Sediment trap metal fluxes from Hawaii Ocean Timeseries (HOT) R/V Kilo Moana cruises at station ALOHA, North Pacific Subtropical Gyre, from December 2020 to November 2023

Website: https://www.bco-dmo.org/dataset/962821
Data Type: Cruise Results
Version: 1
Version Date: 2025-05-29

Project
» Quantifying Iron Turnover in the Upper Ocean via Time-series Measurements at Station ALOHA (HOT Trace Metals)

Program
» Ocean Time-series Sites (Ocean Time-series)
ContributorsAffiliationRole
Hawco, Nicholas JamesUniversity of Hawaiʻi at MānoaPrincipal Investigator
Bates, Eleanor S.University of Hawaiʻi at MānoaStudent
York, Amber D.Woods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager

Abstract
We analyzed the metal fluxes out of the upper 150 m of the water column using surface-tethered sediment traps deployed on Hawaii Ocean Time-series (HOT) cruises between December 2020 and November 2023. All deployments were initiated at Station ALOHA. Sinking particulate metals were collected in Particle Interceptor Traps (PITs) with ~100 ppt trace-metal clean brine derived from seawater over a period of approximately 2.5 days. Following recovery, triplicate PIT traps were filtered onto 0.2 micron polyethersulfone (PES) filters. Filters were subject to a 2-stage digestion: 1) a "Berger" leach consisting of hydroxylamine and acetic acid, to dissolve labile trace metals, and 2) a digestion with nitric acid and hydrofluoric acid to dissolve recalcitrant metals. Dissolved metals for each leach were analyzed by inductively coupled plasma mass spectrometry at the University of Hawaii at Manoa using a Thermo Scientific iCAP-TQ mass spectrometer. This dataset is part of a larger study focused on the cycling of trace metals in the North Pacific Subtropical Gyre, and is embedded within the HOT program.


Coverage

Location: Station ALOHA, North Pacific Subtropical Gyre, 22.75 N, 158.00 W
Spatial Extent: Lat:22.75 Lon:-158
Temporal Extent: 2020-12-18 - 2023-11-08

Methods & Sampling

Sample Collection

Samples were collected on 21 Hawaii Ocean Time-series (HOT) cruises, onboard the R/V Kilo Moana throughout 2020-2023. All samples were collected at Station ALOHA (22.45°N, 158.0°W) following trace metal clean procedures.

Before each cruise, particle interceptor traps (PITs) were acid-cleaned by soaking in Citranox overnight followed by a 10% HCl soak for seven days, followed by several rinses with high purity (18.2 mega-ohm-cm) water. A brine was made by partially freezing trace-metal-clean seawater over multiple cycles until a 100 ppt salinity was achieved. Prior to deployment at sea, the traps were filled with approx. 1.8 L of trace metal clean brine and topped with approx. 0.8 L of trace-metal-clean seawater. 

During deployment, PITs were attached to a surface-tethered array at a depth of 150 m and deployed over approximately 2.5 days. Three replicate traps and one capped control trap were deployed. The trace-metal PITs were deployed 1-2 m above the standard 'cross' used for collection of sinking particles by the HOT program. 

Upon recovery, traps were processed in a trace-metal-clean 'van' laboratory onboard. The samples were vacuum-filtered through 1 mm x 1mm screening mesh onto acid-cleaned 47 mm 0.2 mm Supor filters. The filters were folded and stored in acid-cleaned centrifuge tubes prior to analysis. 1 L of filtrate from each sediment trap was also collected to assess potential solubilization of sinking particulate metals.

