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At least 271 records · Page 15

Impact of Collection Equipment on Ash Variability of Baled Corn Stover Biomass for Bioenergy

Cost-effective conversion of agricultural residues for renewable energy hinges not only on the material’s quality but also the biorefinery’s ability to reliably measure quality specifications. The ash content of biomass is one such specification, influencing pretreatment and disposal costs for the conversion facility and the overall value of a delivered lot of biomass. The biomass harvest process represents a primary pathway for accumulation of soil-derived ash within baled material. In this work, the influence of five collection techniques on the total ash content and variability of ash content within baled corn stover in southwest Kansas is discussed. The equipment tested included a mower for cutting the corn stover stubble, a basket rake, wheel rake, or shred flail to gather the stover, and a mixed or uniform in-feed baler for final collection. The results showed mean ash content to range from 11.5 to 28.2 % depending on operational choice. Resulting impacts on feedstock costs for a biochemical conversion process range from $5.38 to $22.30 Mg-1 based on the loss of convertible dry matter and ash disposal costs. Collection techniques that minimized soil contact (shred flail or nonmowed stubble) were shown to prevent excessive ash contamination, whereas more aggressive techniques (mowing and use of a wheel rake) caused greater soil disturbance and entrainment within the final baled material. Material sampling and testing were shown to become more difficult as within-bale ash variability increased, creating uncertainty around feedstock quality and the associated costs of ash mitigation.

09 BIOMASS FUELS↗

Microbial Communities Influence Soil Dissolved Organic Carbon Concentration by Altering Metabolite Composition

Rapid microbial growth in the early phase of plant litter decomposition is viewed as an important component of soil organic matter (SOM) formation. However, the microbial taxa and chemical substrates that correlate with carbon storage are not well resolved. The complexity of microbial communities and diverse substrate chemistries that occur in natural soils make it difficult to identify links between community membership and decomposition processes in the soil environment. To identify potential relationships between microbes, soil organic matter, and their impact on carbon storage, we used sand microcosms to control for external environmental factors such as changes in temperature and moisture as well as the variability in available carbon that exist in soil cores. Using Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) on microcosm samples from early phase litter decomposition, we found that protein- and tannin-like compounds exhibited the strongest correlation to dissolved organic carbon (DOC) concentration. Proteins correlated positively with DOC concentration, while tannins correlated negatively with DOC. Through random forest, neural network, and indicator species analyses, we identified 42 bacterial and 9 fungal taxa associated with DOC concentration. The majority of bacterial taxa (26 out of 42 taxa) belonged to the phylum Proteobacteria while all fungal taxa belonged to the phylum Ascomycota. Additionally, we identified significant connections between microorganisms and protein-like compounds and found that most taxa (12/14) correlated negatively with proteins indicating that microbial consumption of proteins is likely a significant driver of DOC concentration. This research links DOC concentration with microbial production and/or decomposition of specific metabolites to improve our understanding of microbial metabolism and carbon persistence.

59 BASIC BIOLOGICAL SCIENCES↗

KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N<sub>2</sub>O emission using data from mesocosm experiments

Abstract. Agricultural nitrous oxide (N2O) emission accounts for a non-trivial fraction of global greenhouse gas (GHG) budget. To date, estimating N2O fluxes from cropland remains a challenging task because the related microbial processes (e.g., nitrification and denitrification) are controlled by complex interactions among climate, soil, plant and human activities. Existing approaches such as process-based (PB) models have well-known limitations due to insufficient representations of the processes or uncertainties of model parameters, and due to leverage recent advances in machine learning (ML) a new method is needed to unlock the “black box” to overcome its limitations such as low interpretability, out-of-sample failure and massive data demand. In this study, we developed a first-of-its-kind knowledge-guided machine learning model for agroecosystems (KGML-ag) by incorporating biogeophysical and chemical domain knowledge from an advanced PB model, ecosys, and tested it by comparing simulating daily N2O fluxes with real observed data from mesocosm experiments. The gated recurrent unit (GRU) was used as the basis to build the model structure. To optimize the model performance, we have investigated a range of ideas, including (1) using initial values of intermediate variables (IMVs) instead of time series as model input to reduce data demand; (2) building hierarchical structures to explicitly estimate IMVs for further N2O prediction; (3) using multi-task learning to balance the simultaneous training on multiple variables; and (4) pre-training with millions of synthetic data generated from ecosys and fine-tuning with mesocosm observations. Six other pure ML models were developed using the same mesocosm data to serve as the benchmark for the KGML-ag model. Results show that KGML-ag did an excellent job in reproducing the mesocosm N2O fluxes (overall r2=0.81, and RMSE=3.6 mgNm-2d-1 from cross validation). Importantly, KGML-ag always outperforms the PB model and ML models in predicting N2O fluxes, especially for complex temporal dynamics and emission peaks. Besides, KGML-ag goes beyond the pure ML models by providing more interpretable predictions as well as pinpointing desired new knowledge and data to further empower the current KGML-ag. We believe the KGML-ag development in this study will stimulate a new body of research on interpretable ML for biogeochemistry and other related geoscience processes.

