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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An experimental and kinetic modeling study of the pyrolysis of isoprene, a significant biogenic hydrocarbon in naturally occurring vegetation fires

Isoprene dominates the carbon flux emitted by vegetation and constitutes 40% of non-methane biogenic emissions worldwide. Despite pyrolysis experiments at temperatures above 1000 K showing a link between isoprene combustion and aromatic species formation, comprehensive mechanistic research on isoprene is scarce in the literature. Here, in this work, we carry out an experimental and theoretical study to build, for the first time, a chemical kinetic model describing isoprene pyrolysis. The formation of polycyclic aromatic hydrocarbon (PAH) precursor species, often observed in vegetation fire plumes, is partially explained by isoprene pyrolysis experiments and theoretical modeling. Molecular dynamics (MD) simulations unveil reaction pathways from allylic isoprenyl radicals to allene and cyclopentadiene (CPD) intermediates, two relevant species detected in the experiments. Rate constants for these identified pathways are calculated using variational transition state theory to update the kinetic model, which is validated against single-pulse shock tube (SPST), and jet-stirred reactor (JSR) experimental data in the temperature range of 850–1690 K. The kinetic model presents satisfactory agreement with the SPST experimental data, and a reaction pathway analysis shows that association of propargyl radicals results in benzene formation. The JSR pathway analysis also identifies the prominent reactions for CPD, benzene, styrene, and toluene formation. Our model does not reproduce the CPD experimental profiles, indicating that additional studies are necessary. Overall, our findings advance the understanding of isoprene pyrolysis and its related atmospheric pollutants in naturally occurring vegetation fires where smoldering and oxygen-deficient combustion processes are present.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Evaluating post-fire watershed response to varying burn severity and precipitation regimes using fully-distributed and integrated hydrologic models

Wildfires can cause significant changes in vegetation and soil, which may lead to increased surface runoff and soil erosion, thereby affecting water cycling within ecosystems. This study uses the Advanced Terrestrial Simulator (ATS), an integrated and fully distributed hydrologic model at the watershed scale, to examine post-fire hydrologic responses in selected watersheds with varying burn severities in the Pacific Northwest region of the United States. The model integrates surface overland flow, subsurface flow, and canopy biophysical processes. We have developed a new fire module in ATS to account for changes in soil hydraulic properties caused by fire in the topsoil layer. Modeling results indicate that, in the year following a high-severity burn, watershed-averaged evapotranspiration decreases by 25%. Additionally, post-fire peak flows increase by 18-29% in watersheds burned with medium to high severity due to changes in soil properties. Conversely, a low-severity burn results in less than a 1% increase in post-fire peak flow. Furthermore, a high-severity fire causes a 38% reduction in the infiltration rate within the affected watershed during the first post-fire wet season. Hypothetical numerical experiments with varying precipitation regimes after a high-severity fire show that post-fire peak flows can increase by 1-29% due to fire-induced changes in soil hydraulic properties. This study highlights the importance of using fully distributed hydrologic models to quantify disturbance-feedback loops, which are essential for understanding the complexities brought about by spatial heterogeneity in post-fire landscapes.

ATS↗
DOE OSTI2025

Contributions of vegetation heterogeneity within tower footprint to CO 2 flux estimations through graph neural network modeling

Net ecosystem exchange of CO 2 (Fc) measured directly by eddy covariance towers is based on various assumptions, including large, flat and homogenous land cover type. In reality, often a tower site is not large enough for flux measurements, and landscapes consist of patches of different land cover types within the flux footprint. In addition, some portions of fluxes are contributed by different cover types when a footprint exceeds the size of the target ecosystem. The contributions of non-dominant patches to Fc are often ignored. Here, in this study, we propose a novel integrated modeling framework that combines random forest (RF) and XGBoost with a residual correction module based on a deep graph convolutional network (DeeperGCN) to simulate Fc for seven flux measurement sites in southwest Michigan. High-resolution remote sensing vegetation indices, soil properties, meteorological variables, and footprint-weighted spatial features were used as model inputs at three spatial resolutions (10 m, 20 m, 30 m), and their importance in predicting Fc with DeeperGCN was assessed. We found that residual correction using DeeperGCN significantly improved prediction accuracy, with the R 2 increasing from 0.9098 to 0.9479 for RF and from 0.9235 to 0.9433 for XGBoost. At site level, the maximum improvement in R 2 reached 0.1617. Paired t-tests confirmed that these improvements were statistically significant (p < 0.05). Among all predictors, leaf area index and incoming shortwave radiation emerged as the dominant drivers of spatial residual variation, followed by precipitation, relative humidity, and selected vegetation indices. The 20 m resolution yielded the best balance between model performance and computational efficiency. In conclusion, our modeling framework effectively captures both spatial heterogeneity and nonlinear interactions, offering a robust solution for spatially explicit flux modeling in structurally diverse ecosystems beyond the study sites.

