Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) allows for the characterization of dissolved organic matter at the molecular level. The water sample was collected near the NTL-LTER research buoy on Lake Mendota. Formula assignments were made to raw mass to charge ratios detected in the mass spectrum using a custom processing script and resulting in a list of chemical formulas making up the DOM sample.
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Ultraviolet-visible spectroscopy absorbances for dissolved organic matter from Lake Mendota from June – November 2017
Dissolved organic matter (DOM) is a complex mixture of organic compounds found in all natural waters. Its composition affects its reactivity towards numerous processes. Its composition is a function of both its source (e.g., allochthonous or autochthonous) as well as the extent of environmental processing it has undergone (e.g., chemical or biological degradation). Ultraviolet-visible (UV-vis) spectroscopy is an analytical technique commonly used to assess the composition of dissolved organic matter in water samples. Here, we present spectra from Lake Mendota samples collected from June - November in 2017 at the surface of Lake Mendota as well as at specific depths within the water column. All samples were collected near the NTL-LTER research buoy. Absorbance values are listed for wavelengths 200 - 800 nm for each sample.
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- Award ID(s):
- 2025982
- NSF-PAR ID:
- 10399077
- Publisher / Repository:
- Environmental Data Initiative
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Dissolved organic matter (DOM) is an intermediate between organic carbon formed by primary producers and carbon dioxide (CO2) produced through respiration, making it a key component of the carbon cycle in aquatic ecosystems. Its composition influences the routes of mineralization. Here, we evaluate DOM composition as a function of time and depth in Lake Mendota, a highly productive eutrophic lake that stratifies in warm months and is located in Madison, Wisconsin, USA. Dissolved organic carbon concentrations and optical properties are presented for 73 samples collected at a single location at varying depths within the water column from June to November. A subset of samples is analyzed by Fourier transform‐ion cyclotron resonance mass spectrometry (FT‐ICR MS) to investigate DOM composition at the molecular level. Temporally, increases in more oxidized formulas are observed in both the epilimnion and hypolimnion. At the surface, correlations between DOM formulas and both chlorophyll concentrations and light intensity show that photochemical reactions contribute to DOM oxidation. In the hypolimnion, redox conditions and interactions with sediments likely influence temporal compositional change. Our results show DOM composition varies with depth with more highly oxidized formulas identified deeper in the water column. However, DOM composition varies more temporally than by location within the water column. This work has implications for climate change as DOM photooxidation in lakes represents an understudied flux of CO2to the atmosphere. Additionally, lake eutrophication is increasing due to warming temperatures and this data set yields detailed molecular information about DOM composition and processing in such lakes.
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Site description. This data package consists of data obtained from sampling surface soil (the 0-7.6 cm depth profile) in black mangrove (Avicennia germinans) dominated forest and black needlerush (Juncus roemerianus) saltmarsh along the Gulf of Mexico coastline in peninsular west-central Florida, USA. This location has a subtropical climate with mean daily temperatures ranging from 15.4 °C in January to 27.8 °C in August, and annual precipitation of 1336 mm. Precipitation falls as rain primarily between June and September. Tides are semi-diurnal, with 0.57 m median amplitudes during the year preceding sampling (U.S. NOAA National Ocean Service, Clearwater Beach, Florida, station 8726724). Sea-level rise is 4.0 ± 0.6 mm per year (1973-2020 trend, mean ± 95 % confidence interval, NOAA NOS Clearwater Beach station). The A. germinans mangrove zone is either adjacent to water or fringed on the seaward side by a narrow band of red mangrove (Rhizophora mangle). A near-monoculture of J. roemerianus is often adjacent to and immediately landward of the A. germinans zone. The transition from the mangrove to the J. roemerianus zone is variable in our study area. An abrupt edge between closed-canopy mangrove and J. roemerianus monoculture may extend for up to several hundred meters