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At least 91 records · Page 5

Strong Local Evaporative Cooling Over Land Due to Atmospheric Aerosols

Abstract Aerosols can enhance terrestrial productivity through increased absorption of solar radiation by the shaded portion of the plant canopy—the diffuse radiation fertilization effect. Although this process can, in principle, alter surface evaporation due to the coupling between plant water loss and carbon uptake, with the potential to change the surface temperature, aerosol‐climate interactions have been traditionally viewed in light of the radiative effects within the atmosphere. Here, we develop a modeling framework that combines global atmosphere and land model simulations with a conceptual diagnostic tool to investigate these interactions from a surface energy budget perspective. Aerosols increase the terrestrial evaporative fraction, or the portion of net incoming energy consumed by evaporation, by over 4% globally and as much as ∼40% regionally. The main mechanism for this is the increase in energy allocation from sensible to latent heat due to global dimming (reduction in global shortwave radiation) and slightly augmented by diffuse radiation fertilization. In regions with moderately dense vegetation (leaf area index >2), the local surface cooling response to aerosols is dominated by this evaporative pathway, not the reduction in incident radiation. Diffuse radiation fertilization alone has a stronger impact on gross primary productivity (+2.18 Pg C y −1 or +1.8%) than on land evaporation (+0.18 W m −2 or +0.48%) and surface temperature (−0.01 K). Our results suggest that it is important for land surface models to distinguish between quantity (change in total magnitude) and quality (change in diffuse fraction) of radiative forcing for properly simulating surface climate.

Chakraborty, TC↗

Improving Simulations of Vegetation Dynamics over the Tibetan Plateau: Role of Atmospheric Forcing Data and Spatial Resolution

The efficacy of vegetation dynamics simulations in offline land surface models (LSMs) largely depends on the quality and spatial resolution of meteorological forcing data. In this study, the Princeton Global Meteorological Forcing Data (PMFD) and the high spatial resolution and upscaled China Meteorological Forcing Data (CMFD) were used to drive the Simplified Simple Biosphere model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics (SSiB4/TRIFFID) and investigate how meteorological forcing datasets with different spatial resolutions affect simulations over the Tibetan Plateau (TP), a region with complex topography and sparse observations. By comparing the monthly Leaf Area Index (LAI) and Gross Primary Production (GPP) against observations, we found that SSiB4/TRIFFID driven by upscaled CMFD improved the performance in simulating the spatial distributions of LAI and GPP over the TP, reducing RMSEs by 24.3% and 20.5%, respectively. The multi-year averaged GPP decreased from 364.68 gC m –2 yr –1 to 241.21 gC m –2 yr –1 with the percentage bias dropping from 50.2% to –1.7%. When using the high spatial resolution CMFD, the RMSEs of the spatial distributions of LAI and GPP simulations were further reduced by 7.5% and 9.5%, respectively. This study highlights the importance of more realistic and high-resolution forcing data in simulating vegetation growth and carbon exchange between the atmosphere and biosphere over the TP.

54 ENVIRONMENTAL SCIENCES↗

A split ribozyme system for in vivo plant RNA imaging and genetic engineering

RNA plays a central role in plants, governing various cellular and physiological processes. Monitoring its dynamic abundance provides a discerning understanding of molecular mechanisms underlying plant responses to internal (developmental) and external (environmental) stimuli, paving the way for advances in plant biotechnology to engineer crops with improved resilience, quality and productivity. In general, traditional methods for analysis of RNA abundance in plants require destructive, labour-intensive and time-consuming assays. To overcome these limitations, we developed a transformative innovation for in vivo RNA imaging in plants. Specifically, we established a synthetic split ribozyme system that converts various RNA signals to orthogonal protein outputs, enabling in vivo visualisation of various RNA signals in plants. We demonstrated the utility of this system in transient expression experiments (i.e., leaf infiltration in Nicotiana benthamiana ) to detect RNAs derived from transgenes and tobacco rattle virus, respectively. Also, we successfully engineered a split ribozyme-based biosensor in Arabidopsis thaliana for in vivo visualisation of endogenous gene expression at the cellular level, demonstrating the feasibility of multi-scale (e.g., cellular and tissue level) RNA imaging in plants. Furthermore, we developed a platform for easy incorporation of different protein outputs, allowing for flexible choice of reporters to optimise the detection of target RNAs.

