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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Island influences on plant functional traits and trait–trait associations across species‐ and community‐scales

The island rule predicts gigantism or dwarfism in body size of island species relative to their mainland counterparts. However, whether other functional traits shift and whether trait–trait associations on islands differ between species and community levels remains unclear. We measured 13 carbon- and water-related functional traits in 37 shared tree species across 35 eastern Chinese islands and 66 nearby mainland plots. We examined species-level trait value shifts and associations under the island rule and compared trait associations between species and communities. Most size-related, wood-anatomical, and hydraulic traits shifted on islands, with large values decreasing and small values increasing; yet, their associations remained stable, aligning with the global trait spectrum and trait–trait coevolution. This stability, despite trait value shifts, suggests evolutionary integration of functional strategies. By contrast, island community-scale trait associations diverged from shared species-level patterns and sometimes reversed, such as positive relationships between wood density and resource-acquisitive traits. Community-level trait associations were stronger on islands, likely reflecting constrained environmental filtering and migration limitation. These contrasting patterns suggest that dominant species can restructure trait associations at the community level, with implications for ecosystem functioning and carbon storage, thereby advancing understanding of plant trait strategies in island systems.

Archipelagos↗
DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗
DOE OSTI2024

Soil microenvironmental variation drives below‐ground trait variation and interacts with macroclimate to structure above‐ground trait variation of arctic shrubs

Abstract Intraspecific trait variation can influence plant performance in different environments and may thereby determine the ability of individual plants to respond to climate change. However, our understanding of its patterns and environmental drivers across different spatial scales is incomplete, especially in understudied regions like the Arctic. To fill this knowledge gap, we examined above‐ground and below‐ground traits from three shrub taxa expanding across the tundra biome and evaluated their relationships with multiple microenvironmental and macroclimatic factors. The traits reflected plant size and structure (plant height, leaf area and root to shoot ratio), leaf economics (specific leaf area, nitrogen content), and root economics and collaboration with mycorrhizal fungi (specific root length, root tissue density, nitrogen content, and ectomycorrhizal colonisation intensity). We also measured leaf and root δ 15 N and leaf δ 13 C to characterise nitrogen source and acquisition pathways and plant water stress. Traits were measured in replicated plots ( N = 135) varying in soil microclimate, thaw depth and organic layer thickness established across five sites spanning a macroclimate gradient in northern Alaska. This hierarchical design allowed us to disentangle the independent and combined effects of fine‐scale and broad‐scale factors on intraspecific trait variation. We found substantial intraspecific variation at fine spatial scales for most traits and less variation along the macroclimate gradient and between shrub taxa. Consistent with these patterns, microenvironmental factors, mainly soil moisture and thaw depth, interacted with macroclimate, mainly climatic water deficit, to structure size‐structural and leaf trait variation. In contrast, most root traits responded additively to thaw depth and macroclimate. Synthesis . Our results demonstrate that above‐ground and below‐ground tundra shrub traits respond differently to microenvironmental and macroclimatic variation. These differing responses contribute to substantial trait variation at fine spatial scales and may decouple above‐ground and below‐ground trait responses to climate change.

Environmental Sciences & Ecology↗
DOE OSTI2021

Root anatomy helps to reconcile observed root trait syndromes in tropical tree species

Premise Studying the organization of functional traits in plant leaves and stems has revealed notable patterns linking function and form; however, evidence of similarly robust organization in root tissues remains controversial. We posit that anatomical traits in roots can provide insight on the overall organization of the root system. We hypothesized that size variation in the tissue outside the stele is related in a nonlinear fashion with functional traits associated with direct resource uptake, including a negative relationship with root architectural traits, and that similar relationships detected in tropical areas also hold true in other biomes. Methods We addressed our hypotheses using empirical data from 24 tropical tree species in French Guiana, including anatomical measurements in first order roots and functional trait description for the entire fine root system. In addition, we compiled a global meta‐analysis of root traits for 500+ forest species across tropical, subtropical, and temperate forests. Results Our results supported the expected nonlinear relationships between cortical size and morphological traits and a negative linear trend with architectural traits. We confirmed a global negative relationship among specific root length (SRL), diameter, and tissue density, suggesting similar anatomical constraints in root systems across woody plants. However, the importance of factors varies across biomes, possibly related to the unequal phylogenetic representation across latitudes. Conclusions Our findings imply that the rhizocentric hypothesis can be a valuable approach to understand fine root trait syndromes and the evolution of absorptive roots in vascular plants.