54 ENVIRONMENTAL SCIENCES↗

Phenolic compounds and black carbon feedback controls on peat decomposition and carbon accumulation in southeastern peatlands under regimes of seasonal drought, drainage and frequent fire

Peatlands store one-third of soil C in terrestrial ecosystems and have persisted through changing climate over millennia from the arctic to the tropics. Approximately one-third of peat stores are found in subtropical and tropical peatlands (STPs) formed from high-lignin woody biomass. In this project, our questions are: 1) why do these non-sphagnum peatlands (STPs) accumulate C under warmer-drier climates and 2) how might insights coming from studying control mechanisms in STPs improve the management and conservation of the vast C stores in boreal peatlands subject to increasing climate forcing. We hypothesized that a dual control or “latch mechanism” reduces decomposition in shrub/tree communities in STPs due to both (1) higher production of polyphenol and aromatic compounds in STPs than found in northern Sphagnum/Carex communities and (2) the buildup of recalcitrant organic matter produced by light fire-drought-warming-adapted communities, together leading to a reduction in the microbial decay rate of peat. After three-years of intensive biological and chemical analysis in a series of field and microcosm experiments along our north to south bog gradient from Minnesota to Peru, we show how previously unrecognized biotic factors, particularly dynamic interlinked above- and belowground attributes control C sequestration in peatlands. Our key findings include (1) phenolics-bridged plant-microbe symbioses, principally slow-growing microbes dominated in higher phenolic wooded STPs, preserving C in peatlands under climate change, 2) phenolics are the overarching factor controlling the relative abundance of slow-and fast-growing microbes, the slow-growing microbes in STPs metabolize C slowly and are inherently resistant to disturbance, 3) global data analysis shows that soil respiration does not increase exponentially from boreal to tropical peatlands, suggesting that slow-growing microbes may have become dominant in most non-boreal peatlands, 4) peat chemistry analysis from over 2000 samples show that across peatlands both from the arctic to tropics and from high to low elevation peatlands recalcitrance increases as aromatic content increases, and 5) peat affected by low-severity wildfires displays a similar pattern of higher aromatic content. Our findings all demonstrate links between peat recalcitrance and increased content of phenolics and other aromatic compounds in plants. Thus, linked plant–microbe symbiotic traits are a key to understanding ecological resilience and resistance developed in peatlands under disturbance. New trait-based approaches that can better link above-and below ground processes are needed to advance both the accuracy and precision of current abiotic-factor-based Earth system models in predicting future soil C responses to climate-change feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Bioindicator “fingerprints” of methane-emitting thermokarst features in Alaskan soils