59 BASIC BIOLOGICAL SCIENCES↗

Improving CLM5.0 Biomass and Carbon Exchange Across the Western United States Using a Data Assimilation System

The Western United States is dominated by natural lands that play a critical role for carbon balance, water quality, and timber reserves. This region is also particularly vulnerable to forest mortality from drought, insect attack, and wildfires, thus requiring constant monitoring to assess ecosystem health. Carbon monitoring techniques are challenged by the complex mountainous terrain, thus there is an opportunity for data assimilation systems that combine land surface models and satellite-derived observations to provide improved carbon monitoring. Here, we use the Data Assimilation Research Testbed to adjust the Community Land Model (CLM5.0) with remotely sensed observations of leaf area and above-ground biomass. The adjusted simulation significantly reduced the above-ground biomass and leaf area, leading to a reduction in both photosynthesis and respiration fluxes. The reduction in the carbon fluxes mostly offset, thus both the adjusted and free simulation projected a weak carbon sink to the land. This result differed from a separate observation-constrained model (FLUXCOM) that projected strong carbon uptake to the land. Simulation diagnostics suggested water limitation had an important influence upon the magnitude and spatial pattern of carbon uptake through photosynthesis. We recommend that additional observations important for water cycling (e.g., snow water equivalent, land surface temperature) be included to improve the veracity of the spatial pattern in carbon uptake. Furthermore, the assimilation system should be enhanced to maximize the number of the simulated state variables that are adjusted, especially those related to the recommended observed quantities including water cycling and soil carbon.

54 ENVIRONMENTAL SCIENCES↗

The Global Ecosystem Dynamics Investigation: High-Resolution Laser Ranging of the Earth’s Forests and Topography

Obtaining accurate and widespread measurements of the vertical structure of the Earth’s forests has been a longsought goal for the ecological community. Such observations are critical for accurately assessing the existing biomass of forests, and how changes in this biomass caused by human activities or variations in climate may impact atmospheric CO2 concentrations. Additionally, the three-dimensional structure of forests is a key component of habitat quality and biodiversity at local to regional scales. The Global Ecosystem Dynamics Investigation (GEDI) was launched to the International Space Station in late 2018 to provide high-quality measurements of forest vertical structure in temperate and tropical forests between 51.6 N & S latitude. The GEDI instrument is a geodetic-class laser altimeter/waveform lidar comprised of 3 lasers that produce 8 transects of structural information. Over its two-year nominal lifetime GEDI is anticipated to provide over 10 billion waveforms at a footprint resolution of 25 m. These data will be used to derive a variety of footprint and gridded products, including canopy height, canopy foliar profiles, Leaf Area Index (LAI), sub-canopy topography and biomass. Additionally, data from GEDI are used to demonstrate the efficacy of its measurements for prognostic ecosystem modeling, habit and biodiversity studies, and for fusion using radar and other remote sensing instruments. GEDI science and technology are unique: no other space-based mission has been created that is specifically optimized for retrieving vegetation vertical structure. As such, GEDI promises to advance our understanding of the importance of canopy vertical variations within an ecological paradigm based on structure, composition and function.

Dubayah, Ralph↗

Respiration regimes in rivers: Partitioning source–specific respiration from metabolism time series

Respiration in streams is controlled by the timing, magnitude, and quality of organic matter (OM) inputs from internal primary production and external fluxes. Here, we estimated the contribution of different OM sources to seasonal, annual, and event-driven characteristics of whole-stream ecosystem respiration (ER) using an inverse modeling framework that accounts for possible time-lags between OM inputs and respiration. We modeled site-specific, dynamic OM stocks contributing to ER: autochthonous OM from gross primary production (GPP); allochthonous OM delivered during flow events; and seasonal pulses of leaf litter. OM stored in the sediment and dissolved organic matter (DOM) transported during baseflow were modeled as a stable stock contributing to baseline respiration. We applied this modeling framework to five streams with different catchment size, climate, and canopy cover, where multi-year time series of ER and environmental variables were available. Overall, the model explained between 53% and 74% of observed ER dynamics. Respiration of autochthonous OM tracked seasonal peaks in GPP in spring or summer. Increases in ER were often associated with high-flow events. Respiration associated with litter inputs was larger in smaller streams. Time lags between leaf inputs and respiration were longer than for other OM sources, likely due to lower biological reactivity. Model estimates of source-specific ER and OM stocks compared well with existing measures of OM stocks, inputs, and respiration or decomposition. Our modeling approach has the potential to expand the scale of comparative analyses of OM dynamics within and among freshwater ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

