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DOE OSTI2023

Quantitative, trait-based microbial ecology to accurately model the impacts of nitrogen deposition on soil carbon cycling in the Anthropocene (Final Technical Report)

Atmospheric nitrogen pollution has altered fundamental soil processes, challenging our understanding of the extent to which soils will continue to sequester carbon and slow the pace of future environmental change. While most evidence shows that increases in soil nitrogen have enhanced carbon storage in temperate forests, it remains unclear whether these effects will persist as nitrogen pollution continues to decline. Moreover, there remains uncertainty as to why some forests gain more carbon in response to nitrogen pollution than others. At the heart of this knowledge gap is a failure to link nitrogen–induced shifts in microbial biodiversity with gains or losses in their functional ability to decompose, assimilate, and ultimately stabilize soil carbon. Given that this uncertainty impedes the ability of predictive models to project future soil carbon stocks, there is a critical need to determine how key microbial traits drive soil carbon responses to nitrogen pollution. As such the goals of this project were to: (1) Quantify variation in taxon–specific and community–level microbial traits across gradients in microbial community composition, mycorrhizal symbioses, and nitrogen availability. (2) Integrate empirical data into a novel predictive framework that enhances our ability to project the regional soil carbon consequences of historical nitrogen pollution in temperate forests.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Carbon cycle confidence and uncertainty: Exploring variation among soil biogeochemical models

Emerging insights into factors responsible for soil organic matter stabilization and decomposition are being applied in a variety of contexts, but new tools are needed to facilitate the understanding, evaluation, and improvement of soil biogeochemical theory and models at regional to global scales. To isolate the effects of model structural uncertainty on the global distribution of soil carbon stocks and turnover times we developed a soil biogeochemical testbed that forces three different soil models with consistent climate and plant productivity inputs. The models tested here include a first-order, microbial implicit approach (CASA-CNP), and two recently developed microbially explicit models that can be run at global scales (MIMICS and CORPSE). When forced with common environmental drivers, the soil models generated similar estimates of initial soil carbon stocks (roughly 1,400 Pg C globally, 0–100 cm), but each model shows a different functional relationship between mean annual temperature and inferred turnover times. Subsequently, the models made divergent projections about the fate of these soil carbon stocks over the 20th century, with models either gaining or losing over 20 Pg C globally between 1901 and 2010. Single-forcing experiments with changed inputs, temperature, and moisture suggest that uncertainty associated with freeze-thaw processes as well as soil textural effects on soil carbon stabilization were larger than direct temperature uncertainties among models. Finally, the models generated distinct projections about the timing and magnitude of seasonal heterotrophic respiration rates, again reflecting structural uncertainties that were related to environmental sensitivities and assumptions about physicochemical stabilization of soil organic matter. Here, by providing a computationally tractable and numerically consistent framework to evaluate models we aim to better understand uncertainties among models and generate insights about factors regulating the turnover of soil organic matter.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Higher levels of mixed-linkage (1,3;1,4)-β-glucan in transgenic grasses may impact soil C processing

Carbohydrates, including mixed-linkage glucan (MLG), in grass cell walls make them a valuable potential feedstock for biofuel production. Hence, the development of transgenic grasses with elevated levels of MLG is being actively pursued worldwide. Changes in chemical and physical root characteristics of MLG-overproducing transgenic plants can affect processing of the root-derived carbon (C) by soil microorganisms, impacting soil C cycling. Here, this study is the first attempt to elucidate the impact of MLG-related genetic modifications on root traits, root decomposition, and soil C processing. We explored four genotypes of Brachypodium ( Brachypodium distachyon ): a wildtype, a loss-of-function mutant with low MLG, an MLG overexpressing line, and a line lacking MLG hydrolase (with high MLG), incubating their roots in soils of two contrasting vegetation histories: monoculture switchgrass and polyculture restored prairie. The four genotypes exhibited contrasting root MLG and soluble sugar concentrations, and different growth phenotypes. Roots with the highest MLG content resulted in a ∼55 % increase in microbial biomass C compared to wildtype in both soils. However, the genotype effects on C mineralization rates were influenced by the vegetation history, with significant effects observed only in the soil from switchgrass but not prairie origin. While further work is required to understand the full impact of MLG-overproducing plants on soil C accrual, our findings suggest that their influence on soil C processes cannot be discounted.

