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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Global field observations of tree die-off reveal hotter-drought fingerprint for Earth’s forests

Earth’s forests face grave challenges in the Anthropocene, including hotter droughts increasingly associated with widespread forest die-off events. But despite the vital importance of forests to global ecosystem services, their fates in a warming world remain highly uncertain. Lacking is quantitative determination of commonality in climate anomalies associated with pulses of tree mortality—from published, field-documented mortality events—required for understanding the role of extreme climate events in overall global tree die-off patterns. Here we established a geo-referenced global database documenting climate-induced mortality events spanning all tree-supporting biomes and continents, from 154 peer-reviewed studies since 1970. Our analysis quantifies a global “hotter-drought fingerprint” from these tree-mortality sites—effectively a hotter and drier climate signal for tree mortality—across 675 locations encompassing 1,303 plots. Frequency of these observed mortality-year climate conditions strongly increases nonlinearly under projected warming. Our database also provides initial footing for further community-developed, quantitative, ground-based monitoring of global tree mortality.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

The global spectrum of tree crown architecture

Abstract Trees can differ enormously in their crown architectural traits, such as the scaling relationships between tree height, crown width and stem diameter. Yet despite the importance of crown architecture in shaping the structure and function of terrestrial ecosystems, we lack a complete picture of what drives this incredible diversity in crown shapes. Using data from 374,888 globally distributed trees, we explore how climate, disturbance, competition, functional traits, and evolutionary history constrain the height and crown width scaling relationships of 1914 tree species. We find that variation in height–diameter scaling relationships is primarily controlled by water availability and light competition. Conversely, crown width is predominantly shaped by exposure to wind and fire, while also covarying with functional traits related to mechanical stability and photosynthesis. Additionally, we identify several plant lineages with highly distinctive stem and crown forms, such as the exceedingly slender dipterocarps of Southeast Asia, or the extremely wide crowns of legume trees in African savannas. Our study charts the global spectrum of tree crown architecture and pinpoints the processes that shape the 3D structure of woody ecosystems.

Science & Technology - Other Topics↗
DOE OSTI2021

Decadal changes in fire frequencies shift tree communities and functional traits

Global change has resulted in chronic shifts in fire regimes. Variability in the sensitivity of tree communities to multi-decadal changes in fire regimes is critical to anticipating shifts in ecosystem structure and function, yet remains poorly understood. Here, we address the overall effects of fire on tree communities and the factors controlling their sensitivity in 29 sites that experienced multi-decadal alterations in fire frequencies in savanna and forest ecosystems across tropical and temperate regions. Fire had a strong overall effect on tree communities, with an average fire frequency (one fire every three years) reducing stem density by 48% and basal area by 53% after 50 years, relative to unburned plots. Here, the largest changes occurred in savanna ecosystems and in sites with strong wet seasons or strong dry seasons, pointing to fire characteristics and species composition as important. Analyses of functional traits highlighted the impact of fire-driven changes in soil nutrients because frequent burning favoured trees with low biomass nitrogen and phosphorus content, and with more efficient nitrogen acquisition through ectomycorrhizal symbioses. Taken together, the response of trees to altered fire frequencies depends both on climatic and vegetation determinants of fire behaviour and tree growth, and the coupling between fire-driven nutrient losses and plant traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Tree foliage as a net accumulator of highly toxic methylmercury

Tree canopies are known to elevate atmospheric inputs of both mercury (Hg) and methylmercury (MeHg). While foliar uptake of gaseous Hg is well documented, little is known regarding the temporal dynamics and origins of MeHg in tree foliage, which represents typically less than 1% of total Hg in foliage. In this work, we examined the foliar total Hg and MeHg content by following the growth of five individual trees of American Beech (Fagus grandifolia) for one growing season (April–November, 2017) in North Carolina, USA. We show that similar to other studies foliar Hg content increased almost linearly over time, with daily accumulation rates ranging from 0.123 to 0.161 ng/g/day. However, not all trees showed linear increases of foliar MeHg content along the growing season; we found that 2 out of 5 trees showed elevated foliar MeHg content at the initial phase of the growing season but their MeHg content declined through early summer. However, foliar MeHg content among all 5 trees showed eventual increases through the end of the growing season, proving that foliage is a net accumulator of MeHg while foliar gain of biomass did not “dilute” MeHg content.

