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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Model-Data Fusion Approaches for Retrospective and Predictive Assessment of the Pan-Arctic Scale Permafrost Carbon Feedback to Global Climate

Policy decisions regarding climate change mitigation and adaptation rely on having reliable projections of future climate change. Coupled climate-carbon models predict that the northern high latitudes will serve as a substantial land carbon sink during the 21stcentury, but these models lack many of the key processes governing high-latitude ecosystem processes. Arctic tundra and boreal forests are unique from other biomes particularly because of the presence of snow, ice and frozen ground, and it is important to understand the mechanisms that drive interconnected processes in these landscapes. Increasing our confidence in climate projections requires an integrated approach where existing, on-going and planned observational and experimental studies of high-latitude ecosystem processes are organized and analyzed in a framework designed to target improvements in understanding key ecosystem-climate feedbacks. For this project we designed an approach to improve our scientific understanding of the permafrost carbon feedback through broad-scale assessment of the drivers and responses of the Arctic system carbon cycle using data-driven models of simple-to-intermediate complexity. The made a valuable contribution to the first of its kind, data-driven quantitative assessment of the impact of permafrost thaw on pan-Arctic scale carbon cycle feedbacks to the global climate system. The approach drew on a conceptual framework for integrating the key system components and their underlying data within a “book-keeping” framework for assessment of the key processes driving the permafrost carbon feedback. The results provided quantitative model-data benchmarking to constrain future projections of carbon cycle responses to a warming Arctic. The framework used environmental proxy data sets examining recent-era geomorphologic land-form transitions and vegetation dynamics, through remotely-sensed data, to guide the extrapolation of site-based data on the key system components to larger regions. These products contribute to the development of finer-scale, more complex representation of permafrost carbon processes in terrestrial biogeochemistry models, to operate within coupled Earth system modeling frameworks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Warm-season net CO 2 uptake outweighs cold-season emissions over Alaskan North Slope tundra under current and RCP8.5 climate

Abstract Arctic warming has increased vegetation growth and soil respiration during recent decades. The rate of Arctic warming will likely amplify over the 21st century. Previous studies have revealed that the most severe Arctic warming occurred during the cold season (September to May). The cold-season warming has posited significant CO 2 emissions to the atmosphere via respiration, possibly offsetting warm-season (June to August) net CO 2 uptake. However, prevailing Earth system land models poorly represent cold-season CO 2 emissions, making estimates of Arctic tundra annual CO 2 budgets highly uncertain. Here, we demonstrate that an improved version of the energy exascale Earth system model (E3SM) land model (ELMv1-ECA) captures the large amount of cold-season CO 2 emissions over Alaskan Arctic tundra as reported by two independent, observationally-constrained datasets. We found that the recent seven-decades warming trend of cold-season soil temperature is three times that of the warm-season. The climate sensitivity of warm-season net CO 2 uptake, however, is threefold higher than for the cold-season net CO 2 loss, mainly due to stronger plant resilience than microbial resilience to hydroclimatic extremes. Consequently, the modeled warm-season net CO 2 uptake has a larger positive trend (0.74 ± 0.14 gC m −2 yr −1 ) than that of cold-season CO 2 emissions (0.64 ± 0.11 gC m −2 yr −1 ) from 1950 to 2017, supported by enhanced plant nutrient uptake and increased light- and water-use efficiency. With continued warming and elevated CO 2 concentrations under the representative concentration pathway (RCP) 8.5 scenario, the increasing rate of warm-season net CO 2 uptake is more than twice the rate of cold-season emissions (1.33 ± 0.32 gC m −2 yr −1 vs 0.50 ± 0.12 gC m −2 yr −1 ), making the modeled Alaskan Arctic tundra ecosystem a net CO 2 sink by 2100. However, other geomorphological and ecological disturbances (e.g. abrupt permafrost thaw, thermokarst development, landscape-scale hydrological changes, wildfire, and insects) that are not considered here might alter our conclusion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Greenhouse gas balance over thaw-freeze cycles in discontinuous zone permafrost