Permafrost thaw increases the bioavailability of ancient organic matter, facilitating microbial metabolism of volatile organic compounds (VOCs), carbon dioxide, and methane (CH 4 ). The formation of thermokarst (thaw) lakes in icy, organic-rich Yedoma permafrost leads to high CH 4 emissions, and subsurface microbes that have the potential to be biogeochemical drivers of organic carbon turnover in these systems. However, to better characterize and quantify rates of permafrost changes, methods that further clarify the relationship between subsurface biogeochemical processes and microbial dynamics are needed. In this study, we investigated four sites (two well-drained thermokarst mounds, a drained thermokarst lake, and the terrestrial margin of a recently formed thermokarst lake) to determine whether biogenic VOCs (1) can be effectively collected during winter, and (2) whether winter sampling provides more biologically significant VOCs correlated with subsurface microbial metabolic potential. During the cold season (March 2023), we drilled boreholes at the four sites and collected cores to simultaneously characterize microbial populations and captured VOCs. VOC analysis of these sites revealed “fingerprints” that were distinct and unique to each site. Total VOCs from the boreholes included > 400 unique VOC features, including > 40 potentially biogenic VOCs related to microbial metabolism. Subsurface microbial community composition was distinct across sites; for example, methanogenic archaea were far more abundant at the thermokarst site characterized by high annual CH 4 emissions. The results obtained from this method strongly suggest that ∼10% of VOCs are potentially biogenic, and that biogenic VOCs can be mapped to subsurface microbial metabolisms. By better revealing the relationship between subsurface biogeochemical processes and microbial dynamics, this work advances our ability to monitor and predict subsurface carbon turnover in Arctic soils.

anaerobic degradation↗

Characterization and application of a high-resolution microfluidic device in atmospheric ice nucleation research and integrated science teaching

Ambient ice-nucleating particles (INPs) represent an important subset of aerosol particles that facilitate heterogeneous formation of ice crystals in the atmosphere, which can impact Earth system and energy. In this work, we developed an affordable high-resolution platform to replicate atmospheric immersion freezing through the unique capabilities of microfluidics to measure INP concentration of known ice nucleation active materials, as well as high-latitude soil samples. The new instrument produced comparable and extended freezing efficiency data for a multitude of samples over the temperature range of -5 to -35 °C as compared to an existing freezing assay within known uncertainties. Moreover, the new assay was integrated into science teaching at a primarily undergraduate and Hispanic-serving institute, contributing to fostering a deeper understanding of ice nucleation processes among college students, instilling their enthusiasm for science, and addressing the critical need for a well-informed citizenry. Student research assistants were involved in both research and pedagogical development processes. Three students from our team visited the Pacific Northwest National Laboratory to help characterize physicochemical properties of our test samples and to test modeling of atmospheric ice nucleation using a box model as well as a global climate model (E3SM) for the regional-scale conditions over the North Slope of Alaska (NSA) and Southern Great Plains (SGP). We also assessed student learning experience via hands-on training, research processes, and development of educational materials. On pre- and post-participation surveys and in exit interviews, students reported personal growth as advancements in breadth of experience, research-related skill sets, and regarding their educational and career goals. They also affirmed that the methods enacted incorporated the NASA Minority University Research and Education Program (MUREP) STEM Engagement Best Practices.

58 GEOSCIENCES↗

Microbial O 2 consumption as a function of pore structure in soils of sorghum, switchgrass, and prairie vegetation systems

Abstract Microscale O 2 availability in soil, a main factor influencing microbial processing of soil carbon and nitrogen, is a function of O 2 diffusion and microbial O 2 consumption. While O 2 diffusivity is widely studied, it is difficult to quantify the rate of microbial O 2 consumption ( MO ). In this study, we quantified the MO using O 2 microsensor profiling to compare MO in different soils and vegetation systems while manipulating the soil pore structure. Soil samples were collected from three bioenergy vegetation systems, sorghum ( Sorghum bicolor L. Moench), switchgrass ( Panicum virgatum L.), and prairie, at an experimental site in Southeast Michigan, and from switchgrass and prairie systems at two sites in South and North Wisconsin. We prepared soil cores with two contrasting pore structures, that is, large (>30 µm Ø) pore‐dominated soil (LP) and small (<10 µm Ø) pore‐dominated soil (SP), from the same 1‐ to 2‐mm soil size fraction. We quantified MO (nmol O 2 cm −3 s −1 ) using a microprofiler with an oxygen (OX‐100 µm) microsensor (Unisense) pre‐ and post‐38‐day incubation. Across all studied systems, there was a trend for a decrease in SP MO post‐incubation, suggesting a change in microbial metabolism to lower O 2 utilization. However, sizeable microbial O 2 consumption continued in the LP soils, further corroborated by a positive correlation between the C‐CO 2 emission rate and the post‐incubation MO , highlighting that LP provided a better physical microenvironment for the soil microbes.

