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Spatial Correlation (spatial + correlation)
Selected AbstractsASSESSING WHAT LIES BENEATH THE SPATIAL DISTRIBUTION OF A ZOOARCHAEOLOGICAL RECORD: THE USE OF GIS AND SPATIAL CORRELATIONS AT EL MIRÓN CAVE (SPAIN)*ARCHAEOMETRY, Issue 3 2009A. B. MARÍN ARROYO Geographical Information Systems (GIS) are being incorporated into archaeology as a technique to improve the understanding of spatial organization and the relationships among finds within specific areas. Although their use as a basic tool in predicting the location of archaeological sites or in assessing the extent of their catchment areas is relatively common, in general, they have less often been applied to the study of the spatial distribution of archaeological remains within individual deposits, and in particular to faunal assemblages. Despite this, they can prove essential to understanding dispersion and grouping patterns within deposits fully, and, together with various correlation analytical techniques, they provide valuable information about the economic organization of settlements and inhabitant lifeways. To demonstrate the potential of this methodology, a zooarchaeological GIS has been prepared for the Middle and Late Magdalenian and Azilian layers in El Mirón Cave (eastern Cantabria, Spain), and the spatial distribution patterns of various attributes of the archaeological record have been analysed. Significant conclusions in terms of type and duration of human occupation have been drawn. [source] Testing for Spatial Correlation in Nonstationary Binary Data, with Application to Aberrant Crypt Foci in Colon CarcinogenesisBIOMETRICS, Issue 4 2003Tatiyana V. Apanasovich Summary. In an experiment to understand colon carcinogenesis, all animals were exposed to a carcinogen, with half the animals also being exposed to radiation. Spatially, we measured the existence of what are referred to as aberrant crypt foci (ACF), namely, morphologically changed colonic crypts that are known to be precursors of colon cancer development. The biological question of interest is whether the locations of these ACFs are spatially correlated: if so, this indicates that damage to the colon due to carcinogens and radiation is localized. Statistically, the data take the form of binary outcomes (corresponding to the existence of an ACF) on a regular grid. We develop score-type methods based upon the Matern and conditionally autoregressive (CAR) correlation models to test for the spatial correlation in such data, while allowing for nonstationarity. Because of a technical peculiarity of the score-type test, we also develop robust versions of the method. The methods are compared to a generalization of Moran's test for continuous outcomes, and are shown via simulation to have the potential for increased power. When applied to our data, the methods indicate the existence of spatial correlation, and hence indicate localization of damage. [source] Spatial correlations of Diceroprocta apache and its host plants: evidence for a negative impact from Tamarix invasionECOLOGICAL ENTOMOLOGY, Issue 1 2002Aaron R. Ellingson Abstract 1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m. 2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected. 3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture. 4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies. [source] Rodents, plants, and precipitation: spatial and temporal dynamics of consumers and resourcesOIKOS, Issue 3 2000S. K. Morgan Ernest Resource/consumer dynamics are potentially mediated by both limiting resources and biotic interactions. We examined temporal correlations between precipitation, plant cover, and rodent density, with varying time lags using long-term data from two sites in the Chihuahuan desert of North America: the Sevilleta Long-term Ecological Research site (LTER), New Mexico, USA and a site near Portal, Arizona, USA. We also calculated the spatial correlations in precipitation, plant cover, and rodent dynamics among six sites, five at Sevilleta and one at Portal. At Sevilleta, all three variables were temporally correlated, with plant cover responding to precipitation during the same growing season and rodent populations lagging at least one season behind. At Portal, plant stem count was also correlated with precipitation during the same growing season, but there was no significant correlation between rodents and either precipitation or plant growth. Spatial correlations in plant cover and rodent populations between sites reflected the localized nature of summer rainfall, so that sites with highly correlated summer precipitation exhibited higher correlations in plant cover and rodent populations. In general, our results indicate that limiting resources influence consumer dynamics, but these dynamics also depend crucially on the biotic interactions in the system. [source] Local Structure and Thermodynamics of a Core-Softened Potential Fluid: Theory and SimulationCHEMPHYSCHEM, Issue 1 2007Shiqi Zhou