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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Assessing within-Field Corn and Soybean Yield Variability from WorldView-3, Planet, Sentinel-2, and Landsat 8 Satellite Imagery

Crop yield monitoring is an important component in agricultural assessment. Multispectral remote sensing instruments onboard space-borne platforms such as Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS) have shown to be useful for efficiently generating timely and synoptic information on the yield status of crops across regional levels. However, the coarse spatial resolution data inherent to these sensors provides little utility at the management level. Recent satellite imagery collection advances toward finer spatial resolution (down to 1 m) alongside increased observational cadence (near daily) implies information on crops obtainable at field and within-field scales to support farming needs is now possible. To test this premise, we focus on assessing the efficiency of multiple satellite sensors, namely WorldView-3, Planet/Dove-Classic, Sentinel-2, and Landsat 8 (through Harmonized Landsat Sentinel-2 (HLS)), and investigate their spatial, spectral (surface reflectance (SR) and vegetation indices (VIs)), and temporal characteristics to estimate corn and soybean yields at sub-field scales within study sites in the US state of Iowa. Precision yield data as referenced to combine harvesters’ GPS systems were used for validation. We show that imagery spatial resolution of 3 m is critical to explaining 100% of the within-field yield variability for corn and soybean. Our simulation results show that moving to coarser resolution data of 10 m, 20 m, and 30 m reduced the explained variability to 86%, 72%, and 59%, respectively. We show that the most important spectral bands explaining yield variability were green (0.560 µm), red-edge (0.726 µm), and near-infrared (NIR - 0.865 µm). Furthermore, the high temporal frequency of Planet and a combination of Sentinel-2/Landsat 8 (HLS) data allowed for optimal date selection for yield map generation. Overall, we observed mixed performance of satellite-derived models with the coefficient of determination (R^2) varying from 0.21 to 0.88 (averaging 0.56) for the 30 m HLS and from 0.09 to 0.77 (averaging 0.30) for 3 m Planet. R^2 was lower for fields with higher yields, suggesting saturation of the satellite-collected reflectance features in those cases. Therefore, other biophysical variables, such as soil moisture and evapotranspiration, at similar fine spatial resolutions are likely needed alongside the optical imagery to fully explain the yields.

agriculture; yield; within-field; corn; soybean; r↗
DOE OSTI2021

Soil carbon sequestration potential and the identification of hotspots in the Eastern Corn Belt of the United States

Soil carbon sequestration is a significant CO 2 mitigation strategy but precise assessments of sequestration require spatially explicit modeling of potential changes in soil organic carbon (SOC) in response to soil, climate, land condition and management interactions. We assessed the SOC sequestration potential of the Eastern Corn Belt (ECB) in the USA (Indiana, Kentucky, Maryland, Michigan, Ohio, Pennsylvania, and West Virginia) in response to the adoption of conservation farming practices and land use change (pasture and forestation) using the SOCRATES model. Input data was provided through an intersection of the STATSGO, National Land Cover Database and a PRISM climate surface. At the end of the 20th century, the 15.3 Mha of cropped soils in the ECB contained 632 Tg C, an estimated reduction of 52% since the introduction of agriculture in the mid-1800s. Complete adoption of no-tillage practices on Prime Cropland would potentially recover 147 Tg SOC over 20 years, whereas a continuation of conventional tillage would produce a loss of 35 Tg SOC. Sequestration hotspots (> 500 Gg increase in SOC) under no-tillage cover 2.3 Mha providing 28 Tg C over 20 years. The conversion of Marginal (non-Prime) agricultural lands to Forests would yield an additional 13 Tg C in SOC and 381 Tg C in aboveground biomass. The rehabilitation of Minelands to Forest would yield an additional 4 Tg C in SOC and 42 Tg C in biomass. Here, opportunities to sequester C in the ECB via tillage and reforestation are substantial and should be incorporated into regional and national climate change mitigation strategies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1978

