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All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Aboveground carbon loss associated with the spread of ghost forests as sea levels rise

Coastal forests sequester and store more carbon than their terrestrial counterparts but are at greater risk of conversion due to sea level rise. Saltwater intrusion from sea level rise converts freshwater-dependent coastal forests to more salt-tolerant marshes, leaving 'ghost forests' of standing dead trees behind. Although recent research has investigated the drivers and rates of coastal forest decline, the associated changes in carbon storage across large extents have not been quantified. We mapped ghost forest spread across coastal North Carolina, USA, using repeat Light Detection and Ranging (LiDAR) surveys, multi-temporal satellite imagery, and field measurements of aboveground biomass to quantify changes in aboveground carbon. Between 2001 and 2014, 15% (167 km2) of unmanaged public land in the region changed from coastal forest to transition-ghost forest characterized by salt-tolerant shrubs and herbaceous plants. Salinity and proximity to the estuarine shoreline were significant drivers of these changes. This conversion resulted in a net aboveground carbon decline of 0.13 ± 0.01 TgC. Because saltwater intrusion precedes inundation and influences vegetation condition in advance of mature tree mortality, we suggest that aboveground carbon declines can be used to detect the leading edge of sea level rise. Aboveground carbon declines along the shoreline were offset by inland aboveground carbon gains associated with natural succession and forestry activities like planting (2.46 ± 0.25 TgC net aboveground carbon across study area). Our study highlights the combined effects of saltwater intrusion and land use on aboveground carbon dynamics of temperate coastal forests in North America. By quantifying the effects of multiple interacting disturbances, our measurement and mapping methods should be applicable to other coastal landscapes experiencing saltwater intrusion. As sea level rise increases the landward extent of inundation and saltwater exposure, investigations at these large scales are requisite for effective resource allocation for climate adaptation. In this changing environment, human intervention, whether through land preservation, restoration, or reforestation, may be necessary to prevent aboveground carbon loss.

ghost forests↗
DOE OSTI2024

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a “piecemeal” iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Chemistry↗
NASA NTRS2022

Vegetation and vantage point influence visibility across diverse ecosystems: Implications for animal ecology

Visual information can influence animal behavior and habitat use in diverse ways. Visibility is the property that relates 3D habitat structure to accessibility of visual information. Despite the importance of visibility in animal ecology, this property remains largely unstudied. Our objective was to assess how habitat structure from diverse environments and animal position within that structure can influence visibility. We gathered terrestrial lidar data (1 cm at 10 m) in four ecosystems (forest, shrub-steppe, prairie, and desert) to characterize viewsheds (i.e., estimates of visibility based on spatially explicit sightlines) from multiple vantage points. Both ecosystem-specific structure and animal position influenced potential viewsheds. Generally, as height of the vantage point above the ground increased, viewshed extent also increased, but the relationships were not linear. In low-structure ecosystems (prairie, shrub-steppe, and desert), variability in viewsheds decreased as vantage points increased to heights above the vegetation canopy. In the forest, however, variation in viewsheds was highest at intermediate heights, and markedly lower at the lowest and highest vantage points. These patterns are likely linked to the amount, heterogeneity, and distribution of vegetation structure occluding sightlines. Our work is the first to apply a new method that can be used to estimate viewshed properties relevant to animals (i.e., viewshed extent and variability). We demonstrate that these properties differ across terrestrial landscapes in complex ways that likely influence many facets of animal ecology and behavior.

Rachel Stein↗
NASA NTRS2006

The Need for High Spatial Resolution Multispectral Thermal Remote Sensing Data In Urban Heat Island Research

