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Remote Sensing of CDOM, CDOM Spectral Slope, and Dissolved Organic Carbon in the Global Ocean

A Global Ocean Carbon Algorithm Database (GOCAD) has been developed from over 500 oceanographic field campaigns conducted worldwide over the past 30 years including in situ reflectances and coincident satellite imagery, multi- and hyperspectral Chromophoric Dissolved Organic Matter (CDOM) absorption coefficients from 245–715 nm, CDOM spectral slopes in eight visible and ultraviolet wavebands, dissolved and particulate organic carbon (DOC and POC, respectively), and inherent optical, physical, and biogeochemical properties. From field optical and radiometric data and satellite measurements, several semi-analytical, empirical, and machine learning algorithms for retrieving global DOC, CDOM, and CDOM slope were developed, optimized for global retrieval, and validated. Global climatologies of satellite-retrieved CDOM absorption coefficient and spectral slope based on the most robust of these algorithms lag seasonal patterns of phytoplankton biomass belying Case 1 assumptions, and track terrestrial runoff on ocean basin scales. Variability in satellite retrievals of CDOM absorption and spectral slope anomalies are tightly coupled to changes in atmospheric and oceanographic conditions associated with El Niño Southern Oscillation (ENSO), strongly covary with the multivariate ENSO index in a large region of the tropical Pacific, and provide insights into the potential evolution and feedbacks related to sea surface dissolved carbon in a warming climate. Further validation of the DOC algorithm developed here is warranted to better characterize its limitations, particularly in mid-ocean gyres and the southern oceans.

Dissolved organic carbon↗

Organic Matter Composition in June 2023 and September 2023 Across the McKenzie Sub-Basin Impacted by the 2020 Holiday Farm Fire

This dataset represents results from a field study aiming to understand the variability in post-fire responses of dissolved organic matter and determine drivers of post-fire responses. Samples were collected at 58 sites within the McKenzie River Watershed (Oregon, USA) that were upstream, within, and downstream of the Holiday Farm Fire burn perimeter. The samples were collected in June 2023 and September 2023 during storm events, approximately 3 years post-fire. Samples were characterized for benezenepolycarboxylic acids (BPCA) and ultra-high resolution mass spectrometry. Dissolved organic carbon and optics (absorbance and fluorescence) data can be found in a separate data packages (https://ir.library.oregonstate.edu/concern/datasets/zc77sz60m, https://ir.library.oregonstate.edu/concern/datasets/mc87q034m). Related data from a subset of sites from 2020-2022 can be found at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1869708 and https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2478546. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset contains (1) file-level metadata; (2) data dictionary; (3) data package readme; (4) metadata; (5) methods information; (6) benzene polycarboxylic acid (BPCA) concentration data; (7) Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) methods; (8) folder of high resolution characterization of organic matter via 12 Tesla FTICR-MS data generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗

Satellite-Derived Distributions, Inventories and Fluxes of Dissolved and Particulate Organic Matter Along the Northeastern U.S. Continental Margin

Estuaries and the coastal ocean experience a high degree of variability in the composition and concentration of particulate and dissolved organic matter (DOM) as a consequence of riverine and estuarine fluxes of terrigenous DOM, sediments, detritus and nutrients into coastal waters and associated phytoplankton blooms. Our approach integrates biogeochemical measurements, optical properties and remote sensing to examine the distributions and inventories of organic carbon in the U.S. Middle Atlantic Bight and Gulf of Maine. Algorithms developed to retrieve colored DOM (CDOM), Dissolved (DOC) and Particulate Organic Carbon (POC) from NASA's MODIS-Aqua and SeaWiFS satellite sensors are applied to quantify the distributions and inventories of DOC and POC. Horizontal fluxes of DOC and POC from the continental margin to the open ocean are estimated from SeaWiFS and MODIS-Aqua distributions of DOC and POC and horizontal divergence fluxes obtained from the Northeastern North Atlantic ROMS model. SeaWiFS and MODIS imagery reveal the importance of estuarine outflow to the export of CDOM and DOC to the coastal ocean and a net community production of DOC on the shelf.

Mannino, A.↗

Data and scripts associated with “Non-random processes impacting organic matter chemistry are maximized in mid-order streams”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.

