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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro

As temperatures decrease in autumn, vegetation of temperate and boreal ecosystems increases its tolerance to freezing. This process, known as hardening, results in a set of physiological changes at the molecular level that initiate modifications of cell membrane composition and the synthesis of anti-freeze proteins. Together with the freezing of extracellular water, anti-freeze proteins reduce plant water potentials and xylem conductivity. To represent the responses of vegetation to climate change, land surface schemes increasingly employ “hydrodynamic” models that represent the explicit fluxes of water from soil and through plants. The functioning of such schemes under frozen soil conditions, however, is poorly understood. Nonetheless, hydraulic processes are of major importance in the dynamics of these systems, which can suffer from, e.g., winter “frost drought” events. In this study, we implement a scheme that represents hardening into CLM5.0-FATES-Hydro. FATES-Hydro is a plant hydrodynamics module in FATES, a cohort model of vegetation physiology, growth, and dynamics hosted in CLM5.0. We find that, in frozen systems, it is necessary to introduce reductions in plant water loss associated with hardening to prevent winter desiccation. This work makes it possible to use CLM5.0-FATES-Hydro to model realistic impacts from frost droughts on vegetation growth and photosynthesis, leading to more reliable projections of how northern ecosystems respond to climate change.

58 GEOSCIENCES↗
DOE OSTI2021

Anthropogenic Perturbations to the Atmospheric Molybdenum Cycle

Abstract Molybdenum (Mo) is a key cofactor in enzymes used for nitrogen (N) fixation and nitrate reduction, and the low availability of Mo can constrain N inputs, affecting ecosystem productivity. Natural atmospheric Mo aerosolization and deposition from sources such as desert dust, sea‐salt spray, and volcanoes can affect ecosystem function across long timescales, but anthropogenic activities such as combustion, motor vehicles, and agricultural dust have accelerated the natural Mo cycle. Here we combined a synthesis of global atmospheric concentration observations and modeling to identify and estimate anthropogenic sources of atmospheric Mo. To project the impact of atmospheric Mo on terrestrial ecosystems, we synthesized soil Mo data and estimated the global distribution of soil Mo using two approaches to calculate turnover times. We estimated global emissions of atmospheric Mo in aerosols (<10 μm in diameter) to be 23 Gg Mo yr −1 , with 40%–75% from anthropogenic sources. We approximated that for the top meter of soil, Mo turnover times range between 1,000 and 1,000,000 years. In some industrialized regions, anthropogenic inputs have enhanced Mo deposition 100‐fold, lowering the soil Mo turnover time considerably. Our synthesis of global observational data, modeling, and a mass balance comparison with riverine Mo exports suggest that anthropogenic activity has greatly accelerated the Mo cycle, with potential to influence N‐limited ecosystems.

Wong, Michelle Y.↗
DOE OSTI2022

Framework For Optimization Of Resources And Economics Ecosystem

The Framework for Optimization of ResourCes and Economics is a collection of software tools, models, and datasets acquired and developed under the Integrated Energy Systems (IES) program to enable analysis of technical and economic viability of myriad IES configurations. FORCE is the consolidating interface and data repository for all the IES toolsets ranging from macro technoeconomic analysis to transient process modeling and experimental validation for integrated energy systems.

Frick, KonorL↗
DOE OSTI2023

Human‐induced salinity changes impact marine organisms and ecosystems

Abstract Climate change is fundamentally altering marine and coastal ecosystems on a global scale. While the effects of ocean warming and acidification on ecology and ecosystem functions and services are being comprehensively researched, less attention is directed toward understanding the impacts of human‐driven ocean salinity changes. The global water cycle operates through water fluxes expressed as precipitation, evaporation, and freshwater runoff from land. Changes to these in turn modulate ocean salinity and shape the marine and coastal environment by affecting ocean currents, stratification, oxygen saturation, and sea level rise. Besides the direct impact on ocean physical processes, salinity changes impact ocean biological functions with the ecophysiological consequences are being poorly understood. This is surprising as salinity changes may impact diversity, ecosystem and habitat structure loss, and community shifts including trophic cascades. Climate model future projections (of end of the century salinity changes) indicate magnitudes that lead to modification of open ocean plankton community structure and habitat suitability of coral reef communities. Such salinity changes are also capable of affecting the diversity and metabolic capacity of coastal microorganisms and impairing the photosynthetic capacity of (coastal and open ocean) phytoplankton, macroalgae, and seagrass, with downstream ramifications on global biogeochemical cycling. The scarcity of comprehensive salinity data in dynamic coastal regions warrants additional attention. Such datasets are crucial to quantify salinity‐based ecosystem function relationships and project such changes that ultimately link into carbon sequestration and freshwater as well as food availability to human populations around the globe. It is critical to integrate vigorous high‐quality salinity data with interacting key environmental parameters (e.g., temperature, nutrients, oxygen) for a comprehensive understanding of anthropogenically induced marine changes and its impact on human health and the global economy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Leaf 13 C data constrain the uncertainty of the carbon dynamics of temperate forest ecosystems

