Search NASA⌕ Search

SEARCH · Search NASA

Results for “carbon cycle”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Amazon rainforest photosynthesis increases in response to atmospheric dryness

Earth system models predict that increases in atmospheric and soil dryness will reduce photosynthesis in the Amazon rainforest, with large implications for the global carbon cycle. Using in situ observations, solar-induced fluorescence, and nonlinear machine learning techniques, we show that, in reality, this is not necessarily the case: In many of the wettest parts of this region, photosynthesis and biomass tend to increase with increased atmospheric dryness, despite the associated reductions in canopy conductance to CO 2 . These results can be largely explained by changes in canopy properties, specifically, new leaves flushed during the dry season have higher photosynthetic capacity than the leaves they replace, compensating for the negative stomatal response to increased dryness. As atmospheric dryness will increase with climate change, our study highlights the importance of reframing how we represent the response of ecosystem photosynthesis to atmospheric dryness in very wet regions, to accurately quantify the land carbon sink.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Incorporating the Acclimation of Photosynthesis and Leaf Respiration in the Noah‐MP Land Surface Model: Model Development and Evaluation

Abstract Realistic simulation of leaf photosynthetic and respiratory processes is needed for accurate prediction of the global carbon cycle. These two processes systematically acclimate to long‐term environmental changes by adjusting photosynthetic and respiratory traits (e.g., the maximum photosynthetic capacity at 25°C ( V cmax,25 ) and the leaf respiration rate at 25°C ( R 25 )) following increasingly well‐understood principles. While some land surface models (LSMs) now account for thermal acclimation, they do so by assigning empirical parameterizations for individual plant functional types (PFTs). Here, we have implemented an Eco‐Evolutionary Optimality (EEO)‐based scheme to represent the universal acclimation of photosynthesis and leaf respiration to multiple environmental effects, and that therefore requires no PFT‐specific parameterizations, in a standard version of the widely used LSM, Noah MP. We evaluated model performance with plant trait data from a 5‐year experiment and extensive global field measurements, and carbon flux measurements from FLUXNET2015. We show that observed R 25 and V cmax,25 vary substantially both temporally and spatially within the same PFT ( C.V. >20%). Our EEO‐based scheme captures 62% of the temporal and 70% of the spatial variations in V cmax,25 (73% and 54% of the variations in R 25 ). The standard scheme underestimates gross primary production by 10% versus 2% for the EEO‐based scheme and generates a larger spread in r (correlation coefficient) across flux sites (0.79 ± 0.16 vs. 0.84 ± 0.1, mean ± S.D.). The standard scheme greatly overestimates canopy respiration (bias: ∼200% vs. 8% for the EEO scheme), resulting in less CO 2 uptake by terrestrial ecosystems. Our approach thus simulates climate‐carbon coupling more realistically, with fewer parameters.

Ren, Yanghang [Department of Earth System Science ↗
DOE OSTI2021

The Significance of Aggregation Methods in Functional Group Modeling

The growth of forests and the feedbacks between forests and environmental changes are central issues in the planetary carbon cycle, global climate change, and basic plant ecology. A challenge to understanding both growth and feedbacks from local to global scales is that many critical metabolic processes vary among species. An innovation in solving this challenge is the recognition that species can be lumped into “functional groups” based on metabolic similarity, and these functional groups can then be studied in computational models that simulate ecosystem function. Despite the vast resources devoted to functional group studies and the progress made by them, an important logical and biological question has not been formally addressed, “How do the groupings alter the results of modeling studies?” To what extent do modeling results depend on the choices made in aggregating taxa into functional groups. Here, we consider the effects of using different aggregation strategies in simulating the carbon dynamics of a deciduous forest. Understanding the impacts that aggregation strategy has on efforts to simulate regional-to-global-scale forest dynamics offers insights into both ecosystem regulation and model function and addresses this central problem in the study of carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Cultivation of Methanonezhaarchaeia, the third class of methanogens within the phylum Thermoproteota

Methane is a potent greenhouse gas, largely produced by methanogenic archaea, contributing to Earth’s dynamic climate and biogeochemical cycles. In the past decade, metagenomics revealed that lineages outside of the Euryarchaeota superphylum encode genes for methanogenesis. This was recently confirmed through the cultivation of two classes of methanogenic Thermoproteota. Thus far, all methanogens within the Thermoproteota are predicted or were shown to be methylotrophic. The only exception to this are the Nezhaarchaea, for which metagenomic predictions suggest they are CO 2 -reducing methanogens. Here, we demonstrate methanogenic activity in a third class of Thermoproteota, the Methanonezhaarchaeia. Contrary to genomic predictions for this class, we cultivated a methylotrophic species, Candidatus Methanonezhaarchaeum fastidiosum YNP3N, highlighting the importance of testing metagenomic hypotheses through experimentation. We investigate the metabolic diversity of Methanonezhaarchaeia, including metabolic modifications accompanying frequent loss of methanogenesis in this class. This highlights gaps in our understanding of the biochemistry, diversity, and evolution of thermoproteotal methanogens and their contributions to carbon cycling.