LANDSAT image differencing as an automated land cover change detection technique

Image differencing was investigated as a technique for use with LANDSAT digital data to delineate areas of land cover change in an urban environment. LANDSAT data collected in April 1973 and April 1975 for Austin, Texas, were geometrically corrected and precisely registered to United States Geological Survey 7.5-minute quadrangle maps. At each pixel location reflectance values for the corresponding bands were subtracted to produce four difference images. Areas of major reflectance differences are isolated by thresholding each of the difference images. The resulting images are combined to obtain an image data set to total change. These areas of reflectance differences were found, in general, to correspond to areas of land cover change. Information on areas of land cover change was incorporated into a procedure to mask out all nonchange areas and perform an unsupervised classification only for data in the change areas. This procedure identified three broad categories: (1) areas of high reflectance (construction or extractive), (2) changes in agricultural areas, and (3) areas of confusion between agricultural and other areas.

Stauffer, M. L.↗
NASA NTRS1984

Results of an irrigated lands assessment for water management in California

Periodic assessment of existing and future demands for water within California is one responsibility of the California Department of Water Resources (CDWR). The California Irrigated Lands Assessment for Water Management Project represented a 5-year joint research effort between the NASA and the CDWR with technical support from the University of California (UC) at Berkeley and at Santa Barbara. The objectives were: (1) to develop and demonstrate procedures for providing highly precise, timely, estimates of irrigated area on a statewide basis using Landsat sensor data, and (2) to develop, through research with small demonstration sites, a procedure for the inventory and mapping of crop groups on a regional basis. Both manual and computer-assisted analyses were investigated. This paper highlights the statewide irrigated lands inventory where a procedure for statewide estimation of irrigated land using full frame Landsat MSS imagery and sampled ground data was successfully demonstrated. The statewide estimate of 3 990 112 hectares was within + or - 1.32 percent relative standard error at the 95-percent Confidence Interval, well within the design goal. This procedure represents a new capability for obtaining near-real time data on changes in agricultural water use throughout the state.

Bauer, E. H.↗
NASA NTRS2003

Growth Conditions To Reduce Oxalic Acid Content of Spinach

A controlled-environment agricultural (CEA) technique to increase the nutritive value of spinach has been developed. This technique makes it possible to reduce the concentration of oxalic acid in spinach leaves. It is desirable to reduce the oxalic acid content because oxalic acid acts as an anti-nutritive calcium-binding component. More than 30 years ago, an enzyme (an oxidase) that breaks down oxalic acid into CO2 and H2O2 was discovered and found to be naturally present in spinach leaves. However, nitrate, which can also be present because of the use of common nitratebased fertilizers, inactivates the enzyme. In the CEA technique, one cuts off the supply of nitrate and keeps the spinach plants cool while providing sufficient oxygen. This technique provides the precise environment that enables the enzyme to naturally break down oxalate. The result of application of this technique is that the oxalate content is reduced by 2/3 in one week.

Johnson-Rutzke, Corinne↗
DOE OSTI2024

Enzymatic Routes to Designer Hemicelluloses for Use in Biobased Materials

Various enzymes can be used to modify the structure of hemicelluloses directly in vivo or following extraction from biomass sources, such as wood and agricultural residues. Generally, these enzymes can contribute to designer hemicelluloses through four main strategies: (1) enzymatic hydrolysis such as selective removal of side groups by glycoside hydrolases (GH) and carbohydrate esterases (CE), (2) enzymatic cross-linking, for instance, the selective addition of side groups by glycosyltransferases (GT) with activated sugars, (3) enzymatic polymerization by glycosynthases (GS) with activated glycosyl donors or transglycosylation, and (4) enzymatic functionalization, particularly via oxidation by carbohydrate oxidoreductases and via amination by amine transaminases. Thus, this Perspective will first highlight enzymes that play a role in regulating the degree of polymerization and side group composition of hemicelluloses, and subsequently, it will explore enzymes that enhance cross-linking capabilities and incorporate novel chemical functionalities into saccharide structures. These enzymatic routes offer a precise way to tailor the properties of hemicelluloses for specific applications in biobased materials, contributing to the development of renewable alternatives to conventional materials derived from fossil fuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Influence of sampling frequency and estimation method on phosphorus load uncertainty in the Western Lake Erie Basin, Ohio, USA

