Measured and calculated geochemistry values and uncertainty for water samples taken from the water column of Celestun Lagoon, Yucatan, Mexico in May of 2015
Project
Program
| Contributors | Affiliation | Role |
|---|---|---|
| Paytan, Adina | University of California-Santa Cruz (UCSC) | Principal Investigator, Contact |
| Herrera-Silveira, Jorge A. | Unidad Mérida del Centro de Investigación y de Estudios Avanzados (CINVESTAV) | Co-Principal Investigator |
| You, Chen-Feng | National Cheng Kung University | Co-Principal Investigator |
| Liu, Hou-Chun Arrien | National Cheng Kung University | Scientist |
| Street, Joseph H. | University of California-Santa Cruz (UCSC) | Scientist |
| Wang, Tzu-Hao David | National Cheng Kung University | Scientist |
| Hardage, Kyle H. | University of California-Santa Cruz (UCSC) | Student, Data Manager |
| York, Amber D. | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Abstract
Location: Celestún Biosphere Reserve, Yucatan, Mexico. 20.88 N 90.36 E depth 0.5 m.
Collection: Data collected from dinghy. No vessel name. June 2009 and May 2015.
Water samples from 2015 were filtered (0.45 um) and analyzed for salinity, pH, and elemental concentrations. Analytical methods involved MC-ICPMS for boron and strontium isotopes, with careful sample preparation, including microsublimation for δ11B, Sr-spec resin for 87Sr/86Sr, and isotope ratio mass spectrometry for δ18O and δ13C. Elemental concentrations (B, Mg, Ca) were analyzed using ICPMS. Reproducibility was verified using established standards.
Additional methods citations:
Boron isotope method: Wang et al. (2020).
Strontium isotope method: Liu et al. (2012).
pH and borate equations: Foster et al. (2016).
Related dataset descriptions (See section "Related Datasets" for data citations):
The water sample data in this dataset were collected concurrently with the May 2015 sampling event in BCO-DMO dataset https://www.bco-dmo.org/dataset/941327 which contains isotope data, elemental concentrations, and carbon content collected from the foraminifera Ammonia parkinsoniana and sediments in Celestun Lagoon, Yucatan, Mexico in June 2009 and May 2015.
This study and Paytan (2021, BCO-DMO dataset https://www.bco-dmo.org/dataset/564766) both derive groundwater from the same regional aquifer in Yucatan, Mexico, and both studies review the effects of low-pH springs on saturation and calcification of organisms. They are different sample material.
The sediment cores and assemblages in Hardage et al. (2021, doi:10.25921/qkc1-yw35) at NOAA provide the sample material for the geochemistry reported in this study (foraminifera, bulk sediment, physical observations). The Hardage et al. (2021) dataset also contains additional lithology and geochemistry that can be paired with these new data for interested parties.
Instrument and equipment list:
LDPE bottles: water samples were collected in acid-washed LDPE bottles for trace metals.
rubber septum glass vials: water samples were collected in ashed glass bottles for nutrients.
0.5 mL micro-centrifuge tubes: used to store crushed foraminifera for cleaning.
Yellow Springs Instrument Model 63 handheld sonde and pH probe.
Neptune multi-collector inductively coupled plasma mass spectrometer (MC-ICPMS).
Lachat QuikChem 8000.
UIC Carbon Coulometer Analyzer (CM150).
Orion 950 Titrator.
Thermo Scientific Element XR ICPMS.
ThermoFinnigan Delta Plus XP isotope ratio mass spectrometer.
Element data were corrected for blank, drift, mass bias, and calcium matrix effects.
Boron isotopes were corrected using the standard-sample-standard bracket technique to correct drift and bias across each individual sample.
pKB* and δ11B borate were calculated using Branson (2024) CBSYST with implementation of Hain et al. (2015) speciation of Ca and Mg.
