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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.

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At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Stream Classification Tool User Manual: For Use in Applications in Hydropower-Related Evironmental Mitigation

Stream classifications are an inventory of different types of streams. Classifications help us explore similarities and differences among different types of streams, make inferences regarding stream ecosystem behavior, and communicate the complexities of ecosystems. We developed a nested, layered, and spatially contiguous stream classification to characterize the biophysical settings of stream reaches within the Eastern United States (~ 900,000 reaches). The classification is composed of five natural characteristics (hydrology, temperature, size, confinement, and substrate) along with several disturbance regime layers, and each was selected because of their relevance to hydropower mitigation. We developed the classification at the stream reach level using the National Hydrography Dataset Plus Version 1 (1:100k scale). The stream classification is useful to environmental mitigation for hydropower dams in multiple ways. First, it creates efficiency in the regulatory process by creating an objective and data-rich means to address meaningful mitigation actions. Secondly, the SCT addresses data gaps as it quickly provides an inventory of hydrology, temperature, morphology, and ecological communities for the immediate project area, but also surrounding streams. This includes identifying potential reference streams as those that are proximate to the hydropower facility and fall within the same class. These streams can potentially be used to identify ideal environmental conditions or identify desired ecological communities. In doing so, the stream provides some context for how streams may function, respond to dam regulation, and an overview of specific mitigation needs. Herein, we describe the methodology in developing each stream classification layer and provide a tutorial to guide applications of the classification (and associated data) in regulatory settings, such as hydropower (re)licensing.

13 HYDRO ENERGY↗
DOE OSTI2018

The Electron-Conformational Model of Ryanodine Receptors of the Heart Cell

The main ideas of an electron-conformational (EC) model of ligand-activated ryanodine channels (RyR) that reduces many degrees of freedom of this gigantic nanoscopic molecular complex to two so-called electron and conformational degrees of freedom are presented. In the toy model, the conformational potential or energy profile of the RyR channel represents two branches that describe the dependence of energy on the conformational coordinate (reaction coordinate) in the initial and ligand-activated states, respectively. A model extension that takes into account both the tetrameric structure of the RyR channel and additional (orthogonal) rotational conformational mode has been considered. The EC model has been demonstrated to give a biophysical basis to the traditional phenomenological model of Markov chains. To demonstrate the possibilities of the EC model, we refer to examples of model description of the dynamics of isolated RyR channels and clusters of RyR channels in release units of the heart cell.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Secondary PDZ domain-binding site on class B plexins enhances the affinity for PDZ–RhoGEF

PDZ domains are abundant protein interaction modules and typically recognize a short motif at the C terminus of their ligands, with a few residues in the motif endowing the binding specificity. The sequence-based rules, however, cannot fully account for the specificity between the vast number of PDZ domains and ligands in the cell. Plexins are transmembrane receptors that regulate processes such as axon guidance and angiogenesis. Two related guanine nucleotide exchange factors (GEFs), PDZ–RhoGEF and leukemia-associated RhoGEF (LARG), use their PDZ domains to bind class B plexins and play critical roles in signaling. Here, we present the crystal structure of the full-length cytoplasmic region of PlexinB2 in complex with the PDZ domain of PDZ–RhoGEF. The structure reveals that, in addition to the canonical C-terminal motif/PDZ interaction, the 3D domain of PlexinB2 forms a secondary interface with the PDZ domain. Our biophysical and cell-based assays show that the secondary interface contributes to the specific interaction between plexin and PDZ–RhoGEF and to signaling by plexin in the cell. As a result, formation of secondary interfaces may be a general mechanism for increasing affinity and specificity of modular domain-mediated interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2014

Ferrous iron formation following the co-aggregation of ferric iron and the Alzheimer's disease peptide β-amyloid (1–42)

For decades, a link between increased levels of iron and areas of Alzheimer’s disease (AD) pathology has been recognized, including AD lesions comprised of the peptide b-amyloid (Ab). Despite many observations of this association, the relationship between Ab and iron is poorly understood. Using X-ray microspectroscopy, X-ray absorption spectroscopy, electron microscopy and spectrophotometric iron(II) quantification techniques, we examine the interaction between Ab(1–42) and synthetic iron(III), reminiscent of ferric iron stores in the brain. We report Ab to be capable of accumulating iron(III) within amyloid aggregates, with this process resulting in Ab-mediated reduction of iron(III) to a redox-active iron(II) phase. Additionally, we show that the presence of aluminium increases the reductive capacity of Ab, enabling the redox cycling of the iron. These results demonstrate the ability of Ab to accumulate iron, offering an explanation for previously observed local increases in iron concentration associated with AD lesions. Furthermore, the ability of iron to form redox-active iron phases from ferric precursors provides an origin both for the redox-active iron previously witnessed in AD tissue, and the increased levels of oxidative stress characteristic of AD. These interactions between Ab and iron deliver valuable insights into the process of AD progression, which may ultimately provide targets for disease therapies.

