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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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NASA NTRS2018

Hydraulic Diversity of Forests Regulates Ecosystem Resilience During Drought

Plants influence the atmosphere through fluxes of carbon, water and energy, and can intensify drought through land–atmosphere feedback effects. The diversity of plant functional traits in forests, especially physiological traits related to water (hydraulic) transport, may have a critical role in land–atmosphere feedback, particularly during drought. Here we combine 352 site-years of eddy covariance measurements from 40 forest sites, remote-sensing observations of plant water content and plant functional-trait data to test whether the diversity in plant traits affects the response of the ecosystem to drought. We find evidence that higher hydraulic diversity buffers variation in ecosystem flux during dry periods across temperate and boreal forests. Hydraulic traits were the predominant significant predictors of cross-site patterns in drought response. By contrast, standard leaf and wood traits, such as specific leaf area and wood density, had little explanatory power. Our results demonstrate that diversity in the hydraulic traits of trees mediates ecosystem resilience to drought and is likely to have an important role in future ecosystem–atmosphere feedback effects in a changing climate.

Climate and Earth system modelling↗
NASA NTRS2024

Effects of Water Limitation and Competition on Tree Carbon Allocation in an Earth System Modeling Framework

Earth system models (ESMs) have a limited capacity to represent plant functional diversity and shifts in trait distributions. Approaches to improving the representation of this complexity in ESMs include (i) optimality-based approaches that predict trait–environment responses and (ii) explicitly modelling coexistence and community assembly. These approaches are expected to converge only when optimality-based approaches identify competitively dominant strategies, which often differ from strategies that maximize ecosystem functioning or fitness components in monoculture. We used two models, LM3-PPA (a vegetation demographic model designed as an ESM component) and BiomeE (a computationally efficient analog for LM3-PPA), to explore how water limitation affects carbon allocation strategies of canopy trees. We compared competitive allocation strategies and those that maximize biomass or productivity in monoculture. We did not explicitly model coexistence or community assembly. Rather, we used model experiments to identify competitive and maximizing strategies in a two-dimensional trait space under different precipitation and mortality scenarios. At 10 eastern US locations, we simulated historical, wet and dry climate scenarios, novel drought and three different mortality scenarios (low, medium or high sensitivity to water deficit). For each site and scenario, we identified the competitive strategy and three maximizing strategies (maximum biomass, productivity or drought-tolerance). Root: leaf ratios tended to increase and leaf area tended to decrease with increasing water stress (increasing water limitation and its effects on mortality). However, relative to maximizing strategies, competitive strategies shifted towards greater allocation to roots and leaves with increasing water stress. Competitive overinvestments (greater allocation to roots and leaves by competitive strategies compared with maximizing strategies) were robust across different modelling contexts, including vegetation parameter sets (Acer vs. Populus), models (LM3-PPA vs. BiomeE) and uncalibrated vs. calibrated BiomeE versions. Synthesis: The theoretical prediction that competitive and maximizing allocation strategies differ under water limitation is confirmed for a demographic model designed as an ESM component. Optimality-based trait predictions can simplify representing trait diversity in ESMs but do not always correspond to competitive outcomes. Explicitly modelling coexistence and community assembly in ESMs is challenging but is likely the most general approach to representing trait diversity.

vegetation demographic model↗
NASA NTRS2009

The Crop Evaluation Research for Environmental Strategies (CERES) Remote Sensing 2008 Project Activities