The MarChemSpec (Clegg & Turner, 2023) model uses measured inputs of salinity, temperature, DIC, TA, [B], [Mg], [Ca], [NO3-], [PO4-], and [SiO44-]. Other major ion concentrations were estimated by applying LOESS smoothing regression (R Software version 4.3.1) to salinity versus [Cl-], [SO42-], and [Sr2+] data from a lagoon transect in Young et al., (2008) to account for minor non-linear variations at lower salinity. [Na] and [K] concentrations were estimated from the LOESS-derived [Cl-] using [X] = [Cl]estimated/[Cl]Millero * [X]Millero, where [Cl]Millero = 536 mM and X is typical seawater [Na] = 456 mM or [K] = 10.2 mM (Millero et al., 2008). These estimates apply for mixed lagoon waters only. For endmember waters (well water, seawater, large spring), values from were taken directly from Young et al. (2008) and assumed to reflect expected concentrations in the identical sampling locations in this study. Charge imbalances from MarChemSpec calculations were corrected by adjusting [Na], chosen because it was not measured and because its seawater concentration dominates charge balance adjustments relative to [K]. [Na] absolute adjustment ranged from about -22 to +19 mM (< 10 % of [Na]). MarChemSpec calculated pH on the total scale using Pitzer constants.
Software:
MarChemSpec software (https://marchemspec.org/wp/software/) has been archived at Zenodo (Clegg & Turner, 2023, doi: 10.5281/ZENODO.8373046).
CBSYST software (https://github.com/oscarbranson/cbsyst) Version 0.4.9 has been archived at Zenodo (Branson et al., 2024, doi: 10.5281/ZENODO.14185784).
See the "Parameters" section for more details applicable to each data column in this dataset including how MarChemSpec and CBSYST software was used.
Note about aggregated data (means, standard deviations):
The averages are from the instruments themselves, not from true replicates. They typically take 4 to 10 readings and average the result, depending on the instrument. Since these are mass spectrometers counting individual ions, this averaging is necessary to reduce noise. For parameters calculated using CBSYST, mean and standard deviation are derived from 10,000 Monte Carlo realizations.
* Data table from submitted file "Hardage_boron_water_parameter_values.csv" (file supplied by email on 2024-12-06) was imported into the BCO-DMO data system for this dataset. Values "-999" imported as missing data values.
** In the BCO-DMO data system missing data identifiers are displayed according to the format of data you access. For example, in csv files it will be blank (null) values. In Matlab .mat files it will be NaN values. When viewing data online at BCO-DMO, the missing value will be shown as blank (null) values.
* Datetime with timezone (UTC) added as column from local dates and times provided in GMT-6 (Central Standard Time in Yucatan, Mexico).
* Table row order sorted by DateTime.
| File |
|---|
941377_v1_water-samples.csv (Comma Separated Values (.csv), 6.71 KB) MD5:c35891b6af6afdb0bbaf4aa0754a91bb Primary data file for dataset ID 941377, version 1 |
Relationship Description: Datasets collected as part of the same study. Both contain data from samples collected from Celestun Lagoon, Yucatan, Mexico in May of 2015.
Relationship Description: Low-pH spring studies on the eastern coast of the Yucatan Peninsula. Both derive groundwater from the same regional aquifer in Yucatan, Mexico, and both studies review the effects of low-pH springs on saturation and calcification of organisms. They used different sample material.
