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At least 37 records · Page 2

Integrating Arctic Plant Functional Types in a Land Surface Model Using Above‐ and Belowground Field Observations

Abstract Accurate simulations of high‐latitude ecosystems are critical for confident Earth system model (ESM) projections of carbon cycle feedbacks to global climate change. Land surface model components of ESMs, including the E3SM Land Model (ELM), simulate vegetation growth and ecosystem responses to changing climate and atmospheric CO 2 concentrations by grouping heterogeneous vegetation into like sets of plant functional types (PFTs). Many such models represent high‐latitude vegetation using only two PFTs (shrub and grass), thereby missing the diversity of vegetation growth forms and functional traits in the Arctic. Here, we use field observations of biomass and leaf traits across a gradient of plant communities on the Seward Peninsula in northwest Alaska to replace the original ELM configuration for the first time with nine Arctic‐specific PFTs. The newly developed PFTs include: (1) nonvascular mosses and lichens, (2) deciduous and evergreen shrubs of various height classes, including an alder PFT, (3) graminoids, and (4) forbs. Improvements relative to the original model configuration included greater belowground biomass allocation, persistent fine roots and rhizomes of nonwoody plants, and better representation of variability in total plant biomass across sites with varying plant communities and depth to bedrock. Simulations through 2100 using the RCP8.5 climate scenario and constant PFT fractional areas showed alder‐dominated plant communities gaining more biomass and lichen‐dominated communities gaining less biomass compared to default PFTs. Our results highlight how representing the diversity of arctic vegetation and confronting models with measurements from varied plant communities improves the representation of arctic vegetation in terrestrial ecosystem models.

54 ENVIRONMENTAL SCIENCES↗

Oxidative Deboronation of Boronic Acids by Hydrogen Peroxide in Planta Generates Borate for Cross-Linking of Rhamnogalacturonan II

Vascular plants require boron to cross-link the rhamnogalacturonan-II (RG-II) domain of pectin to form functional cell walls. Boronic acids, which form reversible esters with cis-diols like borate, have been proposed to influence RG-II cross-linking, though the mechanism remains unclear. We used suspension-cultured rose cells adapted to grow without boron to investigate the effect of boronic acids on RG-II dimerization. When grown with phenylboronic acid (PBA) as the sole boron source, nearly all RG-II was crosslinked, whereas methylboronic acid (MBA) only partially restored cross-linking. In contrast, in vitro assays showed that homogeneous RG-II monomers did not dimerize with alkyl or aryl boronic acids unless supplemented with hydrogen peroxide (H2O2), which oxidatively converts boronic acids to boric acid. Real-time NMR spectroscopy and density functional theory calculations provided insight into the reaction mechanism and energetics of oxidation respectively. Together, our data show that exogenous boronic acids are a source of boric acid for plants, and that the deboronation reaction generates aryl or alkyl alcohol byproducts that can undergo further chemical modification in planta. The fate and potential roles of these byproducts in planta remain to be determined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Biomass Demineralization: A Critical Need for Future Biorefineries

Biomass contains up to 14 essential elements that serve as nutrients for plant growth and development, including photosynthesis and enzyme functionalities. These elements in different chemical forms (e.g., minerals) constitute the inorganic fraction of biomass and can cause operational issues in thermal and biochemical biomass conversion technologies. In biomass gasification and pyrolysis processes, for instance, inorganics can cause fouling, tar formation, and corrosion. In catalytic and biochemical processes, inorganics can poison catalysts, alter biochemical pathways, and modify product yields and selectivity. This review provides an overview of the inorganic content in biomass feedstocks, the critical role inorganics play in plant biochemistry, the effect that inorganics have in various thermochemical and biochemical biomass conversion technologies, and different approaches to remove them from biomass. We provide recommendations for future research, focusing on developing technologies to effectively remove inorganics from biomass, using the inorganics to improve soil quality and for alternative applications, and designing biorefineries to convert demineralized biomass obtained from diverse sources.

09 - BIOMASS FUELS↗

Interactions between microbial diversity and substrate chemistry determine the fate of carbon in soil.

