| Contributors | Affiliation | Role |
|---|---|---|
| Druffel, Ellen R.M. | University of California-Irvine (UC Irvine) | Principal Investigator |
| Hauksson, Niels | University of California-Irvine (UC Irvine) | Scientist |
| Mickle, Audrey | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Sample Site Description
The SCR (Santa Clara River) is a SMR (small mountainous river) with a watershed area of 4232 km2, (Henry et al. 2024; Swain et al. 2018). The river is in Ventura and Los Angeles Counties and 37% of the basin is controlled by dams (Brownlie and Taylor, 1981). Rainfall occurs in the winter, resulting in high streamflow from December to March, and dry periods during the rest of the year, typical of a Mediterranean climate. Sediment and POC samples were collected from the SCR after high flow periods from four precipitation events.
Samples were collected from the mouth of the Santa Clara River at three locations: 1) river water (for particulate organic carbon POC) from Santa Clara River Bridge, Highway 101, Oxnard, CA at 34.230, -119.259; 2) river silt (for sedimentary organic carbon SOC) at 34.230, -119.261, and 3) beach sand (SOC) at 34.230, -119.262. Bottle casts were conducted by hand from the Santa Clara River Bridge, Highway 101, CA (1 m depth) and sediment collection from the estuary during December 2023-April 2024. All samplings took place during rain events.
Particulate Matter Collection and Sample Processing
All glass sampling equipment was soaked in 10% HCl for > 2 hours, rinsed with Milli-Q water, and baked at 540˚C for 2 hours. Metal sampling equipment was baked at 540˚C for 2 hours. Bottle and jar lids were lined with Teflon tape cleaned in Chromerge.
River water was collected by submerging a 2.5L glass bottle deployed by rope from the SCR Bridge. The samples were stored on ice for up to 24 hours until vacuum filtered in the lab using pre-combusted 2.2μm quartz fiber filters. The filters were frozen in glass petri dishes, wrapped in clean aluminum foil and plastic bags. For isotope analyses, filters were cut into sections using a razor blade cleaned with methanol, transferred into quartz combustion tubes, then acidified with 3% H3PO4 overnight and dried in vacuo.
Riverbank Sediment Collection and Processing
Sediment from the top 3 cm of the riverbank were collected in glass jars and stored on ice for up to 24 hours until transport to the lab, and frozen. Sub-samples were taken by thawing, and weighing approximately 200 mg of sediment in a petri dish before fumigation with concentrated HCl for 3 to 4 hours (Komada et al. 2008). Samples were transferred into quartz combustion tubes with quartz wool and dried in vacuo. Moisture content of sediment samples was determined by drying samples at 40˚C to a constant mass.
14C Analysis
Cupric oxide and silver were added to the quartz tubes, then vacuum sealed and combusted to CO2 at 850˚C for 2 hours. The CO2 was cryogenically purified and reduced to graphite using zinc reductant and iron catalyst (Xu et al. 2007; Walker and Xu 2019). 14C analyses were performed at the Keck Carbon Cycle AMS (KCCAMS) Laboratory at UCI by our group. Uncertainties for river POC and sediment OC samples was determined by pooled standard deviation of replicates (McNaught and Wilkinson, 1997). Uncertainty of river POC ∆14C values was ±4‰ and that for estuary sediment OC ∆14C values was ±45‰, and were high due to heterogeneity of the samples.
13C Analysis
The CO2 obtained from combusted samples for 14C analysis were split after equilibration for at least 2 minutes to prevent fractionation. The split was analyzed for δ13C using a Finnigan Delta Plus mass spectrometer at UCI. Uncertainty was determined using pooled standard deviation of replicates (McNaught and Wilkinson, 1997). River POC samples have an uncertainty of ± 0.1 ‰; estuary sediment OC samples have an uncertainty of ± 0.5 ‰ and were high due to heterogeneity of the samples.
We use custom programs that are available in our group to process the isotope measurements we make.
This section documents curation actions performed prior to publication review with the submitter, and additional information relevant to understanding and reusing this dataset. It distinguishes changes made to the submitted (meta)data from unresolved issues and/or enhancements that improve future reuse and interoperability.
CURATION ACTIONS PERFORMED ON DATA
- Loaded RAPID BCO-DMO data Druffel.xlsx (sheet "Isotope Data"), assigning explicit column headers: UCID sample number, Sample Description and filter # and date collected, D14C, D14C_error, d13C, d13C_error, latitude, longitude; skipped rows 1-6 (multi-row header, grant note, PI note); set "" and "nd" as missing values
- Split column "Sample Description and filter # and date collected" via regex into sample_type (first 3 letters), site_name (next 3 letters), filter_number (middle text, e.g. "Filter 34", "Silt A"), and date_collected_raw (raw MM-DD-YY date string); deleted original input column
- Converted date_collected_raw (format %m-%d-%y) into new date column date_collected (output format %Y-%m-%d)
- Deleted column date_collected_raw
- Reordered columns to: UCID sample number, sample_type, site_name, filter_number, date_collected, D14C, D14C_error, d13C, d13C_error, latitude, longitude
- Renamed column "UCID sample number" to "UCID_sample_number"
- Output as 1006750_v1_santa_clara_river_isotopes.csv
CURATION ACTIONS PERFORMED ON METADATA
- BCO-DMO's standard metadata entry and text formatting steps were performed.
- Created definitions for newly created fields.
- Changed abstract from "June" to "April" to align with data and extent information.
- Adjusted title and abstract to clarify contents of dataset.