Chakraborty, Poulamee [Department of Plant Soil an↗

Sampling and Analysis Plan for Verification Sampling of LANL-Derived Residual Radionuclides in Soils within Tract A-18-2 for Land Conveyance

Public Law 105-119 directs the U.S. Department of Energy (DOE) to convey or transfer parcels of land to the Incorporated County of Los Alamos or their designees and to the Department of Interior, Bureau of Indian Affairs, in trust for the Pueblo de San Ildefonso. Los Alamos National Security is tasked to support DOE in conveyance and/or transfer of identified land parcels no later than September 2022. Under DOE Order 458.1, Radiation Protection of the Public and the Environment (O458.1, 2013) and Los Alamos National Laboratory (LANL or the Laboratory) implementing Policy 412 (P412, 2014), real property with the potential to contain residual radioactive material must meet the criteria for clearance and release to the public. This Sampling and Analysis Plan (SAP) is a second investigation of Tract A-18-2 for the purpose of verifying the previous sampling results (LANL 2017). This sample plan requires 18 projectspecific soil samples for use in radiological clearance decisions consistent with LANL Procedure ENV-ES-TP-238 (2015a) and guidance in the Multi-Agency Radiation Survey and Site Investigation Manual (MARSSIM, 2000). The sampling work will be conducted by LANL, and samples will be evaluated by a LANL-contracted independent lab. However, there will be federal review (verification) of all steps of the sampling process.

54 ENVIRONMENTAL SCIENCES↗

Soil Microbes Trade-Off Biogeochemical Cycling for Stress Tolerance Traits in Response to Year-Round Climate Change

Winter air temperatures are rising faster than summer air temperatures in high-latitude forests, increasing the frequency of soil freeze/thaw events in winter. To determine how climate warming and soil freeze/thaw cycles affect soil microbial communities and the ecosystem processes they drive, we leveraged the Climate Change across Seasons Experiment (CCASE) at the Hubbard Brook Experimental Forest in the northeastern United States, where replicate field plots receive one of three climate treatments: warming (+5°C above ambient in the growing season), warming in the growing season + winter freeze/thaw cycles (+5°C above ambient +4 freeze/thaw cycles during winter), and no treatment. Soil samples were taken from plots at six time points throughout the growing season and subjected to amplicon (rDNA) and metagenome sequencing. We found that soil fungal and bacterial community composition were affected by changes in soil temperature, where the taxonomic composition of microbial communities shifted more with the combination of growing-season warming and increased frequency of soil freeze/thaw cycles in winter than with warming alone. Warming increased the relative abundance of brown rot fungi and plant pathogens but decreased that of arbuscular mycorrhizal fungi, all of which recovered under combined growing-season warming and soil freeze/thaw cycles in winter. The abundance of animal parasites increased significantly under combined warming and freeze/thaw cycles. We also found that warming and soil freeze/thaw cycles suppressed bacterial taxa with the genetic potential for carbon (i.e., cellulose) decomposition and soil nitrogen cycling, such as N fixation and the final steps of denitrification. These new soil communities had higher genetic capacity for stress tolerance and lower genetic capacity to grow or reproduce, relative to the communities exposed to warming in the growing season alone. Our observations suggest that initial suppression of biogeochemical cycling with year-round climate change may be linked to the emergence of taxa that trade-off growth for stress tolerance traits.

54 ENVIRONMENTAL SCIENCES↗

Concentration of trace elements on branded cigarette in Malaysia

Tobacco is a plant that is used as a recreational drug since the beginning of its use by the Native Americans. Now with the development of the tobacco industry, smoking has become a norm for the public in Malaysia. Trace elements in plants are mostly due to the uptake processes from the soils into the roots of the plants. The concentration of the elements may also be influenced by the elements contained in the water and also fertilizers. This paper aim to analyze the concentration of the trace elements contained in the branded cigarettes sold in Malaysia by utilizing the neutron activation analysis. The tobaccos were taken out from the cigarettes. The collected samples were air dried and passed through 2 mm sieve. Instrumental Neutron Activation Analysis (NAA) has been used for the determination of trace elements. Samples were activated in the Nuclear Malaysia Triga Mark II reactor with a neutron flux of 2.0 x 10{sup 12} n cm{sup -2} s{sup -1}. The samples then were analyzed using ORTEC Gamma Spectrometer a co-axial n-type HPGe detector with resolution of 2.0 keV at 1332 keV and relative efficiency of 20%. The data obtained could help in assessing the concentration of the trace elements that complying with the standard limitation dose proposed by World Health Organization (WHO)

