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NASA NTRS2023

Approaching a Thermal Tipping Point in the Eurasian Boreal Forest at its Southern Margin

Climate change is increasing the intensity and frequency of extreme heat events. Ecological responses to extreme heat will depend on vegetation physiology and thermal tolerance. Here we report that Larix sibirica, a foundation species across boreal Eurasia, is vulnerable to extreme heat at its southern range margin due to its low thermal tolerance (T crit of photosynthesis: ~ 37–48 °C). Projections from CMIP6 Earth System Models (ESMs) suggest that leaf temperatures might exceed the 25 th percentile of Larix sibirica’s T crit by two to three days per year within the next two to three decades (by 2050) under high emission scenarios (SSP3-7.0 and SSP5-8.5). This degree of warming will threaten the biome’s continued ability to assimilate and sequester carbon. This work highlights that under high emission trajectories we may approach an abrupt ecological tipping point in southern boreal Eurasian forests substantially sooner than ESM estimates that do not consider plant thermal tolerance traits.

Boreal ecology↗

NASA NTRSDate not supplied

Sequential Filtering in the Presence of Uniform Measurement Errors

This paper presents a sequential filtering strategy using observations corrupted with uniform measurement noise. While the Kalman filter remains the best linear estimator of the state, other filtering techniques provide minimum variance optimal estimates, a trait only enjoyed by the Kalman filter when the underlying noises are, in fact, Gaussian. This work develops a new approximate optimal estimator for uniform measurement noises. The resulting recursion requires just slightly more computational time to complete a measurement update than the Kalman filter, which generally cannot be claimed by other optimal strategies such as the particle or Gaussian mixture filters.

James S McCabe↗

NASA NTRSDate not supplied

Cardiovascular Responses to Simulated Spaceflight: Molecular Signatures and Surrogate Outputs to Measure CVD Risk

During extended space missions beyond low Earth orbit, astronauts will encounter prolonged periods of weightlessness and low dose space radiation. Previous studies have shown that exposure to small doses of high LET radiation (< 50 cGy) can lead to both short-term and long-term alterations in heart function, structure and underlying molecular mechanisms. In this study, we aim to identify the molecular signature associated with the cardiovascular response to simulated galactic cosmic radiation (5-ion GCR) alone or in combination with simulated weightlessness at time intervals relevant to mission length and recovery. Additionally, we aim to determine whether sex impacts cardiovascular responses to these spaceflight factors. Our overarching goal is to enhance our understanding of the cardiovascular risks associated with extended space missions and the clinical endpoints they suggest. We hypothesize that exposure to simulated space radiation leads to enduring alterations in the transcriptome, redox signaling and cytokine environment of cardiovascular tissue, some which have known links with reduced cardiovascular performance, aging, and increased risk of cardiovascular disease (CVD). Furthermore, we posit that simulated space radiation exposure in combination with simulated microgravity exacerbates cardiovascular deficits compared to single factor exposure. Female and male C57BL/6J mice, aged 23-24 weeks, were exposed to a single dose of 5, 15, or 50 cGy of 5-ion GCR, or sham-treated (0 cGy). Euthanasia was performed at 14 days and ~4 months post-irradiation. Hearts, aorta and blood plasma were collected shortly thereafter. RNA-sequencing of left ventricles at ~4 months post-GCR exposure revealed sex differences in the heart transcriptome with a few genes showing radiation-dependent changes in expression levels. Notably, some of the differentially expressed genes in 15 and 50 cGy GCR groups are known to play roles in the development of CVD. Analysis of protein levels of a subset of inflammatory cytokines in the heart indicated sex differences but no differences between sham and 50 cGy groups. Results also showed correlations among differentially expressed genes and a subset of inflammatory cytokines, with some correlations altered by GCR exposure. These findings suggest that GCR exposure can modify protein and gene networks linked to inflammation and CVD progression. In the aorta, telomere lengths were comparable across treatment groups sexes. Mitochondrial copy number is a biomarker for mitochondrial function with decreased copy numbers associated with cardiometabolic disease traits. Mitochondrial copy numbers of aorta also showed no sex nor dose differences. In a second study, mice underwent one week of simulated microgravity by hindlimb unloading (HU) and then exposed to a single dose of 15 cGy of 5-ion GCR. HU was conducted for an additional two weeks following GCR exposure. Single factor exposure groups (HU or GCR only) also were included in the study. Euthanasia was then performed and the same tissues were collected. Protein levels of select inflammatory cytokines in the heart showed sex-dependent differences in expression. In the aorta, telomere lengths and mitochondrial copy number also showed sex differences. In summary, our results indicate differences between sexes in biomarkers related to cardiovascular health. Exposure to 5-ion GCR or HU, alone or in combination, did not result in changes in most of the cardiovascular biomarkers that were examined. However, in the heart, simulated space radiation at doses of 15 and 50 cGy led to long-term alterations in the expression levels of a small group of genes known to be associated with the progression of CVD. The long-term transcriptomic changes resulting from exposure to simulated space radiation should be carefully investigated to mitigate adverse cardiovascular events during and after deep space missions. Our results also highlight the importance of sex-specific strategies in monitoring and maintaining cardiovascular health during and after deep space missions.