Kohtz, Anthony J. [Montana State Univ., Bozeman, M↗
DOE OSTI2024

Cyanobacteria newly isolated from marine volcanic seeps display rapid sinking and robust, high-density growth

Cyanobacteria are photosynthetic organisms that play important roles in carbon cycling and are promising bioproduction chassis. Here, we isolate two novel cyanobacteria with 4.6Mbp genomes, UTEX 3221 and UTEX 3222, from a unique marine environment with naturally elevated CO₂. We describe complete genome sequences for both isolates and, focusing on UTEX 3222 due to its planktonic growth in liquid, characterize biotechnologically relevant growth and biomass characteristics. UTEX 3222 outpaces other fast-growing model strains on a solid medium. It can double every 2.35 hours in a liquid medium and grows to high density (>31 g/L biomass dry weight) in batch culture, nearly double that of Synechococcus sp. PCC 11901, whose high-density growth was recently reported. In addition, UTEX 3222 sinks readily, settling more quickly than other fast-growing strains, suggesting favorable economics of harvesting UTEX 3222 biomass. These traits may make UTEX 3222 a compelling choice for marine carbon dioxide removal (CDR) and photosynthetic bioproduction from CO₂. Overall, we find that bio-prospecting in environments with naturally elevated CO₂ may uncover novel CO₂-metabolizing organisms with unique characteristics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

An Integrative Model for Soil Biogeochemistry and Methane Processes: I. Model Structure and Sensitivity Analysis

Abstract Environmental changes are anticipated to generate substantial impacts on carbon cycling in peatlands, affecting terrestrial‐climate feedbacks. Understanding how peatland methane (CH 4 ) fluxes respond to these changing environments is critical for predicting the magnitude of feedbacks from peatlands to global climate change. To improve predictions of CH 4 fluxes in response to changes such as elevated atmospheric CO 2 concentrations and warming, it is essential for Earth system models to include increased realism to simulate CH 4 processes in a more mechanistic way. To address this need, we incorporated a new microbial‐functional group‐based CH 4 module into the Energy Exascale Earth System land model (ELM) and tested it with multiple observational data sets at an ombrotrophic peatland bog in northern Minnesota. The model is able to simulate observed land surface CH 4 fluxes and fundamental mechanisms contributing to these throughout the soil profile. The model reproduced the observed vertical distributions of dissolved organic carbon and acetate concentrations. The seasonality of acetoclastic and hydrogenotrophic methanogenesis—two key processes for CH 4 production—and CH 4 concentration along the soil profile were accurately simulated. Meanwhile, the model estimated that plant‐mediated transport, diffusion, and ebullition contributed to ∼23.5%, 15.0%, and 61.5% of CH 4 transport, respectively. A parameter sensitivity analysis showed that CH 4 substrate and CH 4 production were the most critical mechanisms regulating temporal patterns of surface CH 4 fluxes both under ambient conditions and warming treatments. This knowledge will be used to improve Earth system model predictions of these high‐carbon ecosystems from plot to regional scales.

58 GEOSCIENCES↗
DOE OSTI2025

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Seeing the forest for the trees: implementing dynamic representation of forest management and forest carbon in a long-term global multisector model

Abstract Studies have found that understanding forest management is critical in understanding the interaction between the carbon cycle and the integrated human-Earth system. This makes effectively representing forest management decisions such as planting and harvesting important. Here, we implement a novel dynamic forest harvest model in a global state of the art multi-sector dynamics model, namely the Global Change Analysis Model (GCAM). We implement an approach that explicitly tracks forest age and generates rotation ages for forest harvest that are responsive to changes in wood prices, changes in forest age and regional preferences for forest rotation. Furthermore, the forest sector in GCAM competes for investment with other land use types in the future years based on expected profit. Our baseline scenario results indicate that with the new forest harvest model, the current global wood product demand in GCAM can be met with minimal loss of old growth forest through the age-based harvest decisions. We find that economic pressure for deforestation and consequent loss of forest carbon is a bigger driver of global forest change than wood harvests, especially in developing regions. Under alternative scenarios where an economic value is placed on carbon across the terrestrial and energy systems, while there is an increase in forest plantations, there can be corresponding decreases in forest cover in some regions as forest land competes with land for bio-energy crops. When the carbon in forests is assigned a price, we find that the average rotation age for wood harvests can be reduced across regions to harvest forests in a more carbon efficient manner.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Growth–Mortality Coordination Differs Among Xerophytic Versus Mesophytic Tree Species During Severe Drought