footprint model↗
DOE OSTI2026

Gridded Vegetation and Land Unit Datasets over North America (1km x 1km) for E3SM Land Model, Version 2

Gridded 1 km land-surface-property dataset for Energy Exascale Earth System Model Land Model (ELM) simulations over North America. Thirty-metre NALCMS land cover is aggregated to the Daymet grid; vegetation classes are cross-walked to ELM plant functional types using mean-temperature-of-the-coldest-month (MTCO) rules. NetCDF includes PFT and land-unit fractions, counts, and MTCO.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Vegetation heterogeneity reflects soil thermal state and surface soil displacement in a thawing permafrost landscape

Thawing permafrost has the potential to dramatically alter the physical and ecological structure of northern landscapes. Warming of the Arctic and subsequent degradation of permafrost have created a need to assess the stability and movement of soils on hillslopes and the potential impacts on ecosystem structure. In this work, we explore the relationships among vegetation heterogeneity, soil temperature, and soil surface displacements observed from 2019 to 2022 in a watershed in the discontinuous permafrost region on the Seward Peninsula of Alaska. Vegetation heterogeneity was measured as the standard deviation (SD) of the normalized difference vegetation index (NDVI) from 3 m PlanetScope satellite imagery around each soil temperature and active layer thickness observation. Locations of observations were clustered into three soil thermal groups, warm, intermediate, and cold, based on soil temperature and active layer thickness. Average annual horizontal surface displacements were significantly lower for soils within the warm thermal group (median = 0.033 m yr −1 ) compared to soils within the cold thermal group (median = 0.090 m yr −1 ; p < 0.001). Conversely, vegetation heterogeneity was significantly higher in the warm (median = 0.014 SD NDVI; p = 0.002) and intermediate (median = 0.015 SD NDVI; p = 0.002) groups compared with the cold thermal group (median = 0.012 SD NDVI), suggesting a warming-induced shift in vegetation community complexity. Because of the observed associations of ground surface displacement rates and vegetation heterogeneity with soil thermal state, we hypothesize that warming soil conditions induce changes in the rates and patterns of hillslope erosion due to an increase in surface movement as near-surface permafrost thaws, followed by a decrease as the permafrost table deepens and excess ice content diminishes. The transition to warm soils promotes surface ecosystem transformation, shifting the dominant vegetation at the site, given the warming climatic conditions of the region. We integrated our observations of soil temperature, vegetation heterogeneity, and soil surface displacements into a conceptual model that describes the co-evolution of hillslopes and vegetation in warming permafrost environments, which is currently unrepresented in earth system models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The impact of plant‐derived fire management prescriptions on fire‐responsive bird species

Abstract In fire‐prone regions, the occurrence of some faunal species is contingent on the presence of resources that arise through post‐fire plant succession. Through planned burning, managers can alter resource availability and aim to provide the conditions required to promote biodiversity. Understanding how species occurrence changes at different spatial and temporal scales after fire is essential to achieve this goal. However, many fire prescriptions are guided primarily by the responses of fire‐sensitive plants when setting tolerable fire intervals. This approach assumes that maintaining floristic diversity will satisfy the requirements of fauna. We surveyed bird species in two semi‐arid vegetation types across an environmental gradient in south‐eastern Australia. We conducted four surveys at each of 253 sites across a 75‐year chronosequence of time since fire and used generalized additive mixed models to examine changes in the occurrence of birds in response to time since fire. Model predictions were compared to plant‐derived fire prescriptions currently guiding fire management in the region. Time since fire was a significant predictor for 18 of 28 species modeled, in at least one vegetation type, over a gradient of 1.3° of latitude. We detected considerable variation in the responses of some species, both between vegetation types and geographically within a vegetation type. Our evaluation of plant‐derived fire prescriptions suggests that the intervals considered acceptable for maintaining floristic diversity may not be sustainable for populations of birds requiring longer unburnt vegetation, with 6 of the 12 species assessed attaining a mean occurrence probability of 20.3% by the minimum tolerable fire interval, and 57.3% by the maximum tolerable fire interval, in their respective vegetation types. Our findings highlight the potential vulnerability of fire‐responsive bird species if fire prescriptions are applied in a manner that fails to account for the slow development of habitat resources needed by some species, and the variation detected within the responses of species. This highlights the need for species‐specific data collected at an appropriate spatial scale to inform management plans.