cardiovascular↗

NASA NTRSDate not supplied

Preliminary Characterization of Spinel Troctolite Clast Identified in Apollo Next Generation Sample Analysis (ANGSA) Core 73002

The lunar magnesian (Mg-) suite is a diverse lithological group composed of Mg-rich mafic minerals. The Mg-suite consists primarily of troctolites, norites, gabbronorites, and spinel troctolites. These rocks exhibit contradictory geochemical traits, with mafic minerals bearing high Mg# (molar 100×Mg/[Mg+Fe]) indicating primitive parental magmas, but also plagioclase saturation and enrichments in incompatible trace elements (i.e., KREEP) indicate more evolved parental magmas. A variety of models have been invoked to explain the occurrence and petrogenesis of the Mg-suite. Here, we report on a new spinel troctolite clast found in Apollo Next Generation Sample Analysis (ANGSA) program core 73002. Sample 73002 was acquired at Station 3 during Apollo 17 as the upper part of a double-drive tube with sample 73001. During processing, the spinel troctolite clast (0.066 g) was found at the 4.0–4.5 cm depth interval.

A. C. Stadermann↗

NASA NTRS2024

Synthetic Biology to Support Human Exploration of Deep Space

The International Space Station (ISS) has enabled a continuous human presence in space since November 2000. The ISS is in low Earth orbit, facilitating regular resupply missions to deliver air, water, food, spare parts, and science experiments. NASA’s Moon to Mars campaign seeks to return humans to the Moon and prepare for crewed missions to Mars. Increased distance from Earth poses logistical challenges to provide all resources needed by humans for deep space missions. NASA Ames Research Center is conducting a series of synthetic biology projects to test the use of microbes for on-demand biosynthesis of human micronutrients. The BioNutrients spaceflight experiments test an implementation concept to produce fermented food products in which microbe growth enhances micronutrient content. On-demand production of carotenoids was engineered into two yeast (Saccharomyces cerevisiae) strains that have been tested in nearly 5 years of storage. One of the BioNutrients strains will be incorporated into the Lunar Explorer Instrument for Space Biology Applications (LEIA) project. LEIA is developing an instrument suite to be delivered to the lunar south pole region by the Commercial Lunar Payload Services (CLPS) program. The LEIA instrument suite will be used to measure multiple yeast strains for growth, metabolic activity, and synthetic biology-enabled production of carotenoids, while taking real time measurements of biologically relevant radiation exposure on the lunar surface. LEIA data will be used to assess the impact of lunar surface radiation and reduced gravity on the production of engineered traits.

Synthetic Biology↗

NASA NTRS2024

New insight into the global record of the Ediacaran tubular morphotype: a common solution to early multicellularity

The tubular morphogroup is a common component of Earth’s first complex, multicellular communities—the Ediacaran biota—and offers valuable insight into biological traits that are fundamental to animal life because they have intriguing links to metazoan phyla and are highly abundant in Ediacaran ecosystems. Biomineral tubes (e.g. Cloudina) are well described from the Nama assemblage (~550–538 Myr), yielding a relatively detailed understanding of this subset of the morphogroup. Conversely, the non-biomineral tubular taxa of the Nama assemblage, as well as of the older White Sea assemblage (~560–550 Myr), are poorly understood. As a result, the variability of characters that define non-biomineral tubular organisms is unknown and their diversity dynamics throughout the terminal Ediacaran are unconstrained. To test hypotheses related to the diversity, morphological variability and temporal distribution of non-biomineral tubes, a comprehensive database of non-biomineral Ediacaran tubular taxa was compiled. Results demonstrate previously unrecognized morphological disparity in the non-biomineral tubular morphogroup and reveal that it comprises a higher number of genera than all other non-tubular morphogroups in the White Sea and the Nama. Thus, it illustrates that a tubular form dominated Ediacaran ecosystems for considerably longer than previously appreciated and, importantly, was the most common solution to early multicellularity.