In recent years, the use of Plant Incorporated Protectant (PIP) corn by American producers has been increasing dramatically. PIP corn contains genetically inserted traits that produce toxins in the plant that provide narrowly targeted protection against specific insect pests. The plant producing t oxms can offer significant reductions in the application of broad -spectrum pesticides that have ecological and human health consequences. PIP corn as a percentage of total corn acreage planted in the US is expected to continue to increase as these protective traits are "stacked" with other desirable traits by seed companies, and producers are seeing considerable increases in corn yield as a result. The introduction of corn as a bio-fuel source for ethanol has increased production by over 6 million hectares in 2007. The United States Environmental Protection Agency (USEPA), which is responsible for the registration of PIP crops under the Federal Insecticide, Fungicide and Rodenticide Act, views the use of PIP corn as positive. Broad spectrum pesticide use has declined since the PIP traits have been introduced. As the agricultural landscape sees a higher percentage of corn acres using the PIP technology, the risk of the targeted insect pest populations developing resistance to the toxins, thereby rendering the in will increase as well. This result would negate the effectiveness of the PIP corn traits and could reduce production of a US field corn crop valued at $33 billion dollars in 2006 and place US food and now energy security at risk. Concerns over insect pest resistance development to PIP traits have led the USEPA to team with NASA and the Institute for Technology Development (ITD) to develop geo-spatial technologies designed to proactively monitor the corn production landscape for insect pest infestation and possible resistance development. USEPA resistance management simulation models are combined with NASA remote sensi ng products to monitor the corn landscape for resistance development. The two agencies have entered into an agreement which could potentially lead to the development of next generation NASA sensors that will more specifically address the requirements of the USEPA's resistance development strategy and offer opportunities to study the ever changing ecosystem complexities. The USEPA/NASA/ITD team has developed a broad research project entitled CERES (Crop Evaluation Research for Environmental Strategies). CERES is a research effort leading to decision support system tools that are designed to integrate multi-resolution NASA remote sensing data products and USEPA geo -spatial models to monitor the potential for insect pest resistance development from the regional to the landscape and then to the field level.

Casas, Joseph C.↗
NASA NTRSDate not supplied

The Examination of Individual Factors and AFTE Training Outcomes

Introduction: Motion sickness is common among military aviators. It describes a specific group of symptoms that include epigastric awareness, nausea, pallor, sweating, salivation, and fatigue. Occurrences of these symptoms can pose a significant risk to safety and adversely impact mission success. Accordingly, researchers have developed specific interventions to act as countermeasures. For example, Autogenic Feedback Training Exercise has been empirically validated as a training method that mitigates the impact of motion sickness. However, it remains unclear the extent to which individual factors moderate (or mediate) the effects of this intervention. The examination of individual factors such as interoceptive accuracy (IA) and specific personality traits might provide insight into whom may benefit most from AFTE. Methods: Participants were administered the Big Five Inventory (BFI) and State Trait Anxiety Inventory (STAI). In addition, they were given an interoceptive accuracy task (i.e., heartbeat counting task). The participants’ reported value was then compared to the actual number of heart beats obtained via ECG. Completion of the IA task was followed by pre- AFTE and Post-AFTE rotating chair tests to evaluate motion sickness and the effects of AFTE training. Results: Participants (n=16) were evaluated on IA, personality factors (i.e., BFI & STAI) and performance on the rotating chair. IA was unrelated to personality traits (p > .05), but inversely related to state anxiety post training (p < .05). Finally, IA did not predict performance (i.e., rotations or minutes tolerated ?) on rotating chair F (1, 14) = 1.18, p> .05). Discussion:(1) IA is unrelated to personality traits as measured by BFI and STAI. (2) Individual factors are unrelated to AFTE training outcome. (3) AFTE training can be beneficial for all.

motion sickness↗
NASA NTRS1983

What changes and what endures - The capabilities and limitations of training and selection

The contributions of psychology to aviation in the areas of selection, training, and evaluation, and the implementation of new technologies are discussed. The concept of personality traits versus modification of human behavior through principles of learning are analyzed. Particular consideration is given to achievement motivation (defined in terms of mastery, work, and competitiveness) and the differences between traits and attitudes. It is argued that personality traits are important dimensions of the self and are useful measures of individual differences. The selection of individuals with desired personality characteristics and the training of personnel to improve crew coordination, flight-deck management, and interpersonal efficacy are examined.