54 ENVIRONMENTAL SCIENCES↗

Sponge exhalent metabolites influence coral reef picoplankton dynamics

Coral reef sponges efficiently take up particulate and dissolved organic matter (DOM) from the water column and release compounds such as nucleosides, amino acids, and other dissolved metabolites to the surrounding reef via their exhalent seawater, but the influence of this process on reef picoplankton and nutrient processing is relatively unexplored. Here we examined the impact of sponge exhalent on the reef picoplankon community and subsequent alterations to the reef dissolved metabolite pool. We exposed reef picoplankton communities to a sponge exhalent water mixture (Niphates digitalis and Xestospongia muta) or filtered reef seawater (control) in closed, container-based dark incubations. We used 16S rRNA gene sequencing and flow cytometry-based cell counts to examine the picoplankton community and metabolomics and other analyses to examine the dissolved metabolite pool. The initial sponge exhalent was enriched in adenosine, inosine, chorismate, humic-like and amino acid-like components, and ammonium. Following 48 h of exposure to sponge exhalent, the picoplankton differed in composition, were reduced in diversity, showed doubled (or higher) growth efficiencies, and harbored increased copiotrophic and denitrifying taxa (Marinomonas, Pontibacterium, Aliiroseovarius) compared to control, reef-water based incubations. Alongside these picoplankton alterations, the sponge treatments, relative to seawater controls, had decreased adenosine, inosine, tryptophan, and ammonium, metabolites that may support the observed higher picoplankton growth efficiencies. Sponge treatments also had a net increase in several monosaccharides and other metabolites including anthranilate, riboflavin, nitrite, and nitrate. Our work demonstrates a link between sponge exhalent-associated metabolites and the picoplankton community, with exhalent water supporting an increased abundance of efficient, copiotrophic taxa that catabolize complex nutrients. The copiotrophic taxa were often different from those observed in previous algae and coral studies. These results have implications for better understanding the multifaceted role of sponges on picoplankton biomass with subsequent potential impacts to coral and other planktonic feeders in oligotrophic reef environments.

59 BASIC BIOLOGICAL SCIENCES↗

Data for Myers-Pigg et al. (2026), "Short-term coastal forest responses to a hurricane-scale freshwater and saltwater flooding experiment"

Coastal upland forests are exposed to intensifying precipitation regimes and sea level rise, increasing tree mortality and transforming these coastal forests into wetland ecosystems. Despite these well-known risks, the differing degrees to which hydrological, biogeochemical, and biological components of upland forests respond to novel salinity exposure is relatively unknown. The Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experiment decouples two distinct disturbances associated with hydrological extremes: (1) flooding from heavy precipitation and (2) exposure to saline conditions from storm surge. This dataset includes data reported in Myers-Pigg et al. (2025), which analyzed data from the first TEMPEST flooding treatment in 2022. This includes: - Colored dissolved organic matter in porewaters - Soil temperature and oxygen - Groundwater temperature and chemistry - Dissolved organic carbon concentrations in porewaters - Soil-to-atmosphere CH4 and CO2 fluxes - Soil temperature, water content, and electrical conductivity - Root-influenced CH4 and CO2 flux - Tree sap flow velocity - The R analytical code and documentation about the computational environmental in which it was run (the "sessionInfo.txt" file) All data files are plain-text comma separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗

Lambda-PFLOTRAN 1.0: a workflow for incorporating organic matter chemistry informed by ultra high resolution mass spectrometry into biogeochemical modeling

