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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Learning from Non-Linear Ecosystem Dynamics Is Vital for Achieving Land Degradation Neutrality

Land Degradation Neutrality is one of the Sustainable Development Goal targets, requiring on-going degradation to be balanced by restoration and sustainable land management. However, restoration and efforts to prevent degradation have often failed to deliver expected benefits,despite enormous investments. Better acknowledging the close relationships between climate, land management and non-linear ecosystem dynamics can help restoration activities to meet their intended goals, while supporting climate change adaptation and mitigation. This paper is the first to link ecological theory of non-linear ecosystem dynamics to Land Degradation Neutrality offering essential insights into appropriate timings, climate-induced windows of opportunities and risks and the financial viability of investments. These novel insights are pre-requisites for meaningful o and monitoring of progress towards Land Degradation Neutrality

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Model-based analysis of environmental controls over ecosystem primary production in an alpine tundra dry meadow

We investigated several key limiting factors that control alpine tundra productivity by developing an ecosystem biogeochemistry model. The model simulates the coupled cycling of carbon (C), nitrogen (N), and phosphorus (P) and their interactions with gross primary production (GPP). It was parameterized with field observations from an alpine dry meadow ecosystem using a global optimization strategy to estimate the unknown parameters. The model, along with the estimated parameters, was first validated against independent data and then used to examine the environmental controls over plant productivity. Our results show that air temperature is the strongest limiting factor to GPP in the early growing season, N availability becomes important during the middle portion of the growing season, and soil moisture is the strongest limiting factors by late in the growing season. Overall, the controls over GPP during the growing season, from strongest to weakest, are soil moisture content, air temperature, N availability, and P availability. This simulation provides testable predictions of the shifting nature of physical and nutrient limitations on plant growth. The model also indicates that changing environmental conditions in the alpine will likely lead to changes in productivity. For example, warming eliminates the control of P availability on GPP and makes N availability surpass air temperature to become the second strongest limiting factor. In contrast, an increase in atmospheric nutrient deposition eliminates the control of N availability and enhances the importance of P availability. Furthermore, these analyses provide a quantitative and conceptual framework that can be used to test predictions and refine ecological analyses at this long-term ecological research site.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Bridging biofuel sustainability indicators and ecosystem services through stakeholder engagement

Here, continued development of cellulosic-based biofuels is needed to provide renewable energy and strengthen rural investment and development in the United States (US). To ensure biofuel development is sustainable and does not negatively affect ecosystem services, stakeholder input is necessary to identify sensitive and meaningful indicators. A major challenge is that there are substantial differences in terminology, perspectives, and methods used to quantify sustainability and ecosystem services with regard to processes, biodiversity, and socioeconomic effects. Our objectives were to identify relevant indicator categories for both perspectives using a case study from the US state of Iowa. A scientific literature review and engagement with stakeholders were used to identify 11 indicator categories associated with production, harvest, storage, and transport of cellulosic feedstocks. Five categories focus on environmental concerns (soil quality, water quality and quantity, greenhouse gas emissions, biodiversity, and productivity) and six on socioeconomic concerns (social wellbeing, energy security, external trade, profitability, resource conservation, and social acceptability). Although these indicators reflect sustainability concerns of these stakeholders, additional monitoring and stakeholder engagement are needed to support the continual improvement that is part of adaptive management.

09 BIOMASS FUELS↗
DOE OSTI2025

Linking groundwater variability to ecosystem carbon and water use efficiencies across India

Carbon use efficiency (CUE) and water use efficiency (WUE) are important indicators of ecosystem health, reflecting the balance between carbon uptake and allocation, and the relationship between carbon assimilation and water loss. Although India shows large spatiotemporal variation in water table depth (WTD), and increasing groundwater stress, the influence of WTD on ecosystem functioning remains underexplored. This study uses satellite-based, modeled, and in-situ datasets to (1) quantify variations in CUE and WUE under shallow (SWTD) and deep (DWTD) WTD conditions across six homogeneous meteorological regions (HMRs), (2) evaluate temporal roles of gross primary productivity (GPP), net primary productivity (NPP), and evapotranspiration (ET) in driving these efficiencies, and (3) examine temporal responses to WTD shifts. SWTD regions generally showed 12 to 18 % higher GPP, 10 to 15 % higher NPP, and 10 to 20 % higher ET than DWTD zones, especially in semi-arid croplands and forests, leading to 8 to 12 % higher CUE and WUE. However, in humid and heavily irrigated regions such as northeastern and hilly India, CUE was up to 10 % higher in DWTD zones, possibly due to reduced respiration and better soil aeration compared to SWTD areas affected by waterlogging. During the Kharif (wet) season, DWTD croplands in humid zones had higher efficiencies, while in the Rabi (dry) season, SWTD croplands in northern India benefited from irrigation and cooler temperatures. These results highlight strong influence of WTD on carbon and water use processes and support the need for region-specific groundwater strategies.