Microbial decomposition drives the transformation of plant-derived substrates into microbial products that form stable soil organic matter (SOM). Recent theories have posited that decomposition depends on an interaction between SOM chemistry with microbial diversity and resulting function. Here, we explicitly test these theories by coupling quantitative stable isotope probing and metabolomics to track the fate of 13C enriched substrates that vary in chemical composition as they are assimilated by microbes and transformed into new metabolic products in soil. We found that mycorrhizal-driven differences in forest nutrient economies (e.g., nutrient cycling, microbial competition) led to arbuscular mycorrhizal (AM) soils harboring greater micro8ial diversity than ectomycorrhizal (ECM) soils. When incubated with 13C enriched substrates, substrate type drove shifts in the identity of active decomposers and their metabolic products in the highly diverse AM soils. The decomposition pathways were more static in the less diverse, ECM soil. Importantly, the majority of these shifts were driven by taxa only present in the AM soil suggesting a strong link between microbial identity and specialized function. Collectively, these results highlight an important interaction between ecosystem-level processes and microbial diversity; whereby the identity and function of active decomposers impacts the composition of decomposition products that can form stable SOM.

Raczka, Nanette↗

Cynipid wasps systematically reprogram host metabolism and restructure cell walls in developing galls

Many insects have evolved the ability to manipulate plant growth to generate extraordinary structures called galls, in which insect larva can develop while being sheltered and feeding on the plant. In particular, cynipid (Hymenoptera: Cynipidae) wasps have evolved to form morphologically complex galls and generate an astonishing array of gall shapes, colors, and sizes. However, the biochemical basis underlying these remarkable cellular and developmental transformations remains poorly understood. A key determinant in plant cellular development is cell wall deposition that dictates the physical form and physiological function of newly developing cells, tissues, and organs. However, it is unclear to what degree cell walls are restructured to initiate and support the formation of new gall tissue. Here, we characterize the molecular alterations underlying gall development using a combination of metabolomic, histological, and biochemical techniques to elucidate how valley oak (Quercus lobata) leaf cells are reprogrammed to form galls. Strikingly, gall development involves an exceptionally coordinated spatial deposition of lignin and xylan to form de novo gall vasculature. Our results highlight how cynipid wasps can radically change the metabolite profile and restructure the cell wall to enable the formation of galls, providing insights into the mechanism of gall induction and the extent to which plants can be entirely reprogrammed to form unique structures and organs.

59 BASIC BIOLOGICAL SCIENCES↗

Forest tree growth is linked to mycorrhizal fungal composition and function across Europe

Most trees form symbioses with ectomycorrhizal fungi (EMF) which influence access to growth-limiting soil resources. Mesocosm experiments repeatedly show that EMF species differentially affect plant development, yet whether these effects ripple up to influence the growth of entire forests remains unknown. Here we tested the effects of EMF composition and functional genes relative to variation in well-known drivers of tree growth by combining paired molecular EMF surveys with high-resolution forest inventory data across 15 European countries. We show that EMF composition was linked to a three-fold difference in tree growth rate even when controlling for the primary abiotic drivers of tree growth. Fast tree growth was associated with EMF communities harboring high inorganic but low organic nitrogen acquisition gene proportions and EMF which form contact versus medium-distance fringe exploration types. These findings suggest that EMF composition is a strong bio-indicator of underlying drivers of tree growth and/or that variation of forest EMF communities causes differences in tree growth. While it may be too early to assign causality or directionality, our study is one of the first to link fine-scale variation within a key component of the forest microbiome to ecosystem functioning at a continental scale.

54 ENVIRONMENTAL SCIENCES↗

The multiple-function multi-input/multi-output digital controller system for the AFW wind-tunnel model

A real time multiple-function digital controller system was developed for the Active Flexible Wing (AFW) Program. The digital controller system (DCS) allowed simultaneous execution of two control laws: flutter suppression and either roll trim or a rolling maneuver load control. The DCS operated within, but independently of, a slower host operating system environment, at regulated speeds up to 200 Hz. It also coordinated the acquisition, storage, and transfer of data for near real time controller performance evaluation and both open- and closed-loop plant estimation. It synchronized the operation of four different processing units, allowing flexibility in the number, form, functionality, and order of control laws, and variability in the selection of the sensors and actuators employed. Most importantly, the DCS allowed for the successful demonstration of active flutter suppression to conditions approximately 26 percent (in dynamic pressure) above the open-loop boundary in cases when the model was fixed in roll and up to 23 percent when it was free to roll. Aggressive roll maneuvers with load control were achieved above the flutter boundary. The purpose here is to present the development, validation, and wind tunnel testing of this multiple-function digital controller system.

