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At least 631 records · Page 35

Soil incubation methods lead to large differences in inferred methane production temperature sensitivity

Abstract Quantifying the temperature sensitivity of methane (CH 4 ) production is crucial for predicting how wetland ecosystems will respond to climate warming. Typically, the temperature sensitivity (often quantified as a Q 10 value) is derived from laboratory incubation studies and then used in biogeochemical models. However, studies report wide variation in incubation-inferred Q 10 values, with a large portion of this variation remaining unexplained. Here we applied observations in a thawing permafrost peatland (Stordalen Mire) and a well-tested process-rich model ( ecosys ) to interpret incubation observations and investigate controls on inferred CH 4 production temperature sensitivity. We developed a field-storage-incubation modeling approach to mimic the full incubation sequence, including field sampling at a particular time in the growing season, refrigerated storage, and laboratory incubation, followed by model evaluation. We found that CH 4 production rates during incubation are regulated by substrate availability and active microbial biomass of key microbial functional groups, which are affected by soil storage duration and temperature. Seasonal variation in substrate availability and active microbial biomass of key microbial functional groups led to strong time-of-sampling impacts on CH 4 production. CH 4 production is higher with less perturbation post-sampling, i.e. shorter storage duration and lower storage temperature. We found a wide range of inferred Q 10 values (1.2–3.5), which we attribute to incubation temperatures, incubation duration, storage duration, and sampling time. We also show that Q 10 values of CH 4 production are controlled by interacting biological, biochemical, and physical processes, which cause the inferred Q 10 values to differ substantially from those of the component processes. Terrestrial ecosystem models that use a constant Q 10 value to represent temperature responses may therefore predict biased soil carbon cycling under future climate scenarios.

54 ENVIRONMENTAL SCIENCES↗

Additively Manufactured NdFeB Polyphenylene Sulfide Halbach Magnets to Generate Variable Magnetic Fields for Neutron Reflectometry

Halbach arrays are the most efficient closed structures for generating directed magnetic fields and gradients, and are widely used in various electric machines. We utilized fused deposition modeling-based Big Area Additive Manufacturing technology to print customized, compensated concentric Halbach array rings, using polyphenylene sulfide-bonded NdFeB permanent magnets for polarized neutron reflectometry. The Halbach rings could generate a 0 ≤ B ≤ 0.30 T field, while preserving 90% polarization of an axial neutron beam. Polarized neutron beams are used to study a wide range of structural and magnetic phenomena spanning physics, chemistry, and biology. In this study, we demonstrate the effectiveness of additive manufacturing for producing prototype Halbach arrays, characterize their magnetic properties, and generated magnetic fields, and discuss the conservation of neutron beam polarization as a function of magnetic field.

36 MATERIALS SCIENCE↗

Spontaneous Chirality Flipping in an Orthogonal Spin-Charge Ordered Topological Magnet

The asymmetric distribution of chiral objects with opposite chirality is of great fundamental interest ranging from molecular biology to particle physics. In quantum materials, chiral states can build on inversion-symmetry-breaking lattice structures or emerge from spontaneous magnetic ordering induced by competing interactions. Although the handedness of a chiral state can be changed through external fields, a spontaneous chirality flipping has yet to be discovered. We present experimental evidence of chirality flipping via changing temperature in a topological magnet EuAl 4 , which features orthogonal spin density waves (SDW) and charge density waves (CDW). Using circular dichroism of Bragg peaks in the resonant magnetic x-ray scattering, we find that the chirality of the helical SDW flips through a first-order phase transition with modified SDW wavelength. Intriguingly, we observe that the CDW couples strongly with the SDW and displays a rare commensurate-to-incommensurate transition at the chirality flipping temperature. Combining with first-principles calculations and angle-resolved photoemission spectroscopy, our results support a Fermi surface origin of the helical SDW with intertwined spin, charge, and lattice degrees of freedom in EuAl 4 . Our results reveal an unprecedented spontaneous chirality flipping and lay the groundwork for a new functional manipulation of chirality through momentum-dependent spin-charge-lattice interactions. Published by the American Physical Society 2024

3-dimensional systems↗

Microbially mediated climate feedbacks from wetland ecosystems

Wetlands are crucial nodes in the carbon cycle, emitting approximately 20% of global CH4 while also sequestering 20%–30% of all soil carbon. Both greenhouse gas fluxes and carbon storage are driven by microbial communities in wetland soils. However, these key players are often overlooked or overly simplified in current global climate models. Here, we first integrate microbial metabolisms with biological, chemical, and physical processes occurring at scales from individual microbial cells to ecosystems. This conceptual scale-bridging framework guides the development of feedback loops describing how wetland-specific climate impacts (i.e., sea level rise in estuarine wetlands, droughts and floods in inland wetlands) will affect future climate trajectories. Furthermore, these feedback loops highlight knowledge gaps that need to be addressed to develop predictive models of future climates capturing microbial contributions. We propose a roadmap connecting environmental scientific disciplines to address these knowledge gaps and improve the representation of microbial processes in climate models. Together, this paves the way to understand how microbially mediated climate feedbacks from wetlands will impact future climate change.

