Geochemical composition of sediment samples collected in the Equatorial Pacific during October and November 2020 on R/V Kilo Moana cruise KM2012

Website: https://www.bco-dmo.org/dataset/928400
Data Type: Cruise Results
Version: 1
Version Date: 2024-05-23

Project
» Collaborative Research: How and Why eNd Tracks Ocean Circulation (Pacific Porewater Nd)
ContributorsAffiliationRole
Haley, BrianOregon State University (OSU)Co-Principal Investigator
McManus, JamesBigelow Laboratory for Ocean SciencesCo-Principal Investigator
Rauch, ShannonWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
Water column, sediment, and pore water samples were collected during R/V Kilo Moana cruise KM2012 in the Equatorial Pacific during October and November 2020. This dataset includes elemental concentrations, Neodymium isotope ratios, and XRD analyses of the mineralogy of the sediment samples.


Coverage

Location: Equatorial Pacific
Spatial Extent: N:11 E:-152 S:3 W:-152
Temporal Extent: 2020-10-14 - 2020-10-24

Methods & Sampling

Water column, sediment, and pore water samples were collected following the methods in Abbott et al. (2015) during R/V Kilo Moana cruise KM2012 in October and November 2020. Sediment cores were collected using an MC800 multi-corer and sectioned at 1.2 centimeter (cm) intervals. Sediment samples were frozen onboard and freeze-dried in the lab. See 'Related Datasets' for the data from the water column and pore water samples.

Elemental concentrations, including the REEs, were analyzed at Oregon State University (OSU) using an Elemental Scientific seaFAST-pico offline preconcentration technique, and the procedure has been extensively documented as part of the GEOTRACES intercalibration effort (Behrens et al., 2016). Elemental concentrations of the εNd aliquots (~10 milliliters (mL)) were analyzed at ETH Zurich using Nobias Chelate-PA1 resin in a manual column procedure (K. Deng et al., 2022).

Isotope analysis of the εNd aliquots (400~700 mL of pore water or ~1.5 liters (L) of seawater) were done at ETH Zurich. Samples were buffered to a pH of 5.5 ± 5 and pre-concentrated using an in-house extraction manifold containing Nobias Chelate-PA1 resin. After pre-concentration, separation of Nd from the matrix elements and other REE was done using Eichrom RE and LN spec resins. Procedural blanks are <3 picograms (pg). Isotope analysis was done on an Neptune Plus MC-ICP-MS (Thermo-Fisher) following the procedure of Vance and Thirlwall (2002). Internally normalized sample data was renormalized to the 143Nd/144Nd ratio of La Jolla (Thirlwall, 1991). Repeated analysis of 8 parts per billion (ppb) La Jolla solutions results in a long-term external reproducibility of 0.27 ε (2σ). Nd isotope analysis was also quality-controlled by repeated measurements of the USGS reference materials BCR-2 (εNd = -0.11 ± 0.25, 2σ) and BHVO-2 (εNd = 6.70 ± 0.24, 2σ) at the same concentration (5-10 ppb) as the pore water samples in agreement with literature results (Jochum et al., 2005).

Nutrients were analyzed at Oregon State University using Technicon AutoAnalyzer II (phosphate and ammonium) and Alpkem RFA 300 (silicic acid, nitrate+nitrite). The method and data processing follow Gordon et al. (1993). DOC was analyzed with a V-CSN/TNM-1 (Shimadzu Corp, Kyoto, Japan) at the Scripps Institution of Oceanography following White et al. (2023).

Sediment samples were analysed for total organic carbon contents using a GVI (now Elementar) Isoprime 1000 with Eurovector EA at Bigelow Laboratory for Ocean Sciences. Samples were measured for the total carbon (organic plus inorganic) and a separate sample split was acidified to remove carbonate and then measured for the organic fraction.

​X-ray diffraction (XRD) of freeze-dried raw samples were made at K/T GeoServices Inc. (Colorado, USA), using a Siemens D500 automated powder diffractometer equipped with a copper X-ray source (40kV, 30mA) and a scintillation X-ray detector. Semi-quantitative determinations of whole-sediment mineral amounts were done using Jade Software (Materials Data, Inc.) with the Whole Pattern Fitting option.


