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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Tonlé Sap Food Security and Agriculture: Evaluating the Effects of Land Use and Hydrological Change on Ecosystem Vitality using Remotely-Sensed Data in the Tonlé Sap Lake Basin

Tonlé Sap Lake, the largest lake in Southeast Asia, is a critical source of fish and freshwater resources for the region. The health of this freshwater system is under pressure from accelerating dam construction, intensifying agriculture, deforestation, and changing climate patterns, forcing tradeoffs between immediate food security and the long-term vitality and productivity of the ecosystem. Efficient freshwater system monitoring is crucial to navigating these challenges. In collaboration with Conservation International, the Cambodian Ministry of Water Resources and Meteorology, and the Tonlé Sap Authority, we developed and tested remotely-sensed proxies for sub-indicators of the Freshwater Health Index (FHI), which is typically calculated using in situ datasets. We used landcover datasets derived from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), Landsat 8 Operational Land Imager (OLI), PROBA-V Vegetation sensor (VGT), Sentinel-2 Multispectral Imager (MSI), Advanced Very High Resolution Radiometer (AVHRR), and Envisat Medium Resolution Imaging Spectrometer (MERIS) as inputs to calculate land cover naturalness and bank modification. Additionally, we created a lake-level time series using a collection of altimetry data sources to estimate deviation from natural flow. We observed a decrease in landcover naturalness and a breakdown in the volume and regularity of annual lake levels from 2000-2020, reflecting increased pressure on water supply and agricultural productivity. At least 8% of forested areas in the basin were lost and rice harvest intensity increased over the course of the study period. These results will help our partners make informed decisions regarding freshwater management. Furthermore, our remotely-sensed FHI analysis can be replicated in other regions, providing decision makers with a snapshot of freshwater health in data-scarce environments.

Marco Vallejos↗
NASA NTRS2022

Enhancement of a global lake and reservoir database to aid climate studies and resource monitoring utilizing satellite radar altimetry

Here, we describe the expansion and enhancement of a large (surface area ≥100 sq. km) lake and reservoir database (1.GREALD). These efforts have also resulted in the spin-off of two additional databases, one containing lakes and reservoirs (2.GREALD, area 10–99 sq. km), and the other containing ephemeral lakes (3.GELD, area ≥100 sq. km). These databases are unique sources for projects that utilize satellite radar altimeter data to monitor surface water levels. While 1.GREALD aims to be a complete catalog, 2.GREALD focuses on reservoirs in response to applied sciences programs that monitor water and energy resources. The creation of 3.GELD has climate change objectives as well as water resources and ecosystem conservation applications. The recording of information pertaining to the potential overpasses (waterbody crossings) of the current and archive satellite altimeters is a primary objective as is the need to highlight any form of controlled water level variation. The permanent water databases now contain 6282 entries, half experience some form of anthropogenic influence and ∼430 have been identified as potential climatically sensitive terminal lakes. The revised integral surface area distribution is a power law with exponent −1.016. Statistics reveal that with altimetric repeat visit times of 10-day to monthly, at least 80% of the permanent water bodies (≥10 sq. km) have been overflown at some period since the 1990s. Current information on water use and reservoir formation date show that the primary use of the reservoir class is hydroelectric power, and that China, Brazil, India, Turkey, and Vietnam dominate the dam building in recent decades.

Charon M. Birkett↗
DOE OSTI2025

A high-resolution record of Late Holocene drought in the eastern Sierra Nevada (California, USA) from June Lake carbonate geochemistry

As historic drought conditions become more common in western North America, Late Quaternary hydroclimate records become vital for putting present anthropogenic conditions into a longer-term context. Here, we establish a high-resolution record of drought for the eastern Sierra Nevada (California) using lacustrine carbonates from well-dated sediment cores. We used oxygen and carbon stable-isotope ratios, combined with high-resolution scanning X-ray fluorescence counts of calcium (Ca) and titanium (Ti), to reconstruct the drought record over the last 4600 years in June Lake. We found elevated δ 18 O and δ 13 C carbonate isotope values coinciding with peaks in both total inorganic carbon and Ca/Ti, suggesting enhanced carbonate precipitation in response to evaporative concentration of lake water. At least six intervals of prolonged (centennial-scale) carbonate deposition were identified, including three pulses during the Late Holocene Dry Period (LHDP; ~3500–2000 cal yr BP), the Medieval Climate Anomaly (~1200–800 cal yr BP), and the Current Warm Period, which began around 100 cal yr BP. This record highlights the complexities of the LHDP, an interval that was more variable at June Lake than has been previously described in regional records.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Three-dimensional seismic characterization and imaging of the Soda Lake geothermal field

