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At least 307 records · Page 17

Phenotyping stomatal closure by thermal imaging for GWAS and TWAS of water use efficiency-related genes

Abstract Stomata allow CO2 uptake by leaves for photosynthetic assimilation at the cost of water vapor loss to the atmosphere. The opening and closing of stomata in response to fluctuations in light intensity regulate CO2 and water fluxes and are essential for maintaining water-use efficiency (WUE). However, a little is known about the genetic basis for natural variation in stomatal movement, especially in C4 crops. This is partly because the stomatal response to a change in light intensity is difficult to measure at the scale required for association studies. Here, we used high-throughput thermal imaging to bypass the phenotyping bottleneck and assess 10 traits describing stomatal conductance (gs) before, during and after a stepwise decrease in light intensity for a diversity panel of 659 sorghum (Sorghum bicolor) accessions. Results from thermal imaging significantly correlated with photosynthetic gas exchange measurements. gs traits varied substantially across the population and were moderately heritable (h2 up to 0.72). An integrated genome-wide and transcriptome-wide association study identified candidate genes putatively driving variation in stomatal conductance traits. Of the 239 unique candidate genes identified with the greatest confidence, 77 were putative orthologs of Arabidopsis (Arabidopsis thaliana) genes related to functions implicated in WUE, including stomatal opening/closing (24 genes), stomatal/epidermal cell development (35 genes), leaf/vasculature development (12 genes), or chlorophyll metabolism/photosynthesis (8 genes). These findings demonstrate an approach to finding genotype-to-phenotype relationships for a challenging trait as well as candidate genes for further investigation of the genetic basis of WUE in a model C4 grass for bioenergy, food, and forage production.

54 ENVIRONMENTAL SCIENCES↗

Fungal community structure and function shifts with atmospheric nitrogen deposition

Fungal decomposition of soil organic matter depends on soil nitrogen (N) availability. This ecosystem process is being jeopardized by changes in N inputs that have resulted from a tripling of atmospheric N deposition in the last century. Soil fungi are impacted by atmospheric N deposition due to higher N availability, as soils are acidified, or as micronutrients become increasingly limiting. Fungal communities that persist with chronic N deposition may be enriched with traits that enable them to tolerate environmental stress, which may trade-off with traits enabling organic matter decomposition. We hypothesized that fungal communities would respond to N deposition by shifting community composition and functional gene abundances toward those that tolerate stress but are weak decomposers. We sampled soils at seven eastern US hardwood forests where ambient N deposition varied from 3.2 to 12.6 kg N ha -1 year -1 , five of which also have experimental plots where atmospheric N deposition was simulated through fertilizer application treatments (25–50 kg N ha -1 year -1 ). Fungal community and functional responses to fertilizer varied across the ambient N deposition gradient. Fungal biomass and richness increased with simulated N deposition at sites with low ambient deposition and decreased at sites with high ambient deposition. Fungal functional genes involved in hydrolysis of organic matter increased with ambient N deposition while genes involved in oxidation of organic matter decreased. One of four genes involved in generalized abiotic stress tolerance increased with ambient N deposition. In summary, we found that the divergent response to simulated N deposition depended on ambient N deposition levels. Fungal biomass, richness, and oxidative enzyme potential were reduced by N deposition where ambient N deposition was high suggesting fungal communities were pushed beyond an environmental stress threshold. Fungal community structure and function responses to N enrichment depended on ambient N deposition at a regional scale.

59 BASIC BIOLOGICAL SCIENCES↗

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↗

Phosphorus limitation of early growth differs between nitrogen‐fixing and nonfixing dry tropical forest tree species

Summary Tropical forests are often characterized by low soil phosphorus (P) availability, suggesting that P limits plant performance. However, how seedlings from different functional types respond to soil P availability is poorly known but important for understanding and modeling forest dynamics under changing environmental conditions. We grew four nitrogen (N)‐fixing Fabaceae and seven diverse non‐N‐fixing tropical dry forest tree species in a shade house under three P fertilization treatments and evaluated carbon (C) allocation responses, P demand, P‐use, investment in P acquisition traits, and correlations among P acquisition traits. Nitrogen fixers grew larger with increasing P addition in contrast to non‐N fixers, which showed fewer responses in C allocation and P use. Foliar P increased with P addition for both functional types, while P acquisition strategies did not vary among treatments but differed between functional types, with N fixers showing higher root phosphatase activity (RPA) than nonfixers. Growth responses suggest that N fixers are limited by P, but nonfixers may be limited by other resources. However, regardless of limitation, P acquisition traits such as mycorrhizal colonization and RPA were nonplastic across a steep P gradient. Differential limitation among plant functional types has implications for forest succession and earth system models.