Imaging and dosimetric characteristics of 67 Cu

In recent years the use of beta-emitting radiopharmaceuticals for cancer therapy has expanded rapidly following development of therapeutics for neuroendocrine tumors, prostate cancer, and other oncologic malignancies. One emerging beta-emitting radioisotope of interest for therapy is 67 Cu (t 1/2 : 2.6 d) due to its chemical equivalency with the widely-established positron-emitting isotope 64 Cu (t 1/2 : 12.7 h). Here we evaluate both the imaging and dosimetric characteristics of 67 Cu, as well as producing the first report of SPECT/CT imaging using 67 Cu. To this end, 67 Cu was produced by photon-induced reactions on isotopically-enriched 68 Zn at the Low-Energy Accelerator Facility (LEAF) of Argonne National Laboratory, followed by bulk separation of metallic 68 Zn by sublimation and radiochemical purification by column chromatography. Gamma spectrometry was performed by efficiency-calibrated high-purity germanium (HPGe) analysis to verify absolute activity calibration and establish radionuclidic purity. Absolute activity measurements corroborated manufacturer-recommended dose-calibrator settings and no radionuclidic impurities were observed. Using the Clinical Trials Network anthropomorphic chest phantom, SPECT/CT images were acquired. Medium Energy (ME) SPECT collimation was found to provide the best image quality from the primary 185 keV gamma emission of 67 Cu. Reconstructed images of 67 Cu were similar in quality to images acquired using 177 Lu. Recovery coefficients were calculated and compared against quantitative images of 99m Tc, 177 Lu, and 64 Cu within the same anthropomorphic chest phantom. Production and clinical imaging of 67 Cu appears feasible, and future studies investigating the therapeutic efficacy of 67 Cu-based radiopharmaceuticals are warranted.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Exploring the limits of crop productivity: beyond the limits of tipburn in lettuce

The productivity of lettuce in a combination of high light, high temperature, and elevated CO2 has not been commonly studied because rapid growth usually causes a calcium deficiency in meristems called tipburn, which greatly reduces quality and marketability. We eliminated tipburn by blowing air directly onto the meristem, which allowed us to increase the photosynthetic photon flux (PPF) to 1000 micromoles m-2 s-1 (57.6 mol m-2 d-1); two to three times higher than normally used for lettuce. Eliminating tipburn doubled edible yield at the highest PPF level. In addition to high PPF, CO2 was elevated to 1200 micromoles m-2 mol-1, which increased the temperature optimum from 25 to 30 degrees C. The higher temperature increased leaf expansion rate, which improved radiation capture and more than doubled yield. Photosynthetic efficiency, measured as canopy quantum yield in a whole-plant gas exchange system, steadily increased up to the highest temperature of 32 degrees C in high CO2. The highest productivity was 19 g m-2 d-1 of dry biomass (380 g d-1 fresh mass) averaged over the 23 days the plants received light. Without the limitation of tipburn, the combination of high PPF, high temperature, and elevated CO2 resulted in a 4-fold increase in growth rate over productivity in conventional environments.

NASA Discipline Life Support Systems↗

Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) in Support of Plant-Growth Systems

