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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Soil organic matter, tree communities, and fungal communities across mycorrhizal gradients in the Eastern United States

We collected these data to investigate how mycorrhizal associations are related to soil C and N across four sites in the eastern U.S. broadleaf forest biome, which capture broad variability in climate and tree species. Our sites represented each of the four ecoregions in the eastern United States temperate forest—warm continental (New Hampshire), hot continental (Wisconsin), Prairie (Illinios), and subtropical (Georgia). This breadth naturally provided tree species diversity and allowed us to also investigate how soil C and N are related to canopy tree and EcM fungal community composition. Specifically, we analyzed the effects of mycorrhizal association, canopy tree family, and EcM fungal taxa on the proportion of C and N associated with soil minerals (MAOM) and bulk soil C:N. These are plot level data from forests in New Hampshire, Georgia, Wisconsin, and Illinois. The plots are 10 m in radius and vary across gradients of ectomycorrhizal tree basal area. Within each plot, data include the basal area of all trees >2 cm in diameter identified to species, the abundance of different fungal taxa based on ITS sequences, and the %C, %N, C:N of bulk soil and of soil density fractions (free light, occluded light, and particulate) as well as the proportion of soil C and N within each fraction. The soil data (both organic matter and fungal communities) are from the top 10 cm of the mineral soil. This also includes a meta-analysis of leaf litter k and C:N values for the tree species present in the forests.The "Tree_BA_ALL.csv" files include the basal area of all trees >2 cm in diameter at breast height within our 10 cm radii plots. The "Soil_Data_Final.csv" file contains the soil carbon and nitrogen in bulk and density fractions (concentrations as well as proportion for free light fraction (fLF), occluded light fraction (oLF), and heavy or dense fraction (HF), oxalate extractable iron and aluminum concentrations, as well as the geographic coordinates of each plot's location. The "FungiNonRelative.csv" file contains the abundances of fungal taxa identified via ITS sequencing for each plot (with the exception of 4 plots from GA where there was not enough quality DNA to extract).The "R_ReadyK.csv" and "R_Ready_CN.csv" files contain leaf litter decomposition constant (k) and C:N values from the literature for the tree species found at our sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Long-term patterns of post-fire harvest diverge among ownerships in the Pacific West, U.S.A.

Abstract Post-fire harvest (PFH) is a forest management practice designed to salvage value from burned timber, mitigate safety hazards from dead trees, reduce long-term fuels, and prepare sites for replanting. Despite public controversy and extensive ecological research, little is known about how much PFH occurs on private and public lands in the U.S. Pacific West, or how practices changed with shifting forest policy and increasing area burned over the last three decades. We mapped PFH across 2.2M burned hectares in California, Oregon, and Washington between 1986-2017 and used time series intervention analysis to compare trends in area, rate (% of burned area harvested), and mean patch size between private (0.5M ha) and federal (1.6M ha) forest land and across a gradient of burn severity. Harvest rates varied by ownership (4.9% federal, 18.6% private, 8.0% overall), and practices evolved and diverged over the study period. PFH area and rate declined across all ownerships in the mid-1990s during a period of reduced fire activity. As area burned increased between the early 2000s and late 2010s, PFH area rebounded and surpassed late-1980s levels, while rates remained relatively low. On federal lands, PFH practices shifted in the early-to-mid 1990s towards lower rates (10.3% to 3.8%) and smaller patches (6.0 to 3.3 ha), following policy changes and increased litigation. PFH rates on federal lands decreased at all levels of burn severity, with the largest decreases (6.2% to 1.2%) in forests with low tree mortality (i.e. fire refugia). Conversely, private PFH rates and mean patch sizes more than doubled in forests burned at very low-to-moderate severity. Our results highlight how PFH practices have shifted with policy, socio-economic pressure, and increasing area burned over 31 years in the Pacific West. A similar area of post-fire harvest is now dispersed over larger fires, with practices diverging substantially between ownerships.