Accurate estimates of nutrient loads are necessary to identify critical source areas and quantify the impact of management practices on pollutant export. Previous studies have investigated nutrient load estimate uncertainty, but they often focus on nutrient loads estimated using an interpolation method for large-scale watersheds with short-term datasets. The study objective was to quantify uncertainty in soluble reactive phosphorus (SRP), total phosphorus (TP), and suspended solids (SS) load estimates from two small (<10 3 km 2 ) agricultural watersheds in the western Lake Erie Basin resulting from different sampling frequencies. Each watershed had high temporal resolution datasets of discharge (15 min) and nutrient concentration (1 to 3 samples per day) collected over a 30-year period (1990–2020). Firstly, SRP, TP, and SS loads were calculated using the high temporal resolution datasets, which was assumed as “true loads”. Secondly, the high temporal concentration data were decomposed to semiweekly, weekly, biweekly, and monthly sampling and annual loads were estimated using four common load estimation methods to assess the effect of sampling frequency and load estimation method on load estimate error. Across the four different methods, the composite method had the lowest relative root mean square and absolute bias, but the rectangular interpolation method was the most precise. Furthermore, even with semiweekly sampling, the composite method resulted in an unacceptable level of precision (average imprecision = 39 %), while the interpolation method resulted in an unacceptable bias (average absolute bias = 16 %). Because neither method could provide acceptable accuracy and precision at the lowest decrease in sampling (e.t. semiweekly sampling), continued daily sampling is recommended in these watersheds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Phosphoribosylpyrophosphate synthetase as a metabolic valve advances Methylobacterium/Methylorubrum phyllosphere colonization and plant growth

The proficiency of phyllosphere microbiomes in efficiently utilizing plant-provided nutrients is pivotal for their successful colonization of plants. The methylotrophic capabilities of Methylobacterium/Methylorubrum play a crucial role in this process. However, the precise mechanisms facilitating efficient colonization remain elusive. In the present study, we investigate the significance of methanol assimilation in shaping the success of mutualistic relationships between methylotrophs and plants. A set of strains originating from Methylorubrum extorquens AM1 are subjected to evolutionary pressures to thrive under low methanol conditions. A mutation in the phosphoribosylpyrophosphate synthetase gene is identified, which converts it into a metabolic valve. This valve redirects limited C1-carbon resources towards the synthesis of biomass by up-regulating a non-essential phosphoketolase pathway. These newly acquired bacterial traits demonstrate superior colonization capabilities, even at low abundance, leading to increased growth of inoculated plants. This function is prevalent in Methylobacterium/Methylorubrum strains. In summary, our findings offer insights that could guide the selection of Methylobacterium/Methylorubrum strains for advantageous agricultural applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Enabling Technology - Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors

The project “Enabling Technology - Reducing Greenhouse Gas Emissions and Energy Demands in the Meat Production Industry via Scaling Advanced 3D Culture Bioreactors” focuses on developing transformational and disruptive food technologies, specifically in the area of alternative protein and meat production techniques. The impetus for developing alternative protein technologies include reducing intensive greenhouse gas emissions and energy/land/water usages associated with conventional meat production (animal agriculture). Additional rationales include providing alternatives to livestock rearing as a means of reducing antimicrobial resistance (most antibiotic and antimicrobial use occurs in food-producing animals), as well as the transmission of zoonotic diseases. The goal of this ARPA-E project was to research and develop novel and effective technologies to produce cell-cultured meat (also named in vitro meat, cultivated meat). Cell-cultured meat is an alternative protein or meat technology that involves directly growing muscle and fat tissues (which comprise meat) without using the full animal. This offers benefits in terms of animal welfare (elimination of animal slaughter), while also being projected to be more resource efficient in terms of metrics such as land use and greenhouse gas emissions, especially when compared to beef and lamb. Cell cultured meat additionally offers greater control over the cultivated cells, enabling more precise control over nutrition and taste. For example, cultured cells could be tuned to produce antioxidants such as carotenoids to improve human health. However, to date there are no scalable methods of producing cell-cultured meat cheaply at a large scale.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Coronado Ecological Conservation: Assessing Vegetation Change Due to Border Wall Construction and Shifting Social Trails

