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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Climate change–induced stress disrupts ectomycorrhizal interaction networks at the boreal–temperate ecotone

The interaction networks formed by ectomycorrhizal fungi (EMF) and their tree hosts, which are important to both forest recruitment and ecosystem carbon and nutrient retention, may be particularly susceptible to climate change at the boreal–temperate forest ecotone where environmental conditions are changing rapidly. Here, we quantified the compositional and functional trait responses of EMF communities and their interaction networks with two boreal ( Pinus banksiana and Betula papyrifera ) and two temperate ( Pinus strobus and Quercus macrocarpa ) hosts to a factorial combination of experimentally elevated temperatures and reduced rainfall in a long-term open-air field experiment. The study was conducted at the B4WarmED (Boreal Forest Warming at an Ecotone in Danger) experiment in Minnesota, USA, where infrared lamps and buried heating cables elevate temperatures (ambient, +3.1 °C) and rain-out shelters reduce growing season precipitation (ambient, ~30% reduction). EMF communities were characterized and interaction networks inferred from metabarcoding of fungal-colonized root tips. Warming and rainfall reduction significantly altered EMF community composition, leading to an increase in the relative abundance of EMF with contact-short distance exploration types. These compositional changes, which likely limited the capacity for mycelial connections between trees, corresponded with shifts from highly redundant EMF interaction networks under ambient conditions to less redundant (more specialized) networks. Further, the observed changes in EMF communities and interaction networks were correlated with changes in soil moisture and host photosynthesis. Collectively, these results indicate that the projected changes in climate will likely lead to significant shifts in the traits, structure, and integrity of EMF communities as well as their interaction networks in forest ecosystems at the boreal–temperate ecotone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Techno-economic optimization of renewable urea production for sustainable agriculture and CO 2 utilization

Abstract Urea is the most used nitrogen fertilizer due to its ease of storage, transportation, and application. It is made by combining ammonia and carbon dioxide (CO 2 ), both of which are produced predominantly from fossil fuels at present. The recent momentum behind ammonia production using renewable-powered electrolysis offers an opportunity to both make urea in a more sustainable way and utilize CO 2 from external sources. In this work, we present a techno-economic optimization model to minimize the cost of making urea in this way. The model allows for time-varying chemical production in response to renewable variability by simultaneously optimizing production facility design and hourly operation. We performed a case study for Minnesota considering the use of byproduct CO 2 from bioethanol production. We found that the present-day levelized cost of renewable urea is between $268 mt −1 and $413 mt −1 at likely implementable production scales up to 250 000 mt yr −1 . This is within the range of historical conventional urea prices while offering at least 78% carbon intensity reduction. Projecting to 2030, there is a clear economic case for renewable urea production with levelized cost as low as $135 mt −1 due to technology improvement and electrolysis manufacturing expansion, facilitating a urea production scale increase to 525 000 mt yr −1 . Optimal facilities use wind energy, with hydrogen and ammonia production operating in a flexible, time-varying way to minimize battery and hydrogen storage capacities. Urea production operates near steady state due to the relatively low cost of intermediate ammonia buffer storage. A mix of imported methane and locally produced hydrogen are used to provide heat for steam consumed in the urea synthesis.

Chemistry↗
DOE OSTI2020

Species-specific flowering phenology responses to experimental warming and drought alter herbaceous plant species overlap in a temperate–boreal forest community

Abstract Background and Aims Warmer temperatures and altered precipitation patterns are expected to continue to occur as the climate changes. How these changes will impact the flowering phenology of herbaceous perennials in northern forests is poorly understood but could have consequences for forest functioning and species interactions. Here, we examine the flowering phenology responses of five herbaceous perennials to experimental warming and reduced summer rainfall over 3 years. Methods This study is part of the B4WarmED experiment located at two sites in northern Minnesota, USA. Three levels of warming (ambient, +1.6 °C and +3.1 °C) were crossed with two rainfall manipulations (ambient and 27 % reduced growing season rainfall). Key Results We observed species-specific responses to the experimental treatments. Warming alone advanced flowering for four species. Most notably, the two autumn blooming species showed the strongest advance of flowering to warming. Reduced rainfall alone advanced flowering for one autumn blooming species and delayed flowering for the other, with no significant impact on the three early blooming species. Only one species, Solidago spp., showed an interactive response to warming and rainfall manipulation by advancing in +1.6 °C warming (regardless of rainfall manipulation) but not advancing in the warmest, driest treatment. Species-specific responses led to changes in temporal overlap between species. Most notably, the two autumn blooming species diverged significantly in their flowering timing. In ambient conditions, these two species flowered within the same week. In the warmest, driest treatment, flowering occurred over a month apart. Conclusions Herbaceous species may differ in how they respond to future climate conditions. Changes to phenology may lead to fewer resources for insects or a mismatch between plants and pollinators.