| Parameter | Description | Units |
| site | Site code for water sample. | unitless |
| lat | Site latitude in WGS84; north is positive. | decimal degrees |
| long | Site longitude in WGS84; east is negative. | decimal degrees |
| distance | Distance along the central lagoon axis from the northern fringe mangrove to the southern lagoon opening to the ocean. | kilometers (km) |
| region | Biogeographic region of the lagoon identified by Hardage et al. (2022). J. Paleolim. 10.8 km is the dividing point. | unitless |
| date | Date of sample collection in ISO 8601 yyyy-mm-dd format. Time Zone GMT-6 (Central Standard Time in Yucatan, Mexico) | unitless |
| time | Time of sample collection in ISO 8601 format HH:MM. | unitless |
| ISO_DateTime_UTC | DateTime with time zone of sample collection in ISO 8601 format (UTC). | unitless |
| tide | Tide position based on the nearest tide gauge in Progreso, Yucatan, Mexico. | unitless |
| sample | Water sample type. Valid values are Lagoon Water, Seawater, Spring Water, Well Water. | unitless |
| temperature | Water column temperature measured in situ. | degrees Celsius |
| salinity | Water column salinity measured with a salinometer against KCl. | practical salinity units (PSU) |
| pH | Water column pH, measured in situ using standards on the National Bureau of Standards scale and converted to total scale using pH = value - 0.14. | total scale |
| DIC | Water column dissolved inorganic carbon. | micromoles per kilogram (umol/kg) |
| DIC_2sd | Water column dissolved inorganic carbon 2 standard deviations of replicate measurements. | micromoles per kilogram (umol/kg) |
| TA | Water column total alkalinity. Uncertainty determined as 45 based on the Dickson Standard Batch 121. | micromoles per kilogram (umol/kg) |
| NO3 | Water column dissolved nitrate as N. | micromoles per kilogram (umol/kg) |
| NO3_2sd | Water column dissolved nitrate as N 2 standard deviations of replicate measurements. | micromoles per kilogram (umol/kg) |
| PO4 | Water column dissolved phosphate. Uncertainty determined as +- 0.02 based on lab standards. | micromoles per kilogram (umol/kg) |
| SiO4 | Water column dissolved silica. | micromoles per kilogram (umol/kg) |
| SiO4_2sd | Water column dissolved silica 2 standard deviations of replicate measurements. | micromoles per kilogram (umol/kg) |
| Ca_conc | Water column dissolved calcium concentration. Uncertainty determined as +- 0.2 from 2SD of lab standard gravimetric solutions. | millimolar (mM) |
| Mg_conc | Water column dissolved magnesium concentration. Uncertainty determined as +- 0.12 from 2SD of lab standard gravimetric solutions. | millimolar (mM) |
| B_conc | Water column dissolved boron concentration. Uncertainty determined as +- 31.6 from 2SD of lab standard gravimetric solutions. | micromolar (uM) |
| Sr8786 | Water column radiogenic strontium ratio 87Sr/86Sr. | unitless |
| Sr8786_2sd | Water column radiogenic strontium ratio 87Sr/86Sr 2 standard deviations of replicate measurements. | unitless |
| d18O | Water column oxygen-18. | per mil (0/00) |
| d18O_2sd | Water column oxygen-18, 2 standard deviations based on replicate standards. | per mil (0/00) |
| d11B | Water column bulk boron-11. | per mil (0/00) |
| d11B_2sd | Water column bulk boron-11 2 standard deviations of replicate standards. | per mil (0/00) |
| pCO2_mean | Water column partial pressure of carbon dioxide calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | microatmospheres (uatm) |
| pCO2_2sd | Water column partial pressure of carbon dioxide uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST Version 0.4.9 (Branson et al., 2024). | microatmospheres (uatm) |
| CO2_mean | Water column dissolved carbon dioxide concentration calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | micromoles per kilogram (umol/kg) |
| CO2_sd | Water column dissolved carbon dioxide concentration uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST Version 0.4.9 (Branson et al., 2024). | micromoles per kilogram (umol/kg) |
| CO3_mean | Water column dissolved carbonate ion concentration calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | micromoles per kilogram (umol/kg) |
