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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantitative and Predictive Genetic Parts for Plant Synthetic Biology

Plant synthetic biology aims to harness the natural abilities of plants and to turn them to new purposes. A primary goal of plant synthetic biology is to produce predictable and programmable genetic circuits from simple regulatory elements and well-characterized genetic components. The number of available DNA parts for plants is increasing, and the methods for rapid quantitative characterization are being developed, but the field of plant synthetic biology is still in its early stages. We here describe methods used to describe the quantitative properties of genetic components needed for plant synthetic biology. Once the quantitative properties and transfer function of a variety of genetic parts are known, computers can select the optimal components to assemble into functional devices, such as toggle switches and positive feedback circuits. However, while the variety of circuits and traits that can be put into plants are limitless, doing synthetic biology in plants poses unique challenges. Plants are composed of differentiated cells and tissues, each representing potentially unique regulatory or developmental contexts to introduced synthetic genetic circuits. Further, plants have evolved to be highly sensitive to environmental influences, such as light or temperature, any of which can affect the quantitative function of individual parts or whole circuits. Measuring the function of plant components within the context of a plant cell and, ideally, in a living plant, will be essential to using these components in gene circuits with predictable function. Mathematical modeling will be needed to account for the variety of contexts a genetic part will experience in different plant tissues or environments. With such understanding in hand, it may be possible to redesign plant traits to serve human and environmental needs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Root system architecture in cereals: progress, challenges and perspective

We report roots are essential multifunctional plant organs involved in water and nutrient uptake, metabolite storage, anchorage, mechanical support, and interaction with the soil environment. Understanding of this ‘hidden half’ provides potential for manipulation of root system architecture (RSA) traits to optimize resource use efficiency and grain yield in cereal crops. Unfortunately, root traits are highly neglected in breeding due to the challenges of phenotyping, but could have large rewards if the variability in RSA traits can be fully exploited. Until now, a plethora of genes have been characterized in detail for their potential role in improving RSA. The use of forward genetics approaches to find sequence variations in genes underpinning desirable RSA would be highly beneficial. Advances in computer vision applications have allowed image-based approaches for high-throughput phenotyping of RSA traits that can be used by any laboratory worldwide to make progress in understanding root function and dissection of the genetics. At the same time, the frontiers of root measurement include non-invasive methods like X-ray computer tomography and magnetic resonance imaging that facilitate new types of temporal studies. Root physiology and ecology are further supported by spatiotemporal root simulation modeling. The discovery of component traits providing improved resilience and yield advantage in target environments is a key necessity for mainstreaming root-based cereal breeding. The integrated use of pan-genome resources, now available in most cereals, coupled with new in-field phenotyping platforms has the potential for precise selection of superior genotypes with improved RSA.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Association mapping across a multitude of traits collected in diverse environments in maize

Abstract Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Assisted migration in a warmer and drier climate: less climate buffering capacity, less facilitation and more fires at temperate latitudes?

Assisted tree migration has been proposed as a conceptual solution to mitigate lags in biotic responses to anthropogenic climate change. The rationale behind this concept is that tree species currently growing under warmer and drier climates will be more resistant and resilient to the new climatic conditions than tree species naturally growing in currently wetter and colder climates. However, we hypothesize that, by being more stress‐tolerant to warmer and drier conditions, translocated species should exhibit different functional attributes, which could induce important ecological and societal costs and overcome the desired benefits of maintaining wood production and other ecosystem services. We used principal component analysis (PCA) to analyze variation in seven traits of 106 tree and tall shrub species from contrasting latitudinal distributions in western North America and Europe to predict the potential functional changes of forest ecosystems due to the translocation of tree species from low to high latitudes. We show that species from both continents differed primarily by their position on the leaf economy spectrum (LES) and their size traits. Even though, in Europe, differences in LES were significantly correlated to species southern latitudinal positions, in both continents differences in size traits were significantly correlated to latitude. These results suggest that assisted migration by translocating more conservative species of shorter stature in currently cooler climates should decrease the buffering capacity of forest canopies, decrease facilitation for understory species, and increase wildfire risks, whose effects have the potential to accelerate climate warming through negative atmospheric feedback processes. As an alternative solution to assisted migration that may accelerate rather than mitigate climate change, we recommend that foresters gradually diversify the vertical structure and layering of the existing forest canopy to maintain a sustainable water cycle and energy balance between the soil, the tree and the atmosphere without increasing the wildfire risk.