Hoadley, Sherwood T.↗

The multiple-function multi-input/multi-output digital controller system for the AFW wind tunnel model

A real-time multiple-function digital controller system was developed for the Active Flexible Wing (AFW) Program. The digital controller system (DCS) allowed simultaneous execution of two control laws: flutter suppression and either roll trim or a rolling maneuver load control. The DCS operated within, but independently of, a slower host operating system environment, at regulated speeds up to 200 Hz. It also coordinated the acquisition, storage, and transfer of data for near real-time controller performance evaluation and both open- and closed-loop plant estimation. It synchronized the operation of four different processing units, allowing flexibility in the number, form, functionality, and order of control laws, and variability in selection of sensors and actuators employed. Most importantly, the DCS allowed for the successful demonstration of active flutter suppression to conditions approximately 26 percent (in dynamic pressure) above the open-loop boundary in cases when the model was fixed in roll and up to 23 percent when it was free to roll. Aggressive roll maneuvers with load control were achieved above the flutter boundary.

Hoadley, Sherwood T.↗

Using root and soil traits to forecast woody encroachment dynamics in mesic grassland

Grasslands are a widespread and globally important biome providing key ecosystem services including C storage and regulation of the water cycle. Grasslands face multiple threats, including changes in drought intensity and woody encroachment - a process that results in increased woody plant abundance corresponding with decreased herbaceous plant abundance. The combination of reduced soil moisture and shifts in plant dominance from herbaceous to woody are likely to alter C pools in the soil profile. We currently do not have the capacity to predict either the magnitude or rates of change in these C pools. In order to predict changes in grassland vegetation structure and the associated impacts on C cycling requires greater understanding of changes in soil C pools at multiple soil depths, and the responses of these pools to changes in precipitation. To support and perform this parameterization of Land Surface Models, we performed detailed investigations of root (anatomical and physiological) and soil traits (microbial function) at varying soil depths, to capture the belowground impacts of changing dominant plant growth forms (grasses to shrubs) and the impacts of frequent drought.

54 ENVIRONMENTAL SCIENCES↗

Bio‐Imaging quorum sensing signal molecules in a soil‐mimic gel

Rhizosphere, the narrow region surrounding plant roots directly influenced by root exudates and the root associated microbiome, plays an important role in plant productivity and the rhizosphere is well known for stimulating microbial metabolic activities. How microbial communities interact to form stable, metabolically interconnected functional communities is an area of intense interest. The question remains on how microbially produced secreted molecules that function as intercellular communication signals shape the structure and function of microbial communities. Our goal is to detect and quantify signal molecules produced by microbes or plants in the root‐soil environment, spatially and temporarily. As a proof‐of‐concept, we are imaging diffusible extracellular microbial metabolites involved in a bacteria‐bacteria communication process called quorum‐sensing. Quorum‐sensing relies on the accumulation of high concentrations of signal molecules in the environment to control bacterial gene expression, influencing rhizosphere colonization and plant health. Local concentration of quorum sensing molecules are determined using aptamer based sensors. Aptamers that can specifically bind the desired signal molecules are selected through SELEX and immobilized on the surface of nano‐porous membranes. Binding of the signal molecules and aptamer covered surface results in changes in surface charge distribution and steric hinderance and thus modifying the transmembrane ionic transport. Changes in transmembrane impedance can be measured through electrochemical impedance spectroscopy methods to monitor local concentrations of signal molecules. Sensor responses were determined for different concentrations of signal molecules and results showed detection of C4‐HSL in a soil‐mimic solution with K D of 10 nM. We demonstrate that the quorum‐sensing signal molecule C4‐homoserine lactone and (C4‐HSL) can rapidly diffuse in a soil‐mimic gel, providing evidence for our use of a soil‐mimic for further aptasensor development and validation. The sensors were then inserted into soil mimic gel for monitoring C4‐HSL diffusion and the resulted impedance changes were used to determine the C4‐HSL concentration at different positions in the gel. Measurements of local C4‐HSL concentrations variation and numerical solution of diffusion equation were used to create 4D images of C4‐HSL molecule diffusion in the soil‐mimic gel.

