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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Climate drives modeled forest carbon cycling resistance and resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2) model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900 (approximating the clear-cut conditions at the time), and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP), and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Kalyn Dorheim↗
NASA NTRS2021

Climate drives modeled forest carbon cycling resistance and resilience in the Upper Great Lakes Region, USA

Forests dominate the global terrestrial carbon budget, but their ability to continue doing so in the face of a changing climate is uncertain. A key uncertainty is how forests will respond to (resistance) and recover from (resilience) rising levels of disturbance of varying intensities. This knowledge gap can optimally be addressed by integrating manipulative field experiments with ecophysiological modeling. We used the Ecosystem Demography-2.2 (ED-2.2)model to project carbon fluxes for a northern temperate deciduous forest subjected to a real-world disturbance severity manipulation experiment. ED-2.2 was run for 150 years, starting from near bare ground in 1900(approximating the clear-cut conditions at the time),and subjected to three disturbance treatments under an ensemble of climate conditions. Both disturbance severity and climate strongly affected carbon fluxes such as gross primary production (GPP),and interacted with one another. We then calculated resistance and resilience, two dimensions of ecosystem stability. Modeled GPP exhibited a two-fold decrease in mean resistance across disturbance severities of 45%, 65%, and 85% mortality; conversely, resilience increased by a factor of two with increasing disturbance severity. This pattern held for net primary production and net ecosystem production, indicating a trade-off in which greater initial declines were followed by faster recovery. Notably, however, heterotrophic respiration responded more slowly to disturbance, and its highly variable response was affected by different drivers. This work provides insight into how future conditions might affect the functional stability of mature forests in this region under ongoing climate change and changing disturbance regimes.

Kalyn Dorheim↗
DOE OSTI2020

Aboveground Wood Production Is Sustained in the First Growing Season after Phloem-Disrupting Disturbance

Carbon (C) cycling processes are particularly dynamic following disturbance, with initial responses often indicative of longer-term change. In northern Michigan, USA, we initiated the Forest Resilience Threshold Experiment (FoRTE) to identify the processes that sustain or lead to the decline of C cycling rates across multiple levels (0, 45, 65 and 85% targeted gross leaf area index loss) of disturbance severity and, in response, to separate disturbance types preferentially targeting large or small diameter trees. Simulating the effects of boring insects, we stem girdled > 3600 trees below diameter at breast height (DBH), immediately and permanently disrupting the phloem. Weekly DBH measurements of girdled and otherwise healthy trees (n > 700) revealed small but significant increases in daily aboveground wood net primary production (ANPP w ) in the 65 and 85% disturbance severity treatments that emerged six weeks after girdling. However, we observed minimal change in end-of-season leaf area index and no significant differences in annual ANPP w among disturbance severities or between disturbance types, suggesting continued C fixation by girdled trees sustained stand-scale wood production in the first growing season after disturbance. We hypothesized higher disturbance severities would favor the growth of early successional species but observed no significant difference between early and middle to late successional species’ contributions to ANPP w across the disturbance severity gradient. We conclude that ANPP w stability immediately following phloem disruption is dependent on the continued, but inevitably temporary, growth of phloem-disrupted trees. Our findings provide insight into the tree-to-ecosystem mechanisms supporting stand-scale wood production stability in the first growing season following a phloem-disrupting disturbance.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Uncertainty in land carbon budget simulated by terrestrial biosphere models: the role of atmospheric forcing

Global estimates of the land carbon sink are often based on simulations by terrestrial biosphere models (TBMs). The use of a large number of models that differ in their underlying hypotheses, structure and parameters is one way to assess the uncertainty in the historical land carbon sink. Here we show that the atmospheric forcing datasets used to drive these TBMs represent a significant source of uncertainty that is currently not systematically accounted for in land carbon cycle evaluations. We present results from three TBMs each forced with three different historical atmospheric forcing reconstructions over the period 1850–2015. We perform an analysis of variance to quantify the relative uncertainty in carbon fluxes arising from the models themselves, atmospheric forcing, and model-forcing interactions. We find that atmospheric forcing in this set of simulations plays a dominant role on uncertainties in global gross primary productivity (GPP) (75% of variability) and autotrophic respiration (90%), and a significant but reduced role on net primary productivity and heterotrophic respiration (30%). Atmospheric forcing is the dominant driver (52%) of variability for the net ecosystem exchange flux, defined as the difference between GPP and respiration (both autotrophic and heterotrophic respiration). In contrast, for wildfire-driven carbon emissions model uncertainties dominate and, as a result, model uncertainties dominate for net ecosystem productivity. At regional scales, the contribution of atmospheric forcing to uncertainty shows a very heterogeneous pattern and is smaller on average than at the global scale. We find that this difference in the relative importance of forcing uncertainty between global and regional scales is related to large differences in regional model flux estimates, which partially offset each other when integrated globally, while the flux differences driven by forcing are mainly consistent across the world and therefore add up to a larger fractional contribution to global uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Evaluating Northern Hemisphere Growing Season Net Carbon Flux in Climate Models Using Aircraft Observations

