39 resultados para Spatial Distribution


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Invasive species demonstrate rapid evolution within a very short period of time allowing one to understand the underlying mechanism(s). Lantana camara, a highly invasive plant of the tropics and subtropics, has expanded its range and successfully established itself almost throughout India. In order to uncover the processes governing the invasion dynamics, 218 individuals from various locations across India were characterized with six microsatellites. By integrating genetic data with niche modelling, we examined the effect of drift and environmental selection on genetic divergence. We found multiple genetic clusters that were non-randomly distributed across space. Spatial autocorrelation revealed a strong fine-scale structure, i.e. isolation by distance. In addition, we obtained evidence of inhibitory effects of selection on gene flow, i.e. isolation by environmental distance. Perhaps, local adaptation in response to selection is offsetting gene flow and causing the populations to diverge. Niche models suggested that temperature and precipitation play a major role in the observed spatial distribution of this plant. Based on a non-random distribution of clusters, unequal gene flow among them and different bioclimatic niche requirements, we concluded that the emergence of ecotypes represented by two genetic clusters is underway. They may be locally adapted to specific climatic conditions, and perhaps at the very early stages of ecological divergence.

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We investigated the site response characteristics of Kachchh rift basin over the meizoseismal area of the 2001, Mw 7.6, Bhuj (NW India) earthquake using the spectral ratio of the horizontal and vertical components of ambient vibrations. Using the available knowledge on the regional geology of Kachchh and well documented ground responses from the earthquake, we evaluated the H/V curves pattern across sediment filled valleys and uplifted areas generally characterized by weathered sandstones. Although our HIV curves showed a largely fuzzy nature, we found that the hierarchical clustering method was useful for comparing large numbers of response curves and identifying the areas with similar responses. Broad and plateau shaped peaks of a cluster of curves within the valley region suggests the possibility of basin effects within valley. Fundamental resonance frequencies (f(0)) are found in the narrow range of 0.1-2.3 Hz and their spatial distribution demarcated the uplifted regions from the valleys. In contrary, low HIV peak amplitudes (A(0) = 2-4) were observed on the uplifted areas and varying values (2-9) were found within valleys. Compared to the amplification factors, the liquefaction indices (kg) were able to effectively indicate the areas which experienced severe liquefaction. The amplification ranges obtained in the current study were found to be comparable to those obtained from earthquake data for a limited number of seismic stations located on uplifted areas; however the values on the valley region may not reflect their true amplification potential due to basin effects. Our study highlights the practical usefulness as well as limitations of the HIV method to study complex geological settings as Kachchh. (C) 2014 Elsevier Ltd. All rights reserved.

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The similar to 700-km-long ``central seismic gap'' is the most prominent segment of the Himalayan front not to have ruptured in a major earthquake during the last 200-500 yr. This prolonged seismic quiescence has led to the proposition that this region, with a population >10 million, is overdue for a great earthquake. Despite the region's recognized seismic risk, the geometry of faults likely to host large earthquakes remains poorly understood. Here, we place new constraints on the spatial distribution of rock uplift within the western similar to 400 km of the central seismic gap using topographic and river profile analyses together with basinwide erosion rate estimates from cosmogenic Be-10. The data sets show a distinctive physiographic transition at the base of the high Himalaya in the state of Uttarakhand, India, characterized by abrupt strike-normal increases in channel steepness and a tenfold increase in erosion rates. When combined with previously published geophysical imaging and seismicity data sets, we interpret the observed spatial distribution of erosion rates and channel steepness to reflect the landscape response to spatially variable rock uplift due to a structurally coherent ramp-flat system of the Main Himalayan Thrust. Although it remains unresolved whether the kinematics of the Main Himalayan Thrust ramp involve an emergent fault or duplex, the landscape and erosion rate patterns suggest that the decollement beneath the state of Uttarakhand provides a sufficiently large and coherent fault segment capable of hosting a great earthquake.