Abstract. Organic matter (OM) composition plays a central role in microbial respiration of dissolved organic matter and subsequent biogeochemical reactions. Here, a direct connection of organic matter chemistry and thermodynamics to reactive transport simulators has been achieved through the newly developed Lambda-PFLOTRAN workflow tool that succinctly incorporates carbon chemistry data generated from Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) into reaction networks to simulate organic matter degradation and the resulting biogeochemistry. Lambda-PFLOTRAN is a Python-based workflow, executed through a Jupyter notebook interface, that digests raw FTICR-MS data, develops a representative reaction network based on substrate-explicit thermodynamic modeling (also termed lambda modeling due to its key thermodynamic parameter λ used therein), and completes a biogeochemical simulation with the open source, reactive flow and transport code PFLOTRAN. The workflow consists of the following five steps: configuration, thermodynamic (lambda) analysis, sensitivity analysis, parameter estimation, and simulation output and visualization. Two test cases are provided to demonstrate the functionality of the Lambda-PFLOTRAN workflow. The first test case uses laboratory incubation data of temporal oxygen depletion to fit lambda parameters (i.e., maximum utilization rate and microbial carrying capacity). A slightly more complex second test case fits multiple lambda formulation and soil organic matter release parameters to temporal greenhouse gas generation measured during a soil incubation. Overall, the Lambda-PFLOTRAN workflow facilitates upscaling by using molecular-scale characterization to inform biogeochemical processes occurring at larger scales.

58 GEOSCIENCES↗

Untargeted Exometabolomics Provides a Powerful Approach to Investigate Biogeochemical Hotspots with Vegetation and Polygon Type in Arctic Tundra Soils

Rising temperatures in the Arctic have led to the thawing of tundra soils, which is rapidly changing terrain, hydrology, and plant and microbial communities, causing hotspots of biogeochemical activity across the landscape. Despite this, little is known about how nutrient-rich low molecular weight dissolved organic matter (LMW DOM) varies within and across tundra ecosystems. Using a high-resolution nano-liquid chromatography-mass spectrometry (LC/MS) approach, we characterized the composition and availability of LMW DOM from high-centered polygons (HCP) and low-centered polygons (LCP) with Eriophorum angustifolium or Carex aquatilis as the dominant vegetation. Over 3000 unique features (i.e., discrete mass/charge ions) were detected; 521 were identified as differentially abundant between polygonal types and 217 were putatively annotated using high mass accuracy MS data. While polygon type was a strong predictor of LMW DOM composition and availability, vegetation and soil depth were also important drivers. Extensive evidence was found for enhanced microbial processing at the LCP sites, which were dominated by Carex plant species. We detected significant differences between polygon types with varying aboveground landscape features or properties, and hotspots of biogeochemical activity, indicating LMW DOM, as quantified by untargeted exometabolomics, provides a window into the dynamic complex interactions between landscape topography, vegetation, and organic matter cycling in Arctic polygonal tundra soils.

58 GEOSCIENCES↗

Water chemistry in flume channel and hyporheic zone (i.e., porewater) associated with: “Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry”

Dissolved oxygen (DO), total organic carbon (TOC), total nitrogen (TN), molecular data for organic matter, and biochemical reactions for surface water and porewater (i.e., hyporheic zone) collected from a water recirculating flume located at the University of Texas, Austin. The flume contained real river water from Lower Colorado River(Austin, TX) and clean sand. Hyporheic exchange in the flume was induced through The study aims to understand relationships between aerobic metabolism of organic matter and molecular characteristics of organic matter, such as thermodynamic signature and nitrogen content, through the extent of the hyporheic zone at 10 cm- resolution, and through time. During the experiment, organic matter (dry leaves) was added to the flume and removed after 24 hours. The water samples were collected before the addition of leaves, at the time of removal of leaves, and at hour 72. The water samples were analyzed using ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) and total organic carbon (TOC) and total nitrogen (TN) analysis. Dissolved oxygen content throughout the surface water and the hyporheic zone of the flume was measured with a large planar optode. This data package is associated with the publication ’ Rethinking Aerobic Respiration in the Hyporheic Zone Under Variation in Carbon and Nitrogen Stoichiometry’ published in Environmental Science and Technology (Turețcaia et al., 2023 https://doi.org/10.1021/acs.est.3c04765). The dataset is comprised of five folders (1) Diss_O2_pic, (2) input_files (3) output_files; (4) python_code; and (5) R_code . Diss_O2_pic contains siximages of dissolved oxygen distribution in a bedform at hours 0, 24, and 72 of the experiment conducted in a large recirculation flume. Images are in separate R and G channels (i.e., RGB). The input_files contains (1) a csv file with FTICR peaks identified within each sample, (2) a csv file with molecular information pertinent to FTICR data with Gibbs free energy calculations adjusted for environmental temperature, (3) a csv file containing concentrations of non-purgeable organic carbon measured throughout the experiment , (4) a csv file containing concentrations of total nitrogen measured throughout the experiment, (5) a csv file containing total biochemical reactions (i.e., transformations) identified in the dataset, (6) a csv containing transformation profiles, and (7) a csv file containing transformations with formulas, and (8) a jpg file with schematic representation of locations for sample collection. The output_files contains (1) and xlsx file containing percent biochemical reactions containing nitrogen identified across all 39 sample, (2) a csv file of merged FTICR data and molecular information files, (3) a csv files containing average Gibbs free energy within sampling domains and at each sampling location, (4) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 0, (5) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 24, (6) a csv file with average concentrations of dissolved oxygen across sampling locations at hour 72, (7) a csv file with percent chemical classes identified across sampling locations at hour 0, (8) a csv file with percent chemical classes identified across sampling locations at hour 24, (9) a csv file with percent chemical classes identified across sampling locations at hour 72, and (10) a csv file containing percent nitrogen containing biochemical reactions identified across sampling locations at hours 0, 24, and 72. The python_code contains seven ipynb files which are Jupyter Notebooks used for data analysis and figures generation. The R_code contains 3 R files with R code used for data analysis and figures generation. This data package contains the processed data used in the associated manuscript. This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗

Impacts of Forest Fire Ash on Aquatic Mercury Cycling

Mercury (Hg) is a ubiquitous contaminant in the environment and its methylated form, methylmercury (MeHg), poses a worldwide health concern for humans and wildlife, primarily through fish consumption. Global production of forest fire ash, derived from wildfires and prescribed burns, is rapidly increasing due to a warming climate, but their interactions with aqueous and sedimentary Hg are poorly understood. In this study, we compared the differences of wildfire ash with activated carbon and biochar on the sorption of aqueous inorganic Hg and sedimentary Hg methylation. Sorption of aqueous inorganic Hg was greatest for wildfire ash materials (up to 0.21 μg g ₋1 or 2.2 μg g ₋1 C) among all of the solid sorbents evaluated. A similar Hg adsorption mechanism for activated carbon, biochar made of walnut, and wildfire ash was found that involves the formation of complexes between Hg and oxygen-containing functional groups, especially the ₋COO group. Notably, increasing dissolved organic matter from 2.4 to 70 mg C L ₋1 remarkably reduced Hg sorption (up to 40% reduction) and increased the time required to reach Hg–sorbent pseudo-equilibrium. Surprisingly, biochar and wildfire ash, but not activated carbon, stimulated MeHg production during anoxic sediment incubation, possibly due to the release of labile organic matter. Overall, our study indicates that while wildfire ash can sequester aqueous Hg, the leaching of its labile organic matter may promote production of toxic MeHg in anoxic sediments, which has an important implication for potential MeHg contamination in downstream aquatic ecosystems after wildfires.

54 ENVIRONMENTAL SCIENCES↗

Demethylation or Sorption? The Fate of Methylmercury in the Presence of Manganese Dioxide

Manganese oxide (MnO 2 ) amendments to mercury (Hg)-contaminated sediment have been shown to decrease methylmercury (MeHg) concentrations in sediment porewater. In the absence of solid-phase MeHg measurements, it is unclear whether the decreased porewater concentrations are due to inhibition of methylation, adsorption of the MeHg to the MnO 2 , demethylation of MeHg catalyzed by the MnO 2 , or some combination of these mechanisms. We conducted controlled laboratory experiments to determine whether MeHg losses from solution in the presence of amorphous MnO 2 are due to sorption or demethylation. In this work, we quantified MeHg in the dissolved phase and solid phase and found that no demethylation occurred. We used batch and isotherm experiments to determine MeHg sorption efficiency to MnO 2 in a variety of solutions with varying ionic strength and dissolved organic matter (DOM) concentration. Isotherms over an initial concentration range of 5–500 ng/L of MeHg showed no saturation effects. Increasing ionic strength from 0.012 M to 0.1 M produced relatively minor decreases in MeHg sorption. Increasing DOM concentrations from 0.64 to 16.4 mg C/L yielded substantial decreases in MeHg sorption. Under the experimental conditions, MnO2 is a less efficient MeHg sorbent compared to other sorbent materials, such as Thiol-SAMMS®, activated carbon, and biochar.