Sample Processing and Measurement

In the lab, filters underwent a two-stage digestion to isolate 'labile' and 'recalcitrant' metal fractions. The 'labile' digestion followed the procedure outlined by Berger et al. (2008). Filters were submerged in 2 mL of a 25% acetic acid, 0.02 M hydroxylamine hydrochloride solution, with 10 ppb Indium added as an internal standard and recovery tracer. The filter and solution were heated in a water bath at 95C for 10 min, and allowed to return to room temperature. After a total contact time of 2 hrs, the filters were removed and the leachate was transferred to acid-cleaned PFA digestion vials (Savillex). To improve recovery, the filter was then rinsed with a few mL of high-purity (18.2 M-ohm cm-1) water, which was then added back to the leachate. 100 uL of concentrated nitric acid was added to the leachate, which was then dried overnight at 110C. The sample was redissolved in 0.1 M HNO3 for ICP-MS analysis.

Following the 'labile' digestion, the filter was then subject to a total extraction following the procedures used by Planquette & Sherrell (2012). 5 mL of a digest solution containing 8 M HNO3, 2.9 M HF, and 10 ppb Y (also applied as an internal standard and recovery tracer) was added to the filters in a 20 mL PFA vial (Savillex), which was heated for 4 hours at 110°C. The filters were then removed and the sample was evaporated to dryness. 100 ul of concentrated nitric acid was added and the sample was dried again before being redissolved in 5 mL 0.1 M HNO3. 'Labile' metal samples were diluted 100-fold and 'recalcitrant' metals were diluted 10-fold in 0.1 M HNOprior to analysis.

Particulate trace metals collected on the filter corresponding to the 'control' trap were used to determine process blanks. Several blank filter and reagent blank analyses (containing no filter) were also analyzed to estimate the metal contributions of the filters and reagents.

Digested samples were analyzed using a Thermo Scientific iCAP TQ ICP-MS at the University of Hawaiʻi at Mānoa. All elements were analyzed in triple-quadrupole mode with oxygen as the reactive gas (TQ-O2). A multi-element standard (Inorganic Ventures) was run multiple times throughout a run to monitor changes in instrument sensitivity over the course of a run. 

Accuracy of particulate metals from the digestion protocol was assessed by digestion and measurement of certified reference materials BCR-414, PACS-3. Average recoveries for these standards ranged from 85-92% for Al, 80% for Ti, 79-93% for Mn, 83-93% for Fe, 70-80% for Zn, 122-139% for Cd, 97-113% for Ni, 79-84% for Cu, and 89-98% for Co.


Data Processing Description

Prior to calibration, ion intensities derived from the ICP-MS were corrected for matrix suppression and/or sample loss by 115-In ('labile' digestions) and 89-Y ('recalcitrant' digestions). Detection of 115-In in the recalcitrant digestions was used to infer and quantify any carry-over of 'labile' metals into the 'recalcitrant' digest, which were subtracted from the recalcitrant total. The median values of metal contents from digestions of 'control' trap filters across the time-series were subtracted from measured abundances, and the subsequent quantity in moles was then re-scaled to a flux, in mol m-2 day-1, using the area of the PIT trap opening (0.0039 m2) and the duration of the deployment (ranged 1.6-3.3 days).

Samples with concentrations lower than the filter blanks were corrected to 0. Samples from replicate traps were tested for outliers using the Grubbs' test (Grubbs 1950), where Z = | mean - value | / standard deviation. Replicates with a Z score > or = 1.15 (p < 0.05) were marked as outliers.


BCO-DMO Processing Description

* Sheet 1 of submitted file "HOTsedtrapsTM_QCflags.xlsx" was imported into the BCO-DMO data system for this dataset. Table will appear as Data File: 962821_v1_hot-sedtrap-fluxes.csv (along with other download format options).

* Data within sheet 2 "Flag Key" appeared redundant with already entered metadata so was not added (see Problems/Issues section for quality flag info)

* ISO DateTime with timezone (UTC) column added in ISO 8601 format for deployment and recovery.

* Latitude and Longitude columns added with provided coordinates in metadata. Added for consistency with other datasets in project and geospatial-ready capability.