Species monitoring is essential in mitigating the impacts of plant invasion, such as radical changes in an area’s ecosystem, degraded soil health, increased wildfire severity, landslides, and increased flooding. NASA DEVELOP partnered with the National Park Service (NPS) to investigate invasive species in disturbed lands: specifically, areas affected by off-trail walking and US-Mexico border construction activities. The team assessed how construction has impacted the distribution of Lehmann’s lovegrass and Russian thistle invasives throughout Coronado National Memorial, AZ from 1986 to 2022. Using data from Landsat 5 and 8, Sentinel-2, the National Agriculture Imagery Program, and PlanetScope, the team computed vegetation indices including the Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Modified Soil Adjusted Vegetation Index 2, Enhanced Vegetation Index, and Tasseled Cap Wetness, Brightness, and Greenness transformations as vegetation health indicators to input into various machine learning algorithms. To minimize noise, the team conducted Principal Component Analysis on the vegetation indices and spectral bands before running k-means++ clustering and random forest classification algorithms. Between all datasets, we found the median area fully overtaken by invasive plants was 5.37% of the park’s total area in 2022. The NPS will use the end products to help increase restoration efforts in disturbed areas with high concentrations of invasive plants. The NPS’s collection of ground data for 2022–2023, in conjunction with future data collection, will notably improve the accuracy of classification models, leading to more precise monitoring of invasive spread over time.

Carson Schuetze↗
DOE OSTI2025

Comparison of removal and spatial mark‐resight models for estimating wild pig density

Density estimation is critical to effectively manage invasive species and elucidate areas of highest concern. For wild pigs (Sus scrofa), the ability to estimate density is complicated because of their variable home range sizes and social structure. Common methods for estimating density (e.g., mark-recapture) may be unsuitable in management applications because additional data needs to be collected before and after management. Removal models offer a suitable alternative to estimate density changes following management and can be applied broadly across areas where management of wild pigs is ongoing. We collected wild pig removal and camera trap data from 25 private properties ranging in size from approximately 0.5 km 2 to 95 km 2 across 3 ecoregions in South Carolina, USA, from 2020–2023. We compared factors affecting consistency and precision of property-level density estimates between removal and spatial mark-resight (SMR) models. In general, excluding 1 large outlier, density estimates from removal models were between 0.60 and 15.85 wild pigs/km 2 (median = 5.34) with a median coefficient of variation (CV) of 0.76 and 95% confidence intervals for the CV between 0.70 and 0.94. Similarly, excluding 1 large outlier, density estimates from SMR were between 0.22 and 30.97 wild pigs/km 2 (median = 5.48) with a median CV of 0.39 and 95% confidence intervals for the CV between 0.38 and 1.20. We found the precision of removal models was affected primarily by the number of wild pigs dispatched in the removal period (3 months) and the ecoregion in which they were removed. None of the covariates, including the number of recaptures (a corresponding measure of sample size), influenced precision of the SMR models, although recaptures did influence the density estimates. At the individual property level, density estimates from our 2 estimators were dissimilar from each other in approximately 80% of instances, although none of the covariates we examined influenced dissimilarity. Our results provide unique insight into how sample size affects density estimates using 2 common methods and into novel SMR models that incorporate both marked and unmarked detections. In addition, the density estimates in this study can be used as a reference for wild pig densities in common land cover types throughout the southeastern United States.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