Zuspan, Aaron (ORCID:0000000315833710)↗
NASA NTRS2017

Satellite Image Mapping of Tree Mortality in the Sierra Nevada Region of California from 2013 to 2016

Extreme drought from 2013 to 2015 has been linked to extensive tree dieback in the Sierra-Nevada region of California. Landsat satellite imagery was analysed for the region from Lake Tahoe to the southern Sequoia National Forest with the objective of understanding the patterns of tree mortality in the years of 2013 to 2015 and into the near-normal precipitation year of 2016. The main mapping results for Landsat moisture index differences from year-to-year showed that the highest coverage of tree dieback was located in the Sierra and Sequoia National Forests, at four to five times greater area each year than within any other National Park or National Forest unit. Since 2013, over 50% of the Sierra Nevada forest dieback area was detected in the mid elevation zone of 1000-2000 m. The total area of tree mortality in the lower elevation zone of 500-1000 m did not grow notably from 2015 to 2016. Within the largest California river drainages in the Sierra region, new tree mortality in 2015 was detected mainly below 1200 m elevation, whereas new tree mortality in 2016 was detected mainly at higher elevations, up to about 2200 m. In three out of the four years studied, results showed that about 60% of all new tree mortality areas were located on north-facing hill slopes.

Satellite↗
DOE OSTI2022

Mycorrhizal nutrient acquisition strategies shape tree competition and coexistence dynamics

Mycorrhizal fungi with different nutrient acquisition strategies influence plant species performance and physiology, thereby defining their trophic niche. This might drive resource competition dynamics that cumulatively impact tree species coexistence, but few manipulative experiments have directly tested this. Combining surveys and experiments in a modern coexistence theory framework, we tested how variation in mycorrhizal strategies and nutrient conditions affects plant competitive outcomes. We focused on two genera of co-occurring tree species with different mycorrhizal states: Acer (arbuscular mycorrhizal, AM) and Populus (dual mycorrhizal, but often considered predominantly ectomycorrhizal, EM). The EM and AM fungal responsiveness in Populus species varied with latitude and nitrogen (N) limitation. Host-specific soil microbiome conditioning and inorganic N fertilization combined to qualitatively affect coexistence outcomes. Lower N conditions favoured Populus over Acer trees, and N fertilization reversed this outcome for southern species, aligning with regional-scale forest mycorrhizal transitions. Results from the coexistence experiment also predict competitive exclusion between the tree species pairs, which could arise, in part, from their mycorrhizal differences and is consistent with alternative stable states in dominant forest mycorrhizal strategies. Such bistability appears in natural systems as a bimodal distribution of Populus vs. Acer tree species dominance using long-term forest inventory data. Synthesis: The magnitude and outcome of microbially mediated competition between Populus and Acer depends on soil nutrient availability, which likely relates to their mycorrhizal differentiation. These findings support the importance of mycorrhizal symbioses for contributing to large-scale biogeographical patterns of tree species trophic niche separation across soil resource gradients and bistability in forest mycorrhizal structure.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2023

Los Angeles Urban Development: Utilizing NASA Earth Observations to Evaluate the Impact of Tree Coverage on Urban Heat Mitigation

Over the last several decades the city of Los Angeles, California, has been experiencing increased temperatures resulting from the urban heat island effect. This is largely due to the expansion of developed areas which allow for the trapping of heat, posing dangerous health risks. As a solution, many organizations have turned to urban greening and tree planting initiatives to help cool vulnerable communities. NASA DEVELOP has partnered with City Plants and the City of Los Angeles, Office of Forest Management to study the role of trees in urban environments and their relation to the mitigation of local urban heat islands. This team used NASA Earth observation data spanning from 2016 to 2022, including land surface temperature and Normalized Difference Vegetation Index (NDVI) data collected from Landsat 8 Thermal Infrared Sensor (TIRS) and International Space Station (ISS) ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), respectively. Data from the National Agriculture Imagery Program (NAIP) were also used to obtain a supervised classification of tree canopy cover. Our analysis reveals a spatial and temporal connection between temperature and vegetation, suggesting that areas with more vegetation are less likely to suffer high summertime temperatures. Results also highlight the impacts of tree planting programs, such as the Vermont Corridor planting project, which increased tree canopy cover by up to 5% in the community between 2016 and 2022. These findings support the implementation of urban greening practices and inform residents and officials about how investing in trees will help mitigate increasing heat within Los Angeles.

