976 resultados para Spatial Density Dependence


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The prevalence and infestation intensities of Octolasmis lowei in the bronchial chambers of Libinia spinosa were evaluated according to the host's sex, size, and moult condition. Epibionts were classified as cyprid larvae, non-ovigerous or ovigerous according to their developmental stage. A median intensity of infestation of 21 epibionts/host was found (range = 1-644; Q(3) = 81). Epibiont prevalence values (88%) were higher on ovigerous female hosts than on males (55%) or on non-ovigerous females (31%). Intensity of infestation was positively correlated with host size in both sexes for non-ovigerous and ovigerous epibionts. No preference between host sex by cyprid larvae was observed, nor any correlation between cyprid abundance and host size. Cyprid larvae abundance was positively correlated with settled epibionts on both host sexes. The duration of the intermoult phase was the main factor linked to the establishment of sessile epibionts. These observations are important in relation to crabs that have a terminal moult, because these animals cannot eliminate their epibionts in future moults, thus increasing the importance of density-dependent mechanisms on epibiont establishment; in that way, prevalence of infestation alone can underestimate the real impact of infestation on the host's life cycle.

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The importance of networks, in their broad sense, is rapidly and massively growing in modern-day society thanks to unprecedented communication capabilities offered by technology. In this context, the radio spectrum will be a primary resource to be preserved and not wasted. Therefore, the need for intelligent and automatic systems for in-depth spectrum analysis and monitoring will pave the way for a new set of opportunities and potential challenges. This thesis proposes a novel framework for automatic spectrum patrolling and the extraction of wireless network analytics. It aims to enhance the physical layer security of next generation wireless networks through the extraction and the analysis of dedicated analytical features. The framework consists of a spectrum sensing phase, carried out by a patrol composed of numerous radio-frequency (RF) sensing devices, followed by the extraction of a set of wireless network analytics. The methodology developed is blind, allowing spectrum sensing and analytics extraction of a network whose key features (i.e., number of nodes, physical layer signals, medium access protocol (MAC) and routing protocols) are unknown. Because of the wireless medium, over-the-air signals captured by the sensors are mixed; therefore, blind source separation (BSS) and measurement association are used to estimate the number of sources and separate the traffic patterns. After the separation, we put together a set of methodologies for extracting useful features of the wireless network, i.e., its logical topology, the application-level traffic patterns generated by the nodes, and their position. The whole framework is validated on an ad-hoc wireless network accounting for MAC protocol, packet collisions, nodes mobility, the spatial density of sensors, and channel impairments, such as path-loss, shadowing, and noise. The numerical results obtained by extensive and exhaustive simulations show that the proposed framework is consistent and can achieve the required performance.

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Spectroscopic studies of laser -induced plasma from a high-temperature superconducting material, viz., YBa2Cu3O7 (YBCO), have been carried out. Electron temperature and electron density measurements were made from spectral data. The Stark broad ening of emission lines was used to determine the electron density, and the ratio of line in tensities was exploited for the determination of electron temperature. An initial electron temperature of 2.35 eV and electron density of 2.5 3 1017 cm2 3 were observed. The dependence on electron temperature and density on different experimental parameters such as distance from the target, delay time after the in itiation of the plasm a, and laser irradiance is also discussed in detail. Index Headings: Laser -plasma spectroscopy; Plasma diagnostics; Emission spectroscop y; YBa2Cu3O7.

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The effect of increasing population density on the formation of pits, their size and spatial distribution, and on levels of mortality was examined in the antlion Myrmeleon acer Walker. Antlions were kept at densities ranging from 0.4 to 12.8 individuals per 100 cm(2). The distribution of pits was regular or uniform across all densities, but antlions constructed proportionally fewer and smaller pits as density increased. Mortality through cannibalism was very low and only occurred at densities greater than five individuals per 100 cm(2). Antlions in artificially crowded situations frequently relocated their pits and when more space became available, individuals became more dispersed with time. Redistribution of this species results from active avoidance of other antlions and sand throwing associated with pit construction and maintenance, rather than any attempt to optimise prey capture per se.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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One of the criticisms leveled at the model of dispersed city found all over the world is its unarticulated, random, and undifferentiated nature. To check this idea in the Barcelona Metropolitan Region, we estimated the impact of the urban spatial structure (CBD, subcenters and transportation infrastructures) over the population density and commuting distance. The results are unfavorable to the hypothesis of the increasing destructuring of cities given that the explanatory capacity of both functions improves over time, both when other control variables are not included and when they are included.