59 BASIC BIOLOGICAL SCIENCES↗

Soil microbiome predictability increases with spatial and taxonomic scale

Soil microorganisms shape ecosystem function, yet it remains an open question whether we can predict the composition of the soil microbiome in places before observing it. Furthermore, it is unclear whether the predictability of microbial life exhibits taxonomic- and spatial-scale dependence, as it does for macrobiological communities. Here, we leverage multiple large-scale soil microbiome surveys to develop predictive models of bacterial and fungal community composition in soil, then test these models against independent soil microbial community surveys from across the continental United States. We find remark- able scale dependence in community predictability. The predictability of bacterial and fungal communities increases with the spatial scale of observation, and fungal predictability increases with taxonomic scale. These patterns suggest that there is an increasing importance of deterministic versus stochastic processes with scale, consistent with findings in plant and animal communities, suggesting a general scaling relationship across biology. Biogeochemical functional groups and high-level taxonomic groups of microorganisms were equally predictable, indicating that traits and taxonomy are both powerful lenses for understanding soil communities. Here, by focusing on out-of-sample prediction, these findings suggest an emerging generality in our understanding of the soil microbiome, and that this understanding is fundamentally scale dependent

Biogeography↗

A common resequencing‐based genetic marker data set for global maize diversity

SUMMARY Maize ( Zea mays ssp. mays ) populations exhibit vast ranges of genetic and phenotypic diversity. As sequencing costs have declined, an increasing number of projects have sought to measure genetic differences between and within maize populations using whole‐genome resequencing strategies, identifying millions of segregating single‐nucleotide polymorphisms (SNPs) and insertions/deletions (InDels). Unlike older genotyping strategies like microarrays and genotyping by sequencing, resequencing should, in principle, frequently identify and score common genetic variants. However, in practice, different projects frequently employ different analytical pipelines, often employ different reference genome assemblies and consistently filter for minor allele frequency within the study population. This constrains the potential to reuse and remix data on genetic diversity generated from different projects to address new biological questions in new ways. Here, we employ resequencing data from 1276 previously published maize samples and 239 newly resequenced maize samples to generate a single unified marker set of approximately 366 million segregating variants and approximately 46 million high‐confidence variants scored across crop wild relatives, landraces as well as tropical and temperate lines from different breeding eras. We demonstrate that the new variant set provides increased power to identify known causal flowering‐time genes using previously published trait data sets, as well as the potential to track changes in the frequency of functionally distinct alleles across the global distribution of modern maize.

59 BASIC BIOLOGICAL SCIENCES↗

Dynamic microbial assembly processes correspond to soil fertility in sustainable paddy agroecosystems

1. Microorganisms underpin the sustainability of agroecosystems, but we have a poor understanding of how the assembly processes that govern microbial community structure interact through time to maintain soil fertility. 2. Ancient rice paddies have a history of cultivation spanning hundreds or thousands of years and provide an ideal opportunity to explore relationships between community assembly processes and long-term agroecosystem sustainability. We used statistical null models to evaluate temporal patterns of bacterial community assembly processes across rice cultivation years and their associations with increases in soil fertility in paddy agroecosystems. 3. We found that stochasticity was a persistent force structuring paddy soil microbial communities, putatively due to frequent flooding that facilities dispersal. However, determinism gradually increased over centuries of agriculture and corresponded to increases in soil fertility. Accordingly, multifunctionality, calculated using enzymes catalyzing key soil functions in carbon, nitrogen, phosphorous and sulfur cycling significantly increased along rice cultivation years. We therefore propose that balanced assembly processes preserve a diverse array of traits that can dominate under various circumstances (stochasticity) while allowing for traits relevant to soil fertility to be selected for by soil fertility (determinism), thus supporting multifunctionality that underlies sustainable agroecosystems. 4. In total, our results highlight that knowledge on temporal microbial assembly processes, community composition, and ecological function in context of soil fertility is key to understanding ecological mechanisms maintaining agroecosystems sustainability.