Peat in the discontinuous permafrost zone contains a globally significant reservoir of carbon that has undergone multiple permafrost-thaw cycles since the end of the mid-Holocene (~3700 years before present). Periods of thaw increase C decomposition rates which leads to the release of CO 2 and CH 4 to the atmosphere creating potential climate feedback. In this paper, to determine the magnitude and direction of such feedback, we measured CO 2 and CH 4 emissions and modeled C accumulation rates and radiative fluxes from measurements of two radioactive tracers with differing lifetimes to describe the C balance of the peatland over multiple permafrost-thaw cycles since the initiation of permafrost at the site. At thaw features, the balance between increased primary production and higher CH 4 emission stimulated by warmer temperatures and wetter conditions favors C sequestration and enhanced peat accumulation. Flux measurements suggest that frozen plateaus may intermittently (order of years to decades) act as CO 2 sources depending on temperature and net ecosystem respiration rates, but modeling results suggest that—despite brief periods of net C loss to the atmosphere at the initiation of thaw—integrated over millennia, these sites have acted as net C sinks via peat accumulation. In greenhouse gas terms, the transition from frozen permafrost to thawed wetland is accompanied by increasing CO 2 uptake that is partially offset by increasing CH 4 emissions. Finally, in the short-term (decadal time scale) the net effect of this transition is likely enhanced warming via increased radiative C emissions, while in the long-term (centuries) net C deposition provides a negative feedback to climate warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Carbon Density and Anthropogenic Land Use Influences on Net Land-Use Change Emissions

We examine historical and future land-use emissions using a simple mechanistic carbon-cycle model with regional and ecosystem specific parameterizations. Our central estimate of net terrestrial land-use change emissions, exclusive of climate feedbacks, is 250 GtC over the last three hundred years. This estimate is most sensitive to assumptions for preindustrial forest and soil carbon densities. We also find that estimates are sensitive to the treatment of crop and pasture lands. These sensitivities also translate into differences in future terrestrial uptake in the RCP4.5 land-use scenario. This estimate of future uptake is lower than the native values from the GCAM integrated assessment model result due to lower net reforestation in the RCP4.5 gridded land-use data product

Smith, Steven J.↗
DOE OSTI2023

Widespread spring phenology effects on drought recovery of Northern Hemisphere ecosystems

The time required for an ecosystem to recover from severe drought is a key component of ecological resilience. The phenology effects on drought recovery are, however, poorly understood. These effects centre on how phenology variations impact biophysical feedbacks, vegetation growth and, ultimately, recovery itself. Using multiple remotely sensed datasets, we found that more than half of ecosystems in mid- and high-latitudinal Northern Hemisphere failed to recover from extreme droughts within a single growing season. Earlier spring phenology in the drought year slowed drought recovery when extreme droughts occurred in mid-growing season. Delayed spring phenology in the subsequent year slowed drought recovery for all vegetation types (with importance of spring phenology ranging from 46% to 58%). The phenology effects on drought recovery were comparable to or larger than other well-known postdrought climatic factors. These results strongly suggest that the interactions between vegetation phenology and drought must be incorporated into Earth system models to accurately quantify ecosystem resilience.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Woody plants optimise stomatal behaviour relative to hydraulic risk

Abstract Stomatal response to environmental conditions forms the backbone of all ecosystem and carbon cycle models, but is largely based on empirical relationships. Evolutionary theories of stomatal behaviour are critical for guarding against prediction errors of empirical models under future climates. Longstanding theory holds that stomata maximise fitness by acting to maintain constant marginal water use efficiency over a given time horizon, but a recent evolutionary theory proposes that stomata instead maximise carbon gain minus carbon costs/risk of hydraulic damage. Using data from 34 species that span global forest biomes, we find that the recent carbon‐maximisation optimisation theory is widely supported, revealing that the evolution of stomatal regulation has not been primarily driven by attainment of constant marginal water use efficiency. Optimal control of stomata to manage hydraulic risk is likely to have significant consequences for ecosystem fluxes during drought, which is critical given projected intensification of the global hydrological cycle.