Environmental Sciences & Ecology↗
DOE OSTI2025

A stable 15-member bacterial SynCom promotes Brachypodium growth under drought stress

Introduction: Rhizosphere microbiomes are known to drive soil nutrient cycling and influence plant fitness during adverse environmental conditions. Field-derived robust Synthetic Communities (SynComs) of microbes mimicking the diversity of rhizosphere microbiomes can greatly advance a deeper understanding of such processes. However, assembling stable, genetically tractable, reproducible, and scalable SynComs remains challenging. Methods: Here, we present a systematic approach using a combination of network analysis and cultivation-guided methods to construct a 15-member SynCom from the rhizobiome of Brachypodium distachyon. This SynCom incorporates diverse strains from five bacterial phyla. Genomic analysis of the individual strains was performed to reveal encoded plant growth-promoting traits, including genes for the synthesis of osmoprotectants (trehalose and betaine) and Na+/K+ transporters, and some predicted traits were validated by laboratory phenotypic assays. Results: The SynCom demonstrates strong stability both in vitro and in planta. Most strains encoded multiple plant growth-promoting functions, and several of these were confirmed experimentally. The presence of osmoprotectant and ion transporter genes likely contributed to the observed resilience of Brachypodium to drought stress, where plants amended with the SynCom recovered better than those without. We further observed preferential colonization of SynCom strains around root tips under stress, likely due to active interactions between plant root metabolites and bacteria. Discussion: Our results demonstrate that trait-informed construction of synthetic communities can yield stable, functionally diverse consortia that enhance plant resilience under drought. Preferential colonization near root tips points to active, localized plant-microbe signaling as a component of stress-responsive recruitment. This stable SynCom provides a scalable platform for probing mechanisms of plant-microbe interaction and for developing microbiome-based strategies to improve soil and crop performance in variable environments.

Yadav, Archana↗
DOE OSTI2020

Fire as a fundamental ecological process: Research advances and frontiers

Fire is a powerful ecological and evolutionary force that regulates organismal traits, population sizes, species interactions, community composition, carbon and nutrient cycling and ecosystem function. It also presents a rapidly growing societal challenge, due to both increasingly destructive wildfires and fire exclusion in fire–dependent ecosystems. As an ecological process, fire integrates complex feedbacks among biological, social and geophysical processes, requiring coordination across several fields and scales of study. Here, we describe the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth. We explore research priorities in six categories of fire ecology: (a) characteristics of fire regimes, (b) changing fire regimes, (c) fire effects on above–ground ecology, (d) fire effects on below–ground ecology, (e) fire behaviour and (f) fire ecology modelling. We identify three emergent themes: the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts. As fire regimes and our relationships with fire continue to change, prioritizing these research areas will facilitate understanding of the ecological causes and consequences of future fires and rethinking fire management alternatives.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Supporting information for Few-Shot Learning Enables Population-Scale Analysis of Leaf Traits in Populus trichocarpa

In this work, we use few-shot learning to segment the body and vein architecture of P. trichocarpa leaves from high-resolution scans obtained in the UC Davis common garden. Leaf and vein segmentation are formulated as separate tasks, in which convolutional neural networks (CNNs) are used to iteratively expand partial segmentations until reaching stopping criteria. Our leaf and vein segmentation approaches use just 50 and 8 manually traced images for training, respectively, and are applied to a set of 2,634 top and bottom leaf scans. We show that both methods achieve high segmentation accuracy, in some cases exceeding even human-level segmentation. The leaf and vein segmentations are subsequently used to extract 68 morphological traits using traditional open-source image processing tools, which are validated using real-world physical measurements. For a biological perspective, we perform a genome-wide association study using the vein density trait to discover novel genetic architectures associated with multiple physiological processes relating to leaf development and function. In addition to sharing all of the few-shot learning code (see https://github.com/jlager/few-shot-leaf-segmentation), we are releasing all images, manual segmentations, model predictions, 68 extracted leaf phenotypes, and a new set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes. The data folder includes all images, ground truth segmentations, predicted segmentations, and extracted leaf traits. All images encode the sample ID in the file name by indicating the treatment, block, row, position, and leaf side, respectively. For example, the file, C_1_1_2_bot.jpeg, indicates the control treatment, block 1, row 1, position 2, and the bottom side of the leaf. Tabulated results include position IDs as well as the corresponding genotype IDs. The images folder includes the 2,906 high-resolution leaf scans taken in the field. The leaf_masks folder includes 50 ground truth segmentations used for training the leaf tracing algorithm. The leaf_preds folder includes the 2,906 predicted segmentations from the leaf tracing algorithm. The vein_masks folder includes 8 ground truth segmentations used for training the vein growing algorithm. The vein_preds folder includes the 1,453 predicted segmentations from the vein growing algorithm. The vein_probs folder includes the 1,453 predicted probability maps from the vein growing algorithm before thresholding. The genomes folder includes the set of SNPs called against the v4 P. trichocarpa genome for 1,419 genotypes with a README file detailing the steps taken. The results folder includes: (i) raw values of the 68 predicted leaf traits in digital_traits.tsv, (ii) manually measured values of petiole length and width in manual_traits.tsv, (iii) thin plate spline (TPS) adjusted values of the vein density trait in vein_density_tps_adj.tsv, (iv) best linear unbiased prediction (BLUP) adjusted values of the vein density trait in vein_density_blups.tsv, and (v) GWAS results for the vein density trait, including chromosome positions and corresponding P values, in gwas_results.csv.