Makdissi, Rhys↗
DOE OSTI2021

Effects of different vegetation drag parameterizations on the tidal propagation in coastal marshlands

Vegetation drag is a fundamental quantity directly affecting results for both long- and short-term coastal marsh and geomorphological studies. The vegetation drag in coastal marshland has been modeled by various two-dimensional (2D) and threedimensional (3D) numerical parameterizations. 2D parameterizations treat coastal marshes as bottom roughness elements, while 3D parameterizations resolve the vertically-variable vegetation drag through the water column. However, differences in tidal propagation arising from different drag parameterizations within a single model are largely unknown, and clear guidance on parameterization selection is still missing. In this study, we implemented four vegetation drag parameterizations into the Model for Prediction Across Scales-Ocean (MPAS-O), which include 1) a 2D parameterization using land-cover type-determined Manning’s n (2DLM); 2) a 2D parameterization using vegetation-determined Manning’s n (2DVM); 3) a 3D parameterization for stiff vegetation (3DSV); and 4) a 3D parameterization for flexible vegetation (3DFV). Estimates of the flow resistance effects from these parameterizations were compared using a series of idealized tidal propagation simulations. Given the same tidal condition, flooding depth and flooding distance are the largest in the 2DLM simulations and the smallest in the 3DSV simulations. 2DVM results are the closest to the 2DLM results. 3DFV results are the closest to the average of 2DVM, 3DSV, and 3DFV results. 2DVM and 3DSV results are the least and most sensitive to the vegetation aboveground biomass, respectively. Based on the input data requirement and computational efficiency of each parameterization, a comparison summary is provided to help inform parameterization selection for specific applications. Here, the effects of these parameterizations on coastal geomorphology are further discussed, and the results demonstrate that estimates of the long-term evolution of coastal marshes and coastal morphology depend upon the selection of the vegetation drag parameterization

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Increasing evapotranspiration decouples the positive correlation between vegetation cover and warming in the Tibetan plateau

Plant growth generally responds positively to an increase in ambient temperature. Hence, most Earth system models project a continuous increase in vegetation cover in the future due to elevated temperatures. Over the last 40 years, a considerable warming trend has affected the alpine ecosystem across the Tibetan Plateau. However, we found vegetation growth in the moderately vegetated areas of the plateau were negatively related to the warming temperatures, thus resulting in a significant degradation of the vegetative cover (LAI: slope = -0.0026 per year, p < 0.05). The underlying mechanisms that caused the decoupling of the relationship between vegetation growth and warming in the region were elaborated with the analysis of water and energy variables in the ecosystem. Results indicate that high temperatures stimulated evapotranspiration and increased the water consumption of the ecosystem (with an influence coefficient of 0.34) in these degrading areas, significantly reducing water availability (with an influence coefficient of -0.68) and limiting vegetation growth. Moreover, the negative warming effect on vegetation was only observed in the moderately vegetated areas, as evapotranspiration there predominantly occupied a larger proportion of available water (compared to the wet and highly vegetated areas) and resulted in a greater increase in total water consumption in a warmer condition (compared to dry areas with lower levels of vegetation cover). These findings highlight the risk of vegetation degradation in semi-arid areas, with the degree of vulnerability depending on the level of vegetation cover. Furthermore, results demonstrate the central role of evapotranspiration in regulating water stress intensity on vegetation under elevated temperatures.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Rapid estimation of photosynthetic leaf traits of tropical plants in diverse environmental conditions using reflectance spectroscopy