Urban heat island↗
NASA NTRS1972

Remote sensing of changes in morphology and physiology of trees under stress

Previsual detection of Fomes annosus in pine plantations was studied. Detailed analyses of photographic imagery obtained over the Ann Arbor Test Site during 1969 and 1970 reveal that the Ektachrome Infrared film was superior to Ektachrome Aerographic, Infrared Aerographic, or Plus-X Aerographic films for detecting Fomes annosus damage. Of far more significance in controlling the accuracy of damage detection, however, was the experience of the photo interpreter. Ratio-processing of multispectral scanner data was investigated with data collected in June of 1970 and in June of 1972. Ratioing of the 1.5-1.8 and 1.0-1.4 micrometer channels gave good results at detecting openings in the crown canopy and adjacent infected trees. Combined level slicing of the 1.5-1.8 micrometer channel and the 1.5-1.8 to 1.0-1.4 micrometer ratio permitted separation and recognition of forest litter in the openings and stressed trees adjacent ot the openings.

Olson, C. F., Jr.↗
DOE OSTI2022

Climate and hydraulic traits interact to set thresholds for liana viability

Lianas, or woody vines, and trees dominate the canopy of tropical forests and comprise the majority of tropical aboveground carbon storage. These growth forms respond differently to contemporary variation in climate and resource availability, but their responses to future climate change are poorly understood because there are very few predictive ecosystem models representing lianas. We compile a database of liana functional traits (846 species) and use it to parameterize a mechanistic model of liana-tree competition. The substantial difference between liana and tree hydraulic conductivity represents a critical source of inter-growth form variation. Here, we show that lianas are many times more sensitive to drying atmospheric conditions than trees as a result of this trait difference. Further, we use our competition model and projections of tropical hydroclimate based on Representative Concentration Pathway 4.5 to show that lianas are more susceptible to reaching a hydraulic threshold for viability by 2100.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Soil fertility and drought interact to determine large variations in wood production for a hyperdominant Amazonian tree species

The productivity of the Amazon Rainforest is related to climate and soil fertility. However, the degrees to which these interactions influence multiannual to decadal variations in tree diameter growth are still poorly explored. To fill this gap, we used radiocarbon measurements to evaluate the variation in tree growth rates over the past decades in an important hyperdominant species, Eschweilera coriacea (Lecythidaceae), from six sites in the Brazilian Amazon that span a range of soil properties and climate. Using linear mixed-effects models, we show that temporal variations in mean annual diameter increment evaluated over a specific time period reflect interactions between soil fertility and the drought index (SPEI-Standardized Precipitation and Evapotranspiration Index). Our results indicate that the growth response of trees to drought is strongly dependent on soil conditions, a facet of forest productivity that is still underexplored, and which has great potential for improving predictions of future tropical tree growth in the face of projected climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Seasonal variability of forest sensitivity to heat and drought stresses: A synthesis based on carbon fluxes from North American forest ecosystems

Climate extremes such as heat waves and droughts are projected to occur more frequently with increasing temperature and an intensified hydrological cycle. It is important to understand and quantify how forest carbon fluxes respond to heat and drought stress. In this study, we developed a series of daily indices of sensitivity to heat and drought stress as indicated by air temperature (T a ) and evaporative fraction (EF). Using normalized daily carbon fluxes from the FLUXNET Network for 34 forest sites in North America, the seasonal pattern of sensitivities of net ecosystem productivity (NEP), gross ecosystem productivity (GEP) and ecosystem respiration (RE) in response to T a and EF anomalies were compared for different forest types. The results showed that warm temperatures in spring had a positive effect on NEP in conifer forests but a negative impact in deciduous forests. GEP in conifer forests increased with higher temperature anomalies in spring but decreased in summer. The drought-induced decrease in NEP, which mostly occurred in the deciduous forests, was mostly driven by the reduction in GEP. In conifer forests, drought had a similar dampening effect on both GEP and RE, therefore leading to a neutral NEP response. The NEP sensitivity to T a anomalies increased with increasing mean annual temperature. Drier sites were less sensitive to drought stress in summer. Natural forests with older stand age tended to be more resilient to the climate stresses compared to managed younger forests. The results of the Classification and Regression Tree analysis showed that seasons and ecosystem productivity were the most powerful variables in explaining the variation of forest sensitivity to heat and drought stress. Our results implied that the magnitude and direction of carbon flux changes in response to climate extremes are highly dependent on the seasonal dynamics of forests and the timing of the climate extremes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Constraining long‐term model predictions for woody growth using tropical tree rings