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The spatial error structure of daily precipitation derived from the latest version 7 (v7) tropical rainfall measuring mission (TRMM) level 2 data products are studied through comparison with the Asian precipitation highly resolved observational data integration toward evaluation of the water resources (APHRODITE) data over a subtropical region of the Indian subcontinent for the seasonal rainfall over 6 years from June 2002 to September 2007. The data products examined include v7 data from the TRMM radiometer Microwave Imager (TMI) and radar precipitation radar (PR), namely, 2A12, 2A25, and 2B31 (combined data from PR and TMI). The spatial distribution of uncertainty from these data products were quantified based on performance metrics derived from the contingency table. For the seasonal daily precipitation over a subtropical basin in India, the data product of 2A12 showed greater skill in detecting and quantifying the volume of rainfall when compared with the 2A25 and 2B31 data products. Error characterization using various error models revealed that random errors from multiplicative error models were homoscedastic and that they better represented rainfall estimates from 2A12 algorithm. Error decomposition techniques performed to disentangle systematic and random errors verify that the multiplicative error model representing rainfall from 2A12 algorithm successfully estimated a greater percentage of systematic error than 2A25 or 2B31 algorithms. Results verify that although the radiometer derived 2A12 rainfall data is known to suffer from many sources of uncertainties, spatial analysis over the case study region of India testifies that the 2A12 rainfall estimates are in a very good agreement with the reference estimates for the data period considered.

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Climate change in response to a change in external forcing can be understood in terms of fast response to the imposed forcing and slow feedback associated with surface temperature change. Previous studies have investigated the characteristics of fast response and slow feedback for different forcing agents. Here we examine to what extent that fast response and slow feedback derived from time-mean results of climate model simulations can be used to infer total climate change. To achieve this goal, we develop a multivariate regression model of climate change, in which the change in a climate variable is represented by a linear combination of its sensitivity to CO2 forcing, solar forcing, and change in global mean surface temperature. We derive the parameters of the regression model using time-mean results from a set of HadCM3L climate model step-forcing simulations, and then use the regression model to emulate HadCM3L-simulated transient climate change. Our results show that the regression model emulates well HadCM3L-simulated temporal evolution and spatial distribution of climate change, including surface temperature, precipitation, runoff, soil moisture, cloudiness, and radiative fluxes under transient CO2 and/or solar forcing scenarios. Our findings suggest that temporal and spatial patterns of total change for the climate variables considered here can be represented well by the sum of fast response and slow feedback. Furthermore, by using a simple 1-D heat-diffusion climate model, we show that the temporal and spatial characteristics of climate change under transient forcing scenarios can be emulated well using information from step-forcing simulations alone.

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Purpose - The purpose of this paper is to investigate the possibility to construct tissue-engineered bone repair scaffolds with pore size distributions using rapid prototyping techniques. Design/methodology/approach - The fabrication of porous scaffolds with complex porous architectures represents a major challenge in tissue engineering and the design aspects to mimic complex pore shape as well as spatial distribution of pore sizes of natural hard tissue remain unexplored. In this context, this work aims to evaluate the three-dimensional printing process to study its potential for scaffold fabrication as well as some innovative design of homogeneously porous or gradient porous scaffolds is described and such design has wider implication in the field of bone tissue engineering. Findings - The present work discusses biomedically relevant various design strategies with spatial/radial gradient in pore sizes as well as with different pore sizes and with different pore geometries. Originality/value - One of the important implications of the proposed novel design scheme would be the development of porous bioactive/biodegradable composites with gradient pore size, porosity, composition and with spatially distributed biochemical stimuli so that stem cells loaded into scaffolds would develop into complex tissues such as those at the bone-cartilage interface.

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To improve the spatial distribution of nano particles in a polymeric host and to enhance the interfacial interaction with the host, the use of chain-end grafted nanoparticle has gained popularity in the field of polymeric nanocomposites. Besides changing the material properties of the host, these grafted nanoparticles strongly alter the dynamics of the polymer chain at both local and cooperative length scales (relaxations) by manipulating the enthalpic and entropic interactions. It is difficult to map the distribution of these chain-end grafted nanoparticles in the blend by conventional techniques, and herein, we attempted to characterize it by unique technique(s) like peak force quantitative nanomechanical mapping (PFQNM) through AFM (atomic force microscopy) imaging and dielectric relaxation spectroscopy (DRS). Such techniques, besides shedding light on the spatial distribution of the nanoparticles, also give critical information on the changing elasticity at smaller length scales and hierarchical polymer chain dynamics in the vicinity of the nanoparticles. The effect of one-dimensional rodlike multiwall carbon nanotubes (MWNTs), with the characteristic dimension of the order of the radius of gyration of the polymeric chain, on the phase miscibility and chain dynamics in a classical LCST mixture of polystyrene/ poly(vinyl methyl ether) (PS/PVME) was examined in detail using the above techniques. In order to tune the localization of the nanotubes, different molecular weights of PS (13, 31, and 46 kDa), synthesized using RAFT (reversible addition fragmentation chain transfer) polymerization, was grafted onto MWNTs in situ. The thermodynamic miscibility in the blends was assessed by low-amplitude isochronal temperature sweeps, the spatial distribution of MWNTs in the blends was evaluated by PFQNM, and the hierarchical polymer chain dynamics was studied by DRS. It was observed that the miscibility, concentration fluctuation, and cooperative relaxations of the PS/PVME blends are strongly governed by the spatial distribution of MWNTs in the blends. These findings should help guide theories and simulations of hierarchical chain dynamics in LCST mixtures containing rodlike nanoparticles.