Tropical forests are one of the main carbon sinks on Earth, but the magnitude of CO 2 absorbed by tropical vegetation remains uncertain. Terrestrial biosphere models (TBMs) are commonly used to estimate the CO 2 absorbed by forests, but their performance is highly sensitive to the parameterization of processes that control leaf-level CO 2 exchange. Direct measurements of leaf respiratory and photosynthetic traits that determine vegetation CO 2 fluxes are critical, but traditional approaches are time-consuming. Reflectance spectroscopy can be a viable alternative for the estimation of these traits and, because data collection is markedly quicker than traditional gas exchange, the approach can enable the rapid assembly of large datasets. However, the application of spectroscopy to estimate photosynthetic traits across a wide range of tropical species, leaf ages and light environments has not been extensively studied. Here, we used leaf reflectance spectroscopy together with partial least-squares regression (PLSR) modeling to estimate leaf respiration ( R dark25 ), the maximum rate of carboxylation by the enzyme Rubisco ( V cmax25 ), the maximum rate of electron transport ( J max25 ), and the triose phosphate utilization rate ( T p25 ), all normalized to 25°C. We collected data from three tropical forest sites and included leaves from fifty-three species sampled at different leaf phenological stages and different leaf light environments. Our resulting spectra-trait models validated on randomly sampled data showed good predictive performance for V cmax25 , J max25 , T p25 and R dark25 (RMSE of 13, 20, 1.5 and 0.3 μmol m -2 s -1 , and R 2 of 0.74, 0.73, 0.64 and 0.58, respectively). The models showed similar performance when applied to leaves of species not included in the training dataset, illustrating that the approach is robust for capturing the main axes of trait variation in tropical species. We discuss the utility of the spectra-trait and traditional gas exchange approaches for enhancing tropical plant trait studies and improving the parameterization of TBMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Consistent responses of vegetation gas exchange to elevated atmospheric CO 2 emerge from heuristic and optimization models

Elevated atmospheric CO 2 concentration is expected to increase leaf CO 2 assimilation rates, thus promoting plant growth and increasing leaf area. It also decreases stomatal conductance, allowing water savings, which have been hypothesized to drive large-scale greening, in particular in arid and semiarid climates. However, the increase in leaf area could reduce the benefits of elevated CO 2 concentration through soil water depletion. The net effect of elevated CO 2 on leaf- and canopy-level gas exchange remains uncertain. To address this question, we compare the outcomes of a heuristic model based on the Partitioning of Equilibrium Transpiration and Assimilation (PETA) hypothesis and three model variants based on stomatal optimization theory. Predicted relative changes in leaf- and canopy-level gas exchange rates are used as a metric of plant responses to changes in atmospheric CO 2 concentration. Both model approaches predict reductions in leaf-level transpiration rate due to decreased stomatal conductance under elevated CO 2 , but negligible (PETA) or no (optimization) changes in canopy-level transpiration due to the compensatory effect of increased leaf area. Leaf- and canopy-level CO 2 assimilation is predicted to increase, with an amplification of the CO 2 fertilization effect at the canopy level due to the enhanced leaf area. The expected increase in vapour pressure deficit (VPD) under warmer conditions is generally predicted to decrease the sensitivity of gas exchange to atmospheric CO 2 concentration in both models. The consistent predictions by different models that canopy-level transpiration varies little under elevated CO 2 due to combined stomatal conductance reduction and leaf area increase highlight the coordination of physiological and morphological characteristics in vegetation to maximize resource use (here water) under altered climatic conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Simulations of flaming combustion and flaming-to-smoldering transition in wildland fire spread at flame scale

Our objective in the present study is to provide basic insights into the coupling between external-gas and solid biomass vegetation processes that control the dynamics of flame spread in wildland fire problems. Here we focus on a modeling approach that resolves processes occurring at vegetation and flame scales, i.e., the formation of flammable vapors due to the thermal degradation of the solid biomass, the subsequent combustion in ambient air, the thermal feedback to the biomass through radiative and convective heat transfer, and the possible transition from flaming combustion (taking place outside of the solid biomass) to smoldering combustion (taking place inside the solid biomass). The capability uses a multiphase combustion framework and treats external-gas processes through a Large Eddy Simulation solver and solid biomass processes through a discrete particle model. The discrete particle model adopts a one-dimensional porous medium formulation, includes descriptions of drying, thermal pyrolysis, oxidative pyrolysis, and char oxidation, as well as a description of the external-gas-to-solid-biomass diffusion of oxygen mass; the discrete particle model thereby provides a treatment of in-depth oxidative processes and allows the simulation of smoldering combustion. The modeling capability is applied to the simulation of fire spread across a surrogate biomass vegetation bed corresponding to a discrete array of cylindrical-shaped, vertically-oriented, pine wood sticks, characterized by a monomodal size distribution, in horizontal flat terrain and under wind-aided conditions. The numerical results demonstrate that the model can simulate successful flaming-to-smoldering transition followed by complete biomass consumption.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska

Observations indicate shrubs are expanding across the Arctic tundra, mainly on hillslopes and primarily in response to climate warming. However, the impact topography exerts on hydrology, nutrient dynamics, and plant growth can make untangling the mechanisms behind shrub expansion difficult. We examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. Modeled biomass of the dominant plant functional types agreed well with field measurements (R 2 = 0.89) and accurately represented shrub expansion over the past 30 years inferred from satellite observations. In the well-drained crest position, canopy water potential and plant nitrogen (N) uptake was modeled to be low from plant and microbial water stress. Intermediate soil water content in the mid-slope position enhanced mineralization and plant N uptake, increasing shrub biomass. The deciduous shrub growth in the mid-slope position was further enhanced by symbiotic N 2 fixation primed by increased root carbon allocation. The gentle slope in the poorly drained lower-slope position resulted in saturated soil conditions that reduced soil O 2 concentrations, leading to lower root O 2 uptake and lower nutrient uptake and plant biomass. Additionally, a simulation that removed topographical interconnectivity between grid cells resulted in (1) a 28% underestimate of mean shrub biomass and (2) over or underestimated shrub productivity at the various hillslope positions. Our results indicate that land models need to account for hillslope-scale coupled surface and subsurface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

GriddingMachine, a database and software for Earth system modeling at global and regional scales

Land and Earth system modeling is moving towards more explicit biophysical representations, requiring increasing variety of datasets for initialization and benchmarking. However, researchers often have difficulties in identifying and integrating non-standardized datasets from various sources. We aim towards a standardized database and one-stop distribution method of global datasets. Here, we present the GriddingMachine as (1) a database of global-scale datasets commonly used to parameterize or benchmark the models, from plant traits to vegetation indices and geophysical information and (2) a cross-platform open source software to download and request a subset of datasets with only a few lines of code. The GriddingMachine datasets can be accessed either manually through traditional HTTP, or automatically using modern programming languages including Julia, Matlab, Octave, Python, and R. The GriddingMachine collections can be used for any land and Earth modeling framework and ecological research at the regional and global scales, and the number of datasets will continue to grow to meet the increasing needs of research communities.

58 GEOSCIENCES↗
DOE OSTI2020

Pronounced and unavoidable impacts of low-end global warming on northern high-latitude land ecosystems

Arctic ecosystems are particularly vulnerable to climate change because of Arctic amplification. Here, we assessed the climatic impacts of low-end, 1.5 °C, and 2.0 °C global temperature increases above pre-industrial levels, on the warming of terrestrial ecosystems in northern high latitudes (NHL, above 60 °N including pan-Arctic tundra and boreal forests) under the framework of the Inter-Sectoral Impact Model Intercomparison Project phase 2b protocol. We analyzed the simulated changes of net primary productivity, vegetation biomass, and soil carbon stocks of eight ecosystem models that were forced by the projections of four global climate models and two atmospheric greenhouse gas pathways (RCP2.6 and RCP6.0). Our results showed that considerable impacts on ecosystem carbon budgets, particularly primary productivity and vegetation biomass, are very likely to occur in the NHL areas. The models agreed on increases in primary productivity and biomass accumulation, despite considerable inter-model and inter-scenario differences in the magnitudes of the responses. The inter-model variability highlighted the inadequacies of the present models, which fail to consider important components such as permafrost and wildfire. The simulated impacts were attributable primarily to the rapid temperature increases in the NHL and the greater sensitivity of northern vegetation to warming, which contrasted with the less pronounced responses of soil carbon stocks. The simulated increases of vegetation biomass by 30–60 Pg C in this century have implications for climate policy such as the Paris Agreement. Comparison between the results at two warming levels showed the effectiveness of emission reductions in ameliorating the impacts and revealed unavoidable impacts for which adaptation options are urgently needed in the NHL ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Effects of Horizontal Resolution, Domain Size, Boundary Conditions, and Surface Heterogeneity on Coarse LES of a Convective Boundary Layer