redox↗
DOE OSTI2016

The Tp0684 (MglB-2) Lipoprotein of Treponema pallidum : A Glucose-Binding Protein with Divergent Topology

Treponema pallidum , the bacterium that causes syphilis, is an obligate human parasite. As such, it must acquire energy, in the form of carbon sources, from the host. There is ample evidence that the principal source of energy for this spirochete is D-glucose acquired from its environment, likely via an ABC transporter. Further, there is genetic evidence of a D-glucose chemotaxis system in T. pallidum . Both of these processes may be dependent on a single lipidated chemoreceptor: Tp0684, also called TpMglB-2 for its sequence homology to MglB of Escherichia coli . To broaden our understanding of this potentially vital protein, we determined a 2.05-Å X-ray crystal structure of a soluble form of the recombinant protein. Like its namesake, TpMglB-2 adopts a bilobed fold that is similar to that of the ligand-binding proteins (LBPs) of other ABC transporters. However, the protein has an unusual, circularly permuted topology. This feature prompted a series of biophysical studies that examined whether the protein’s topological distinctiveness affected its putative chemoreceptor functions. Differential scanning fluorimetry and isothermal titration calorimetry were used to confirm that the protein bound D-glucose in a cleft between its two lobes. Additionally, analytical ultracentrifugation was employed to reveal that D-glucose binding is accompanied by a significant conformational change. TpMglB-2 thus appears to be fully functional in vitro, and given the probable central importance of the protein to T. pallidum’s physiology, our results have implications for the viability and pathogenicity of this obligate human pathogen.

Science & Technology - Other Topics↗
DOE OSTI2018

Soil properties and sediment accretion modulate methane fluxes from restored wetlands

Wetlands are the largest source of methane (CH 4 ) globally, yet our understanding of how process-level controls scale to ecosystem fluxes remains limited. It is particularly uncertain how variable soil properties influence ecosystem CH 4 emissions on annual time scales. Here. we measured ecosystem carbon dioxide (CO 2 ) and CH 4 fluxes by eddy covariance from two wetlands recently restored on peat and alluvium soils within the Sacramento–San Joaquin Delta of California. Annual CH 4 fluxes from the alluvium wetland were significantly lower than the peat site for multiple years following restoration, but these differences were not explained by variation in dominant climate drivers or productivity across wetlands. Soil iron (Fe) concentrations were significantly higher in alluvium soils, and alluvium CH 4 fluxes were decoupled from plant processes compared with the peat site, as expected when Fe reduction inhibits CH 4 production in the rhizosphere. Soil carbon content and CO 2 uptake rates did not vary across wetlands and, thus, could also be ruled out as drivers of initial CH 4 flux differences. Differences in wetland CH 4 fluxes across soil types were transient; alluvium wetland fluxes were similar to peat wetland fluxes 3 years after restoration. Changing alluvium CH 4 emissions with time could not be explained by an empirical model based on dominant CH 4 flux biophysical drivers, suggesting that other factors, not measured by our eddy covariance towers, were responsible for these changes. Recently accreted alluvium soils were less acidic and contained more reduced Fe compared with the pre-restoration parent soils, suggesting that CH 4 emissions increased as conditions became more favorable to methanogenesis within wetland sediments. This study suggests that alluvium soil properties, likely Fe content, are capable of inhibiting ecosystem-scale wetland CH 4 flux, but these effects appear to be transient without continued input of alluvium to wetland sediments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Estimating CO 2 fluxes through integrating spatial and temporal input layers via deep learning algorithms