Plant Sciences↗
DOE OSTI2020

Warming and disturbance alter soil microbiome diversity and function in a northern forest ecotone

ABSTRACT The response to global change by soil microbes is set to affect important ecosystem processes. These impacts could be most immediate in transitional zones, such as the temperate-boreal forest ecotone, yet previous work in these forests has primarily focused on specific subsets of microbial taxa. Here, we examined how bacterial and fungal communities respond to simulated above- and below-ground warming under realistic field conditions in closed and open canopy treatments in Minnesota, USA. Our results show that warming and canopy disturbance shifted bacterial and fungal community structure as dominant bacterial and fungal groups differed in the direction and intensity of their responses. Ectomycorrhizal and saprotrophic fungal communities with greater connectivity (higher prevalence of strongly interconnected taxa based on pairwise co-occurrence relationships) were more resistant to compositional change. Warming effects on soil enzymes involved in the hydrolytic and oxidative liberation of carbon from plant cell walls and nutrients from organic matter were most strongly linked to fungal community responses, although community structure–function relationships differed between fungal guilds. Collectively, these findings indicate that warming and disturbance will influence the composition and function of microbial communities in the temperate-boreal ecotone, and fungal responses are particularly important to understand for predicting future ecosystem functioning.

Microbiology↗
DOE OSTI2025

Greedy emulators for nuclear two-body scattering

Applications of reduced basis method emulators are increasing in low-energy nuclear physics because they enable fast and accurate sampling of high-fidelity calculations, enabling robust uncertainty quantification. Here, in this paper, we develop, implement, and test two model-driven emulators based on the (Petrov-)Galerkin projection using the prototypical test case of two-body scattering with the Minnesota potential and a more realistic local chiral potential. The high-fidelity scattering equations are solved with the matrix Numerov method, a reformulation of the popular Numerov recurrence relation for solving special second-order differential equations as a linear system of coupled equations. A novel error estimator based on reduced-space residuals is applied to an active learning approach (a greedy algorithm) to choosing training samples (“snapshots”) for the emulator and contrasted with a proper orthogonal decomposition (POD) approach. Both approaches allow for computationally efficient offline-online decompositions, but the greedy approach requires many fewer snapshot calculations. These developments set the groundwork for emulating scattering observables based on chiral nucleon-nucleon and three-nucleon interactions and optical models, where computational speed-ups are necessary for Bayesian uncertainty quantification. Our emulators and error estimators are widely applicable to linear systems.

Bayesian methods↗
DOE OSTI2022

Comparative analysis of internal energy excitation and dissociation of nitrogen predicted by independently developed ab initio potential energy surfaces

In this article we present a comparative atomic level study analyzing the vibrational excitation and dissociation of molecular nitrogen due to N 2 ⁢( 1 Σ g ⁢ + )+N⁢( 4 S u ) and N 2 ⁢( 1 Σ g ⁢ + )+N 2 ⁢( 1 Σ g ⁢+ ) interactions governed by independently developed potential energy surfaces at the University of Minnesota and NASA Ames Research Center. Further, vibrational excitation was studied for N 2 +N 2 interactions from T=10000 to 25000 K and for N 2 +N from T=5000 to 30000 K. Nonequilibrium dissociation is studied from T=10000 to 30000 K under the quasi-steady-state condition for N 2 +N 2 and N 2 +N interactions. Finally, an inviscid Mach 20 dissociating nitrogen flow over a cylinder with a Knudsen number of 0.015 is carried out to study the impact of molecular interactions predicted by independently developed potential energy surfaces on a canonical hypersonic flow.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2020

The incommensurately modulated structures of low-temperature labradorite feldspars: a single-crystal X-ray and neutron diffraction study

