Discovery of animal eggs and embryos from the Ediacaran (Terminal Proterozoic) Chambaghat Formation,Krol Group,Himachal Lesser Himalaya

The globular to suboval microfossils with distinctively ornamented outer coverings interpreted as animal eggs and embryos have been discovered from the black phosphatic chert lentils of the Ediacaran (Terminal Proterozoic) Chambaghat Formation (Krol sandstone), Krol Group, Himachal Lesser Himalaya, India. Similar animal eggs and embryos have earlier been recorded only from the phosphorites of the uppermost Neoproterozoic Doushantuo Formation (Ca. 570±20 Ma) exposed at Weng’an, South China. Present record of eggs and embryos is comparable with extant eggs and embryos of cnidarians and bilaterians like molluscs, annelids and arthropods. The eggs and embryos from the Terminal Proterozoic rocks of India are the only one recorded from the equivalent stratigraphic horizon outside China. This discovery of eggs and embryos adds to the understanding the evolutionary trends in the Proterozoic metazoan life.     

Elemental variations in glacier cryoconites of Indian Himalaya and Spitsbergen,Arctic

Cryoconite samples were collected from two different climatic domains i.e., the Sutri Dhaka glacier, western Himalaya India and Svalbard glaciers, the Spitsbergen, Arctic, to understand the elemental source and elemental deposition patterns. The data of geochemical analysis suggest that the Himalayan cryoconite samples accumulate higher concentrations as compared to the cryoconite samples of the Arctic glaciers. The concentration of lithophile elements (Cs, Li, Rb and U) was recorded higher in the cryoconite holes of the Himalayas, especially, in the lower to the higher parts of the glacier, whereas, lower concentrations were recorded in the Arctic samples. Chalcophile elements in the Himalayan cryoconites are enriched in As and Bi while the Arctic cryoconite samples show a higher concentration of Bi, Pb and As. The higher concentrations are responsible for influencing the ecosystem and in human health related issues. Siderophile elements (Co, Fe, Mn and Ni) show high concentrations in the Himalayan samples, whereas, the Arctic samples show minor variations and low elemental concentration in these elements, respectively. In addition, a few elements, such as Ag, Mg, and Ca show higher concentration in the Himalayan glacier samples. Ca also occurs in high concentrations in Arctic glacier samples. R-mode factor analysis of the Himalayas (Arctic) samples indicate that the elements are distributed in four (three) factors, explaining 89% (90%) of the variance in their elemental distribution. The Factor 1 suggests statistically significant positive loadings for most of the lithophile, chalcophile and siderophile elements of the “Himalayan” and the Arctic cryoconite samples. The sample-wise factor score distribution shows a considerable variation in the sampling locations along the glaciers of both the regions. Factors 2 and 3, demonstrate insignificant loading for most of the elements, except statistically significant positive loading in some of the elements of the both, Himalayan and Arctic “cryoconites”. The higher elemental concentration in the cryoconites of the Himalayan region may be an indicator of the natural processes and/or attributed to the rapid industrialization in the Asian countries.     

Hydrochemical characterization and suitability assessment of groundwater in Baga–Calangute stretch of Goa,India

The present study is the first attempt to determine the suitability of groundwater for drinking and irrigation in the Baga–Calangute stretch of Goa. The suitability of groundwater for potable use was assessed by comparing observed values against standards prescribed by the Bureau of Indian Standards, and the quality was classified based on the Weighted Arithmetic Water Quality Index. Most of the groundwater samples (90%) were found to be suitable for drinking except for hardness, chlorides, and nitrates. The percent sodium (%Na), residual sodium carbonate, soluble sodium percentage, sodium adsorption ratio, Kelly’s ratio, and Permeability Index were found to be within the prescribed limits for irrigation purposes. The major mechanism controlling groundwater chemistry, i.e., rock–water interaction, was also studied, and it was found that silicate weathering plays a major role in the dissolution of minerals. Based on the hydrochemical characterization, the water was observed to be of the Ca–Na–SO₄ composition type except for one sample which was of the Na–Cl composition type. Classification of the meteoric genesis suggested that the groundwater in surficial aquifers in the region had a deep meteoric percolation, and its chemistry is regulated by rock–water interaction.     