ISSUES POTENTIALLY IMPACTING REUSE
- N/A
| File |
|---|
1006750_v1_santa_clara_river_isotopes.csv (Comma Separated Values (.csv), 5.05 KB) MD5:d3f358a22a55a5f5f7ba815795901215 Primary data file for dataset ID 1006750, version 1 |
| Parameter | Description | Units |
| UCID_sample_number | Unique laboratory sample identification number | unitless |
| sample_type | Sample type: Particulate organic carbon (POC) from river water or sedimentary organic carbon (SOC) from river silt or beach sand | unitless |
| site_name | Body of water name: SCR (Santa Clara River) | unitless |
| filter_number | Filter number: Filter 34, Filter 42, Filter 51, Filter 60, Filter 63, Filter 69, Sand A, Sand B, Silt A, Silt B | unitless |
| date_collected | Date sample was collected | unitless |
| D14C | Radiocarbon content expressed as Δ14C in per mil (‰), following the reporting conventions of Radiocarbon. Measurements were made at the Keck Carbon Cycle AMS Laboratory at the University of California, Irvine using accelerator mass spectrometry (AMS). Samples were graphitized from CO2 using the zinc reduction method. | ‰ |
| D14C_error | Analytical uncertainty of the Δ14C measurement, in per mil (‰), expressed as the standard error of replicate analyses. | ‰ |
| d13C | carbon-13/carbon-12 content expressed as δ13C in per mil (‰), following the reporting conventions using secondary standards corrected to Pee Dee Belemnite limestone standard. Measurements were made at the Keck Carbon Cycle AMS Laboratory at the University of California, Irvine using using a Gas Bench II and Thermo Electron Delta Plus isotope ratio mass spectrometer. | ‰ |
| d13C_error | Analytical uncertainty of the δ13C measurement, in per mil (‰), expressed as the standard error of replicate analyses. | ‰ |
| latitude | Latitude of sample collection, positive is North | decimal degrees |
| longitude | Longitude of samples collection, negative is West | decimal degrees |
| Dataset-specific Instrument Name | Keck Carbon Cycle AMS (KCCAMS) |
| Generic Instrument Name | Accelerator Mass Spectrometer |
| Dataset-specific Description | 14C analyses were performed at the Keck Carbon Cycle AMS (KCCAMS) Laboratory at UCI by our group. |
| Generic Instrument Description | An AMS measures "long-lived radionuclides that occur naturally in our environment. AMS uses a particle accelerator in conjunction with ion sources, large magnets, and detectors to separate out interferences and count single atoms in the presence of 1x1015 (a thousand million million) stable atoms, measuring the mass-to-charge ratio of the products of sample molecule disassociation, atom ionization and ion acceleration." AMS permits ultra low-level measurement of compound concentrations and isotope ratios that traditional alpha-spectrometry cannot provide. More from Purdue University: http://www.physics.purdue.edu/primelab/introduction/ams.html |
| Dataset-specific Instrument Name | Finnigan Delta Plus mass spectrometer |
| Generic Instrument Name | Isotope-ratio Mass Spectrometer |
| Dataset-specific Description | The CO2 obtained from combusted samples for 14C analysis were split and analyzed for δ13C using a Finnigan Delta Plus mass spectrometer at UCI. |
| 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). |
NSF abstract:
El Niño–Southern Oscillation (ENSO) causes changes in winds and sea surface temperature over the tropical eastern Pacific Ocean. Typically, this results in above average rainfall in Southern California. This project aims to understand how high rainfall associated with ENSO influences the delivery of carbon from land to the ocean. Specifically, the scientists will evaluate whether a unique pool of aged carbon derived from eroded soils in the watershed is transported to the ocean during these events. Samples of particulate and sedimentary organic carbon will be collected from the Santa Clara River in California. The samples will be collected under different river flow conditions between December 2023 and April 2024. The chemical composition of these samples will be analyzed and compared to samples collected during previous ENSO and non-ENSO time periods. This unique set of samples will record whether there are differences in the amounts and sources of carbon delivered to the ocean under different river flow conditions. Results from this study will improve global and long-term estimates of carbon export from land to the ocean. This project will support an early career scientist and an undergraduate student at the University of California-Irvine, a Hispanic-serving institution.
This study will examine the sources of organic carbon (OC) delivered to the coastal zone of Southern California during the upcoming El Niño event of 2023-24. The project will test the hypothesis that extreme precipitation in the Santa Clara River watershed mobilizes a unique pool of mineral-associated OC that differs from the OC that is mobilized during normal or low precipitation years. Previous studies have shown that the mineral-associated OC mobilized during the strong El Niño of 1997-98 had higher ∆14C and d13C values than the OC exported during low flow periods. The science team will collect particulate OC (POC) and sedimentary OC (SOC) samples from the Santa Clara River under different flow conditions during the 2023-2024 El Niño event. Radiocarbon (∆14C) and stable carbon isotope values (d13C) for bulk OC, and compound specific isotope analyses of n-alkanes will be measured. These data will be compared to data obtained during time periods when precipitation and river flow conditions varied (1997-98, 2002-03, 2021-22). This combination of isotope information will allow the scientists to estimate the relative contributions of organic matter derived from different sources as well as the contribution of eroded mineral associated OC to the sediments. The project will provide research and training opportunities for a postdoc and an undergraduate student at the University of California-Irvine (UCI), a Hispanic-serving institution. The postdoc will participate in the CLEAN Education Program (Climate, Literacy, Empowerment and iNquery) and design phenomenon–based science curricula for use in local high schools and undergraduate labs in the Earth System Science Department at UCI.
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.
| Funding Source | Award |
|---|---|
| NSF Division of Ocean Sciences (NSF OCE) |