Dr. Abstract Phase behavior and structural properties of homogeneous and inhomogeneous core-softened (CS) fluid consisting of particles interacting via the potential, which combines the hard-core repulsion and double attractive well interaction, are investigated. The vapour,liquid coexistence curves and critical points for various interaction ranges of the potential are determined by discrete molecular dynamics simulations to provide guidance for the choice of the bulk density and potential parameters for the study of homogeneous and inhomogeneous structures. Spatial correlations in the homogeneous CS system are studied by the Ornstein-Zernike integral equation in combination with the modified hypernetted chain (MHNC) approximation. The local structure of CS fluid subjected to diverse external fields maintaining the equilibrium with the bulk CS fluid are studied on the basis of a recently proposed third order+second order perturbation density functional approximation (DFA). The accuracy of DFA predictions is tested against the results of a grand canonical ensemble Monte Carlo simulation. Reasonable agreement between the results of both methods proves that the DFA theory applied in this work is a convenient theoretical tool for the investigation of the CS fluid, which is practically applicable for modeling numerous real systems. [source] Metapopulation Extinction Risk under Spatially Autocorrelated DisturbanceCONSERVATION BIOLOGY, Issue 2 2005A. S. KALLIMANIS patrón espacial de perturbación; simulaciones espacialmente explícitas; SLOSS; umbral de extinción Abstract:,Recent extinction models generally show that spatial aggregation of habitat reduces overall extinction risk because sites emptied by local extinction are more rapidly recolonized. We extended such an investigation to include spatial structure in the disturbance regime. A spatially explicit metapopulation model was developed with a wide range of dispersal distances. The degree of aggregation of both habitat and disturbance pattern could be varied from a random distribution, through the intermediate case of a fractal distribution, all the way to complete aggregation (single block). Increasing spatial aggregation of disturbance generally increased extinction risk. The relative risk faced by populations in different landscapes varied greatly, depending on the disturbance regime. With random disturbance, the spatial aggregation of habitat reduced extinction risk, as in earlier studies. Where disturbance was spatially autocorrelated, however, this advantage was eliminated or reversed because populations in aggregated habitats are at risk of mass extinction from coarse-scale disturbance events. The effects of spatial patterns on extinction risk tended to be reduced by long-distance dispersal. Given the high levels of spatial correlation in natural and anthropogenic disturbance processes, population vulnerability may be greatly underestimated both by classical (nonspatial) models and by those that consider spatial structure in habitat alone. Resumen:,Los modelos recientes de extinción generalmente muestran que la agregación espacial de hábitat reduce el riesgo de extinción debido a una recolonización más rápida de sitios vacíos por extinción local. Extendimos la investigación para incluir la estructura espacial en el régimen de perturbación. Desarrollamos un modelo metapoblacional espacialmente explícito en el que el patrón espacial tanto del hábitat como de los regímenes de perturbación podía variar aleatoriamente de fractal a completamente agregado (bloque) y con una amplia gama de distancias de dispersión. El incremento de la agregación espacial de la perturbación generalmente incrementó el riesgo de extinción. El riesgo relativo que enfrentan poblaciones en paisajes diferentes fue muy variable, dependiendo del régimen de perturbación. Con perturbación aleatoria, la agregación espacial de hábitat redujo el riesgo de extinción, como en estudios anteriores. Sin embargo, cuando la perturbación estaba autocorrelacionada espacialmente, esta ventaja se eliminaba o invertía debido a que las poblaciones en hábitats agregados están en riesgo de extinción masiva por eventos perturbadores a escala gruesa. Los efectos de patrones espaciales sobre el riesgo de extinción tendieron a reducirse por la dispersión de larga distancia. Debido a los altos niveles de correlación espacial en los procesos naturales y humanos de perturbación, la vulnerabilidad puede estar enormemente subestimada tanto por modelos clásicos (no espaciales) como por los que sólo consideran la estructura espacial del habitat. Los modelos que consideran la estructura espacial del hábitat solo subestiman el riesgo en comparación con modelos que consideran la estructura especial de la perturbación. [source] Patterns of spatial autocorrelation of assemblages of birds, floristics, physiognomy, and primary productivity in the central Great Basin, USADIVERSITY AND DISTRIBUTIONS, Issue 3 2006Erica Fleishman ABSTRACT We fitted spatial autocorrelation