As the National Aeronautics and Space Association (NASA) begins to pursue long-duration space flights, they will need to be able to provide astronauts with a nutritious and reliable food source. To meet the administration’s goal of traveling to the Moon and Mars, astronauts will need to begin to grow their own food in space. To protect their food source, extensive monitoring will occur to test for the effects of a space flight environment (e.g., radiation) as well as for early pathogen and disease detection. Genomic sequencing allows for both concerns to be tested on a regular basis. However, NASA’s current sequencer is unable to process plant tissues. Therefore, a novel method for plant DNA extraction using microneedle (MN) patches that will be able to feed into NASA’s existing system, but also require minimal human input is proposed. To support this, the design was broken down into four components (1) MN patch fabrication (2) MN patch extraction, (3) automated sampling motion control, and (4) a processing module. The MN patch is fabricated using a custom mold with conically shaped needles. The mold is filled with Polyvinyl alcohol (PVA) solution and placed in a vacuum desiccator. The mold is left in the vacuum overnight until the patch is dry and ready for use. The protocol was tested with varying pressures, drying times, volume amounts, and preparation methods to determine if highquality needles can be produced. A MN is a method of DNA extraction where the patch is applied to a leaf, the needles penetrate the leaf, breaking the rigid plant cell wall to isolate the DNA. A protocol for this method of extraction was tested to ensure the patch could produce the needed yield and purity. The tests varied by the number of patches, number of applications, and plant type. To automate the MN extraction method, motion control will utilize two separate axis tables which move in the x and y directions. The y-axis table will have an end effector that fits a MN patch and will have the ability to apply the patch to the leaf sample. This end effector will also act as a lid for a downstream processing module. The other axis will position the leaf sample and processing container so that the patch can be applied accurately. The Joint Comprehensive Sequencing System (JCSS) module integrates all the components together. The output of this module feeds into the NASA Charged Information-Storage Polymer Preparation System (CHIPPS) for genomic sequencing. The extraction module operates using a series of syringes and tubing to pump the varying reagents needed for the extraction protocol. The results of the study proved that MN patches are a viable method of DNA extraction. While fabrication of high-quality needles was unsuccessful, the protocol was able to be further developed using centrifugation. The integrated design between the motion control and the JCSS enabled the potential for automation with a complete conceptual design and prototype. Future research and development for this study would include (1) further testing for fabrication (2) expanding the range of plant species compatible with the MN patch, and (3) building a working prototype for the integrated system.

Peter Ling↗

Pests, diseases, and aridity have shaped the genome of Corymbia citriodora

Corymbia citriodora is a member of the predominantly Southern Hemisphere Myrtaceae family, which includes the eucalypts (Eucalyptus, Corymbia and Angophora; ~800 species). Corymbia is grown for timber, pulp and paper, and essential oils in Australia, South Africa, Asia, and Brazil, maintaining a high-growth rate under marginal conditions due to drought, poor-quality soil, and biotic stresses. To dissect the genetic basis of these desirable traits, we sequenced and assembled the 408 Mb genome of Corymbia citriodora, anchored into eleven chromosomes. Comparative analysis with Eucalyptus grandis reveals high synteny, although the two diverged approximately 60 million years ago and have different genome sizes (408 vs 641 Mb), with few large intra-chromosomal rearrangements. C. citriodora shares an ancient whole-genome duplication event with E. grandis but has undergone tandem gene family expansions related to terpene biosynthesis, innate pathogen resistance, and leaf wax formation, enabling their successful adaptation to biotic/abiotic stresses and arid conditions of the Australian continent.

59 BASIC BIOLOGICAL SCIENCES↗

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors: Theory - Part 1

The generation of multi-decade long Earth System Data Records (ESDRs) of Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR) from remote sensing measurements of multiple sensors is key to monitoring long-term changes in vegetation due to natural and anthropogenic influences. Challenges in developing such ESDRs include problems in remote sensing science (modeling of variability in global vegetation, scaling, atmospheric correction) and sensor hardware (differences in spatial resolution, spectral bands, calibration, and information content). In this paper, we develop a physically based approach for deriving LAI and FPAR products from the Advanced Very High Resolution Radiometer (AVHRR) data that are of comparable quality to the Moderate resolution Imaging Spectroradiometer (MODIS) LAI and FPAR products, thus realizing the objective of producing a long (multi-decadal) time series of these products. The approach is based on the radiative transfer theory of canopy spectral invariants which facilitates parameterization of the canopy spectral bidirectional reflectance factor (BRF). The methodology permits decoupling of the structural and radiometric components and obeys the energy conservation law. The approach is applicable to any optical sensor, however, it requires selection of sensor-specific values of configurable parameters, namely, the single scattering albedo and data uncertainty. According to the theory of spectral invariants, the single scattering albedo is a function of the spatial scale, and thus, accounts for the variation in BRF with sensor spatial resolution. Likewise, the single scattering albedo accounts for the variation in spectral BRF with sensor bandwidths. The second adjustable parameter is data uncertainty, which accounts for varying information content of the remote sensing measurements, i.e., Normalized Difference Vegetation Index (NDVI, low information content), vs. spectral BRF (higher information content). Implementation of this approach indicates good consistency in LAI values retrieved from NDVI (AVHRRmode) and spectral BRF (MODIS-mode). Specific details of the implementation and evaluation of the derived products are detailed in the second part of this two-paper series.