Anderegg, William R. L.↗
NASA NTRS2014

The Role of Temporal Evolution in Modeling Atmospheric Emissions from Tropical Fires

Fire emissions associated with tropical land use change and maintenance influence atmospheric composition, air quality, and climate. In this study, we explore the effects of representing fire emissions at daily versus monthly resolution in a global composition-climate model. We find that simulations of aerosols are impacted more by the temporal resolution of fire emissions than trace gases such as carbon monoxide or ozone. Daily-resolved datasets concentrate emissions from fire events over shorter time periods and allow them to more realistically interact with model meteorology, reducing how often emissions are concurrently released with precipitation events and in turn increasing peak aerosol concentrations. The magnitude of this effect varies across tropical ecosystem types, ranging from smaller changes in modeling the low intensity, frequent burning typical of savanna ecosystems to larger differences when modeling the short-term, intense fires that characterize deforestation events. The utility of modeling fire emissions at a daily resolution also depends on the application, such as modeling exceedances of particulate matter concentrations over air quality guidelines or simulating regional atmospheric heating patterns.

aerosols↗
DOE OSTI2021

Modeled Surface-Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks

The eddy covariance (EC) method is one of the most widely used approaches to quantify surface-atmosphere fluxes. However, scaling up from a single EC tower to the landscape remains an open challenge. To address this, we used 63 site years of data to examine simulated annual and growing season sums of carbon fluxes from three paired land-cover type sites of corn, restored-prairie, and switchgrass ecosystems. This was also done across the landscape by modeling fluxes using different land-cover type input data. An artificial neural network (ANN) approach was used to model net ecosystem exchange (NEE), ecosystem respiration (R eco ), and gross primary production (GPP) at one paired site using environmental observations from the second site only. With a mean spatial separation of 11 km between paired sites, we were able to model annual sums of NEE, R eco , and GPP with uncertainties of 20%, 22%, and 8%, respectively, relative to observation sums. When considering the growing season only, model uncertainties were 17%, 22%, and 9%, respectively for the three flux terms. We also show that ANN models can estimate sums of R eco and GPP fluxes without needing the constraint of similar land-cover-type, with annual uncertainties of 12% and 10%. These results provide new insights to scaling up observations from one EC site beyond the footprint of the EC tower to multiple land-cover types across the landscape.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Octofitter: Fast, Flexible, and Accurate Orbit Modeling to Detect Exoplanets

As next-generation imaging instruments and interferometers search for planets closer to their stars, they must contend with increasing orbital motion and longer integration times. These compounding effects make it difficult to detect faint planets but also present an opportunity. Increased orbital motion makes it possible to move the search for planets into the orbital domain, where direct images can be freely combined with the radial velocity and proper motion anomaly, even without a confirmed detection in any single epoch. In this paper, we present a fast and differentiable multimethod orbit-modeling and planet detection code called Octofitter. This code is designed to be highly modular and allows users to easily adjust priors, change parameterizations, and specify arbitrary function relations between the parameters of one or more planets. Octofitter further supplies tools for examining model outputs including prior and posterior predictive checks and simulation-based calibration. We demonstrate the capabilities of Octofitter on real and simulated data from different instruments and methods, including HD 91312, simulated JWST/NIRISS aperture masking interferometry observations, radial velocity curves, and grids of images from the Gemini Planet Imager. We show that Octofitter can reliably recover faint planets in long sequences of images with arbitrary orbital motion. This publicly available tool will enable the broad application of multiepoch and multimethod exoplanet detection, which could improve how future targeted ground- and space-based surveys are performed. Finally, its rapid convergence makes it a useful addition to the existing ecosystem of tools for modeling the orbits of directly imaged planets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

Development of mpi_EPIC model for global agroecosystem modeling

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmental effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