07 ISOTOPE AND RADIATION SOURCES↗

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗

Microbial abundances and carbon use under ambient temperature or experimental warming in a southern boreal peatland

Abstract Organic peat soils occupy relatively little of the global land surface area but store vast amounts of soil carbon in northern latitudes where climate is warming at a rapid pace. Warming may result in strong positive feedbacks of carbon loss and global climate change driven by microbial processes if warming alters the balance between primary productivity and decomposition. To elucidate effects of warming on the microbial communities mediating peat carbon dynamics, we explored the abundance of broad microbial groups and their source of carbon (i.e. old carbon versus more recently fixed photosynthate) using microbial lipid analysis (δ 13 C PLFA) of peat samples under ambient temperatures and before/after initiation of experimental peat warming (+ 2.25, + 4.5, + 6.75, and + 9 °C). This analysis occurred over a profile to 2 m depth in an undrained, ombrotrophic peat bog in northern Minnesota. We found that the total microbial biomass and individual indicator lipid abundances were stratified by depth and strongly correlated to temperature under ambient conditions. However, under experimental warming, statistically significant effects of temperature on the microbial community were sporadic and inconsistent. For example, 3 months after experimental warming the relative abundance of Gram-negative bacterial indicators across depth combined and > 50 cm depth and Gram-positive bacterial indicators at 20–50 cm depth showed significant positive relationships to temperature. At that same timepoint, however, the relative abundance of Actinobacterial indicators across depth showed a significant negative relationship to temperature. After 10 months of experimental warming, the relative abundance of fungal biomarkers was positively related to temperature in all depths combined, and the absolute abundance of anaerobic bacteria declined with increasing temperature in the 20–50 cm depth interval. The lack of observed response in the broader microbial community may suggest that at least initially, microbial community structure with peat depth in these peatlands is driven more by bulk density and soil water content than temperature. Alternatively, the lack of broad microbial community response may simply represent a lag period, with more change to come in the future. The long-term trajectory of microbial response to warming in this ecosystem then could either be direct, after this initial lag time, or indirect through other physical or biogeochemical changes in the peat profile. These initial results provide an important baseline against which to measure long-term microbial community and carbon-cycling responses to warming and elevated CO 2 .

Felice, Mark↗

Soil incubations reproduce field methane dynamics in a subarctic wetland

A major challenge in peatland carbon cycle modeling is the estimation of subsurface methane (CH 4 ) and carbon dioxide (CO 2 ) production and consumption rates and pathways. The most common methods for modeling these processes are soil incubations and stable isotope modeling, both of which may involve departures from field conditions. To explore the impacts of these departures, we measured CH 4 /CO 2 concentration ratios and 13 C fractionation factors (α C , indicating CH 4 production pathways) in field pore water from a thawing subarctic peatland, and compared these values to those observed in incubations of corresponding peat samples. Incubation CH 4 /CO 2 production ratios were significantly and positively correlated with observed field CH 4 /CO 2 concentration ratios, though observed field ratios were ~20 % of those in incubations due to CH 4 ’s lower solubility in pore water. After correcting the field ratios for CH 4 loss with an isotope mass balance model, the incubation CH 4 /CO 2 ratios and α C were both significantly positively correlated with field ratios and α C (respectively), both with slopes indistinguishable from 1. Finally, although CH 4 /CO 2 ratios and α C were slightly higher in the incubations, these shifts were consistent along the thaw progression, indicating that ex situ incubations can replicate trends in in situ CH 4 production.