Rachel L. Surprenant↗

NASA NTRS2024

Transfer of NASA Technology to the DoD: Mitigating Motion Sickness with Autogenic Feedback Training Exercise

Motion sickness poses a significant safety risk, particularly in the context of aviation. Given its prevalence among aviators and its detrimental impact on performance, researchers have attempted to identify effective mitigation strategies for motion sickness. Currently, many of the existing interventions are pharmacological, and while effective, they present a problem due to their associated adverse side effects. The primary goals of the current research were 1) demonstrate the value of the application of Autogenic-Feedback Training Exercise (AFTE), a physiological training program developed by NASA to mitigate the impact of operational stressors such as motion sickness and spatial disorientation on human physiology and performance and 2) evaluate a new enhanced version of AFTE training software and demonstrate the ability to apply it remotely and train other personnel to administer it. AFTE combines principles of autogenic therapy, and biofeedback in training individuals to control their physiological reactions through a series of relaxation and arousal exercises. This study included twenty-six participants, 17 men and 9 women. On day 1 participants were tested in a rotating chair (pre-test) to determine their motion sickness tolerance (measured as minutes of rotation); days 2-5 consisted of four AFTE training sessions, each 30-min. in duration for a total of 2 hours; and on day 6 the participants were re-tested in the rotating chair. Results revealed a significant increase in motion sickness tolerance with AFTE on the post-test when compared to pre-test, participants had significantly lower symptom diagnostic scores post-test, and there was no significant gender effect. In addressing the first goal it was concluded that the modified 2-hour version of AFTE significantly improved motion sickness tolerance with participants experiencing fewer symptoms. A second goal of this research was to refine and transfer a NASA technology, software and methods for applications within DOD by training other personnel to administer AFTE. A comparison of NASA and NAMRU-D trainers on AFTE outcome for improving participants’ motion sickness tolerance revealed no significant difference indicating the successful transfer of methods to DOD. In addition, remote AFTE training of military aviators at distant sites was feasible. A third goal was to identify individual patterns of interoceptive abilities and related autonomic metrics able to predict stress response and training outcome. These data included measures of personality traits obtained from questionnaires and specific autonomic measures (e.g., heart rate variability) collected by NAMRU-D investigators. These results will be reported in a separate paper.

autonomic nervous system↗

NASA NTRSDate not supplied

State of Wildfires

Fire is an essential component of ecosystems and acts as key driver of biogeochemical cycling with impacts on vegetation structure and composition, soil conditions, and climate feedbacks. Fire behavior and effects vary based on the types of fuel, fuel dryness, and frequency of ignition. Due to changing climate and land use patterns, fire danger is increasing in many regions globally, and fires are having increasingly devastating impacts on human health, infrastructure, and ecosystem services. Recurrent fires help to determine the distribution of trees and grasses, and overall fuel load, which inform the behavior of future fires. Process-based models can be used to capture multi-scale impacts at the forest stand-level up to the landscape level, and across minutes to centuries, but must capture variation in fire behavior and intensity as a function of the fuel and climate, from high intensity forest crown fires within boreal regions to low intensity rapid grass fires of the tropics. Fire model development demonstrates our ability to capture large scale fire influenced biogeography and vegetation distribution at the earth system scale through vegetation traits and fire feedbacks. At the individual stand scale the importance of interactions and feedbacks between above and below ground process is essential to capturing the vegetation dynamics across boreal forest systems. Improving the mechanics of including plant physiology and specifically live fuel moisture content is the next step to advancing the capability of process based models to inform fire research. Advances in the testing and creation of a mechanistic live fuel moisture model demonstrate the foundation for future live fuel dynamics research that can be informed by field and remote sensing information. Improved remote sensing, technological and modeling capabilities support a more comprehensive and cohesive fire response that will be better equipped to overcome current barriers and anticipate the new reality of fires in a warming world.