Jiang, Nianyu↗

Grassland ecosystem type drives AM fungal diversity and functional guild distribution in North American grasslands

Nutrient exchange forms the basis of the ancient symbiotic relationship that occurs between most land plants and arbuscular mycorrhizal (AM) fungi. Plants provide carbon (C) to AM fungi and fungi provide the plant with nutrients such as nitrogen (N) and phosphorous (P). Nutrient addition can alter this symbiotic coupling in key ways, such as reducing AM fungal root colonization and changing the AM fungal community composition. However, environmental parameters that differentiate ecosystems and drive plant distribution patterns (e.g., pH, moisture), are also known to impact AM fungal communities. Identifying the relative contribution of environmental factors impacting AM fungal distribution patterns is important for predicting biogeochemical cycling patterns and plant-microbe relationships across ecosystems. Here, to evaluate the relative impacts of local environmental conditions and long-term nutrient addition on AM fungal abundance and composition across grasslands, we studied experimental plots amended for 10 years with N, P, or N and P fertilizer in different grassland ecosystem types, including tallgrass prairie, montane, shortgrass prairie, and desert grasslands. Contrary to our hypothesis, we found ecosystem type, not nutrient treatment, was the main driver of AM fungal root colonization, diversity, and community composition, even when accounting for site-specific nutrient limitations. We identified several important environmental drivers of grassland ecosystem AM fungal distribution patterns, including aridity, mean annual temperature, root moisture, and soil pH. This work provides empirical evidence for niche partitioning strategies of AM fungal functional guilds and emphasizes the importance of long-term, large scale research projects to provide ecologically relevant context to nutrient addition studies.

59 BASIC BIOLOGICAL SCIENCES↗

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

54 ENVIRONMENTAL SCIENCES↗

Five draft genome assemblies from Bacillaceae isolated from a degraded wetland environment

Abstract We isolated 5 Bacillaceae from a degraded wetland environment and sequenced their genomes using Illumina NextSeq. Here, we report draft genome sequences of Bacillus velezensus-SC119, Priestia megaterium-SC120, Bacillus zhangzhouensis-SC123, Bacillus pumilis-SC124, and Bacillus idriensis-SC127. The genomes range between 3,657,353 and 5,772,725 base pairs with %GC between 37.62% and 46.38%. Introduction Wetland environments play critical roles in the terrestrial carbon and water cycles and microbial communities are key players in healthy ecosystem function. Endospore forming bacteria in the Bacillaceae family are metabolically and genomically diverse soil heterotrophs that influence plant health, carbon and nitrogen cycling, and often produce diverse natural products that influence other bacterial and non-bacterial species in their environment (1). We collected two soil samples on January 19, 2023 from 42°43'12.7"N 73°45'01.4"W. One was highly hydrated and within a patch of invasive common reeds (Phragmites sp.) and the other was near the base of an Eastern cottonwood tree (Populus deltoides). Bacillus pumilis strain SC124 was isolated from the soil from near the cottonwood tree, while Bacillus velezensis strain SC119, Priestia megaterium strain SC120, Bacillus zhangzhouensis strain SC123, Bacillus idriensis strain SC127 and were isolated from the marshy soil.

isolate, wetlands, genome announcement↗

A parameterization of minimal plants

The authors present the input-normal Riccati parameterization which allows a minimal plant (A, B, C, D) to be represented completely by its B, C, and D matrices. In addition to the basic parameterization, they present useful gradient expressions for a cost functional J(A, B, C, D) when the plant is restricted to the input-normal Riccati form. The parameterization is valid for both stable and unstable, and continuous-time and discrete-time systems.

Davis, L.↗

Aboveground biomass density models for NASA’s Global Ecosystem Dynamics Investigation (GEDI) lidar mission

NASA’s Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI’s footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI’s waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Laura Duncanson↗

Through form to function: root hair development and nutrient uptake

Root hairs project from the surface of the root to aid nutrient and water uptake and to anchor the plant in the soil. Their formation involves the precise control of cell fate and localized cell growth. We are now beginning to unravel the complexities of the molecular interactions that underlie this developmental regulation. In addition, after years of speculation, nutrient transport by root hairs has been demonstrated clearly at the physiological and molecular level, with evidence for root hairs being intense sites of H(+)-ATPase activity and involved in the uptake of Ca(2+), K(+), NH(4)(+), NO(3)(-), Mn(2+), Zn(2+), Cl(-) and H(2)PO(4)(-).