* After discussion with the data submitter, Cruise ID changed to HOT-### to match the project convention


Problem Description

Quality flags were applied following the GEOTRACES policy (https://www.geotraces.org/geotraces-quality-flag-policy/), which recommends the SeaDataNet Scheme:

0 = no quality control;
1 = good value;
2 = probably good value;
3 = probably bad value; (used here for samples determined to be outliers using Grubbs' test)
4 = bad value;
5 = changed value;
6 = value below detection; (used here when samples < filter blank)
7 = value in excess;
8 = interpolated value;
9 = missing value;
A = value phenomenon uncertain.

Additional issues:

Our protocol can be used to determine particulate phosphorus (P) fluxes, a parameter that is also determined by the HOT program. We observed a large ~15-fold discrepancy between the measured P flux into the trace metal clean sediment traps and the standard traps used by HOT, with the trace-metal-clean traps having the larger flux. This discrepancy cannot be explained by analytical artifacts associated with ICP-MS calibration.

There are two possible explanations for this offset.

1) Because our sediment traps did not include a preservative, and because our screening protocol used a larger mesh size than HOT, it is possible that the excess P in the trace metal clean traps reflects input from swimming organisms that entered the traps after deployment and subsequently died. Visual comparisons indicated that our mesh size excluded swimming organisms from the 0.2 um filter (which is smaller than the standard GF/F used by the HOT program and could also increase retention of particulate P in small particles, e.g. bacterial cells).

2) To make our sediment trap deployment acceptable for trace metal measurements, our brine compositions differed from the standard HOT protocols (where non-trace-metal clean seawater is supplemented with sodium chloride and preserved with formalin). Our brines were obtained by freeze concentrating seawater, which led to a ~2.5-fold increase in all dissolved substrates, which decreases the solubility of P-containing minerals. A further nucleation mechanism due to the abundance of particulate matter in the 'open' traps would be required to increase particulate P concentrations above the controls. Mass balance calculations emphasize that even relatively low P concentrations in initial seawater (0.1 uM) used in the preparation of our brines could account for the excess flux. 

We note that attempts to compare the derived flux of other metals to reported values generally showed good comparisons (i.e. there was no 16-fold excess in Al, Ti, Fe, Ni, Cu, Cd, Co, or Mn flux in our study compared to the VERTIGO sediment traps reported by Lamborg et al.  2008 for deployments at Station ALOHA). As a result, we feel that this issue is largely restricted to P and should have limited impact on other elements reported here. 

As a result of these concerns, we do not report P fluxes from our sediment traps and encourage users to use the corresponding measurements made by the HOT program, which were conducted on the same array as our datasets.

We also made attempts to determine the potential solubilization of trace metals from particulate phases into the dissolved phase by measuring the concentration of metals in our sediment trap brine following deployment. For all elements except for Cd, there was no difference between 'open' and 'closed' (i.e. control) traps. For Cd, higher concentrations in brines may reflect dissolution of sinking particulate Cd. However, this mechanism would require an extremely high Cd flux, which may not be realistic. Replacement of our initial trace-metal-clean seawater 'cap', which overlayed the brine, by relatively Cd-rich waters at 150 m depth during deployment may account for the excess Cd observed in the brine sample (which includes both the brine and the seawater cap obtained during recovery of the sediment traps).

In this dataset, we report the particulate Cd fluxes that remained on the filter at the time of collection. 

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Data Files

File
962821_v1_hot-sedtrap-fluxes.csv
(Comma Separated Values (.csv), 16.68 KB)
MD5:3159db0fd85900f8b4ad41f77bc6f9fe
Primary data file for dataset ID 962821, version 1

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Related Publications

European Virtual Institute for Speciation Analysis (EVISA) (2025). Material Database: BCR-414 - Trace elements in plankton. Available from https://speciation.net/Database/Materials/JRC--Joint-Research-Centre/BCR414--Trace-elements-in-plankton-;i195
Methods
Willie, S., Boyko, V., Brophy, C., Clancy, V., Pihillagawa Gedara, I., Grinberg, P., Kumkrong, P., Mercier, P. H. J., Mihai, O., Tyo, D. D., Jiang, C., Kingston, D. M., Maxwell, P., Meija, J., Mester, Z., Sturgeon, R., & Yang, L. (2013). PACS-3: Marine Sediment Certified Reference Material for total and extractable metal content (Version 1). National Research Council of Canada. https://doi.org/10.4224/CRM.2013.PACS-3 https://doi.org/10.4224/crm.2013.pacs-3
Methods