Background Accurate estimation of net ecosystem exchange of CO 2 fluxes (Fc) is essential for understanding carbon cycle processes and assessing ecosystem carbon budgets. However, conventional modeling approaches often emphasize temporal dynamics while overlooking the pronounced spatial heterogeneity within the footprint of eddy covariance (EC) towers, potentially limiting predictive accuracy and interpretability of Fc estimates. To address this challenge, we developed a spatiotemporal model that integrates high-resolution footprint-weighted spatial information with sequential environmental drivers. Results The integrated model combines a deeper graph convolutional network to characterize fine-scale spatial variability within EC footprints and a gated recurrent unit network to capture temporal dependencies in biophysical conditions. Using multi-year flux tower observations, remote sensing vegetation indices and footprint modeling, we evaluate the proposed method across three land cover types. This spatiotemporal model consistently outperforms temporal-only and spatial-only baselines, achieving the highest overall accuracy (R 2 = 0.9569) and the lowest RMSE (1.8128 μmol m −2 s −1 ) and MAE (1.1939 μmol m −2 s −1 ). Performance gains are particularly evident in ecosystems with strong vegetation heterogeneity, where spatial structure substantially modulates Fc variability. Conclusions This study demonstrates the importance of joint modeling spatial heterogeneity and temporal dynamics for improving Fc estimation and provides a robust method for advancing footprint-based Fc estimates across diverse ecosystems, supporting refined assessments of terrestrial carbon fluxes, and enhancing scientific foundations for carbon studies.

CO2 flux estimate↗
DOE OSTI2023

Energy dissipation efficiency in the CP43 assembly intermediate complex of photosystem II

Photosystem II in oxygenic organisms is a large membrane bound rapidly turning over pigment protein complex. During its biogenesis, multiple assembly intermediates are formed, including the CP43-preassembly complex (pCP43). Here, to understand the energy transfer dynamics in pCP43, we first engineered a His-tagged version of the CP43 in a CP47-less strain of the cyanobacterium Synechocystis 6803. Isolated pCP43 from this engineered strain was subjected to advanced spectroscopic analysis to evaluate its excitation energy dissipation characteristics. These included measurements of steady-state absorption and fluorescence emission spectra for which correlation was tested with Stepanov relation. Comparison of fluorescence excitation and absorptance spectra determined that efficiency of energy transfer from β-carotene to chlorophyll a is 39 %. Time-resolved fluorescence images of pCP43-bound Chl a were recorded on streak camera, and fluorescence decay dynamics were evaluated with global fitting. These demonstrated that the decay kinetics strongly depends on temperature and buffer used to disperse the protein sample and fluorescence decay lifetime was estimated in 3.2–5.7 ns time range, depending on conditions. The pCP43 complex was also investigated with femtosecond and nanosecond time-resolved absorption spectroscopy upon excitation of Chl a and β-carotene to reveal pathways of singlet excitation relaxation/decay, Chl a triplet dynamics and Chl a → β-carotene triplet state sensitization process. The latter demonstrated that Chl a triplet in the pCP43 complex is not efficiently quenched by carotenoids. Finally, detailed kinetic analysis of the rise of the population of β-carotene triplets determined that the time constant of the carotenoid triplet sensitization is 40 ns.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

CRISPR–Cas9 bends and twists DNA to read its sequence

In bacterial defense and genome editing applications, the CRISPR-associated protein Cas9 searches millions of DNA base pairs to locate a 20-nucleotide, guide RNA-complementary target sequence that abuts a protospacer-adjacent motif (PAM). Target capture requires Cas9 to unwind DNA at candidate sequences using an unknown ATP-independent mechanism. Here we show that Cas9 sharply bends and undertwists DNA on PAM binding, thereby flipping DNA nucleotides out of the duplex and toward the guide RNA for sequence interrogation. Cryogenic-electron microscopy (cryo-EM) structures of Cas9–RNA–DNA complexes trapped at different states of the interrogation pathway, together with solution conformational probing, reveal that global protein rearrangement accompanies formation of an unstacked DNA hinge. Bend-induced base flipping explains how Cas9 ‘reads’ snippets of DNA to locate target sites within a vast excess of nontarget DNA, a process crucial to both bacterial antiviral immunity and genome editing. This mechanism establishes a physical solution to the problem of complementarity-guided DNA search and shows how interrogation speed and local DNA geometry may influence genome editing efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

DeepDriveMD: Deep-Learning Driven Adaptive Molecular Simulations for Protein Folding