Labradorite feldspars of the plagioclase solid solution series have been known for their complicated subsolidus phase relations and enigmatic incommensurately modulated structures. Characterized by the irrationally indexed e -reflections in the diffraction pattern, e -labradorite shows the largest variation in the incommensurate ordering states among the e -plagioclase structures. The strongly ordered low-temperature e -labradorite is one of the last missing pieces of the e -plagioclase puzzle. Nine plutonic and metamorphic labradorite feldspar samples from Canada, Ukraine, Minnesota (USA), Tanzania and Greenland with compositions ranging from An 52.5 to An 68 were studied with single-crystal X-ray diffraction. Two crystals from Labrador, Canada, and Duluth, MN, USA, with wide enough twin lamellae were analyzed with single-crystal neutron diffraction. The incommensurately modulated structures of e -plagioclase are refined for the first time with neutron diffraction data, which confirmed that the T—O distance modulation in the low-temperature e -plagioclase results from the Al–Si ordering in the framework. Detailed configurations of the M site are also observed in the structures refined from neutron diffraction data, which were not possible to see with X-ray diffraction data. The relation between the q -vectors and the mole% An composition is revealed for the entire compositional range of e -plagioclase, from An 25 to An 75 . The previously proposed two-trend relation depending on the cooling rate and phase transition path is confirmed. A new classification of e -plagioclase ( e α , e β and e γ ) is proposed based on the q -vector of the structure, which makes it an independent character from the presence/absence of density modulation. New parameters are proposed to quantify the ordering states of these complicated aperiodic structures of e -plagioclases, such as the difference between $\langle$T 1 o—O$\rangle$ and $\langle$T 1 m—O$\rangle$ at phase t = 0.2 or the normalized intensity of the (071\bar 1) reflection.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Soil enzymes as indicators of soil function: A step toward greater realism in microbial ecological modeling

Soil carbon (C) and nitrogen (N) cycles and their complex responses to environmental changes have received increasing attention. However, large uncertainties in model predictions remain, partially due to the lack of explicit representation and parameterization of microbial processes. One great challenge is to effectively integrate rich microbial functional traits into ecosystem modeling for better predictions. Here, using soil enzymes as indicators of soil function, we developed a competitive dynamic enzyme allocation scheme and detailed enzyme-mediated soil inorganic N processes in the Microbial-ENzyme Decomposition (MEND) model. We conducted a rigorous calibration and validation of MEND with diverse soil C-N fluxes, microbial C:N ratios, and functional gene abundances from a 12-year CO 2 × N grassland experiment (BioCON) in Minnesota, USA. In addition to accurately simulating soil CO 2 fluxes and multiple N variables, the model correctly predicted microbial C:N ratios and their negative response to enriched N supply. Model validation further showed that, compared to the changes in simulated enzyme concentrations and decomposition rates, the changes in simulated activities of eight C-N-associated enzymes were better explained by the measured gene abundances in responses to elevated atmospheric CO 2 concentration. In conclusion, our results demonstrated that using enzymes as indicators of soil function and validating model predictions with functional gene abundances in ecosystem modeling can provide a basis for testing hypotheses about microbially mediated biogeochemical processes in response to environmental changes. Further development and applications of the modeling framework presented here will enable microbial ecologists to address ecosystem-level questions beyond empirical observations, toward more predictive understanding, an ultimate goal of microbial ecology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Across‐model spread and shrinking in predicting peatland carbon dynamics under global change

Abstract Large across‐model spread in simulating land carbon (C) dynamics has been ubiquitously demonstrated in model intercomparison projects (MIPs), and became a major impediment in advancing climate change prediction. Thus, it is imperative to identify underlying sources of the spread. Here, we used a novel matrix approach to analytically pin down the sources of across‐model spread in transient peatland C dynamics in response to a factorial combination of two atmospheric CO 2 levels and five temperature levels. We developed a matrix‐based MIP by converting the C cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM4.5 and ORCHIDEE) into eight matrix models. While the model average of ecosystem C storage was comparable to the measurement, the simulation differed largely among models, mainly due to inter‐model difference in baseline C residence time. Models generally overestimated net ecosystem production (NEP), with a large spread that was mainly attributed to inter‐model difference in environmental scalar. Based on the sources of spreads identified, we sequentially standardized model parameters to shrink simulated ecosystem C storage and NEP to almost none. Models generally captured the observed negative response of NEP to warming, but differed largely in the magnitude of response, due to differences in baseline C residence time and temperature sensitivity of decomposition. While there was a lack of response of NEP to elevated CO 2 (eCO 2 ) concentrations in the measurements, simulated NEP responded positively to eCO 2 concentrations in most models, due to the positive responses of simulated net primary production. Our study used one case study in Minnesota peatland to demonstrate that the sources of across‐model spreads in simulating transient C dynamics can be precisely traced to model structures and parameters, regardless of their complexity, given the protocol that all the matrix models were driven by the same gross primary production and environmental variables.