Abstract Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial‐based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial‐enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal‐spatial scales. The dormancy model consistently produced better match with field‐observed heterotrophic soil CO 2 efflux ( R H ) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 Pg C yr −1 ). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon‐to‐nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale‐dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial‐based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

He, Yujie↗
DOE OSTI2014

Satellite remote sensing data can be used to model marine microbial metabolite turnover

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10-6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

NASA GRC ICME Schema for Materials Data Management: An Executive Summary

Integrated Computational Materials Engineering (ICME) has received a growing emphasis in attention due its potential impact on rapid material design, reduction in cost and time to market for new applications, and the promise of ‘fit-for-purpose’ materials coupled with recent advances in high performance computing and material characterization tools. However, for an organization to implement ICME practices for material discovery and design, a series of both technical and cultural challenges must be overcome to foster an environment that enables efficient, traceable, and predictive multiscale simulations of material behavior to enable virtual design of materials. In 2016, NASA sponsored a 2040 Vision study to define the potential 25-year future state required for integrated multiscale modeling of materials and systems to improve both the associated time and cost for aerospace and aeronautical innovation. The study envisions a cyber-physical-social ecosystem of experimentally validated computational models, tools, and techniques, along with the associated digital tapestry, that can enable rapid, optimized, ‘fit-for-purpose’ design of materials, components, and systems. A key requirement for such an ecosystem is the development of a robust information management system for materials across their full lifecycle, including material pedigree, experimental (real) and virtual (simulation) data, developed material models, and the implementation of models in engineering applications, such that process-structure-property-performance relationships can be established, thereby enabling the virtual design and optimization of materials. Such an information management system must be able to effectively capture: i) material information at each length scale; ii) test data and analysis; iii) associated material models; and iv) material and model deployment in engineering applications. These systems must also provide traceability between experimental and virtual representations of the material to ensure, when appropriate, the material digital twin is maintained. Additionally, this robust material information management system must be able to seamlessly connect with both commercial and an organization’s in-house software tools, be they analysis tools, other material databases, product lifecycle management (PLM) or simulation data management (SDM) tools, etc., such that automation of the design and analysis of a material across multiple length scales is possible. In this paper, an executive summary of the NASA GRC ICME Schema for materials information management is presented. The database best practices and schema design philosophy specifically for ICME materials data management and an overview description of each element in the schema is given, along with its associated role in an ICME workflow. Additionally, auxiliary tools that interact with the database and provide judicious automation with regards to importing, exporting, and analyzing materials data are presented. Such tools are critical to an ICME ecosystem, not only for their role in enabling optimization, but also in relieving users of tedious manual tasks, thus helping to promote adoption and combat the cultural challenges organizations face in enabling ICME.

Materials↗
DOE OSTI2015

Identifying multiscale zonation and assessing the relative importance of polygon geomorphology on carbon fluxes in an Arctic tundra ecosystem

Abstract We develop a multiscale zonation approach to characterize the spatial variability of Arctic polygonal ground geomorphology and to assess the relative controls of these elements on land surface and subsurface properties and carbon fluxes. Working within an ice wedge polygonal region near Barrow, Alaska, we consider two scales of zonation: polygon features (troughs, centers, and rims of polygons) that are nested within different polygon types (high, flat, and low centered). In this study, we first delineated polygons using a digital elevation map and clustered the polygons into four types along two transects, using geophysical and kite‐based landscape‐imaging data sets. We extrapolated those data‐defined polygon types to all the polygons over the study site, using the polygon statistics extracted from the digital elevation map. Based on the point measurements, we characterized the distribution of vegetation, hydrological, thermal, and geochemical properties, as well as carbon fluxes, all as a function of polygon types and polygon features. Results show that nested polygon geomorphic zonation—polygon types and polygon features—can be used to represent distinct distributions of carbon fluxes and associated properties, as well as covariability among those properties. Importantly, the results indicate that polygon types have more power to explain the variations in those properties than polygon features. The approach is expected to be useful for improved system understanding, site characterization, and parameterization of numerical models aimed at predicting ecosystem feedbacks to the climate.

