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Data server object:  SF_Bay_Transects

    Vascular plant and microbial biomarkers of dissolved organic matter from San Francisco Bay transects

Vascular plant and microbial biomarkers of dissolved organic matter from San Francisco Bay transects

Website: https://www.bco-dmo.org/dataset/734790
Data Type: Other Field Results
Version: 2
Version Date: 2019-01-31

» Collaborative Research: Calibration and application of vascular plant and aqueous microbial biomarkers to examine transformations of dissolved organic matter (DOM biomarkers)
Hernes, PeterUniversity of California-Davis (UC Davis)Principal Investigator
Kaiser, KarlTexas A&M University (TAMU)Co-Principal Investigator
Spencer, RobertFlorida State University (FSU)Contact
Rauch, ShannonWoods Hole Oceanographic Institution (WHOI BCO-DMO)BCO-DMO Data Manager


Spatial Extent: N:38.478 E:-121.265 S:37.679 W:-122.508
Temporal Extent: 2014-12 - 2016-05

Dataset Description

Vascular plant and microbial biomarkers of dissolved organic matter from San Francisco Bay transects. San Francisco Bay transects were collected in December 2014 (Dec-14), June 2015 (Jun-15), and May 2016 (May-16).

Acquisition Description

Samples were collect on the USGS R/V Mary Landsteiner and pumped directly from the surface (1 m deep) with a pump and clean tycoon tubing connected to an inline 0.2 um Whatman Polycap filter.

All filters were pumped and field filtered through 0.7 um Whatman glass fiber filters (GF/F, precombusted at 550 degrees C) using a peristaltic pump after purging the line.

Samples for DOC concentration were acidified to pH 2 and stored in a refrigerator (4 degrees C) until analysis by high-temperature combustion on a Shimadzu TOC-L CPH within two weeks following collection. DOC was calculated as the mean of between three and five injections using a six-point standard curve using established protocols (Mann et al., 2012) and the coefficient of variance was always <2%.

Samples for CDOM absorbance were analyzed in a 1 cm cuvette on a Horiba Aqualog-UV-800-C. Absorbance spectra were measured from 230-800 nm, and corrected for a small offset either due to long-term baseline drift or derived from glass fiber particles during filtration (Blough et al., 1993), by subtracting the mean absorbance measured between 750-800 nm. Two spectral slopes were calculated at 275-295 nm and 350-400 nm (S275-295 and S350-400, respectively), and the spectral slope ratio (SR) was then calculated by dividing the former by the latter (Helms et al., 2008). The CDOM absorption ratio at 250 nm to 365 nm was calculated (a250:a365) and specific ultraviolet absorbance (SUVA254) was calculated by dividing the decadic absorption coefficient at 254 nm by DOC concentration (Weishaar et al., 2003; Fellman et al., 2009).

Fluorescence properties of FDOM were determined using a Horiba Aqualog-UV-800-C. The excitation emission matrices (EEMs) were generated in a 1 cm cuvette at varying integration times (1-10 seconds) to maximize the signal-to-noise ratio based on absorbance values. The EEMs were obtained at excitation (ex) 250-600 nm and at emission (em) 250-600 nm with 5 nm and 2 nm intervals respectively, and the EEMs were corrected for lamp intensity (Cory et al., 2010), inner filter effects (Kothawala et al., 2013), and normalized to Raman units (R.U.) (Stedmon et al., 2003). All corrections were performed using the FDOMcorr toolbox version 1.6 (Murphy, 2011). EEMs were analyzed with parallel factor analysis (PARAFAC) using the procedure described in Murphy et al. (2013). Furthermore, the fluorescence index (FI) (Cory et al., 2010), humification index (HIX) (Ohno, 2002; Zsolnay et al., 1999), and autotrophic productivity index (BIX) (Huguet et al., 2009) were calculated. FI was calculated from the emission wavelengths at 470 nm and 520 nm, obtained at excitation 370 nm (Cory and McKnight, 2005). HIX was calculated using the area under the emission sepctra 435-480 nm divided by the peak area 300-345 + 435-480 nm, at excitation 254 nm (Ohno, 2002). BIX was calculated from the emission intensity of 380 nm and 430 nm, obtained at excitation 310 nm (Wang et al., 2014).