Although the study of the Urban Heat Island (UHI) effect dates back to the early 1800's when Luke Howard discovered London s heat island, it has only been with the advent of thermal remote sensing systems that the extent, characteristics, and impacts of the UHI have become to be understood. Analysis of the UHI effect is important because above all, this phenomenon can directly influence the health and welfare of urban residents. For example, in 1995, over 700 people died in Chicago due to heat-related causes. UHI s are characterized by increased temperature in comparison to rural areas and mortality rates during a heat wave increase exponentially with the maximum temperature, an effect that is exacerbated by the UHI. Aside from the direct impacts of the UHI on temperature, UHI s can produce secondary effects on local meteorology, including altering local wind patterns, increased development of clouds and fog, and increasing rates of precipitation either over, or downwind, of cities. Because of the extreme heterogeneity of the urban surface, in combination with the sprawl associated with urban growth, thermal infrared (TIR) remote sensing data have become of significant importance in understanding how land cover and land use characteristics affect the development and intensification of the UHI. TIR satellite data have been used extensively to analyze the surface temperature regimes of cities to help observe and measure the impacts of surface temperatures across the urban landscape. However, the spatial scales at which satellite TIR data are collected are for the most part, coarse, with the finest readily available TIR data collected by the Landsat ETM+ sensor at 60m spatial resolution. For many years, we have collected high spatial resolution (10m) data using an airborne multispectral TIR sensor over a number of cities across the United States. These high resolution data have been used to develop an understanding of how discrete surfaces across the urban environment (e.g., rooftops, pavements) interact from a surface-lower atmosphere energy flux perspective, to force the development of the UHI. Moreover, the airborne TIR sensor we used in our UHI studies was a multispectral sensor that had six channels in the 8-12pm range. The advantages of collecting multispectral TIR data became readily evident as a valuable tool for better calculation of unique surface thermal energy responses for urban materials over the 8-12 micrometer region, and also for getting a better handle on surface emissivity characteristics for these discrete surfaces. In this presentation, we will provide evidence on the virtues of how high spatial resolution multispectral TIR data can provide for better analysis of the UHI that cannot now be attained via TIR data obtained from satellites. Furthermore, we wish to provide compelling evidence on why future TIR satellite sensors should collect data at fine spatial resolutions (e.g. less than or equal to 30m) to better allow for measurement of surface thermal energy fluxes from discrete urban surfaces, and to better understand how surface fluxes from different urban materials in cities around the world in different climatic regimes, affect development of the UHI characteristics.

Quattrochi, Dale A.↗
DOE OSTI2023

Climate and air pollution impacts of generating biopower from forest management residues in California

California faces crisis conditions on its forested landscapes. A century of aggressive logging and fire suppression in combination with conditions exacerbated by climate change have created an ongoing ecological, economic, and public health emergency. Between commercial harvests on California’s working forestlands and the increasing number of acres the state treats each year for fire risk reduction and carbon sequestration, California forests generate millions of tons of woody residues annually—residues that are typically left or burned in the field. State policymakers have turned to biomass electricity generation as a key market for woody biomass in the hope that it can support sustainable forest management activities while also providing low-carbon renewable electricity. However, open questions surrounding the climate and air pollution performance of electricity generation from woody biomass have made it difficult to determine how best to manage the risks and opportunities posed by forest residues. The California Biomass Residue Emissions Characterization (C-BREC) model offers a spatially-explicit life cycle assessment framework to rigorously and transparently establish the climate and air pollution impacts of biopower from forest residues in California under current conditions. The C-BREC model characterizes the variable emissions from different biomass supply chains as well as the counterfactual emissions from prescribed burn, wildfire, and decay avoided by residue mobilization. We find that the life cycle ‘carbon footprint’ of biopower from woody residues generated by recent forest treatments in California ranges widely—from comparable with solar photovoltaic on the low end to comparable with natural gas on the high end. This variation stems largely from the heterogeneity in the fire and decay conditions these residues would encounter if left in the field, with utilization of residue that would otherwise have been burned in place offering the best climate and air quality performance. California’s energy and forest management policies should account for this variation to ensure desired climate benefits are achieved.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1996

Approximate scaling properties of RNA free energy landscapes

RNA free energy landscapes are analysed by means of "time-series" that are obtained from random walks restricted to excursion sets. The power spectra, the scaling of the jump size distribution, and the scaling of the curve length measured with different yard stick lengths are used to describe the structure of these "time series". Although they are stationary by construction, we find that their local behavior is consistent with both AR(1) and self-affine processes. Random walks confined to excursion sets (i.e., with the restriction that the fitness value exceeds a certain threshold at each step) exhibit essentially the same statistics as free random walks. We find that an AR(1) time series is in general approximately self-affine on timescales up to approximately the correlation length. We present an empirical relation between the correlation parameter rho of the AR(1) model and the exponents characterizing self-affinity.