Atmospheric properties in a convective boundary layer vary over a wide range of spatial scales and are commonly studied using large-eddy simulations (LES) in various configurations. We examine how the boundary layer depth and distribution of variability across scales are affected by LES grid spacing, domain size, inhomogeneity of surface properties, and external forcing. Two different setups of the Weather Research and Forecasting (WRF) model are analyzed. A semi-idealized configuration uses a periodic domain, flat surface, prescribed homogeneous surface heat fluxes, and horizontally uniform profiles of large-scale advective tendencies. A nested LES setup employs a larger domain and realistic initial and boundary conditions, including an interactive land surface model with representative topography and vegetation and soil types. Subdomains of identical size are analyzed for all simulations. Characteristic structure sizes are quantified using the variability scales L 50 and L 95 , defined such that features smaller than that contain 50% and 95% of the total variance, respectively. Progressive increase in L 50 from vertical velocity to temperature and moisture structures is systematically reproduced in all simulation configurations. This dependence of L 50 on the considered variable complicates the development of scale-aware parameterizations for models with grid spacing in the “terra incognita”. In simulations using a larger domain with heterogeneous surface properties, the development of internal mesoscale patterns significantly affects variance distributions inside analyzed subdomains. Sizes of boundary layer structures also strongly depend on the LES grid spacing and, in case of heterogeneous surface and topography, on location of the subdomain inside a larger computational domain.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Permafrost Formation in a Meandering River Floodplain

Abstract Permafrost influences 25% of land in the Northern Hemisphere, where it stabilizes the ground beneath communities and infrastructure and sequesters carbon. However, the coevolution of permafrost, river dynamics, and vegetation in Arctic environments remains poorly understood. As rivers meander, they erode the floodplain at cutbanks and build new land through bar deposition, creating sequences of landforms with distinct formation ages. Here we mapped these sequences along the Koyukuk River floodplain, Alaska, analyzing permafrost occurrence, and landform and vegetation types. We used radiocarbon and optically stimulated luminescence (OSL) dating to develop a floodplain age map. Deposit ages ranged from modern to 10 ka, with more younger deposits near the modern channel. Permafrost rapidly reached 50% areal extent in all deposits older than 200 years then gradually increased up to ∼85% extent for deposits greater than 4 Kyr old. Permafrost extent correlated with increases in black spruce and wetland abundance, as well as increases in permafrost extent within wetland, and shrub and scrub vegetation classes. We developed an inverse model to constrain permafrost formation rate as a function of air temperature. Permafrost extent initially increased by ∼25% per century, in pace with vegetation succession, before decelerating to <10% per millennia as insulating overbank mud and moss slowly accumulated. Modern permafrost extent on the Koyukuk floodplain therefore reflects a dynamic balance between widespread, time‐varying permafrost formation and rapid, localized degradation due to cutbank erosion that might trigger a rapid loss of permafrost with climatic warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Warming, permafrost thaw and increased nitrogen availability as drivers for plant composition and growth across the Tibetan Plateau

Permafrost-affected ecosystems are subject to warming and thawing, which can increase the availability of subsurface nitrogen (N) with consequences in otherwise N-limited tundra and alpine vegetation. Here, we quantify the extent of warming and permafrost thawing and the corresponding effects on nitrogen availability and plant growth based on a 20-year survey across 14 sites on the Tibetan Plateau. The survey showed that most sites have been subject to warming and thawing and that the upper permafrost zone across all sites was rich in inorganic N, mainly as ammonium. We further explore the efficiency of plants to utilize 15 N-labelled inorganic N over five years following 15 N addition at the permafrost table far below the main root zone. The 15 N experiment showed that deep-rooted plant species were able to utilize the labelled N. A SEM model suggests that changes in vegetation can be explained by both active layer warming and permafrost thawing and the associated changes in inorganic nitrogen availability. Our results highlight a feedback mechanism of climate warming, in which released plant-available N may favour deep-rooted plants. This can explain important changes in plant composition and growth across the sites on the Tibetan Plateau.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