BCO-DMO Processing Description

- Imported sheet "BCO-DMO sediment" from original file "BCO-DMOv2.xlsx" into the BCO-DMO system.
- Renamed fields to comply with BCO-DMO naming conventions.
- Corrected bottom depth of station 4 from 505 to 5050.
- Saved the final file as "928400_v1_sediment_geochemical_composition.csv".


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Data Files

File
928400_v1_sediment_geochemical_composition.csv
(Comma Separated Values (.csv), 21.97 KB)
MD5:41adb2e842015eb958d2c808fc5bbd0e
Primary data file for dataset ID 928400, version 1

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Related Publications

Abbott, A. N., Haley, B. A., McManus, J., & Reimers, C. E. (2015). The sedimentary flux of dissolved rare earth elements to the ocean. Geochimica et Cosmochimica Acta, 154, 186–200. https://doi.org/10.1016/j.gca.2015.01.010
Methods
Behrens, M. K., Muratli, J., Pradoux, C., Wu, Y., Böning, P., Brumsack, H.-J., … Pahnke, K. (2016). Rapid and precise analysis of rare earth elements in small volumes of seawater - Method and intercomparison. Marine Chemistry, 186, 110–120. doi:10.1016/j.marchem.2016.08.006
Methods
Deng, Kai, Yang, Shouye, Du, Jianghui, Lian, Ergang, & Vance, Derek. (2022). Dominance of benthic flux of REEs on continental shelves: implications for oceanic budgets. ETH Zurich. https://doi.org/10.3929/ETHZ-B-000559675 https://doi.org/10.3929/ethz-b-000559675
Methods
Gordon, L.I., J.C. Jennings, Jr., A.A. Ross, and J.M. Krest (1993) A Suggested Protocol For Continuous Flow Automated Analysis of Seawater Nutrients, in WOCE Operation Manual, WHP Office Report 90-1, WOCE Report 77 No. 68/91, 1-52. https://cchdo.github.io/hdo-assets/documentation/manuals/pdf/91_1/gordnut.pdf
Methods
Jochum, K. P., Nohl, U., Herwig, K., Lammel, E., Stoll, B., & Hofmann, A. W. (2005). GeoReM: A New Geochemical Database for Reference Materials and Isotopic Standards. Geostandards and Geoanalytical Research, 29(3), 333–338. https://doi.org/10.1111/j.1751-908x.2005.tb00904.x https://doi.org/10.1111/j.1751-908X.2005.tb00904.x
Methods
Thirlwall, M. F. (1991). Long-term reproducibility of multicollector Sr and Nd isotope ratio analysis. Chemical Geology, 94(2), 85–104. https://doi.org/10.1016/s0009-2541(10)80021-x https://doi.org/10.1016/S0009-2541(10)80021-X
Methods
Vance, D., & Thirlwall, M. (2002). An assessment of mass discrimination in MC-ICPMS using Nd isotopes. Chemical Geology, 185(3–4), 227–240. https://doi.org/10.1016/s0009-2541(01)00402-8 https://doi.org/10.1016/S0009-2541(01)00402-8
Methods
White, M. E., Nguyen, T. B., Koester, I., Lardie Gaylord, M. C., Beman, J. M., Smith, K. L., McNichol, A. P., Beaupré, S. R., & Aluwihare, L. I. (2023). Refractory Dissolved Organic Matter has Similar Chemical Characteristics but Different Radiocarbon Signatures With Depth in the Marine Water Column. Global Biogeochemical Cycles, 37(4). Portico. https://doi.org/10.1029/2022gb007603 https://doi.org/10.1029/2022GB007603
Methods

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Related Datasets

IsRelatedTo
Haley, B., McManus, J. (2024) Geochemical composition of sediment pore water samples collected in the Equatorial Pacific during October and November 2020 on R/V Kilo Moana cruise KM2012. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-05-23 doi:10.26008/1912/bco-dmo.928246.1 [view at BCO-DMO]
Haley, B., McManus, J. (2024) Geochemical composition of water column samples collected in the Equatorial Pacific during October and November 2020 on R/V Kilo Moana cruise KM2012. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-05-23 doi:10.26008/1912/bco-dmo.928152.1 [view at BCO-DMO]