in some locations, while other stretches of ecotone present a gradual transition where smaller, widely spaced trees are interspersed into the herbaceous marsh. Juncus roemerianus then extends landward to a high marsh patchwork of succulent halophytes (including Salicornia bigellovi, Sesuvium sp., and Batis maritima), scattered dwarf mangrove, and salt pans, followed in turn by upland vegetation that includes Pinus sp. and Serenoa repens. Field design and sample collection. We established three study sites spaced at approximately 5 km intervals along the western coastline of the central Florida peninsula. The sites consisted of the Salt Springs (28.3298°, -82.7274°), Energy Marine Center (28.2903°, -82.7278°), and Green Key (28.2530°, -82.7496°) sites on the Gulf of Mexico coastline in Pasco County, Florida, USA. At each site, we established three plot pairs, each consisting of one saltmarsh plot and one mangrove plot. Plots were 50 m^2 in size. Plots pairs within a site were separated by 230-1070 m, and the mangrove and saltmarsh plots composing a pair were 70-170 m apart. All plot pairs consisted of directly adjacent patches of mangrove forest and J. roemerianus saltmarsh, with the mangrove forests exhibiting a closed canopy and a tree architecture (height 4-6 m, crown width 1.5-3 m). Mangrove plots were located at approximately the midpoint between the seaward edge (water-mangrove interface) and landward edge (mangrove-marsh interface) of the mangrove zone. Saltmarsh plots were located 20-25 m away from any mangrove trees and into the J. roemerianus zone (i.e., landward from the mangrove-marsh interface). Plot pairs were coarsely similar in geomorphic setting, as all were located on the Gulf of Mexico coastline, rather than within major sheltering formations like Tampa Bay, and all plot pairs fit the tide-dominated domain of the Woodroffe classification (Woodroffe, 2002, "Coasts: Form, Process and Evolution", Cambridge University Press), given their conspicuous semi-diurnal tides. There was nevertheless some geomorphic variation, as some plot pairs were directly open to the Gulf of Mexico while others sat behind keys and spits or along small tidal creeks. Our use of a plot-pair approach is intended to control for this geomorphic variation. Plot center elevations (cm above mean sea level, NAVD 88) were estimated by overlaying the plot locations determined with a global positioning system (Garmin GPS 60, Olathe, KS, USA) on a LiDAR-derived bare-earth digital elevation model (Dewberry, Inc., 2019). The digital elevation model had a vertical accuracy of ± 10 cm (95 % CI) and a horizontal accuracy of ± 116 cm (95 % CI). Soil samples were collected via coring at low tide in June 2011. From each plot, we collected a composite soil sample consisting of three discrete 5.1 cm diameter soil cores taken at equidistant points to 7.6 cm depth. Cores were taken by tapping a sleeve into the soil until its top was flush with the soil surface, sliding a hand under the core, and lifting it up. Cores were then capped and transferred on ice to our laboratory at the University of South Florida (Tampa, Florida, USA), where they were combined in plastic zipper bags, and homogenized by hand into plot-level composite samples on the day they were collected. A damp soil subsample was immediately taken from each composite sample to initiate 1 y incubations for determination of active C and N (see below). The remainder of each composite sample was then placed in a drying oven (60 °C) for 1 week with frequent mixing of the soil to prevent aggregation and liberate water. Organic wetland soils are sometimes dried at 70 °C, however high drying temperatures can volatilize non-water liquids and oxidize and decompose organic matter, so 50 °C is also a common drying temperature for organic soils (Gardner 1986, "Methods of Soil Analysis: Part 1", Soil Science Society of America); we accordingly chose 60 °C as a compromise between sufficient water removal and avoidance of non-water mass loss. Bulk density was determined as soil dry mass per core volume (adding back the dry mass equivalent of the damp subsample removed prior to drying). Dried subsamples were obtained for determination of soil organic matter (SOM), mineral texture composition, and extractable and total carbon (C) and nitrogen (N) within the following week. Sample analyses. A dried subsample was apportioned from each composite sample to determine SOM as mass loss on ignition at 550 °C for 4 h. After organic matter was removed from soil via ignition, mineral particle size composition was determined using a combination of wet sieving and density separation in 49 mM (3 %) sodium hexametaphosphate ((NaPO_3)_6) following procedures in Kettler et al. (2001, Soil Science Society of America Journal 65, 849-852). The percentage of dry soil mass composed of silt and clay particles (hereafter, fines) was calculated as the mass lost from dispersed mineral soil after sieving (0.053 mm mesh sieve). Fines could have been slightly underestimated if any clay particles were burned off during the preceding ignition of soil. An additional subsample was taken from each composite sample to determine extractable N and organic C concentrations via 0.5 M potassium sulfate (K_2SO_4) extractions. We combined soil and extractant (ratio of 1 g dry soil:5 mL extractant) in plastic bottles, reciprocally shook the slurry for 1 h at 120 rpm, and then gravity filtered it through Fisher G6 (1.6 μm pore size) glass fiber filters, followed by colorimetric detection of nitrite (NO_2^-) + nitrate (NO_3^-) and ammonium (NH_4^+) in the filtrate (Hood Nowotny et al., 2010,Soil Science Society of America Journal 74, 1018-1027) using a microplate spectrophotometer (Biotek Epoch, Winooski, VT, USA). Filtrate was also analyzed for dissolved organic C (referred to hereafter as extractable organic C) and total dissolved N via combustion and oxidation followed by detection of the evolved CO_2 and N oxide gases on a Formacs HT TOC/TN analyzer (Skalar, Breda, The Netherlands). Extractable organic N was then computed as total dissolved N in filtrate minus extractable mineral N (itself the sum of extractable NH_4-N and NO_2-N + NO_3-N). We determined soil total C and N from dried, milled subsamples subjected to elemental analysis (ECS 4010, Costech, Inc., Valencia, CA, USA) at the University of South Florida Stable Isotope Laboratory. Median concentration of inorganic C in unvegetated surface soil at our sites is 0.5 % of soil mass (Anderson, 2019, Univ. of South Florida M.S. thesis via methods in Wang et al., 2011, Environmental Monitoring and Assessment 174, 241-257). Inorganic C concentrations are likely even lower in our samples from under vegetation, where organic matter would dilute the contribution of inorganic C to soil mass. Nevertheless, the presence of a small inorganic C pool in our soils may be counted in the total C values we report. Extractable organic C is necessarily of organic C origin given the method (sparging with HCl) used in detection. Active C and N represent the fractions of organic C and N that are mineralizable by soil microorganisms under aerobic conditions in long-term soil incubations. To quantify active C and N, 60 g of field-moist soil were apportioned from each composite sample, placed in a filtration apparatus, and incubated in the dark at 25 °C and field capacity moisture for 365 d (as in Lewis et al., 2014, Ecosphere 5, art59). Moisture levels were maintained by frequently weighing incubated soil and wetting them up to target mass. Daily CO_2 flux was quantified on 29 occasions at 0.5-3 week intervals during the incubation period (with shorter intervals earlier in the incubation), and these per day flux rates were integrated over the 365 d period to compute an estimate of active C. Observations of per day flux were made by sealing samples overnight in airtight chambers fitted with septa and quantifying headspace CO_2 accumulation by injecting headspace samples (obtained through the septa via needle and syringe) into an infrared gas analyzer (PP Systems EGM 4, Amesbury, MA, USA). To estimate active N, each incubated sample was leached with a C and N free, 35 psu solution containing micronutrients (Nadelhoffer, 1990, Soil Science Society of America Journal 54, 411-415) on 19 occasions at increasing 1-6 week intervals during the 365 d incubation, and then extracted in 0.5 M K_2SO_4 at the end of the incubation in order to remove any residual mineral N. Active N was then quantified as the total mass of mineral N leached and extracted. Mineral N in leached and extracted solutions was detected as NH_4-N and NO_2-N + NO_3-N via colorimetry as above. This incubation technique precludes new C and N inputs and persistently leaches mineral N, forcing microorganisms to meet demand by mineralizing existing pools, and thereby directly assays the potential activity of soil organic C and N pools present at the time of soil sampling. Because this analysis commences with disrupting soil physical structure, it is biased toward higher estimates of active fractions. Calculations. Non-mobile C and N fractions were computed as total C and N concentrations minus the extractable and active fractions of each element. This data package reports surface-soil constituents (moisture, fines, SOM, and C and N pools and fractions) in both gravimetric units (mass constituent / mass soil) and areal units (mass constituent / soil surface area integrated through 7.6 cm soil depth, the depth of sampling). Areal concentrations were computed as X × D × 7.6, where X is the gravimetric concentration of a soil constituent, D is soil bulk density (g dry soil / cm^3), and 7.6 is the sampling depth in cm.more » « less