09 BIOMASS FUELS↗
DOE OSTI2024

A systems genetic analysis identifies putative mechanisms and candidate genes regulating vessel traits in poplar wood

Wood is the water conducting tissue of tree stems. Like most angiosperm trees, poplar wood contains water-conducting vessel elements whose functional properties affect water transport and growth rates, as well as susceptibility to embolism and hydraulic failure during water stress and drought. Here we used a unique hybrid poplar pedigree carrying genomically characterized chromosomal insertions and deletions to undertake a systems genomics analysis of vessel traits. We assayed gene expression in wood forming tissues from clonal replicates of genotypes covering dosage quantitative trait loci with insertions and deletions, genotypes with extreme vessel trait phenotypes, and control genotypes. A gene co-expression analysis was used to assign genes to modules, which were then used in integrative analyses to identify modules associated with traits, to identify putative molecular and cellular processes associated with each module, and finally to identify candidate genes using multiple criteria including dosage responsiveness. These analyses identified known processes associated with vessel traits including stress response, abscisic acid and cell wall biosynthesis, and in addition identified previously unexplored processes including cell cycle and protein ubiquitination. We discuss our findings relative to component processes contributing to vessel trait variation including signaling, cell cycle, cell expansion, and cell differentiation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Significance of lysogeny for the metabolism of Desulfovibrio spp. strains isolated from aquatic environments of Georgia

Sulphate-reducing bacteria (SRB) are ecologically important group of anaerobic micro-organisms that can reduce sulphate to form hydrogen sulphide-a toxic gas causing iron corrosion on metal surfaces. In this work, SRB strains were isolated from aquatic environments in the country of Georgia to determine their lysogenicity and the role of temperate phages in host metabolism. SRB strains were isolated in samples from the Black Sea coast of Georgia. Based on their genetic, cytological and physiological properties of bacteria, 10 Georgian isolates were assigned to the genus Desulfovibrio. Temperate bacteriophages were induced from three out of ten strains by UV-exposure. Comparison of metal (Fe and Cr) reduction and utilization of various carbon sources by the wild-type (lysogenic) bacterial strains and their UV-irradiated counterparts was done. Temperate phage in the cells of SRB could alter significant functions of bacteria and may have a contribution in the acquisition of different traits by SRB. This article pointed to a significant role for temperate bacteriophages in the metabolism and metabolic potential of host strains of SRB, which were first isolated from the aquatic environment of Georgia.

temperate phage↗
DOE OSTI2023

Automating methods for estimating metabolite volatility

The volatility of metabolites can influence their biological roles and inform optimal methods for their detection. Yet, volatility information is not readily available for the large number of described metabolites, limiting the exploration of volatility as a fundamental trait of metabolites. Here, we adapted methods to estimate vapor pressure from the functional group composition of individual molecules (SIMPOL.1) to predict the gas-phase partitioning of compounds in different environments. We implemented these methods in a new open pipeline called volcalc that uses chemoinformatic tools to automate these volatility estimates for all metabolites in an extensive and continuously updated pathway database: the Kyoto Encyclopedia of Genes and Genomes (KEGG) that connects metabolites, organisms, and reactions. We first benchmark the automated pipeline against a manually curated data set and show that the same category of volatility (e.g., nonvolatile, low, moderate, high) is predicted for 93% of compounds. We then demonstrate how volcalc might be used to generate and test hypotheses about the role of volatility in biological systems and organisms. Specifically, we estimate that 3.4 and 26.6% of compounds in KEGG have high volatility depending on the environment (soil vs. clean atmosphere, respectively) and that a core set of volatiles is shared among all domains of life (30%) with the largest proportion of kingdom-specific volatiles identified in bacteria. With volcalc , we lay a foundation for uncovering the role of the volatilome using an approach that is easily integrated with other bioinformatic pipelines and can be continually refined to consider additional dimensions to volatility. The volcalc package is an accessible tool to help design and test hypotheses on volatile metabolites and their unique roles in biological systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