Accurate characterization of subsurface geophysical properties and detection of the fault system are essential for geothermal energy exploration and production. The Soda Lake geothermal field is in western Nevada with a complex fault system. Previous seismic characterization only produced a low-resolution, smooth velocity model along with a simple, conceptual fault model. Using optimized correlation-based full-waveform inversion, wavefield-separation-based reverse-time migration, and automatic fault detection techniques, we present 3D seismic characterization for the Soda Lake geothermal field using 3D surface seismic data acquired with Vibroseis sources. Here, we obtain 3D high-resolution velocity, density, and acoustic impedance models, 3D seismic images with different grid spacings, and a high-resolution fault system. Consistency check between the constructed faults and currently active injection and production geothermal wells verifies that our seismic inversion and imaging results and detected faults are reliable. These results can provide valuable information for optimizing well placement and geothermal energy production at the Soda Lake geothermal field.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Mercury methylation potential in a sand dune on Lake Michigan's eastern shoreline

Lake Michigan hosts the largest freshwater sand dune system in the world and is economically important for the fishery industry and tourism. Due to industrial pollution and atmospheric mercury (Hg) deposition, toxic levels of methylmercury (MeHg) have been found in the Lake biota, but little information is known regarding MeHg sources and Hg methylation potential in the shoreline sand dunes. In this study, we conducted anaerobic incubation experiments with beach sands collected from Ludington, Michigan, and examined the effects of organic carbon substrate addition, inorganic nitrogen, and mineral magnetite on Hg methylation. Despite nutrient poor and low-organic carbon conditions, appreciable Hg methylation activity coupled with carbon degradation was observed in the sands. Addition of acetate as a carbon source substantially increased MeHg production from 2 to 380 ng/kg sediment while acetate was rapidly degraded in the first 19 days of incubation. Ammonium addition showed little influence on carbon degradation or Hg methylation, whereas iron oxide addition (~1% dry weight) significantly inhibited both carbon degradation and MeHg production (by up to 90%), highlighting strongly coupled interactions between microbes, carbon substrates, and minerals. This research demonstrates the potential of microbial Hg methylation in the sand dunes, which may play a role in MeHg input and bioaccumulation in the Lake Michigan ecosystem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Water level changes in Lake Erie drive 21st century CO 2 and CH 4 fluxes from a coastal temperate wetland

Wetland water depth influences microbial and plant communities, which can alter the above- and below-ground carbon cycling of a wetland. Wetland water depths are likely to change due to shifting precipitation patterns, which will affect projections of greenhouse gas emissions; however, these effects are rarely incorporated into wetland greenhouse gas models. Seeking to address this gap, we used a mechanistic model, ecosys, to simulate a range of water depth scenarios in a temperate wetland, and analyzed simulated predictions of carbon dioxide (CO 2 ) andmethane (CH 4 ) fluxes over the 21st century. We tested our model using eddy covariance measurements of CO 2 and CH 4 fluxes collected at the Old Woman Creek National Estuarine Research Reserve (OWC) during 2015 and 2016. OWC is a lacustrine, estuarine, freshwater, mineral-soil marsh. An empirical model found that the wetland water depth is highly dependent on the water depth of the nearby Lake Erie. Future wetland surface water depths were modeled based on projection of Lake Erie's water depth using four separate NOAA projections, resulting in four wetland water-depth scenarios. Two of the four 21st century projections for Lake Erie water depths used in this study indicated that the water depth of the wetland would remain nearly steady; however, the other two indicated decreases in the wetland water depth. In our scenario where the wetland dries out, we project the wetland's climatological warming effect will decrease due to smaller CH 4 fluxes to the atmosphere and larger CO 2 uptake by the wetland. We also found that increased water level can lower emissions by shifting the site towards more open water areas, which have lower CH 4 emissions. We found that decreased water depths would cause more widespread colonization of the wetland by macrophyte vegetation. Using an empirical relationship, we also found that further drying could result in other, non-wetland vegetation to emerge, dramatically altering soil carbon cycling. In three of our four projections, we found that in general the magnitude of CO 2 and CH 4 fluxes steadily increase over the next 100 years in response to higher temperatures. However, in our driest simulations, we projected a different response due to increased oxidation of soil carbon, with CH 4 emissions decreasing substantially from an annual cumulative peak of 224.6 to a minimum of 104.7 gC m –2 year –1 . In that same simulation, net cumulative flux of CO 2 changed from being a sink of 56.5 gC m –2 year –1 to a source of 369.6 gCm –2 year –1 over the same period, despite a temperature increase from 13.7 °C to 14.2 °C. This temperature shift in our other three cases with greater water depths increased the source strength of CH 4 and the sink strength of CO 2 . Here, we conclude that the magnitude of wetland greenhouse-gas fluxes depended on the water depth primarily as it affected the areal percentage of the wetland available for plant colonization, but dramatic decreases in water depths could cause significant reductions in the wetland CH 4 fluxes, while simultaneously altering the wetland vegetation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”

