/api/dataset/641479";
    Float64 Northernmost_Northing -17.4907;
    String param_mapping "{'641479': {'lat': 'master - latitude', 'lon': 'master - longitude'}}";
    String parameter_source "https://www.bco-dmo.org/mapserver/dataset/641479/parameters";
    String people_0_affiliation "California State University Northridge";
    String people_0_affiliation_acronym "CSU-Northridge";
    String people_0_person_name "Peter J. Edmunds";
    String people_0_person_nid "51536";
    String people_0_role "Principal Investigator";
    String people_0_role_type "originator";
    String people_1_affiliation "California State University Northridge";
    String people_1_affiliation_acronym "CSU-Northridge";
    String people_1_person_name "Darren  J Brown";
    String people_1_person_nid "523715";
    String people_1_role "Student";
    String people_1_role_type "related";
    String people_2_affiliation "California State University Northridge";
    String people_2_affiliation_acronym "CSU-Northridge";
    String people_2_person_name "Darren  J Brown";
    String people_2_person_nid "523715";
    String people_2_role "Contact";
    String people_2_role_type "related";
    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 "OA_Corals";
    String projects_0_acronym "OA_Corals";
    String projects_0_description 
"While coral reefs have undergone unprecedented changes in community structure in the past 50 y, they now may be exposed to their gravest threat since the Triassic. This threat is increasing atmospheric CO2, which equilibrates with seawater and causes ocean acidification (OA). In the marine environment, the resulting decline in carbonate saturation state (Omega) makes it energetically less feasible for calcifying taxa to mineralize; this is a major concern for coral reefs. It is possible that the scleractinian architects of reefs will cease to exist as a mineralized taxon within a century, and that calcifying algae will be severely impaired. While there is a rush to understand these effects and make recommendations leading to their mitigation, these efforts are influenced strongly by the notion that the impacts of pCO2 (which causes Omega to change) on calcifying taxa, and the mechanisms that drive them, are well-known. The investigators believe that many of the key processes of mineralization on reefs that are potentially affected by OA are only poorly known and that current knowledge is inadequate to support the scaling of OA effects to the community level. It is vital to measure organismal-scale calcification of key taxa, elucidate the mechanistic bases of these responses, evaluate community scale calcification, and finally, to conduct focused experiments to describe the functional relationships between these scales of mineralization.
This project is a 4-y effort focused on the effects of Ocean Acidification (OA) on coral reefs at multiple spatial and functional scales. The project focuses on the corals, calcified algae, and coral reefs of Moorea, French Polynesia, establishes baseline community-wide calcification data for the detection of OA effects on a decadal-scale, and builds on the research context and climate change focus of the Moorea Coral Reef LTER.
This project is a hypothesis-driven approach to compare the effects of OA on reef taxa and coral reefs in Moorea. The PIs will utilize microcosms to address the impacts and mechanisms of OA on biological processes, as well as the ecological processes shaping community structure. Additionally, studies of reef-wide metabolism will be used to evaluate the impacts of OA on intact reef ecosystems, to provide a context within which the experimental investigations can be scaled to the real world, and critically, to provide a much needed reference against which future changes can be gauged.
The following publications and data resulted from this project:
2016    Edmunds P.J. and 15 others.  Integrating the effects of ocean acidification across functional scales on tropical coral reefs.  Bioscience (in press Feb 2016) **not yet available**
2016    Comeau S, Carpenter RC, Lantz CA, Edmunds PJ.  Parameterization of the response of calcification to temperature and pCO2 in the coral Acropora pulchra and the alga Lithophyllum kotschyanum.  Coral Reefs (in press Feb 2016)
2016    Brown D., Edmunds P.J.  Differences in the responses of three scleractinians and the hydrocoral Millepora platyphylla to ocean acidification.  Marine Biology (in press Feb 2016) **available soon**MarBio. 2016: calcification and biomassMarBio. 2016: tank conditions
2016    Comeau, S., Carpenter, R.C., Edmunds, P.J.  Effects of pCO2 on photosynthesis and respiration of tropical scleractinian corals and calcified algae.  ICES Journal of Marine Science doi:10.1093/icesjms/fsv267
2015    Evensen NR, Edmunds PJ, Sakai K.  Effects of pCO2 on the capacity for spatial competition by the corals Montipora aequituberculata and massive Porites spp. Marine Ecology Progress Series 541: 123–134. doi: 10.3354/meps11512MEPS 2015: chemistryMEPS 2015: field surveyMEPS 2015: linear extensionDownload data for this publication (Excel file)
2015    Comeau S., Lantz C. A., Edmunds P. J., Carpenter R. C. Framework of barrier reefs threatened by ocean acidification. Global Change Biology doi: 10.1111/gcb.13023