Ganguly, Sangram↗

Researcher-driven Campaigns Engage Nature's Notebook Participants in Scientific Data Collection

One of the many benefits of citizen science projects is the capacity they hold for facilitating data collection on a grand scale and thereby enabling scientists to answer questions they would otherwise not been able to address. Nature's Notebook, the plant and animal phenology observing program of the USA National Phenology Network (USA-NPN) suitable for scientists and non-scientists alike, offers scientifically-vetted data collection protocols and infrastructure and mechanisms to quickly reach out to hundreds to thousands of potential contributors. The USA-NPN has recently partnered with several research teams to engage participants in contributing to specific studies. In one example, a team of scientists from NASA, the New Mexico Department of Health, and universities in Arizona, New Mexico, Oklahoma, and California are using juniper phenology observations submitted by Nature's Notebookparticipants to improve predictions of pollen release and inform asthma and allergy alerts. In a second effort, researchers from the University of Maryland Center for Environmental Science are engaging Nature's Notebookparticipants in tracking leafing phenophases of poplars across the U.S. These observations will be compared to information acquired via satellite imagery and used to determine geographic areas where the tree species are most and least adapted to predicted climate change. Researchers in these partnerships receive benefits primarily in the form of ground observations. Launched in 2010, the juniper pollen effort has engaged participants in several western states and has yielded thousands of observations that can play a role in model ground validation. Periodic evaluation of these observations has prompted the team to improve and enhance the materials that participants receive, in an effort to boost data quality. The poplar project is formally launching in spring of 2013 and will run for three years; preliminary findings from 2013 will be presented. Participants in these special campaigns benefit through direct engagement in science. This form of researcher partnership has now been successfully pilot-tested and implemented in several instances, and provides a template for future research project campaigns.

Crimmins, Theresa M.↗

Researcher-driven Campaigns Engage Nature's Notebook Participants in Scientific Data Collection

One of the many benefits of citizen science projects is the capacity they hold for facilitating data collection on a grand scale and thereby enabling scientists to answer questions they would otherwise not been able to address. Nature's Notebook, the plant and animal phenology observing program of the USA National Phenology Network (USA-NPN) suitable for scientists and non-scientists alike, offers scientifically-vetted data collection protocols and infrastructure and mechanisms to quickly reach out to hundreds to thousands of potential contributors. The USA-NPN has recently partnered with several research teams to engage participants in contributing to specific studies. In one example, a team of scientists from NASA, the New Mexico Department of Health, and universities in Arizona, New Mexico, Oklahoma, and California are using juniper phenology observations submitted by Nature's Notebookparticipants to improve predictions of pollen release and inform asthma and allergy alerts. In a second effort, researchers from the University of Maryland Center for Environmental Science are engaging Nature's Notebookparticipants in tracking leafing phenophases of poplars across the U.S. These observations will be compared to information acquired via satellite imagery and used to determine geographic areas where the tree species are most and least adapted to predicted climate change. Results/Conclusions Researchers in these partnerships receive benefits primarily in the form of ground observations. Launched in 2010, the juniper pollen effort has engaged participants in several western states and has yielded thousands of observations that can play a role in model ground validation. Periodic evaluation of these observations has prompted the team to improve and enhance the materials that participants receive, in an effort to boost data quality. The poplar project is formally launching in spring of 2013 and will run for three years; preliminary findings from 2013 will be presented. Participants in these special campaigns benefit through direct engagement in science. This form of researcher partnership has now been successfully pilot-tested and implemented in several instances, and provides a template for future research project campaigns.