ABSTRACT Forest composition is changing, yet the consequences for terrestrial carbon cycling are unclear. In the eastern United States, water‐demanding “mesophytic” tree species are replacing “xerophytic” oaks (Quercusspp.) and hickories (Caryaspp.), raising concerns that forest productivity will become increasingly sensitive to more frequent and severe drought conditions predicted for the region. However, we have a limited understanding of the extent to which the mortality risk of xerophytes versus mesophytes is coordinated with their growth sensitivity during drought. Here, we evaluated growth and mortality dynamics for 20 abundant eastern United States tree species following a severe drought in the summer of 2012. We synthesized data from ~4500 forest inventory plots and used an approach that quantified relative drought responses between co‐located trees to minimize impacts from environmental heterogeneity. We found that mesophytes were just as likely to perish as co‐occurring xerophytes but were more sensitive to drought in terms of diminished growth. These findings suggest that xerophytic decline is likely to lead to reduced carbon uptake during drought and that management efforts to conserve oak‐hickory stands will be decisive to sustain the carbon mitigation potential of these forests. However, we also found that growth‐mortality relationships differed between functional groups. Among xerophytes, growth and survival during drought were decoupled. Among mesophytes, there was a high degree of coordination, where species that experienced greater mortality also experienced greater growth reductions. Therefore, mesophytes with high growth sensitivity to water deficits are likely to be the most vulnerable to drought‐driven die‐off events moving forward.

Biodiversity & Conservation↗
DOE OSTI2021

Climate and atmospheric deposition drive the inter-annual variability and long-term trend of dissolved organic carbon flux in the conterminous United States

The lateral flux of dissolved organic carbon (DOC) from soils to inland waters and ultimately to the ocean represents a fundamental component of the global carbon cycle. To estimate the DOC flux, we developed an empirical terrestrial-aquatic DOC fluxes model (TAF-DOC). TAF-DOC incorporates various environmental factors (e.g., meteorology, sulfur, and nitrogen deposition) that to-date have not been comprehensively considered or well-represented in existing modeling frameworks. TAF-DOC was applied to estimate spatial-temporal patterns of DOC flux and potential fates across the conterminous United States during the 1985 to 2018 time period. Our results suggest that TAF-DOC successfully characterized spatial-temporal of DOC flux. As expected, the interannual pattern of DOC flux was strongly regulated by precipitation, but the long-term trend was significantly influenced by the rate of atmospheric wet sulfur deposition. From 1985 to 2018, TAF-DOC estimated DOC loading from terrestrial to aquatic ecosystems in the conterminous United States to be 33.5 ± 2.2 TgC per year, which was roughly 0.39–0.49% of total soil organic carbon stock estimates. The dominant fate of terrestrially-derived DOC was delivery to the coastal ocean in riverine export (41%), with another 21% buried in sediment and the remaining 12.8 ± 0.4 TgC per year (38%) returned to the atmosphere through outgassing from inland waters. Finally, assuming the quantities of DOC sediment burial and export to the ocean as an annual sink of terrestrially-derived carbon, budget inventories and models that do not account for DOC flux in the conterminous United States will underestimate the net annual carbon sink by as much as 5.5–6.4%.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain. The global annual mean GPP is historically thought to be around 120 PgC yr −1 , which is about 30–50 PgC yr −1 lower than GPP inferred from the oxygen-18 ( 18 O) isotope and soil respiration. This disparity is a source of uncertainty in predicting climate–carbon cycle feedbacks. Here, in this study, we infer GPP from carbonyl sulfide, an innovative tracer for CO 2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr −1 , which is consistent with estimates from 18 O (150–175 PgC yr −1 ) and soil respiration ($149^{+29}_{-23}$) PgC yr −1 ), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120–140 PgC yr –1 ) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories, our findings lay a physiological foundation on which the understanding and prediction of carbon–climate feedbacks can be advanced.

