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At least 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Climate change in tundra regions may alter vegetation species composition and ecosystem carbon balance. Remote sensing provides critical tools for monitoring these changes as optical signals provide a way to scale from plot measurements to regional patterns. Gas exchange measurements of pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK, show three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012 0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Further, discriminant analysis of patch reflectance identifies five spectral bands that can separate each vegetation functional type as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. Patch-level statistical discriminant functions applied to in situ hyperspectral reflectance successfully unmixed cover fractions of the vegetation functional types. These functions, developed from the tram data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine regional variability in distribution of the vegetation functional types and from those distributions, the variability of LUE. Across the landscape, there was a fivefold variation in tundra LUE that was correlated to a spectral vegetation index developed to detect vegetation chlorophyll content.

Huemmrich, Karl F.↗
NASA NTRS2013

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013+/-0.001, 0.0018+/-0.0002, and 0.0012+/-0.0001 mol C/mol absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals.

Huemmrich, Karl F.↗
NASA NTRS2014

Physiological Observations and Omics to Develop Personalized Sensormotor Adaptability Countermeasures Using Bed Rest and Space Flight Data

Astronauts experience sensorimotor disturbances during the initial exposure to microgravity and during the re-adapation phase following a return to an earth-gravitational environment. These alterations may disrupt the ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from space flight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual space flight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures that include: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; 3) genotype markers for genetic polymorphisms in Catechol-O-Methyl Transferase, Dopamine Receptor D2, Brain-derived neurotrophic factor and genetic polymorphism of alpha2-adrenergic receptor that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration space flight and an analog bed rest environment. We will be conducting a retrospective study leveraging data already collected from relevant ongoing/completed bed rest and space flight studies. These data will be combined with predictor metrics that will be collected prospectively - behavioral, brain imaging and genomic measures; from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions against decrements in post-mission adaptive capability. This ability will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗
NASA NTRS2013

Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties

Non-vascular plants (lichens and mosses) are significant components of tundra landscapes and may respond to climate change differently from vascular plants affecting ecosystem carbon balance. Remote sensing provides critical tools for monitoring plant cover types, as optical signals provide a way to scale from plot measurements to regional estimates of biophysical properties, for which spatial-temporal patterns may be analyzed. Gas exchange measurements were collected for pure patches of key vegetation functional types (lichens, mosses, and vascular plants) in sedge tundra at Barrow, AK. These functional types were found to have three significantly different values of light use efficiency (LUE) with values of 0.013 plus or minus 0.0002, 0.0018 plus or minus 0.0002, and 0.0012 plus or minus 0.0001 mol C mol (exp -1) absorbed quanta for vascular plants, mosses and lichens, respectively. Discriminant analysis of the spectra reflectance of these patches identified five spectral bands that separated each of these vegetation functional types as well as nongreen material (bare soil, standing water, and dead leaves). These results were tested along a 100 m transect where midsummer spectral reflectance and vegetation coverage were measured at one meter intervals. Along the transect, area-averaged canopy LUE estimated from coverage fractions of the three functional types varied widely, even over short distances. The patch-level statistical discriminant functions applied to in situ hyperspectral reflectance data collected along the transect successfully unmixed cover fractions of the vegetation functional types. The unmixing functions, developed from the transect data, were applied to 30 m spatial resolution Earth Observing-1 Hyperion imaging spectrometer data to examine variability in distribution of the vegetation functional types for an area near Barrow, AK. Spatial variability of LUE was derived from the observed functional type distributions. Across this landscape, a fivefold variation in tundra LUE was observed. LUE calculated from the functional type cover fractions was also correlated to a spectral vegetation index developed to detect vegetation chlorophyll content. The concurrence of these alternate methods suggest that hyperspectral remote sensing can distinguish functionally distinct vegetation types and can be used to develop regional estimates of photosynthetic LUE in tundra landscapes.

VEGETATION↗
NASA NTRS2015

Development of Bone Remodeling Model for Spaceflight Bone Physiology Analysis

Current spaceflight exercise countermeasures do not eliminate bone loss. Astronauts lose bone mass at a rate of 1-2% a month (Lang et al. 2004, Buckey 2006, LeBlanc et al. 2007). This may lead to early onset osteoporosis and place the astronauts at greater risk of fracture later in their lives. NASA seeks to improve understanding of the mechanisms of bone remodeling and demineralization in 1g in order to appropriately quantify long term risks to astronauts and improve countermeasures. NASA's Digital Astronaut Project (DAP) is working with NASA's bone discipline to develop a validated computational model to augment research efforts aimed at achieving this goal.

Microgravity↗
NASA NTRS2015

Weaving Together Space Biology and the Human Research Program: Selecting Crops and Manipulating Plant Physiology to Produce High Quality Food for ISS Astronauts

Researchers from the Human Research Program (HRP) have teamed up with plant biologists at KSC to explore the potential for plant growth and food production on the international space station (ISS) and future exploration missions. KSC Space Biology (SB) brings a history of plant and plant-microbial interaction research for station and for future bioregenerative life support systems. JSC HRP brings expertise in Advanced Food Technology (AFT), Advanced Environmental Health (AEH), and Behavioral Health and Performance (BHP). The Veggie plant growth hardware on the ISS is the platform that first drove these interactions. As we prepared for the VEG-01 validation test of Veggie, we engaged with BHP to explore questions that could be asked of the crew that would contribute both to plant and to behavioral health research. AFT, AEH and BHP stakeholders were engaged immediately after the return of the Veggie flight samples of space-grown lettuce, and this team worked with the JSC human medical offices to gain approvals for crew consumption of the lettuce on ISS. As we progressed with Veggie testing we began performing crop selection studies for Veggie that were initiated through AFT. These studies consisted of testing and down selecting leafy greens, dwarf tomatoes, and dwarf pepper crops based on characteristics of plant growth and nutritional levels evaluated at KSC, and organoleptic quality evaluated at JSCs Sensory Analysis lab. This work has led to a successful collaborative proposal to the International Life Sciences Research Announcement for a jointly funded HRP-SB investigation of the impacts of light quality and fertilizer on salad crop productivity, nutrition, and flavor in Veggie on the ISS. With this work, and potentially with other pending joint projects, we will continue the synergistic research that will advance the space biology knowledge base, help close gaps in the human research roadmap, and enable humans to venture out to Mars and beyond.