Samples for FT-ICR MS analysis were solid-phase extracted using the procedure described in Dittmar et al., 2008. Filtered samples were acidified to pH 2 before solid phase extraction on 500 mg Agilent Bond Elut PPL cartridges. Each 1 L sample was extracted by eluting 2 mL of of methanol and then diluted to a DOC target concentration of 50 ug C mL-1. Extracted samples were stored at -20 degrees C prior to analysis on a 21 T (Bruker Daltonics, Billerica, MA, USA) FT-ICR MS located at the National High Magnetic Field Laboratory (NHMFL) (Tallahassee, Florida). Direct infusion electrospray ionization (ESI) generates negative ions at a flow rate of 700 nL min-1, and 100 time domain acquisitions were coadded for each mass spectrum.

Molecular formulas were assigned to signals >6RMS baseline noise with EnviroOrg ©,TM software (Koch et al., 2007; Stubbins et al., 2010). Elemental combinations of C1–45H1–92N0–4O1–25S0–2 with a mass accuracy of ≤300 ppb were considered for assignment. Classification of formulas were based on their elemental ratios (Corilo, 2015). The modified aromaticity index (Almod) of each formula was calculated and Almod values of 0.5-0.67 and ≥0.67 were classified as aromatic and condensed aromatic structures (Koch and Dittmar, 2006; Koch and Dittmar, 2016). Other compound classes were unsaturated low oxygen=Almod<0.5, H/C<1.5, O/C<0.5; unsaturated high oxygen=Almod<0.5, H/ C<1.5, O/C>0.5; aliphatics=H/C 1.5-2.0, O/C<0.9, N=0; peptide-like=H/C 1.5-2.0, O/C<0.9, N>0, and sugar-like= O/C>0.9. Sugar-like compounds provide a very minor contribution to %RA (mean = 0.05, ± 0.06 %RA) and so were combined with peptide-like compounds throughout. Although FT-ICR MS allows for the precise assignment of molecular formulas to signals that may represent multiple isomers, they describe the underlying molecular compounds comprising DOM, thus the term compound may be used when describing the signals detected by FT-ICR MS.

Lignin derived phenols were isolated from the dried solid phase extracts followed by cupric oxide oxidation and liquid-liquid extraction modified from Spencer et al., (2010). Briefly, PPL extracts were redissolved in O2 free 2 M NaOH in a 6 mL Teflon vial (Savillex Corp) containing 500 mg CuO, and amended with 100 mg ferrous ammonium sulfate and 50 mg glucose and reacted in a 155 degree C oven for 3 hours. Following oxidation, the samples were centrifuged and supernatants were decanted into 40 mL vials. Oxidation products were acidified to pH 1 with H3PO4 and t-cinnamic acid was added as an internal standard. Liquid-liquid extractions of the oxidation products were undertaken by addition of 4 mL ethyl acetate, vortexing, and centrifugation prior to removal of the ethyl acetate. Extracts were pipetted through drying columns containing sodium sulfate into a 4 mL vial. Samples were dried under ultra-high purity argon between each extraction for a total of three extractions, following the last extraction the sodium sulfate was rinsed with 1 mL of ethyl acetate into the extract vial. Dried ethyl acetate extracts were dissolved in pyridine and derivatized with N/O bis-trimethylsilyltrifluoromethylacetamide (BSTFA) at 60 degrees C for ten minutes. Lignin phenol monomers were measured as trimethylsilane derivatives using an Agilent 6890N GC/5975 MS and were quantified as the relative response factors of each compound compared to the response of t- cinnamic acid and a five-point calibration curve bracketing the concentration range. Eight lignin phenols from three phenol groups were quantified; vanillyl (vanillin, acetovanillone, vanillic acid), syringyl (syringaldehyde, acetosyringone, syringic acid), and coumaryl (coumaric acid, ferulic acid).

Seven neutral sugars (fucose, rhamnose, arabinose, galactose, glucose, mannose, xylose) were analyzed according to Skoog and Benner (1997) with modifications. Briefly, samples were hydrolyzed in 1.2 mol L−1 sulfuric acid and neutralized with a self-absorbed ion retardation resin (Kaiser and Benner, 2000). After desalting with a mixture of cation and anion exchange resins, neutral sugars were isocratically separated with 25 mM NaOH on a PA 1 column in a Dionex 500 system with a pulsed amperiometric detector (PAD).