In materials science, plant biology, agriculture, and environmental research, the automated analysis of high-magnification, complex microscopy images, such as those generated by freeze-fracture electron microscopy (FF-TEM), remains a critical challenge that limits the scalability of data interpretation. We present a deep learning computer vision pipeline for high-throughput detection and morphological characterization analysis of cellulose synthase complexes (CSCs, or rosettes) in FF-TEM images. The pipeline integrates preprocessing, detection, human-in-the-loop verification, and semantic segmentation to quantify features such as rosette diameter and inter-lobe spacing. The approach was trained and tested on a curated dataset of high-resolution FF-TEM micrographs of Physcomitrium patens, expanded via strategic tiling and augmentation to over 650 images. We compare YOLOv8 and YOLOv9 architectures and demonstrate that YOLOv9 achieves superior performance in both localization accuracy (mAP50-95 = 0.854) and inference speed. The resulting distributions revealed biological variability consistent with prior manual studies, validating the approach for high-throughput applications. Our results show that the pipeline achieves human-expert level accuracy while dramatically reducing analysis time, enabling scalable, reproducible structural characterization of intramembrane protein complexes. The pipeline is broadly applicable to other domains requiring precise interpretation of complex microscopy data and establishes a foundation for future artificial intelligence (AI)-assisted workflows in biological imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Synthetic feed-forward loop circuit boosts transgene expression in sugarcane

Bio-based products derived from natural plant-derived materials offer a promising alternative to petroleum-based products, which are essential for achieving global sustainability (Gupta et al. 2022). Sugarcane provides 40% of the world’s biofuel (Brant et al. 2025). Recently, metabolic engineering of sugarcane for hyperaccumulation of biomass oil is emerging as a strategy to elevate the crop’s energy content (Cao et al. 2023; Maitra et al. 2024). Synthetic transcription factors offer a powerful tool for modulating entire metabolic pathways by enabling fine-tuned activation or repression of specific genes (Liu and Stewart 2016; Hooghvorst and Altpeter 2023). However, the application of these technologies faces challenges, including the availability of well-characterized genetic building blocks for precise manipulation of gene expression, and the inherently challenging properties of gene expression in highly polyploid crops like sugarcane (Liu and Stewart 2016).