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none. (Ed.)The concentration and isotopic composition (δC; C/N) of sedimentary organic matter (SOM) in near-shore bays and offshore shelves and basins is impacted by organic matter source (e.g., marine algae, terrestrial plants, and agricultural and sewage runoff) and natural and anthropogenic processes such as pollution, terrestrial runoff, and climate change, which can expand oxygen minimum zones, leading to decreased bottom-water dissolved oxygen (DO) and enhanced organic matter preservation. The factors that affect the sources and concentrations of SOM have not been extensively investigatedin the California margin. The objective of this study was to determine how the SOM concentrations andstable isotopes (δC; C/N) vary between shallow urban bays, offshore shelves, and deep basins and with other factors (water depth, DO and grain size). On cruises in 2018, surface sediments were collected using multicores and van-veen grabs. Samples were collected from shelves (10-14km offshore; 100-300m) and basins (90-130km offshore; 618-997m)and for comparison, urban bays in San Diego. The dissolved oxygen (DO) concentrations of seafloor-water preserved in the multicores were measured with a hand-held DO meter. In the lab, SOM concentrations were determined by Loss on Ignition (5 hours, 550°C) and grain-size distributions were determined by scanning on a CILAS 1190 particle size analyzer. Select sediments were dissolved in HCl and filtered to remove inorganic carbonates and the δC and C/N measured at UC Davis. All sediments were organic rich (2-21%) with mean grain sizes of fi ne sand or silt with variable clay (3-12%). In general, the sands were lower in organic matter (< 5%) compared to silty samples withvariable concentrations (2-22%). The greatest organic matter was found in the deeper hypoxic basins where DO was less than 1.5 mg/L. The δC & C/N were consistent with mixed terrestrial and marine organic sources and there was not a difference in mean values between the bays, shelves and basins.However, the values were highly variable for the urban bay and shelf sediments suggesting heterogenous input. Organic matter in coastal sediments are an important component of the global carbon cycle and abetter understanding of controlling factors is important in the face of climate change and increased anthropogenic impacts.more » « less
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Abstract This study presents a unique data set from a laboratory experiment where we explored changes in the chemical composition of deionized water samples exposed to smoke. Inside a laboratory hood, water samples placed into a chamber were exposed to smoke for up to 60 min. The pattern of variations in hydrochemistry observed over time with increasing smoke exposure was similar in response to two different smoke treatments generated from burning tree litter. To estimate the smoke dosage and assess the consistency of replicate smoke treatments, we conducted additional experiments to evaluate changes in light transmission. Smoke inputs to the deionized water samples drove changes in hydrochemistry, with increases in acidity (with decreasing pH values), the content of organic matter (with increasing concentrations of dissolved organic carbon and dissolved organic nitrogen), and the content of inorganic N species (with increasing concentrations of ammonium, nitrate, and nitrite). The study was conducted on deionized water samples, and the results may not be directly transferrable to natural waters. Stream or lake waters that are low in ionic strength, poorly buffered, or low in acid‐neutralizing capacity might respond the most similar to the results of this study. In contrast, well‐buffered surface waters having higher acid‐neutralizing capacity would be more likely to neutralize acidic inputs from the smoke without significant effects on water quality. The publicly available dataset associated with this study will contribute to further consideration of the relative importance of short‐term changes in hydrochemistry driven by in‐stream inputs (e.g., changes in water chemistry from direct smoke deposition to the water surface) in contrast to terrestrial inputs (e.g., changes in water chemistry stemming from altered flow paths and source areas of the burned watershed landscape).