functions to distance-based data for assemblages of birds and for three attributes of birds' habitats at 140 locations, separated by up to 65 km, in the Great Basin (Nevada, USA). The three habitat characteristics were taxonomic composition of the vegetation, physical structure of the vegetation, and a measure of primary productivity, the normalized difference vegetation index, estimated from satellite imagery. We found that a spherical model was the best fit to data for avifaunal composition, vegetation composition, and primary productivity, but the distance at which spatial correlation effectively was zero differed substantially among data sets (c. 30 km for birds, 20 km for vegetation composition, and 60 km for primary productivity). A power-law function was the best fit to data for vegetation structure, indicating that the structure of vegetation differed by similar amounts irrespective of distance between locations (up to the maximum distance measured). Our results suggested that the spatial structure of bird assemblages is more similar to vegetation composition than to either vegetation structure or primary productivity, but is autocorrelated over larger distances. We believe that the greater mobility of birds compared with plants may be responsible for this difference. [source] Multi-scale system reliability analysis of lifeline networks under earthquake hazardsEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 3 2010Junho Song Abstract Recent earthquake events evidenced that damage of structural components in a lifeline network may cause prolonged disruption of lifeline services, which eventually results in significant socio-economic losses in the affected area. Despite recent advances in network reliability analysis, the complexity of the problem and various uncertainties still make it a challenging task to evaluate the post-hazard performance and connectivity of lifeline networks efficiently and accurately. In order to overcome such challenges and take advantage of merits of multi-scale analysis, this paper develops a multi-scale system reliability analysis method by integrating a network decomposition approach with the matrix-based system reliability (MSR) method. In addition to facilitating system reliability analysis of large-size networks, the multi-scale approach enables optimizing the level of computational effort on subsystems; identifying the relative importance of components and subsystems at multiple scales; and providing a collaborative risk management framework. The MSR method is uniformly applied for system reliability analyses at both the lower-scale (for link failure) and the higher-scale (for system connectivity) to obtain the probability of general system events, various conditional probabilities, component importance measures, statistical correlation between subsystem failures and parameter sensitivities. The proposed multi-scale analysis method is demonstrated by its application to a gas distribution network in Shelby County of Tennessee. A parametric study is performed to determine the number of segments during the lower-scale MSR analysis of each pipeline based on the strength of the spatial correlation of seismic intensity. It is shown that the spatial correlation should be considered at both scales for accurate reliability evaluation. The proposed multi-scale analysis approach provides an effective framework of risk assessment and decision support for lifeline networks under earthquake hazards. Copyright © 2009 John Wiley & Sons, Ltd. [source] Correlation model for spatially distributed ground-motion intensitiesEARTHQUAKE ENGINEERING AND STRUCTURAL DYNAMICS, Issue 15 2009Nirmal Jayaram Abstract Risk assessment of spatially distributed building portfolios or infrastructure systems requires quantification of the joint occurrence of ground-motion intensities at several sites, during the same earthquake. The ground-motion models that are used for site-specific hazard analysis do not provide information on the spatial correlation between ground-motion intensities, which is required for the joint prediction of intensities at multiple sites. Moreover, researchers who have previously computed these correlations using observed ground-motion recordings differ in their estimates of spatial correlation. In this paper, ground motions observed during seven past earthquakes are used to estimate correlations between spatially distributed spectral accelerations at various spectral periods. Geostatistical tools are used to quantify and express the observed correlations in a standard format. The estimated correlation model is also compared with previously published results, and apparent discrepancies among the previous results are explained. The analysis shows that the spatial correlation reduces with increasing separation between the sites of interest. The rate of decay of correlation typically decreases with increasing spectral acceleration period. At periods longer than 2,s, the correlations were similar for all the earthquake