The following amino acids were analyzed using the method of Kaiser and Benner, 2005: histidine, serine, arginine, glycine, aspartic acid, glutamic acid, threonine, alanine, lysine, tyrosine, methionine, valine, norvaline, isoleucine, leucine, phenylalanine.

Processing Description

BCO-DMO Processing:
- modified parameter names to conform with BCO-DMO naming conventions (removed units, replaced spaces with underscores);
- replaced "NaN" with "nd" (no data);
- 31-Jan-2019: updated dataset to version submitted on 20-Dec-2018.

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Related Publications

Blough, N. V., Zafiriou, O. C., & Bonilla, J. (1993). Optical absorption spectra of waters from the Orinoco River outflow: Terrestrial input of colored organic matter to the Caribbean. Journal of Geophysical Research: Oceans, 98(C2), 2271–2278. doi:10.1029/92jc02763 https://doi.org/10.1029/92JC02763
Corilo, Y. (2015) PetroOrg Software; Florida State University: Tallahassee, FL, 2014.
Cory, R. M., & McKnight, D. M. (2005). Fluorescence Spectroscopy Reveals Ubiquitous Presence of Oxidized and Reduced Quinones in Dissolved Organic Matter. Environmental Science & Technology, 39(21), 8142–8149. doi:10.1021/es0506962
Cory, R. M., Miller, M. P., McKnight, D. M., Guerard, J. J., & Miller, P. L. (2010). Effect of instrument-specific response on the analysis of fulvic acid fluorescence spectra. Limnology and Oceanography: Methods, 8(2), 67–78. doi:10.4319/lom.2010.8.67
Dittmar, T., Koch, B., Hertkorn, N., & Kattner, G. (2008). A simple and efficient method for the solid-phase extraction of dissolved organic matter (SPE-DOM) from seawater. Limnology and Oceanography: Methods, 6(6), 230–235. doi:10.4319/lom.2008.6.230
Fellman, J. B., Hood, E., D’Amore, D. V., Edwards, R. T., & White, D. (2009). Seasonal changes in the chemical quality and biodegradability of dissolved organic matter exported from soils to streams in coastal temperate rainforest watersheds. Biogeochemistry, 95(2-3), 277–293. doi:10.1007/s10533-009-9336-6
Helms, J. R., Stubbins, A., Ritchie, J. D., Minor, E. C., Kieber, D. J., & Mopper, K. (2008). Absorption spectral slopes and slope ratios as indicators of molecular weight, source, and photobleaching of chromophoric dissolved organic matter. Limnology and Oceanography, 53(3), 955–969. doi:10.4319/lo.2008.53.3.0955
Huguet, A., Vacher, L., Relexans, S., Saubusse, S., Froidefond, J. M., & Parlanti, E. (2009). Properties of fluorescent dissolved organic matter in the Gironde Estuary. Organic Geochemistry, 40(6), 706–719. doi:10.1016/j.orggeochem.2009.03.002
Kaiser, K., & Benner, R. (2005). Hydrolysis-induced racemization of amino acids. Limnology and Oceanography: Methods, 3(8), 318–325. doi:10.4319/lom.2005.3.318
Koch, B. P., & Dittmar, T. (2006). From mass to structure: an aromaticity index for high-resolution mass data of natural organic matter. Rapid Communications in Mass Spectrometry, 20(5), 926–932. doi:10.1002/rcm.2386
Koch, B. P., & Dittmar, T. (2015). From mass to structure: an aromaticity index for high-resolution mass data of natural organic matter. Rapid Communications in Mass Spectrometry, 30(1), 250–250. doi:10.1002/rcm.7433
