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Compositions of glasses in the Apollo 14 soil correspond to four types of Fra Mauro basalts, to mare basalts and soils, and, in minor amounts, to gabbroic anorthosite and potash granite. The Fra Mauro basalts can be related by simple low pressure crystal-liquid fractionation that implies a parent composition like that of Apollo 14 sample 14310.
Reports given by Soviet specialists at a meeting of Socialist countries on remote sensing of the earth using aerospace methods are presented.
We measured changes in key soil processes and the fluxes of CO2, CH4 and N2O associated with the conversion of tropical rainforest to pasture in Rondonia, a state in the southwest Amazon that has experienced rapid deforestation, primarily for cattle ranching, since the late 1970s. These measurements provide a comprehensive quantitative picture of the nature of surface soil element stocks, C and nutrient dynamics, and trace gas fluxes between soils and the atmosphere during the entire sequence of land-use change from the initial cutting and burning of native forest, through planting and establishment of pasture grass and ending with very old continuously-pastured land. All of our work is done in cooperation with Brazilian scientists at the Centro de Energia Nuclear na Agricultura (CENA) through an extant official bi-lateral agreement between the Marine Biological Laboratory and the University of Sao Paulo, CENA's parent institution.
Microclimate acts as a strong filter on species performance in restored and regenerating forests, particularly in seasonally dry tropical forests (SDTF). Yet few studies have measured microclimate patterns across succession in SDTF. Furthermore, although dynamic vegetation models simulate microclimate, evaluation of these simulated variables with field observations has been relatively uncommon. Here, we investigated the seasonal patterns of soil temperature and soil water in naturally regenerated and planted successional vegetation in SDTF in Costa Rica and Puerto Rico, using complementary approaches of intensive field observations and simulation modeling with the Ecosystem Demography model. We found that plots representing later successional stages were wetter on average, but only during the dry season. During the wet season, mean soil water did not differ across vegetation types, but open, early successional vegetation experienced more frequent extreme wet and dry conditions than older forest and plantations. Soil temperature tended to decline with forest structure, and later successional vegetation also experienced less extreme daily temperature fluctuations. Basal area and leaf area index were the best predictors of differences in soil water and temperature across plots. Model simulations were consistent with observations of wet season soil temperature and soil water, but the model failed to reproduce dry season soil moisture dynamics, suggesting that further work is needed to reduce model biases in microclimate variables. Collectively, our results imply that common assumptions about how microclimates influence successional processes in SDTF should be revisited.
Two oedometer and three direct shear tests have been performed in vacuum on a 200 g sample of lunar soil from Apollo 12 (12001, 119). The compressibility data have been used to calculate bulk density and shear wave velocity versus depth on the lunar surface. The shear wave velocity was found to increase approximately with the one-fourth power of the depth, and the results suggest that the Apollo 14 Active Seismic Experiment may not have detected the Fra Mauro formation at a depth of 8.5 m, but only naturally consolidated lunar soil. The shear data indicate that the strength of the lunar soil sample is about 65% that of a ground basalt simulant at the same void ratio.
Global surface soil moisture (SSM) datasets are being produced based on active and passive microwave satellite observations and simulations from land surface models (LSM). This study investigates the consistency of two global satellite-based SSM datasets based on microwave remote sensing observations from the passive Soil Moisture and Ocean Salinity (SMOS;SMOSL3 version 2.5) and the active Advanced Scatterometer (ASCAT; version TUWien- WARP 5.5) with respect to LSM SSM from the MERRA-Land data product. The relationship between the global-scale SSM products was studied during the 2010-2012 period using (1) a time series statistics (considering both original SSM data and anomalies), (2) a space-time analysis using Hovmoller diagrams, and (3) a triple collocation error model. The SMOSL3 and ASCAT retrievals are consistent with the temporal dynamics of modeled SSM (correlation R (is) greater than 0.70 for original SSM) in the transition zones between wet and dry climates, including the Sahel, the Indian subcontinent, the Great Plains of North America, eastern Australia, and southeastern Brazil. Over relatively dense vegetation covers, a better consistency with MERRA-Land was obtained with ASCAT than with SMOSL3. However, it was found that ASCAT retrievals exhibit negative correlation versus MERRA-Land in some arid regions (e.g., the Sahara and the Arabian Peninsula). In terms of anomalies, SMOSL3 better captures the short term SSM variability of the reference dataset (MERRA-Land) than ASCAT over regions with limited radio frequency interference (RFI) effects (e.g., North America, South America, and Australia). The seasonal and latitudinal variations of SSM are relatively similar for the three products, although the MERRALand SSM values are generally higher and their seasonal amplitude is much lower than for SMOSL3 and ASCAT. Both SMOSL3 and ASCAT have relatively comparable triple collocation errors with similar spatial error patterns: (i) lowest errors in arid regions (e.g., Sahara and Arabian Peninsula), due to the very low natural variability of soil moisture in these areas, and Central America, and (ii) highest errors over most of the vegetated regions (e.g., northern Australia, India, central Asia, and South America). However, the ASCAT SSM product is prone to larger random errors in some regions (e.g., north-western Africa, Iran, and southern South Africa). Vegetation density was found to be a key factor to interpret the consistency with MERRA-Land between the two remotely sensed products (SMOSL3 and ASCAT) which provides complementary information on SSM. This study shows that both SMOS and ASCAT have thus a potential for data fusion into long-term data records.