Understanding terrestrial ecosystems and their response to anthropogenic climate change requires quantification of land-atmosphere carbon exchange. However, top-down and bottom-up estimates of large-scale land-atmosphere fluxes, including the northern extratropical growing season net flux (GSNF), show significant discrepancies. We developed a data-driven metric for the GSNF using atmospheric carbon dioxide concentration observations collected during the High-Performance Instrumented Airborne Platform for Environmental Research Pole-to-Pole Observations and Atmospheric Tomography Mission flight campaigns. This aircraft-derived metric is bias-corrected using three independent atmospheric inversion systems. We estimate the northern extratropical GSNF to be 5.7 ± 0.3 Pg C and use it to evaluate net biosphere productivity from the Coupled Model Intercomparison Project phase 5 and 6 (CMIP5 and CMIP6) models. While the model-to-model spread in the GSNF has decreased in the CMIP6 models relative to that of the CMIP5 models, there is still disagreement on the magnitude and timing of seasonal carbon uptake with most models underestimating the GSNF and overestimating the length of the growing season relative to the observations. We also use an emergent constraint approach to estimate annual northern extratropical gross primary productivity to be 56 ± 17 Pg C, heterotrophic respiration to be 25 ± 13 Pg C, and net primary productivity to be 28 ± 12 Pg C. The flux inferred from these aircraft observations provides an additional constraint on large-scale gross fluxes in prognostic Earth system models that may ultimately improve our ability to accurately predict carbon-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Extending a land-surface model with <i>Sphagnum</i> moss to simulate responses of a northern temperate bog to whole ecosystem warming and elevated CO<sub>2</sub>

Abstract. Mosses need to be incorporated into Earth system models to better simulate peatland functional dynamics under the changing environment. Sphagnum mosses are strong determinants of nutrient, carbon, and water cycling in peatland ecosystems. However, most land-surface models do not include Sphagnum or other mosses as represented plant functional types (PFTs), thereby limiting predictive assessment of peatland responses to environmental change. In this study, we introduce a moss PFT into the land model component (ELM) of the Energy Exascale Earth System Model (E3SM) by developing water content dynamics and nonvascular photosynthetic processes for moss. The model was parameterized and independently evaluated against observations from an ombrotrophic forested bog as part of the Spruce and Peatland Responses Under Changing Environments (SPRUCE) project. The inclusion of a Sphagnum PFT with some Sphagnum-specific processes in ELM allows it to capture the observed seasonal dynamics of Sphagnum gross primary production (GPP) albeit with an underestimate of peak GPP. The model simulated a reasonable annual net primary production (NPP) for moss but with less interannual variation than observed, and it reproduced aboveground biomass for tree PFTs and stem biomass for shrubs. Different species showed highly variable warming responses under both ambient and elevated atmospheric CO2 concentrations, and elevated CO2 altered the warming response direction for the peatland ecosystem. Microtopography is critical: Sphagnum mosses on hummocks and hollows were simulated to show opposite warming responses (NPP decreasing with warming on hummocks but increasing in hollows), and hummock Sphagnum was modeled to have a strong dependence on water table height. The inclusion of this new moss PFT in global ELM simulations may provide a useful foundation for the investigation of northern peatland carbon exchange, enhancing the predictive capacity of carbon dynamics across the regional and global scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The response of coarse root biomass to long-term CO 2 enrichment and nitrogen application in a maturing Pinus taeda stand with a large broadleaved component