42 ENGINEERING↗

Data and scripts associated with a manuscript investigating impacts of solid phase extraction on freshwater organic matter optical signatures and mass spectrometry pairing

This data package is associated with the publication “Investigating the impacts of solid phase extraction on dissolved organic matter optical signatures and the pairing with high-resolution mass spectrometry data in a freshwater system” submitted to “Limnology and Oceanography: Methods.” This data is an extension of the River Corridor and Watershed Biogeochemistry SFA’s Spatial Study 2021 (https://doi.org/10.15485/1898914). Other associated data and field metadata can be found at the link provided. The goal of this manuscript is to assess the impact of solid phase extraction (SPE) on the ability to pair ultra-high resolution mass spectrometry data collected from SPE extracts with optical properties collected on ambient stream samples. Forty-seven samples collected from within the Yakima River Basin, Washington were analyzed dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), absorbance, and fluorescence. Samples were subsequently concentrated with SPE and reanalyzed for each measurement. The extraction efficiency for the DOC and common optical indices were calculated. In addition, SPE samples were subject to ultra-high resolution mass spectrometry and compared with the ambient and SPE generated optical data. Finally, in addition to this cross-platform inter-comparison, we further performed and intra-comparison among the high-resolution mass spectrometry data to determine the impact of sample preparation on the interpretability of results. Here, the SPE samples were prepared at 40 milligrams per liter (mg/L) based on the known DOC extraction efficiency of the samples (ranging from ~30 to ~75%) compared to the common practice of assuming the DOC extraction efficiency of freshwater samples at 60%. This data package folder consists of one main data folder with one subfolder (Data_Input). The main data folder contains (1) readme; (2) data dictionary (dd); (3) file-level metadata (flmd); (4) final data summary output from processing script; and (5) the processing script. The R-markdown processing script (SPE_Manuscript_Rmarkdown_Data_Package.rmd) contains all code needed to reproduce manuscript statistics and figures (with the exception of that stated below). The Data_Input folder has two subfolders: (1) FTICR and (2) Optics. Additionally, the Data_Input folder contains dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data (SPS_NPOC_Summary.csv) and relevant supporting Solid Phase Extraction Volume information (SPS_SPE_Volumes.csv). Methods information for the optical and FTICR data is embedded in the header rows of SPS_EEMs_Methods.csv and SPS_FTICR_Methods.csv, respectively. In addition, the data dictionary (SPS_SPE_dd.csv), file level metadata (SPS_SPE_flmd.csv), and methods codes (SPS_SPE_Methods_codes.csv) are provided. The FTICR subfolder contains all raw FTICR data as well as instructions for processing. In addition, post processed FTICR molecular information (Processed_FTICRMS_Mol.csv) and sample data (Processed_FTICRMS_Data.csv) is provided that can be directly read into R with the associated R-markdown file. The Optics subfolder contains all Absorbance and Fluorescence Spectra. Fluorescence spectra have been blank corrected, inner filter corrected, and undergone scatter removal. In addition, this folder contains Matlab code used to make a portion of Figure 1 within the manuscript, derive various spectral parameters used within the manuscript, and used for parallel factor analysis (PARAFAC) modeling. Spectral indices (SPS_SpectralIndices.csv) and PARAFAC outputs (SPS_PARAFAC_Model_Loadings.csv and SPS_PARAFAC_Sample_Scores.csv) are directly read into the associated R-markdown file. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected some of these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Optical Classification of Lower Amazon Waters Based on In Situ Data and Sentinel-3 Ocean and Land Color Instrument Imagery