Brachypodium distachyon↗

DOE OSTI2012

Nanoparticles Formed from Bacterial Oxyanion Reduction of Toxic Group 15 and Group 16 Metalloids

Environmental Significance of Group 15 and 16 Toxic Metalloids Selenium, tellurium, and arsenic are present naturally in aquatic and terrestrial environments and share many similar biogeochemical characteristics. These elements are released into the environment through the weathering and decomposition of minerals contained within a variety of lithologies, with slow release rates resulting in low environmental concentrations. Selenium, tellurium, and arsenic occur in several oxidation states as oxyanions (e.g., selenate [SeO4 2], selenite [SeO3 2], tellurate [TeO4 2], tellurite [TeO3 2], arsenate [HAsO4 2], and arsenite [HAsO3 2]) in their native elemental states [e.g., Se(0), Te(0)] or in their most reduced states as selenide (-II) and telluride (-II) or arsenide/arsines (-III). These elements can be methylated through microbial activity to form compounds such as dimethylselenide (Ehrlich, 2002; Masscheleyn, et al., 1990), dimethyltelluride (Basnayake, et al., 2001; Fleming and Alexander, 1972), and methylarsonous acid (Dopp, et al., 2004) as well as a variety of toxic methylated arsine gases (Yuan, et al., 2008). These elements are also found as analogues of sulfurous proteins such as selenocysteine and selenomethionine (Bock, et al., 1991; Jones, et al., 1979; Stolz, et al., 2006; Zannoni, et al., 2008), tellurocysteine, telluromethionine (Zannoni, et al., 2008), and the arsenic-containing amino acid, arsenomethionine (Dembitsky and Levitsky, 2004).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Anthropogenic N Deposition Slows Decay by Favoring Bacterial Metabolism: Insights from Metagenomic Analyses

Litter decomposition is an enzymatically-complex process that is mediated by a diverse assemblage of saprophytic microorganisms. It is a globally important biogeochemical process that can be suppressed by anthropogenic N deposition. In a northern hardwood forest ecosystem located in Michigan, USA, 20 years of experimentally increased atmospheric N deposition has reduced forest floor decay and increased soil C storage. Here, we paired extracellular enzyme assays with shotgun metagenomics to assess if anthropogenic N deposition has altered the functional potential of microbial communities inhabiting decaying forest floor. Experimental N deposition significantly reduced the activity of extracellular enzymes mediating plant cell wall decay, which occurred concurrently with changes in the relative abundance of metagenomic functional gene pathways mediating the metabolism of carbohydrates, aromatic compounds, as well as microbial respiration. Moreover, experimental N deposition increased the relative abundance of 50 of the 60 gene pathways, the majority of which were associated with saprotrophic bacteria. Conversely, the relative abundance and composition of fungal genes mediating the metabolism of plant litter was not affected by experimental N deposition. Future rates of atmospheric N deposition have favored saprotrophic soil bacteria, whereas the metabolic potential of saprotrophic fungi appears resilient to this agent of environmental change. Results presented here provide evidence that changes in the functional capacity of saprotrophic soil microorganisms mediate how anthropogenic N deposition increases C storage in soil.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Photodegradation accelerates ecosystem N cycling in a simulated California grassland

Abstract Photodegradation accelerates litter decay in arid grasslands where plant growth and litter decay are strongly controlled by precipitation and evapotranspiration. However, the effects of photodegradation on ecosystem C and N dynamics are not well understood. We examined the effects using an ecosystem biogeochemical model DayCent‐ UV with photodegradation explicitly represented and validated. The model was parameterized for a California grassland where photodegradation was documented to release CO 2 from litter. The model was parameterized with an inverse modeling approach using an extensive data set of six years of daily observed carbon and water gas exchange (gross primary production, ecosystem respiration, and evapotranspiration), soil temperature, and soil moisture. DayCent‐ UV correctly simulated the seasonal patterns of the observed gas exchange and closely simulated the inter‐annual variation in the gas exchange and biomass production rates. The simulations suggested that the inter‐annual variation is driven more by actual evapotranspiration than by precipitation because a large portion of precipitation is lost as runoff during wet years. Photodegradation in DayCent‐ UV accelerated C and N cycling, decreasing system C and N by 9.2% and 9.5% and C and N residence times by 9.4% and 18.2%. Accelerated N cycling made a greater fraction of system N available for plants, increasing net N mineralization and plant production for a given amount of system N. Increased net N mineralization was due to decreased immobilization by microbes in the aboveground organic matter. Photodegradation did not alter the control on plant production by evapotranspiration. These results suggest that at the ecosystem level, the central effect of photodegradation is to suppress microbial activity. We conclude that photodegradation accelerates N cycling at the expense of microbes in this grassland, making it more efficient in supporting plant growth for a given amount of N in the system.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Root exudates induced coupled carbon and phosphorus cycling in a soil with low phosphorus availability