Elevated atmospheric CO 2 (eCO 2 ) typically increases aboveground growth in both growth chamber and free-air carbon enrichment (FACE) studies. We report on the impacts of eCO 2 and nitrogen amendment on coarse root biomass and net primary productivity (NPP) at the Duke FACE study, where half of the eight plots in a 30-year-old loblolly pine (Pinus taeda, L.) plantation, including competing naturally regenerated broadleaved species, were subjected to eCO 2 (ambient, aCO 2 plus 200 ppm) for 15–17 years, combined with annual nitrogen amendments (11.2 g N m -2 ) for 6 years. Allometric equations were developed following harvest to estimate coarse root (>2 mm diameter) biomass. Pine root biomass under eCO 2 increased 32%, 1.80 kg m -2 above the 5.66 kg m -2 observed in aCO 2 , largely accumulating in the top 30 cm of soil. In contrast, eCO2 increased broadleaved root biomass more than twofold (aCO 2 : 0.81, eCO 2 : 2.07 kg m -2 ), primarily accumulating in the 30–60 cm soil depth. Combined, pine and broadleaved root biomass increased 3.08 kg m -2 over aCO 2 of 6.46 kg m -2 , a 48% increase. Elevated CO 2 did not increase pine root:shoot ratio (average 0.24) but increased the ratio from 0.57 to 1.12 in broadleaved species. Averaged over the study (1997–2010), eCO 2 increased pine, broadleaved and total coarse root NPP by 49%, 373% and 86% respectively. Nitrogen amendment had smaller effects on any component, singly or interacting with eCO 2 . A sustained increase in root NPP under eCO 2 over the study period indicates that soil nutrients were sufficient to maintain root growth response to eCO 2 . These responses must be considered in computing coarse root carbon sequestration of the extensive southern pine and similar forests, and in modelling the responses of coarse root biomass of pine–broadleaved forests to CO 2 concentration over a range of soil N availability.

9 allometry↗
NASA NTRS2003

Ocean Primary Production Estimates from Terra MODIS and Their Dependency on Satellite Chlorophyll Alpha Algorithms

Simplistic models relating global satellite ocean color, temperature, and light to ocean net primary production (ONPP) are sensitive to the accuracy and limitations of the satellite estimate of chlorophyll and other input fields, as well as the primary productivity model. The standard MODIS ONPP product uses the new semi-analytic chlorophyll algorithm as its input for two ONPP indexes. The three primary MODIS chlorophyll Q estimates from MODIS, as well as the SeaWiFS 4 chlorophyll product, were used to assess global and regional performance in estimating ONPP for the full mission, but concentrating on 2001. The two standard ONPP algorithms were examined with 8-day and 39 kilometer resolution to quantify chlorophyll algorithm dependency of ONPP. Ancillary data (MLD from FNMOC, MODIS SSTD1, and PAR from the GSFC DAO) were identical. The standard MODIS ONPP estimates for annual production in 2001 was 59 and 58 GT C for the two ONPP algorithms. Differences in ONPP using alternate chlorophylls were on the order of 10% for global annual ONPP, but ranged to 100% regionally. On all scales the differences in ONPP were smaller between MODIS and SeaWiFS than between ONPP models, or among chlorophyll algorithms within MODIS. Largest regional ONPP differences were found in the Southern Ocean (SO). In the SO, application of the semi-analytic chlorophyll resulted in not only a magnitude difference in ONPP (2x), but also a temporal shift in the time of maximum production compared to empirical algorithms when summed over standard oceanic areas. The resulting increase in global ONPP (6-7 GT) is supported by better performance of the semi-analytic chlorophyll in the SO and other high chlorophyll regions. The differences are significant in terms of understanding regional differences and dynamics of ocean carbon transformations.

Essias, Wayne E.↗
NASA NTRS1998

A Method to Access Absolute fIPAR fo Vegetation in Spatially Complex Ecosystems

Arid and semi-arid lands compose a large fraction of the earth's terrestrial vegetation, and thereby contribute significantly to global atmospheric-biospheric interactions. The thorny shrubs and small trees in these semi-arid shrub lands have counterparts throughout much of the world's tropical and subtropical zones and have captured substantial areas of the world's former grasslands. The objective of our field and remotely sensed measurements in the semi-arid shrublands of Texas is to monitor interannual variability and directional change in landscape structure, ecosystem processes and atmosphere-biosphere exchanges. To understand the role ecosystems play in controlling the composition of the atmosphere, it is necessary to quantify processes such as photosynthesis and primary production, decomposition and soil carbon storage, and trace gas exchanges. Photosynthesis is the link whereby surface-atmosphere exchanges such as the radiation balance and exchange of heat, moisture, and gas can be inferred. It also describes the efficiency of carbon dioxide exchange and is directly related to the primary production of vegetation. Our efforts in this paper focus on the indirect, quantification of photosynthesis, and thereby carbon flux and net primary production, via remote sensing and direct measurements of intercepted photosynthetically active radiation (IPAR).