wildfires↗

NASA NTRSDate not supplied

A Heritage BioSensor for Lunar Biology Experiments

Introduction: Automated biological experiments on small spacecraft missions have gained prominence over the past decade due to their simplicity, accessibility, and small mass, volume, and power needs. Most recently, the BioSensor microfluidic CubeSat payload aboard BioSentinel used an automated microfluidic cell culture system to study the effects of environmental stressors like deep space radiation and microgravity on yeast growth and metabolism. BioSentinel’s successor, the Lunar Explorer Instrument for space biology Applications (LEIA), will study the effects of lunar gravity and radiation using an improved version of the BioSensor microfluidic platform. The BioSensor payload has great adaptability to host a diverse range of biological experiments with single- and multi-celled organisms in both crewed and uncrewed missions, making it a compelling candidate for future space biology studies in a lunar surface environment. BioSensor Instrumentation on BioSentinel: The first spaceflight mission with the BioSensor, BioSentinel’s biology experiments occurred at three locations -- deep space, ISS and ground. The payload contained 18 microfluidic cards, each featuring 16 growth wells (a total of 288 growth wells). Each well was loaded before launch with desiccated yeast. In space, liquid culture medium (nutrients) was automatically introduced to batches of wells at a time to initiate a series of biology experiments. Temperature was maintained by thin film heaters on both sides of each card. Each well was equipped with three LEDs emitting at 570 nm, 630 nm, and 850 nm, paired with photodetectors to measure cell concentration and the alamarBlue (metabolic indicator dye) color transition from blue to pink. Phenotypic parameters like cell viability, metabolic rate, and generation time can be derived from these measurements. The sequence and timing of fluid fills, optical measurements, and thermal control were stored onboard, but could be updated asynchronously via ground communication. LEIA: LEIA is slated for launch no earlier than 2026 on a CLPS lander. BioSentinel’s BioSensor has been modified for use in LEIA. These improvements include: (a) storage for multiple culture medium types, (b) additional LED color (465 nm) for a new biological assay for antioxidant (carotenoid) production, (c) housing modifications for later biology load before launch, (d) improved isolation between electronic and fluidic components, and (e) improved humidity control for prolonged organism viability in case of post-load launch delay. Future Prospects: The consistent and successful demonstration of complex fluidics platforms alongside reliable instrument operations in a space environment is poised to create strong momentum for BioSensor-based biological experiment payloads. Planned future developments with the BioSensor include extending compatibility to a broader range of organisms and assays. Preliminary work has already demonstrated successful growth of Arabidopsis seedlings in fluidic cards. With a few modifications to the optical assembly, the setup could easily measure photosynthetic traits in plants and cyanobacteria. The addition of fluorescence measurements and generation of novel luminescent assays will elevate BioSensor’s functionality further. Beyond the BioSensor’s potential uses on free-flyer missions, ISS and Gateway, and CLPS landers, deploying the BioSensor to the lunar surface or in an artificial habitat on crewed missions could enable pioneering research on both how life responds to lunar conditions and future bioproduction capabilities making the BioSensor an indispensable tool for future space biology research.

Chinmayee Govinda Raj↗

NASA NTRSDate not supplied

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗

NASA NTRSDate not supplied

Performance Evaluation of a Cartesian Move Algorithm for the LSMS Family of Cable-Driven Cranes

The Lightweight Surface Manipulation System, or LSMS, is a family of cable-actuated cranes, designed for surface operations on the Moon and Mars. Its structural design focuses on three fundamental traits for space environments: a high payload-to-mass ratio to reduce launch costs, compactness for space travel in reduced cargo bays, and self-erecting capabilities for operations before astronauts arrive. The resulting design confers nonlinear and switched dynamics to the LSMS, making these cranes an interesting challenge for autonomous and teleoperated applications. One of the protocols required for these applications is a Cartesian move algorithm. This algorithm is responsible for placing the end effector of the crane at a desired location, specified in Cartesian coordinates. This paper evaluates the performance of a Cartesian move algorithm developed for the LSMS at the NASA Langley Research Center. To this end, several payload manipulation tasks were performed with LSMS-L35, the smallest version within the LSMS family. The evaluated algorithm can place the end effector with accuracy, as shown in the hardware and simulation tests.