Simulations of biological macromolecules are important in understanding the physical basis of complex processes such as protein folding. However, even with increasing computational capacity and specialized architectures, the ability to simulate protein folding at atomistic scales still remains challenging. This stems from the dual aspects of high dimensionality of protein conformational landscapes, and the inability of atomistic molecular dynamics (MD) simulations to sufficiently sample these landscapes to observe folding events. Machine learning/deep learning (ML/DL) techniques, when combined with atomistic MD simulations offer the opportunity to potentially overcome these limitations by: (1) effectively reducing the dimensionality of MD simulations to automatically build latent representations that correspond to biophysically relevant reaction coordinates (RCs), and (2) driving MD simulations to automatically sample potentially novel conformational states based on these RCs. We examine how coupling DL approaches with MD simulations can lead to effective approaches to fold small proteins on supercomputers. In particular, we study the computational costs and effectiveness of scaling DL-coupled MD workflows implemented using RADICAL-Cybertools in folding two prototypical systems, namely Fs-peptide and the fast-folding variant of the villin head piece protein. We demonstrate that a DL-coupled MD workflow is able to effectively learn latent representations and drive adaptive simulations. Compared to traditional MD-based approaches, our approach achieves an effective performance gain in sampling the folded states by at least 2.3x. Together, our study provides quantitative basis to understand how coupling DL approaches to MD simulations, can lead to effective performance gains and reduced times to solution on supercomputing resources.

Lee, Hyungro↗
DOE OSTI2024

Personalized whole-brain neural mass models reveal combined Aβ and tau hyperexcitable influences in Alzheimer's disease.

Neuronal dysfunction and cognitive deterioration in Alzheimer's disease (AD) are likely caused by multiple pathophysiological factors. However, mechanistic evidence in humans remains scarce, requiring improved non-invasive techniques and integrative models. We introduce personalized AD computational models built on whole-brain Wilson-Cowan oscillators and incorporating resting-state functional MRI, amyloid-β (Aβ) and tau-PET from 132 individuals in the AD spectrum to evaluate the direct impact of toxic protein deposition on neuronal activity. This subject-specific approach uncovers key patho-mechanistic interactions, including synergistic Aβ and tau effects on cognitive impairment and neuronal excitability increases with disease progression. The data-derived neuronal excitability values strongly predict clinically relevant AD plasma biomarker concentrations (p-tau217, p-tau231, p-tau181, GFAP) and grey matter atrophy obtained through voxel-based morphometry. Furthermore, reconstructed EEG proxy quantities show the hallmark AD electrophysiological alterations (theta band activity enhancement and alpha reductions) which occur with Aβ-positivity and after limbic tau involvement. Microglial activation influences on neuronal activity are less definitive, potentially due to neuroimaging limitations in mapping neuroprotective vs detrimental activation phenotypes. Mechanistic brain activity models can further clarify intricate neurodegenerative processes and accelerate preventive/treatment interventions.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2012

Solution-phase photochemistry of a [FeFe]hydrogenase model compound: Evidence of photoinduced isomerisation

The solution-phase photochemistry of the [FeFe] hydrogenase subsite model ({mu}-S(CH{sub 2}){sub 3}S)Fe{sub 2}(CO){sub 4}(PMe{sub 3}){sub 2} has been studied using ultrafast time-resolved infrared spectroscopy supported by density functional theory calculations. In three different solvents, n-heptane, methanol, and acetonitrile, relaxation of the tricarbonyl intermediate formed by UV photolysis of a carbonyl ligand leads to geminate recombination with a bias towards a thermodynamically less stable isomeric form, suggesting that facile interconversion of the ligand groups at the Fe center is possible in the unsaturated species. In a polar or hydrogen bonding solvent, this process competes with solvent substitution leading to the formation of stable solvent adduct species. The data provide further insight into the effect of incorporating non-carbonyl ligands on the dynamics and photochemistry of hydrogenase-derived biomimetic compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Synchrotron based infrared imaging and spectroscopy via focal plane array on live fibroblasts in D2O enriched medium

We tested the viability of using synchrotron based infrared imaging to study biochemical processes inside living cells. As a model system, we studied fibroblast cells exposed to a medium highly enriched with D2O. We could show that the experimental technique allows us to reproduce at the cellular level measurements that are normally performed on purified biological molecules. We can obtain information about lipid conformation and distribution, kinetics of hydrogen/deuterium exchange, and the formation of concentration gradients of H and O isotopes in water that are associated with cell metabolism. The implementation of the full field technique in a sequential imaging format gives a description of cellular biochemistry and biophysics that contains both spatial and temporal information.