Wessman, Carol A.↗
NASA NTRS2016

Combining Livestock Production Information in a Process-Based Vegetation Model to Reconstruct the History of Grassland Management

Grassland management type (grazed or mown) and intensity (intensive or extensive) play a crucial role in the greenhouse gas balance and surface energy budget of this biome, both at field scale and at large spatial scale. However, global gridded historical information on grassland management intensity is not available. Combining modelled grass-biomass productivity with statistics of the grass-biomass demand by livestock, we reconstruct gridded maps of grassland management intensity from 1901 to 2012. These maps include the minimum area of managed vs. maximum area of unmanaged grasslands and the fraction of mown vs. grazed area at a resolution of 0.5deg by 0.5deg. The grass-biomass demand is derived from a livestock dataset for 2000, extended to cover the period 19012012. The grass-biomass supply (i.e. forage grass from mown grassland and biomass grazed) is simulated by the process-based model ORCHIDEE-GM driven by historical climate change, risingCO2 concentration, and changes in nitrogen fertilization. The global area of managed grassland obtained in this study increases from 6.1 x 10(exp 6) km(exp 2) in 1901 to 12.3 x 10(exp 6) kmI(exp 2) in 2000, although the expansion pathway varies between different regions. ORCHIDEE-GM also simulated augmentation in global mean productivity and herbage-use efficiency over managed grassland during the 20th century, indicating a general intensification of grassland management at global scale but with regional differences. The gridded grassland management intensity maps are model dependent because they depend on modelled productivity. Thus specific attention was given to the evaluation of modelled productivity against a series of observations from site-level net primary productivity (NPP) measurements to two global satellite products of gross primary productivity (GPP) (MODIS-GPP and SIF data). Generally, ORCHIDEE-GM captures the spatial pattern, seasonal cycle, and inter-annual variability of grassland productivity at global scale well and thus is appropriate for global applications presented here.

Livestock dataset↗
DOE OSTI2022

Near‐Surface Hydrology and Soil Properties Drive Heterogeneity in Permafrost Distribution, Vegetation Dynamics, and Carbon Cycling in a Sub‐Arctic Watershed

Abstract Discontinuous permafrost environments exhibit strong spatial heterogeneity at scales too small to be driven by weather forcing or captured by Earth System Models. Here we analyze effects of observed spatial heterogeneity in soil and vegetation properties, hydrology, and thermal dynamics on ecosystem carbon dynamics in a watershed on the Seward Peninsula in Alaska. We apply a Morris global sensitivity analysis to a process‐rich, successfully tested terrestrial ecosystem model (TEM), ecosys , varying soil properties, boundary conditions, and weather forcing. We show that landscape heterogeneity strongly impacts soil temperatures and vegetation composition. Snow depth, O‐horizon thickness, and near‐surface water content, which vary at scales of O(m), control the soil thermal regime more than an air temperature gradient corresponding to a 140 km north–south distance. High shrub productivity is simulated only in talik (perennially unfrozen) soils with high nitrogen availability. Through these effects on plant and permafrost dynamics, landscape heterogeneity impacts ecosystem productivity. Simulations with near‐surface taliks have higher microbial respiration (by 78.0 gC m −2 yr −1 ) and higher net primary productivity (by 104.9 gC m −2 yr −1 ) compared to runs with near‐surface permafrost, and simulations with high shrub productivity have outlying values of net carbon uptake. We explored the prediction uncertainty associated with ignoring observed landscape heterogeneity, and found that watershed net carbon uptake is 60% larger when heterogeneity is accounted for. Our results highlight the complexity inherent in discontinuous permafrost environments and demonstrate that missing representation of subgrid heterogeneity in TEMs could bias predictions of high‐latitude carbon budget.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1997

Pre-Launch Tasks Proposed in our Contract of December 1991

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Running, Steven W.↗
NASA NTRS1998