Valverde‐Barrantes, Oscar J.↗
DOE OSTI2020

Genetic architecture of leaf morphological and physiological traits in a Populus deltoides ‘Danhong’ × P. simonii ‘Tongliao1’ pedigree revealed by quantitative trait locus analysis

Understanding the genetic architecture of leaf morphological and physiological traits will help plant breeders develop high biomass poplar genotypes. Quantitative trait locus (QTL) studies combining next-generation sequencing techniques can advance our understanding of the genetic basis of complex traits. In this study, we measured 13 leaf morphological and physiological traits and identified quantitative trait loci (QTLs) in a Populus deltoides ‘Danhong’ × P. simonii ‘Tongliao1’ F1 population (500 progenies) using a high-density genetic map constructed by whole genome re-sequencing. This linkage map consisted of 5796 single nucleotide polymorphism (SNP) markers assigned to 19 linkage groups (LGs), spanning 2683.80 centimorgans (cM) of genetic length, with an average marker density of 0.46 cM. We identified 109 QTLs on 18 LGs for leaf morphological traits and 55 QTLs on 14 LGs for leaf physiological traits. One-hundred eight putative candidate genes were identified within the candidate genomic region. Co-expression network and gene ontology enrichment analyses suggested that these candidate genes were involved in the photosynthetic process. The differential expression patterns of the CYCLIN (Potri.015G112200) and RED CHLOROPHYLL REDUCTASE (Potri.007G043600) genes between two parents indicated their potential roles in leaf morphological and physiological traits. These findings decipher the genetic architecture of leaf morphological and physiological traits in the P. deltoides ‘Danhong’ × P. simonii ‘Tongliao1’ pedigree and provide candidate genes for future poplar genetic improvement.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Divergences in hydraulic conductance and anatomical traits of stems and leaves in three temperate tree species coping with drought, N addition and their interactions

Drought and N addition have been shown to affect tree hydraulic traits, but few studies have been made on their interactions across species with different wood types or leaf forms. We examined the responses of hydraulic conductance and xylem anatomical traits of Quercus mongolica (ring-porous with simple-leaves), Fraxinus mandshurica (ring-porous with compound-leaves), and Tilia amurensis (diffuse-porous with simple-leaves) to drought, N addition and their interactions. Drought stress decreased current-year xylem-specific conductivity in stems (Ksx) and leaf hydraulic conductance (Kleaf), but N addition affected Ksx and Kleaf differently among species and watering regimes. These divergent effects were associated with different responses of anatomical traits and leaf forms. Higher mean vessel diameter in stems (Dstem) and lower vessel density in leaves (VDvein) were observed with N addition. The three-way interactive effects of drought, N addition and tree species were significant for most values of anatomical traits. These results were also reflected in large differences in vessel diameter and density among species with different wood types or leaf forms. The two-way interactive effects of drought and N addition were significant on Kleaf and predawn water potential (?pd), but not Ksx, indicating that leaves were more sensitive than stems to a combination of drought stress and N addition. Our results provide mechanistic insight into the variable responses of xylem water transport to the interactions of drought and N availability.