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Parameters

ParameterDescriptionUnits
Station_Number

Station number

unitless
Latitude

Latitude of sampling site in degrees North

degrees North
Longitude

Longitude of sampling site in degrees East (negative values are West)

degrees East
Date

Date of sampling

unitless
bottom_depth

Depth to seafloor

meters (m)
nominal_depth

Due to the nature of pore water sampling, the exact depth of sampling is not exact. We have provided the best median-depth for the sample taken such that it is comparable to other data/pore water/sediment. The resolution we used for these "nominal depths" is 0.5 cm.

centimeters (cm)
Be_ug_g

Beryllium micrograms per gram sediment digested

micrograms per gram (ug/g)
Be_error

Beryllium error of analysis

micrograms per gram (ug/g)
Na_wt_pcnt

Sodium micrograms per gram sediment digested

weight %
Na_error

Sodium error of analysis

weight %
Mg_wt_pcnt

Magnesium micrograms per gram sediment digested

weight %
Mg_error

Magnesium error of anlaysis

weight %
Al_wt_pcnt

Aluminium micrograms per gram sediment digested

weight %
Al_error

Aluminium error of anlaysis

weight %
S_wt_pcnt

Sulfur g per g sediment digested

weight %
S_error

Sulfur error of anlaysis

weight %
K_wt_pcnt

Potassium g per g sediment digested

weight %
K_error

Potassium error of anlaysis

weight %
Ca_wt_pcnt

Calcium g per g sediment digested

weight %
Ca_error

Calcium error of anlaysis

weight %
Sc_ug_g

Scandium micrograms per gram sediment digested

weight %
Sc_error

Scandium error of anlaysis

weight %
Ti_wt_pcnt

Titanium g per g sediment digested

weight %
Ti_error

Titanium error of anlaysis

weight %
V_ug_g

Vanadium micrograms per gram sediment digested

micrograms per gram (ug/g)
V_error

Vanadium error of anlaysis

micrograms per gram (ug/g)
Cr_ug_g

Chromium micrograms per gram sediment digested

micrograms per gram (ug/g)
Cr_error

Chromium error of anlaysis

micrograms per gram (ug/g)
Mn_ug_g

Manganese micrograms per gram sediment digested

micrograms per gram (ug/g)
Mn_error

Manganese error of anlaysis

micrograms per gram (ug/g)
Fe_wt_pcnt

Iron g per g sediment digested

weight %
Fe_error

Iron error of anlaysis

weight %
Co_ug_g

Cobalt micrograms per gram sediment digested

micrograms per gram (ug/g)
Co_error

Cobalt error of analysis

micrograms per gram (ug/g)
Ni_ug_g

Nickel nanograms per gram sediment digested

micrograms per gram (ug/g)
Ni_error

Nickel error of analysis

micrograms per gram (ug/g)
Cu_ug_g

Copper micrograms per gram sediment digested

micrograms per gram (ug/g)
Cu_error

Copper error of analysis

micrograms per gram (ug/g)
Zn_ug_g

Zinc micrograms per gram sediment digested

micrograms per gram (ug/g)
Zn_error

Zinc error of analysis

micrograms per gram (ug/g)
As_ug_g

Arsenic micrograms per gram sediment digested

micrograms per gram (ug/g)
As_error

Arsenic error of analysis

micrograms per gram (ug/g)
Sr_ug_g

Strontium micrograms per gram sediment digested

micrograms per gram (ug/g)
Sr_error

Strontium error of analysis

micrograms per gram (ug/g)
Y_ug_g

Ytterbium micrograms per gram sediment digested

micrograms per gram (ug/g)
Y_error

Ytterbium error of analysis

micrograms per gram (ug/g)
Zr_ug_g

Zirconium micrograms per gram sediment digested

micrograms per gram (ug/g)
Zr_error

Zirconium error of analysis

micrograms per gram (ug/g)
Nb_ug_g

Niobium micrograms per gram sediment digested

micrograms per gram (ug/g)
Nb_error

Niobium error of analysis

micrograms per gram (ug/g)
Mo_ug_g

Molybdenum micrograms per gram sediment digested

micrograms per gram (ug/g)