Signal Processing, Computer-Assisted↗
DOE OSTI2013

Neutron-skin uncertainties of Skyrme energy density functionals

Neutron-skin thickness is an excellent indicator of isovector properties of atomic nuclei. As such, it correlates strongly with observables in finite nuclei that depend on neutron-to-proton imbalance and the nuclear symmetry energy that characterizes the equation of state of neutron-rich matter. A rich worldwide experimental program involving studies with rare isotopes, parity-violating electron scattering, and astronomical observations is devoted to pinning down the isovector sector of nuclear models. We assess the theoretical systematic and statistical uncertainties of neutron-skin thickness and relate them to the equation of state of nuclear matter, and in particular to nuclear symmetry energy parameters. We use the nuclear superfluid density functional theory with several Skyrme energy density functionals and density dependent pairing. To evaluate statistical errors and their budget, we employ the statistical covariance technique. We find that the errors on neutron skin increase with neutron excess. Statistical errors due to uncertain coupling constants of the density functional are found to be larger than systematic errors, the latter not exceeding 0.06 fm in most neutron-rich nuclei across the nuclear landscape. The single major source of uncertainty is the poorly determined slope $L$ of the symmetry energy that parametrizes its density dependence. To provide essential constraints on the symmetry energy of the nuclear energy density functional, next-generation measurements of neutron skins are required to deliver precision better than 0.06 fm.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2005

Texturing Blood-Glucose-Monitoring Optics Using Oxygen Beams

A method has been invented for utilizing directed, hyperthermal oxygen atoms and ions for texturing tips of polymeric optical fibers or other polymeric optical components for use in optical measurement of concentration of glucose in blood. The required texture of the sensory surface of such a component amounts to a landscape of microscopic hills having high aspect ratios (hills taller than they are wide), with an average distance between hills of no more than about 5 m. This limit on the average distance between hills is chosen so that blood cells (which are wider) cannot enter the valleys between the hills, where they could obstruct optical sensing of glucose in the blood plasma. On the other hand, the plasma is required to enter the valleys, and a high aspect ratio is intended to maximize the hillside and valley surface area in contact with the plasma, thereby making it possible to obtain a given level of optical glucose- measurement sensitivity with a relatively small volume of blood. The present method of texturing by use of directed, hyperthermal (particle energy >1 eV) oxygen atoms and ions stands in contrast to a prior method of texturing by use of thermal monatomic oxygen characterized by a temperature of the order of 0.5 eV. The prior method yields low-aspect- ratio (approximately hemispherical) craters that are tens of microns wide . too wide to exclude blood cells. The figure schematically depicts parts of a typical apparatus for texturing according to the present method. One or more polymeric optical components to be textured (e.g., multiple optical fibers bundled together for simultaneous processing) are mounted in a vacuum chamber facing a suitable ion- or atom-accelerating device capable of generating a beam of oxygen atoms and/or ions having kinetic energies >1 eV. Typically, such a device includes a heated cathode, in which case it is desirable to interpose a water-cooled thermal-radiation shield to prevent melting of the polymeric component(s) to be textured. In operation, the chamber is evacuated to a pressure .10.5 torr (less than or equal to approximately 1.3 mPa), then the beam is turned on. The resulting texture is characterized by approximately conical hills having aspect ratios greater than 1. In experiments, it was demonstrated that separations between adjacent hills can be made .1 m and that the separations and heights of the hills can be varied by varying the fluence of monatomic oxygen and/or oxygen ions.

Banks, Bruce↗
NASA NTRSDate not supplied

A Transmission Electron Microscopy Study of a Refractory Metal Grain from a Calcium-Aluminum-Rich Inclusion in the Leoville CV3 Chondrite

