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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine learning identifies novel signatures of antifungal drug resistance in Saccharomycotina yeasts

Antifungal drug resistance is a major challenge in fungal infection management. Numerous genomic changes are known to contribute to acquired drug resistance in clinical isolates of specific pathogens, but whether they broadly explain natural resistance across entire lineages is unknown. We leveraged genomic, ecological, and phenotypic trait data from naturally sampled strains from nearly all known species in subphylum Saccharomycotina to examine the evolution of resistance to eight antifungal drugs. The phylogenetic distribution of drug resistance varied by drug; fluconazole resistance was widespread, while 5-fluorocytosine resistance was rare, except in Lipomycetales. A random forest algorithm trained on genomic data predicted drug-resistant yeasts with 54–75% accuracy. Fluconazole resistance was consistently predicted with the highest accuracy (75.2%). Furthermore, fluconazole resistance prediction accuracy was similar between models trained on genome-wide variation in the presence and number of InterPro protein annotations across Saccharomycotina (75.2%) and those trained on amino acid sequence alignment data of Erg11, a protein known to be involved in fluconazole resistance (74.3-74.9%). Interestingly, the top Erg11 residues for predicting fluconazole resistance across Saccharomycotina do not overlap with, are not spatially close to, and are less conserved than those previously linked to resistance in clinical isolates of Candida albicans. In silico deep mutational scanning of the C. albicans Erg11 protein reveals that amino acid variants implicated in clinical cases of resistance are almost universally destabilizing while variants in our most informative residues are energetically more neutral, explaining why the latter are much more common than the former in natural populations. Importantly, previous experimental analyses of C. albicans Erg11 have shown that amino acid variation in our most informative residues, despite having never been directly implicated in clinical cases, can directly contribute to resistance. Our results suggest that studies of natural resistance in yeast species never encountered in the clinic will yield a fuller understanding of antifungal drug resistance.

Harrison, Marie-Claire [Vanderbilt Univ., Nashvill↗
DOE OSTI2020

Active layer depth and soil properties impact specific leaf area variation and ecosystem productivity in a boreal forest

Specific leaf area (SLA, leaf area per unit dry mass) is a key canopy structural characteristic, a measure of photosynthetic capacity, and an important input into many terrestrial process models. Although many studies have examined SLA variation, relatively few data exist from high latitude, climate-sensitive permafrost regions. We measured SLA and soil and topographic properties across a boreal forest permafrost transition, in which dominant tree species changed as permafrost deepened from 54 to >150 cm over 75 m hillslope transects in Caribou-Poker Creeks Research Watershed, Alaska. We characterized both linear and threshold relationships between topographic and edaphic variables and SLA and developed a conceptual model of these relationships. We found that the depth of the soil active layer above permafrost was significantly and positively correlated with SLA for both coniferous and deciduous boreal tree species. Intraspecific SLA variation was associated with a fivefold increase in net primary production, suggesting that changes in active layer depth due to permafrost thaw could strongly influence ecosystem productivity. While this is an exploratory study to begin understanding SLA variation in a non-contiguous permafrost system, our results indicate the need for more extensive evaluation across larger spatial domains. These empirical relationships and associated uncertainty can be incorporated into ecosystem models that use dynamic traits, improving our ability to predict ecosystem-level carbon cycling responses to ongoing climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Deciphering the microbial and molecular responses of geographically diverse Setaria accessions grown in a nutrient-poor soil