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To improve the spatial distribution of nano particles in a polymeric host and to enhance the interfacial interaction with the host, the use of chain-end grafted nanoparticle has gained popularity in the field of polymeric nanocomposites. Besides changing the material properties of the host, these grafted nanoparticles strongly alter the dynamics of the polymer chain at both local and cooperative length scales (relaxations) by manipulating the enthalpic and entropic interactions. It is difficult to map the distribution of these chain-end grafted nanoparticles in the blend by conventional techniques, and herein, we attempted to characterize it by unique technique(s) like peak force quantitative nanomechanical mapping (PFQNM) through AFM (atomic force microscopy) imaging and dielectric relaxation spectroscopy (DRS). Such techniques, besides shedding light on the spatial distribution of the nanoparticles, also give critical information on the changing elasticity at smaller length scales and hierarchical polymer chain dynamics in the vicinity of the nanoparticles. The effect of one-dimensional rodlike multiwall carbon nanotubes (MWNTs), with the characteristic dimension of the order of the radius of gyration of the polymeric chain, on the phase miscibility and chain dynamics in a classical LCST mixture of polystyrene/ poly(vinyl methyl ether) (PS/PVME) was examined in detail using the above techniques. In order to tune the localization of the nanotubes, different molecular weights of PS (13, 31, and 46 kDa), synthesized using RAFT (reversible addition fragmentation chain transfer) polymerization, was grafted onto MWNTs in situ. The thermodynamic miscibility in the blends was assessed by low-amplitude isochronal temperature sweeps, the spatial distribution of MWNTs in the blends was evaluated by PFQNM, and the hierarchical polymer chain dynamics was studied by DRS. It was observed that the miscibility, concentration fluctuation, and cooperative relaxations of the PS/PVME blends are strongly governed by the spatial distribution of MWNTs in the blends. These findings should help guide theories and simulations of hierarchical chain dynamics in LCST mixtures containing rodlike nanoparticles.

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Anthropogenic aerosols play a crucial role in our environment, climate, and health. Assessment of spatial and temporal variation in anthropogenic aerosols is essential to determine their impact. Aerosols are of natural and anthropogenic origin and together constitute a composite aerosol system. Information about either component needs elimination of the other from the composite aerosol system. In the present work we estimated the anthropogenic aerosol fraction (AF) over the Indian region following two different approaches and inter-compared the estimates. We espouse multi-satellite data analysis and model simulations (using the CHIMERE Chemical transport model) to derive natural aerosol distribution, which was subsequently used to estimate AF over the Indian subcontinent. These two approaches are significantly different from each other. Natural aerosol satellite-derived information was extracted in terms of optical depth while model simulations yielded mass concentration. Anthropogenic aerosol fraction distribution was studied over two periods in 2008: premonsoon (March-May) and winter (November-February) in regard to the known distinct seasonality in aerosol loading and type over the Indian region. Although both techniques have derived the same property, considerable differences were noted in temporal and spatial distribution. Satellite retrieval of AF showed maximum values during the pre-monsoon and summer months while lowest values were observed in winter. On the other hand, model simulations showed the highest concentration of AF in winter and the lowest during pre-monsoon and summer months. Both techniques provided an annual average AF of comparable magnitude (similar to 0.43 +/- 0.06 from the satellite and similar to 0.48 +/- 0.19 from the model). For winter months the model-estimated AF was similar to 0.62 +/- 0.09, significantly higher than that (0.39 +/- 0.05) estimated from the satellite, while during pre-monsoon months satellite-estimated AF was similar to 0.46 +/- 0.06 and the model simulation estimation similar to 0.53 +/- 0.14. Preliminary results from this work indicate that model-simulated results are nearer to the actual variation as compared to satellite estimation in view of general seasonal variation in aerosol concentrations.