Introduction: Calcium-aluminum-rich inclusions (CAIs) are an important component of chondritic meteorites. They can contain materials that are thermodynamically predicted and isotopically age dated to be among the first-formed solids in our solar system [1-5]. Observed in some CAIs are micron to sub-micron sized inclusions rich in Fe, Ni, and high-Z elements such as Pt, Os, Ir and W, in the form of refractory metal nuggets (RMNs), fremdlinges, and ‘nugget like objects’ (NLOs) [1,6]. Refractory siderophile elements such as Os, Ir and Ru are thermodynamically predicted to condense at temperatures well in excess of the major CAI phases such as melilite, perovskite, spinel and hibonite [2,7-9]. These refractory metal inclusions in CAIs can therefore serve as probes into the thermodynamic landscape of the early solar protoplanetary disk. Here we report on a refractory grain identified in a CAI of the Leoville CV3 chondrite. This work is part of an ongoing effort to gain insight into the thermochemistry of the early solar system through systematic analyses of the structure and chemistry of various components in CAIs [10-13]. Sample and Analytical Techniques: A fluffy type A CAI (Fig. 1A) was identified in a section of the Leoville, CV3 chondrite (Center for Meteorite Studies, Arizona State University collection, #821_C_3) using a JOEL-JXA 8530F electron microprobe at Arizona State University. Backscattered electron (BSE) imaging and energy-dispersive X-ray spectroscopy (EDS) were used to identify refractory metal grains in the CAI using a Thermo Fisher (formerly FEI) Helios NanoLab 660 G3 focused-ion-beam scanning-electron microscope (FIBSEM) located at the Kuiper Materials Imaging and Characterization Facility (KMICF) at the Lunar and Planetary Laboratory, University of Arizona. The FIB is equipped with an EDAX EDS system. We selected one of the larger (micron-sized) refractory metal grains, designated as ‘Spud’ (Fig. 1B) for further analysis. ‘Spud’ was extracted and thinned to electron transparency (<100 nm) using the FIB-SEM located in KMICF, following methods described by [14- 15]. The FIB section was analyzed using a 200 keV Hitachi HF5000 scanning transmission electron microscope (S/TEM) located at KMICF. The HF5000 is equipped with cold-field emission gun, 3rd-order spherical aberration corrector for STEM imaging, and an Oxford Instruments X-Max N 100 TLE energydispersive spectroscopy (EDS) system with dual 100 mm2 windowless silicon-drift detectors (Ω = 2.0 sr). Selected-area electron-diffraction (SAED) patterns were acquired to aid in determination of crystallinity and phase. Results: The mineralogy, texture, and morphology of the CAI are consistent with that of a fluffy type A (FTA) CAI [16]. BSE imaging at high magnifications revealed grains with high contrast, indicative of compositions rich in elements of higher atomic number relative to surrounding material. These high-Z grains have sizes that range from ∼250 nm to 4 µm. EDS analyses confirm that the bright grains are metal-rich inclusions. A minor fraction of the grains are composed of only Fe and Ni, but the majority (∼60%) of the identified inclusions also contained various refractory siderophiles including Os, Ru, Zr, Ir and Mo. EDS analysis on the FIB-SEM of Spud shows that it contains Fe, Ni, Mo and Ru. High-angle annular dark-field (HAAFD) imaging and EDS mapping in the TEM (Fig. 2) show that Spud occurs in melilite (Ca1.9Al1.99Si1.06O7). Spud contains a subhedral to anhedral morphology