The microbial and molecular characterization of the ectorhizosphere is an important step towards developing a more complete understanding of how the cultivation of biofuel crops can be undertaken in nutrient poor environments. The ectorhizosphere of Setaria is of particular interest because the plant component of this plant-microbe system is an important agricultural grain crop and a model for biofuel grasses. Importantly, Setaria lends itself to high throughput molecular studies. As such, we have identified important intra- and interspecific microbial and molecular differences in the ectorhizospheres of three geographically distant Setaria italica accessions and their wild ancestor S . viridis . All were grown in a nutrient-poor soil with and without nutrient addition. To assess the contrasting impact of nutrient deficiency observed for two S . italica accessions, we quantitatively evaluated differences in soil organic matter, microbial community, and metabolite profiles. Together, these measurements suggest that rhizosphere priming differs with Setaria accession, which comes from alterations in microbial community abundances, specifically Actinobacteria and Proteobacteria populations. When globally comparing the metabolomic response of Setaria to nutrient addition, plants produced distinctly different metabolic profiles in the leaves and roots. With nutrient addition, increases of nitrogen containing metabolites were significantly higher in plant leaves and roots along with significant increases in tyrosine derived alkaloids, serotonin, and synephrine. Glycerol was also found to be significantly increased in the leaves as well as the ectorhizosphere. These differences provide insight into how C 4 grasses adapt to changing nutrient availability in soils or with contrasting fertilization schemas. Gained knowledge could then be utilized in plant enhancement and bioengineering efforts to produce plants with superior traits when grown in nutrient poor soils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Structural and functional insights into the first Bacillus thuringiensis vegetative insecticidal protein of the Vpb4 fold, active against western corn rootworm

The western corn rootworm (WCR), Diabrotica virgifera virgifera LeConte, is a major maize pest in the United States causing significant economic loss. The emergence of field-evolved resistant WCR to Bacillus thuringiensis (Bt) traits has prompted the need to discover and deploy new insecticidal proteins in transgenic maize. In the current study we determined the crystal structure and mode of action (MOA) of the Vpb4Da2 protein (formerly known as Vip4Da2) from Bt, the first identified insecticidal Vpb4 protein with commercial level control against WCR. The Vpb4Da2 structure exhibits a six-domain architecture mainly comprised of antiparallel β-sheets organized into β-sandwich layers. The amino-terminal domains 1–3 of the protein share structural homology with the protective antigen (PA) PA14 domain and encompass a long β-pore forming loop as in the clostridial binary-toxB module. Domains 5 and 6 at the carboxyl-terminal half of Vpb4Da2 are unique as this extension is not observed in PA or any other structurally-related protein other than Vpb4 homologs. These unique Vpb4 domains adopt the topologies of carbohydrate-binding modules known to participate in receptor-recognition. Functional assessment of Vpb4Da2 suggests that domains 4–6 comprise the WCR receptor binding region and are key in conferring the observed insecticidal activity against WCR. The current structural analysis was complemented by in vitro and in vivo characterizations, including immuno-histochemistry, demonstrating that Vpb4Da2 follows a MOA that is consistent with well-characterized 3-domain Bt insecticidal proteins despite significant structural differences.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Phototrophy and carbon fixation in Chlorobi postdate the rise of oxygen

While most productivity on the surface of the Earth today is fueled by oxygenic photosynthesis, for much of Earth history it is thought that anoxygenic photosynthesis—using compounds like ferrous iron or sulfide as electron donors—drove most global carbon fixation. Anoxygenic photosynthesis is still performed by diverse bacteria in niche environments today. Of these, the Chlorobi (formerly green sulfur bacteria) are often interpreted as being particularly ancient and are frequently proposed to have fueled the biosphere during late Archean and early Paleoproterozoic time before the rise of oxygenic photosynthesis. Here, we perform comparative genomic, phylogenetic, and molecular clock analyses to determine the antiquity of the Chlorobi and their characteristic phenotypes. We show that contrary to common assumptions, the Chlorobi clade is relatively young, with anoxygenic phototrophy, carbon fixation via the rTCA pathway, and iron oxidation all significantly postdating the rise of oxygen ~2.3 billion years ago. The Chlorobi therefore could not have fueled the Archean biosphere, but instead represent a relatively young radiation of organisms which likely acquired the capacity for anoxygenic photosynthesis and other traits via horizontal gene transfer sometime after the evolution of oxygenic Cyanobacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Arbuscular mycorrhizal fungal response to fire and urbanization in the Great Smoky Mountains National Park