Liu, Wenjing↗

Sulfated Zirconium Metal–Organic Frameworks as Well-Defined Supports for Enhancing Organometallic Catalysis

Understanding heterogeneous catalysts is a challenging pursuit due to surface site nonuniformity and aperiodicity in traditionally-used materials. One example is sulfated metal oxides, which function as highly-active catalysts and as supports for organometallic complexes. These applications are due to traits such as acidity, ability to act as a weakly coordinating ligand, and aptitude for promoting transformations via radical cation intermediates. Research is ongoing about the structural features of sulfated metal oxides that imbue the aforementioned properties, such as sulfate geometry and coordination. To better understand these materials, metal–organic frameworks (MOFs) have been targeted as structurally-defined analogs. Composed of inorganic nodes and organic linkers, MOFs possess features such as high porosity and crystallinity, which make them attractive for mechanistic studies of heterogeneous catalysts. In this work, a Zr 6 -based MOF NU-1000 is sulfated and characterized using atomically-precise techniques such as single crystal X-ray diffraction (SCXRD) in addition to diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Here, the dynamic nature of the sulfate binding motif is found to transition from monodentate, to bidentate, to tridentate depending on the degree of hydration, as supported by density functional theory (DFT) calculations. Heightened Brønsted acidity compared to the parent MOF was observed upon sulfation, and probed through trimethylphosphine oxide (TMPO) physisorption, ammonia sorption, in-situ ammonia DRIFTS, and DFT studies. With the support structure benchmarked, an organoiridium complex was chemisorbed onto the sulfated MOF node and the efficacy of this supported catalyst was demonstrated for stoichiometric and catalytic activation of benzene-d6 and toluene with structure-activity relationships derived.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data and scripts associated with a manuscript modeling microbial regulation of priming effects

This data package is associated with the publication “Modeling Microbial Regulatory Feedback in Organic Matter Decomposition Identifies Copiotrophic Traits as Key Drivers of Positive Priming” published as a preprint on BioRXiv by Ahamed et al. (2026); https://doi.org/10.1101/2024.08.11.607483. The package contains MATLAB scripts and saved simulation outputs used to implement a cybernetic model of microbial regulation during complex organic matter (OM) decomposition governing priming effects. It includes models of (i) single microbial functional groups (copiotrophic or oligotrophic degraders) and (ii) binary consortia composed of degraders and non-degraders with contrasting or common growth traits. Simulation results were generated using Monte Carlo analyses, with randomized key model parameters across a range of environmental mixing fractions of complex and labile OM. The dataset was created to provide a transparent and reusable computational framework for systematically exploring how microbial growth traits, metabolic regulation, and community composition influence OM decomposition dynamics and priming effects. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes the variable definitions. This package includes: (1) annotated MATLAB code implementing the system of ordinary differential equations and cybernetic control laws; (2) saved output files containing data (e.g., biomass, substrates, enzyme levels, priming metrics); and (3) scripts for processing saved outputs and regenerating figures. Specifically, the data package contains three main MATLAB scripts: runPrimingModel.m, runPlotData.m, and runPlotSuppFigS1.m, along with this readme and supporting documentation. Users should begin with runPrimingModel.m, which contains the annotated code implementing the system of ordinary differential equations and cybernetic control laws. This script runs the Monte Carlo simulations of microbial OM decomposition and allows users to modify microbial trait definitions, adjust parameter distributions, or define new community configurations. Simulation outputs are automatically saved as .mat files in the folder named SavedData, which stores all pre-generated results included in this package. The second script, runPlotData.m, reads files from the SavedData folder and processes them to regenerate the figures presented in the manuscript. The third script, runPlotSuppFigS1.m, specifically generates Figure S1 in the Supplementary Material of the manuscript. The package also includes the aforementioned files in non-proprietary .txt format. If users intend to use them, they should first save the files in their respective .m or .mat formats prior to execution in MATLAB.