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO 2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO 2 (C a ). When forced with historical C a , ED2.2-hydro reproduced the magnitude of increases in intercellular CO 2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C a based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO 2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to C a and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C a . Finally, more accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C a rise predicted by biosphere models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1991

Combined fluorescence, reflectance, and ground measurements of a stressed Norway spruce forest for forest damage assessment

The detection and monitoring of stress and damage in forested areas is of utmost importance to forest managers for planning purposes. Remote sensing are the most suitable means to obtain this information. This requires that remote sensing data employed in a forest survey be properly chosen and utilized for their ability to measure canopy spectral features directly related to key tree and canopy properties that are indicators of forest health and vitality. Plant reflectance in the visible to short wave IR regions (400 to 2500 nm) provides information on its biochemical, biophysical, and morphological make up, whereas plant fluorescence in the 400 to 750 nm region is more indicative of the capacity and functioning of its photosynthetic apparatus. A measure of both these spectral properties can be used to provide an accurate assessment of stress and damage within the forest canopy. Foliar chlorophyll and nitrogen are essential biochemical constituents required for the proper functioning and maintenance of a plant's biological processes. Chlorophyll-a is the prime reactive center for photosynthesis, by which a plant converts CO2 and H2O into necessary plant products. Nitrogen forms an important component of the amino-acids, enzymes, proteins, alkaloids, and cyanogenic compounds that make up a plant, including its pigments. Both chlorophyll and nitrogen have characteristic absorption features in the visible to short wave IR region. By measuring the wavelength position and depth of these features and the fluorescence response of the foliage, the health and vitality of a canopy can be ascertained. Examples for a stressed Norway spruce forest in south-eastern Austria are presented.

Banninger, C.↗
NASA NTRS1978

Identification of wood energy resources in central Michigan

Existing biomass studies were compiled for determining their applicability in measuring forest biomass in an entirely new way. Over sixty tree-weight tables were prepared from existing tables or formulas. An estimate of forest biomass was made on a defined area by using Landsat Satellite data analysis, existing forest cover type maps and actual weighting of the entire biomass. Control plots were cruised for normal volume data and weight data, harvested and weighed to determine actual tonnage yields.

Hudson, W. D.↗
DOE OSTI2020

Groundwater Depth Overrides Tree-Species Effects on the Structure of Soil Microbial Communities Involved in Nitrogen Cycling in Plantation Forests

Microbial communities found in soil ecosystems play important roles in decomposing organic materials and recycling nutrients. A clear understanding on how biotic and abiotic factors influence the microbial community and its functional role in ecosystems is fundamental to terrestrial biogeochemistry and plant production. The purpose of this study was to investigate microbial communities and functional genes involved in nitrogen cycling as a function of groundwater depth (deep and shallow), tree species (pine and eucalypt), and season (spring and fall). Soil fungal, bacterial, and archaeal communities were determined by length heterogeneity polymerase chain reaction (LH-PCR). Soil ammonia oxidation archaeal (AOA) amoA gene, ammonia oxidation bacterial (AOB) amoA gene, nitrite oxidoreductase nrxA gene, and denitrifying bacterial narG, nirK, nirS, and nosZ genes were further studied using PCR and denaturing gradient gel electrophoresis (DGGE). Soil fungal and bacterial communities remained similar between tree species and groundwater depths, respectively, regardless of season. Soil archaeal communities remained similar between tree species but differed between groundwater depths in the spring only. Archaeal amoA for nitrification and bacterial nirK and nosZ genes for denitrification were detected in DGGE, whereas bacterial amoA and nrxA for nitrification and bacterial narG and nirS genes for denitrification were undetectable. The detected nitrification and denitrification communities varied significantly with groundwater depth. There was no significant difference of nitrifying archaeal amoA or denitrifying nirK communities between different tree species regardless of season. The seasonal difference in microbial communities and functional genes involved in nitrogen cycling suggests microorganisms exhibit seasonal dynamics that likely impact relative rates of nitrification and denitrification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Harvest Intensity Effects on Carbon Stocks and Biodiversity Are Dependent on Regional Climate in Douglas-Fir Forests of British Columbia