Wildfires are increasing in frequency and intensity as drier and warmer climates increase plant detrital fuel loads. At the same time, increases in urbanization position 9% of fire-prone land within the United States at the wildland–urban interface. While rarely studied, the compounded effects of urbanization and wildfires may have unknown synergistically negative effects on ecosystems. Previous studies at the wildland–urban interface often focus on aboveground plant communities, but belowground ecosystems may also be affected by this double disturbance. In particular, it is unclear how much fire and urbanization independently or interactively affect nutritional symbioses such as those between arbuscular mycorrhizal (AM) fungi and the majority of terrestrial plants. In November 2016, extreme drought conditions and long-term fire suppression combined to create a wildfire within the Great Smoky Mountains National Park and the neighboring exurban city of Gatlinburg, TN. To understand how the double disturbance of urbanization and fire affected AM fungal communities, we collected fine roots from the 5 dominant understory species in September 2018 at each of 18 sites spanning 3 burn severities in both exurban and natural sites. Despite large variation in burn severity, plant species identity had the largest influence on AM fungi. AM fungal colonization, richness, and composition all varied most among plant species. Fire and urbanization did influence some AM fungal metrics; colonization was lower in burned sites and composition was more variable among exurban locations. There were no interactions among burn severity and urbanization on AM fungi. Our results point to the large influence of plant species identity structuring this obligate nutritional symbiosis regardless of disturbance regime. Therefore, the majority of AM fungal taxa may be buffered from fire-induced ecosystem changes if plant community composition largely remains intact, plant species life history traits allow for AM fungal persistence after fire disturbance, and/or nearby undisturbed habitat can act as an inoculum source for recolonization following fires. Thus, it is critical to maintain natural, undisturbed habitats interspersed within the wildland–urban interface.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Microbial extracellular enzyme activity with simulated climate change

It is critical to understand the consequences of environmental change for the microbial regulation of carbon and nutrient cycling. Specifically, understanding microbial community traits, such as extracellular enzyme activity, can help inform nutrient cycling models and address knowledge gaps. We analyzed data on extracellular enzyme activities and litter decomposition from an 18-month experiment in which microbial communities were reciprocally transplanted along a climate gradient in Southern California. Communities were from desert, scrubland, grassland, pine–oak, and subalpine ecosystems. We aimed to test how enzyme activities responded to climate change following transplantation and how those responses related to decomposition rates. We hypothesized that microbial communities would specialize on their native climate conditions, resulting in higher enzyme activities when transplanted back into their native climate. We investigated the relationship between extracellular enzyme Vmax values, substrate mass loss, and microbial biomass as well as variation in these variables across the climate gradient. We found little evidence for climate specialization, and there was rarely a reduction in enzyme functioning after microbial communities were transplanted into new climate conditions. Moreover, observed differences in decomposition were not related to changes in extracellular enzyme potential, although there were significant differences in enzyme activities and decomposition rates across sites. These results suggest that direct, physiological impacts of climate are likely to be important for enzyme-mediated decomposition, but climate specialization will not constrain the microbial response to climate change in our system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Dataset 1: A National and City Dataset on Human Factors in Pooled Rideshare, 2021

Dataset 1: A National and City Dataset on Human Factors in Pooled Rideshare, 2021. Dataset Description: Pooled Rideshare Acceptance Survey - Phase 1 (2021, N = 5,385). This dataset captures responses from a nationally representative sample of 5,385 adults across the United States to understand public acceptance, preferences, and behavioral intentions related to pooled rideshare (PR) services. The primary objective of this research is to provide actionable insights to inform the design, deployment, and policy development of sustainable shared mobility systems. Data was collected via an online survey administered through a national panel provider. Participants ranged in age from 18 to 95 years, and representation from all U.S. regions. The survey instrument was designed to explore numerous dimensions related to PR adoption including demographic traits, current travel habits, rideshare familiarity, trust, safety, environmental attitudes, and user experience preferences. Both rideshare users and non-users were included, offering a diverse range of perspectives. - Phase_1_Final - The dataset includes survey items developed from literature reviews, and prior field studies. Each row represents an individual respondent, and each column corresponds to a variable such as willingness to use pooled rideshare, attitudes toward specific service features, and sociodemographic data. The data is available in both .CSV and .SAV formats. - Phase_1_Final_MapFile - The accompanying data dictionary explains all variable labels, response scales, and codes. An .XLSX format of the full survey instrument is also included to support interpretation and reuse of the dataset.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Data from: "Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest"