Koch, B. P., Dittmar, T., Witt, M., & Kattner, G. (2007). Fundamentals of Molecular Formula Assignment to Ultrahigh Resolution Mass Data of Natural Organic Matter. Analytical Chemistry, 79(4), 1758–1763. doi:10.1021/ac061949s
Kothawala, D. N., Murphy, K. R., Stedmon, C. A., Weyhenmeyer, G. A., & Tranvik, L. J. (2013). Inner filter correction of dissolved organic matter fluorescence. Limnology and Oceanography: Methods, 11(12), 616–630. doi:10.4319/lom.2013.11.616
Mann, P. J., Davydova, A., Zimov, N., Spencer, R. G. M., Davydov, S., Bulygina, E., … Holmes, R. M. (2012). Controls on the composition and lability of dissolved organic matter in Siberia’s Kolyma River basin. Journal of Geophysical Research: Biogeosciences, 117(G1). doi:10.1029/2011jg001798 https://doi.org/10.1029/2011JG001798
Murphy, K. R. (2011). A Note on Determining the Extent of the Water Raman Peak in Fluorescence Spectroscopy. Applied Spectroscopy, 65(2), 233–236. doi:10.1366/10-06136
Ohno, T. (2002). Fluorescence Inner-Filtering Correction for Determining the Humification Index of Dissolved Organic Matter. Environmental Science & Technology, 36(4), 742–746. doi:10.1021/es0155276
Skoog, A., & Benner, R. (1997). Aldoses in various size fractions of marine organic matter: Implications for carbon cycling. Limnology and Oceanography, 42(8), 1803–1813. doi:10.4319/lo.1997.42.8.1803
Spencer, R. G. M., Aiken, G. R., Dyda, R. Y., Butler, K. D., Bergamaschi, B. A., & Hernes, P. J. (2010). Comparison of XAD with other dissolved lignin isolation techniques and a compilation of analytical improvements for the analysis of lignin in aquatic settings. Organic Geochemistry, 41(5), 445–453. doi:10.1016/j.orggeochem.2010.02.004
Stedmon, C. A., Markager, S., & Bro, R. (2003). Tracing dissolved organic matter in aquatic environments using a new approach to fluorescence spectroscopy. Marine Chemistry, 82(3-4), 239–254. doi:10.1016/s0304-4203(03)00072-0 https://doi.org/10.1016/S0304-4203(03)00072-0
Stubbins, A., Spencer, R. G. M., Chen, H., Hatcher, P. G., Mopper, K., Hernes, P. J., … Six, J. (2010). Illuminated darkness: Molecular signatures of Congo River dissolved organic matter and its photochemical alteration as revealed by ultrahigh precision mass spectrometry. Limnology and Oceanography, 55(4), 1467–1477. doi:10.4319/lo.2010.55.4.1467
Wang, Y., Zhang, D., Shen, Z., Chen, J., & Feng, C. (2014). Characterization and spacial distribution variability of chromophoric dissolved organic matter (CDOM) in the Yangtze Estuary. Chemosphere, 95, 353–362. doi:10.1016/j.chemosphere.2013.09.044
Weishaar, J. L., Aiken, G. R., Bergamaschi, B. A., Fram, M. S., Fujii, R., & Mopper, K. (2003). Evaluation of Specific Ultraviolet Absorbance as an Indicator of the Chemical Composition and Reactivity of Dissolved Organic Carbon. Environmental Science & Technology, 37(20), 4702–4708. doi:10.1021/es030360x
Zsolnay, A., Baigar, E., Jimenez, M., Steinweg, B., & Saccomandi, F. (1999). Differentiating with fluorescence spectroscopy the sources of dissolved organic matter in soils subjected to drying. Chemosphere, 38(1), 45–50. doi:10.1016/s0045-6535(98)00166-0 https://doi.org/10.1016/S0045-6535(98)00166-0