Hou, Enqing↗
DOE OSTI2023

Climate drivers alter nitrogen availability in surface peat and decouple N 2 fixation from CH 4 oxidation in the Sphagnum moss microbiome

Peat mosses (Sphagnum spp.) are keystone species in boreal peatlands, where they dominate net primary productivity and facilitate the accumulation of carbon in thick peat deposits. Sphagnum mosses harbor a diverse assemblage of microbial partners, including N 2 -fixing (diazotrophic) and CH 4 -oxidizing (methanotrophic) taxa that support ecosystem function by regulating transformations of carbon and nitrogen. In this work, we investigate the response of the Sphagnum phytobiome (plant + constituent microbiome + environment) to a gradient of experimental warming (+0°C to +9°C) and elevated CO 2 (+500 ppm) in an ombrotrophic peatland in northern Minnesota (USA). By tracking changes in carbon (CH 4 , CO 2 ) and nitrogen (NH 4 -N) cycling from the belowground environment up to Sphagnum and its associated microbiome, we identified a series of cascading impacts to the Sphagnum phytobiome triggered by warming and elevated CO 2 . Under ambient CO 2 , warming increased plant-available NH 4 -N in surface peat, excess N accumulated in Sphagnum tissue, and N 2 fixation activity decreased. Elevated CO 2 offset the effects of warming, disrupting the accumulation of N in peat and Sphagnum tissue. Methane concentrations in porewater increased with warming irrespective of CO 2 treatment, resulting in a ~10× rise in methanotrophic activity within Sphagnum from the +9°C enclosures. Warming's divergent impacts on diazotrophy and methanotrophy caused these processes to become decoupled at warmer temperatures, as evidenced by declining rates of methane-induced N 2 fixation and significant losses of keystone microbial taxa. In addition to changes in the Sphagnum microbiome, we observed ~94% mortality of Sphagnum between the +0°C and +9°C treatments, possibly due to the interactive effects of warming on N-availability and competition from vascular plant species. Collectively, these results highlight the vulnerability of the Sphagnum phytobiome to rising temperatures and atmospheric CO 2 concentrations, with significant implications for carbon and nitrogen cycling in boreal peatlands.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deciphering the shifting role of intrinsic and extrinsic drivers on moss decomposition in peatlands over a 5-year period

Bryophytes are largely responsible for globally significant carbon accumulation in peatland ecosystems. This accumulation is primarily caused by the slow decomposition of these mosses, which can be attributed to a combination of intrinsic (chemical) characteristics of decaying mosses and extrinsic (environmental) influences. Here we investigated the importance of intrinsic and extrinsic drivers of moss decomposition in peatlands and hypothesized that the early stages of decay will be driven primarily by intrinsic characteristics, while extrinsic drivers will become more important in the later phases of decomposition. We tested this hypothesis by placing litterbags of three moss types (Sphagnum divinum, Sphagnum angustifolium/fallax and Polytrichum sp.) into hummock and hollow microtopographies in a bog and a lawn microtopography in a nearby poor fen in northern Minnesota, USA. Decomposition was measured over a 5-year period and confirmed our hypothesis; while intrinsic and extrinsic variables were both important in driving decay rates over time, decay in the first year was primarily predicted by litter type, while extrinsic influences (e.g. peat temperature, moisture, nutrient limitation) that varied at peatland and microtopographic scales became more important by year 5. Though the nutrient (i.e. nitrogen [N] and phosphorus [P]) content of decaying mosses did not explain the variation in decay rates among litter types, analysis of N:P in moss litter suggested that litter-decaying microorganisms became increasingly P-limited over time. The majority of litter decomposition studies in peatlands are generally of short duration (< 3 years). Our study suggests that longer-term studies are needed to reveal the roles of multiple drivers of moss decay. Improving the mechanistic understanding of decomposition processes in peatlands will be critical to developing more robust representations of peatlands and their ecosystem processes in carbon and climate models.

29 poor fen↗
DOE OSTI2020

Interactive effects of elevated CO 2 , warming, reduced rainfall, and nitrogen on leaf gas exchange in five perennial grassland species

Abstract Global changes can interact to affect photosynthesis and thus ecosystem carbon capture, yet few multi‐factor field studies exist to examine such interactions. Here, we evaluate leaf gas exchange responses of five perennial grassland species from four functional groups to individual and interactive global changes in an open‐air experiment in Minnesota, USA, including elevated CO 2 (eCO 2 ), warming, reduced rainfall and increased soil nitrogen supply. All four factors influenced leaf net photosynthesis and/or stomatal conductance, but almost all effects were context‐dependent, i.e. they differed among species, varied with levels of other treatments and/or depended on environmental conditions. Firstly, the response of photosynthesis to eCO 2 depended on species and nitrogen, became more positive as vapour pressure deficit increased and, for a C 4 grass and a legume, was more positive under reduced rainfall. Secondly, reduced rainfall increased photosynthesis in three functionally distinct species, potentially via acclimation to low soil moisture. Thirdly, warming had positive, neutral or negative effects on photosynthesis depending on species and rainfall. Overall, our results show that interactions among global changes and environmental conditions may complicate predictions based on simple theoretical expectations of main effects, and that the factors and interactions influencing photosynthesis vary among herbaceous species.