Carbon use efficiency↗
DOE OSTI2015

Is the ecosystem service concept improving impact assessment? Evidence from recent international practice

Considering ecosystem services (ES) could foster innovation and improve environmental and social impact assessment (ESIA) practice, but is the potential being fulfilled? In order to investigate how ES have been treated in recent international practice, three questions are asked: (i) were the tasks of an ES analysis carried out? (ii) how is such analysis integrated with other analysis presented in the ESIA? (iii) does ES analysis result in additional or improved mitigation or enhancement measures? These research questions were unfolded into 15 auxiliary questions for reviewing five ESIA reports prepared for mining, hydroelectric and transportation infrastructure projects in Africa, Asia and South America. All cases incorporated ES into ESIA to meet a requirement of the International Finance Corporation's Performance Standards on Environmental and Social Sustainability. It was found that: (i) in only three cases most tasks recommended by current guidance were adopted (ii) all reports feature a dedicated ES chapter or section, but in three of them no evidence was found that the ES analysis was integrated within impact assessment (iii) in the two ESIAs that followed guidance, ES analysis resulted in specific mitigation measures. Few evidence was found that the ES concept is improving current ESIA practice. Key challenges are: (i) integrating ES analysis in such a way that it does not duplicate other analysis; (ii) adequately characterizing the beneficiaries of ES; and (iii) quantifying ES supply for impact prediction. - Highlights: • Incorporating ecosystem services analysis in impact assessment can improve results. • Additional impacts and mitigation were identified. • Challenges include developing appropriate indicators for impact prediction. • A key challenge is integrating the concept in such a way that it does not duplicate other analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Addressing ecological effects of radiation on populations and ecosystems to improve protection of the environment against radiation: Agreed statements from a Consensus Symposium

This paper reports the output of a consensus symposium organized by the International Union of Radioecology in November 2015. The symposium gathered an academically diverse group of 30 scientists to consider the still debated ecological impact of radiation on populations and ecosystems. Stimulated by the Chernobyl and Fukushima disasters' accidental contamination of the environment, there is increasing interest in developing environmental radiation protection frameworks. Scientific research conducted in a variety of laboratory and field settings has improved our knowledge of the effects of ionizing radiation on the environment. However, the results from such studies sometimes appear contradictory and there is disagreement about the implications for risk assessment. The Symposium discussions therefore focused on issues that might lead to different interpretations of the results, such as laboratory versus field approaches, organism versus population and ecosystemic inference strategies, dose estimation approaches and their significance under chronic exposure conditions. The participating scientists, from across the spectrum of disciplines and research areas, extending also beyond the traditional radioecology community, successfully developed a constructive spirit directed at understanding discrepancies. From the discussions, the group has derived seven consensus statements related to environmental protection against radiation, which are supplemented with some recommendations. Each of these statements is contextualized and discussed in view of contributing to the orientation and integration of future research, the results of which should yield better consensus on the ecological impact of radiation and consolidate suitable approaches for efficient radiological protection of the environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

The root-zone soil moisture spectrum in a mediterranean ecosystem

Storage of water within soil pores of the root zone introduce memory effects in the dynamics of soil moisture that are considerably longer than the integral timescale of many atmospheric processes. Thus, hydro-climatic states can be “sustained” through land-surface heat and water vapor fluxes primarily because they can “feed off” on this long-term soil moisture memory. Root-zone soil moisture memory is only but one feature characterizing the spectrum of soil moisture dynamics, which is analyzed here using a combination of long-term measurements and models. In particular, the spectrum of root-zone soil moisture content in a Mediterranean ecosystem is examined using 14-years of half-hourly measurements. A distinguishing hydro-climatic feature in such ecosystems is that sources (mainly rainfall) and sinks (mainly evapotranspiration) of soil moisture are roughly out of phase with each other. For over 4 decades of time scales and 7 decades of energy, the canonical shape of the measured soil moisture spectrum is shown to be approximately Lorentzian determined by the soil moisture variance and its memory but with two exceptions: the occurrences of a peak at diurnal-to-daily time scales and a weaker peak at near annual time scales. Model calculations and spectral analysis demonstrate that diurnal and seasonal variations in hydroclimate forcing responsible for variability in evapotranspiration had minor impact on the normalized shape of the soil moisture spectrum. However, their impact was captured by adjustments in the temporal variance. These findings indicate that precipitation and not evapotranspiration variability dominates the multi-scaling properties of soil moisture variability consistent with prior climate model simulations. Furthermore, the soil moisture memory inferred by the annual peak of soil moisture (340 d) is consistent with climate model simulations, while the memory evaluated from the loss function of a linearized mass balance approach leads to a smaller value (50 d), highlighting the effect of weak non-stationarity on soil moisture variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