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DateDate of sample collection. Format: month-year. (e.g. Dec-14 = December 2014, Jun-15 = June 2015, May-16 = May 2016) unitless
SalinitySalinity PSU
LatLatitude of sample collection decimal degrees
LongLongitude of sample collection decimal degrees
TempTemperature degrees Celsius
pHpH unitless
DODissolved oxygen milligrams per liter (mg/L)
TurbidityTurbidity FNU
TSSTotal suspended solids milligrams per liter (mg/L)
DOC_uMDissolved organic carbon in uM micromolar (uM)
DOC_mgLDissolved organic carbon in mg/L milligrams per liter (mg/L)
FIFluorescence Index (DOM composition metric) unitless
HIXHumification Index (DOM composition metric) unitless
HIX_NormHumification Index Norm (DOM composition metric) unitless
BIXAutotrophic productivity index (DOM composition metric) unitless
abs_250CDOM absorbance at 250 nm reciprocal meters (m-1)
abs_254CDOM absorbance at 254 nm m-1
abs_350CDOM absorbance at 350 nm m-1
abs_365CDOM absorbance at 365 nm m-1
abs_412CDOM absorbance at 412 nm m-1
abs_440CDOM absorbance at 440 nm m-1
abs_ratio_250_365Absorbance ratio; absorbance at 250/365 unitless
SUVA254Specific UV absorbance at 254 nm L mgC-1 m-1
S275_295Spectral slope range 275-295 unitless
S350_400Spectral slope range 350-400 unitless
SrSpectral slope ratio (275-295/350-400) unitless
C1Fluorescence intensity of component 1 Raman units
C2Fluorescence intensity of component 2 Raman units
C3Fluorescence intensity of component 3 Raman units
C4Fluorescence intensity of component 4 Raman units
C5Fluorescence intensity of component 5 Raman units
C6Fluorescence intensity of component 6 Raman units
C7Fluorescence intensity of component 7 Raman units
C8Fluorescence intensity of component 8 Raman units
C9Fluorescence intensity of component 9 Raman units
C10Fluorescence intensity of component 10 Raman units
CtotalFluorescence intensity total Raman units
Num_formulaFT-ICR MS: Number of formula assigned unitless
Aliphatic_HighOCAliphatic High OC (FT-ICR MS compound class) % relative abundance
Aliphatic_LowOCAliphatic Low OC (FT-ICR MS compound class) % relative abundance
Condensed_aromaticsCondensed Aromatics (FT-ICR MS compound class) % relative abundance
Highly_Unsaturated_and_Phenolic_HighOCHighly unsaturated and phenolic high OC (FT-ICR MS compound class) % relative abundance
Highly_Unsaturated_and_Phenolic_LowOCHighly unsaturated and phenolic low OC (FT-ICR MS compound class) % relative abundance
Peptide_likePeptide-like (FT-ICR MS compound class) % relative abundance
Polyphenolic_HighOCPolyphenolic high OC (FT-ICR MS compound class) % relative abundance
Polyphenolic_LowOCPolyphenolic low OC (FT-ICR MS compound class) % relative abundance
conc_Sum8Lignin Phenols Concentration Sum of 8 micrograms per liter (ug/L)
conc_Sum6Lignin Phenols Concentration Sum of 6 micrograms per liter (ug/L)
Cnorm_Sum8Lignin Phenols C-normalized Sum of 8 mg/100 mg OC
Cnorm_Sum6Lignin Phenols C-normalized Sum of 6 mg/100 mg OC
S_to_VS:V (syringyl to vanillyl ratio) unitless
C_to_VC:V (cinnamyl to vanillyl ratio) unitless
Ad_to_Al_v(Ad:Al)v (Vanillic acid to aledhyde ratio) unitless
Ad_to_Al_s(Ad:Al)s (Syringic acid to aledhyde ratio) unitless
THAATotal hydrolyzable amino acids micromoles per liter (umol/L)
AspAspartic acid mol%
GluGlutamic acid mol%
SerSerine mol%
HisHistidine mol%
ThrThreonine mol%
GlyGlycine mol%
ArgArginine mol%
AlaAlanine mol%
TyrTyrosine mol%
ValValine mol%
IleIsoleucine mol%
PhePhenylalanine mol%
LeuLeucine mol%
LysLysine mol%
THNSTotal hydrolyzable neutral sugars micromoles per liter (umol/L)
FucFucose mol%
RhaRhamnose mol%
AraArabinose mol%
GalGalactose mol%
GlcGlucose mol%
ManMannose mol%
XylXylose mol%