54 ENVIRONMENTAL SCIENCES↗

Wildfire smoke impacts lake ecosystems

Abstract Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities.

54 ENVIRONMENTAL SCIENCES↗

Fostering Peat Moss Feedbacks to Accelerate Peatland Restoration

Extensive knowledge exists on plant-species traits and functions, but we understand less about how population- or community-level emergent traits influence ecosystem functioning. This knowledge gap is important for ecosystems like peatlands, arid drylands, salt marshes, seagrass meadows and mangroves, where emergent traits of plant communities can create plant-environment feedbacks that amplify or dampen ecosystem processes. Recent insights from restoration ecology suggest that these feedbacks can critically influence restoration success. Despite growing recognition of emergent trait-driven feedbacks in other ecosystems, they remain underexplored in peatland restoration, world’s most carbon-dense ecosystem. Here, we review emergent self-amplifying and self-dampening feedbacks with net positive effects for peat moss-dominated systems. We show how these feedbacks can promote key physical, chemical, and biological processes that enhance peat moss growth, increase water retention, and reduce microbial decomposition of organic matter. Understanding and fostering these feedbacks offers a promising framework to accelerate peatland restoration across diverse degradation states.

Sphagnum↗

An exopolysaccharide pathway from a freshwater Sphingomonas isolate

Bacteria embellish their cell envelopes with a variety of specialized polysaccharides. Biosynthesis pathways for these glycans are complex, and final products vary greatly in their chemical structures, physical properties, and biological activities. This tremendous diversity comes from the ability to arrange complex pools of monosaccharide building blocks into polymers with many possible linkage configurations. Due to the complex chemistry of bacterial glycans, very few biosynthetic pathways have been defined in detail. As part of an initiative to characterize novel polysaccharide biosynthesis enzymes, we isolated a bacterium from Lake Michigan called Sphingomonas sp. LM7 that is proficient in exopolysaccharide (EPS) production. We identified genes that contribute to EPS biosynthesis in LM7 by screening a transposon mutant library for colonies displaying altered colony morphology. A gene cluster was identified that appears to encode a complete wzy/wzx-dependent polysaccharide assembly pathway. Deleting individual genes in this cluster caused a non-mucoid phenotype and a corresponding loss of EPS secretion, confirming the role of this gene cluster in polysaccharide production. We extracted EPS from LM7 cultures and determined that it contains a linear chain of 3- and 4-linked glucose, galactose, and glucuronic acid residues. Finally, we show that the EPS pathway in Sphingomonas sp. LM7 diverges from that of sphingan-family EPSs and adhesive polysaccharides such as the holdfast that are present in other Alphaproteobacteria. Our approach of characterizing complete biosynthetic pathways holds promise for engineering polysaccharides with valuable properties.

59 BASIC BIOLOGICAL SCIENCES↗

Priorities, opportunities, and challenges for integrating microorganisms into Earth system models for climate change prediction

ABSTRACT Climate change jeopardizes human health, global biodiversity, and sustainability of the biosphere. To make reliable predictions about climate change, scientists use Earth system models (ESMs) that integrate physical, chemical, and biological processes occurring on land, the oceans, and the atmosphere. Although critical for catalyzing coupled biogeochemical processes, microorganisms have traditionally been left out of ESMs. Here, we generate a “top 10” list of priorities, opportunities, and challenges for the explicit integration of microorganisms into ESMs. We discuss the need for coarse-graining microbial information into functionally relevant categories, as well as the capacity for microorganisms to rapidly evolve in response to climate-change drivers. Microbiologists are uniquely positioned to collect novel and valuable information necessary for next-generation ESMs, but this requires data harmonization and transdisciplinary collaboration to effectively guide adaptation strategies and mitigation policy.

Microbiology↗

Double and Charge-Transfer Excitations in Time-Dependent Density Functional Theory

Time-dependent density functional theory has emerged as a method of choice for calculations of spectra and response properties in physics, chemistry, and biology, with its system-size scaling enabling computations on systems much larger than otherwise possible. While increasingly complex and interesting systems have been successfully tackled with relatively simple functional approximations, there has also been increasing awareness that these functionals tend to fail for certain classes of approximations. Here I review the fundamental challenges the approximate functionals have in describing double excitations and charge-transfer excitations, which are two of the most common impediments for the theory to be applied in a black-box way. At the same time, I describe the progress made in recent decades in developing functional approximations that give useful predictions for these excitations.