The package contains the data layers used in “Enguehard et al. 2022, Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie”. Spatial data layers include: topography, wetland vegetation cover, time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. The study aims to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Glycerol Is an Osmoprotectant in Two Antarctic Chlamydomonas Species From an Ice-Covered Saline Lake and Is Synthesized by an Unusual Bidomain Enzyme

Glycerol, a compatible solute, has previously been found to act as an osmoprotectant in some marine Chlamydomonas species and several species of Dunaliella from hypersaline ponds. Recently, Chlamydomonas reinhardtii and Dunaliella salina were shown to make glycerol with an unusual bidomain enzyme, which appears to be unique to algae, that contains a phosphoserine phosphatase and glycerol-3-phosphate dehydrogenase. Here we report that two psychrophilic species of Chlamydomonas (C. spp. UWO241 and ICE-MDV) from Lake Bonney, Antarctica also produce high levels of glycerol to survive in the lake’s saline waters. Glycerol concentration increased linearly with salinity and at 1.3 M NaCl, exceeded 400 mM in C. sp. UWO241, the more salt-tolerant strain. We also show that both species expressed several isoforms of the bidomain enzyme. An analysis of one of the isoforms of C. sp. UWO241 showed that it was strongly upregulated by NaCl and is thus the likely source of glycerol. These results reveal another adaptation of the Lake Bonney Chlamydomonas species that allow them to survive in an extreme polar environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Arsenolipids in Cultured Picocystis Strain ML and Their Occurrence in Biota and Sediment from Mono Lake, California

Primary production in Mono Lake, a hypersaline soda lake rich in dissolved inorganic arsenic, is dominated by Picocystis strain ML. We set out to determine if this photoautotrophic picoplankter could metabolize inorganic arsenic and in doing so form unusual arsenolipids (e.g., arsenic bound to 2-O-methyl ribosides) as reported in other saline ecosystems and by halophilic algae. We cultivated Picocystis strain ML on a seawater-based medium with either low (37 µM) or high (1000 µM) phosphate in the presence of arsenite (400 µM), arsenate (800 µM), or without arsenic additions (ca 0.025 µM). Cultivars formed a variety of organoarsenic compounds, including a phytyl 2-O-methyl arsenosugar, depending upon the cultivation conditions and arsenic exposure. When the cells were grown at low P, the organoarsenicals they produced when exposed to both arsenite and arsenate were primarily arsenolipids (~88%) with only a modest content of water-soluble organoarsenic compounds (e.g., arsenosugars). When grown at high P, sequestration shifted to primarily water-soluble, simple methylated arsenicals such as dimethylarsinate; arsenolipids still constituted ~32% of organoarsenic incorporated into cells exposed to arsenate but < 1% when exposed to arsenite. Curiously, Picocystis strain ML grown at low P and exposed to arsenate sequestered huge amounts of arsenic into the cells accounting for 13.3% of the dry biomass; cells grown at low P and arsenite exposure sequestered much lower amounts, equivalent to 0.35% of dry biomass. Extraction of a resistant phase with trifluoroacetate recovered most of the sequestered arsenic in the form of arsenate. Uptake of arsenate into low P-cultivated cells was confirmed by X-ray fluorescence, while XANES/EXAFS spectra indicated the sequestered arsenic was retained as an inorganic iron precipitate, similar to scorodite, rather than as an As-containing macromolecule. Samples from Mono Lake demonstrated the presence of a wide variety of organoarsenic compounds, including arsenosugar phospholipids, most prevalent in zooplankton (Artemia) and phytoplankton samples, with much lower amounts detected in the bottom sediments. These observations suggest a trophic transfer of organoarsenicals from the phytoplankton (Picocystis) to the zooplankton (Artemia) community, with efficient bacterial mineralization of any lysis-released organoarsenicals back to inorganic oxyanions before they sink to the sediments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Machine-Learning Functional Zonation Approach for Characterizing Terrestrial–Aquatic Interfaces: Application to Lake Erie