54 ENVIRONMENTAL SCIENCES↗

Generalizing Microbial Parameters in Soil Biogeochemical Models: Insights From a Multi‐Site Incubation Experiment

Abstract Incorporating microbial processes into soil biogeochemical models has received growing interest. However, determining the parameters that govern microbially driven biogeochemical processes typically requires case‐specific model calibration in various soil and ecosystem types. Here each case refers to an independent and individual experimental unit subjected to repeated measurements. Using the Microbial‐ENzyme Decomposition model, this study aimed to test whether a common set of microbially‐relevant parameters (i.e., generalized parameters) could be obtained across multiple cases based on a two‐year incubation experiment in which soil samples of four distinct soil series (i.e., Coland, Kesswick, Westmoreland, and Etowah) collected from forest and grassland were subjected to cellulose or no cellulose amendment. Results showed that a common set of parameters controlling microbial growth and maintenance as well as extracellular enzyme production and turnover could be generalized at the soil series level but not land cover type. This indicates that microbial model developments need to prioritize soil series type over plant functional types when implemented across various sites. This study also suggests that, in addition to heterotrophic respiration and microbial biomass data, extracellular enzyme data sets are needed to achieve reliable microbial‐relevant parameters for large‐scale soil model projections.

58 GEOSCIENCES↗

RhizoMAP: a comprehensive, nondestructive, and sensitive platform for metabolic imaging of the rhizosphere

Elucidating the intricate structural organization and spatial gradients of biomolecular composition within the rhizosphere is critical to understanding important biogeochemical processes, which include the mechanisms of root-microbe interactions for maintaining sustainable plant ecosystem services. While various analytical methods have been developed to assess the spatial heterogeneity within the rhizosphere, a comprehensive view of the fine distribution of metabolites within the root-soil interface has remained a significant challenge. This is primarily due to the difficulty of maintaining the original spatial organization during sample preparation without compromising its molecular content.

59 BASIC BIOLOGICAL SCIENCES↗

Metagenome-assembled genomes from topsoils collected during NEON campaign in East River, CO (06/14/2018-06/28/2018)

The Watershed Function Science Focus Area (WF SFA) at Lawrence Berkeley National Lab is working to build a mechanistic understanding of the distribution and dynamics of biogeochemical processes in mountainous watersheds and their response to perturbation. In June 2018, the NEON (National Ecological Observatory Network) Airborne Observatory Platform (AOP) performed a taskable airborne imaging campaign to collect visible to shortwave infrared (VSWIR) imaging spectroscopy and LiDAR data across 330 km2 in the Upper East River at Crested Butte, CO. We conducted a parallel ground sampling campaign to sample vegetation traits, as well as soil physical, chemical, and microbiological characteristics. We collected these samples from 438 sites across 12 locations spanning much of the elevation, topographic, and geologic variability across the study area. A subset of 250 samples were used for soil metagenomics which is presented here. In addition, at each site, vegetation samples were collected to measure species-specific leaf water content and leaf mass area, foliar elemental composition and foliar CN stable isotope ratios. Soil samples were collected to measure soil physical properties which include bulk density and soil texture analysis. A suite of soil chemical properties was measured from the samples collected at each site, including pH, organic matter, concentrations exchangeable cations, total elemental composition, and the concentrations of extractable N pools (e.g. total free amino acids, ammonium, nitrate, dissolved organic N, and total dissolved N). Additionally, we have measured soil microbial biomass CN stoichiometry. Here, we present 1982 metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from topsoil collected from during NEON 2018 campaign. All metagenomes were sequenced at JGI (Joint Genome Institute) (GOLD Study ID: Gs0149986). Metagenomes were assembled using JGI Metagenome Workflow (10.1128/mSystems.00804-20). The dataset includes (1) zip files for 1982 MAG fasta files (neon_genomes1-5.tar.gz, split into 5 tarballs to keep tarballs under 0.5 GB), (2) neon_Gs0149986_samples_soilproperties_metagenomes.csv: the sample information together with the accession numbers for the underlying metagenomes and the associated soil physical and chemical measurements in NMDC (National Microbiome Data Collaborative) compliant format, (3) neon_Gs0149986.kml: location bounding box file for the sampled locations, (4) samples.csv: sample metadata file used to register Internationall Generic Sample Numbers (IGSNs), (5) flmd.csv: file level metadata file, and (6) dd.csv: data dictionary file. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