Biomass concentration↗

Small Signaling Peptides in Sorghum bicolor : Integrating Phylogeny and Gene Expression to Characterize Roles in Stem Development

Small signaling peptides (SSPs) are important regulators of plant growth, development, and responses to biotic and abiotic stress, yet their role in the C4 grass Sorghum bicolor is largely uncharacterized. To help fill this knowledge gap, 219 sorghum genes that encode SSPs were identified based on SSP sequences previously identified in Arabidopsis thaliana, Zea mays, Oryza sativa, Triticum aestivum , and Brachypodium distachyon . The 219 sorghum SSP-encoding genes were assigned to 19 gene families, analyzed for the presence of motifs, and aligned with genes that encode SSPs in other plants using phylogenetic analysis. Sorghum genes in 12 of the 19 SSP gene families had not been previously characterized. Expression of the 219 SSP-encoding genes in sorghum organs, during stem development, and in stem tissues and cell types revealed distinct spatial, temporal, and developmental patterns of expression. Genes associated with the SbCEP and SbRGF families were preferentially expressed in roots, whereas SbEPF genes were expressed in stem epidermal and pith parenchyma cells and panicles. The expression of genes during bioenergy sorghum stem growth and development was investigated because stems account for ~80% of harvested biomass and serve as conduits for water and nutrient transport between leaves and roots. During stem development, 28 SSP genes in several families ( CLE, EPF, CEP, GASS, PSY, ES, PSK, CAPE, POE ) were expressed at higher levels in zones of cell proliferation. For example, the TDIF homologs SbCLE41 and SbCLE42 were expressed at high levels in nascent stem nodes where they may regulate vascular bundle cambial activity and cell differentiation. A different set of 15 genes in the CIF, POE, CAPE, PSY, CEP, RALF , and CLE families were expressed at higher levels in zones of stem tissue differentiation highlighted by elevated expression of five SbRALFR s in the stem nodal plexus. Cell type–specific expression of many sorghum genes that encode SSPs was observed in fully elongated internodes indicating gene expression is regulated with high spatial resolution. Overall, the results provide a foundation of information for analysis of SSP function in sorghum that can be integrated with knowledge of sorghum gene regulatory networks to modulate traits important for production of sorghum crops.

bioenergy sorghum↗

Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle

By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testisspecific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.

59 BASIC BIOLOGICAL SCIENCES↗

Morphological traits for allometric scaling of the European Sea Bass Dicentrarchus labrax (Linnaeus, 1758) from Southern Portugal population

Abstract The present study aimed to determine the allometric scaling among a selection of morphological traits in European sea bass ( Dicentrarchus labrax ) to estimate fish body weight. A set of morphological traits (fish body weight, length, height, and width) were directly measured in 146 fish of a recirculating aquaculture system, with body weights ranging from 17.11 to 652.21 g. In addition, a collection of digital imagery of each anesthetized fish from the side and top views were used to estimate other traits (indirect measures). Multiple regression analysis and regression coefficients were calculated using all possible combinations of biometric data (predictors) to estimate fish body weight, applying different numerical fitting models (linear, log‐linear, quadratic, exponential). The results showed that the best combination of traits for estimating fish body weight were fish body width, length and height, collected from direct measure ( R 2 = 0.995), for a log‐linear model fitting, which revealed more accurate determinations than the most commonly used length–weight relationship. Nevertheless, other combinations of morphological traits and fitting models were also found to be suitable in successfully predict fish body weight, with variability ranging between 92.5% and 98.5%. For indirect measures, the best predictor was a combination of traits from top view (width, eye distance and area without fins) fitted with a log‐linear function. These results comprise a relevant baseline in supporting the high potential of noninvasive methods to accurately follow the growth of European sea bass juveniles, recurring to imagery analysis of anesthetized fish. It has major potential applications in feeding consumption trials and fish growth models, as it allows for continuously following up fish growth under different experimental conditions without therein distress derived from manipulation.