and is compositionally heterogenous (polyphasic, Fig. 2). Local spatial correlation occurs among Fe, Ni, and Pt, and also among Os, Ru, and Mo. SAED patterns show that the Fe-Ni-Pt, Fe-Os-Mo-Ru and Fe-Pt regions are crystalline. Discussion: CAIs can contain various types of inclusions rich in Fe, Ni and refractory siderophiles such as Os, Ru, W and Pt [1]. RMNs are micron-sized, single phase alloy grains and can contain Os, Ir, Ru and Rh [1,7,17]. NLOs are also micron-sized inclusions, but contain two phases, a refractory metal, and an oxide [6]. Fremdlinge are the largest of such inclusions (tens of microns in size) and are complex aggregates of Fe-Ni alloy, silicates, oxides, and sulfides [1,17]. While the size of Spud matches previous descriptions of RMNs and NLOs, Spud is neither a single-phase alloy like RMNs, nor does it contain one metal phase and one oxide like NLOs. Spud does not match the above described categories of refractory metal inclusions. The presence of refractory siderophiles such as Mo, Os, Ru, and Pt suggests a high-temperature origin. Thermodynamic modelling by [7] indicates condensation temperatures of 1917 K, 1693 K, 1613 K and 1415 K for Os, Mo, Ru and Pt respectively. These models also show that following the initial condensation of a refractory metal, alloying of solutes such as Fe, Ni and W, occurs in levels proportional to their partial pressures in the surrounding gas. Such alloying occurs at temperatures above the condensation temperatures of common CAI phases such as melilite (1529 K), perovskite (1441 K), spinel (197 K) and forsterite (1354 K) [2]. The polyphasic nature of Spud could be the result of such high-temperature alloying, possibly shortly after the condensation of Mo and Ru at 1693 K and 1613 K respectively. That Spud occurs as an inclusion is consistent with it having formed prior to and at temperature above that of its host melilite in this FTA CAI, which is qualitatively consistent with such prior thermodynamic modeling. Further, the polyphasic nature of Spud is similar to refractory grains from a FTA CAI in the Northwest Africa (NWA) 8323, CV3 chondrite [11-13]. These data suggest that such refractory metal grains could have been widespread in the inner and early solar protoplanetary disk and represent some of the earliest formed solids to have condensed. Acknowledgments: Research and instrumentation supported by NASA grants #NNX12AL47G, #NNX15AJ22G and #80NSSC19K0509, and NSF grants #1531243 and #0619599. Fig 2. STEM data on ‘Spud’. HAADF Image (Top) False-color EDS Maps (Bottom) References: [1] MacPherson G. J. (2014) T. of Geochem. Vol I: Met. And Cosmochem. Processes, 139-179. [2] Lodders K. (2003) ApJ, 591, 1220-1247. [3] Ebel D. S. (2006) Met. & the Early S. Sys. II., 253- 277. [4] Amelin Y. (2002) Science, 297, 1678-1683. [5] Connelly J.N. et.al. (2012) Science, 338, 651-655. [6] Schwander D. et al. (2015) GCA, 18, 70-87. [7] Palme H. and Wlotzka F. (1976) EPSL, 33, 45-60. [8] Berg T. et al. (2009) ApJ, 702, 172-176. [9] Liffman K. et al. (2021) Icarus, 221, 89-105. [10] Zega T.J. et al. (2021) PSJ, 2, 115. [11] Ramprasad T. et al. (2020) LPSC LI, Abstract #2472. [12] Ramprasad T. et al. (2021) Microscopy & Microanalysis, S1, 2792-2794. [13] Ramprasad T. et al. (2021) 84th MetSoc, Abstract #6123. [14] Zega T.J. et al. (2007) MAPS, 42, 1373-1386. [15] Ramprasad T. et al. (2022) MAPS, in revision. [16] Grossman L. (1975), GCA, 39, 433-454. [17] El Goresy A. et al. (1978) LPSC IX, Abstract#1100