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Parameters

ParameterDescriptionUnits
Cruise

HOT cruise number

unitless
Time_deployment

DateTime the array was deployed in local HST timezone

unitless
Time_recovery

DateTime the array was recovered in local HST timezone

unitless
Time_deployment_UTC

DateTime with timezone the array was deployed in UTC timezone

unitless
Time_recovery_UTC

DateTime with timezone the array was recovered in UTC timezone

unitless
Depth

Depth at which sediment traps were deployed.

meters (m)
Longitude

Longitude

decimal degrees
Latitude

Latitude

decimal degrees
Replicate

Sediment trap ID letter

unitless
Flux_Al_labile

Flux of labile Aluminum

micromoles per square meter per day (umol/m2/day)
Flux_Al_labile_qc

data flag for labile aluminum flux

unitless
Flux_Ti_labile

Flux of labile Titanium

micromoles per square meter per day (umol/m2/day)
Flux_Ti_labile_qc

data flag for labile titanium flux

unitless
Flux_Mn_labile

Flux of labile Manganese

micromoles per square meter per day (umol/m2/day)
Flux_Mn_labile_qc

data flag for labile manganese flux

unitless
Flux_Fe_labile

Flux of labile Iron

micromoles per square meter per day (umol/m2/day)
Flux_Fe_labile_qc

data flag for labile iron flux

unitless
Flux_Co_labile

Flux of labile Cobalt

micromoles per square meter per day (umol/m2/day)
Flux_Co_labile_qc

data flag for labile cobalt flux

unitless
Flux_Ni_labile

Flux of labile Nickel

micromoles per square meter per day (umol/m2/day)
Flux_Ni_labile_qc

data flag for labile nickel flux

unitless
Flux_Cu_labile

Flux of labile Copper

micromoles per square meter per day (umol/m2/day)
Flux_Cu_labile_qc

data flag for labile copper flux

unitless
Flux_Zn_labile

Flux of labile Zinc

micromoles per square meter per day (umol/m2/day)
Flux_Zn_labile_qc

data flag for labile Zinc flux

unitless
Flux_Cd_labile

Flux of labile Cadmium

micromoles per square meter per day (umol/m2/day)
Flux_Cd_labile_qc

data flag for labile Cadmium flux

unitless
Flux_Pb_labile

Flux of labile Lead

micromoles per square meter per day (umol/m2/day)
Flux_Pb_labile_qc

data flag for labile Lead flux

unitless
Flux_Al_recal

Recalcitrant Aluminum flux

micromoles per square meter per day (umol/m2/day)
Flux_Al_recal_qc

Data flag for recalcitrant Aluminum flux

unitless
Flux_Ti_recal

Recalcitrant Titanium flux

micromoles per square meter per day (umol/m2/day)
Flux_Ti_recal_qc

Data flag for recalcitrant Titanium flux

unitless
Flux_Mn_recal

Recalcitrant Manganese flux

micromoles per square meter per day (umol/m2/day)
Flux_Mn_recal_qc

Data flag for recalcitrant Manganese flux

unitless
Flux_Fe_recal

Recalcitrant Iron flux

micromoles per square meter per day (umol/m2/day)
Flux_Fe_recal_qc

Data flag for recalcitrant Iron flux

unitless
Flux_Co_recal

Recalcitrant Cobalt flux

micromoles per square meter per day (umol/m2/day)
Flux_Co_recal_qc

Data flag for recalcitrant Cobalt flux

unitless
Flux_Ni_recal

Recalcitrant Nickel flux

micromoles per square meter per day (umol/m2/day)
Flux_Ni_recal_qc

Data flag for recalcitrant Nickel flux

unitless
Flux_Cu_recal

Recalcitrant Copper flux

micromoles per square meter per day (umol/m2/day)
Flux_Cu_recal_qc

Data flag for recalcitrant Copper flux

unitless
Flux_Zn_recal

Recalcitrant Zinc flux

micromoles per square meter per day (umol/m2/day)
Flux_Zn_recal_qc

Data flag for recalcitrant Zinc flux

unitless
Flux_Cd_recal

Recalcitrant Cadmium flux

micromoles per square meter per day (umol/m2/day)
Flux_Cd_recal_qc

Data flag for recalcitrant Cadmium flux

unitless
Flux_Pb_recal

Recalcitrant Lead flux

micromoles per square meter per day (umol/m2/day)
Flux_Pb_recal_qc

Data flag for recalcitrant Lead flux

unitless


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Instruments

Dataset-specific Instrument Name
Generic Instrument Name