Stable carbon isotope discrimination occurred in plant biophysical and biogeochemical processes can help understand plant physiology and soil biogeochemistry with respect to carbon cycling. Here, we incorporated the photosynthetic carbon isotope discrimination into a process-based land surface model (iTEM) to test if stable carbon isotope composition (δ 13 C) can impose additional constraint on model parameters. Sequential data assimilation was implemented at six eddy covariance flux tower sites using carbon flux observations including gross primary productivity (GPP) and net ecosystem exchange (NEE) with and without considering foliar δ 13 C (δ 13 C f ) measurement constraints, respectively. Our model-data fusion showed that δ 13 C f can provide useful constraint on photosynthetic (V cmax25 , the maximum rate of carboxylation at 25°C) and stomatal (g1, the slope of stomatal function) parameters as well as the posterior carbon fluxes. When including δ 13 C f measurement, g1 spatially varies among the six sites and is significantly correlated with annual precipitation. We incorporated the statistical relationship between g1 and annual precipitation into iTEM, which is then used to quantify the regional carbon dynamic in temperate forest ecosystems of the Northern Hemisphere. Compared with the simulation only conditioned on carbon flux observations, regional carbon flux estimations performed slightly better against the FLUXCOM products and the uncertainties of modeled carbon fluxes were reduced by 27%. Our study demonstrated that δ 13 C f data constrains carbon flux uncertainties across space.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Extrapolating carbon dynamics of seasonally dry tropical forests across geographic scales and into future climates: improving simulation models with empirical observations. Final report

This research focused on seasonally dry tropical forests (SDTFs), a biome that exhibits strong variation in ecological, hydrological and physical characteristics. Climate change is expected to strongly impact the atmospheric environment of SDTFs, and long-term trends in precipitation seasonality have already been detected. The extent to which such changes in seasonal moisture availability will impact SDTF carbon dynamics is highly uncertain, and much of this uncertainty hinges on poorly-understood belowground processes. Thus, the central objectives of this research were to qualitatively and quantitatively describe how belowground processes mediate the response of SDTF carbon dynamics to environmental change. We accomplished these aims through field campaigns in four tropical countries to characterize soil biogeochemistry and plant hydraulic traits, ecosystem-scale field experiments that manipulated both nutrients and rainfall, and simulation modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Modelling the Sensitivity of Yukon River Biogeochemical Dynamics to Environmental and Chemical Drivers: Implications for Dissolved Organic Carbon

Riverine dissolved organic carbon (DOC) is a critical biogeochemical component that transmits information from Arctic soils to the Arctic Ocean, significantly influencing carbon dynamics in this unique ecosystem. As DOC travels downstream, it undergoes transformations that alter its composition and fate. The Yukon River serves as an effective testbed for modelling these dynamics, offering sufficient scale to capture key biogeochemical processes while having a simpler hydrology than other major Arctic rivers, as well as long-term DOC observational data for model validation. To investigate DOC transformations during transit in the Yukon River, we adapted our Arctic Riverine Organic Macromolecular Model by applying regional-specific parameterisations. Our model simulates the transport and transformation of 15 organic macromolecules, including CDOM (coloured dissolved organic matter), proteins, polysaccharides, lipids, lignin phenols, and humic substances. Initial DOC concentrations were derived from observed soil organic carbon stocks in the surrounding watershed, while chemical transformations and hydrological dynamics were modelled along the river's course. Sensitivity and uncertainty analyses were conducted using a Monte Carlo approach under two experimental setups. Results revealed that variability in DOC and CDOM concentrations at the river mouth were predominantly driven by initial DOC concentration (~70% of variability explained) and dilution at confluence points (~10%). The refractory fraction of DOC explained 21%–88% of the variability in 14 macromolecular concentrations and ranked in the top five sensitive parameters for all outputs when a uniform parameter distribution was assumed. However, when a more likely variability was applied to this parameter, its influence on DOC and CDOM decreased. Given that refractory DOC accounts for ~80% of total DOC in Arctic Rivers, this suggests that most DOC resists degradation and retains its chemical composition during transport to the coastal environment. River velocity, which determines residence time, explained 8%–47% of the variability in protein, polysaccharide, lipid, pigments, and lignin phenols at the river mouth. In contrast, chemical turnover times contributed only 1%–5% to output variability. Our findings underscore the need for improved land-specific headwater observations, including seasonal soil moisture and lateral transport dynamics that control the initial tributary-specific DOC inputs. With accelerated permafrost thaw and increasing river discharge, extending our model to other Arctic River systems and seasons will enhance understanding of Arctic riverine carbon fluxes and their contributions to the Arctic Ocean.