T. Ramprasad↗
DOE OSTI2018

Thermal hysteresis of the Campbell response as a probe for bulk pinning landscape spectroscopy

In type-II superconductors, the macroscopic response of vortex matter to an external perturbation depends on the local interaction of flux lines with the pinning landscape (pinscape). The (Campbell) penetration depth λ C of an ac field perturbation is often associated with a phenomenological pinning curvature. However, this basic approach is unable to capture thermal hysteresis effects observed in a variety of superconductors. The recently developed framework of strong-pinning theory has established a quantitative relationship between the microscopic pinscape and macroscopic observables. Specifically, it identifies history-dependent vortex arrangements as the primary source for thermal hysteresis in the Campbell response. In this work, we show that this interpretation is well-suited to capture the experimental results of the clean superconductor NbSe 2 , as observed through Campbell response (linear ac susceptibility) and small-angle neutron scattering measurements. Furthermore, we exploit the hysteretic Campbell response upon thermal cycling to extract the temperature dependence of microscopic pinning parameters from bulk measurements, specifically the pinning force and pinning length. Finally, this spectroscopic tool may stimulate further pinscape characterization in other superconducting systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Coherent diffractive imaging with twisted X-rays: Principles, applications, and outlook

Recent technological breakthroughs in synchrotron and x-ray free electron laser facilities have revolutionized nanoscale structural and dynamic analyses in condensed matter systems. This review provides a comprehensive overview of the advancements in coherent scattering and diffractive imaging techniques, which are now at the forefront of exploring materials science complexities. These techniques, notably Bragg coherent diffractive imaging and x-ray photon correlation spectroscopy, x-ray magnetic dichroism, and x-ray correlation analysis leverage beam coherence to achieve volumetric three-dimensional imaging at unprecedented sub-nanometer resolutions and explore dynamic phenomena within sub-millisecond timeframes. Such capabilities are critical in understanding and developing advanced materials and technologies. Simultaneously, the emergence of chiral crystals—characterized by their unique absence of standard inversion, mirror, or other roto-inversion symmetries—presents both challenges and opportunities. These materials exhibit distinctive interactions with light, leading to phenomena such as molecular optical activity, chiral photonic waveguides, and valley-specific light emissions, which are pivotal in the burgeoning fields of photonic and spintronic devices. This review elucidates how novel x-ray probes can be leveraged to unravel these properties and their implications for future technological applications. A significant focus of this review is the exploration of new avenues in research, particularly the shift from conventional methods to more innovative approaches in studying these chiral materials. Inspired by structured optical beams, the potential of coherent scattering techniques utilizing twisted x-ray beams is examined. This promising direction not only offers higher spatial resolution but also opens the door to previously unattainable insights in materials science. By contextualizing these advancements within the broader scientific landscape and highlighting their practical applications, this review aims to chart a course for future research in this rapidly evolving field.

Physics↗
DOE OSTI2023

Investigating permafrost carbon dynamics in Alaska with artificial intelligence

Abstract Positive feedbacks between permafrost degradation and the release of soil carbon into the atmosphere impact land–atmosphere interactions, disrupt the global carbon cycle, and accelerate climate change. The widespread distribution of thawing permafrost is causing a cascade of geophysical and biochemical disturbances with global impacts. Currently, few earth system models account for permafrost carbon feedback (PCF) mechanisms. This research study integrates artificial intelligence (AI) tools and information derived from field-scale surveys across the tundra and boreal landscapes in Alaska. We identify and interpret the permafrost carbon cycling links and feedback sensitivities with GeoCryoAI, a hybridized multimodal deep learning (DL) architecture of stacked convolutionally layered, memory-encoded recurrent neural networks (NN). This framework integratesin-situmeasurements and flux tower observations for teacher forcing and model training. Preliminary experiments to quantify, validate, and forecast permafrost degradation and carbon efflux across Alaska demonstrate the fidelity of this data-driven architecture. More specifically, GeoCryoAI logs the ecological memory and effectively learns covariate dynamics while demonstrating an aptitude to simulate and forecast PCF dynamics—active layer thickness (ALT), carbon dioxide flux (CO 2 ), and methane flux (CH 4 )—with high precision and minimal loss (i.e. ALT RMSE : 1.327 cm [1969–2022]; CO 2 RMSE : 0.697µmolCO 2 m −2 s −1 [2003–2021]; CH 4 RMSE : 0.715 nmolCH 4 m −2 s −1 [2011–2022]). ALT variability is a sensitive harbinger of change, a unique signal characterizing the PCF, and our model is the first characterization of these dynamics across space and time.

Environmental Sciences & Ecology↗
DOE OSTI2024

Controls on Stable Methane Isotope Values in Northern Peatlands and Potential Shifts in Values Under Permafrost Thaw Scenarios

Abstract Northern peatlands are a globally significant source of methane (CH 4 ), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH 4 production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ 13 C‐CH 4 ) being a powerful tool for characterizing these drivers. Given that δ 13 C‐CH 4 is used in top‐down atmospheric inversion models to partition sources, our ability to model CH 4 production pathways and associated δ 13 C‐CH 4 values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ 13 C‐CH 4 values from high‐latitude peatlands. We measured porewater and emitted CH 4 stable isotopes, pH, and vegetation composition from five boreal‐Arctic peatlands. Porewater δ 13 C‐CH 4 was strongly associated with peatland type, with δ 13 C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost‐free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ 13 C‐CH 4 was best explained by sedge cover, CH 4 concentration, and the interactive effect of peatland type and pH (r 2 = 0.50,p < 0.001). Emitted δ 13 C‐CH 4 varied greatly but was positively correlated with porewater δ 13 C‐CH 4 . We calculated a mixed atmospheric δ 13 C‐CH 4 value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ 13 C‐CH 4 values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models.