Azevedo, Ana↗

Few-shot leaf segmentation

In this work, we use few-shot learning to segment the body and vein architecture of Populus 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, 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.

Lagergren, John [Oak Ridge National Lab. (ORNL), O↗

Plant Growth Promotion Diversity in Switchgrass-Colonizing, Diazotrophic Endophytes

Endophytic nitrogen-fixing (diazotrophic) bacteria are essential members of the microbiome of switchgrass ( Panicum virgatum ), considered to be an important commodity crop in bioenergy production. While endophytic diazotrophs are known to provide fixed atmospheric nitrogen to their host plant, there are many other plant growth-promoting (PGP) capabilities of these organisms to be demonstrated. The diversity of PGP traits across different taxa of switchgrass-colonizing endophytes is understudied, yet critical for understanding endophytic function and improving cultivation methods of important commodity crops. Here, we present the isolation and characterization of three diazotrophic endophytes: Azospirillum agricola R1C, Klebsiella variicola F10Cl, and Raoultella terrigena R1Gly. Strains R1C and F10Cl were isolated from switchgrass and strain R1Gly, while isolated from tobacco, is demonstrated herein to colonize switchgrass. Each strain exhibited highly diverse genomic and phenotypic PGP capabilities. Strain F10Cl and R1Gly demonstrated the highest functional similarity, suggesting that, while endophyte community structure may vary widely based on host species, differences in functional diversity are not a clearly delineated. The results of this study advance our understanding of diazotrophic endophyte diversity, which will allow us to design robust strategies to improve cultivation methods of many economically important commodity crops.

59 BASIC BIOLOGICAL SCIENCES↗

At least it is a dry cold: the global distribution of freeze–thaw and drought stress and the traits that may impart poly-tolerance in conifers

Abstract Conifers inhabit some of the most challenging landscapes where multiple abiotic stressors (e.g., aridity, freezing temperatures) often co-occur. Physiological tolerance to multiple stressors (‘poly-tolerance’) is thought to be rare because exposure to one stress generally limits responses to another through functional trade-offs. However, the capacity to exhibit poly-tolerance may be greater when combined abiotic stressors have similar physiological impacts, such as the disruption of hydraulic function imposed by drought or freezing. Here, we reviewed empirical data in light of theoretical expectations for conifer adaptations to drought and freeze–thaw cycles with particular attention to hydraulic traits of the stem and leaf. Additionally, we examined the commonality and spatial distribution of poly-stress along indices of these combined stressors. We found that locations with the highest values of our poly-stress index (PSi) are characterized by moderate drought and moderate freeze–thaw, and most of the global conifer distribution occupies areas of moderate poly-stress. Among traits examined, we found diverse responses to the stressors. Turgor loss point did not correlate with freeze–thaw or drought stress individually, but did with the PSi, albeit inverse to what was hypothesized. Leaf mass per area was more strongly linked with drought stress than the poly-stress and not at all with freeze–thaw stress. In stems, the water potential causing 50% loss of hydraulic conductivity became more negative with increasing drought stress and poly-stress but did not correlate with freeze–thaw stress. For these traits, we identified a striking lack of coverage for substantial portions of species ranges, particularly at the upper boundaries of their respective PSis, demonstrating a critical gap in our understanding of trait prevalence and plasticity along these stress gradients. Future research should investigate traits that confer tolerance to both freeze–thaw and drought stress in a wide range of species across broad geographic scales.