At the interfaces of the hydrologic sciences: Connecting water, elements, ecosystems, and people through the major contributions of Dr. Emily Bernhardt

Here, in this paper, we describe the major contributions of Professor Emily Bernhardt to the hydrologic sciences. Dr. Bernhardt’s work addresses how carbon, nutrient, and contaminant dynamics respond to a wide range of environmental perturbations that alter hydrologic dynamics within and connectivity among ecosystems. Her research leverages intensive and extensive field sampling, experimental manipulations, macroscale data harmonization and exploration, and continental to global-scale synthesis activities to uncover key drivers and patterns of the impacts human perturbations have on water and elemental cycles. Dr. Bernhardt’s research program is defined by her ability to ask questions and use approaches that explicitly consider connectivity and interfaces in a variety of ways. Here, we highlight significant contributions from Dr. Bernhardt’s work, organized by connectivity, interfaces, and interactions among and across (1) elemental cycles, (2) ecosystems, (3) watersheds, (4) scales, and (5) disciplines. We conclude with a section on Dr. Bernhardt’s impact on the hydrologic sciences and beyond through her exceptional dedication to mentorship, engagement, and service.

58 GEOSCIENCES↗
DOE OSTI2023

Experiential findings for sustainable software ecosystems to support experimental and observational science

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. Here, the study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: (i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and (ii) data management requirements for data-driven science using artificial intelligence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Advancing Terrestrial Ecosystem Science With a Novel Automated Measurement System for Sun‐Induced Chlorophyll Fluorescence for Integration With Eddy Covariance Flux Networks

Abstract Sun‐induced chlorophyll fluorescence (SIF) provides critical information on the dynamics of gross primary productivity, a unique role not readily achievable using other methods. Long‐term continuous SIF observations have the potential to advance terrestrial ecosystem science. Realizing this potential, however, requires synergistic implementation of SIF measurements within eddy covariance (EC) flux networks. There is a need for SIF systems that can integrate seamlessly with EC instrumentation to maximize synergistic use of obtained data. Here we introduce the Fluorescence Auto‐Measurement Equipment (FAME) and protocol that fulfill such a purpose. FAME is designed specifically for plug‐and‐play integration with existing EC data acquisition systems. Its innovative hardware and software designs provide versatility, extensibility, autonomous operation, and ease of maintenance for acquiring SIF data of high quality and quantity. A major novel feature of FAME is its synchronized sampling of spectral irradiance and environmental variables, allowing for more precise interpretation of the SIF signal. FAME has been deployed since September 2016 at the Missouri Ozark AmeriFlux site, providing high‐quality measurements even when air temperatures approached 40 °C. Results reveal that canopy SIF saturated or even slightly decreased at high light, similar to leaf‐level photosynthesis. Clear diurnal hysteresis was observed: For the same light, morning SIF was higher than afternoon. Dynamic energy dissipation processes and stress‐induced movements of chloroplasts and leaves may explain the observed pattern. The technology and measurement protocol introduced here advances the coordinated observation of SIF and EC fluxes and represents a step change in observational ecosystem and carbon cycle science research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Six years of ecosystem-atmosphere greenhouse gas fluxes measured in a sub-boreal forest