cable-actuated↗

NASA NTRS2024

Discounting Water for Optimal Carbon Gain as a Basis of Stomatal Closure

The exchange of carbon dioxide and water vapor between terrestrial ecosystems and the atmosphere is regulated by stomata (small pores in the leaves of plants). Unsurprisingly, environmental factors controlling the opening and closure of stomata has been sought as early as 1800. One approach, popularized in the early 1970s, is a stomatal optimization framework. This framework is based on the hypothesis that plants optimize carbon gain subject to water loss or water availability constraints. This constraint optimization problem was solved in various forms assuming instantaneous adjustments of stomatal aperture to maximize a reward function with no future foresight or legacy effects. Holtzman et al. (2024, https://doi.org/10.1029/2023av001113) offers a novel approach that can diagnose the effective timescale over which the reward function maximization must be time-integrated. The developed method thus optimizes an integrated carbon gain function but adjusted by a discount factor subject to water availability in the root zone. The discount factor considers how the plant values carbon gain to save water and its timescale can be inferred from observations because the model is analytically tractable. The results suggest that the most important climate factor that determines this discount timescale is multi-annual mean of the longest dry period during the growing season. The findings highlight how local climate traits influence the spatial variation in ecosystem-level water use strategies. This sets the stage for expanding such a framework to cases where multiple constraints act in concert while operating at distinct time scales.

stomata↗

NASA NTRS2007

NASA Laser Remote Sensing Technology Needs for Earth Science in the Next Decade and Beyond

In late 2005 the NASA Earth Science Technology Office convened a working group to review decadal-term technology needs for Earth science active optical remote sensing objectives. The outcome from this effort is intended to guide future NASA investments in laser remote sensing technologies. This paper summarizes the working group findings and places them in context with the conclusions of the National Research Council assessment of Earth science needs, completed in 2007.

Trait, David M.↗

NASA NTRS2021

Tracking the Rates and Mechanisms of Canopy Damage and Recovery Following Hurricane Maria Using Multitemporal Lidar Data

Hurricane Maria, a Category 4 storm, snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne Lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100–800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥ 1 m in canopy height (mean = −7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13.5% of the study area had canopy heights ≤ 2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss > 1 m (2017–2018) followed by rapid height gain > 1 m (2018–2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no height changes larger than ± 1 m in either period. Canopy layers < 10 m tall accounted for most increases in canopy height and fractional cover between 2018 and 2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage and highlight the diversity of ecosystem impacts from heterogeneous spatial patterns and vertical stratification of forest regrowth following a major disturbance event.

forest structure↗

NASA NTRS2021

Tracking the Rates and Mechanisms of Canopy Damage and Recovery Following Hurricane Maria Using Multitemporal Lidar Data

forest structure↗

NASA NTRS2022

Modeling Demographic-Driven Vegetation Dynamics and Ecosystem Biogeochemical Cycling in NASA GISS’s Earth System Model (ModelE-BiomeE v.1.0)

We developed a demographic vegetation model, BiomeE, to improve the modeling of vegetation dynamics and ecosystem biogeochemical cycles in the NASA Goddard Institute of Space Studies' ModelE Earth system model. This model includes the processes of plant growth, mortality, reproduction, vegetation structural dynamics, and soil carbon and nitrogen storage and transformations. The model combines the plant physiological processes of ModelE's original vegetation model, Ent, with the plant demographic and ecosystem nitrogen processes that have been represented in the Geophysical Fluid Dynamics Laboratory's LM3-PPA. We used nine plant functional types to represent global natural vegetation functional diversity, including trees, shrubs, and grasses, and a new phenology model to simulate vegetation seasonal changes with temperature and precipitation fluctuations. Competition for light and soil resources is individual based, which makes the modeling of transient compositional dynamics and vegetation succession possible. Overall, the BiomeE model simulates, with fidelity comparable to other models, the dynamics of vegetation and soil biogeochemistry, including leaf area index, vegetation structure (e.g., height, tree density, size distribution, and crown organization), and ecosystem carbon and nitrogen storage and fluxes. This model allows ModelE to simulate transient and long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems. Furthermore, BiomeE also allows for the eco-evolutionary modeling of community assemblage in response to past and future climate changes with its individual-based competition and demographic processes.

Biogeochemical cycles↗