| CO3_2sd | Water column dissolved carbonate ion concentration uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST. | micromoles per kilogram (umol/kg) |
| HCO3_mean | Water column dissolved bicarbonate ion concentration calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | micromoles per kilogram (umol/kg) |
| HCO3_2sd | Water column dissolved bicarbonate ion concentration uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST. | micromoles per kilogram (umol/kg) |
| omegaC_mean | Water column calcite saturation state, calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 monte carlo simulations. | unitless |
| omegaC_2sd | Water column calcite saturation state uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST. | unitless |
| delta_carb | Water column degree of calcite saturation, calculated from CO3_mean - (CO3_mean / omegaC_mean). | micromoles per kilogram (umol/kg) |
| delta_carb_err | Water column delta_carb propagated error calculated as delta_carb_err = sqrt(CO3_sd^2 + (CO3_mean/omegaC_mean*omegaC_sd)^2) | micromoles per kilogram (umol/kg) |
| pKB_mean | Stoichiometric dissociation (equilibrium) constant for the borate-boric acid system. Calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | unitless |
| pKB_2sd | Stoichiometric dissociation (equilibrium) constant uncertainty for the borate-boric acid system, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST Version 0.4.9 (Branson et al., 2024). | unitless |
| BOH4_mean | Water column dissolved borate, calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | micromoles per kilogram (umol/kg) |
| BOH4_2sd | Water column dissolved borate uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST Version 0.4.9 (Branson et al., 2024). | micromoles per kilogram (umol/kg) |
| d11B_BOH4_mean | Water column boron-11 ratio of borate ion,calculated using CBSYST Version 0.4.9 (Branson et al., 2024). Mean of 10,000 Monte Carlo simulations. | per mil (0/00) |
| d11B_BOH4_2sd | Water column boron-11 ratio of borate ion uncertainty, calculated as 2 * standard deviation of 10,000 Monte Carlo simulations of CBSYST Version 0.4.9 (Branson et al., 2024). | per mil (0/00) |
| Cl_est | Water column dissolved chloride. Estimated from LOESS smoothing of Cl transect data in Tables 1 and 4 of Young et al. (2008). Marine Chemistry. https://doi.org/10.1016/j.marchem.2007.07.010 | millimolar (mM) |
| SO4_est | Water column dissolved sulfate. Estimated from LOESS smooethin of SO4 transect data in Tables 1 and 4 of Young et al. (2008).Marine Chemistry. https://doi.org/10.1016/j.marchem.2007.07.010 | millimolar (mM) |
| Sr_est | Water column dissolved strontium. Estimated from LOESS smoothing of Sr data in Tables 1 and 4 of Young et al. (2008).Marine Chemistry. https://doi.org/10.1016/j.marchem.2007.07.010 | micromolar (uM) |
| K_est | Water column dissolved potassium. Estimated from Na/Cl ratio of seawater using Cl data herein and seawater [K] from Millero et al. (2008). Deep Sea Research Part 1. https://doi.org/10.1016/j.dsr.2007.10.001 | millimolar (mM) |
| Na_est | Water column dissolved sodium. Estimated from Na/Cl ratio of seawater using Cl data herein and seawater [Na] from Millero et al. (2008). Deep Sea Research Part 1. https://doi.org/10.1016/j.dsr.2007.10.001 | millimolar (mM) |
| adjusted_Na | Water column dissolved sodium, determined by adjusting column (Na) to reduce column (charge_imbalance) value within MarChemSpec (Clegg & Turner, 2023). | millimolar (mM) |
| charge_imbalance | Solution charge imbalance resulting from MarChemSpec (Clegg & Turner, 2023) calculation of pH using parameters in this file. | moles |
| pH_MarcChemSpec | Water column pH calculated from MarChemSpec (Clegg & Turner, 2023) using Pitzer constants. | total scale |
| Dataset-specific Instrument Name | Orion 950 Titrator |
| Generic Instrument Name | Automatic titrator |
| Generic Instrument Description | Instruments that incrementally add quantified aliquots of a reagent to a sample until the end-point of a chemical reaction is reached. |
| Dataset-specific Instrument Name | |
| Generic Instrument Name | Bottle |
| Dataset-specific Description | LDPE bottles: water samples were collected in acid-washed LDPE bottles for trace metals.