Environmental Sciences & Ecology↗
DOE OSTI2023

Comprehensive Genetic Characterization of Four Novel HIV-1 Circulating Recombinant Forms (CRF129_56G, CRF130_A1B, CRF131_A1B, and CRF138_cpx): Insights from Molecular Epidemiology in Cyprus

Molecular investigations of the HIV-1 pol region (2253–5250 in the HXB2 genome) were conducted on sequences obtained from 331 individuals infected with HIV-1 in Cyprus between 2017 and 2021. This study unveiled four distinct HIV-1 putative transmission clusters, encompassing 19 previously unidentified HIV-1 recombinants. These recombinants, each comprising eight, three, four, and four sequences, respectively, did not align with previously established Circulating Recombinant Forms (CRFs). To characterize these novel HIV-1 recombinants, near-full-length genome sequences were successfully obtained for 16 of the 19 recombinants (790–8795 in the HXB2 genome) using an in-house-developed RT-PCR assay. Phylogenetic analyses, employing MEGAX and Cluster-Picker, along with confirmatory neighbor-joining tree analyses of subregions, were conducted to identify distinct clusters and determine subtypes. The uniqueness of the HIV-1 recombinants was evident in their exclusive clustering within generated maximum likelihood trees. Recombination analyses highlighted the distinct chimeric nature of these recombinants, with consistent mosaic patterns observed across all sequences within each of the four putative transmission clusters. Conclusive genetic characterization identified four novel HIV-1 CRFs: CRF129_56G, CRF130_A1B, CRF131_A1B, and CRF138_cpx. CRF129_56G exhibited two recombination breakpoints and three fragments of subtypes CRF56_cpx and G. Both CRF130_A1B and CRF131_A1B featured seven recombination breakpoints and eight fragments of subtypes A1 and B. CRF138_cpx displayed five recombination breakpoints and six fragments of subtypes CRF22_01A1 and F2, along with an unclassified fragment. Additional BLAST analyses identified a Unique Recombinant Form (URF) of CRF138_cpx with three additional recombination sites, involving subtype F2, a fragment of unknown subtype origin, and CRF138_cpx. Post-identification, all putative transmission clusters remained active, with CRF130_A1B, CRF131_A1B, and CRF138_cpx clusters exhibiting further growth. Furthermore, international connections were identified through BLAST analyses, linking one sequence from the USA to the CRF130_A1B strain, and three sequences from Belgium and Cameroon to the CRF138_cpx strain. This study contributes valuable insights into the dynamic landscape of HIV-1 diversity and transmission patterns, emphasizing the need for ongoing molecular surveillance and global collaboration in tracking emerging viral variants.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

A spatially distributed model for the assessment of land use impacts on stream temperature in small urban watersheds

Stream temperatures in urban watersheds are influenced to a high degree by anthropogenic impacts related to changes in landscape, stream channel morphology, and climate. These impacts can occur at small time and length scales, hence require analytical tools that consider the influence of the hydrologic regime, energy fluxes, topography, channel morphology, and near-stream vegetation distribution. Here we describe a modeling system that integrates the Distributed Hydrologic Soil Vegetation Model, DHSVM, with the semi-Lagrangian stream temperature model RBM, which has the capability to simulate the hydrology and water temperature of urban streams at high time and space resolutions, as well as a representation of the effects of riparian shading on stream energetics. We demonstrate the modeling system through application to the Mercer Creek watershed, a small urban catchment near Bellevue, Washington. The results suggest that the model is able both to produce realistic streamflow predictions at fine temporal and spatial scales, and to provide spatially distributed water temperature predictions that are consistent with observations throughout a complex stream network. We use the modeling construct to characterize impacts of land use change and near-stream vegetation change on stream temperature throughout the Mercer Creek system. We then explore the sensitivity of stream temperature to land use changes and modifications in vegetation along the riparian corridor.

climate change↗
DOE OSTI2024

Role of CeNiSi 2 and BaNiSn 3 Structure Types in the Emergent Magnetism of the Homologous Series Ln n +1 M n X 3 n +1 :Ce 4 Fe 3 Ge 10