60 APPLIED LIFE SCIENCES↗
NASA NTRS2017

Landsat at 45: How it Changed the Way We See the Earth

On October 24, 1946, more than 10 years before the launch of the first artificial satellite Sputnik, scientists at the White Sands Missile Range in New Mexico placed a camera on top of a captured German V-2 ballistic missile. As the rocket flew to an altitude of about 65 miles - just above the generally recognized border of outer space - the 35-millimeter motion picture camera snapped a frame every one and a half seconds. Minutes later, the missile came crashing back down and slammed into the ground at more than 340 mph, but the film survived and gave us our first glimpse of Earth from space. Earth Resources Technology Satellite aka Landsat It was images like those first grainy black and white pictures and later those taken by America's first astronauts in the 1960's that inspired the development of the Earth Resources Technology Satellite (ERTS). From the unique vantage point of space, we could now observe Earth using a variety of different instruments to monitor changes over time. The ERTS-1 satellite, wisely renamed Landsat-1, was launched aboard a Delta rocket on July 23, 1972, into a Sun-synchronous polar orbit at an altitude of about 560 miles. In this unique orbit, Landsat could observe the same point on the Earth every 18 days, always with the same solar illumination, allowing for precise monitoring of changes on the ground over time. Landsat-1, derived from the highly successful Nimbus weather satellites, carried two instruments that allowed it to take images not only in visible light but also in infrared, well-suited to track changes in vegetation over time. Designed to last only one year, Landsat-1 actually operated for nearly three years, by which time it had been joined in space by Landsat-2, a near identical copy of the original. Since then, ever more sophisticated instruments were flown aboard Landsat-3 through -8, with Landsat-9 planned for launch in 2020, acquiring millions of images of Earth over more than four decades. At first, images from Landsat were processed by NASA and hardcopies sold to users for a fee, a somewhat tedious process. Since 2008, images have been made available to all interested users by the US Geological Survey (USGS) at no cost via the Internet in near real time. So, how can Landsat help? In short, Landsat looks. And looks. And proves Yogi right. Space-based images from Landsat and other similar satellites offer a unique and critical capability to observe land use over time by providing repetitive observations of the Earth otherwise unavailable. The data provided by the images can be used by scientists and politicians to inform wise decisions in areas such as agriculture, climate, ecosystems and biodiversity, energy, forest management, human health, fire, natural disasters, urban growth and water management. This overview article doesn't allow for examples from each of these disciplines, but details can be found at the following website: https://landsat.gsfc.nasa.gov/how_landsat_helps/. One third of the US economy is influenced by climate, weather and natural hazards, providing strong economic incentives to sustain a healthy space-based Earth observation program. One example, however, may be illustrative of how Landsat and other space-based observations can be helpful in monitoring and documenting some effects of global climate change. It had been noted since the 1970's that permafrost in subarctic areas like Siberia was melting at an accelerating rate. It also became apparent that this led to the formation of hundreds of melt lakes and the liberation of large quantities of methane, a gas that in the short-term has more potent greenhouse effects than carbon dioxide. The methane turned the water in these lakes blue, making them easy to track over time by satellite. Additionally, the newly released methane has been carbon dated to tens of thousands of years ago, meaning that it had remained frozen since the last Ice Age and therefore hadn't been accounted for in models of the Earth's overall carbon balance. Release of sufficient methane by an increasingly warming climate could actually cause a positive feedback loop in global warming, melting more permafrost and releasing yet more methane. Further monitoring by Landsat and other platforms will reveal whether this process is reversible or whether we've passed the tipping point. In addition to the highly successful Landsat series of satellites, NASA and other agencies such as the National Oceanic and Atmospheric Administration (NOAA) operate a fleet of other Earth observing platforms, many with more specific research goals such as monitoring sea ice levels or atmospheric carbon content. Several instruments aboard the International Space Station also contribute to this overall effort to better understand short- and long-term changes to the Earth. Many of these missions are guided by the 2009 Decadal Survey published by the National Research Council of the National Academy of Sciences. Europe, Russia and China all see the value of space-based Earth observation by deploying their own fleet of satellites.

Uri, John↗
DOE OSTI2025

Soil Texture and Organic Matter from Teller Field Site and Barrow Environmental Observatory, Alaska, 2024

Understanding soil texture and organic matter content supports our understanding of hydrology and ecology of Arctic sites. Soil organic matter content and composition of sand, silt, and clay were measured from soils collected at the Teller 27 field site on the Seward Peninsula and at the Barrow Environmental Observatory (BEO) near Utqiaġvik, Alaska, on August 2nd and 6th 2024, respectively. Soil samples were collected from the active layer to varied depths. Precise location data were collected at each observation point using Avenza Maps on a mobile device. Sand, silt, clay, and organic matter percentages were measured at Desert Research Institute Soil Characterization and Quaternary Pedology Laboratory in Reno, NV. This dataset contains a *.csv file of soil properties, a *.kml file of measurement locations, a *.pdf user guide, a *.csv data dictionary, and a *.csv file level metadata.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

GWAS identifies candidate genes controlling adventitious rooting in Populus trichocarpa