Helmreich, Robert L.↗
NASA NTRS2000

Predictors of Behavior and Performance in Extreme Environments: The Antarctic Space Analogue Program

To determine which, if any, characteristics should be incorporated into a select-in approach to screening personnel for long-duration spaceflight, we examined the influence of crewmember social/ demographic characteristics, personality traits, interpersonal needs, and characteristics of station physical environments on performance measures in 657 American men who spent an austral winter in Antarctica between 1963 and 1974. During screening, subjects completed a Personal History Questionnaire which obtained information on social and demographic characteristics, the Deep Freeze Opinion Survey which assessed 5 different personality traits, and the Fundamental Interpersonal Relations Orientation-Behavior (FIRO-B) Scale which measured 6 dimensions of interpersonal needs. Station environment included measures of crew size and severity of physical environment. Performance was assessed on the basis of combined peer-supervisor evaluations of overall performance, peer nominations of fellow crewmembers who made ideal winter-over candidates, and self-reported depressive symptoms. Social/demographic characteristics, personality traits, interpersonal needs, and characteristics of station environments collectively accounted for 9-17% of the variance in performance measures. The following characteristics were significant independent predictors of more than one performance measure: military service, low levels of neuroticism, extraversion and conscientiousness, and a low desire for affection from others. These results represent an important first step in the development of select-in criteria for personnel on long-duration missions in space and other extreme environments. These criteria must take into consideration the characteristics of the environment and the limitations they place on meeting needs for interpersonal relations and task performance, as well as the characteristics of the individuals and groups who live and work in these environments.

Palinkas, Lawrence A.↗
NASA NTRS2003

Quantitative analysis of bristle number in Drosophila mutants identifies genes involved in neural development

BACKGROUND: The identification of the function of all genes that contribute to specific biological processes and complex traits is one of the major challenges in the postgenomic era. One approach is to employ forward genetic screens in genetically tractable model organisms. In Drosophila melanogaster, P element-mediated insertional mutagenesis is a versatile tool for the dissection of molecular pathways, and there is an ongoing effort to tag every gene with a P element insertion. However, the vast majority of P element insertion lines are viable and fertile as homozygotes and do not exhibit obvious phenotypic defects, perhaps because of the tendency for P elements to insert 5' of transcription units. Quantitative genetic analysis of subtle effects of P element mutations that have been induced in an isogenic background may be a highly efficient method for functional genome annotation. RESULTS: Here, we have tested the efficacy of this strategy by assessing the extent to which screening for quantitative effects of P elements on sensory bristle number can identify genes affecting neural development. We find that such quantitative screens uncover an unusually large number of genes that are known to function in neural development, as well as genes with yet uncharacterized effects on neural development, and novel loci. CONCLUSIONS: Our findings establish the use of quantitative trait analysis for functional genome annotation through forward genetics. Similar analyses of quantitative effects of P element insertions will facilitate our understanding of the genes affecting many other complex traits in Drosophila.

Non-NASA Center↗
NASA NTRS2005

Team Performance and Error Management in Chinese and American Simulated Flight Crews: The Role of Cultural and Individual Differences