Chemistry↗

Urban-Scale Processes in High-Spatial-Resolution Earth System Models

Cities and their associated urban areas have a much larger impact on the environment than their spatial footprint on the Earth's surface. This is undoubtedly true at local and regional scales, but also at global scales. At this time, more than half of the world's population lives in urban areas (80% in the United States), and the global proportion is projected to climb to 70% by 2050. Therefore, numerical models to study physics, chemistry, and biology affecting the Earth system at regional and global scales must represent the effects of urban areas on climate and the effects of a changing climate on urban areas. At the same time, it is essential to develop state of the art, simple and accurate urban models to better understand the relevant processes and also to address issues related to urban security against the spectra of chemical, biological and radiological (CBR) hazards. Towards bringing urban scientific communities together, a two-and-a-half-day international workshop was held at the Argonne National Laboratory (ANL) in the Chicago area on May 22-24, 2019. This workshop brought together more than 60 national and international experts to develop a roadmap for a better understanding of the issues associated with urban areas and at enhancing the capabilities of regional and global Earth System models (ESMs) in representing the atmospheric dynamics and chemistry, unique aspects of the biosphere and land use, and human dimensions of the urban environment.

54 ENVIRONMENTAL SCIENCES↗

Randomized probe imaging through deep k-learning

Randomized probe imaging (RPI) is a single-frame diffractive imaging method that uses highly randomized light to reconstruct the spatial features of a scattering object. The reconstruction process, known as phase retrieval, aims to recover a unique solution for the object without measuring the far-field phase information. Typically, reconstruction is done via time-consuming iterative algorithms. In this work, we propose a fast and efficient deep learning based method to reconstruct phase objects from RPI data. The method, which we call deep k-learning, applies the physical propagation operator to generate an approximation of the object as an input to the neural network. This way, the network no longer needs to parametrize the far-field diffraction physics, dramatically improving the results. Deep k-learning is shown to be computationally efficient and robust to Poisson noise. The advantages provided by our method may enable the analysis of far larger datasets in photon starved conditions, with important applications to the study of dynamic phenomena in physical science and biological engineering.

Guo, Zhen (ORCID:0000000213473451)↗

Data for: Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events

This dataset contains data and code associated with the paper Patel et al. "Time to anoxia: Observations and predictions of oxygen drawdown following coastal flood events".The coastal terrestrial-aquatic interface (TAI) is a highly dynamic system characterized by strong physical, chemical, and biological gradients. In particular, shifting soil redox conditions and consumption of terminal electron acceptors, due in part to dynamic hydrologic conditions, is a strong driver of carbon availability and transformations across TAIs. However, while redox dynamics are well described, our ability to quantitatively forecast rates of oxic to anoxic shifts in soils with different characteristics and inundation regimes is limited. We integrated field measurements, laboratory incubations, and model simulations to improve mechanistic understanding of oxygen consumption dynamics in coastal soils. Continuous in situ monitoring unexpectedly revealed that flooding caused temporary spikes in subsurface dissolved oxygen followed by rapid consumption in the wetlands. To further investigate these mechanisms in a controlled setting, we performed laboratory incubations using surface and subsurface soils from a TAI gradient (defined here as upland forest to transitional forest to wetland) in Western Lake Erie to measure oxygen consumption rates in TAI soils during flood events. In our experiments, wetland soils reached anoxia the fastest, in ∼ 9 h on average, whereas upland soils turned anoxic in ∼ 18 h. Subsurface upland soils did not turn anoxic even after two weeks of saturation in the lab, and their oxygen consumption patterns suggested carbon and/or nutrient limitation. These results are consistent with in-situ groundwater redox and oxygen measurements in the field, where wetland soils exhibited the highest rates of oxygen consumption along the TAI. Model simulations of oxygen consumption suggested that oxygen consumption had stronger abiotic controls in wetland soils but stronger biotic controls in upland soils, providing a useful framework for future incubation experiments. Microbial activity is a strong driver of oxygen consumption in TAI soils, although it is constrained by the availability of dissolved carbon in subsurface soils.This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/COMPASS-DOE/cmps-time_to_anoxia (DOI: 10.5281/zenodo.10815374).

54 ENVIRONMENTAL SCIENCES↗

A Modular System for Increasing Predictiveness for Extreme Climate Predictions

We know that climate change is poised to reshape our world, but we lack clear enough predictions about precisely how. The preponderance of these changes is associated with human activity, specifically the emission of CO 2 and other greenhouse gases. Problematically, projections of climate change continue to be marred by unacceptably large uncertainties which hamper informed decision-making and cost society a chance to adapt proactively and effectively. These uncertainties stem from deficiencies in predictions of future greenhouse gas emissions, but also from inaccuracies in the representation of the physical models used to predict the climate response to such emissions. The uncertainties in projections associated with the inaccurate representation of climate physics, chemistry and biology are similar to those that plagued the first global climate models developed fifty years ago, despite more than a factor 10 8 increase in computer performance. Our transformational question is then, how can the accuracy of climate projections be dramatically improved by applying recent advances in the computational and data sciences to train the models with the wealth of data being constantly collected about the ongoing changes in the climate system?