Lai, Jiameng↗
DOE OSTI2023

Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)

Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Assessing carbon storage capacity and saturation across six central US grasslands using data–model integration

Abstract. Future global changes will impact carbon (C) fluxes and pools in most terrestrial ecosystems and the feedback of terrestrial carbon cycling to atmospheric CO2. Determining the vulnerability of C in ecosystems to future environmental change is thus vital for targeted land management and policy. The C capacity of an ecosystem is a function of its C inputs (e.g., net primary productivity – NPP) and how long C remains in the system before being respired back to the atmosphere. The proportion of C capacity currently stored by an ecosystem (i.e., its C saturation) provides information about the potential for long-term C pools to be altered by environmental and land management regimes. We estimated C capacity, C saturation, NPP, and ecosystem C residence time in six US grasslands spanning temperature and precipitation gradients by integrating high temporal resolution C pool and flux data with a process-based C model. As expected, NPP across grasslands was strongly correlated with mean annual precipitation (MAP), yet C residence time was not related to MAP or mean annual temperature (MAT). We link soil temperature, soil moisture, and inherent C turnover rates (potentially due to microbial function and tissue quality) as determinants of carbon residence time. Overall, we found that intermediates between extremes in moisture and temperature had low C saturation, indicating that C in these grasslands may trend upwards and be buffered against global change impacts. Hot and dry grasslands had greatest C saturation due to both small C inputs through NPP and high C turnover rates during soil moisture conditions favorable for microbial activity. Additionally, leaching of soil C during monsoon events may lead to C loss. C saturation was also high in tallgrass prairie due to frequent fire that reduced inputs of aboveground plant material. Accordingly, we suggest that both hot, dry ecosystems and those frequently disturbed should be subject to careful land management and policy decisions to prevent losses of C stored in these systems.

58 GEOSCIENCES↗
DOE OSTI2019

Agricultural impacts on nitrogen cycling: climate and air pollution

Ratios of key soil nitrogen fluxes from two terrestrial ecosystem models (TEMs) are compared to observational values in the literature. The fluxes included nitrification, denitrification, mineralization, immobilization and plant uptake, with the latter two fluxes partitioned into NH 4 + and NO 3 -. The two TEMs, ELMv1-ECA and CLM5.0, originated from a common model but have diverged in their handling of plant/microbe competition for soil mineral N. Both models predict unrealistically low assimilation (i.e, immobilization) of NO 3 - by soil bacteria compared to literature values and unrealistic dominance of plant uptake by a single form of mineral nitrogen (NO 3 - for ELM, NH 4 + for CLM5.0). Global ratios of net mineralization (i.e., gross mineralization – gross immobilization) appear unrealistically high in both models compared to literature values while rates of nitrification/gross mineralization appear unrealistically high (ELM) and low (CLM5.0). The ratio of denitrification/nitrification is likely high in both models (3:1 ELM; 2:1 CLM5.0), but few experimental data exist to evaluate these ratios, in part because nitrification and denitrification are quantified with different techniques and generally are not measured simultaneously. The same is true of plant N uptake and microbial N assimilation. Single grid point experiments with CLM5.0 at the Hubbard Brook long-term ecological research site in New Hampshire indicate that the parameterization of nitrification is a potentially important focus area that can bring soil nitrogen flux ratios into better agreement with observations. The current flux ratios raise questions about the credibility of present and future simulations of mineral N limitation on the carbon cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

A Bayesian approach to evaluation of soil biogeochemical models

Abstract. To make predictions about the carbon cycling consequences of rising global surface temperatures, Earth system scientists rely on mathematical soil biogeochemical models (SBMs). However, it is not clear which models have better predictive accuracy, and a rigorous quantitative approach for comparing and validating the predictions has yet to be established. In this study, we present a Bayesian approach to SBM comparison that can be incorporated into a statistical model selection framework. We compared the fits of linear and nonlinear SBMs to soil respiration data compiled in a recent meta-analysis of soil warming field experiments. Fit quality was quantified using Bayesian goodness-of-fit metrics, including the widely applicable information criterion (WAIC) and leave-one-out cross validation (LOO). We found that the linear model generally outperformed the nonlinear model at fitting the meta-analysis data set. Both WAIC and LOO computed higher overfitting risk and effective numbers of parameters for the nonlinear model compared to the linear model, conditional on the data set. Goodness of fit for both models generally improved when they were initialized with lower and more realistic steady-state soil organic carbon densities. Still, testing whether linear models offer definitively superior predictive performance over nonlinear models on a global scale will require comparisons with additional site-specific data sets of suitable size and dimensionality. Such comparisons can build upon the approach defined in this study to make more rigorous statistical determinations about model accuracy while leveraging emerging data sets, such as those from long-term ecological research experiments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Exploiting Metal–Ligand Cooperativity to Sequester, Activate, and Reduce Atmospheric Carbon Dioxide with a Neutral Zinc Complex