54 ENVIRONMENTAL SCIENCES↗

RNAi and genome editing of sugarcane: Progress and prospects

SUMMARY Sugarcane, which provides 80% of global table sugar and 40% of biofuel, presents unique breeding challenges due to its highly polyploid, heterozygous, and frequently aneuploid genome. Significant progress has been made in developing genetic resources, including the recently completed reference genome of the sugarcane cultivar R570 and pan‐genomic resources from sorghum, a closely related diploid species. Biotechnological approaches including RNA interference (RNAi), overexpression of transgenes, and gene editing technologies offer promising avenues for accelerating sugarcane improvement. These methods have successfully targeted genes involved in important traits such as sucrose accumulation, lignin biosynthesis, biomass oil accumulation, and stress response. One of the main transformation methods—biolistic gene transfer or Agrobacterium ‐mediated transformation—coupled with efficient tissue culture protocols, is typically used for implementing these biotechnology approaches. Emerging technologies show promise for overcoming current limitations. The use of morphogenic genes can help address genotype constraints and improve transformation efficiency. Tissue culture‐free technologies, such as spray‐induced gene silencing, virus‐induced gene silencing, or virus‐induced gene editing, offer potential for accelerating functional genomics studies. Additionally, novel approaches including base and prime editing, orthogonal synthetic transcription factors, and synthetic directed evolution present opportunities for enhancing sugarcane traits. These advances collectively aim to improve sugarcane's efficiency as a crop for both sugar and biofuel production. This review aims to discuss the progress made in sugarcane methodologies, with a focus on RNAi and gene editing approaches, how RNAi can be used to inform functional gene targets, and future improvements and applications.

Brant, Eleanor [Agronomy Department, Plant Molecul↗

Phosphoribosylpyrophosphate synthetase as a metabolic valve advances Methylobacterium/Methylorubrum phyllosphere colonization and plant growth

The proficiency of phyllosphere microbiomes in efficiently utilizing plant-provided nutrients is pivotal for their successful colonization of plants. The methylotrophic capabilities of Methylobacterium/Methylorubrum play a crucial role in this process. However, the precise mechanisms facilitating efficient colonization remain elusive. In the present study, we investigate the significance of methanol assimilation in shaping the success of mutualistic relationships between methylotrophs and plants. A set of strains originating from Methylorubrum extorquens AM1 are subjected to evolutionary pressures to thrive under low methanol conditions. A mutation in the phosphoribosylpyrophosphate synthetase gene is identified, which converts it into a metabolic valve. This valve redirects limited C1-carbon resources towards the synthesis of biomass by up-regulating a non-essential phosphoketolase pathway. These newly acquired bacterial traits demonstrate superior colonization capabilities, even at low abundance, leading to increased growth of inoculated plants. This function is prevalent in Methylobacterium/Methylorubrum strains. In summary, our findings offer insights that could guide the selection of Methylobacterium/Methylorubrum strains for advantageous agricultural applications.

59 BASIC BIOLOGICAL SCIENCES↗

Assessing climate change impacts on live fuel moisture and wildfire risk using a hydrodynamic vegetation model

Abstract. Live fuel moisture content (LFMC) plays a critical role in wildfire dynamics, but little is known about responses of LFMC to multivariate climate change, e.g., warming temperature, CO2 fertilization, and altered precipitation patterns, leading to a limited prediction ability of future wildfire risks. Here, we use a hydrodynamic demographic vegetation model to estimate LFMC dynamics of chaparral shrubs, a dominant vegetation type in fire-prone southern California. We parameterize the model based on observed shrub allometry and hydraulic traits and evaluate the model's accuracy through comparisons between observed and simulated LFMC of three plant functional types (PFTs) under current climate conditions. Moreover, we estimate the number of days per year of LFMC below 79 % (which is a critical threshold for wildfire danger rating of southern California chaparral shrubs) from 1960 to 2099 for each PFT and compare the number of days below the threshold for medium and high greenhouse gas emission scenarios (RCP4.5 and 8.5). We find that climate change could lead to more days per year (5.2 %–14.8 % increase) with LFMC below 79 % between the historical (1960–1999) and future (2080–2099) periods, implying an increase in wildfire danger for chaparral shrubs in southern California. Under the high greenhouse gas emission scenario during the dry season, we find that the future LFMC reductions mainly result from a warming temperature, which leads to 9.1 %–18.6 % reduction in LFMC. Lower precipitation in the spring leads to a 6.3 %–8.1 % reduction in LFMC. The combined impacts of warming and precipitation change on fire season length are equal to the additive impacts of warming and precipitation change individually. Our results show that the CO2 fertilization will mitigate fire risk by causing a 3.5 %–4.8 % increase in LFMC. Our results suggest that multivariate climate change could cause a significant net reduction in LFMC and thus exacerbate future wildfire danger in chaparral shrub systems.

54 ENVIRONMENTAL SCIENCES↗