EcoSpec: Highly Equipped Tower-Based Hyperspectral and Thermal Infrared Automatic Remote Sensing System for Investigating Plant Responses to Environmental Changes

Despite an advanced ability to forecast ecosystem functions and climate at regional and global scales, little is known about relationships between local variations in water and carbon fluxes and large-scale phenomena. To enable data collection of local-scale ecosystem functions to support such investigations, we developed the EcoSpec system, a highly equipped remote sensing system that houses a hyperspectral radiometer (350–2500 nm) and five optical and infrared sensors in a compact tower. Its custom software controls the sequence and timing of movement of the sensors and system components and collects measurements at 12 locations around the tower. The data collected using the system was processed to remove sun-angle effects, and spectral vegetation indices computed from the data (i.e., the Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Photochemical Reflectance Index (PRI), and Moisture Stress Index (MSI)) were compared with the fraction of photochemically active radiation (fPAR) and canopy temperature. The results showed that the NDVI, NDWI, and PRI were strongly correlated with fPAR; the MSI was correlated with canopy temperature at the diurnal scale. These correlations suggest that this type of near-surface remote sensing system would complement existing observatories to validate satellite remote sensing observations and link local and large-scale phenomena to improve our ability to forecast ecosystem functions and climate. The system is also relevant for precision agriculture to study crop growth, detect disease and pests, and compare traits of cultivars.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Effects of root litter traits on soil organic matter dynamics depend on decay stage and root branching order

Decaying roots contribute disproportionately to soil organic carbon (SOC) stocks in many ecosystems, yet few studies have examined the afterlife effects of root trait variability on the formation, stability and mineralization of SOC. In order to assess how root functional class (absorptive vs. transport) and mycorrhizal association (ectomycorrhizal vs. arbuscular mycorrhizal fungi) affect both formation and loss of SOC, we decayed lower-order absorptive (orders 1–2) and higher-order transport (orders 3–4) roots from six arbuscular mycorrhizal (AM) and six ectomycorrhizal (EcM) associated hardwood tree species in an isotopically distinct soil under laboratory conditions. We found that root litter effects on SOC differed significantly among root functional classes and mycorrhizal types. AM absorptive and transport roots (high in nitrogen and soluble compounds) contributed more to the formation of new mineral-associated organic carbon (MAOC), but also contributed to higher mineralization of native SOC (via priming effects). Moreover, absorptive AM roots formed MAOC gradually and rates saturated, whereas ECM roots formed MAOC more quickly, despite slower decay (via greater formation efficiency). Altogether, these findings demonstrate how different combinations of root traits might contribute to soil C balance, and that failure to account for the chemical and morphological heterogeneity of roots, as well their interactions with microbes over time, may lead to incorrect projections of SOC stocks and turnover.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Climate-Driven Legacies in Simulated Microbial Communities Alter Litter Decomposition Rates

The mechanisms underlying diversity-functioning relationships have been a consistent area of inquiry in biogeochemistry since the 1950s. Though these mechanisms remain unresolved in soil microbiomes, many approaches at varying scales have pointed to the same notion—composition matters. Confronting the methodological challenge arising from the complexity of microbiomes, this study used the model DEMENTpy, a trait-based modeling framework, to explore trait-based drivers of microbiome-dependent litter decomposition. We parameterized DEMENTpy for five sites along a climate gradient in Southern California, United States, and conducted reciprocal transplant simulations analogous to a prior empirical study. The simulations demonstrated climate-dependent legacy effects of microbial communities on plant litter decomposition across the gradient. This result is consistent with the previous empirical study across the same gradient. An analysis of community-level traits further suggests that a 3-way tradeoff among resource acquisition, stress tolerance, and yield strategies influences community assembly. Simulated litter decomposition was predictable with two community traits (indicative of two of the three strategies) plus local environment, regardless of the system state (transient vs. equilibrium). Although more empirical confirmation is still needed, community traits plus local environmental factors (e.g., environment and litter chemistry) may robustly predict litter decomposition across spatial-temporal scales. In conclusion, this study offers a potential trait-based explanation for climate-dependent community effects on litter decomposition with implications for improved understanding of whole-ecosystem functioning across scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Wildfire impact on soil microbiome life history traits and roles in ecosystem carbon cycling