Mo_error

Molybdenum error of analysis

micrograms per gram (ug/g)
Cd_ug_g

Cadmium micrograms per gram sediment digested

micrograms per gram (ug/g)
Cd_error

Cadmium error of analysis

micrograms per gram (ug/g)
Ba_ug_g

Barium micrograms per gram sediment digested

micrograms per gram (ug/g)
Ba_error

Barium error of analysis

micrograms per gram (ug/g)
La_ug_g

Lanthanum micrograms per gram sediment digested

micrograms per gram (ug/g)
La_error

Lanthanum error of analysis

micrograms per gram (ug/g)
Ce_ug_g

Cerium micrograms per gram sediment digested

micrograms per gram (ug/g)
Ce_error

Cerium error of analysis

micrograms per gram (ug/g)
Pr_ug_g

Praeseodymium micrograms per gram sediment digested

micrograms per gram (ug/g)
Pr_error

Praeseodymium error of analysis

micrograms per gram (ug/g)
Nd_ug_g

Neodymnium micrograms per gram sediment digested

micrograms per gram (ug/g)
Nd_error

Neodymium error of analysis

micrograms per gram (ug/g)
Sm_ug_g

Samarium micrograms per gram sediment digested

micrograms per gram (ug/g)
Sm_error

Samarium error of analysis

micrograms per gram (ug/g)
Eu_ug_g

Europium micrograms per gram sediment digested

micrograms per gram (ug/g)
Eu_error

Europiumerror of analysis

micrograms per gram (ug/g)
Gd_ug_g

Gadolinium micrograms per gram sediment digested

micrograms per gram (ug/g)
Gd_error

Gadolinium error of analysis

micrograms per gram (ug/g)
Tb_ug_g

Terbium micrograms per gram sediment digested

micrograms per gram (ug/g)
Tb_error

Terbium error of analysis

micrograms per gram (ug/g)
Dy_ug_g

Dysprosium micrograms per gram sediment digested

micrograms per gram (ug/g)
Dy_error

Dysprosium error of analysis

micrograms per gram (ug/g)
Ho_ug_g

Holmium micrograms per gram sediment digested

micrograms per gram (ug/g)
Ho_error

Holmium error of analysis

micrograms per gram (ug/g)
Er_ug_g

Erbium micrograms per gram sediment digested

micrograms per gram (ug/g)
Er_error

Erbium error of analysis

micrograms per gram (ug/g)
Tm_ug_g

Thulium micrograms per gram sediment digested

micrograms per gram (ug/g)
Tm_error

Thulium error of analysis

micrograms per gram (ug/g)
Yb_ug_g

Ytterbium micrograms per gram sediment digested

micrograms per gram (ug/g)
Yb_error

Ytterbium error of analysis

micrograms per gram (ug/g)
Lu_ug_g

Lutetium micrograms per gram sediment digested

micrograms per gram (ug/g)
Lu_error

Lutetium error of analysis

micrograms per gram (ug/g)
Re_ng_ml

Rhenium nanograms per gram sediment digested

nanograms/gram (ng/g)
Re_error

Rhenium error of analysis

nanograms/gram (ng/g)
Pb_ug_g

Lead micrograms per gram sediment digested

micrograms per gram (ug/g)
Pb_error

Lead error of analysis

micrograms per gram (ug/g)
U_ug_g

Uranium micrograms per gram sediment digested

micrograms per gram (ug/g)
U_error

Uranium error of analysis

micrograms per gram (ug/g)
Quartz

XRD analyses of mineralogy: Quartz

% of total
K_Feldspar

XRD analyses of mineralogy: Potassium feldspar

% of total
Plagioclase

XRD analyses of mineralogy: Plagioclase feldspar

% of total
Calcite

XRD analyses of mineralogy: Calcite

% of total
Barite

XRD analyses of mineralogy: Barite

% of total
Gypsum

XRD analyses of mineralogy: Gypsum

% of total
Halite

XRD analyses of mineralogy: Halite

% of total
Amorphous

XRD analyses of mineralogy: Amorphous phases

% of total
Illite_Mica

XRD analyses of mineralogy: Illite plus Mica

% of total
Kaolinite

XRD analyses of mineralogy: Kaolinite

% of total
Chlorite

XRD analyses of mineralogy: Chlorite

% of total
R0_M_L_I_S_90_pcnt_S

XRD analyses of mineralogy

% of total
total