Hydraulic conductance, hydraulic architecture, N f↗
DOE OSTI2026

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity

Accurate assessment of leaf functional traits is crucial for a diverse range of applications from crop phenotyping to parameterizing global climate models. Leaf reflectance spectroscopy offers a promising avenue to advance ecological and agricultural research by complementing traditional, time-consuming gas exchange measurements. However, the development of robust hyperspectral models for predicting leaf photosynthetic capacity and associated traits from reflectance data has been hindered by limited data availability across species and environments. Here we introduce the Global Spectra-Trait Initiative (GSTI), a collaborative repository of paired leaf hyperspectral and gas exchange measurements from diverse ecosystems. The GSTI repository currently encompasses over 7500 observations from 397 species and 41 sites gathered from 36 published and unpublished studies, thereby offering a key resource for developing and validating hyperspectral models of leaf photosynthetic capacity. The GSTI database is developed on GitHub (https://github.com/plantphys/gsti, last access: 4 January 2026) and published to ESS-DIVE https://doi.org/10.15485/2530733, Lamour et al., 2025). It includes gas exchange data, derived photosynthetic parameters, and key leaf traits often associated with traditional gas exchange measurements such as leaf mass per area and leaf elemental composition. By providing a standardized repository for data sharing and analysis, we present a critical step towards creating hyperspectral models for predicting photosynthetic traits and associated leaf traits for terrestrial plants.

Lamour, Julien [Université of Toulouse (France); U↗
DOE OSTI2020

Genome‐wide association study of multiple yield traits in a diversity panel of polyploid sugarcane ( Saccharum spp.)

Abstract Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of sugar and approximately 60% of biofuel globally. To meet the increased demand for sugar and biofuel supplies, it is critical to breed sugarcane cultivars with robust performance in yield traits. Therefore, dissection of causal DNA sequence variants is of great importance, as it provides genetic resources and fundamental information for crop improvement. In this study, we analyzed nine yield traits in a sugarcane diversity panel consisting of 308 accessions primarily selected from the World Collection of Sugarcane and Related Grasses. By genotyping the diversity panel via target enrichment sequencing, we identified a large number of sequence variants. Genome‐wide association studies between the markers and traits were conducted, taking dosages and gene actions into consideration. In total, 217 nonredundant markers and 225 candidate genes were identified to be significantly associated with the yield traits, which can serve as a comprehensive genetic resource database for future gene identification, characterization, and selection for sugarcane improvement. We further investigated runs of homozygosity (ROH) in the sugarcane diversity panel. We characterized 282 ROHs and found that the occurrence of ROHs in the genome were nonrandom and probably under selection. The ROHs were associated with total weight and dry weight, and high ROHs resulted in a decrease in the two traits. This study suggests that genomic inbreeding has led to negative impacts on sugarcane yield.

Yang, Xiping↗
DOE OSTI2020

Genome‐wide quantitative trait loci detection for biofuel traits in switchgrass ( Panicum virgatum L.)

Abstract Switchgrass ( Panicum virgatum L.) has been identified as a potential feedstock for cellulosic ethanol production in United States for its high biomass yield and adaptation to marginal lands. Composition of the cell wall plays an important role in bioethanol conversion. A total of 209 pseudo‐F 1 testcross progenies obtained from a biparental cross, AP13 × VS16, were grown at three locations from 2008 to 2011. Near‐infrared spectroscopy was used to estimate cell wall composition from biomass harvested at maturity. A linkage map of the pseudo‐F 1 testcross was constructed with 8,757 SNPs developed by genotyping‐by‐sequencing. Quantitative trait loci (QTL) analysis was performed on eight lignocellulosic traits, namely, klason lignin, sugar, glucose, xylose, hexose, ethanol, hexosoic ethanol, and cell wall ethanol conversion percentage. A total of 327 QTL were recorded for the eight lignocellulosic traits. We have identified 111 major regions in the switchgrass genome that underlie these lignocellulosic traits. Scanning of the genome sequence for genes flanking the QTL peaks, we identified 45 important genes that are involved in lignin biosynthesis, carbohydrate and sugar metabolism, and other biological and cellular functions. Identification of valuable genes associated with QTL along with pleotropic effects of the significant number of QTL suggests that simultaneous selection and genetic improvement of these traits are possible using marker‐assisted selection.