Ecosystems at coastal terrestrial–aquatic interfaces play a significant role in global biogeochemical cycles. In this study, we aimed to characterize coastal wetlands with particular focus on the co-variability between plant dynamics, topography, soil, and other environmental factors. We proposed a functional zonation approach based on machine learning clustering to identify the spatial regions, i.e., zones that capture these co-varied properties. This approach was applied to publicly available datasets along Lake Erie, in the Great Lakes Region. We investigated the heterogeneity of coastal ecosystem structures as a function of along-shore distance and transverse distance, based on the spatial data layers, including topography, wetland vegetation cover, and the time series of Landsat’s enhanced vegetation index (EVI) between 1990 and 2020. Results showed that the topographic metrics (elevation and slope), soil texture, and plant productivity influence the spatial distribution of wetland land-covers (emergent and phragmites). These results highlight a natural organization along the transverse axis, where the elevation and the EVI increase further away from the coastline. In addition, the clustering analysis allowed us to identify regions with distinct environmental characteristics, as well as the ones that are more sensitive to interannual lake-level variations.

47 OTHER INSTRUMENTATION↗
NASA NTRS2019

New Insights into the Heterogeneity of the Tagish Lake Meteorite: Soluble Organic Compositions of Variously Altered Specimens

The Tagish Lake carbonaceous chondrite exhibits a unique compositional heterogeneity that may be attributed to varying degrees of aqueous alteration within the parent body asteroid. Previous analyses of soluble organic compounds from four Tagish Lake meteorite specimens (TL5b, TL11h, TL11i, TL11v) identified distinct distributions and isotopic compositions that appeared to be linked to their degree of parent body processing (Herd et al. 2011; Glavin et al. 2012; Hilts et al. 2014). In the present study, we build upon these initial observations and evaluate the molecular distribution of amino acids, aldehydes and ketones, monocarboxylic acids, and aliphatic and aromatic hydrocarbons, including compound‐specific δ13C compositions, for three additional Tagish Lake specimens: TL1, TL4, and TL10a. TL1 contains relatively high abundances of soluble organics and appears to be a moderately altered specimen, similar to the previously analyzed TL5b and TL11h lithologies. In contrast, specimens TL4 and TL10a both contain relatively low abundances of all of the soluble organic compound classes measured, similar to TL11i and TL11v. The organic‐depleted composition of TL4 appears to have resulted from a relatively low degree of parent body aqueous alteration. In the case of TL10a, some unusual properties (e.g., the lack of detection of intrinsic monocarboxylic acids and aliphatic and aromatic hydrocarbons) suggest that it has experienced extensive alteration and/or a distinct organic‐depleted alteration history. Collectively, these varying compositions provide valuable new insights into the relationships between asteroidal aqueous alteration and the synthesis and preservation of soluble organic compounds.

Tagish Lake↗
NASA NTRS1993

Evaluation of the TOPEX/Poseidon Altimeter System Over the Great Lakes

The TOPEX/POSEIDON altimeter measurement system is evaluated over the Great Lakes. Using in situ lake level measurements, the temporal variations in lake level are removed from the altimeter measurements, thus permitting the performance of the altimeter system to be assessed.

TOPEX/POSEIDON↗
NASA NTRSDate not supplied

Observing Supraglacial Lakes Using Deep Learning and PlanetScope Imagery

Supraglacial lakes (SGL)s result from melt water accumulation in topographic depressions on the surface of glaciers. SGLs primarily affect glacial dynamics through a positive feedback loop in which the albedo-lowering effect of SGLs can escalate surface melt leading to increases in lake extent and depth, amplifying the afore mentioned albedo-lowering effect. The implications of accelerated glacial melt include increased sea level rise and modifications to ocean primary productivity. SGLs are critical indicators of surface melt and its downstream impacts and should be monitored efficiently. In situ observations and measurements of SGLs are time consuming, cost-prohibitive and difficult to scale. Earth observation data and machine learning enable scalable monitoring of SGLs through pattern detection and quantification of lake evolution over time [1]. This work presents a model developed by training a convolutional neural network with imagery and labels from NASA Operation IceBridge and predicting SGLs in high temporal and spatial resolution PlanetScope imagery.