International Space Station↗
NASA NTRS2018

Overview and Evaluation of a Computational Bone Physiology Modeling Toolchain and Its Application to Testing of Exercise Countermeasures

Prolonged microgravity exposure disrupts natural bone remodeling processes and can lead to a significant loss of bone strength, increasing injury risk during missions and placing astronauts at a greater risk of bone fracture later in life. Resistance-based exercise during missions is used to combat bone loss, but current exercise countermeasures do not completely mitigate the effects of microgravity. To address this concern, we present work to develop a personalizable, site-specific computational modeling toolchain of bone remodeling dynamics to understand and estimate changes in volumetric bone mineral density (BMD) in response to microgravity-induced bone unloading and in-flight exercise. The toolchain is evaluated against data collected from subjects in a 70-day bed rest study and is found to provide insight into the amount of exercise stimulus needed to minimize bone loss, quantitatively predicting post-study volumetric BMD of control subjects who did not perform exercise, and qualitatively predicting the effects of exercise. Results suggest that, with additional data, the toolchain could be improved to aid in developing customized in-flight exercise regimens and predict exercise effectiveness.

Schepelmann, Alexander↗
NASA NTRS2019

Overview and Evaluation of a Computational Bone Physiology Modeling Toolchain and Its Application to Testing of Exercise Countermeasures

Prolonged microgravity exposure disrupts natural bone remodeling processes and can lead to a significant loss of bone strength, increasing injury risk during missions and placing astronauts at a greater risk of bone fracture later in life. Resistance-based exercise during missions is used to combat bone loss, but current exercise countermeasures do not completely mitigate the effects of microgravity. To address this concern, we present work to develop a personalizable, site-specific computational modeling toolchain of bone remodeling dynamics to understand and estimate changes in volumetric bone mineral density (BMD) in response to microgravity-induced bone unloading and in-flight exercise. The toolchain is evaluated against data collected from subjects in a 70-day bedrest study and is found to provide insight into the amount of exercise stimulus needed to minimize bone loss, quantitatively predicting post-study volumetric BMD of control subjects who did not perform exercise, and qualitatively predicting the effects of exercise. Results suggest that, with additional data, the toolchain could be improved to aid in developing customized in-flight exercise regimens and predict exercise effectiveness.

Schepelmann, Alexander↗
NASA NTRS2020

Introduction to Sleep and Circadian Physiology

The purpose of this talk is to provide an undergraduate student audience with basic information about the sleep and circadian challenges that astronauts and pilots face. Dr. Flynn-Evans will begin by highlighting how NASA works. She will next cover basic information about sleep, circadian rhythms, and performance, including how sleep works on earth. She will explain how people have circadian rhythms of different lengths and how the circadian clock has to be re-set each day. She will also describe how jet-lag works as an example of what happens during circadian misalignment. Dr. Flynn-Evans will describe how modest circadian misalignment affects airline pilots during short-haul flights. She will also describe how sleep is different in space and will highlight the challenges that astronauts face in low-earth orbit. She will discuss how astronauts have a shorter sleep duration in space relative to on the ground and how their schedules can shift due to operational constraints. She will also describe how these issues affect alertness and performance. She will then discuss how sleep and scheduling may be different on a long-duration mission to Mars. She will discuss the differences in light and day length on earth and mars and illustrate how those differences pose significant challenges to sleep and circadian rhythms.

Flynn-Evans, Erin↗
NASA NTRS2020

Community Composition and Photosynthetic Physiology of Phytoplankton in the Western Subarctic Pacific Near the Kuril Islands With Special Reference to Iron Availability

The western subarctic Pacific (WSP) is known as one of the most productive regions among the world's oceans in spring. However, its oceanic waters are also known as a high‐nutrient, low‐chlorophyll region during summer due to low iron (Fe) availability in seawater. Indeed, recent studies have demonstrated that the distribution of Fe in the WSP is complex and heterogeneous. This study thus investigated the effects of Fe availability on the community composition and photophysiology of surface phytoplankton from coastal to offshore waters in the WSP in the summer of 2014. Although relatively high concentrations (>2 mg/m3) of chlorophyll (chl) a were found in the Sea of Okhotsk and some coastal waters, low chl a concentrations (<1 mg/m3) were commonly observed in offshore waters. Based on dissolved Fe and macronutrient concentrations, we deduced that low Fe availability limited phytoplankton growth in offshore waters, whereas low silicate and/or nitrate levels limited growth in the shelf areas. Scanning electron microscopy also revealed that the centric diatom Chaetoceros exclusively dominated the diatom assemblages in the shelf and coexisted with pennate diatoms in offshore waters, respectively. Primary productivity in surface waters was negatively correlated with the bottom of the euphotic layer or the light saturation index of the photosynthesis‐irradiance curve, which indicates that the phytoplankton assemblages were well acclimated to in situ light conditions regardless of the water masses.

Yoshida, Kazuhiro↗