Growth, ionic and osmotic relations of an Allenrolfea occidentalis population in an inland salt playa of the Great Basin Desert

Variation in growth, physiology and ionic relations patterns of Allenrolfea occidentalis, a perennial halophyte of dry habitats, was studied under field conditions from May 1996 to November 1997. An A. occidentalis community has a characteristic soil pH of 7·3–8·3. During the two years, the population was exposed to great variations in soil salinity, from 29 to 146 dS m⁻¹, and soil moisture, ranging from drought (9·2%) to wet (19%). The salt concentrations were significantly higher in the surface soil layers than in the subsurface layers. Seasonal changes in dry weight are directly related to soil salinity stress. Allenrolfea occidentalis had greater growth and biomass production under saline conditions. Na⁺and Cl⁻ions were accumulated in plant tissues in much greater amounts than K⁺, Ca²⁺, and Mg²⁺. Soil salinities were significantly reduced at the end of the growing season. Water potentials of the shoots decreased significantly with increasing salinity. The plant (F_v/F_mratio) was more affected by salinity and irradiation levels during the summer period.     

RHESSI Microflares: II. Implications for Loop Structure and Evolution

We present simple analytic models which predict the peak X-ray emission measure and temperature attained in flares in which the chromospheric evaporation process takes place either in a single ‘monolithic’ loop or in a loop consisting of several filaments that are created successively as the energy release process proceeds in time. As possible mechanisms driving chromospheric evaporation we consider both classical heat conduction from the loop top and non-thermal electron beams. The model predictions are tested for a set of 18 well studied RHESSI microflares. The results suggest beam driven evaporation in filamented loops as being capable of accounting for the observed emission measures and temperatures though there are issues with the very high beam densities needed. On the other hand, estimates of the emission measures achieved by conductive evaporation which are derived by using the Rosner – Tucker – Vaiana (RTV) scaling law are much larger than the observed ones. Possible reasons for this discrepancy are discussed.     

Validation of an annual cycle simulation with a T42-L20 GCM

An annual cycle of an atmospheric general circulation model (AGCM) is presented. The winter and summer zonal averages of the atmospheric fields are compared with an observed climatology. The main features of the observed seasonal means are well reproduced by the model. One of the main discrepancies is that the simulated atmosphere is too cold, particularly in its upper part. Some other discrepancies might be explained by the interannual variability. The AGCM surface fluxes are directly compared to climatological estimates. On the other hand, the calculation of meridional heat transport by the ocean, inferred from the simulated energy budget, can be compared to transport induced from climatologies. The main result of this double comparison is that AGCM fluxes generally are within the range of climatological estimates. The main deficiency of the model is poor partitioning between solar and non-solar heat fluxes in the tropical belt. The meridional heat transport also reveals a significant energy-loss by the Northern Hemisphere ocean north of 45° N. The possible implications of model surface flux deficiencies on coupling with an oceanic model are discussed.This paper was presented at the International Conference on Modelling of Global Climate Change and Variability, held in Hamburg 11–15 September 1989 under the auspices of the Meteorological Institute of the University of Hamburg and the Max Planck Institute for Meteorology. Guest Editor for these papers is Dr. L. Dümenil     

Land cover classification by an artificial neural network with ancillary information

Abstract

Remote sensing is an important source of land cover data required by many GIS users. Land cover data are typically derived from remotely–sensed data through the application of a conventional statistical classification. Such classification techniques are not, however, always appropriate, particularly as they may make untenable assumptions about the data and their output is hard, comprising only the code of the most likely class of membership. Whilst some deviation from the assumptions may be tolerated and a fuzzy output may be derived, making more information on class membership properties available, alternative classification procedures are sometimes required. Artificial neural networks are an attractive alternative to the statistical classifiers and here one is used to derive a fuzzy classification output from a remotely–sensed data set that may be post–processed with ancillary data available in a GIS to increase the accuracy with which land cover may be mapped. With the aid ancillary information on soil type and prior knowledge of class occurrence the accuracy of an artificial neural network classification was increased by 29–93 to 77–37 per cent. An artificial neural network can therefore be used generate a fuzzy classification output that may be used with other data sets in a GIS, which may not have been available to the producer of the classification, to increase the accuracy with which land cover may be classified.     

First Data on the Isotopic Age of Zircons from Rocks of the Roseta Ultramafic Massif,Southern Margin of the São Francisco Craton (Brazil)

Doklady Earth Sciences - The results of isotope U–Pb dating of zircons from lherzolite and vein olivine orthopyroxenite composing the Roseta ultramafic massif are presented. The zircons...     