Thermo Fisher Scientific iCAP TQ inductively coupled plasma mass spectrometer
Generic Instrument Description
A benchtop triple quadrupole (TQ) inductively coupled plasma mass spectrometer (ICP-MS) with a four channel peristaltic pump, three plasma gas flow controllers, and four QCell mass flow controllers. The iCAP TQ utilises triple quadrupole technology which allows the analyte signal to be isolated from interferences, enabling the analysis of complex or high-matrix samples. The high frequency (4 MHz) quadrupole mass analyser has pre and post filters for isolation of wanted ions. The instrument features Peltier cooled high purity quartz or perfluoroalkoxy alkane (PFA), and low volume, baffled cyclonic or double pass spray chambers to efficiently filter out larger aerosol droplets for improved plasma stability. A reaction finder method development assistant aids easy method development. The plasma system is designed to rapidly adapt to changing matrices and provide robustness for challenging samples such as highly volatile organic solvents. The argon ICP ion source has a digital, solid state radiofrequency generator, and dynamic frequency impedance matching the plasma at 27 MHz. The iCAP TQ has applications in trace element analysis of solid or liquid (particularly sediment or sea water) samples. It has a nebuliser default flow rate of 400 uL/min.


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Deployments

HOT_cruises

Website
Platform
Multiple Vessels
Report
Start Date
1988-10-31
Description
Since October 1988, the Hawaii Ocean Time-series (HOT) program has investigated temporal dynamics in biology, physics, and chemistry at Stn. ALOHA (22°45' N, 158°W), a deep ocean field site in the oligotrophic North Pacific Subtropical Gyre (NPSG). HOT conducts near monthly ship-based sampling and makes continuous observations from moored instruments to document and study NPSG climate and ecosystem variability over semi-diurnal to decadal time scales.


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Project Information

Quantifying Iron Turnover in the Upper Ocean via Time-series Measurements at Station ALOHA (HOT Trace Metals)

Coverage: North Pacific Subtropical Gyre


NSF Award Abstract:
Phytoplankton are the base of marine food webs but their ability to grow in the open ocean by photosynthesis is limited by the scarcity of key nutrients especially iron. To understand how phytoplankton respond to global environmental changes, it is essential to predict how the nutrient content of seawater will change as well. Iron is essential to the light-harvesting machinery of phytoplankton but is an extremely small fraction of seawater (1 part per billion) . Iron is much more abundant in soils and when dust storms blow these soils out to sea, the iron content of seawater increases. It is unknown how long the effects of these iron supply events last, which depends on how well the marine ecosystem can recover and reuse iron before it sinks to the seafloor. It is also unknown if human activities have added to the natural Fe supply. The proposed research will address these questions by conducting a 3 year time-series of iron measurements in the North Pacific Ocean. Here, dust supply from Asia occurs mainly during spring, allowing the loss of iron over the summer and fall months to be documented. Unique chemical signatures will be used to distinguish iron supply from the deposition of desert dust or from human sources. This record of the marine iron cycle will be important for validating ecosystem models that are used to predict how climate change will influence the growth of phytoplankton in the future. The research would make a scientific contribution to the Hawaii Ocean Time-Series, help improve biogeochemical iron models, student training at the graduate and undergraduate level, and support an early career scientist.