XRD analyses of mineralogy

% of total
Nd143_Nd144

Isotope ratio of Neodymium-143 to Neodymium-144 (2 s.d. std. dev. = 0.000021)

unitless
eNd

Neodymium isotope composition given in epsilon notation (deviation of 143Nd/144Nd ratio from CHUR; 2 s.d. std. dev. = 0.4)

unitless


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Instruments

Dataset-specific Instrument Name
Alpkem RFA 300
Generic Instrument Name
Alpkem RFA300
Generic Instrument Description
A rapid flow analyser (RFA) that may be used to measure nutrient concentrations in seawater. It is an air-segmented, continuous flow instrument comprising a sampler, a peristaltic pump which simultaneously pumps samples, reagents and air bubbles through the system, analytical cartridge, heating bath, colorimeter, data station, and printer. The RFA-300 was a precursor to the smaller Alpkem RFA/2 (also RFA II or RFA-2).

Dataset-specific Instrument Name
GVI (now Elementar) Isoprime 1000
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
MC800 multi-corer
Generic Instrument Name
Multi Corer
Generic Instrument Description
The Multi Corer is a benthic coring device used to collect multiple, simultaneous, undisturbed sediment/water samples from the seafloor. Multiple coring tubes with varying sampling capacity depending on tube dimensions are mounted in a frame designed to sample the deep ocean seafloor. For more information, see Barnett et al. (1984) in Oceanologica Acta, 7, pp. 399-408.

Dataset-specific Instrument Name
Elemental Scientific seaFAST-pico
Generic Instrument Name
SeaFAST Automated Preconcentration System
Generic Instrument Description
The seaFAST is an automated sample introduction system for analysis of seawater and other high matrix samples for analyses by ICPMS (Inductively Coupled Plasma Mass Spectrometry).

Dataset-specific Instrument Name
V-CSN/TNM-1 (Shimadzu Corp)
Generic Instrument Name
Shimadzu TOC-V Analyzer
Generic Instrument Description
A Shimadzu TOC-V Analyzer measures DOC by high temperature combustion method.

Dataset-specific Instrument Name
Technicon AutoAnalyzer II
Generic Instrument Name
Technicon AutoAnalyzer II
Generic Instrument Description
A rapid flow analyzer that may be used to measure nutrient concentrations in seawater. It is a continuous segmented flow instrument consisting of a sampler, peristaltic pump, analytical cartridge, heating bath, and colorimeter. See more information about this instrument from the manufacturer.

Dataset-specific Instrument Name
Neptune Plus MC-ICP-MS (Thermo-Fisher)
Generic Instrument Name
Thermo Finnigan Neptune inductively coupled plasma mass spectrometer
Generic Instrument Description
A laboratory high mass resolution inductively coupled plasma mass spectrometer (ICP-MS) designed for elemental and isotopic analysis. The instrument is based on a multicollector platform, comprising eight moveable collector supports and one fixed center channel equipped with a Faraday cup and, optionally, an ion counter with or without a retardation lens. The Faraday cup is connected to a current amplifier, whose signal is digitized by a high linearity voltage to frequency converter. The instrument was originally manufactured by Thermo Finnigan, which has since been replaced by Thermo Scientific (part of Thermo Fisher Scientific). This model is no longer in production.

Dataset-specific Instrument Name
Siemens D500 automated powder diffractometer
Generic Instrument Name
X-ray diffractometer
Generic Instrument Description
Instruments that identify crystalline solids by measuring the characteristic spaces between layers of atoms or molecules in a crystal.