54 ENVIRONMENTAL SCIENCES↗
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↗
DOE OSTI2022

Properly Learning Decision Trees in almost Polynomial Time

We give an n O (log log n ) -time membership query algorithm for properly and agnostically learning decision trees under the uniform distribution over { ± 1} n . Even in the realizable setting, the previous fastest runtime was n O (log n ) , a consequence of a classic algorithm of Ehrenfeucht and Haussler. Our algorithm shares similarities with practical heuristics for learning decision trees, which we augment with additional ideas to circumvent known lower bounds against these heuristics. To analyze our algorithm, we prove a new structural result for decision trees that strengthens a theorem of O’Donnell, Saks, Schramm, and Servedio. While the OSSS theorem says that every decision tree has an influential variable, we show how every decision tree can be “pruned” so that every variable in the resulting tree is influential.

Computer Science↗
NASA NTRS1987

The fault-tree compiler

The Fault Tree Compiler Program is a new reliability tool used to predict the top event probability for a fault tree. Five different gate types are allowed in the fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N gates. The high level input language is easy to understand and use when describing the system tree. In addition, the use of the hierarchical fault tree capability can simplify the tree description and decrease program execution time. The current solution technique provides an answer precise (within the limits of double precision floating point arithmetic) to the five digits in the answer. The user may vary one failure rate or failure probability over a range of values and plot the results for sensitivity analyses. The solution technique is implemented in FORTRAN; the remaining program code is implemented in Pascal. The program is written to run on a Digital Corporation VAX with the VMS operation system.

Martensen, Anna L.↗
NASA NTRS1989

The Fault Tree Compiler (FTC): Program and mathematics

The Fault Tree Compiler Program is a new reliability tool used to predict the top-event probability for a fault tree. Five different gate types are allowed in the fault tree: AND, OR, EXCLUSIVE OR, INVERT, AND m OF n gates. The high-level input language is easy to understand and use when describing the system tree. In addition, the use of the hierarchical fault tree capability can simplify the tree description and decrease program execution time. The current solution technique provides an answer precisely (within the limits of double precision floating point arithmetic) within a user specified number of digits accuracy. The user may vary one failure rate or failure probability over a range of values and plot the results for sensitivity analyses. The solution technique is implemented in FORTRAN; the remaining program code is implemented in Pascal. The program is written to run on a Digital Equipment Corporation (DEC) VAX computer with the VMS operation system.

Butler, Ricky W.↗
NASA NTRS1988

Learning from examples - Generation and evaluation of decision trees for software resource analysis

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

Selby, Richard W.↗
NASA NTRS1989

Direct evaluation of fault trees using object-oriented programming techniques

Object-oriented programming techniques are used in an algorithm for the direct evaluation of fault trees. The algorithm combines a simple bottom-up procedure for trees without repeated events with a top-down recursive procedure for trees with repeated events. The object-oriented approach results in a dynamic modularization of the tree at each step in the reduction process. The algorithm reduces the number of recursive calls required to solve trees with repeated events and calculates intermediate results as well as the solution of the top event. The intermediate results can be reused if part of the tree is modified. An example is presented in which the results of the algorithm implemented with conventional techniques are compared to those of the object-oriented approach.

Patterson-Hine, F. A.↗
NASA NTRS1993

Fault-Tree Compiler

Fault-Tree Compiler (FTC) program, is software tool used to calculate probability of top event in fault tree. Gates of five different types allowed in fault tree: AND, OR, EXCLUSIVE OR, INVERT, and M OF N. High-level input language easy to understand and use. In addition, program supports hierarchical fault-tree definition feature, which simplifies tree-description process and reduces execution time. Set of programs created forming basis for reliability-analysis workstation: SURE, ASSIST, PAWS/STEM, and FTC fault-tree tool (LAR-14586). Written in PASCAL, ANSI-compliant C language, and FORTRAN 77. Other versions available upon request.