This data package contains data used to support conclusions drawn in “Warming and provenance limit tree recruitment across and beyond the elevation range of subalpine forest”, by Kueppers et al. 2017. Data were collected in field sites within the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, on the eastern slope of the Colorado Rocky Mountains, USA. Files containing geospatial data are also included, to provide additional locational context.There are four document formats associated with this archive: three comma-separated values (.csv) files, three Microsoft Excel (.xlsx) files, one .pdf data user’s guide, four keyhole markup language (.kml) files, and a compressed folder containing seven ESRI shapefiles (.shp). The .csv files can be opened using any simple text-editor software, R, or Microsoft Excel. The .xlsx files can only be opened using Microsoft Excel. The .kml file can be opened by Google Earth and Google Maps, and the shapefiles can be opened with any GIS application compatible with the file type, such as ESRI’s ArcGIS, and QGIS.We provide two versions of the seedling data file: “PIEN_PIFLseedlings20150522_20150525rev12222020.csv/.xlsx” (hereafter PIEN_PIFLseedlings2015) and “PIEN_PIFLseedlings20160408rev12222020.csv/.xlsx” (hereafter PIEN_PIFLseedlings2016). PIEN_PIFLseedlings2015 contains the data we used in the paper. PIEN_PIFLseedlings2016 contains an updated version of these data that includes sampling from later years. The main differences between the two files lie in the columns titled “k[YEAR],” which describe the number of seedlings that were killed in a particular year. In PIEN_PIFLseedlings2016, there also is an additional year of data for k2015, and k2014 also has additional data input for the 2014 cohort. Additionally, in years 2010-2014, there are minor differences in the number of seedlings killed -- in as few as 0 plots (in 2011) to as many as 5 plots (in 2014) -- due to errors in data input that were rectified in later years.------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Upslope range shifts by subalpine tree species are a widely anticipated effect of climate change. Climate niche models predict subalpine forests to expand upslope, given more suitable growing conditions for adult trees. However, these models do not take into account climates required for successful seedling recruitment and establishment, an essential element for expansion. Further, localized upper treeline populations are hypothesized to contain favorable traits for colonizing the alpine. To test these expectations and to expand our knowledge of seedling recruitment under climate change, we designed a common garden, climate-warming experiment spread across an elevation gradient at Niwot Ridge in the Colorado Rocky Mountains. We focus on two widespread Western North American species, Engelmann spruce (Picea engelmannii Parry ex. Engelm) and limber pine (Pinus flexilis James), which occur at treeline. While the former is considered a late-seral species more tolerant of shade, limber pine is a shade-intolerant pioneer species able to establish on infertile sites.Every autumn, seeds of the two species were collected from high- (3370 m–3570 m) and low-provenance (2910–3240 m) sources close to the experimental sites and sown in our plots. A subset of plots were heated and another subset watered over the summer months to offset the effects of warming. Across five years, we found that seeds originating from low elevation recruited more strongly for both species, although this provenance difference diminished by the fourth year for Engelmann spruce, likely due to small sample sizes. Despite the recruitment of low-provenance seed, warming treatments decreased recruitment at all elevations. Combining this with the likeliness and availability of lower-quality, high provenance seed moving upslope at the treeline, tree migration into the alpine may be slowed. Overall, our findings suggest that the hardier limber pine is likely to become a more significant species in subalpine forest communities in the future, while the more sensitive Engelmann spruce may experience range contraction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Seedling nitrogen uptake and rhizodeposition between mycorrhizal types