Wainwright, Haruko M.↗
DOE OSTI2023

Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)

Abstract. Vegetation plays a key role in the global carbon cycle and thus is an important component within Earth system models (ESMs) that project future climate. Many ESMs are adopting methods to resolve plant size and ecosystem disturbance history, using vegetation demographic models. These models make it feasible to conduct more realistic simulation of processes that control vegetation dynamics. Meanwhile, increasing understanding of the processes governing plant water use, and ecosystem responses to drought in particular, has led to the adoption of dynamic plant water transport (i.e., hydrodynamic) schemes within ESMs. However, the extent to which variations in plant hydraulic traits affect both plant water stress and the risk of mortality in trait-diverse tropical forests is understudied. In this study, we report on a sensitivity analysis of an existing hydrodynamic scheme (HYDRO) model that is updated and incorporated into the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) (FATES–HYDRO V1.0). The size- and canopy-structured representation within FATES is able to simulate how plant size and hydraulic traits affect vegetation dynamics and carbon–water fluxes. To better understand this new model system, and its functionality in tropical forest systems in particular, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We assembled 942 observations of plant hydraulic traits on 306 tropical plant species for stomata, leaves, stems, and roots and determined the best-fit statistical distribution for each trait, which was used in model parameter sampling to assess the parametric sensitivity. We showed that, for simulated leaf water potential and loss of hydraulic conductivity across different plant organs, the four most important traits were associated with xylem conduit taper (buffers increasing hydraulic resistance with tree height), stomatal sensitivity to leaf water potential, maximum stem hydraulic conductivity, and the partitioning of total hydraulic resistance above vs. belowground. Our analysis of individual ensemble members revealed that trees at a high risk of hydraulic failure and potential tree mortality generally have a lower conduit taper, lower maximum xylem conductivity, lower stomatal sensitivity to leaf water potential, and lower resistance to xylem embolism for stem and transporting roots. We expect that our results will provide guidance on future modeling studies using plant hydrodynamic models to predict the forest responses to droughts and future field campaigns that aim to better parameterize plant hydrodynamic models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

An integrated environmental and health performance quantification model for pre-occupancy phase of buildings in China

To comprehensively pre-evaluate the damages to both the environment and human health due to construction activities in China, this paper presents an integrated building environmental and health performance (EHP) assessment model based on the Building Environmental Performance Analysis System (BEPAS) and the Building Health Impact Analysis System (BHIAS) models and offers a new inventory data estimation method. The new model follows the life cycle assessment (LCA) framework and the inventory analysis step involves bill of quantity (BOQ) data collection, consumption data formation, and environmental profile transformation. The consumption data are derived from engineering drawings and quotas to conduct the assessment before construction for pre-evaluation. The new model classifies building impacts into three safeguard areas: ecosystems, natural resources and human health. Thus, this model considers environmental impacts as well as damage to human wellbeing. The monetization approach, distance-to-target method and panel method are considered as optional weighting approaches. Finally, nine residential buildings of different structural types are taken as case studies to test the operability of the integrated model through application. The results indicate that the new model can effectively pre-evaluate building EHP and the structure type significantly affects the performance of residential buildings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

EcoFAB: Advancing microbiome science through standardized fabricated ecosystems

The vital role microbiomes play in ecosystems and for human health is now apparent. Great progress has been made by using model systems to gain insight into host-microbe interactions, yet lack of standardized reproducible experimental systems and methods greatly limits microbiome science. Recent successes highlight the importance of developing these types of systems to deconstruct mechanisms mediating host-microbe interactions. Standardization of ‘fabricated ecosystems’ would enable detailed mechanistic interrogation and more effective knowledge transfer between researchers – analogous to the significant impact model organisms and cell systems have had in molecular and cell biology. To advance these efforts we advocate for strategies and overarching themes to enable communities of scientists to work together to develop standardized laboratory microbial consortia for studying host-associated microbiomes.

Zengler, Karsten↗