Adventitious rooting (AR) is critical to the propagation, breeding, and genetic engineering of trees. The capacity for plants to undergo this process is highly heritable and of a polygenic nature; however, the basis of its genetic variation is largely uncharacterized. To identify genetic regulators of AR, we performed a genome-wide association study (GWAS) using 1148 genotypes of Populus trichocarpa. GWASs are often limited by the abilities of researchers to collect precise phenotype data on a high-throughput scale; to help overcome this limitation, we developed a computer vision system to measure an array of traits related to adventitious root development in poplar, including temporal measures of lateral and basal root length and area. GWAS was performed using multiple methods and significance thresholds to handle non-normal phenotype statistics and to gain statistical power. These analyses yielded a total of 277 unique associations, suggesting that genes that control rooting include regulators of hormone signaling, cell division and structure, reactive oxygen species signaling, and other processes with known roles in root development. Numerous genes with uncharacterized functions and/or cryptic roles were also identified. These candidates provide targets for functional analysis, including physiological and epistatic analyses, to better characterize the complex polygenic regulation of AR.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Measurement Error and Resolution in Quantitative Stable Isotope Probing: Implications for Experimental Design

Quantitative stable isotope probing (qSIP) estimates isotope tracer incorporation into DNA of individual microbes and can link microbial biodiversity and biogeochemistry in complex communities. As with any quantitative estimation technique, qSIP involves measurement error, and a fuller understanding of error, precision, and statistical power benefits qSIP experimental design and data interpretation. We used several qSIP data sets—from soil and seawater microbiomes—to evaluate how variance in isotope incorporation estimates depends on organism abundance and resolution of the density fractionation scheme. We assessed statistical power for replicated qSIP studies, plus sensitivity and specificity for unreplicated designs. As a taxon’s abundance increases, the variance of its weighted mean density declines. Nine fractions appear to be a reasonable trade-off between cost and precision for most qSIP applications. Increasing the number of density fractions beyond that reduces variance, although the magnitude of this benefit declines with additional fractions. Our analysis suggests that, if a taxon has an isotope enrichment of 10 atom% excess, there is a 60% chance that this will be detected as significantly different from zero (with alpha 0.1). With five replicates, isotope enrichment of 5 atom% could be detected with power (0.6) and alpha (0.1). Finally, we illustrate the importance of internal standards, which can help to calibrate per sample conversions of %GC to mean weighted density. These results should benefit researchers designing future SIP experiments and provide a useful reference for metagenomic SIP applications where both financial and computational limitations constrain experimental scope.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2014

Prospects for Chlorophyll Fluorescence Remote Sensing from the Orbiting Carbon Observatory-2

The Orbiting Carbon Observatory-2 (OCO-2), scheduled to launch in July 2014, is a NASA mission designed to measure atmospheric CO2. Its main purpose is to allow inversions of net flux estimates of CO2 on regional to continental scales using the total column CO2 retrieved using high-resolution spectra in the 0.76, 1.6, and 2.0 nm ranges. Recently, it was shown that solar-induced chlorophyll fluorescence (SIF), a proxy for gross primary production (GPP, carbon uptake through photosynthesis), can be accurately retrieved from space using high spectral resolution radiances in the 750 nm range from the Japanese GOSAT and European GOME-2 instruments. Here, we use real OCO-2 thermal vacuum test data as well as a full repeat cycle (16 days) of simulated OCO-2 spectra under realistic conditions to evaluate the potential of OCO-2 for retrievals of chlorophyll fluorescence and also its dependence on clouds and aerosols. We find that the single-measurement precision is 0.3-0.5 Wm(exp -2)sr(exp -1) nm(exp -1) (15-25% of typical peak values), better than current measurements from space but still difficult to interpret on a single-sounding basis. The most significant advancement will come from smaller ground-pixel sizes and increased measurement frequency, with a 100-fold increase compared to GOSAT (and about 8 times higher than GOME-2). This will largely decrease the need for coarse spatial and temporal averaging in data analysis and pave the way to accurate local studies.We also find that the lack of full global mapping from the OCO-2 only incurs small representativeness errors on regional averages. Eventually, the combination of net ecosystem exchange (NEE) derived from CO2 source/sink inversions and SIF as proxy for GPP from the same satellite will provide a more process-based understanding of the global carbon cycle.

vegetation agriculture satellite↗