Rubber septum glass vials: water samples were collected in ashed glass bottles for nutrients. |
| Generic Instrument Description | A container, typically made of glass or plastic and with a narrow neck, used for storing drinks or other liquids. |
| Dataset-specific Instrument Name | UIC Carbon Coulometer Analyzer (CM150, UIC, Inc.) |
| Generic Instrument Name | CM150 Total Carbon Analyzer |
| Dataset-specific Description | Instrument housed at UCSC Marine Analytical Lab. CM150 (UIC, Inc.) Carbon Analysis (TC/TIC/TOC) By Combustion, Acidification And Coulometric Detection. |
| Generic Instrument Description | The CM150 Total Carbon Analyzer, made by UIC, Inc., is a complete analytical system capable of measuring total carbon, total organic carbon and total inorganic carbon in solid and/or liquid samples. (From https://www.uicinc.com/cm150-carbon-analysis/). |
| Dataset-specific Instrument Name | Carlo Erba elemental analyzer IRMS |
| Generic Instrument Name | Elemental Analyzer |
| Generic Instrument Description | Instruments that quantify carbon, nitrogen and sometimes other elements by combusting the sample at very high temperature and assaying the resulting gaseous oxides. Usually used for samples including organic material. |
| Dataset-specific Instrument Name | Thermo Scientific Element XR ICPMS |
| Generic Instrument Name | Inductively Coupled Plasma Mass Spectrometer |
| Generic Instrument Description | An ICP Mass Spec is an instrument that passes nebulized samples into an inductively-coupled gas plasma (8-10000 K) where they are atomized and ionized. Ions of specific mass-to-charge ratios are quantified in a quadrupole mass spectrometer. |
| Dataset-specific Instrument Name | ThermoFinnigan Delta Plus XP isotope ratio mass spectrometer. |
| Generic Instrument Name | Isotope-ratio Mass Spectrometer |
| Generic Instrument Description | The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer). |
| Dataset-specific Instrument Name | |
| Generic Instrument Name | Isotope-ratio Mass Spectrometer |
| Generic Instrument Description | The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer). |
| Dataset-specific Instrument Name | ThermoScientific MAT-253 dual-inlet isotope ratio mass spectrometer |
| Generic Instrument Name | Isotope-ratio Mass Spectrometer |
| Generic Instrument Description | The Isotope-ratio Mass Spectrometer is a particular type of mass spectrometer used to measure the relative abundance of isotopes in a given sample (e.g. VG Prism II Isotope Ratio Mass-Spectrometer). |
| Dataset-specific Instrument Name | Lachat QuikChem 8000 |
| Generic Instrument Name | Lachat QuikChem 8000 flow injection analyzer and Ion Chromatography (IC) system |
| Generic Instrument Description | The Lachat QuikChem 8000 can operate flow injection analysis and ion chromatography simultaneously and independently on the same instrument platform. Instrument includes sampler, dilutor, sampling pump, electronics unit, and data station. Analysis takes 20-60 seconds, with a sample throughput of 60-120 samples per hour. Measurements are in the range of parts per trillion to parts per hundred. |
| Dataset-specific Instrument Name | |
| Generic Instrument Name | Multi Collector Inductively Coupled Plasma Mass Spectrometer |
| Dataset-specific Description | Neptune multi-collector inductively coupled plasma mass spectrometer (MC-ICPMS). |
| Generic Instrument Description | A Multi Collector Inductively Coupled Plasma Mass Spectrometry (MC-ICPMS) is a type of mass spectrometry where the sample is ionized in a plasma (a partially ionized gas, such as Argon, containing free electrons) that has been generated by electromagnetic induction. A series of collectors is used to detect several ion beams simultaneously.
A MC-ICPMS is a hybrid mass spectrometer that combines the advantages of an inductively coupled plasma source and the precise measurements of a magnetic sector multicollector mass spectrometer. The primary advantage of the MC-ICPMS is its ability to analyze a broader range of elements, including those with high ionization potential that are difficult to analyze by Thermal Ionization Mass Spectrometry (TIMS). The ICP source also allows flexibility in how samples are introduced to the mass spectrometer and allows the analysis of samples introduced either as an aspirated solution or as an aerosol produced by laser ablation. |
| Dataset-specific Instrument Name | Yellow Springs Instrument Model 63 handheld sonde and pH probe |
| Generic Instrument Name | Multi Parameter Portable Meter |
| Dataset-specific Description | YSI Model 63 Handheld pH, Conductivity, Salinity and Temperature System. |
| Generic Instrument Description | An analytical instrument that can measure multiple parameters, such as pH, EC, TDS, DO and temperature with one device and is portable or hand-held. |
| Dataset-specific Instrument Name | |
| Generic Instrument Name | Piston Corer |
| Dataset-specific Description | Piston, Bolivia, Livingstone corers: coring devices used to collect sediments. |
| Generic Instrument Description | The piston corer is a type of bottom sediment sampling device. A long, heavy tube is plunged into the seafloor to extract samples of mud sediment. A piston corer uses a "free fall" of the coring rig to achieve a greater initial force on impact than gravity coring. A sliding piston inside the core barrel reduces inside wall friction with the sediment and helps to evacuate displaced water from the top of the corer. A piston corer is capable of extracting core samples up to 90 feet in length. |
Calcification in low saturation seawater: What can we learn from organisms in the proximity of low pH; undersaturated submarine springs (CalcificationLowSatSeawater)
NSF Abstract:
To date scientists have primarily used short-term single species experiments to study responses of organisms to increased pCO2. While these experiments are important, they represent an artificial situation, being isolated from many of the biological interactions. Moreover, these experiments do not truly reflect the effects on organisms over longer timescales in actual field situations.