Cell Lipids↗
DOE OSTI2016

MO-AB-BRA-09: Development and Evaluation of a Biomechanical Modeling-Assisted CBCT Reconstruction Technique (Bio-Recon)

Purpose: To develop a Bio-recon technique by incorporating the biomechanical properties of anatomical structures into the deformation-based CBCT reconstruction process. Methods: Bio-recon reconstructs the CBCT by deforming a prior high-quality CT/CBCT using a deformation-vector-field (DVF). The DVF is solved through two alternating steps: 2D–3D deformation and finite-element-analysis based biomechanical modeling. 2D–3D deformation optimizes the DVF through an ‘intensity-driven’ approach, which updates the DVF to minimize intensity mismatches between the acquired projections and the simulated projections from the deformed CBCT. In contrast, biomechanical modeling optimizes the DVF through a ‘biomechanical-feature-driven’ approach, which updates the DVF based on the biophysical properties of anatomical structures. In general, Biorecon extracts the 2D–3D deformation-optimized DVF at high-contrast structure boundaries, and uses it as the boundary condition to drive biomechanical modeling to optimize the overall DVF, especially at low-contrast regions. The optimized DVF is fed back into the 2D–3D deformation for further optimization, which forms an iterative loop. The efficacy of Bio-recon was evaluated on 11 lung patient cases, each with a prior CT and a new CT. Cone-beam projections were generated from the new CTs to reconstruct CBCTs, which were compared with the original new CTs for evaluation. 872 anatomical landmarks were also manually identified by a clinician on both the prior and new CTs to track the lung motion, which was used to evaluate the DVF accuracy. Results: Using 10 projections for reconstruction, the average (± s.d.) relative errors of reconstructed CBCTs by the clinical FDK technique, the 2D–3D deformation-only technique and Bio-recon were 46.5±5.9%, 12.0±2.3% and 10.4±1.3%, respectively. The average residual errors of DVF-tracked landmark motion by the 2D–3D deformation-only technique and Bio-recon were 5.6±4.3mm and 3.1±2.4mm, respectively. Conclusion: Bio-recon improved accuracy for both the reconstructed CBCT and the DVF. The accurate DVF can benefit multiple clinical practices, such as image-guided adaptive radiotherapy. We acknowledge funding support from the American Cancer Society (RSG-13-326-01-CCE), from the US National Institutes of Health (R01 EB020366), and from the Cancer Prevention and Research Institute of Texas (RP130109).

60 APPLIED LIFE SCIENCES↗
NASA NTRS2011

Acute Radiation Risk and BRYNTRN Organ Dose Projection Graphical User Interface

The integration of human space applications risk projection models of organ dose and acute radiation risk has been a key problem. NASA has developed an organ dose projection model using the BRYNTRN with SUM DOSE computer codes, and a probabilistic model of Acute Radiation Risk (ARR). The codes BRYNTRN and SUM DOSE are a Baryon transport code and an output data processing code, respectively. The risk projection models of organ doses and ARR take the output from BRYNTRN as an input to their calculations. With a graphical user interface (GUI) to handle input and output for BRYNTRN, the response models can be connected easily and correctly to BRYNTRN. A GUI for the ARR and BRYNTRN Organ Dose (ARRBOD) projection code provides seamless integration of input and output manipulations, which are required for operations of the ARRBOD modules. The ARRBOD GUI is intended for mission planners, radiation shield designers, space operations in the mission operations directorate (MOD), and space biophysics researchers. BRYNTRN code operation requires extensive input preparation. Only a graphical user interface (GUI) can handle input and output for BRYNTRN to the response models easily and correctly. The purpose of the GUI development for ARRBOD is to provide seamless integration of input and output manipulations for the operations of projection modules (BRYNTRN, SLMDOSE, and the ARR probabilistic response model) in assessing the acute risk and the organ doses of significant Solar Particle Events (SPEs). The assessment of astronauts radiation risk from SPE is in support of mission design and operational planning to manage radiation risks in future space missions. The ARRBOD GUI can identify the proper shielding solutions using the gender-specific organ dose assessments in order to avoid ARR symptoms, and to stay within the current NASA short-term dose limits. The quantified evaluation of ARR severities based on any given shielding configuration and a specified EVA or other mission scenario can be made to guide alternative solutions for attaining determined objectives set by mission planners. The ARRBOD GUI estimates the whole-body effective dose, organ doses, and acute radiation sickness symptoms for astronauts, by which operational strategies and capabilities can be made for the protection of astronauts from SPEs in the planning of future lunar surface scenarios, exploration of near-Earth objects, and missions to Mars.