The amount and type of root exudates can influence P availability in the rhizosphere directly by desorption or dissolution of soil minerals, or indirectly by decomposition of soil organic matter (SOM). Here this study aimed to determine the mechanisms by which specific root exudates influence the distribution and availability of P in soils with low P availability. Water, glucose, alanine, and oxalate were delivered through a simulated root into soils for 15 days. Zymography and planar optodes were used to image potential phosphatase activity, and O2 and pH distribution, respectively. Soils were analyzed for resin extractable inorganic P (Pi), dissolved organic C (DOC), water soluble Fe, and Al, and microbial community structure. Characterization of SOM and P were conducted using ultra-high resolution mass spectrometry and 31P solution nuclear magnetic resonance (NMR), respectively. The addition of oxalate resulted in the greatest resin extractable Pi, DOC, and water-soluble Fe, and Al compared to the other exudates suggesting destabilization of mineral associated organic matter (MAOM) and release of organic P (Po). Both 31P solution NMR and ultra-high resolution mass spectrometry analysis provided evidence of mineralization of Po released from the destabilization of MAOM. The study demonstrates the important role microbial and plant-derived metal chelating ligands play in destabilizing MAOM, releasing SOM and importantly Po, that when mineralized may contribute to increasing Pi availability in soils with low P availability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Biogeochemistry simulations for the Salt Marsh Accretion Response to Temperature eXperiment (SMARTX)

Coastal ecosystems have been largely ignored in Earth system models but are important zones for carbon and nutrient processing. Interactions between water, microbes, soil, sediments, and vegetation are important for mechanistic representation of coastal processes and ecosystem function. To investigate the role of these feedbacks, we used a reactive transport model (PFLOTRAN) that has the capability to be connected to the Energy Exascale Earth System Model (E3SM). PFLOTRAN was used to incorporate redox reactions and track chemical species important for coastal ecosystems as well as define simple representations of vegetation dynamics. Our goal was to incorporate oxygen flux, salinity, pH, sulfur cycling, and methane production along with plant-mediated transport of gases and tidal flux. Using porewater profile and incubation data for model calibration and evaluation, we were able to create depth-resolved biogeochemical soil profiles for saltmarsh habitat and use this updated representation to simulate direct and indirect effects of elevated CO2 and temperature on subsurface biogeochemical cycling. We found that simply changing the partial pressure of CO2 or increasing temperature in the model did not fully reproduce observed changes in the porewater profile, but the inclusion of plant or microbial responses to CO2 and temperature manipulations was more accurate in representing porewater concentrations. This indicates the importance of characterizing tightly coupled vegetation-subsurface processes for developing predictive understanding and the need for measurement of plant-soil interactions on the same time scale to understand how hotspots or moments are generated.Included in this data package are PFLOTRAN input (PFLOTRAN input files and chemical database) files for simulating single column biogeochemistry, root, and tide interactions at the Global Change Research Wetland (Kirkpatrick Marsh; Edgewater, MD). The biogeochemical network includes soil organic matter decomposition, nitrogen, iron, and sulfur cycling, and methanogenesis. Reduced species can be oxidized and plant processes include oxygen and nutrient priming, methane release, and nutrient uptake.Inputs:TAI_database.dat - geochemical database for reactions, more information on database structure and variables can be found here https://www.pflotran.org/documentation/user_guide/cards/pages/geochemical_database.htmlswamp.in - input file for biogeochemical network in PFLOTRANswamp_eCO2.in - input file for biogeochemical network in PFLOTRAN with input gas partial pressures/concentrations adjusted for elevated CO2 treatmentsOutputs:swamp_obs_0.tec - hourly porewater concentrations from from multiple depths in the soil columnswamp_eCO2_obs_0.tec - hourly porewater concentrations from multiple depths in the soil column for elevated CO2 treatmentsPFLOTRAN code access: https://github.com/fmyuan/pflotran-elm-interface.git

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Interactive Effects of Climate Change and Decomposer Communities on the Stabilization of Wood-Derived Carbon Pools: Catalyst for a New Study