Butler, Ricky W.↗
NASA NTRS2004

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Shiffman, Smadar↗
NASA NTRS1994

(abstract) Characterization of Tree Water Status and Dielectric Constant Changes of North American Boreal Forests in Combination with Synthetic Aperture Radar Remote Sensing

The occurrence and magnitude of temporal and spatial tree water status changes in the boreal environment were studied in a floodplain forest in Alaska and in four forest types of Central Canada. Under limited water supply conditions from the rooted soil zone in early spring (freeze/thaw transition) and during summer, trees show declining water potentials. Coincidental change in tree water potential, tree transpiration and tree dielectric constant had been observed in previous studies performed in Mediterranean ecotones. If radar is sensitive to chances in tree water status as reflected through changes in dielectric constant, then radar remote sensing could be used to monitor the water status of forests. The SAR imagery is examined to determine the response of the radar backscatter to the ground based observations of the water status of forest canopies. Comparisons are made between stands and also along the large North-South gradient between sites. Data from SAR are used to examine the radar response to canopy physiological state as related to vegetation freeze/thaw and growing season length.

remote sensing imaging↗
NASA NTRS2008

Microwave Soil Moisture Retrieval Under Trees

Soil moisture is recognized as an important component of the water, energy, and carbon cycles at the interface between the Earth's surface and atmosphere. Current baseline soil moisture retrieval algorithms for microwave space missions have been developed and validated only over grasslands, agricultural crops, and generally light to moderate vegetation. Tree areas have commonly been excluded from operational soil moisture retrieval plans due to the large expected impact of trees on masking the microwave response to the underlying soil moisture. Our understanding of the microwave properties of trees of various sizes and their effect on soil moisture retrieval algorithms at L band is presently limited, although research efforts are ongoing in Europe, the United States, and elsewhere to remedy this situation. As part of this research, a coordinated sequence of field measurements involving the ComRAD (for Combined Radar/Radiometer) active/passive microwave truck instrument system has been undertaken. Jointly developed and operated by NASA Goddard Space Flight Center and George Washington University, ComRAD consists of dual-polarized 1.4 GHz total-power radiometers (LH, LV) and a quad-polarized 1.25 GHz L band radar sharing a single parabolic dish antenna with a novel broadband stacked patch dual-polarized feed, a quad-polarized 4.75 GHz C band radar, and a single channel 10 GHz XHH radar. The instruments are deployed on a mobile truck with an 19-m hydraulic boom and share common control software; real-time calibrated signals, and the capability for automated data collection for unattended operation. Most microwave soil moisture retrieval algorithms developed for use at L band frequencies are based on the tau-omega model, a simplified zero-order radiative transfer approach where scattering is largely ignored and vegetation canopies are generally treated as a bulk attenuating layer. In this approach, vegetation effects are parameterized by tau and omega, the microwave vegetation opacity and single scattering albedo. One goal of our current research is to determine whether the tau-omega model can work for tree canopies given the increased scatter from trees compared to grasses and crops, and. if so, what are effective values for tau and omega for trees.

O'Neill, P.↗
NASA NTRS2005

ANTLR Tree Grammar Generator and Extensions

A computer program implements two extensions of ANTLR (Another Tool for Language Recognition), which is a set of software tools for translating source codes between different computing languages. ANTLR supports predicated- LL(k) lexer and parser grammars, a notation for annotating parser grammars to direct tree construction, and predicated tree grammars. [ LL(k) signifies left-right, leftmost derivation with k tokens of look-ahead, referring to certain characteristics of a grammar.] One of the extensions is a syntax for tree transformations. The other extension is the generation of tree grammars from annotated parser or input tree grammars. These extensions can simplify the process of generating source-to-source language translators and they make possible an approach, called "polyphase parsing," to translation between computing languages. The typical approach to translator development is to identify high-level semantic constructs such as "expressions," "declarations," and "definitions" as fundamental building blocks in the grammar specification used for language recognition. The polyphase approach is to lump ambiguous syntactic constructs during parsing and then disambiguate the alternatives in subsequent tree transformation passes. Polyphase parsing is believed to be useful for generating efficient recognizers for C++ and other languages that, like C++, have significant ambiguities.