Carbon dioxide (CO 2 ), methane (CH 4 ), and nitrous oxide (N 2 O) are the greenhouse gases largely responsible for anthropogenic climate change. Natural plant and microbial metabolic processes play a major role in the global atmospheric budget of each. We have been studying ecosystem-atmosphere trace gas exchange at a sub-boreal forest in the northeastern United States for over two decades. Historically our emphasis was on turbulent fluxes of CO 2 and water vapor. In 2012 we embarked on an expanded campaign to also measure CH 4 and N 2 O. Here we present continuous tower-based measurements of the ecosystem-atmosphere exchange of CO 2 and CH 4 , recorded over the period 2012–2018 and reported at a 30-minute time step. Additionally, we describe a five-year (2012–2016) dataset of chamber-based measurements of soil fluxes of CO 2 , CH 4 , and N 2 O (2013–2016 only), conducted each year from May to November. These data can be used for process studies, for biogeochemical and land surface model validation and benchmarking, and for regional-to-global upscaling and budgeting analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Coupled machine learning–ecosystem ensemble models substantially improve predictions of nitrous oxide (N 2 O) fluxes from US croplands

Nitrous oxide (N 2 O) is a potent and persistent greenhouse gas, with rising atmospheric concentrations driven in part by inefficient use of synthetic nitrogen (N) fertilizers in agriculture. Predicting soil N 2 O emissions is challenging due to high spatial and temporal variability arising from complex soil biogeochemical processes. Process-based ecosystem models and standalone machine learning (ML) approaches without extensive site-specific calibration often miss high-emission episodes. Here, we show how an Ensemble Modeling System (EMS) based on outputs from an ensemble of ecosystem models coupled to an ensemble of ML models can improve predictions and understanding of N 2 O fluxes from US cropland. Trained and validated on ~12,000 N 2 O chamber measurements at 17 US Midwest sites (six crops, 35 management practices), the EMS accurately predicted daily fluxes of N 2 O at both training (R 2 = 0.84, RMSE = 16.4 g N ha −1 d −1 ) and held-out testing sites (R 2 = 0.84, RMSE = 6.2 g N ha −1 d −1 ). Analyses identified six dominant N 2 O drivers: soil organic carbon (SOC), NH 4 + , NO 3 - , water-filled pore space, temperature, and aboveground biomass production. Wet, warm soils produced large N 2 O peaks only with sufficient SOC and mineral N; in low-SOC soils, fluxes remained low. Incorporating these drivers into process-based models might significantly improve their predictive capacity. The EMS demonstrates a strong potential to predict N 2 O fluxes at unseen sites, enabling more reliable regional inventories, improved gap-filling where measurements are sparse, and enhanced understanding of mechanisms to advance targeted mitigation strategies in food, feed, and bioenergy crops.

AI↗
DOE OSTI2023

Reducing uncertainty of high-latitude ecosystem models through identification of key parameters

Abstract Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Ecosystems for Scientific Computing in the Age of AI

Scientific computing is at an inflection point. Artificial intelligence (AI) is reshaping how scientific software is developed, how teams collaborate, how projects are governed, and how the next generation is trained. Drawing on insights from a 2025 workshop report, this article argues that the future of discovery will depend on agile, robust ecosystems built through socio-technical co-design—the intentional integration of technical and human systems. This perspective is essential for ensuring that future scientific computing remains trustworthy, sustainable, and scalable. It combines advances in AI, high-performance computing, and software with new models for cross-disciplinary collaboration, education, and workforce development. Key recommendations include building modular, trustworthy AI-enabled software ecosystems; enabling teams to integrate AI into scientific workflows while preserving human creativity, integrity, and rigor; and developing adaptive training pathways that keep pace with rapid technological change. By sharing these perspectives, we hope to stimulate broader community dialogue and encourage coordinated action.

AI↗
DOE OSTI2018

Nutrient foraging by mycorrhizas: From species functional traits to ecosystem processes

1. Plant roots and the associated mycorrhizal fungal hyphae often selectively proliferate into patchily distributed soil nutrient hotspots, but interactions between these two components of a mycorrhizal root system are usually ignored or experimentally isolated in nutrient foraging studies. 2. From studies in which both roots and mycorrhizal hyphae had access to nutrient hotspots, we compiled data on root foraging precision (increase in roots in nutrient hotspots relative to outside hotspots) of plant species from different ecosystems, ranging from temperate grasslands to subtropical forests. We found that root for- aging precision across the wide range of plant species was strongly influenced by root morphology and mycorrhizal type. 3. The precision of root nutrient foraging, as a plant functional trait, may coordinate with other root traits that are related to the economics of nutrient acquisition. High foraging precision is expected to associate with the strategy of fast return on the investment in roots, such as low construction cost, high metabolic rate and rapid turnover. 4. Nutrient foraging by mycorrhizal fungi alone may be influenced by functional traits such as hyphal exploration distance, hyphal turnover, and hyphal uptake capacity and efficiency, but such data are limited to a small portion of mycorrhizal fungal species. 5. We propose a conceptual framework in which to simulate nitrogen and phosphorus acquisition from both nutrient hotspots and outside hotspots in mixed-species plant communities. Simulation outputs suggest that plant species with varying root morphology and mycorrhizal type can be adaptive to a range of nutrient heterogeneity. 6. Although there are still knowledge gaps related to nutrient foraging, as well as many unexplored plant and fungal species, we suggest that scaling nutrient foraging from individual plants to communities would advance understanding of plant species interactions and below-ground ecosystem function.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Peak season carbon exchange shifts from a sink to a source following 50+ years of herbivore exclusion in an Arctic tundra ecosystem