Tree mycorrhizal associations are associated with patterns in N cycling and soil organic matter (SOM) storage, however, we still lack a mechanistic understanding of what tree and fungal traits drive these patterns and how they will respond to global changes in soil N availability. To address this knowledge gap, we investigated how arbuscular mycorrhizal (AM)- and ectomycorrhizal (EcM)-associated seedlings alter rhizodeposition in response to increased inorganic N acquisition. Specifically, we conducted this greenhouse experiment in a sealed labeling chamber with an enriched 13Carbon atmosphere and 15Nitrogen enriched fertilizer over the course of five months from April 2021 - August 2021. To include the variability across tree species, we grew eight species of seedlings belonging to eight families that were either arbuscular (Acer rubrum, Nyssa sylvatica, Thuja occidentalis, and Prunus seritina) or ectomycorrhizal-associated (Quercus rubra, Tilia americana, Pinus strobus, and Betula lenta). We measured rhizodeposition (mg 13C), plant N uptake from fertilizer (mg N), net soil carbon, and the abundance of mycorrhizal fungi (ITS sequencing and qPCR). We also characterized fungal (ITS2) and bacterial (16S) soil communities.The data from this project are ".csv" files that can up downloaded into a folder, and then run in the associated R markdown scripts after changing the source folder location at the top of the script. These data include raw outputs and processed files (using the R markdown files) for seedling growth and biomass, 15N content, soil 13C content, raw reads and processed file versions for fungal and bacterial ASVS, and a final summary file used for modeling. R software is needed to run these data, and the packages needed are listed at the top of the R markdown file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Plant physiology, shrub size, thaw depth and soil water content, Seward Peninsula, Alaska, 2023

Stomatal response to changing irradiance measurements (m curves), CO2 response (ACi) and light response (AQ) curves on common tussock tundra shrub, graminoid and forb species. Data were collected in July 2023 from three sites on the Seward Peninsula, Kougarok Mile 64, Teller Mile 27 and Council. Measurements were made with LI-COR LI-6800 gas exchange systems on 18 species. For samples from Teller and Kougarok, thaw depth, soil moisture content and dGPS locations are also provided for most samples. Canopy height and canopy diameter are provided for shrubs measured at the Teller site. The data package files include data files, metadata files and the complete instrument output for all gas exchange measurements in .csv format, and a pdf describing the experimental protocols. See the related data package NGA508 for foliar trait data (leaf mass per area, leaf nitrogen concentration).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↗
DOE OSTI2024

Ultrahigh-resolution mass spectrometry data associated with the manuscript “A functional microbiome catalog crowdsourced from North American rivers"

This data package is associated with the publication “A functional microbiome catalog crowdsourced from North American rivers” submitted to Nature (Borton et al., 2024); (https://www.biorxiv.org/content/10.1101/2023.07.22.550117v1). Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial determinants governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). GROWdb is a publicly available resource that paves the way for watershed predictive modeling and microbiome-based management practices. This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. We identified the most cosmopolitan microbiome members, while also revealing local drivers of strain endemism across ecological dimensions. We provide the first evidence that microbial functional trait expression followed the tenets of the River Continuum Concept, suggesting the structure and function of river microbiomes is predictable. The Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data were one of many different data types used in establishing the ecological dimensions along which different microbes were detected .This data package only contains the processed FTICR-MS data associated with this manuscript; all other data is accessible via Zenodo (https://zenodo.org/records/8173287), GitHub (https://github.com/jmikayla1991/Genome-Resolved-Open-Watersheds-database-GROWdb), KBase (https://doi.org/10.25982/109073.30/1895615), and NCBI via Bioproject PRJNA946291.This dataset consists of (1) a file-level metadata (flmd) file; (2) a data dictionary (dd) file; (3) a readme; (4) three Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) processed data files (a ‘data’ file containing peak-by-sample observations, a ‘mol’ file containing peak metadata, and a transformation profile containing transformation-by-sample observations). All files are .csv or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Maps of plant functional type (PFT), PFT fractional cover, and uncertainty derived from AVIRIS-NG data, 2019, Seward Peninsula