In this study, researchers at the University of California at Santa Cruz will assess the utility of low pH submarine springs as field study sites for investigating calcification at low aragonite saturation. It has been reported that many reef-building corals cease calcification at saturation as high as 2.0; around these springs calcifying corals inhibit waters well below this value. Work will take place at a series of springs in Mexico where discharging water pH ranges from 8.07 to 7.25 and saturation from less than 0.5 to 5. While these springs are by no means analogs for future ocean calcification they can still provide a natural laboratory to study controls on coral calcification. Field observations are usually confounded by the presence of many potentially important variables in addition to saturation. Moreover, it is not trivial to quantify the natural spatial and temporal variability of the parameters of interest. Thus it is not clear how useful this setting might be for conducting extensive field based calcification research (high risk). Accordingly, the research team will conduct field surveys to map the chemical and physical characteristics of the water around the springs (and corals) and describe population and community patterns along the saturation gradient. They will install probes to capture the temporal and spatial variability. These observations should allow assessment of the site's utility for researching processes that sustain calcification at low saturation and for future manipulative experiments.
Background publications:
Crook ED, Potts D, Rebolledo-Vieyra M, Hernandez L, Paytan A. 2011. Calcifying coral abundance near low pH springs: implications for future ocean acidification. Coral Reefs, 31(1): 239-245.
Paytan A, Crook ED, Cohen AL, Martz T, Takeshita Y et al. 2014. Reply to Iglesias-Prieto et al.: Combined field and laboratory approaches for the study of coral calcification. Proc Natl Acad Sci USA, 111 (3): E302-E303.
Crook ED, Cohen AL, Rebolledo-Veiyra M, Hernandez L, Paytan A. 2013. Reduced calcification and lack of acclimatization by coral colonies growing in areas of persistent natural acidification. Proc Natl Acad Sci USA, 110 (27): 1044-1049.
Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES): Ocean Acidification (formerly CRI-OA) (SEES-OA)
NSF Climate Research Investment (CRI) activities that were initiated in 2010 are now included under Science, Engineering and Education for Sustainability NSF-Wide Investment (SEES). SEES is a portfolio of activities that highlights NSF's unique role in helping society address the challenge(s) of achieving sustainability. Detailed information about the SEES program is available from NSF (https://www.nsf.gov/funding/pgm_summ.jsp?pims_id=504707).
In recognition of the need for basic research concerning the nature, extent and impact of ocean acidification on oceanic environments in the past, present and future, the goal of the SEES: OA program is to understand (a) the chemistry and physical chemistry of ocean acidification; (b) how ocean acidification interacts with processes at the organismal level; and (c) how the earth system history informs our understanding of the effects of ocean acidification on the present day and future ocean.
Solicitations issued under this program:
NSF 10-530, FY 2010-FY2011
NSF 12-500, FY 2012
NSF 12-600, FY 2013
NSF 13-586, FY 2014
NSF 13-586 was the final solicitation that will be released for this program.
PI Meetings:
1st U.S. Ocean Acidification PI Meeting(March 22-24, 2011, Woods Hole, MA)
2nd U.S. Ocean Acidification PI Meeting(Sept. 18-20, 2013, Washington, DC)
3rd U.S. Ocean Acidification PI Meeting (June 9-11, 2015, Woods Hole, MA – Tentative)
NSF media releases for the Ocean Acidification Program:
Press Release 10-186 NSF Awards Grants to Study Effects of Ocean Acidification
Discovery Blue Mussels "Hang On" Along Rocky Shores: For How Long?
Press Release 13-102 World Oceans Month Brings Mixed News for Oysters
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |
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