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BACKGROUND: Body mass index (BMI) may cluster in space among adults and be spatially dependent. Whether BMI clusters among children and how age-specific BMI clusters are related remains unknown. We aimed to identify and compare the spatial dependence of BMI in adults and children in a Swiss general population, taking into account the area's income level. METHODS: Geo-referenced data from the Bus Santé study (adults, n=6663) and Geneva School Health Service (children, n=3601) were used. We implemented global (Moran's I) and local (local indicators of spatial association (LISA)) indices of spatial autocorrelation to investigate the spatial dependence of BMI in adults (35-74 years) and children (6-7 years). Weight and height were measured using standardized procedures. Five spatial autocorrelation classes (LISA clusters) were defined including the high-high BMI class (high BMI participant's BMI value correlated with high BMI-neighbors' mean BMI values). The spatial distributions of clusters were compared between adults and children with and without adjustment for area's income level. RESULTS: In both adults and children, BMI was clearly not distributed at random across the State of Geneva. Both adults' and children's BMIs were associated with the mean BMI of their neighborhood. We found that the clusters of higher BMI in adults and children are located in close, yet different, areas of the state. Significant clusters of high versus low BMIs were clearly identified in both adults and children. Area's income level was associated with children's BMI clusters. CONCLUSIONS: BMI clusters show a specific spatial dependence in adults and children from the general population. Using a fine-scale spatial analytic approach, we identified life course-specific clusters that could guide tailored interventions.

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1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

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We have employed time-dependent local-spin density-functional theory to analyze the multipole spin and charge density excitations in GaAs-AlxGa1-xAs quantum dots. The on-plane transferred momentum degree of freedom has been taken into account, and the wave-vector dependence of the excitations is discussed. In agreement with previous experiments, we have found that the energies of these modes do not depend on the transferred wave vector, although their intensities do. Comparison with a recent resonant Raman scattering experiment [C. Schüller et al., Phys. Rev. Lett. 80, 2673 (1998)] is made. This allows us to identify the angular momentum of several of the observed modes as well as to reproduce their energies

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The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.

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Although the influence of clay mineralogy on soil physical properties has been widely studied, spatial relationships between these features in Alfisols have rarely been examined. The purpose of this work was to relate the clay minerals and physical properties of an Alfisol of sandstone origin in two slope curvatures. The crystallographic properties such as mean crystallite size (MCS) and width at half height (WHH) of hematite, goethite, kaolinite and gibbsite; contents of hematite and goethite; aluminium substitution (AS) and specific surface area (SSA) of hematite and goethite; the goethite/(goethite+hematite) and kaolinite/(kaolinite+gibbsite) ratios; and the citrate/bicarbonate/dithionite extractable Fe (Fe d) were correlated with the soil physical properties through Pearson correlation coefficients and cross-semivariograms. The correlations found between aluminium substitution in goethite and the soil physical properties suggest that the degree of crystallinity of this mineral influences soil properties used as soil quality indicators. Thus, goethite with a high aluminium substitution resulted in large aggregate sizes and a high porosity, and also in a low bulk density and soil penetration resistance. The presence of highly crystalline gibbsite resulted in a high density and micropore content, as well as in smaller aggregates. Interpretation of the cross-semivariogram and classification of landscape compartments in terms of the spatial dependence pattern for the relief-dependent physical and mineralogical properties of the soil proved an effective supplementary method for assessing Pearson correlations between the soil physical and mineralogical properties.

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The spatial correlation between soil properties and weeds is relevant in agronomic and environmental terms. The analysis of this correlation is crucial for the interpretation of its meaning, for influencing factors such as dispersal mechanisms, seed production and survival, and the range of influence of soil management techniques. This study aimed to evaluate the spatial correlation between the physical properties of soil and weeds in no-tillage (NT) and conventional tillage (CT) systems. The following physical properties of soil and weeds were analyzed: soil bulk density, macroporosity, microporosity, total porosity, aeration capacity of soil matrix, soil water content at field capacity, weed shoot biomass, weed density, Commelina benghalensis density, and Bidens pilosa density. Generally, the ranges of the spatial correlations were higher in NT than in CT. The cross-variograms showed that many variables have a structure of combined spatial variation and can therefore be mapped from one another by co-kriging. This combined variation also allows inferences about the physical and biological meanings of the study variables. Results also showed that soil management systems influence the spatial dependence structure significantly.

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Brazilian soils have natural high chemical variability; thus, apparent electrical conductivity (ECa) can assist interpretation of crop yield variations. We aimed to select soil chemical properties with the best linear and spatial correlations to explain ECa variation in the soil using a Profiler sensor (EMP-400). The study was carried out in Sidrolândia, MS, Brazil. We analyzed the following variables: electrical conductivity - EC (2, 7, and 15 kHz), organic matter, available K, base saturation, and cation exchange capacity (CEC). Soil ECa was measured with the aid of an all-terrain vehicle, which crossed the entire area in strips spaced at 0.45 m. Soil samples were collected at the 0-20 cm depth with a total of 36 samples within about 70 ha. Classical descriptive analysis was applied to each property via SAS software, and GS+ for spatial dependence analysis. The equipment was able to simultaneously detect ECa at the different frequencies. It was also possible to establish site-specific management zones through analysis of correlation with chemical properties. We observed that CEC was the property that had the best correlation with ECa at 15 kHz.