Remote sensing maps of plant functional type (PFT), PFT fractional cover (fCover), and fCover uncertainty maps derived from NASA’s Airborne Visible / Infrared Imaging Spectrometer – Next Generation (AVIRIS-NG). The AVIRIS-NG imaging spectroscopy data (380 ~ 2510 nm) was collected as a part of the collaboration between NASA’s Arctic-Boreal Vulnerability Experiment (ABoVE; Miller et al., 2019) and DOE’s Next Generation Ecosystem Experiment in the Arctic (NGEE-Arctic). This package includes maps for flights over Teller, Kougarok, and Council watersheds created using eight AVIRIS-NG imagery collected in July, 2019. The map data and metadata are provided as image (ENVI, *.png) and text (*.txt, *hdr) formats. Additional supporting map quicklooks are provided as GIS *.kml files. Detailed description of the methods for each map are provided in Yang et al., (2023). These datasets are provided in support of Yang et al., (In revision) “Topography and Functional Traits Control the Distribution of Key Shrub Plant Functional Types in Low-Arctic Tundra”.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 OSTI2024

Soil properties and root characteristics across four lowland Panamanian forests from 0 - 1 m soil depths

Objectives:Fine roots significantly influence ecosystem-scale cycling of nutrients, carbon (C), and water, yet there is limited understanding of how fine root traits vary across and within tropical forests, some of Earth's most C-rich ecosystems. The biomass of fine roots can impact soil carbon storage, as root mortality is a primary source of new carbon to soils. A positive relationship has been observed between fine root biomass and soil carbon stocks in Panama (Cusack et al 2018). Beyond biomass, root characteristics like specific root length (SRL) could also influence soil carbon, as roots with higher SRL are less dense and thinner, potentially decomposing more easily or promoting soil aggregation. Understanding the effects of root morphology and tissue quality on soil carbon storage and with soil properties in general can improve predictions of landscape-scale carbon patterns. We aggregated new data of root biomass, morphology and nutrient content at 0-10 cm, 10-20 cm, 20-50 cm and 50-100 cm depth increments across four distinct lowland Panamanian forests and paired with already published datasets (Cusack et al 2018; Cusack and Turner 2020) of soil chemistry from the same sites and soil depths to explore relationship between soil carbon stocks and root characteristics.Datasets included:The datasets provided include .csv and .xlsx files for fine root characteristics and soil chemistry from four different forests across 0-10 cm, 10-20 cm, 20-50 cm, and 50-100 cm depth increments. Root characteristics include live fine root biomass, dead fine root biomass, coarse root biomass, specific root length, root diameter, root tissue density, specific root area, root %N, root %C, and root C/N ratio. Soil chemistry data includes total carbon (TC), dissolved organic carbon (DOC), bulk density, total phosphorus (TP), available phosphorus (AEM Pi), and various Mehlich-extractable elements such as aluminum, calcium, iron, potassium, manganese, phosphorus, and zinc. Nitrogen content measures include ammonium, nitrate, total dissolved nitrogen (TDN), dissolved inorganic nitrogen (DIN), and dissolved organic nitrogen (DON). The dataset also includes total exchangeable bases (TEB) and effective cation exchange capacity (ECEC) in both centimoles of charge per kilogram and micromoles of charge per gram. The soil chemistry data was obtained from Cusack et al (2018) and Cusack and Turner (2020) and paired with root characteristics data for the same depth increments and sites. Additionally, a .kml file is provided with coordinates for all 32 plots included in the study across four forests (n = 8 plots per site). Root data was averaged across these 8 plots per site and soil data was collected in one pit in each site. This dataset serves as baseline data before a throughfall exclusion experiment, Panama Rainforest Changes with Experimental Drying (PARCHED), was implemented. No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Radiocarbon of deep fine roots across four in lowland seasonal tropical forests in Panama