Ali, Shahjahan↗
DOE OSTI2025

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Mapping quantitative trait loci for seed traits in Camelina sativa

Camelina (Camelina sativa L. Crantz) is an oilseed crop that has great potential to provide sustainable feedstock for biofuel production and to improve dryland agriculture. A significant breeding objective for camelina is to increase seed size and oil content. Understanding the genetics behind variations of seed size and associated traits such as oil content would help breeders develop varieties of increased oil yield that are more robust, easier to plant and harvest, and better for oil pro- cessing. In this study, we developed a recombinant inbred population derived from the two camelina accessions, Suneson and Pryzeth, with contrasting traits, especially seed size and oil content. Using 189 lines, a genetic map was constructed containing 2376 single nucleotide polymorphism markers spanning 2034.6 cM of 20 linkage groups with an average density of 1.5 cM per locus. Field trials were conducted for 2 years (2017 and 2018) in two environments (dryland and irrigated) in Bozeman, Montana. The results revealed important correlations of seed size with other associated traits such as oil content, pod size and seed number per pod. Significant QTLs were also discovered for these traits. The findings of this study are the first step to isolate genes controlling seed development and oil accumulation and to develop advanced varieties of camelina better adapted to modern agriculture by marker-assisted breeding.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Genome mapping of quantitative trait loci (QTL) controlling domestication traits of intermediate wheatgrass ( Thinopyrum intermedium )

Allohexaploid (2n = 6x = 42) intermediate wheatgrass (Thinopyrum intermedium), abbreviated IWG, is an outcrossing perennial grass belonging to the tertiary gene pool of wheat. Perenniality would be valuable option for grain production, but attempts to introgress this complex trait from wheat-Thinopyrum hybrids have not been commercially successful. Efforts to breed IWG itself as a dual-purpose forage and grain crop have demonstrated useful progress and applications, but grain yields are significantly less than wheat. Therefore, genetic and physical maps have been developed to accelerate domestication of IWG. Herein, these maps were used to identify quantitative trait loci (QTLs) and candidate genes associated with IWG grain production traits in a family of 266 full-sib progenies derived from two heterozygous parents, M26 and M35. Transgressive segregation was observed for 17 traits related to seed size, shattering, threshing, inflorescence capacity, fertility, stem size, and flowering time. A total of 111 QTLs were detected in 36 different regions using 3826 genotype-by-sequence markers in 21 linkage groups. The most prominent QTL had a LOD score of 15 with synergistic effects of 29% and 22% over the family means for seed retention and percentage of naked seeds, respectively. Many QTLs aligned with one or more IWG gene models corresponding to 42 possible domestication orthogenes including the wheat Q and RHT genes. A cluster of seed-size and fertility QTLs showed possible alignment to a putative Z self-incompatibility gene, which could have detrimental grain-yield effects when genetic variability is low. Finally, these findings elucidate pathways and possible hurdles in the domestication of IWG.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

NGEE Arctic Plant Traits: Plant Aboveground Biomass, NPP and Traits, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, beginning 2016

Aboveground biomass was determined in twelve plots at the Kougarok hillslope site Kougarok Road, Mile Marker 64 (KG_MM64), Seward Peninsula, Alaska, from samples collected in late July of 2016. The sampled plots were located across six ecotypes present at this site (n=2 replicates per ecotype). Methods employed included destructive harvests to sample understory species (Understory Clip plots) and shrub surveys combined with existing allometric relationships to determine the aboveground biomass of tall shrub species (Shrub Clip Plots). Current year leaves and stems were separated to quantify net primary production of leaves and stems. This data package contains two CSV data files, one pdf and one zip file.The October 2020 update (*.v3) now provides of aboveground biomass and net primary production data (NPP) by plant species and tissue type. The initial release (*.v2) reported just aboveground biomass by plant functional type. Both versions are provided.Foliar specific leaf area, %C, %N, %P, d15N and d13C were measured on an array of vascular plant leaves collected at the Kougarok hillslope site starting in 2016. Leaves were collected during various plant harvests, including understory clip plots, shrub clip plots, nodule biomass plots, N fixation rate measurements and alder point-center-quarter transects. Paired observations from these harvests are also available through the NGEE Arctic data catalogue (see supplemental files).This October 2020 update (*v3) only removed the Ecotype column. No data were changed from initial release (*v2). Both versions are provided.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) 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↗