Pastore, Melissa A.↗
DOE OSTI2023

Melanization slows the rapid movement of fungal necromass carbon and nitrogen into both bacterial and fungal decomposer communities and soils

Microbial necromass contributes significantly to both soil carbon (C) persistence and ecosystem nitrogen (N) availability, but quantitative estimates of C and N movement from necromass into soils and decomposer communities are lacking. Additionally, while melanin is known to slow fungal necromass decomposition, how it influences microbial C and N acquisition as well as elemental release into soils remains unclear. Here, we tracked decomposition of isotopically labeled low and high melanin fungal necromass and measured 13 C and 15 N accumulation in surrounding soils and microbial communities over 77 d in a temperate forest in Minnesota, USA. Mass loss was significantly higher from low melanin necromass, corresponding with greater 13 C and 15 N soil inputs. A taxonomically and functionally diverse array of bacteria and fungi was enriched in 13 C and/or 15 N at all sampling points, with enrichment being consistently higher on low melanin necromass and earlier in decomposition. Similar patterns of preferential C and N enrichment of many bacterial and fungal genera early in decomposition suggest that both microbial groups co-contribute to the rapid assimilation of resource-rich soil organic matter inputs. While overall richness of taxa enriched in C was higher than in N for both bacteria and fungi, there was a significant positive relationship between C and N in co-enriched taxa. Collectively, our results demonstrate that melanization acts as a key ecological trait mediating not only fungal necromass decomposition rate but also necromass C and N release and that both elements are rapidly co-utilized by diverse bacterial and fungal decomposers in natural settings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

2010-2012 Minneapolis - St. Paul Travel Behavior Inventory

The 2010-2012 Travel Behavior Inventory (TBI) provided Minnesota policymakers and researchers with data about travel in the Minneapolis - St. Paul region. It also updated the region's travel demand forecasting, including transit ridership for major transportation projects. The Metropolitan Council in the Minneapolis-St. Paul area conducted the survey. The TBI consists of a paper-based survey and a wearable global positioning system survey. The data collection process for these two surveys was independent, and the results are not intended to function together.

1Hz data↗
DOE OSTI2026

1982 The Twin Cities Metropolitan Area Travel Behavior Inventory

The purpose of the 1982 Travel Behavior Inventory was to update socioeconomic and travel data gathered in a 1970 home interview survey. The area in Minnesota studied included the counties of Ramsey, Hennepin, Dakota, Anoka, Washington, Carver, and Scott. The inventory collected demographic and travel data from September 1, 1982, to February 27, 1983. The survey contains data from 2,640 participating households. From participants' travel records, a total of 21,944 trips were reported by 6,059 household members for a 24-hour period.

1Hz data↗
DOE OSTI2025

2019 and 2022 Twin Cities Travel Behavior Inventory Surveys

# 2019 and 2022 Twin Cities Travel Behavior Inventory Surveys To help local and regional planning agencies understand shifting demographics and travel patterns, surveys were conducted in Minnesota’s greater Twin Cities region in 2019 and 2022. Survey results aided the Metropolitan Council in proposing practical transportation investments, preparing competitive grant applications, and prioritizing improvements to best fit regional needs. ## Data Collection Agency RSG conducted the surveys for the Metropolitan Council. ## Survey Methodology These mixed-mode surveys focused on bus, rail, car, micromobility, ride-hailing, and walking. Designed as household travel surveys, they were carried out in English, Spanish, Karen, Oromo, Somali, and Hmong during two timeframes: Oct. 1, 2018—Sept. 30, 2019 and June 22, 2021—Feb. 5, 2022. Participants accessed the surveys using a smartphone-based app, website, or call center. A questionnaire captured data about demographics, daily travel activities, and typical transportation patterns to inform model updates and gain information about emerging behavioral changes such as electric vehicle adoption and teleworking frequency. It also addressed the impacts of COVID-19 on participants’ typical travel behavior. ## Survey Records, Data, and Documentation Survey records include a total of 31,251 participants—16,152 participants from 7,837 households during the 2019 survey and 15,099 participants from 7,952 households during the 2022 survey.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