Pre-Launch Tasks Proposed in our Contract of December 1991

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Source record↗
NASA NTRS1997

Sensitivity of Spruce/Moss Boreal Forest Net Ecosystem Productivity to Seasonal Anomalies in Weather

Abstract. A process-oriented, daily time step model of a spruce/moss boreal ecosystem simulated 1994 and 1995 productivity for a Boreal Ecosystem-Atmosphere Study site near Thompson, Manitoba. Simulated black spruce net primary productivity (NPP) was 139 g C m(exp -2) in 1994 and 112 in 1995; feathermoss NPP was 13.0 g C m(exp -2) in 1994 and 9.7 in 1995; decomposition was 126 g C m(exp -2) in 1994 and 130 in 1995; net ecosystem productivity (NEP) was an uptake of 26.3 g C m(exp -2)in 1994 and 2.5 in 1995. A very dry period for the first half of the 1995 summer was the major cause of that year's lower productivity. Sensitivity simulations explored the impact of 2-month long warmer, cooler, wetter, and drier spells on ecosystem productivity. Warmer summers decreased spruce NPP, moss NPP, and NEP; cooler summers had the opposite effect. Earlier snowmelt (due to either warmer spring temperatures or reduced winter precipitation) increased moss and spruce NPP; later snowmelt had the opposite effect. The largest effect on decomposition was a 5% reduction due to a drier summer. One-month droughts (April through October) were also imposed on 1975 base year weather. Early summer droughts reduced moss annual NPP by -30-40%; summer droughts reduced spruce annual NPP by 10%; late summer droughts increased moss NPP by about 20% due to reduced respiration; May to September monthly droughts reduced heterotrophic respiration by about 10%. Variability in NEP was up to roughly +/- 35%. Finally, 1975 growing season precipitation was redistributed into frequent, small rainstorms and infrequent, large rainstorms. These changes had no effect on spruce NPP. Frequent rainstorms increased decomposition by a few percent, moss NPP by 50%, and NEP by 20%. Infrequent rainstorms decreased decomposition by 5%, moss NPP by 50% and NEP by 15%. The impact of anomalous weather patterns on productivity of this ecosystem depended on their timing during the year. Multiyear data sets are necessary to understand this behavior and test these types of models.

Frolking, Steve↗
NASA NTRS2016

Directional and Spectral Irradiance in Ocean Models: Effects on Simulated Global Phytoplankton, Nutrients, and Primary Production

The importance of including directional and spectral light in simulations of ocean radiative transfer was investigated using a coupled biogeochemical-circulation-radiative model of the global oceans. The effort focused on phytoplankton abundances, nutrient concentrations and vertically-integrated net primary production. The importance was approached by sequentially removing directional (i.e., direct vs. diffuse) and spectral irradiance and comparing results of the above variables to a fully directionally and spectrally-resolved model. In each case the total irradiance was kept constant; it was only the pathways and spectral nature that were changed. Assuming all irradiance was diffuse had negligible effect on global ocean primary production. Global nitrate and total chlorophyll concentrations declined by about 20% each. The largest changes occurred in the tropics and sub-tropics rather than the high latitudes, where most of the irradiance is already diffuse. Disregarding spectral irradiance had effects that depended upon the choice of attenuation wavelength. The wavelength closest to the spectrally-resolved model, 500 nm, produced lower nitrate (19%) and chlorophyll (8%) and higher primary production (2%) than the spectral model. Phytoplankton relative abundances were very sensitive to the choice of non-spectral wavelength transmittance. The combined effects of neglecting both directional and spectral irradiance exacerbated the differences, despite using attenuation at 500 nm. Global nitrate decreased 33% and chlorophyll decreased 24%. Changes in phytoplankton community structure were considerable, representing a change from chlorophytes to cyanobacteria and coccolithophores. This suggested a shift in community function, from light-limitation to nutrient limitation: lower demands for nutrients from cyanobacteria and coccolithophores favored them over the more nutrient-demanding chlorophytes. Although diatoms have the highest nutrient demands in the model, their relative abundances were generally unaffected because they only prosper in nutrient-rich regions, such as the high latitudes and upwelling regions, which showed the fewest effects from the changes in radiative simulations. The results showed that including directional and spectral irradiance when simulating the ocean light field can be important for ocean biology, but the magnitude varies with variables and regions. The quantitative results are intended to assist ocean modelers when considering improved irradiance representations relative to other processes or variables associated with the issues of interest.