2015    Comeau, S., Carpenter, R. C., Lantz, C. A., and Edmunds, P. J. Ocean acidification accelerates dissolution of experimental coral reef communities, Biogeosciences, 12, 365-372, doi:10.5194/bg-12-365-2015.calcification rates - flume exptcarbonate chemistry - flume expt
External data repository: http://doi.pangaea.de/10.1594/PANGAEA.847986
2014    Comeau S, Carpenter RC, Edmunds PJ.  Effects of irradiance on the response of the coral Acropora pulchra and the calcifying alga Hydrolithon reinboldii to temperature elevation and ocean acidification.  Journal of Experimental Marine Biology and Ecology (in press)
2014    Comeau S, Carpenter RC, Nojiri Y, Putnam HM, Sakai K, Edmunds PJ.  Pacific-wide contrast highlights resistance of reef calcifiers to ocean acidification.  Royal Society of London (B) 281: doi.org/10.1098/rspb.2014.1339
External data repository: http://doi.pangaea.de/10.1594/PANGAEA.832834
2014    Comeau, S., Edmunds, P. J., Lantz, C. A., & Carpenter, R. C. Water flow modulates the response of coral reef communities to ocean acidification. Scientific Reports, 4. doi:10.1038/srep06681calcification rates - flume exptcarbonate chemistry - flume expt
2014    Comeau, S., Edmunds, P. J., Spindel, N. B., & Carpenter, R. C. Fast coral reef calcifiers are more sensitive to ocean acidification in short-term laboratory incubations. Limnology and Oceanography, 59(3), 1081–1091. doi:10.4319/lo.2014.59.3.1081algae_calcificationcoral_calcification
External data repository: http://doi.pangaea.de/10.1594/PANGAEA.832584
2014    Comeau S, Edmunds PJ, Spindel NB, Carpenter RC.  Diel pCO2 oscillations modulate the response of the coral Acropora hyacinthus to ocean acidification. Marine Ecology Progress Series 453: 28-35
2013    Comeau, S, Carpenter, RC, Edmunds PJ. Response to coral reef calcification: carbonate, bicarbonate and proton flux under conditions of increasing ocean acidification. Proceedings of the Royal Society of London 280: doi.org/10.1098/rspb.2013.1153
2013    Comeau S, Carpenter RC. Edmunds PJ.  Effects of feeding and light intensity on the response of the coral Porites rus to ocean acidification.  Marine Biology 160: 1127-1134
External data repository: http://doi.pangaea.de/10.1594/PANGAEA.829815
2013    Comeau, S., Edmunds, P. J., Spindel, N. B., Carpenter, R. C. The responses of eight coral reef calcifiers to increasing partial pressure of CO2 do not exhibit a tipping point. Limnol. Oceanogr. 58, 388–398.algae_calcificationcoral_calcification
External data repository: http://doi.pangaea.de/10.1594/PANGAEA.833687
2012    Comeau, S., Carpenter, R. C., & Edmunds, P. J. Coral reef calcifiers buffer their response to ocean acidification using both bicarbonate and carbonate. Proceedings of the Royal Society B: Biological Sciences, 280(1753), 20122374. doi:10.1098/rspb.2012.2374carbonate_chemistrylight_dark_calcificationmean_calcification
External data repository: http://doi.pangaea.de/10.1594/PANGAEA.832834";
    String projects_0_end_date "2014-12";
    String projects_0_geolocation "Moorea, French Polynesia";
    String projects_0_name "The effects of ocean acidification on the organismic biology and community ecology of corals, calcified algae, and coral reefs";
    String projects_0_project_nid "2242";
    String projects_0_start_date "2011-01";
    String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
    String publisher_type "institution";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing -17.4907;
    String standard_name_vocabulary "CF Standard Name Table v55";
    String subsetVariables "location,latitude,longitude";
    String summary 
"Area-normalized calcification (mg cm-2 d-1) and biomass normalized
calcification (mg mg-1) for Pocillopora meandrina, massive Porites spp.,
Acropora pulchra and Millepora platyphylla, as a function of pCO2 (408
\\u00b5atm versus 913 \\u00b5atm) and temperature (28.0\\u00b0C and 30.1\\u00b0C),
collected in Moorea 2011.
 
Related Reference:  
 Darren Brown, Peter J. Edmunds. Differences in the responses of three
scleractinians and the hydrocoral Millepora platyphylla to ocean
acidification. Marine Biology, 2016 (in press).
 
Related Dataset:  
[MarBio. 2016: tank conditions](\\\\https://www.bco-dmo.org/dataset/641759\\\\)";
    String title "Calcification Rates and Biomass of 4 Coral Species, 2 Temperatures and 2 pCO2 Levels from Experiments at LTER site in Moorea, French Polynesia, 2011 (OA_Corals project)";
    String version "1";
    Float64 Westernmost_Easting -149.826;
    String xml_source "osprey2erddap.update_xml() v1.3";
  }
}

 

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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 Data Access Protocol (DAP) and its selection constraints.

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.

• (easy) You can get data by using the dataset's Data Access Form or Subset form. They make the URL for you.
• (easy) You can make a graph or map by using the dataset's Make A Graph form. It makes the URL for you.
• (not hard) You can bypass the forms and get the data or make a graph or map by generating the URL by hand or with a computer program or script.

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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