The synthesis and characterization of Ce 4 Fe 3 Ge 10 , n =3 member of the homologous series Ln n+1 M n X 3n+1 (Ln = lanthanides, M = transition metal, X = tetrel), is reported. The structure can be modelled with the Cmcm space group adopting the Eu 2 Ni 2-x Sn 5 structure type, with lattice parameters of a = 4.3323 (15) Å, b = 35.507 (9) Å, and c = 4.3069 (12) Å. Members of the series for n > 2 consist of stacking of ordered (CeNiSi 2 type) and disordered (BaNiSn 3 / AuCu 3 type) subunits with the acting as a “spacer” between CeNiSi 2 subunits. Although neither CeFeGe 3 nor CeFe 0.63 Ge 2 order magnetically down to 2 K, Ce 4 Fe 3 Ge 10 is an antiferromagnet below 3.6 K. To rationalize the emergent magnetism: (i) we established the Kondo and RKKY interaction dominant regions for the Ce analogues adopting the BaNiSn 3 and CeNiSi 2 by creating an electronic landscape for each, (ii) mapped the strained subunits, due to stacking, within the series. Here, we established the CeFeGe 3 subunit within Ce 4 Fe 3 Ge 10 contracts and is located within the Kondo-interaction dominant region, while the CeFe 0.63 Ge 2 subunit expands and is in the RKKY-interaction dominant region.

36 MATERIALS SCIENCE↗
DOE OSTI2021

An Indicator-based Approach to Sustainable Management of Natural Resources (Chapter 12)

Assessing the sustainability of natural resource management choices for agricultural and forest lands requires quantification of potential changes to a set of environmental and socioeconomic indicators selected to characterize reference scenarios relative to projected future scenarios. Correctly framing the questions with local stakeholders is a critical first step in the sustainability assessment, and the questions that can be addressed are often limited by data availability. Selecting and prioritizing indicators with stakeholders to address their needs and concerns improves the likelihood of investment in monitoring and evaluation of those indicators over time. Computational techniques for analyzing interactions between the selected indicators are inherently affected by the scales and formats of the assembled indicator datasets. Data analytics have the potential to improve understanding of the potential synergies and tradeoffs involved with meeting multiple environmental and socioeconomic goals simultaneously, but timely and appropriate indicator datasets are not always available—even in this new era of “big data.” Continued improvements in data science and data analytics are needed to broaden understanding and acceptance of problems and to provide valuable information for natural resource management. Advances in these areas will enable society to design future landscapes that meet multiple objectives, including the provisioning of agricultural and forest resources along with a variety of ecosystem services (e.g., clean water and healthy soils).

Parish, Esther↗
DOE OSTI2023

The underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems in the Northern and Eastern United States

Spring phenology of temperate ecosystems is highly sensitive to climate change, generating various impacts on many important terrestrial surface biophysical processes. Although various prognostic models relying on environmental variables of temperature and photoperiod have been developed for spring phenology, comprehensive ecosystem-scale evaluations over large landscapes and long-time periods remain lacking. Further, environmental variables other than temperature and photoperiod might also importantly constrain spring phenology modelling but remain under-investigation. To address these issues, we leveraged around 20-years datasets of environmental variables (from Daymet and GLDAS products) and the spring phenology metric (i.e., the greenup date) respectively derived from MODIS and PhenoCams across 108 sites in the Northern and Eastern United States. We firstly cross-compared MODIS-derived greenup date with official PhenoCams product with high accuracy (R 2 = 0.70). Then, we evaluated the three prognostic models (i.e., Growing Degree Date (GDD), Sequential (SEQ) and optimality-based (OPT)) with MODIS-derived spring phenology, assessed the model residuals and their associations with soil moisture, rainfall, and solar radiation, and revised the two photoperiod-relevant models (SEQ, OPT) by replacing the daylength variable with solar radiation, which was found to contribute the most to model residuals. We found that 1) all models demonstrated good capability in characterizing spring phenology, with OPT performing the best (RMSE = 8.04 ± 5.05 days), followed by SEQ (RMSE = 10.57 ± 7.77 days) and GDD (RMSE = 10.84 ± 8.42 days), 2) all models displayed high model residuals showing tight correlation with solar radiation (r = 0.45–0.75), and 3) the revised models that included solar radiation significantly performed better with an RMSE reduction by 22.08%. Such results are likely because solar radiation better constrains early growing season plant photosynthesis than photoperiod, supporting the hypothesis of spring phenology as an adaptive strategy to maximize photosynthetic carbon gain (approximated by solar radiation) while minimizing frost damage risk (captured by temperature). Collectively, our study here reveals the underappreciated importance of solar radiation in constraining spring phenology of temperate ecosystems, and suggests ways to improve spring phenology modelling and other phenology-related ecological processes.

54 ENVIRONMENTAL SCIENCES↗