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Dataset-specific Instrument Name
Horiba Aqualog-UV-800-C
Generic Instrument Name
Dataset-specific Description
Samples for CDOM absorbance were analyzed in a 1 cm cuvette on a Horiba Aqualog-UV-800-C (benchtop fluorometer). Fluorescence properties of FDOM were also determined using a Horiba Aqualog-UV-800-C. 
Generic Instrument Description
A fluorometer or fluorimeter is a device used to measure parameters of fluorescence: its intensity and wavelength distribution of emission spectrum after excitation by a certain spectrum of light. The instrument is designed to measure the amount of stimulated electromagnetic radiation produced by pulses of electromagnetic radiation emitted into a water sample or in situ.

Dataset-specific Instrument Name
Agilent 6890N GC/5975 MS
Generic Instrument Name
Gas Chromatograph
Dataset-specific Description
Lignin phenol monomers were measured as trimethylsilane derivatives using an Agilent 6890N GC/5975 MS.
Generic Instrument Description
Instrument separating gases, volatile substances, or substances dissolved in a volatile solvent by transporting an inert gas through a column packed with a sorbent to a detector for assay. (from SeaDataNet, BODC)

Dataset-specific Instrument Name
Dionex 500 system
Generic Instrument Name
Ion Chromatograph
Dataset-specific Description
Neutral sugars were isocratically separated in a Dionex 500 system with a pulsed amperiometric detector (PAD).
Generic Instrument Description
Ion chromatography is a form of liquid chromatography that measures concentrations of ionic species by separating them based on their interaction with a resin. Ionic species separate differently depending on species type and size. Ion chromatographs are able to measure concentrations of major anions, such as fluoride, chloride, nitrate, nitrite, and sulfate, as well as major cations such as lithium, sodium, ammonium, potassium, calcium, and magnesium in the parts-per-billion (ppb) range. (from http://serc.carleton.edu/microbelife/research_methods/biogeochemical/ic....)

Dataset-specific Instrument Name
Agilent 6890N GC/5975 MS
Generic Instrument Name
Mass Spectrometer
Dataset-specific Description
Lignin phenol monomers were measured as trimethylsilane derivatives using an Agilent 6890N GC/5975 MS.
Generic Instrument Description
General term for instruments used to measure the mass-to-charge ratio of ions; generally used to find the composition of a sample by generating a mass spectrum representing the masses of sample components.

Dataset-specific Instrument Name
Shimadzu TOC-L CPH
Generic Instrument Name
Shimadzu TOC-L Analyzer
Dataset-specific Description
DOC concentration was determined on a Shimadzu TOC-L CPH.
Generic Instrument Description
A Shimadzu TOC-L Analyzer measures DOC by high temperature combustion method. Developed by Shimadzu, the 680 degree C combustion catalytic oxidation method is now used worldwide. One of its most important features is the capacity to efficiently oxidize hard-to-decompose organic compounds, including insoluble and macromolecular organic compounds. The 680 degree C combustion catalytic oxidation method has been adopted for the TOC-L series. http://www.shimadzu.com/an/toc/lab/toc-l2.html

Dataset-specific Instrument Name
Generic Instrument Name
Fourier Transform Ion Cyclotron Resonance Mass Spectrometer
Dataset-specific Description
Samples were analyzed on a 21 T (Bruker Daltonics, Billerica, MA, USA) FT-ICR MS located at the National High Magnetic Field Laboratory (NHMFL) (Tallahassee, Florida).
Generic Instrument Description
In Fourier Transform Ion Cyclotron Resonance Mass Spectrometry, the mass-to-charge ratio (m/z) of an ion is experimentally determined by measuring the frequency at which the ion processes in a magnetic field. These frequencies, which are typically in the 100 KHz to MHz regime, can be measured with modern electronics making it possible to determine the mass of an ion to within +/- 0.000005 amu or 5 ppm.

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Project Information

Collaborative Research: Calibration and application of vascular plant and aqueous microbial biomarkers to examine transformations of dissolved organic matter (DOM biomarkers)

Coverage: San Francisco Bay Delta

NSF abstract:
Organic matter (OM) fluxes between and within terrestrial and oceanic reservoirs play an important role in the global carbon cycle. A clearer understanding of OM dynamics is critical for understanding fundamental processes and effects on greenhouse gases and climate. At present, researchers have an abundance of analytical methods and tools for investigating dissolved organic matter (DOM) cycling, but the field struggles to move past a qualitative understanding of sources, processing, and fates toward a quantitative understanding. Researchers from University of California-Davis, Woods Hole Oceanographic Institute, and Texas A&M University will develop biomarker tools to advance quantitative understanding of DOM cycling in riverine and estuarine environments in California, specifically targeting vascular plant and microbial markers. Results from this study will allow for future biomarker studies to quantitatively address DOM source and processing in aquatic environments and improve the limited understanding of the fate of terrestrial DOM in the ocean.

Broader Impacts: This study will provide interdisciplinary scientific training and development for undergraduate and graduate students, including individuals from underrepresented groups. Results from the study will be disseminated to the public, California stakeholders, and college students to educate them about the carbon cycle.

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

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This document is created by info v 4.1f 5 Oct 2018 from the content of the BCO-DMO metadata database.    2022-05-17  11:05:12