To date, the majority of our knowledge regarding the impacts of herbivory on arctic ecosystem function has been restricted to short-term (<5 years) exclusion or manipulation experiments. Here, our understanding of long-term responses of sustained herbivory and/or herbivore exclusion on arctic tundra ecosystem function is severely limited.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Differential Expression of Core Metabolic Functions in Candidatus Altiarchaeum Inhabiting Distinct Subsurface Ecosystems

Candidatus Altiarchaea are widespread across aquatic subsurface ecosystems and possess a highly conserved core genome, yet adaptations of this core genome to different biotic and abiotic factors based on gene expression remain unknown. Here, we investigated the metatranscriptome of two Ca. Altiarchaeum populations that thrive in two substantially different subsurface ecosystems. In Crystal Geyser, a high-CO2 groundwater system in the USA, Ca. Altiarchaeum crystalense co-occurs with the symbiont Ca. Huberiarchaeum crystalense, while in the Muehlbacher sulfidic spring in Germany, an artesian spring high in sulfide concentration, Ca. A. hamiconexum is heavily infected with viruses. We here mapped metatranscriptome reads against their genomes to analyse the in situ expression profile of their core genomes. Out of 537 shared gene clusters, 331 were functionally annotated and 130 differed significantly in expression between the two sites. Main differences were related to genes involved in cell defence like CRISPR-Cas, virus defence, replication, transcription and energy and carbon metabolism. Our results demonstrate that altiarchaeal populations in the subsurface are likely adapted to their environment while influenced by other biological entities that tamper with their core metabolism. We consequently posit that viruses and symbiotic interactions can be major energy sinks for organisms in the deep biosphere.

archaea↗
DOE OSTI2014

El Niño Southern Oscillation (ENSO) Enhances CO 2 Exchange Rates in Freshwater Marsh Ecosystems in the Florida Everglades

This research examines the relationships between El Niño Southern Oscillation (ENSO), water level, precipitation patterns and carbon dioxide (CO 2 ) exchange rates in the freshwater wetland ecosystems of the Florida Everglades. Data was obtained over a 5-year study period (2009–2013) from two freshwater marsh sites located in Everglades National Park that differ in hydrology. At the shorthydroperiod site (Taylor Slough; TS) and the long-hydroperiod site (Shark River Slough; SRS) fluctuations in precipitation patterns occurred with changes in ENSO phase, suggesting that extreme ENSO phases alter Everglades hydrology which is known to have a substantial influence on ecosystem carbon dynamics. Variations in both ENSO phase and annual net CO 2 exchange rates co-occurred with changes in wet and dry season length and intensity. Combined with site-specific seasonality in CO 2 exchanges rates, El Niño and La Niña phases magnified season intensity and CO 2 exchange rates at both sites. At TS, net CO 2 uptake rates were higher in the dry season, whereas SRS had greater rates of carbon sequestration during the wet season. As La Niña phases were concurrent with drought years and extended dry seasons, TS became a greater sink for CO 2 on an annual basis (211 to 2110 g CO 2 m -2 yr -1 ) compared to El Niño and neutral years (25 to 243.5 g CO 2 m -2 yr -1 ). SRS was a small source for CO 2 annually (1.81 to 80 g CO 2 m -2 yr -1 ) except in one exceptionally wet year that was associated with an El Niño phase (216 g CO 2 m -2 yr -1 ). Considering that future climate predictions suggest a higher frequency and intensity in El Nin˜o and La Nin˜a phases, these results indicate that changes in extreme ENSO phases will significantly alter CO 2 dynamics in the Florida Everglades.

54 ENVIRONMENTAL SCIENCES↗