Supraglacial lake↗
DOE OSTI2020

2D Dam-Break Analysis of L Lake and PAR Pond Dams Using HEC-RAS

In 1991 a dam-break study was conducted for the high hazard dams located at L Lake and PAR Pond on the Savannah River Site. Two scenarios were considered, over topping from a Probable Maximum Flood (PMF), and a fair weather dam-break for either or both dams. Unfortunately, no inundation map was developed from the study. The purpose of this project was to redo the original dam-break study with improved data and methodology to generate Inundation maps to assist with emergency response and evacuation plans. The Hydrologic Engineering Center's River Analysis System (HEC-RAS) is a free to download river analysis modeling program developed by the US Army Corps of Engineers capable of 1D and 2D hydraulic calculations. Version 5.0.7 (released March 2019) was used for this project. Digital elevation models for the area were retrieved from the US Geological Survey database and converted to a .hdf file within the program. Then the 2D flood area was identified from the contours. Both L Lake and PAR Pond were inputted as 1D storage areas because DEM data does not contain elevation values under water bodies. An elevation vs volume curve was available for both storage areas. Initial elevations were set for both scenarios. Both dams are earthen dams. The Steel Creek dam at L Lake has 6 ft diameter conduit with an upper and lower sluice gate. PAR pond dam consist of a weir and sluice gate connected to an 8 x 8 ft channel. Both outlets were modeled with a pool elevation vs discharge curve. The steel creek dam sluice gates were assumed to be fully open in all cases. As in the previous study, the dams were set to breach when they were overtopped by 1.5 ft during PMF conditions (Figure 1). A fair weather breach was set to be due to a piping failure (Figure 1). In the dual dam break during fair weather conditions the PAR pond dam fails 3 hours after Steel Creek to achieve maximum flooding in the down stream reaches. Simulation was run 3 days for each case and with a 1 minute computational interval. Maximum flooding occurs under PMF conditions with the failure of both dams. PAR pond dam fails first 16 hours and 32 minutes after the start of the simulation with the Steel creek dam failing 6 minutes later. In all cases, the bridges and roads spanning Steel Creek and Lower Three Runs will be inundated and potentially washed away. The Burtons Ferry Highway south of the storage areas will be partially flooded during PMF failure, dual fair weather failure, and PAR pond failure under fair weather conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Estimation of pollen productivity and dispersal: How pollen assemblages in small lakes represent vegetation

Abstract Quantitative understanding of vegetation dynamics over timespans beyond a century remains limited. In this regard, the pollen‐based reconstruction of past vegetation enables unique research opportunities by quantifying changes in plant community compositions during hundreds to thousands of years. Critically, the methodological basis for most reconstruction approaches rests upon estimates of pollen productivity and dispersal. Previous studies, however, have reached contrasting conclusions concerning these estimates, which may be perceived to challenge the applicability and reliability of pollen‐based reconstruction. Here we show that conflicting estimates of pollen production and dispersal are, at least in part, artifacts of fixed assumptions of pollen dispersal and insufficient spatial resolution of vegetation data surrounding the pollen‐collecting lake. We implemented a Bayesian statistical model that related pollen assemblages in surface sediments of 33 small lakes (<2 ha) in the northeastern United States, with surrounding vegetation ranging from 10 1 to >10 5 m from the lake margin. Our analysis revealed three key insights. First, pollen productivity is largely conserved within taxa and across forest types. Second, when local (within a 1‐km radius) vegetation abundances are not considered, pollen‐source areas may be overestimated for some common taxa (Cupressaceae, Pinus , Quercus , and Tsuga ). Third, pollen dispersal mechanisms may differ between local and regional scales; this is missed by pollen‐dispersal models used in previous studies. These findings highlight the complex interactions between vegetation heterogeneity on the landscape and pollen dispersal. We suggest that, when estimating pollen productivity and dispersal, both detailed local and extended regional vegetation must be taken into account. Also, both deductive (mechanistic models) and inductive (statistical models) approaches are needed to better understand the emergent properties of pollen dispersal in heterogeneous landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Physical drivers facilitating a toxigenic cyanobacterial bloom in a major Great Lakes tributary