Optical water types (OWTs) were identified from an in situ dataset of concomitant biogeochemical and optical parameters acquired in the Amazon River and its tributaries, in the Lower Amazon region, at different hydrological conditions from 2014 to 2017. A seasonal bio-optical characterization was performed. The k-means classification was applied to the in situ normalized reflectance spectra (rn(λ)), allowing the identification of four OWTs. An optical index method was also applied to the rn(λ) defining the thresholds of the OWTs. Next, level-3 Sentinel-3 Ocean and Land Color Instrument images representative of the seasonal discharge conditions were classified using the identified in situ OWTs as reference. The differences between Amazon River and clearwater tributary OWTs were dependent on the hydrological dynamics of the Amazon River, also showing a strong seasonal variability. Each OWT was associated with a specific bio-optical and biogeochemical environment assessed from the corresponding absorption coefficient values of colored dissolved organic matter (aCDOM) and particulate matter (ap), chlorophyll-a and suspended particulate matter (SPM) concentrations, and aCDOM/ap ratio. The rising water season presented a unique OWT with high SPM concentration and high relative contribution of ap to total absorption compared to the other OWTs. This bio-optical characterization of Lower Amazon River waters represents a first step for developing remote sensing inversion models adjusted to the optical complexity of this region.

54 ENVIRONMENTAL SCIENCES↗

Multi-Scale Temporal Patterns in Stream Biogeochemistry Indicate Linked Permafrost and Ecological Dynamics of Boreal Catchments

Temporal patterns in stream chemistry provide integrated signals describing the hydrological and ecological state of whole catchments. However, stream chemistry integrates multi-scale signals of processes occurring in both the catchment and stream. Deconvoluting these signals could identify mechanisms of solute transport and transformation and provide a basis for monitoring ecosystem change. Here, we applied trend analysis, wavelet decomposition, multivariate autoregressive state-space modeling, and analysis of concentration-discharge relationships to assess temporal patterns in high-frequency (15 min) stream chemistry from permafrost-influenced boreal catchments in Interior Alaska at diel, storm, and seasonal time scales. We compared catchments that varied in spatial extent of permafrost to identify characteristic biogeochemical signals. Catchments with higher spatial extents of permafrost were characterized by increasing nitrate concentration through the thaw season, an abrupt increase in nitrate and fluorescent dissolved organic matter (fDOM) and declining conductivity in late summer, and flushing of nitrate and fDOM during summer rainstorms. In contrast, these patterns were absent, of lower magnitude, or reversed in catchments with lower permafrost extent. Solute dynamics revealed a positive influence of permafrost on fDOM export and the role of shallow, seasonally dynamic flowpaths in delivering solutes from high-permafrost catchments to streams. Lower spatial extent of permafrost resulted in static delivery of nitrate and limited transport of fDOM to streams. Shifts in concentration-discharge relationships and seasonal trends in stream chemistry toward less temporally dynamic patterns might therefore indicate reorganized catchment hydrology and biogeochemistry due to permafrost thaw.

54 ENVIRONMENTAL SCIENCES↗

A Synthesis of Light Absorption Properties of the Arctic Ocean: Application to Semi-analytical Estimates of Dissolved Organic Carbon Concentrations from Space

The light absorption coefficients of particulate and dissolved materials are the main factors determining the light propagation of the visible part of the spectrum and are, thus, important for developing ocean color algorithms. While these absorption properties have recently been documented by a few studies for the Arctic Ocean [e.g., Matsuoka et al., 2007, 2011; Ben Mustapha et al., 2012], the datasets used in the literature were sparse and individually insufficient to draw a general view of the basin-wide spatial and temporal variations in absorption. To achieve such a task, we built a large absorption database at the pan-Arctic scale by pooling the majority of published datasets and merging new datasets. Our results showed that the total non-water absorption coefficients measured in the Eastern Arctic Ocean (EAO; Siberian side) are significantly higher 74 than in the Western Arctic Ocean (WAO; North American side). This higher absorption is explained 75 by higher concentration of colored dissolved organic matter (CDOM) in watersheds on the Siberian 76 side, which contains a large amount of dissolved organic carbon (DOC) compared to waters off 77 North America. In contrast, the relationship between the phytoplankton absorption (a()) and chlorophyll a (chl a) concentration in the EAO was not significantly different from that in the WAO. Because our semi-analytical CDOM absorption algorithm is based on chl a-specific a() values [Matsuoka et al., 2013], this result indirectly suggests that CDOM absorption can be appropriately erived not only for the WAO but also for the EAO using ocean color data. Derived CDOM absorption values were reasonable compared to in situ measurements. By combining this algorithm with empirical DOC versus CDOM relationships, a semi-analytical algorithm for estimating DOC concentrations for coastal waters at the Pan-Arctic scale is presented and applied to satellite ocean color data.