54 ENVIRONMENTAL SCIENCES↗

Co-Generation Wastewater Treatment at Coal-Fired Energy Plants (Final Report)

Steam electric energy generation typically results in the discharge of one or more effluent streams. Coal-fired energy plant air quality regulations have had the effect of transferring pollutants previously in the flue gas to water by means of the flue gas desulfurization (FGD) system. Combined physical-chemical and biological treatment solutions are currently the most economical approach for treating FGD wastewater. Multi-effect evaporators are significantly higher cost but can meet potential upcoming regulations that are more stringent.

01 COAL, LIGNITE, AND PEAT↗

Enhanced Atmospheric Research at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) (Final Report)

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was an international scientific expedition into the central Arctic sea ice to study the changing atmosphere-ice-ocean system and its key physical, chemical, and biological processes in a way that will support improved understanding and modeling of Arctic climate. The US Department of Energy’s Atmospheric Research Measurement (ARM) Program operated its second ARM Mobile Facility (AMF2) as a major contribution to the expedition, and the Atmospheric System Research (ASR) program supported this project to maximize the success of DOE’s involvement in MOSAiC. This project has enabled the successful collection of data through support of field operations plans, in-field operational implementation, oversight of real-time data quality, and representing DOE’s interests within the broader international MOSAiC endeavor. The project has promoted scientific research by facilitating and leading a number of efforts to develop value-added products that will support research, including products related to aerosol properties, trace gases, cloud properties, snowfall, the surface energy budget, and a merged product designed for model assessment. These products and related analyses have also contributed to numerous scientific publications on related themes as well as direct model evaluation. Lastly, the project has engaged in a great deal of communication and outreach activities that help to publicize and promote both MOSAiC and DOE’s specific contribution to a broad audience that includes the scientific community, program management, policy makers, and the general public.

54 ENVIRONMENTAL SCIENCES↗

Support for the Second MOSAiC Science Conference support (Final Report)

This is a final report for a conference support project. The US Department of Energy’s Atmospheric System Research Program provided funding support for the Second MOSAiC Science Conference. MOSAiC is the Multidisciplinary drifting Observatory for the Study of Arctic Climate, a yearlong, international expedition into the rapidly changing Arctic sea ice. The expedition collected measurements of the atmosphere, sea ice, and ocean to study coupled physical, chemical, and biological processes. The Second MOSAiC Science Conference provided an important opportunity to bring the MOSAiC-interested community together to discuss MOSAiC data, scientific analyses, synthesis, modeling activities, and more. Overall, the conference was a significant success and has motivated and facilitated a great deal of ongoing research. The support provide by this project was used along with support from other agencies to implement a participant support program that enabled participation in the conference by a diverse collection of researchers from many different countries and disciplines, 60% of whom were female. Most of these participants were Early Career Researchers. Participation by these researchers was vital to the overall success of the conference and has helped to build leadership and research skills for the participants that will serve both themselves and the broader scientific community in the future.

54 ENVIRONMENTAL SCIENCES↗

Development of high throughput light-sheet fluorescence lifetime imaging microscopy for 3D functional imaging of metabolic pathways in plant and microorganisms (Final Technical Report)

This research program will enable new biochemical contrast in the nanosecond lifetime domain through use of the recently demonstrated electro-optic fluorescence lifetime imaging technique (EO-FLIM) for wide-field lifetime imaging. The Stanford/Stanford Linear Accelerator Center multidisciplinary collaboration -- physics, applied physics, and structural biology -- will develop a light-sheet fluorescence lifetime imaging microscope for functional studies of microbial and plant metabolic pathways and dynamic interactions between plants and microorganisms in the rhizosphere. The proposed approach overcomes the imaging time bottleneck associated with existing fluorescence lifetime imaging methods. Initial demonstrations have shown a factor of 100,000 improvement in photon throughput compared to existing methods. High photon efficiency allowed the first wide-field fluorescence lifetime imaging of single molecules. Recent work has improved the technique’s repetition rate to enable compatibility with mode-locked lasers and demonstrated the combination of wide-field fluorescence lifetime imaging with super-resolution localization microscopy, observations of single molecule dynamics, and observation of donor lifetime quenching in single-molecule imaging. These results were achieved on standard camera sensors and would not have been possible with other wide-field approaches. The throughput and photon economy of the EO-FLIM method enables new BER-relevant imaging opportunities. In particular, scanned single- and two-photon light-sheet excitation will be used to achieve volumetric imaging with time-domain contrast.

47 OTHER INSTRUMENTATION↗

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↗