The Maumee River is the primary source for nutrients fueling seasonal Microcystis -dominated blooms in western Lake Erie's open waters though such blooms in the river are infrequent. The river also serves as source water for multiple public water systems and a large food services facility in northwest Ohio. On 20 September 2017, an unprecedented bloom was reported in the Maumee River estuary within the Toledo metropolitan area, which triggered a recreational water advisory. Here we (1) explore physical drivers likely contributing to the bloom's occurrence, and (2) describe the toxin concentration and bacterioplankton taxonomic composition. A historical analysis using 10-years of seasonal river discharge, water level, and local wind data identified two instances when high-retention conditions occurred over ≥ 10 d in the Maumee River estuary: in 2016 and during the 2017 bloom. Observation by remote sensing imagery supported the advection of cyanobacterial cells into the estuary from the lake during 2017 and the lack of an estuary bloom in 2016 due to a weak cyanobacterial bloom in the lake. A rapid-response survey during the 2017 bloom determined levels of the cyanotoxins, specifically microcystins, in excess of recreational contact limits at sites within the lower 20 km of the river while amplicon sequencing found these sites were dominated by Microcystis . These results highlight the need to broaden our understanding of physical drivers of cyanobacterial blooms within the interface between riverine and lacustrine systems, particularly as such blooms are expected to become more prominent in response to a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Organic sulfur from source to sink in low‐sulfate Lake Superior

Abstract Organic sulfur plays a crucial role in the biogeochemistry of aquatic sediments, especially in low sulfate (< 500 μ M) environments like freshwater lakes and the Earth's early oceans. To better understand organic sulfur cycling in these systems, we followed organic sulfur in the sulfate‐poor (< 40 μ M) iron‐rich (30–80 μ M) sediments of Lake Superior from source to sink. We identified microbial populations with shotgun metagenomic sequencing and characterized geochemical species in porewater and solid phases. In anoxic sediments, we found an active sulfur cycle fueled primarily by oxidized organic sulfur. Sediment incubations indicated a microbial capacity to hydrolyze sulfonates, sulfate esters, and sulfonic acids to sulfate. Gene abundances for dissimilatory sulfate reduction ( dsrAB ) increased with depth and coincided with sulfide maxima. Despite these indicators of sulfide formation, sulfide concentrations remain low (< 40 nM) due to both pyritization and organic matter sulfurization. Immediately below the oxycline, pyrite accounted for 13% of total sedimentary sulfur. Both free and intact lipids in this same interval accumulated disulfides, indicating rapid sulfurization even at low concentrations of sulfide. Our investigation revealed a new model of sulfur cycling in a low‐sulfate environment that likely extends to other modern lakes and possibly the ancient ocean, with organic sulfur both fueling sulfate reduction and consuming the resultant sulfide.

Phillips, Alexandra A.↗
DOE OSTI2024

In situ aerobic methane oxidation rates in a stratified lake

Abstract Microbial aerobic methane oxidation is an important sink for aquatic methane worldwide. Despite its importance to global methane fluxes, few aerobic methane oxidation rates have been obtained in freshwater or marine environments without imposing changes to the microbial community through use of ex situ methods. A novel in situ incubation method for continuous time‐series measurements was used in Jordan Lake, North Carolina, during 2020–2021, to determine reaction kinetics for aerobic methane oxidation rates across a wide range of naturally varying methane (55–1833 nM) and dissolved oxygen (DO; 28–366 μM) concentrations and temperatures (17–30°C). Methane oxidation began immediately at the start of each of 21 incubations and methane oxidation rates were 1 st order with respect to methane. The data density allowed for accurate calculation of 1 st ‐order rate constants,k, that ranged from 0.018 to 0.462 h −1 (R 2 > 0.967). Addition of ammonium (20–45 μM) to natural concentrations ranging from 0.057 to 2.4 μM did not change aerobic methane oxidation rate kinetics, suggesting that the natural population of aerobic methane oxidizers in this eutrophic lake was not nitrogen limited. Values ofkinversely correlated most strongly with initial DO concentrations (R 2 = 0.82) rather than temperature. Values forkincreased with Julian day throughout our sampling period, suggesting seasonal influences on methane oxidation via responses to geochemical changes or shifts in microbial community abundance and composition. These experiments demonstrate a high variability in the enzymatic capacity for 1 st ‐order methane oxidation rates in this eutrophic lake that is tightly and inversely coupled to oxygen concentrations. Measurements of in situ aerobic methane oxidation rate constants allow for the direct quantification and modeling of the microbial community's capacity for methane oxidation over a wide range of natural methane concentrations.

Marine & Freshwater Biology↗