Abstract The reconstruction of bacterial and archaeal genomes from shotgun metagenomes has enabled insights into the ecology and evolution of environmental and host-associated microbiomes. Here we applied this approach to >10,000 metagenomes collected from diverse habitats covering all of Earth’s continents and oceans, including metagenomes from human and animal hosts, engineered environments, and natural and agricultural soils, to capture extant microbial, metabolic and functional potential. This comprehensive catalog includes 52,515 metagenome-assembled genomes representing 12,556 novel candidate species-level operational taxonomic units spanning 135 phyla. The catalog expands the known phylogenetic diversity of bacteria and archaea by 44% and is broadly available for streamlined comparative analyses, interactive exploration, metabolic modeling and bulk download. We demonstrate the utility of this collection for understanding secondary-metabolite biosynthetic potential and for resolving thousands of new host linkages to uncultivated viruses. This resource underscores the value of genome-centric approaches for revealing genomic properties of uncultivated microorganisms that affect ecosystem processes.
Optical reflection characteristics of various natural sands and soils measured at wavelengths of 4920, 6430 and 7960 angstroms show strong dependence of intensity and degree of polarization on angle of incidence
Effects of thermoradiation inactivation on Bacillus subtilis var. niger at various temperature, and natural spores in soil
The mechanistic basis of the synergetic effect of combined heat and radiation on microbial destruction was analyzed and results show that radiation intensity, temperature, and relative humidity are the determining factors. Dry heat resistance evaluation for selected bacterial spore crops indicates that different strains of Bacillus stearothermophilus demonstrate marked differences in resistance. Preliminary work to determine the effects of storage time, suspending medium, storage temperature and spore crop cleaning procedures on dry heat survival characteristics of Bacillus subtilis var. Niger, and dry heat resistance of natural microflora in soil particles is also reported.
The author has identified the following significant results. The Cement oil field, Oklahoma, was a test site for an experiment designed to evaluate LANDSAT's capability to detect an alteration zone in surface rocks caused by hydrocarbon microseepage. Loss of iron and impregnation of sandstone by carbonate cements and replacement of gypsum by calcite were the major alteration phenomena at Cement. The bedrock alterations were partially masked by unaltered overlying beds, thick soils, and dense natural and cultivated vegetation. Interpreters, biased by detailed ground truth, were able to map the alteration zone subjectively using a magnified, filtered, and sinusoidally stretched LANDSAT composite image; other interpreters, unbiased by ground truth data, could not duplicate that interpretation.
This paper describes the Resource Analysis Program, an applied geographic information system. Several applications are presented which utilized soil, and other natural resource data, to develop integrated maps and data analyses. These applications demonstrate the methods of analysis and the philosophy of approach used in the mapping system. The applications are evaluated in reference to four major needs of a functional mapping system: data capture, data libraries, data analysis, and mapping and data display. These four criteria are then used to describe an effort to develop the next generation of applied mapping systems. This approach uses inexpensive microcomputers for field applications and should prove to be a viable entry point for users heretofore unable or unwilling to venture into applied computer mapping.
The atmospheric effect on the upward radiance of sunlight scattered from the Earth-atmosphere system is strongly influenced by the contrasts between fields and their sizes. For a given atmospheric turbidity, the atmospheric effect on classification of surface features is much stronger for nonuniform surfaces than for uniform surfaces. Therefore, the classification accuracy of agricultural fields and urban areas is dependent not only on the optical characteristics of the atmosphere, but also on the size of the surface do not account for the nonuniformity of the surface have only a slight effect on the classification accuracy; in other cases the classification accuracy descreases. The radiances above finite fields were computed to simulate radiances measured by a satellite. A simulation case including 11 agricultural fields and four natural fields (water, soil, savanah, and forest) was used to test the effect of the size of the background reflectance and the optical thickness of the atmosphere on classification accuracy. It is concluded that new atmospheric correction methods, which take into account the finite size of the fields, have to be developed to improve significantly the classification accuracy.