Globally, forest soils store ~two-thirds as much carbon (C) as the atmosphere. Although wood makes up the majority of forest biomass, the importance of wood contributions to soil C pools is unknown. Even with recent advances in the mechanistic understanding of soil processes, integrative studies tracing C input pathways and biological fluxes within and from soils are lacking. Therefore, our research objectives were to assess the impact of different fungal decay pathways (i.e., white-rot versus brown-rot)—in interaction with wood quality, soil temperature, wood location (i.e., soil surface and buried in mineral soil), and soil texture—on the transformation of woody material into soil CO 2 efflux, dissolved organic carbon (DOC), and soil C pools. The use of 13 C-depleted woody biomass harvested from the Rhinelander, WI free-air carbon dioxide enrichment (Aspen-FACE) experiment affords the unique opportunity to distinguish the wood-derived C from other soil C fluxes and pools. We established 168 treatment plots across six field sites (three sand and three loam textured soil). Treatment plots consisted of full-factorial design with the following treatments: 1. Wood chips from elevated CO 2 , elevated CO 2 + O 3 , or ambient atmosphere AspenFACE treatments; 2. Inoculated with white rot (Bjerkandera adusta) or brown rot (Gloeophyllum sepiarium) pure fungal cultures, or the original suite of endemic microbial community on the logs; and 3. Buried (15cm in soil as a proxy for coarse roots) or surface applied wood chips. We also created a warming treatment using open-topped, passive warming chambers on a subset of the above treatments. Control plots with no added wood (“no chip control”) were incorporated into the research design. Soils were sampled for initial δ 13 C values, CN concentrations, and bulk density. A subset of plots were instrumented with lysimeters for sampling soil water and temperature data loggers for measuring soil temperatures. To determine the early pathways of decomposition, we measured soil surface CO 2 efflux, dissolved organic C (DOC), and DO 13 C approximately monthly over two growing seasons from a subsample of the research plots. To determine the portion of soil surface CO 2 efflux attributable to wood-derived C, we used Keeling plot techniques to estimate the associated δ 13 C values of the soil CO 2 efflux. We measured the δ 13 CO 2 once during the peak of each growing season. Initial values for soil δ 13 C values and CN concentrations averaged across the six sites were -26.8‰ (standard error = 0.04), 2.46% (se = 0.11), and 0.15% (se = 0.01), respectively. The labeled wood chips from the Aspen FACE treatments had an average δ13C value of -39.5‰ (se 0.10). The >12 ‰ isotopic difference between the soil and wood chip δ 13 C values provides the basis for tracking the wood-derived C through the early stages of decomposition and subsequent storage in the soil. Across our six research sites, average soil surface CO 2 efflux ranged from 1.04 to 2.00 g CO 2 m -2 h -1 for the first two growing seasons. No wood chip controls had an average soil surface CO 2 efflux of 0.67 g CO 2 m -2 h -1 or about half of that of the wood chip treatment plots. Wood-derived CO 2 efflux was higher for loam textured soils relative to sands (0.70 and 0.54 g CO 2 m -2 h -1 , respectively; p = 0.045)), for surface relative to buried wood chip treatments (0.92 and 0.39 g CO 2 m -2 h -1 , respectively; p < 0.001), for warmed relative to ambient temperature treatments (0.99 and 0.78 g CO 2 m -2 h -1 , respectively; 0.004), and for natural rot relative to brown and white rots (0.93, 0.82, and 0.78 g CO 2 m -2 h -1 , respectively; p = 0.068). Our first two growing seasons of soil surface CO 2 efflux data show that wood chip location (i.e., surface vs. buried chip application) is very important, with surface chips loosing twice the wood-derived CO 2 . The DOC data support this trend for greater loss of ecosystem C from surface chips. This has strong implications for the importance of root and buried wood for ecosystem C retention. This strong chip location effect on wood-derived C loss was significantly modified by soil texture, soil temperature, decomposer communities, and wood quality as effected by potential future CO 2 and O 3 levels.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

GOTTCHA, Version2

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions. In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure. During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably. During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.

Freitas, Tracey↗

DOE OSTI2015

GOTTCHA Database, Version 1

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.