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

Predicting spring green-up across diverse North American grasslands

Vegetation phenology influences many ecosystem and climate processes, such as carbon uptake and energy and water cycles. Thus, understanding drivers of vegetation phenology is crucial for predicting current and future impacts of climate change on ecological systems. Existing models can accurately predict the date of spring green-up in temperate forests but tend to perform poorly in grassland systems. We hypothesize this is because most do not incorporate water availability, a primary limiting factor for grassland plants. In this study, we used long-term datasets of digital imagery from the PhenoCam Network of 43 diverse North American grassland sites (195 site-years) to test existing spring phenology models, as well as develop several new models that incorporate precipitation or soil moisture (53 models). As a result, most of the new models performed substantially better, with the best model requiring sufficient accumulated precipitation followed by warm temperatures to trigger spring onset (root mean square error, RMSE, between predicted and observed dates = 16.0 days). Importantly, the best model performed well across all grassland types using a single set of parameters, from temperate to arid grasslands. Since plants are adapted to their local climates, model performance was further improved when parameters were independently optimized for four separate climate regions (RMSE = 10.4 days). Therefore, both sufficient precipitation and temperature are required for grassland green-up, but optimal thresholds vary by region. Running the top model with projected climate data (representative concentration pathway 8.5) suggests that, depending on the climate region, spring onset will occur up to 12 days earlier within 100 years in temperature-limited sites, but the trend is unclear for precipitation-limited sites (3.5 ± 8.0 days later). This new phenology model improves our ability to understand and predict grassland dynamics, with implications for both current and future ecosystem processes related to carbon and water cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Evapotranspiration partitioning estimates from 8 methods from 47 NEON sites, 2019-2021

This dataset provides daily estimates of evapotranspiration (ET) and the transpiration-to-evapotranspiration ratio (T/ET) across 47 terrestrial National Ecological Observatory Network (NEON) sites spanning diverse environmental and biome conditions in the United States across three years of data (2019-2021). Daily ET is reported in both energy units (MJ m⁻² day⁻¹) and equivalent water depth (mm day⁻¹), assuming a constant latent heat of vaporization of 2.45 MJ/kg. The primary method uses a hybrid recurrent neural network–Penman–Monteith framework (RNN-PM), which integrates physically based surface energy balance constraints with data-driven learning to partition ET into transpiration and evaporation components. Model inputs include in situ meteorological observations (air temperature, vapor pressure deficit, wind speed, and radiation) combined with satellite-derived land surface temperature, leaf area index, and soil moisture. For benchmarking and uncertainty assessment, T/ET estimates from seven additional models are included: Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), Penman-Monteith (P-M), Two-Source Energy Balance (TSEB), Support Vector Regression (SVR), and Categorical Boosting (CatBoost), among others—spanning empirical, machine-learning, and process-based approaches (see methods section or linked publication for detailed descriptions). Data Package Contents: The dataset a csv files containing daily ET and T/ET estimates for each site and model, along with associated metadata files these variables. Data can be accessed using common spreadsheet software (e.g., Microsoft Excel, LibreOffice) or programming environments such as R or Python. Together, these data support cross-site comparisons of ecosystem water use, evaluation of ET partitioning methods, and development of improved land–atmosphere exchange models.