Craymer, Loring↗
DOE OSTI2025

An end-to-end deep learning solution for automated LiDAR tree detection in the urban environment

Cataloging and classifying trees in the urban environment is a crucial step in urban and environmental planning; however, manual collection and maintenance of this data is expensive and time-consuming. Although algorithmic approaches that rely on remote sensing data have been developed for tree detection in forests, they generally struggle in the more varied urban environment. This work proposes a novel end-to-end deep learning method for the detection of trees in the urban environment from remote sensing data. Specifically, we develop and train a novel PointNet-based neural network architecture to predict tree locations directly from LiDAR data augmented with multi-spectral imagery. We compare this model to a number of high-performing baselines on a large and varied dataset in the Southern California region, and find that our method outperforms all baselines in terms of tree detection ability (75.5% F-score) and positional accuracy (2.28 meter root mean squared error), while being highly efficient. We then analyze and compare the sources of errors, and how these reveal the strengths and weaknesses of each approach. Our results highlight the importance of fusing spectral and structural information for remote sensing tasks in complex urban environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Plant a Trillion Trees Campaign to Reduce Global Warming – Fleshing Out the Concept

The campaign to plant a trillion trees provided an easily understood approach to reduce the threat of global warming. However, focusing on trees does not consider that a maturing forest releases carbon (C) from dying trees offsetting C intake from growth of other trees, and results in only a one-time carbon storage benefit. Under sustainable management that harvests before forest growth slows down, forest C is transferred to wood products that substitute for fossil fuel (FF)- intensive products, reducing the carbon dioxide (CO 2 ) emissions with every harvest. Sustainably managed forests maintain growth by replanting (or regenerating), sustaining the C stored in products, as well as avoiding FF-intensive product emissions with every harvest. This paper addresses the question: Could planting more trees significantly reduce atmospheric CO 2 ; and if so, how? Survey data from many wood-producing mills show life cycle inventory (LCI) data on C that has been tracked through every stage of processing for many different wood products specific to each United States (USA) supply region, as well as C displacement measurements when substituting wood for FFintensive products. Results show that more and better-managed forest lands and more efficient product uses provide significant opportunities to reduce CO 2 emissions, especially in highly productive forest regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Sap Velocity Data for Urban Trees in Chicago, Illinois (2024-2025)

This dataset contains uncorrected sap velocity measurements using the heat ratio method (HRM) collected using ICT International SFM1x sensors at five urban sites in Chicago, Illinois, as part of the DOE CROCUS project. The data includes continuous monitoring of sap velocity from various tree species, including Maples (Acer spp.): Sugar Maple (Acer saccharum), Silver Maple (Acer saccharinum), and Red Maple (Acer rubrum); Oaks (Quercus spp.): Swamp White Oak (Quercus bicolor); American Elm (Ulmus americana); Honey Locust (Gleditsia triacanthos); Cottonwood (Populus deltoides); and Tree of Heaven (Ailanthus altissima) across Chicago State University (CSU), Northeastern Illinois University (NEIU), Northwestern University (NU), University of Illinois Chicago (UIC), and West Woodlawn "Blacks in Green" (BIG). These include both street trees and those in urban park locations. Measurements were collected at 15-20 minute intervals, depending on the sensor, and transmitted via Long Range Wide Area Network (LoRaWAN) protocols. The wireless data was collected by Sage Network (https://sagecontinuum.org/) nodes. The dataset includes sensor ID, Global Positioning System (GPS) coordinates, tree species (common and scientific names), tree identification number, diameter at breast height (DBH in cm), uncorrected sap velocity measurements (cm/hr) from both inner and outer probes, and Sage Node identifiers so the data can be mapped to related variables such as air quality and wind speed that were collected on the Sage nodes. All timestamps are in local Chicago time (CDT/CST). Quality control flags are provided using a 3-bit binary system indicating physical range violations (< -10 or > 60 cm/hr), step spikes (absolute difference > 36 cm/hr), and stuck sensor conditions (> 10 consecutive identical values). These are raw data, not corrected for wood anatomy or species-specific characteristics. Data is provided in comma separated (CSV) format. This dataset is part of a larger collection of CROCUS environmental monitoring data, including linked datasets from Air Quality Transmitter (AQT) sensors, Weather Transmitter (WXT) sensors, and Multi-Function Research LoRaWAN (MFR) Nodes. DOIs for the supporting data are provided as part of this data package.

Chicago↗