Cucinotta, Francis A.↗
DOE OSTI2019

Quantifying Shear-Induced Deformation and Detachment of Individual Adherent Sickle Red Blood Cells

According to the article, vaso-occlusive crisis, a common painful complication of sickle cell disease, is a complex process triggered by intercellular adhesive interactions among blood cells and the endothelium in all human organs (e.g., the oxygen-rich lung as well as hypoxic systems such as liver and kidneys). We present a combined experimental-computational study to quantify the adhesive characteristics of sickle mature erythrocytes (SMEs) and irreversibly sickled cells (ISCs) under flow conditions mimicking those in postcapillary venules. We employed an in vitro microfluidic cell adherence assay, which is coated uniformly with fibronectin. We investigated the adhesion dynamics of SMEs and ISCs in pulsatile flow under well-controlled hypoxic conditions, inferring the cell adhesion strength by increasing the flow rate (or wall shear stress (WSS)) until the onset of cell detachment. In parallel, we performed simulations of individual SMEs and ISCs under shear. We introduced two metrics to quantify the adhesion process, the cell aspect ratio (AR) as a function of WSS and its rate of change (the dynamic deformability index). We found that the AR of SMEs decreases significantly with the increase of WSS, consistent between the experiments and simulations. In contrast, the AR of ISCs remains constant in time and independent of the flow rate. The critical WSS value for detaching a single SME in oxygenated state is in the range of 3.9–5.5 Pa depending on the number of adhesion sites; the critical WSS value for ISCs is lower than that of SMEs. Our simulations show that the critical WSS value for SMEs in deoxygenated state is above 6.2 Pa (multiple adhesion sites), which is greater than their oxygenated counterparts. We investigated the effect of cell shear modulus on the detachment process; we found that for the same cell adhesion spring constant, the higher shear modulus leads to an earlier cell detachment from the functionalized surface. These findings may aid in the understanding of individual roles of sickle cell types in sickle cell disease vaso-occlusion.

Biophysics↗
DOE OSTI2012

Improved crystallographic models through iterated local density-guided model deformation and reciprocal-space refinement

A density-based procedure is described for improving a homology model that is locally accurate but differs globally. The model is deformed to match the map and refined, yielding an improved starting point for density modification and further model-building. An approach is presented for addressing the challenge of model rebuilding after molecular replacement in cases where the placed template is very different from the structure to be determined. The approach takes advantage of the observation that a template and target structure may have local structures that can be superimposed much more closely than can their complete structures. A density-guided procedure for deformation of a properly placed template is introduced. A shift in the coordinates of each residue in the structure is calculated based on optimizing the match of model density within a 6 Å radius of the center of that residue with a prime-and-switch electron-density map. The shifts are smoothed and applied to the atoms in each residue, leading to local deformation of the template that improves the match of map and model. The model is then refined to improve the geometry and the fit of model to the structure-factor data. A new map is then calculated and the process is repeated until convergence. The procedure can extend the routine applicability of automated molecular replacement, model building and refinement to search models with over 2 Å r.m.s.d. representing 65–100% of the structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Biophysical drivers of seasonal variability in Sphagnum gross primary production in a northern temperate bog

Sphagnum mosses are the keystone species of peatland ecosystems. With rapid rates of climate change occurring in high latitudes, vast reservoirs of carbon accumulated over millennia in peatland ecosystems are potentially vulnerable to rising temperature and changing precipitation. We investigate the seasonal drivers of Sphagnum gross primary production (GPP)—the entry point of carbon into wetland ecosystems. Continuous flux measurements and flux partitioning show a seasonal cycle of Sphagnum GPP that peaked in the late summer, well after the peak in photosynthetically active radiation. Wavelet analysis showed that water table height was the key driver of weekly variation in Sphagnum GPP in the early summer and that temperature was the primary driver of GPP in the late summer and autumn. Flux partitioning and a process-based model of Sphagnum photosynthesis demonstrated the likelihood of seasonally dynamic maximum rates of photosynthesis and a logistic relationship between the water table and photosynthesizing tissue area when the water table was at the Sphagnum surface. Here, the model also suggested that variability in internal resistance to CO 2 transport, a function of Sphagnum water content, had minimal effect on GPP. To accurately model Sphagnum GPP, we recommend the following: (1) understanding seasonal photosynthetic trait variation and its triggers in Sphagnum ; (2) characterizing the interaction of Sphagnum photosynthesizing tissue area with water table height; (3) modeling Sphagnum as a “soil” layer for consistent simulation of water dynamics; and (4) measurement of Sphagnum “canopy” properties: extinction coefficient (k), clumping (Ω), and maximum stem area index (SAI).

54 ENVIRONMENTAL SCIENCES↗