Freitas, Tracey↗

DOE OSTI2015

GOTTCHA, Version 1

Freitas, Tracey↗

DOE OSTI2015

GOTTCHA Database, Version 1

One major challenge in the field of shotgun metagenomics is the accurate identification of the organisms present within the community, based on classification of short sequence reads. Though microbial community profiling methods have emerged to attempt to rapidly classify the millions of reads output from contemporary sequencers, the combination of incomplete databases, similarity among otherwise divergent genomes, and the large volumes of sequencing data required for metagenome sequencing has led to unacceptably high false discovery rates (FDR). Here we present the application of a novel, gene-independent and signature-based metagenomic taxonomic profiling tool with significantly smaller FDR, which is also capable of classifying never-before seen genomes into the appropriate parent taxa.The algorithm is based upon three primary computational phases: (I) genomic decomposition into bit vectors, (II) bit vector intersections to identify shared regions, and (III) bit vector subtractions to remove shared regions and reveal unique, signature regions.In the Decomposition phase, genomic data is first masked to highlight only the valid (non-ambiguous) regions and then decomposed into overlapping 24-mers. The k-mers are sorted along with their start positions, de-replicated, and then prefixed, to minimize data duplication. The prefixes are indexed and an identical data structure is created for the start positions to mimic that of the k-mer data structure.During the Intersection phase -- which is the most computationally intensive phase -- as an all-vs-all comparison is made, the number of comparisons is first reduced by four methods: (a) Prefix restriction, (b) Overlap detection, (c) Overlap restriction, and (d) Result recording. In Prefix restriction, only k-mers of the same prefix are compared. Within that group, potential overlap of k-mer suffixes that would result in a non-empty set intersection are screened for. If such an overlap exists, the region which intersects is first reduced by performing a binary search of the boundary suffixes of the smaller set into the larger set, which defines the limits of the zipper-based intersection process. Rather than recording the actual k-mers of the intersection, another data structure of identical "shape" is created which consists of only bit vectors so that only a 1 or 0 will be stored in the location of the k-mer suffix that was found in the intersection. This reduces the amount of data generated and stored considerably.During the Subtraction phase, relevant intersection bitmasks are first unionized together to form a single bitmask which is then applied over the original genome to reveal only those regions of the genome that are unique. These regions are then exported to disk in FASTA format and used in the application of determining the constituents of an unknown metagenomic community.The DATABASE provided is the result of the algorithm described.

Freitas, Tracey↗

DOE OSTI2024

Environmental matrix and moisture are key determinants of microbial phenotypes expressed in a reduced complexity soil-analog

Soil moisture and porosity regulate microbial metabolism by influencing factors such as redox conditions, substrate availability, and soil connectivity. However, the inherent biological, chemical, and physical heterogeneity of soil complicates laboratory investigations into microbial phenotypes that mediate community metabolism. This difficulty arises from challenges in accurately representing the soil environment and in establishing a tractable microbial community that limits confounding variables. To address these challenges in our investigation of community metabolism, we use a reduced-complexity microbial consortium grown in a soil analog using a glass-bead matrix amended with chitin. Long-read and short-read metagenomes, metatranscriptomes, metaproteomes, and metabolomes were analyzed to test the effects of soil structure and moisture on chitin degradation. Our soil structure analog system greatly altered microbial expression profiles compared to the liquid-only incubations, emphasizing the importance of incorporating environmental parameters, like pores and surfaces, for understanding microbial phenotypes relevant to soil ecosystems. These changes were mainly driven by differences in overall expression of chitin-degrading Streptomyces species and stress-tolerant Ensifer. Our findings suggest that the success of Ensifer in a structured environment is likely related to its ability to repurpose carbon via the glyoxylate shunt while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits like motility, stress resistance, and biofilm formation that underlie the degradation of chitin across our treatments and inform how they may ultimately alter carbon use efficiency. Together our results demonstrate that community functions like decomposition are sensitive to environmental conditions and more complex than the multi-enzyme pathways involved in depolymerization.

Rodriguez-Ramos, Josue A↗

NASA NTRS1994

Methane production and consumption in grassland and boreal ecosystems

The objectives of the this project were to develop a mechanistic understanding of methane production and oxidation suitable for incorporation into spatially explicit models for spatial extrapolation. Field studies were undertaken in Minnesota, Canada, and Colorado to explore the process controls over the two microbial mediated methane transformations in a range of environments. Field measurements were done in conjunction with ongoing studies in Canada (the Canadian Northern Wetlands Projects: NOWES) and in Colorado (The Shortgrass Steppe Long Term Ecological Research Project: LTER). One of the central hypotheses of the proposal was that methane production should be substrate limited, as well as being controlled by physical variables influencing microbial activity (temperature, oxidation status, and pH). Laboratory studies of peats from Canada and Minnesota (Northern and Southern Boreal) were conducted with amendments of a methanogenic substrate at multiple temperatures and at multiple pHs (the latter by titrating samples). The studies showed control by substrate, pH, and temperature in order in anaerobic samples. Field and laboratory manipulations of natural plant litter, rather than an acetogenic substrate, showed similarly large effects. The studies concluded that substrate is an important control over methanogenesis, that substrate availability in the field is closely coupled to the chemistry of the dominant vegetation influencing its decomposition rate, that most methane is produced from recent plant litter, and that landscape changes in pH are an important control, highly correlated with vegetation.