EARTH SCIENCE > ATMOSPHERE↗
DOE OSTI2022

Plankton energy flows using a global size-structured and trait-based model

Plankton community models are critical tools for understanding the processes that shape marine plankton communities, how plankton communities impact biogeochemical cycles, and the feedbacks between community structure and function. Here, using the flexible Marine Biogeochemistry Library (MARBL), we present the Size-based Plankton ECological TRAits (MARBL-SPECTRA) model, which is designed to represent a diverse plankton community while remaining computationally tractable. MARBL-SPECTRA is composed of nine phytoplankton and six zooplankton size classes represented using allometric scaling relationships for physiological traits and interactions within multiple functional types. MARBL-SPECTRA is embedded within the global ocean component of the Community Earth System Model (CESM) and simulates large-scale, emergent patterns in phytoplankton growth limitation, plankton phenology, plankton generation time, and trophic transfer efficiency. The model qualitatively reproduces observed global patterns of surface nutrients, chlorophyll biomass, net primary production, and the biogeographies of a range of plankton size classes. In addition, the model simulates how predator:prey dynamics and trophic efficiency vary across gradients in total ecosystem productivity. Shorter food chains that export proportionally more carbon from the surface to the ocean interior occur in productive, eutrophic regions, whereas in oligotrophic regions, the food chains are relatively long and export less organic matter from the surface. The union of functional type modeling with size-resolved, trait-based modeling approaches allows MARBL-SPECTRA to capture both large-scale elemental cycles and the structure of planktonic food webs affecting trophic transfer efficiency.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks (Final Technical Report)

This is the final technical report from the first phase of a project that changed institutions. The grant was titled “Understanding spatial and temporal drivers of variation in tree hydraulic processes and their consequences for climate feedbacks.” The overall objectives of this project were to (1) provide model‐compatible datasets of key plant hydraulic traits and status for model evaluation, parameterization and validation and (2) use these data to pinpoint ecosystem responses to a changing hydroclimate by addressing both long‐term climatic drying and episodic extreme droughts. We planned to address the objectives with three research activities to quantify plant responses to chronic water stress and episodic drought: (1) generate high frequency observations of soil and plant hydraulic data across different landscape positions at multiple sites, (2) quantify plant hydraulic trait plasticity in response to experimental soil moisture reduction in situ in two central hardwood forests, and (3) simulate the carbon consequences of incorporating plant hydrodynamics and plant acclimation to water stress in the DOE‐sponsored plant hydrodynamics model FATES‐HYDRO. As of the transfer of this project to another institution, we had made substantial progress on activities 1 and 2, and started activity 3.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Modeling and Analysis of a Novel Offshore Binary Species Free-Floating Longline Macroalgal Farming System

The investigation of innovative macroalgal cultivation is important and needed to optimize farming operations, increase biomass production, reduce the impact on the ecosystem, and lower system and operational costs. However, most macroalgal farming systems (MFSs) are stationary, which need to occupy a substantial coastal area, require extensive investment in farm infrastructure, and cost high fertilizer and anchoring expenses. This study aims to model, analyze, and support a novel binary species free-floating longline macroalgal cultivation concept. The expected outcomes could provide a basis for the design and application of the novel MFS to improve biomass production, decrease costs, and reduce the impact on the local ecosystem. In this paper, Saccharina latissima and Nereocystis luetkeana were modeled and validated, and coupled with longline to simulate the binary species MFS free float in various growth periods and associated locations along the US west coast. Further, the numerical predictions indicated the possibility of failure on the longline and breakage at the kelp holdfasts is low. However, the large forces due to an instantaneous change in dynamic loads caused by loss of hydrostatic buoyancy when the longline stretches out of the water would damage the kelps. Buoy-longline contact interactions could damage the buoy, resulting in the loss of the system by sinking. Furthermore, the kelp-longline and kelp-kelp entanglements could potentially cause kelp damage.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Data, figures, animations, and scripts associated with the manuscript "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface"