Phytoplankton↗
DOE OSTI2021

Coupling plant litter quantity to a novel metric for litter quality explains C storage changes in a thawing permafrost peatland

Abstract Permafrost thaw is a major potential feedback source to climate change as it can drive the increased release of greenhouse gases carbon dioxide (CO 2 ) and methane (CH 4 ). This carbon release from the decomposition of thawing soil organic material can be mitigated by increased net primary productivity (NPP) caused by warming, increasing atmospheric CO 2 , and plant community transition. However, the net effect on C storage also depends on how these plant community changes alter plant litter quantity, quality, and decomposition rates. Predicting decomposition rates based on litter quality remains challenging, but a promising new way forward is to incorporate measures of the energetic favorability to soil microbes of plant biomass decomposition. We asked how the variation in one such measure, the nominal oxidation state of carbon (NOSC), interacts with changing quantities of plant material inputs to influence the net C balance of a thawing permafrost peatland. We found: (1) Plant productivity (NPP) increased post‐thaw, but instead of contributing to increased standing biomass, it increased plant biomass turnover via increased litter inputs to soil; (2) Plant litter thermodynamic favorability (NOSC) and decomposition rate both increased post‐thaw, despite limited changes in bulk C:N ratios; (3) these increases caused the higher NPP to cycle more rapidly through both plants and soil, contributing to higher CO 2 and CH 4 fluxes from decomposition. Thus, the increased C‐storage expected from higher productivity was limited and the high global warming potential of CH 4 contributed a net positive warming effect. Although post‐thaw peatlands are currently C sinks due to high NPP offsetting high CO 2 release, this status is very sensitive to the plant community's litter input rate and quality. Integration of novel bioavailability metrics based on litter chemistry, including NOSC, into studies of ecosystem dynamics, is needed to improve the understanding of controls on arctic C stocks under continued ecosystem transition.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Seasonal grassland productivity forecast for the U.S. Great Plains using Grass–Cast

Every spring, ranchers in the drought-prone U.S. Great Plains face the same difficult challenge —trying to estimate how much forage will be available for livestock to graze during the upcoming summer grazing season. To reduce this uncertainty in predicting forage availability, we developed an innovative new grassland productivity forecast system, named Grass-Cast, to provide science-informed estimates of growing season above ground net primary production (ANPP). Grass-Cast uses over 30 yr of historical data including weather and the satellite-derived normalized vegetation difference index (NDVI)—combined with ecosystem modeling and seasonal precipitation forecasts—to predict if rangelands in individual counties are likely to produce below-normal, near-normal, or above-normal amounts of grass biomass (lbs/ac). Grass-Cast also provides a view of rangeland productivity in the broader region, to assist in larger scale decision-making—such as where forage resources for grazing might be more plentiful if a rancher’s own region is at risk of drought. Grass-Cast is updated approximately every two weeks from April through July. Each Grass-Cast forecast provides three scenarios of ANPP for the upcoming growing season based on different precipitation outlooks. Near real-time 8-d NDVI can be used to supplement Grass-Cast in predicting cumulative growing season NDVI and ANPP starting in mid-April for the Southern Great Plains and mid-May to early June for the Central and Northern Great Plains. Here, we present the scientific basis and methods for Grass-Cast along with the county-level production forecasts from 2017 and 2018 for ten states in the U.S. Great Plains. The correlation between early growing season forecasts and the end-of growing season ANPP estimate is >50% by late May or early June. In a retrospective evaluation, we compared Grass-Cast end-of-growing season ANPP results to an independent dataset and found that the two agreed 69% of the time over a 20-yr period. Although some predictive tools exist for forecasting upcoming growing season conditions, none predict actual productivity for the entire Great Plains. The Grass-Cast system could be adapted to predict grassland ANPP outside of the Great Plains or to predict perennial biofuel grass production.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

BOREAS TE-17 Production Efficiency Model Images

A Boreal Ecosystem-Atmospheric Study (BOREAS) version of the Global Production Efficiency Model (http://www.inform.umd.edu/glopem/) was developed by TE-17 (Terrestrial Ecology) to generate maps of gross and net primary production, autotrophic respiration, and light use efficiency for the BOREAS region. This document provides basic information on the model and how the maps were generated. The data generated by the model are stored in binary image-format files. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Hall, Forrest G.↗