Objectives:Fine roots are key to ecosystem-scale nutrient, carbon (C), and water cycling, but our understanding of fine root traits variation within and among tropical forests, one of Earth’s most C-rich ecosystems, is limited. In 2022 and 2023, we aimed to explore differences in deep root characteristics among four lowland tropical forests in Panama, which vary in fertility and mean annual precipitation. We measured radiocarbon content (fraction modern [FM] and Δ14C) and δ13C of live fine roots at depths greater than 80 cm, up to 120 cm. The goal was to understand how deep root characteristics differ across these sites.Datasets included:The datasets provided include .csv and .xlsx files for radiocarbon content (fraction modern [FM] and Δ14C) and δ13C of live fine roots at depths greater than 80 cm, up to 120 cm collected from late 2017 to 2018 across four different forests. Additionally, a .kml file is provided with coordinates for all 32 plots included in the study across four forests (n = 8 plots per site). This dataset serves as baseline data before a throughfall exclusion experiment, Panama Rainforest Changes with Experimental Drying (PARCHED), was implemented. No special software is needed to open these files.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Leaf mass area, leaf carbon and nitrogen content of 18 plant species, Seward Peninsula, Alaska, 2023

Leaf mass per area (LMA), and leaf carbon and nitrogen content of Arctic vegetation species from three sites on the Seward Peninsula, Alaska. The plants were sampled in July 2023 from the Kougarok Mile 64, Teller Mile 27 and Council sites as part of an ongoing project to improve the understanding of stomatal conductance and photosynthetic parameterization of Arctic plant functional types (PFTs). Species sampled included deciduous tall and dwarf shrubs, forbs, and graminoids, for a total of 18 species. All sampled leaves were used for gas exchange measurements prior to analysis of LMA and leaf carbon and nitrogen content. The data and metadata files included in this data package are in .csv format. See related dataset NGA509 for leaf-level gas exchange measurements and shrub traits (size, thaw depth, soil moisture).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↗
DOE OSTI2025

Litter Production and Foliar Nutrient Resorption in Pioneer and Non-Pioneer Species in a Selective Logging Experiment in the Central Amazon, BIONTE, ZF-2, Manaus, 2022-23

This dataset was collected near the city of Manaus, Brazil, at the Experimental Station of Tropical Forestry (EEST, aka “ZF2”), inside the BIONTE (BIOmass and NuTrient Experiment). The experiment included three levels of increasing selective logging intensity, along with control, with 1-hectare permanent plots (12 total) located at the center of 4-hectare treatment plots. The vegetation has a high floristic diversity, the soils of the region are poor in nutrients, and the topography is characterized by plateaus (where BIONTE is located), and also valley bottoms and slopes. Three treatments of differing logging intensities were applied in the BIONTE experiment (T1, T2 and T3). The study was conducted in Treatment 3 (Block I – permanent plot), which represents the most intensive logging treatment, with 69% of the basal area (m²∙ha⁻¹) removed in 1988. The present dataset spans the period from May 1, 2022, to May 1, 2023. The data package includes leaf_nutrient_data, litterfall_total_data, leaf_litterfall_species_specific_data, and species_info, all provided in .csv format. These formats allow users to process and analyze the data in various software applications and programming languages, such as Python and R. This dataset was collected to advance knowledge on nutrient cycling in Amazonian forests, specifically distinguishing between species with two distinct functional traits: fast-growing and slow-growing. It also aims to improve Earth System Models, such as the E3SM Functionally Assembled Terrestrial Ecosystem Simulator (FATES). Additionally, it was used in a paper currently in preparation (Carvalho et al., in prep.), which aims to quantify seasonal litter production and foliar nutrient resorption in pioneer (fast-growing) and non-pioneer (slow-growing) tree species in the central Amazon. Specifically, it seeks to answer two key questions: 1) Is there a difference in leaf litter production, leaf nutrient flux and leaf nutrient concentration between pioneers and non-pioneers species? Is there a difference in the efficiency of foliar nutrient resorption between pioneers and non-pioneers species?

54 ENVIRONMENTAL SCIENCES↗