This package contains the data, figures, animations, and scripts used in "Integrated Effects of Site Hydrology and Vegetation on Exchange Fluxes and Carbon Cycling at the Coastal Terrestrial Aquatic Interface" (Li et al., 2023). This study examines the interactions between soil, vegetation and hydrologic conditions in coastal areas, with a focus on the Chesapeake Bay region. The researchers used a mechanistic model called ATS-PFLOTRAN to explore how these interactions affect exchange process in different regions and the carbon/nitrogen cycle across the terrestrial-aquatic interface (TAI). Simulation scenarios isolate the effects of control factors and reaction constants derived from laboratory experiments. The results show a carbon cycle "hot zone" in coastal wetlands and in the transition zone between wetlands and uplands. Transpiration enhances fluxes between the surface and subsurface domains and increases dissolved oxygen in TAI. The decomposition of leaf-derived organic carbon provides an additional source of carbon for aerobic respiration and denitrification in the TAI. Microbial activity plays a key role in controlling redox conditions and their variability. This modeling study improves the understanding of complex TAI interactions and facilitates the representation of coastal ecosystems in larger-scale Earth system models.Several files can be found from this data package.1. Readme,md: This file describe the Title, Target Journal, Target submission date, Co-author, Science Questions, Hypotheses, Key words, Key message, Model and Data, Repo Structure. The user can read this file first and then go to details.2. mesh.zip: This file contains the mesh file for simulation cases. 3. Figure.zip: This file contains figures used in the manuscript . 4. animation.zip: This file contains animations used in the manuscript . 5. Data.zip: This file contains all required input data, such as concentration and flow boundaries. Also, it contains the DEM and processes results on area fraction. 6. Simulation_setup_and_results.zip: This file contains setup of cases used in the manuscript . The result files are too large, if you need that data, please contact to the Author. 7. notebooks.zip: This file contains the Jupyter notebooks for performing sensitivity analysis and other pre-process and post-process analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance, canopy height model, normalized difference vegetation index, Seward Peninsula, Alaska, 2021

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) - operated by the Terrestrial Ecosystem Science Technology group at Brookhaven National Laboratory. This package includes data from 10 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska, in August 2021. Derived image products include point cloud, ortho-mosaiced multispectral image, ortho-mosaiced RGB image, a digital surface model (DSM) using the structure from motion (SfM) technique, a canopy height model (CHM), and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) formats. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Session Introduction: Graph Representations and Algorithms in Biomedicine

Connectivity is a fundamental property of biological systems: on the cellular level, proteins interact with each other to form protein-protein interaction networks (PPIs); on the organism level, neurons are arranged in a network; and on a community-level, species can have complex relationships with one another that drive the development and balance of an ecosystem. Graphs, representations of systems consisting of entities as vertices and their connections as edges, are a useful structure to characterize many such systems. Such models can be used to understand biological systems that naturally have a network structure, including PPIs, biological neurons, and ecosystems. In today’s information age, graph representations and algorithms (often in combination with machine learning techniques) are used to organize massive amounts of related data, much of which may be heterogeneous or unstructured, and identify patterns that represent novel biological insights. PSB’s 2023 session “Graph Representations and algorithms in Biomedicine,” encompasses modern developments in graph theory and its applications to various fields of biomedicine. This session includes a wide range of research - knowledge graphs built from text-mined health data, heterogeneous networks using multi-omic databases, and graphs refined to represent uncertainty or improve memory usage.

Chrisman, Brianna S.↗
DOE OSTI2023

DUET - Distribution of Understory using Elliptical Transport: A mechanistic model of leaf litter and herbaceous spatial distribution based on tree canopy structure

Heterogeneity in surface fuels produced by overstory trees and understory vegetation is a major driver of fire behavior and ecosystem dynamics. Previous attempts at predicting tree leaf and needle litter accumulation over time have been constrained in scope to probabilistic models that consider a limited number of key factors influencing tree litter dispersal patterns and decomposition processes. Here we present a mechanistic model for estimating variation in surface fuels called the Distribution of Understory using Elliptical Transport (DUET). DUET uses a pre-generated voxelated canopy array and distributes the leaf litter from the trees in an elliptical shape based on tree species characteristics, wind data, and location-specific features. DUET then calculates grass growth between trees and around the litter patterns and sets moisture levels based on relative humidity. In this study, we use DUET to simulate spatial distributions of leaf litter and illustrate model sensitivity to several parameters, providing inputs for testing fuel spatial heterogeneity impacts on fire behavior using process-based models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

UAS remote sensing (Autel EVO II platform): Red-green-blue (RGB) imagery and derived products (Level 0-2 data), Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a optical red-green-blue (RGB) sensor installed on an Autel EVO II unoccupied aerial system (UAS). This package includes data from 15 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska USA, in July 2022. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors, and Level 1-2 processed products including digital surface models (DSM), photo orthomosaics, canopy height models (CHM) and digital terrain models (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as image (*.jpg, *.tif), point cloud (*.laz), tabular (*.csv) and *.pdf formats. Raw images are compressed as tar.gz. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the data and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