Schimel, David S.↗

DOE OSTI2018

Geothermally warmed soils reveal persistent increases in the respiratory costs of soil microbes contributing to substantial C losses

Increasing temperatures can accelerate soil organic matter decomposition and release large amounts of CO 2 to the atmosphere, potentially inducing positive warming feedbacks. Alterations to the temperature sensitivity and physiological functioning of soil microorganisms may play a key role in these carbon (C) losses. Geothermally active areas in Iceland provide stable and continuous soil temperature gradients to test this hypothesis, encompassing the full range of warming scenarios projected by the Intergovernmental Panel on Climate Change for the northern region. We took soils from these geothermal sites 7 years after the onset of warming and incubated them at varying temperatures and substrate availability conditions to detect persistent alterations of microbial physiology to long-term warming. Seven years of continuous warming ranging from 1.8 to 15.9 °C triggered a 8.6–58.0% decrease on the C concentrations in the topsoil (0–10 cm) of these sub-arctic silt-loam Andosols. The sensitivity of microbial respiration to temperature (Q 10 ) was not altered. However, soil microbes showed a persistent increase in their microbial metabolic quotients (microbial respiration per unit of microbial biomass) and a subsequent diminished C retention in biomass. After an initial depletion of labile soil C upon soil warming, increasing energy costs of metabolic maintenance and resource acquisition led to a weaker capacity of C stabilization in the microbial biomass of warmer soils. This mechanism contributes to our understanding of the acclimated response of soil respiration to in situ soil warming at the ecosystem level, despite a lack of acclimation at the physiological level. Furthermore, persistent increases in the respiratory costs of soil microbes in response to warming constitute a fundamental process that should be incorporated into climate change-C cycling models.

58 GEOSCIENCES↗

DOE OSTI2019

Agricultural Management Affects Root-Associated Microbiome Recruitment Over Maize Development

Diversified cropping systems provide yield benefits that may result from enhanced nutrient availability via the root microbiome. We hypothesized that root-associated microbial communities in diversified and conventional systems would differ most during high plant nitrogen demand, reflecting microbiome-derived benefits, and that these effects would be greatest nearest the root. We compared maize bulk soil, rhizosphere, and rhizoplane prokaryotic and fungal communities in two systems at four plant developmental stages using amplicon sequencing. The greatest differences between systems in root-selected prokaryotic community composition occurred within the rhizoplane during vegetative stage 11 (high nitrogen demand). During this period, the rhizoplane of maize from the diversified, compared to the conventional, cropping system hosted higher abundances of bacteria implicated in complex organic matter decomposition ( Verrucomicrobia and Acidobacteria ). In contrast, fungal root-associated communities differed most between cropping systems during vegetative stage 4 (low nitrogen demand) and became more similar over time. Unexpectedly, prokaryotic rhizosphere communities, unlike rhizoplane communities, did not always differentiate from bulk soil communities, indicating value in differentiating between root compartments to understand root-microbiome-management interactions. For example, the diversified system rhizosphere and bulk soil prokaryotic communities were not well differentiated compared to in the conventional system, indicating the possibility of a camouflage effect.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2014

Detection of Nitric Oxide by the Sample Analysis at Mars (SAM) Instrument Implications for the Presence of Nitrates

One of the main goals of the Mars Science Laboratory is to determine whether the planet ever had environmental conditions able to support microbial life. Nitrogen is a fundamental element for life, and is present in structural (e.g., proteins), catalytic (e.g., enzymes and ribozymes), energy transfer (e.g., ATP) and information storage (RNA and DNA) biomolecules. Planetary models suggest that molecular nitrogen was abundant in the early Martian atmosphere, but was rapidly lost to space by photochemistry, sputtering impact erosion, and oxidized and deposited to the surface as nitrate. Nitrates are a fundamental source for nitrogen to terrestrial microorganisms. Therefore, the detection of nitrates in soils and rocks is important to assess the habitability of a Martian environment. SAM is capable of detecting nitrates by their thermal decomposition into nitric oxide, NO. Here we analyze the release of NO from soils and rocks examined by the SAM instrument at Gale crater, and discuss its origin.

Navarro-Gonzalez, R.↗