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Deployments

KM2012

Website
Platform
R/V Kilo Moana
Start Date
2020-10-09
End Date
2020-11-02
Description
See more information at R2R: https://www.rvdata.us/search/cruise/KM2012


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Project Information

Collaborative Research: How and Why eNd Tracks Ocean Circulation (Pacific Porewater Nd)

Coverage: Central Pacific


NSF Award Abstract:
Circulation of water is a fundamental trait of the oceans that impacts its physics, chemistry and biology; however, understanding modern and past patterns of circulation - especially in the vast bodies of deep water - is challenging because global circulation defies direct measurement. The problems with direct measurement largely stem from the vast scales of space and time that are of interest in understanding global circulation. One tool for estimating global circulation patterns that holds promise is seen in neodymium isotopes which appear to be powerful tracers of deep ocean circulation, over a variety of timescales. Unfortunately, the elemental behavior of neodymium contrasts the isotopic behavior of neodymium in the oceans, a puzzle branded the "neodymium paradox." This inconsistency of geochemical behavior opens to question the application of neodymium isotopes as a tracer of circulation. Therefore, scientists from Oregon State University, Tulane University, and Bigelow Laboratory of Ocean Sciences propose to test the hypothesis that there is a yet unconstrained (even poorly identified) source of neodymium to the oceans that can explain the discrepancies seen between the elemental and isotopic neodymium marine budgets. The scientists further seek to understand the mechanistic cause of this source and thus be able to start making global constraints on its influence. Understanding these processes will fundamentally change our interpretations of neodymium data and allow us to more accurately quantify ocean circulation with a greater degree of confidence. For outreach activities, the scientists plan to participate in open house days held at Oregon State University, da Vinci days, National Ocean Science Bowls, Salmon Bowl and Bigelow Laboratory for Ocean Sciences' Cafe Scientifique. Undergraduate students and one graduate student from Tulane University would be supported and trained as part of this project.

Scientists from Oregon State University, Tulane University, and Bigelow Laboratory for Ocean Sciences propose to test the hypothesis that there is a benthic source of neodymium (Nd) to the oceans that exerts a primary control over the distribution of this element and its isotopes (eNd) in the ocean. This benthic flux results from early diagenetic reactions that release rare earth elements (REEs) from the solid phase to pore fluid. The scientists contend this flux will explain eNd distributions throughout the modern and past global oceans. The planned research will be guided by three questions:

(1) What are the mechanisms that control the magnitude and isotope composition of the benthic flux?
(2) What are the relationships among bottom water, pore fluid, and the terminal solid phase compositions? Particularly, how and under what chemical conditions does an eNd signature become part of a preserved archival record of [Nd] and eNd?
(3) Can our understanding of the deep water benthic fluxes account for the integrated bottom water eNd as a function of apparent water mass age and circulation path (e.g., how do the pore fluid and solid phase values reconcile with the existing water column signature and water mass age data)?

To test these ideas, sediments and their pore fluids will be collected from a diverse set of deep sea sites in the Pacific Ocean that reflect slow-to-fast sedimentation rates, carbonate-, terrigenous-, volcaniclastic- and siliceous-sediment, and low-to-high organic carbon. The sediments and porewater samples, as well as samples from the overlying water column will be characterized for the following parameters: major, minor, and trace metals, Nd isotopes, carbonate chemistry, oxygen, nutrients, particulate organic carbon, particulate organic nitrogen, radiocarbon, porosity, and grain size. With these observations we will build a quantitative numeric geochemical model (e.g., PHREEQC, Geochemist's Workbench, Humic Ion Binding Model) that can capture the cardinal controls over the benthic source. Our goal is to provide a new interpretive framework for Nd and eNd, such that we can offer quantitative estimates of benthic fluxes for use in models of global circulation. This work has potentially transformative implications on our understanding and application of REEs and Nd isotope data in both the modern and ancient oceans.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)
NSF Division of Ocean Sciences (NSF OCE)

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