Thematic Mapper signal counts in the six reflective bands (i.e., excluding the thermal band) are simulated using field and laboratory spectrometer measurements of a variety of crops, crop conditions, and soil types. The Dave atmospheric model and prelaunch sensor characteristics comprise the other components of the simulation. The simulated data are found to occupy essentially three dimensions, two of which are equivalent to the MSS Tasseled Cap Greennes and Brightness features, and a third which is substantially influenced by the mid-infrared bands of the TM. This new dimension is primarily related to soil characteristics, including soil moisture. The nature and characteristics of each dimension are discussed, as are some of the expected information gains (over MSS data) resulting from the additional dimensionality of the data.
The atmospheric effect on the upward radiance of sunlight scattered from the earth-atmosphere system is strongly influenced by the contrasts between fields and their sizes. In this paper, the radiances above finite fields are computed to simulate radiances measured by a satellite. A simulation case including 11 agricultural fields and four natural fields (water, soil, savanah, and forest) is used to test the effect of field size, background reflectance, and optical thickness of the atmosphere on the classification accuracy. For a given atmospheric turbidity, the atmospheric effect on classification of surface features may be much stronger for nonuniform surfaces than for uniform surfaces. Therefore, the classification accuracy of agricultural fields and urban areas is dependent not only on the optical characteristics of the atmosphere, but also on the size of the surface elements to be classified and their contrasts. It is concluded that new atmospheric correction methods, which take into account the finite size of the fields, are needed.
Analysis will be presented which explores the impact of land conditions on monthly to seasonal climate simulations in a variety of atmospheric general circulation models (AGCMs). In one set of experiments, the Geophysical Fluid Dynamics Laboratory (GDFL) AGCM is used to explore the nature of soil-moisture predictability and associated climate predictability as an initial value problem. For another set of experiments, the Center for Ocean Land Atmosphere (COLA) and the Goddard Earth Observing System 2 (GEOS-2) AGCMs are used to investigate the impact of realistic snow initialization and assimilation in retrospective climate forecasts for the northern hemisphere spring (March-June).
Brownout is a dangerous problem for rotorcraft operating in arid and dusty environments such as the current operating theaters in Iraq and Afghanistan. Although the interest in brownout has increased in the past decade, the fundamental physics that govern the shape and size of the cloud are not yet well understood. Many computational and scaled experimental studies have been performed in an attempt to further this understanding and to simulate and predict the brownout cloud formation. However, the phenomenon significantly lacks experimental data, particularly at full-scale, which is needed to help validate the brownout simulations being performed. In an effort to increase the data set needed for this validation, tests were performed at the US Army Yuma Proving Ground using photogrammetry to obtain brownout cloud data of an EH-60L Black Hawk. Particle testing was performed on a sample of sand from the landing zone to gain more understanding on the nature of the soil. The photogrammetry technique applied to obtaining data on the formation and evolution of a brownout cloud was verified in an earlier study. The data for a landing approach was examined in greater detail and enabled velocity components of points on the cloud to be determined, as well as the dimensions of structures within the cloud.
This study intercompares, among five global models, the potential impacts of all commercial aircraft emissions worldwide on surface ozone and particulate matter (PM (sub 2.5)). The models include climate-response models (CRMs) with interactive meteorology, chemical-transport models (CTMs) with prescribed meteorology, and models that integrate aspects of both. Model inputs are harmonized in an effort to achieve a consensus about the state of understanding of impacts of 2006 commercial aviation emissions. Models find that aircraft increase near-surface ozone (0.3 to 1.9 percent globally), with qualitatively similar spatial distributions, highest in the Northern Hemisphere. Annual changes in surface-level PM (sub 2.5) in the CTMs (0.14 to 0.4 percent) and CRMs (-1.9 to 1.2 percent) depend on differences in nonaircraft baseline aerosol fields among models and the inclusion of feedbacks between aircraft emissions and changes in meteorology. The CTMs tend to result in an increase in surface PM (sub 2.5) primarily over high-traffic regions in the North American midlatitudes. The CRMs, on the other hand, demonstrate the effects of aviation emissions on changing meteorological fields that result in large perturbations over regions where natural emissions (e.g., soil dust and sea spray) occur. The changes in ozone and PM (sub 2.5) found here may be used to contextualize previous estimates of impacts of aircraft emissions on human health.