A portable extruder for accurate and precise high-resolution subsampling of unconsolidated sediment cores

Journal of Paleolimnology - We developed a portable extruder for precise and accurate high-resolution subsampling of unconsolidated sediment cores. This extruder is capable of producing subsamples...     

Distinguishing lower and upper crustal processes in magmas erupted during the buildup to the 7.7 ka climactic eruption of Mount Mazama, Crater Lake, Oregon, using 238U–230Th disequilibria

Uranium-series isotope ratios determined for 35 volcanic rocks and 4 glass separates erupted from ~36 to 4.8 ka at Mt. Mazama, Crater Lake, Oregon, identify both ²³⁰Th-excess and ²³⁸U-excess components. U–Th isotope compositions cover a wide range, exceeding those previously measured for the Cascade arc. Age-corrected (²³⁰Th/²³²Th) and (²³⁸U/²³²Th) activity ratios range from 1.113 to 1.464 and from 0.878 to 1.572 (44.4 % ²³⁰Th-excess to 8.8 % ²³⁸U-excess), respectively. The most distinctive aspect of the data set is the contrast in U–Th isotope ratios between low and high Sr (LSr, HSr) components that have been previously identified in products of the 7.7 ka caldera-forming climactic eruption and preclimactic rhyodacite lavas. The LSr component exclusively contains ²³⁸U-excess, but the HSr component, as well as more primitive lavas, are marked by ²³⁰Th-excess. ²³⁰Th-excesses such as those recorded at Mt. Mazama are commonly observed in the Cascades. Melting models suggest that high ²³⁰Th-excesses observed in the more primitive lavas evolved through mixing of a mantle melt with a partial melt of a mafic lower crustal composition that contained garnet in the residuum that was produced through dehydration melting of amphibolite that was initially garnet free. Dehydration melting in the lower crust offers a solution to the “hot-slab paradox” of the Cascades, where low volatile contents are predicted due to high slab temperatures, yet higher water contents than expected have been documented in erupted lavas. The ²³⁸U-excess observed at Mt. Mazama is rare in Cascade lavas, but occurs in more than half of the samples analyzed in this study. Traditionally, ²³⁸U-excess in arc magmas is interpreted to reflect slab fluid fluxing. Indeed, ²³⁸U-excess in arcs is common and likely masks ²³⁰Th-excess resulting from lower crustal interaction. Isotopic and trace element data, however, suggest a relatively minor role for slab fluid fluxing in the Cascades. We propose that ²³⁸U-excess reflects melting and assimilation of young, hydrothermally altered upper crust. The processes related to generating ²³⁸U-excess are likely important features at Mt. Mazama that accompanied development of a large-scale silicic magma chamber that led to the caldera-forming eruption.     

Automated co-registration of images from multiple bands of Liss-4 camera

Three multi-spectral bands of the Liss-4 camera of IRS-P6 satellite are physically separated in the focal plane in the along-track direction. The time separation of 2.1 s between the acquisition of first and last bands causes scan lines acquired by different bands to lie along different lines on the ground which are not parallel. Therefore, the raw images of multi-spectral bands need to be registered prior to any simple application like data visualization. This paper describes a method for co-registration of multiple bands of Liss-4 camera through photogrammetric means using the collinearity equations. A trajectory fit using the given ephemeris and attitude data, followed by direct georeferencing is being employed in this model. It is also augmented with a public domain DEM for the terrain dependent input to the model. Finer offsets after the application of this parametric technique are addressed by matching a small subsection of the bands (100×100 pixels) using an image-based method. Resampling is done by going back to original raw data when creating the product after refining image coordinates with the offsets. Two types of aligned products are defined in this paper and their operational flow is described. Datasets covering different types of terrain and also viewed with different geometries are studied with extensive number of points. The band-to-band registration (BBR) accuracies are reported. The algorithm described in this paper for co-registration of Liss-4 bands is an integral part of the software package Value Added Products generation System (VAPS) for operational generation of IRS-P6 data products.     

Maximum Entropy and Random Forest Modeling of Mineral Potential: Analysis of Gold Prospectivity in the Hezuo–Meiwu District,West Qinling Orogen,China

Natural Resources Research - This study tested and compared the mineral potential mapping capabilities of the random forest (RF) and maximum entropy (MaxEnt) algorithms using gold deposit...