Crimmins, Theresa M.↗

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗

Generating a Long-Term Land Data Record from the AVHRR and MODIS Instruments

The goal of NASA's Land Long Term Iiata Record (LTDR) project is to produce a consistent long term data set from the AVHRR and MODIS instruments for land climate studies. The project will create daily surface reflectance and normalized difference vegetation index (NDVI) products at a resolution of 0.05 deg., which is identical to the Climate Modeling Grid (CMG) used for MODIS products from EOS Terra and Aqua. Higher order products such as burned area, land surface temperature, albedo, bidirectional reflectance distribution function (BRDF) correction, leaf area index (LAI), and fraction of photosyntheticalIy active radiation absorbed by vegetation (fPAR), will be created. The LTDR project will reprocess Global Area Coverage (GAC) data from AVHRR sensors onboard NOAA satellites by applying the preprocessing improvements identified in the AVHRR Pathfinder Il project and atmospheric and BRDF corrections used in MODIS processing. The preprocessing improvements include radiometric in-flight vicarious calibration for the visible and near infrared channels and inverse navigation to relate an Earth location to each sensor instantaneous field of view (IFOV). Atmospheric corrections for Rayleigh scattering, ozone, and water vapor are undertaken, with aerosol correction being implemented. The LTDR also produces a surface reflectance product for channel 3 (3.75 micrometers). Quality assessment (QA) is an integral part of the LTDR production system, which is monitoring temporal trands in the AVHRR products using time-series approaches developed for MODIS land product quality assessment. The land surface reflectance products have been evaluated at AERONET sites. The AVHRR data record from LTDR is also being compared to products from the PAL (Pathfinder AVHRR Land) and GIMMS (Global Inventory Modeling and Mapping Studies) systems to assess the relative merits of this reprocessing vis-a-vis these existing data products. The LTDR products and associated information can be found at http://ltdr.nascom.nasa.gov/ltdr/ltdr.html.

Pedelty, Jeffrey↗

Casual Rerouting of AERONET Sun/Sky Photometers: Toward a New Network of Ground Measurements Dedicated to the Monitoring of Surface Properties?

This paper presents an innovative method for observing vegetation health at a very high spatial resolution (~5 × 5 cm) and low cost by upgrading an existing Aerosol RObotic NETwork (AERONET) ground station dedicated to the observation of aerosols in the atmosphere. This study evaluates the capability of a sun/sky photometer to perform additional surface reflectance observations. The ground station of Toulouse, France, which belongs to the AERONET sun/sky photometer network, is used for this feasibility study. The experiment was conducted for a 5-year period (between 2016 and 2020). The sun/sky photometer was mounted on a metallic structure at a height of 2.5 m, and the acquisition software was adapted to add a periodical (every hour) ground-observation scenario with the sun/sky photometer observing the surface instead of being inactive. Evaluation is performed by using a classical metric characterizing the vegetation health: the normalized difference vegetation index (NDVI), using as reference the satellite NDVI derived from a Sentinel-2 (S2) sensor at 10 × 10 m resolution. Comparison for the 5-year period showed good agreement between the S2 and sun/sky photometer NDVIs (i.e., bias = 0.004, RMSD = 0.082, and R = 0.882 for a mean value of S2A NDVI around 0.6). Discrepancies could have been due to spatial-representativeness issues (of the ground measurement compared to S2), the differences between spectral bands, and the quality of the atmospheric correction applied on S2 data (accuracy of the sun/sky photometer instrument was better than 0.1%). However, the accuracy of the atmospheric correction applied on S2 data in this station appeared to be of good quality, and no dependence on the presence of aerosols was observed. This first analysis of the potential of the CIMEL CE318 sun/sky photometer to monitor the surface is encouraging. Further analyses need to be carried out to estimate the potential in different AERONET stations. The occasional rerouting of AERONET stations could lead to a complementary network of surface reflectance observations. This would require an update of the software, and eventual adaptations of the measurement platforms to the station environments. The additional cost, based on the existing AERONET network, would be quite limited. These new surface measurements would be interesting for measurements of vegetation health (monitoring of NDVI, and also of other vegetation indices such as the leaf area and chlorophyll indices), for validation and calibration exercise purposes, and possibly to refine various scientific algorithms (i.e., algorithms dedicated to cloud detection or the AERONET aerosol retrieval algorithm itself). CIMEL is ready to include the ground scenario used in this study in all new sun/sky photometers.

Dominique Carrer↗

Generating Global Leaf Area Index from Landsat: Algorithm Formulation and Demonstration

This paper summarizes the implementation of a physically based algorithm for the retrieval of vegetation green Leaf Area Index (LAI) from Landsat surface reflectance data. The algorithm is based on the canopy spectral invariants theory and provides a computationally efficient way of parameterizing the Bidirectional Reflectance Factor (BRF) as a function of spatial resolution and wavelength. LAI retrievals from the application of this algorithm to aggregated Landsat surface reflectances are consistent with those of MODIS for homogeneous sites represented by different herbaceous and forest cover types. Example results illustrating the physics and performance of the algorithm suggest three key factors that influence the LAI retrieval process: 1) the atmospheric correction procedures to estimate surface reflectances; 2) the proximity of Landsatobserved surface reflectance and corresponding reflectances as characterized by the model simulation; and 3) the quality of the input land cover type in accurately delineating pure vegetated components as opposed to mixed pixels. Accounting for these factors, a pilot implementation of the LAI retrieval algorithm was demonstrated for the state of California utilizing the Global Land Survey (GLS) 2005 Landsat data archive. In a separate exercise, the performance of the LAI algorithm over California was evaluated by using the short-wave infrared band in addition to the red and near-infrared bands. Results show that the algorithm, while ingesting the short-wave infrared band, has the ability to delineate open canopies with understory effects and may provide useful information compared to a more traditional two-band retrieval. Future research will involve implementation of this algorithm at continental scales and a validation exercise will be performed in evaluating the accuracy of the 30-m LAI products at several field sites. ©