A 3 year time-series of iron (Fe) measurements is proposed to constrain the magnitude of external Fe input and Fe recycling in the open ocean. Near-monthly observations will be conducted in the North Pacific Subtropical Gyre onboard Hawaii Ocean Timeseries cruises, which receives regular dust input during springtime and is minimally influenced by deep mixing. Water column profiling of dissolved and particulate Fe concentrations – combined with the flux of Fe recorded in trace-metal-clean sediment traps – will define a residence time of Fe in the upper water column. Iron uptake rates will be quantified through short-term incubations using a novel stable isotope technique and will be used to derive a turnover time with respect to biological uptake. Finally, the isotopic composition of dissolved and particulate Fe in the mixed layer will be measured to evaluate the potential importance of anthropogenic and Hawaiian Fe sources, which are poorly constrained. Together, these measurements will define the tempo and variability of the open ocean Fe cycle and provide a means to validate models that simulate the biogeochemistry of this key micronutrient.

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.

See more information about the Hawaii Ocean Time Series (HOT) on the related project page:  https://www.bco-dmo.org/project/2101 



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Program Information

Ocean Time-series Sites (Ocean Time-series)

Coverage: Bermuda, Cariaco Basin, Hawaii


Program description text taken from Chapter 1: Introduction from the Global Intercomparability in a Changing Ocean: An International Time-Series Methods Workshop report published following the workshop held November 28-30, 2012 at the Bermuda Institute of Ocean Sciences. The full report is available from the workshop Web site hosted by US OCB: http://www.whoi.edu/website/TS-workshop/home

Decades of research have demonstrated that the ocean varies across a range of time scales, with anthropogenic forcing contributing an added layer of complexity. In a growing effort to distinguish between natural and human-induced earth system variability, sustained ocean time-series measurements have taken on a renewed importance. Shipboard biogeochemical time-series represent one of the most valuable tools scientists have to characterize and quantify ocean carbon fluxes and biogeochemical processes and their links to changing climate (Karl, 2010; Chavez et al., 2011; Church et al., 2013). They provide the oceanographic community with the long, temporally resolved datasets needed to characterize ocean climate, biogeochemistry, and ecosystem change.

The temporal scale of shifts in marine ecosystem variations in response to climate change are on the order of several decades.  The long-term, consistent and comprehensive monitoring programs conducted by time-series sites are essential to understand large-scale atmosphere-ocean interactions that occur on interannual to decadal time scales.  Ocean time-series represent one of the most valuable tools scientists have to characterize and quantify ocean carbon fluxes and biogeochemical processes and their links to changing climate.

Launched in the late 1980s, the US JGOFS (Joint Global Ocean Flux Study; http://usjgofs.whoi.edu) research program initiated two time-series measurement programs at Hawaii and Bermuda (HOT and BATS, respectively) to measure key oceanographic measurements in oligotrophic waters. Begun in 1995 as part of the US JGOFS Synthesis and Modeling Project, the CARIACO Ocean Time-Series (formerly known as the CArbon Retention In A Colored Ocean) Program has studied the relationship between surface primary production, physical forcing variables like the wind, and the settling flux of particulate carbon in the Cariaco Basin.

The objective of these time-series effort is to provide well-sampled seasonal resolution of biogeochemical variability at a limited number of ocean observatories, provide support and background measurements for process-oriented research, as well as test and validate observations for biogeochemical models. Since their creation, the BATS, CARIACO and HOT time-series site data have been available for use by a large community of researchers.
 
Data from those three US funded, ship-based, time-series sites can be accessed at each site directly or by selecting the site name from the Projects section below.

 



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Funding

Funding SourceAward
NSF Division of Ocean Sciences (NSF OCE)

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