Estimating soil moisture using remote sensing data: A machine learning approach

Soil moisture is an integral quantity in hydrology that represents the average conditions in a finite volume of soil. In this paper, a novel regression technique called Support Vector Machine (SVM) is presented and applied to soil moisture estimation using remote sensing data. SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach. SVM has been used to predict a quantity forward in time based on training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. SVM model is applied to 10 sites for soil moisture estimation in the Lower Colorado River Basin (LCRB) in the western United States. The sites comprise low to dense vegetation. Remote sensing data that includes backscatter and incidence angle from Tropical Rainfall Measuring Mission (TRMM), and Normalized Difference Vegetation Index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) are used to estimate soil water content (SM). Simulated SM (%) time series for the study sites are available from the Variable Infiltration Capacity Three Layer (VIC) model for top 10 cm layer of soil for the years 1998–2005. SVM model is trained on 5 years of data, i.e. 1998–2002 and tested on 3 years of data, i.e. 2003–2005. Two models are developed to evaluate the strength of SVM modeling in estimating soil moisture. In model I, training and testing are done on six sites, this results in six separate SVM models – one for each site. Model II comprises of two subparts: (a) data from all six sites used in model I is combined and a single SVM model is developed and tested on same sites and (b) a single model is developed using data from six sites (same as model II-A) but this model is tested on four separate sites not used to train the model. Model I shows satisfactory results, and the SM estimates are in good agreement with the estimates from VIC model. The SM estimate correlation coefficients range from 0.34 to 0.77 with RMSE less than 2% at all the selected sites. A probabilistic absolute error between the VIC SM and modeled SM is computed for all models. For model I, the results indicate that 80% of the SM estimates have an absolute error of less than 5%, whereas for model II-A and II-B, 80% and 60% of the SM estimates have an error less than 10% and 15%, respectively. SVM model is also trained and tested for measured soil moisture in the LCRB. Results with RMSE, MAE and R of 2.01, 1.97, and 0.57, respectively show that the SVM model is able to capture the variability in measured soil moisture. Results from the SVM modeling are compared with the estimates obtained from feed forward-back propagation Artificial Neural Network model (ANN) and Multivariate Linear Regression model (MLR); and show that SVM model performs better for soil moisture estimation than ANN and MLR models.     

Spherules from the Late Cretaceous Phosphorite of the Fatehgarh Formation, Barmer Basin, India

A first report of discovery of spherules, glassy balls, highly magnetic fine dust and microbracciated matrix in the Fatehgarh Formation of Barmer Basin, Rajasthan, India is being presented in this paper. The Fatehgarh Formation is a mixed siliciclastic, carbonate and phosphorite formation of Cretaceous age in the Barmer Basin that comprises sediments of Middle Jurassic to Lower Eocene age. The phosphorite zone in the Fatehgarh Formation is 8 metre-thick zone that comprises phosphatic sandstone, bone bed, bedded phosphorite and phosphatic and non phosphatic gastropod beds. The spherules occur in a thin phosphatic-clay mud and silt band of bone bed, which also yielded a very rich and diverse microvertebrate assemblage with a dominant Late Cretaceous (Maastrichtian) form of Igdabatis along with forms comprising of Semionodontid, Lapisosteum and Enchodontid. The end Cretaceous is marked for a mass extinction of numerous species including dinosaurs. An extraterrestrial impact is interpreted as the reason for this mass extinction. Whether these spherules are related to the volcanic source or K/T Boundary impact ejecta found at Caribbean and Gulf of Mexico region needs detailed chemical and age characterization for which study is in progress.     

An iron isotope signature related to electron transfer between aqueous ferrous iron and goethite

We measured the Fe isotope fractionation during the reactions of Fe(II) with goethite in the presence and absence of a strong Fe(III) chelator (desferrioxamine mesylate, DFAM). All experiments were completed in an O₂-free glove box. The concentrations of aqueous Fe(II) ([Fe(II)_aq]) decreased below the initial total dissolved Fe concentrations ([Fe(II)_total], 2.15 mM) due to fast adsorption within 0.2 day. The concentration of adsorbed Fe(II) ([Fe(II)_ads]) was determined as the difference between [Fe(II)_aq] and the concentration of extracted Fe(II) in 0.5 M HCl ([Fe(II)_extr]) (i.e., [Fe(II)_ads] = [Fe(II)_extr] − [Fe(II)_aq]). [Fe(II)_ads] also decreased with time in experiments with and without DFAM, documenting that fast adsorption was accompanied by a second, slower reaction. Interestingly, [Fe(II)_extr] was always smaller than [Fe(II)_total], indicating that some Fe(II) was sequestered into a pool that is not HCl-extractable. The difference was attributed to Fe(II) incorporated into goethite structure (i.e., [Fe(II)_inc] = [Fe(II)_total] −[Fe(II)_extr]). More Fe(II) was incorporated in the presence of DFAM than in its absence at all time steps. Regardless of the presence of DFAM, both aqueous and extracted Fe(II) (δ^56/54Fe(II)_aq and δ^56/54Fe(II)_extr) became isotopically lighter than or similar to goethite (− 0.27‰) at day 7, implying that the isotope exchange occurred between bulk goethite and aqueous Fe. Consistently, the mass balance indicated that the incorporated Fe is isotopically heavier than extracted Fe. These observations suggested that (i) co-adsorption of Fe(II) with DFAM resulted in more pervasive electron transfer, (ii) the electron transfer from heavy Fe(II) in the adsorbed Fe(II) to light Fe(III) in goethite results in the fixation of heavy adsorbed Fe(III) on the surface and accumulation of Fe(II) within the goethite, and (iii) desorption of the reduced, light Fe from goethite does not necessarily occur at the same surface sites where adsorption occurred.     