As atmospheric levels of carbon dioxide (CO 2 ) continue to increase, there is an immediate need to balance the carbon cycle. Current approaches require multiple processes to fix CO 2 from the atmosphere or flue gas and then reduce it to value-added products. The zinc(II) catalyst Zn(DMTH) (DMTH = diacetyl-2-(4-methyl-3-thiosemicarbazonate)-3-(2-pyridinehydrazonato)) reduces CO 2 from air to formate with a faradaic efficiency of 15.1% based on total charge. The catalyst utilizes metal–ligand cooperativity and redox-active ligands to fix, activate, and reduce CO 2 . Our approach provides a new strategy that incorporates sustainable earth-abundant metals that are oxygen and water tolerant.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Substrate Utilization and Competitive Interactions Among Soil Bacteria Vary With Life-History Strategies

Microorganisms have evolved various life-history strategies to survive fluctuating resource conditions in soils. However, it remains elusive how the life-history strategies of microorganisms influence their processing of organic carbon, which may affect microbial interactions and carbon cycling in soils. Here, we characterized the genomic traits, exometabolite profiles, and interactions of soil bacteria representing copiotrophic and oligotrophic strategists. Isolates were selected based on differences in ribosomal RNA operon ( rrn ) copy number, as a proxy for life-history strategies, with pairs of “high” and “low” rrn copy number isolates represented within the Micrococcales, Corynebacteriales, and Bacillales. We found that high rrn isolates consumed a greater diversity and amount of substrates than low rrn isolates in a defined growth medium containing common soil metabolites. We estimated overlap in substrate utilization profiles to predict the potential for resource competition and found that high rrn isolates tended to have a greater potential for competitive interactions. The predicted interactions positively correlated with the measured interactions that were dominated by negative interactions as determined through sequential growth experiments. This suggests that resource competition was a major force governing interactions among isolates, while cross-feeding of metabolic secretion likely contributed to the relatively rare positive interactions observed. By connecting bacterial life-history strategies, genomic features, and metabolism, our study advances the understanding of the links between bacterial community composition and the transformation of carbon in soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Large isotopic variability at the micron-scale in ‘Shuram’ excursion carbonates from South Australia

Ediacaran-aged (635–541 million years ago) marine sediments contain a large negative carbon isotope (δ 13 C) excursion, in which carbonate δ 13 C values reach -12‰ (VPDB). Known as the ‘Shuram’ excursion, many workers have interpreted this δ 13 C record as an unprecedented perturbation to the global carbon cycle, leading to speculation about a causal connection to the broadly contemporaneous rise of animal life. Others have interpreted the δ 13 C signal as a product of diagenesis, thereby minimizing its relevance for understanding the evolution of metazoans. In this work, we present SEM imaging and in-situ δ 13 C and δ 18 C values measured by secondary ion mass spectrometry (SIMS) to assess these competing hypotheses in the Wonoka Formation of South Australia. Our results from the minimum of the excursion show that rounded sedimentary grains of calcite have δ 13 C values between -12.8 to -10.6‰ and δ 18 C values between 17.8 to 15.5‰ (VPDB). Euhedral dolomite that appears to have grown unimpeded in open sedimentary pore spaces also is present. These early-stage dolomites are interpreted as early authigenic in origin and have δ 13 C values that reach +5‰, requiring a formation fluid with a substantially different δ 13 C composition from basin waters or bulk sediment. Together, these results provide little evidence for the hypothesis that a late diagenetic overprint has generated the ‘Shuram’ excursion in the Wonoka. Instead, they suggest the presence of a large carbon isotopic gradient in the surface environment, with shallow waters capable of precipitating carbonates with very low δ 13 C (down to 12‰) and deeper shelf and/or marine pore waters generating carbonates with positive carbon isotope values (up to +5‰). Because negative isotope excursions of similar magnitude are found in widely dispersed Ediacaran basins, it is likely that this gradient was characteristic of shelf environments of this period and that a still-unknown global process led to the ‘Shuram’ excursion in shallow water carbonates.

58 GEOSCIENCES↗