Pan-Arctic↗

Quantitative Separation of Unknown Organic–Metal Complexes by Liquid Chromatography–Inductively Coupled Plasma-Mass Spectrometry

Dissolved organic matter (DOM) is widely recognized to control the solubility and reactivity of trace metals in the environment. However, the mechanisms that govern metal-DOM complexation remain elusive, primarily due to the analytical challenge of fractionating and quantifying metal–organic species within the complex mixture of organic compounds that comprise DOM. Here, we describe a quantitative method for fractionation and element-specific detection of organic–metal complexes using liquid chromatography with online inductively coupled plasma mass spectrometry (LC–ICP-MS). The method implements a post-column compensation gradient to stabilize ICP–MS elemental response across the LC solvent gradient, thereby overcoming a major barrier to achieving quantitative accuracy with LC–ICP-MS. With external calibration and internal standard correction, the method yields concentrations of organic–metal complexes that were consistently within 6% of their true values, regardless of the complex’s elution time. We used the method to evaluate the effects of four stationary phases (C18, phenyl, amide, and pentafluoroylphenyl propyl) on the recovery and separation of environmentally relevant trace metals (Mn, Fe, Co, Ni, Cu, Zn, Cd, and Pb) in Suwannee River Fulvic Acid and Suwannee River Natural Organic Matter. The C18, amide, and phenyl phases generally yielded optimal metal recoveries (>75% for all metals except Pb), with the phenyl phase separating polar species to a greater extent than C18 or amide. We also fractionated organic-bound Fe, Cu, and Ni in oxidized and reduced soils, revealing divergent metal-DOM speciation across soil redox environments. Finally, by enabling quantitative fractionation of DOM-bound metals, our method offers a means for advancing a mechanistic understanding of metal–organic complexation throughout the environment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Phytoplankton exudates and lysates support distinct microbial consortia with specialized metabolic and ecophysiological traits

Marine dissolved organic matter, which originates from phytoplankton, holds as much carbon as Earth’s atmosphere; yet, the biological processes governing its fate are primarily studied under idealized laboratory conditions or through indirect measures such as genome sequencing. In this work, we used isotope labeling to directly quantify uptake of complex carbon pools from the two primary sources of marine organic carbon (diatoms and cyanobacteria) by a natural microbial community. Furthermore, our data show that carbon pools are partitioned into distinct microbial lineages whose physiological properties and resource acquisition strategies match the chemical nature of their preferred substrates. Our results provide ecological and functional insights into the patterns of microbial community structure changes that occur during marine phytoplankton blooms.

59 BASIC BIOLOGICAL SCIENCES↗

Compositional changes of dissolved organic molecules along water flow and their influencing factors in the Three Gorges Reservoir

Molecular composition of dissolved organic matter (DOM) and its influencing factors in river reservoirs remains elusive. Here, molecular compositions of DOM, bacterial community structures, and water physiochemistry were investigated in the field and microcosm samples of the Three Gorges Reservoir (TGR). The results showed that DOM molecular compositions were significantly (R 2 = 0.245, p < 0.001) correlated with bacterial community structures in the studied field samples, suggesting that bacteria may actively interact with DOM molecules. In this study, the molecular compositions of DOM in the studied field samples were significantly (p < 0.05) affected by the distance between the sample sites and the Three Gorges Dam and by bacterial groups of Actinobacteria and Alphaproteobacteria, suggesting that both hydrological and bacterial processes may contribute to the variation in DOM molecular composition in the TGR water. Furthermore, microcosm experiments demonstrated that both microbial and abiotic processes may transform and/or produce DOM in the TGR, thereby affecting DOM molecular composition. Microbial process increased the average aromaticity index and decreased the carbon number of DOM molecules with increasing incubation duration; whereas average oxygen number, double bond equivalent, and oxidation state of carbon of DOM molecules increased during the first 14 days of incubation and began to decrease thereafter. Taken together, this study expands our understanding of the impact of microbial process on the DOM molecular composition in reservoir ecosystems, and has great implications for carbon cycling in major rivers.

58 GEOSCIENCES↗