U–Pb geochronology,Sr–Nd isotopic compositions,geochemistry and petrogenesis of Shah Soltan Ali granitoids,Birjand, Eastern Iran

The Shah Soltan Ali area (SSA) is located in the eastern part of the Lut Block metallogenic province. In this area different types of sub-volcanic intrusions including diorite porphyry, monzonite porphyry and monzodiorite porphyry have intruded into basaltic and andesitic rocks. Zircon U–Pb dating and field observations indicate that intermediate to mafic volcanic rocks (38.9 Ma) are older than subvolcanic units (38.3 Ma). The subvolcanic intrusions show high-K calc-alkaline to shoshonitic affinity and are metaluminous. Based on mineralogy, high values of magnetic susceptibility [(634 to 3208) × 10^?5 SI], and low initial ⁸⁷Sr/⁸⁶Sr ratios, they are classified as belonging to the magnetite-series of oxidant I-type granitoids and are characterized by an enrichment in LREEs relative to HREEs, with negative Nb, Ti, Zr and Eu anomalies. These granitoids are related to volcanic arc (VAG) and were generated in an active continental margin. Low initial ⁸⁷Sr/⁸⁶Sr ratios (0.7043 to 0.7052) and positive εNd values (+1.48 to +3.82) indicate that the parental magma was derived from mantle wedge. Parental magma was probably formed by low degree of partial melting and metasomatized by slab derived fluids. Then assimilation and fractional crystallization processes (AFC) produced the SSA rocks. This magma during the ascent was contaminated with the crustal material.All data suggest that Middle-Late Eocene epoch magmatism in the SSA area, occurred during subduction of Neo-Tethys Ocean in east of Iran (between Afghan and Lut Blocks).     

The Raghunathpura iron meteorite from Alwar,India

Abstract— The Raghunathpura iron meteorite fell on 20 November 1986 around 8 p.m.; it weighed 10.2 kg. It is a group IIA hexahedrite based on metallographic, x-ray diffraction and chemical studies. Eighteen major, minor and trace elements were determined using classical, atomic-absorption spectrometry and semiquantitative spectrographic procedures.     

Effects of atmospheric boundary layer mixing representations on vertical distribution of passive and reactive tracers

Summary A one-dimensional chemistry-boundary layer model was used to study the effects of differing representations of atmospheric boundary layer (ABL) processes on simulated concentrations of passive and chemically reactive tracers. Two local- and two nonlocal-closure ABL schemes were used to perform numerical simulations during convective conditions in the ABL. Observational data from the First International Statellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) were used to provide initial meteorological conditions while representative chemical concentrations and surface and elevated emission rates were used to provide initial chemical conditions and chemical sources to the one-dimensional model. Two sets of numerical simulations were performed using the four ABL schemes. The first set simulated bottom-to-top mixing characteristics, and the second set simulated top-to-bottom mixing characteristics. Model simulations were performed for 12h starting from 0700LT 11 July 1987.Our analysis indicate that the simulated concentrations of both passive and reactive chemical species were sensitive to the type of ABL scheme used to represent turbulent mixing processes. Characteristic features associated with each scheme (e.g., growth and intensity of mixing in the ABL) contributed to the differences among the simulated species concentrations. For some of the chemical species these differences were large, particularly in the surface layer and in the interfacial layers of the ABL. In turn, differences caused by the differing mixing representations resulted in different chemical production/destruction rates. As a consequence, the simulated species concentrations differed among the simulations. We also found that chemical species concentrations were more sensitive to the type of ABL scheme in the bottom-to-top mixing simulations than in the top-to-bottom simulations.With 10 Figures