Temperate forests provide crucial ecosystems services as living sinks for atmospheric carbon (C) and repositories of biodiversity. Applying harvesting at intensities that minimize losses offers one means for mitigating global change. However, little is known of overstory retention levels that best conserve ecosystem services in different regional climates, and likewise as climate changes. To quantify the effect of harvest intensity on C stocks and biodiversity, we compared five harvesting intensities (clearcutting, seedtree retention, 30% patch retention, 60% patch retention, and uncut controls) across a climatic aridity gradient that ranged from humid to semi-arid in the Douglas-fir (Pseudotsuga menziesii) forests of British Columbia. We found that increased harvesting intensity reduced total ecosystem, above ground, and live tree C stocks 1 year post-harvest, and the magnitude of these losses were negatively correlated with climatic aridity. In humid forests, total ecosystem C ranged from 50% loss following clearcut harvest, to 30% loss following large patch retention harvest. In arid forests this range was 60 to 8% loss, respectively. Where lower retention harvests are sought, the small patch retention treatment protected both C stocks and biodiversity in the arid forests, whereas the seedtree method performed as well or better in the humid forests. Below ground C stocks declined by an average of 29% after harvesting, with almost all of the loss from the forest floor and none from the mineral soil. Of the secondary pools, standing and coarse deadwood declined in all harvesting treatments regardless of cutting intensity or aridity, while C stocks in fine fuels and stumps increased. The understory plant C pool declined across all harvesting intensities in the humid forests, but increased in arid forests. Shannon’s diversity and richness of tree and bryoid species declined with harvesting intensity, where tree species losses were greatest in the humid forests and bryoid losses greatest in arid forests. Shrub and herb species were unaffected. This study showed that the highest retention level was best at reducing losses in C stocks and biodiversity, and clearcutting the poorest, and while partial retention of canopy trees can reduce losses in these ecosystem services, outcomes will vary with climatic aridity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2016

DeepSAT: A Deep Learning Approach to Tree-Cover Delineation in 1-m NAIP Imagery for the Continental United States

High resolution tree cover classification maps are needed to increase the accuracy of current land ecosystem and climate model outputs. Limited studies are in place that demonstrates the state-of-the-art in deriving very high resolution (VHR) tree cover products. In addition, most methods heavily rely on commercial softwares that are difficult to scale given the region of study (e.g. continents to globe). Complexities in present approaches relate to (a) scalability of the algorithm, (b) large image data processing (compute and memory intensive), (c) computational cost, (d) massively parallel architecture, and (e) machine learning automation. In addition, VHR satellite datasets are of the order of terabytes and features extracted from these datasets are of the order of petabytes. In our present study, we have acquired the National Agriculture Imagery Program (NAIP) dataset for the Continental United States at a spatial resolution of 1-m. This data comes as image tiles (a total of quarter million image scenes with ~60 million pixels) and has a total size of ~65 terabytes for a single acquisition. Features extracted from the entire dataset would amount to ~8-10 petabytes. In our proposed approach, we have implemented a novel semi-automated machine learning algorithm rooted on the principles of "deep learning" to delineate the percentage of tree cover. Using the NASA Earth Exchange (NEX) initiative, we have developed an end-to-end architecture by integrating a segmentation module based on Statistical Region Merging, a classification algorithm using Deep Belief Network and a structured prediction algorithm using Conditional Random Fields to integrate the results from the segmentation and classification modules to create per-pixel class labels. The training process is scaled up using the power of GPUs and the prediction is scaled to quarter million NAIP tiles spanning the whole of Continental United States using the NEX HPC supercomputing cluster. An initial pilot over the state of California spanning a total of 11,095 NAIP tiles covering a total geographical area of 163,696 sq. miles has produced true positive rates of around 88 percent for fragmented forests and 74 percent for urban tree cover areas, with false positive rates lower than 2 percent for both landscapes.

Imagery↗