Review, Tutorial↗

Novel Cell-Type-Specific Drought-Responsive Proteins in Root Tips of Field-Grown Perennial Switchgrass

The root-tip region of plants, including the root cap, forms the most basal terminal of the root and exhibits a high degree of cellular complexity in terms of morphology, cytological function, and interaction with environmental cues in the soil. Cells in this region follow a developmental trajectory, transitioning from stem cells to meristematic cells, and ultimately to fully differentiated cell types. However, our understanding of root-tip cell-type specific proteomic responses to abiotic stresses, such as drought, particularly under field conditions, remains limited. This study aimed to identify spatially resolved, cell type-specific proteomes in switchgrass (Panicum virgatum) root tips under drought stress. Root tips were collected from seven-year-old, field-grown switchgrass ‘Alamo’ plants excavated under both well-watered and long-term drought conditions. Cell type-specific proteins were identified using laser capture microdissection (LCM) coupled with nanoPOTS (Nanodroplet Processing in One Pot for Trace Samples) and nano-LC-MS proteomics analysis. Five distinct cell types were targeted: (1) cells in the quiescent center and stem cell niche (QuC), (2) protodermal epidermal cells (PEC) in the meristematic zone, (3) epidermal cells in the transition and elongation zones above the root cap (Epi), (4) peripheral root cap cells (PRC), forming 2–3 layers below the PEC and 1–2 layers above the root border cells, and (5) columella root cap cells (Col) comprising of the columella initials and a single underlying layer of cells undergoing active growth. Principal component analysis (PCA) revealed clear separation among the five targeted cell types, confirming distinct proteomic profiles. Proteins predominantly enriched in each cell type were linked to distinct cellular functions, with QuC cells showing involvement in chromosomal behavior, DNA replication, and mitosis—key processes for stem cell niche regulation. Drought stress resulted in alterations of proteostasis, as evidenced by significant decreases in ribosomal proteins and increases in protein synthesis inhibitors. Moreover, drought stress induced unique cell-type–specific proteins involved in phytohormone biosynthesis and signaling pathways, including auxin, cytokinin, and jasmonic acid. In particular, QuC cells were more highly enriched in proteins associated with DNA repair and mitotic processes. Metabolic pathways related to amino acids, carbohydrates, and lipids were differentially affected in a cell-type–dependent manner, whereas general stress-responsive proteins exhibited consistent changes across all five cell types. Overall, this study provides unique spatially resolved, cell-type-specific proteomic profiles in root tips, representing a significant advancement in our understanding of the cellular mechanisms underlying plant responses to drought stress in natural field conditions.

perennial grass↗

On the formulation of a minimal uncertainty model for robust control with structured uncertainty

In the design and analysis of robust control systems for uncertain plants, representing the system transfer matrix in the form of what has come to be termed an M-delta model has become widely accepted and applied in the robust control literature. The M represents a transfer function matrix M(s) of the nominal closed loop system, and the delta represents an uncertainty matrix acting on M(s). The nominal closed loop system M(s) results from closing the feedback control system, K(s), around a nominal plant interconnection structure P(s). The uncertainty can arise from various sources, such as structured uncertainty from parameter variations or multiple unsaturated uncertainties from unmodeled dynamics and other neglected phenomena. In general, delta is a block diagonal matrix, but for real parameter variations delta is a diagonal matrix of real elements. Conceptually, the M-delta structure can always be formed for any linear interconnection of inputs, outputs, transfer functions, parameter variations, and perturbations. However, very little of the currently available literature addresses computational methods for obtaining this structure, and none of this literature addresses a general methodology for obtaining a minimal M-delta model for a wide class of uncertainty, where the term minimal refers to the dimension of the delta matrix. Since having a minimally dimensioned delta matrix would improve the efficiency of structured singular value (or multivariable stability margin) computations, a method of obtaining a minimal M-delta would be useful. Hence, a method of obtaining the interconnection system P(s) is required. A generalized procedure for obtaining a minimal P-delta structure for systems with real parameter variations is presented. Using this model, the minimal M-delta model can then be easily obtained by closing the feedback loop. The procedure involves representing the system in a cascade-form state-space realization, determining the minimal uncertainty matrix, delta, and constructing the state-space representation of P(s). Three examples are presented to illustrate the procedure.

Belcastro, Christine M.↗