This report describes results of a study conducted for NASA-Langley Research Center. This study is part of a program of research conducted for NASA-LARC that has focused on identifying the influence of national culture on the performance of flight crews. We first reviewed the literature devoted to models of teamwork and team performance, crew resource management, error management, and cross-cultural psychology. Davis (1999) reported the results of this review and presented a model that depicted how national culture could influence teamwork and performance in flight crews. The second study in this research program examined accident investigations of foreign airlines in the United States conducted by the National Transportation Safety Board (NTSB). The ability of cross-cultural values to explain national differences in flight outcomes was examined. Cultural values were found to covary in a predicted way with national differences, but the absence of necessary data in the NTSB reports and limitations in the research method that was used prevented a clear understanding of the causal impact of cultural values. Moreover, individual differences such as personality traits were not examined in this study. Davis and Kuang (2001) report results of this second study. The research summarized in the current report extends this previous research by directly assessing cultural and individual differences among students from the United States and China who were trained to fly in a flight simulator using desktop computer workstations. The research design used in this study allowed delineation of the impact of national origin, cultural values, personality traits, cognitive style, shared mental model, and task workload on teamwork, error management and flight outcomes. We briefly review the literature that documents the importance of teamwork and error management and its impact on flight crew performance. We next examine teamwork and crew resource management training designed to improve teamwork. This is followed by discussion of the potential influence of national culture on teamwork and crew resource management. We then examine the influence of other individual and team differences, such as personality traits, cognitive style, shared mental model, and task workload. We provide a heuristic model that depicts the influence of national culture and individual differences on teamwork, error management and flight outcomes. The results demonstrate the usefulness of the model for future research.

Davis, Donald D.↗
NASA NTRS2010

Particle Swarm Optimization Toolbox

The Particle Swarm Optimization Toolbox is a library of evolutionary optimization tools developed in the MATLAB environment. The algorithms contained in the library include a genetic algorithm (GA), a single-objective particle swarm optimizer (SOPSO), and a multi-objective particle swarm optimizer (MOPSO). Development focused on both the SOPSO and MOPSO. A GA was included mainly for comparison purposes, and the particle swarm optimizers appeared to perform better for a wide variety of optimization problems. All algorithms are capable of performing unconstrained and constrained optimization. The particle swarm optimizers are capable of performing single and multi-objective optimization. The SOPSO and MOPSO algorithms are based on swarming theory and bird-flocking patterns to search the trade space for the optimal solution or optimal trade in competing objectives. The MOPSO generates Pareto fronts for objectives that are in competition. A GA, based on Darwin evolutionary theory, is also included in the library. The GA consists of individuals that form a population in the design space. The population mates to form offspring at new locations in the design space. These offspring contain traits from both of the parents. The algorithm is based on this combination of traits from parents to hopefully provide an improved solution than either of the original parents. As the algorithm progresses, individuals that hold these optimal traits will emerge as the optimal solutions. Due to the generic design of all optimization algorithms, each algorithm interfaces with a user-supplied objective function. This function serves as a "black-box" to the optimizers in which the only purpose of this function is to evaluate solutions provided by the optimizers. Hence, the user-supplied function can be numerical simulations, analytical functions, etc., since the specific detail of this function is of no concern to the optimizer. These algorithms were originally developed to support entry trajectory and guidance design for the Mars Science Laboratory mission but may be applied to any optimization problem.

Grant, Michael J.↗
NASA NTRSDate not supplied

A Process Model of Interpersonal Relationship Formation in Isolated and Confined Environments

Future space crews will face several challenges such as living and working in a confined environment, isolated from others. These circumstances increase the importance of interpersonal compatibility, teamwork, and team performance. The interpersonal compatibility of space crews has been and continues to be of interest to both NASA and the Institute of Biomedical Problems (IBMP), whose research informs operations for Roscosmos. In NASA-sponsored research, interpersonal compatibility has been examined in terms of how the combination of team members’ personality traits, values, and demographics shape team member relationships and team performance overtime. IBMP-sponsored research mostly has moved away from trait-based approaches toward an idiographic (in-depth, heavily descriptive) approach to researching crew interpersonal relations. This research uses software such as Personal Self-Perception and Attitudes (PSPA), network approaches to team member relations, and content analysis of interactions to assess interpersonal compatibility, and infer states and team dynamics. Our research program integrated these ideas. Our primary research aim was to develop and empirically test a process model of interpersonal relationship formation in isolated and confinement environments. We created a model, collected data from teams in an isolated and confined environment, and applied a novel analytical strategy that combines trait, state, and interaction data (i.e., relational events). We focused specifically on the formation of strained relationships in isolation and confinement—or with whom fellow crewmembers find it difficult to work.

S T Bell↗