Abstract Wildfires, which are increasing in frequency and severity with climate change, reduce soil microbial biomass and alter microbial community composition and function. The soil microbiome plays a vital role in carbon (C) and nitrogen (N) cycling, but its complexity makes it challenging to predict post-wildfire soil microbial dynamics and resulting impacts on ecosystem biogeochemistry. The application of biogeochemically relevant conceptual trait-based frameworks to the soil microbiome can distill this complexity, enabling enhanced predictability of soil microbiome recovery following wildfire and subsequent impacts to biogeochemical cycles. Conceptual frameworks that have direct links to soil C and N cycling have been developed for the soil microbiome; the Y-A-S framework overviews soil microbiome life history strategies that have tradeoffs with one another and others have proposed frameworks specific to wildfire. Here, we aimed to delineate post-wildfire changes of bacterial traits in western US coniferous forests to inform how severe wildfire influences soil microbiome recovery and resultant biogeochemical cycling. We utilized a comprehensive metagenome-assembled genome catalog from post-wildfire soils representing 1 to 11 years following low- and high-severity burning to identify traits that enable the persistence of microbial taxa in burned soils and influence ecosystem C and N cycling. We found that high-severity wildfire initially selects for fast growers and, up to a decade post-fire, taxa that invest in genes for acquiring diverse resources from the external environment, which in combination could increase soil C losses. This work begins to disentangle how climate change–induced shifts in wildfire behavior might alter microbially mediated soil biogeochemical cycling.

Nelson, Amelia R.↗
DOE OSTI2024

Halophytes and heavy metals: A multi‐omics approach to understand the role of gene and genome duplication in the abiotic stress tolerance of Cakile maritima

Abstract Premise The origin of diversity is a fundamental biological question. Gene duplications are one mechanism that provides raw material for the emergence of novel traits, but evolutionary outcomes depend on which genes are retained and how they become functionalized. Yet, following different duplication types (polyploidy and tandem duplication), the events driving gene retention and functionalization remain poorly understood. Here we usedCakile maritima, a species that is tolerant to salt and heavy metals and shares an ancient whole‐genome triplication with closely related salt‐sensitive mustard crops (Brassica), as a model to explore the evolution of abiotic stress tolerance following polyploidy. Methods Using a combination of ionomics, free amino acid profiling, and comparative genomics, we characterize aspects of salt stress response inC. maritimaand identify retained duplicate genes that have likely enabled adaptation to salt and mild levels of cadmium. Results Cakile maritimais tolerant to both cadmium and salt treatments through uptake of cadmium in the roots. Proline constitutes greater than 30% of the free amino acid pool inC. maritimaand likely contributes to abiotic stress tolerance. We find duplicated gene families are enriched in metabolic and transport processes and identify key transport genes that may be involved inC. maritimaabiotic stress tolerance. Conclusions These findings identify pathways and genes that could be used to enhance plant resilience and provide a putative understanding of the roles of duplication types and retention on the evolution of abiotic stress response.

Plant Sciences↗
DOE OSTI2021

Targeted DNA insertion in plants

Conventional methods of DNA sequence insertion into plants, using Agrobacterium -mediated transformation or microprojectile bombardment, result in the integration of the DNA at random sites in the genome. These plants may exhibit altered agronomic traits as a consequence of disruption or silencing of genes that serve a critical function. Also, genes of interest inserted at random sites are often not expressed at the desired level. For these reasons, targeted DNA insertion at suitable genomic sites in plants is a desirable alternative. In this paper we review approaches of targeted DNA insertion in plant genomes, discuss current technical challenges, and describe promising applications of targeted DNA insertion for crop genetic improvement.

Dong, Oliver Xiaoou↗
DOE OSTI2021

Global maximum carboxylation rate trait scaling in the Sheffield Dynamic Global Vegetation Model 1901-2012

This data package contains model output data and climate input data associated with the New Phytologist publication: Walker, A.P., Quaife, T., van Bodegom, P.M., De Kauwe, M.G., Keenan, T.F., Joiner, J., Lomas, M.R., MacBean, N., Xu, C., Yang, X., Woodward, F.I., 2017. The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production. New Phytologist 215, 1370–1386. https://doi.org/10.1111/nph.14623. This dataset contains maximum carboxylation rate at 25 ºC (Vcmax,25), Gross Primary Production (GPP), Net Biome Production (NBP), vegetation carbon, and soil carbon data from Sheffield Dynamic Global Vegetation Model (SDGVM) for multiple trait-scaling methods for scaling Vcmax,25 across Earth, and alternative instantaneous temperature scaling functions. Vcmax,25 values are mean top-leaf values taken during the growing seasons, which were defined as periods during which leaf area index (LAI) was greater than one. Vcmax,25 values were reported prior to scaling of Vcmax by water-stress or leaf-age. The attached metadata file (SDGVM_vcmax_dataset.docx) describes the methods used and explains the organization of data within the included .zip file. This metadata file is also included in PDF format.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.

54 ENVIRONMENTAL SCIENCES↗