Landsat↗

VEG-05 Tomato Crop Testing on the International Space Station

Production of fresh, nutritious, and tasty produce for astronauts during spaceflight may provide health-promoting, bioavailable nutrients, enhance the dietary experience, and reduce menu fatigue as we move into longer-duration missions. Growing and caring for plants may also reduce the psychological stresses associated with spaceflight and enhance connection to Earth. A diversity of crops will be required to provide nutrition, variety, and resiliency, however requirements for consistent growth under spaceflight environmental conditions remain unclear. VEG-05 is part of a series of experiments with pick-and-eat salad crops to better define best practices for crop production in space. VEG-05 and predecessor experiments VEG-04A and VEG-04B, grew salad crops in the Veggie vegetable production facilities on the International Space Station using different lighting treatments. In VEG-05 we grew ‘Red Robin’ dwarf cherry tomatoes under two different red: blue lighting spectra. Light can impact the growth habit, yield, nutritional composition, microbial levels, and even flavor attributes within crops, and our goal was to assess these characteristics in ‘Red Robin’ tomatoes during VEG-05. Considerable pre-flight verification testing was performed prior to launch in Nov. 2022. Prior to the flight and ground experiments, lighting in both Veggie units on ISS was measured and lights were standardized between flight and ground hardware. VEG-05 flight operations ran between December 2022 and March 2023, with a ground control initially 48 hours delayed. Due to environmental challenges of very low humidity during the first week of the experiment, seed germination was low for both flight and ground plants. The flight experiment ultimately had 4 - 5 plants per treatment out of the planned 6 plants, but the initial ground control had only three plants in one treatment and none in the other, so this ground control was restarted at the beginning of Feb. 2023 and ran through May, with successful growth of all 12 plants. Both flight and ground control ran 100 days, with harvests of fruit at day 83, day 90, and day 100. Flight plants had uneven growth, and following the early drying events, excess water was frequently observed, which led to a variety of plant stress responses including uneven plant growth, excess adventitious root formation, flower and fruit abortion, and visible microbial growth. In total, from the five surviving red-rich lighted plants, only 5 ripe fruit were produced, and from the four surviving blue-rich lighted plants, 10 fruit were produced with only 6 of these ripe by day 100. Because of the small fruit number and the unsatisfactory growth, crew members were not allowed to consume the tomatoes, and all fruit, as well as large branches with leaves, samples of the adventitious roots, two plant rooting pillows from each treatment, microbial sampling swabs, and some water samples were returned for analysis. Because of the small sample sizes and factors affecting growth on the ISS, objectives of assessing light quality effect (red: blue light treatments) will not be achieved. Revised objectives of this study include to compare stressed flight plants with normal ground plants to determine the impact of plant overwatering stress in space on food safety and the plant microbial community, to determine nutrient content changes in fruit and leaves from stressed plants, and to evaluate stress metabolism changes in returned tissue by transcriptomic analysis. Postflight analysis is underway with the following analyses being conducted: A. culturable microbiology and food safety as well as molecular microbial community analysis of 1. ripe fruit, 2. leaves, stems, and adventitious roots, 3. pillow components (roots, wicks, and substrates), 4. swabs, and 5. water samples from root mats before and after growth. B. transcriptomics of leaf tissue and adventitious roots, and C. elemental analysis of leaf tissue. If sufficient tissue remains elemental analyses will also be conducted on fruit. While not generating the desired information on spaceflight growth responses of healthy crops, our team is hopeful that these analyses will shed light on tomato responses to stress in this environment as plant overwatering stress is a mission-relevant condition that could occur in future space crop growth systems. This research was co-funded by the Human Research Program and Space Biology (MTL#1075) in the ILSRA 2015 NRA call.

Gioia D. Massa↗