ground motions considered. At shorter periods, however, the correlations were found to be related to the local-site conditions (as indicated by site Vs30 values) at the ground-motion recording stations. The research work also investigates the assumption of isotropy used in developing the spatial correlation models. It is seen using the Northridge and Chi-Chi earthquake time histories that the isotropy assumption is reasonable at both long and short periods. Based on the factors identified as influencing the spatial correlation, a model is developed that can be used to select appropriate correlation estimates for use in practical risk assessment problems. Copyright © 2009 John Wiley & Sons, Ltd. [source] Regularity of species richness relationships to patch size and shapeECOGRAPHY, Issue 4 2007Einar Heegaard This study aims to assess the degree of regularity in the effect of patch size and patch shape on plant species richness across a macroscale region, and to evaluate the implications for nature conservation. Our study area covers south-eastern Norway and contains 16 agricultural landscapes with 2162 patches. To analyse regularity a local linear mixed model (LLMM) was applied. This procedure estimates the richness trends due to shared effects of size and shape, and simultaneously provides the landscape-specific random effect. The latter is a direct estimate of the degree of irregularity between the landscapes, conditioned on specific values of size and shape. The results show a positive interaction between the shape and size of patches, which is repeated for all landscapes. The shape of the patches produces more regular patterns in species richness than the size of patches. This we attribute to effects of dispersal and distance to neighbouring patches of different environmentally conditioned species pools. Large and complex patches have shorter average distance to neighbouring patches (of different types) than large simple-shaped (circular) patches have. We attribute the higher species richness of the former, given a similar area, to a higher number of species dispersed from the outside into the more complex plot. For small patches, however, the distance to the edge is short relative to normal dispersal distances, for patches of all shapes. This explains why the positive effect of shape complexity on species richness is stronger for large patches. This interpretation is supported by a strong spatial correlation conditioned on the most complex patches. Theories of dynamics in biodiversity in patchy landscapes must consider shape as a regulator at the same level as size, and both shape and size of patches should be simultaneously taken into account for management planning. [source] Comparison of missing value imputation methods for crop yield dataENVIRONMETRICS, Issue 4 2006Ravindra S. Lokupitiya Abstract Most ecological data sets contain missing values, a fact which can cause problems in the analysis and limit the utility of resulting inference. However, ecological data also tend to be spatially correlated, which can aid in estimating and imputing missing values. We compared four existing methods of estimating missing values: regression, kernel smoothing, universal kriging, and multiple imputation. Data on crop yields from the National Agricultural Statistical Survey (NASS) and the Census of Agriculture (Ag Census) were the basis for our analysis. Our goal was to find the best method to impute missing values in the NASS datasets. For this comparison, we selected the NASS data for barley crop yield in 1997 as our reference dataset. We found in this case that multiple imputation and regression were superior to methods based on spatial correlation. Universal kriging was found to be the third best method. Kernel smoothing seemed to perform very poorly. Copyright © 2005 John Wiley & Sons, Ltd. [source] Systematic sample design for the estimation of spatial meansENVIRONMETRICS, Issue 1 2003Luis Ambrosio Flores Abstract This article develops a practical approach to undertaking systematic sampling for the estimation of the spatial mean of an attribute in a selected area. A design-based approach is used to estimate population parameters, but it is combined with elements of a model-based approach in order to identify the spatial correlation structure, to evaluate the relative efficiency of the sample mean under simple random and systematic sampling, to estimate sampling error and to assess the sample size needed in order to achieve a desired level of precision. Using two case studies (land use estimation and weed seedbank in soil) it is demonstrated how the practical basis for the design of systematic samples provided in this work should be applied and it is shown that if the spatial correlation is ignored the sampling error of the sample mean and the sample size needed in order to achieve a desired level of precision with systematic sampling are overestimated. Copyright © 2003 John Wiley & Sons, Ltd. [source] Contending with space,time interaction in the spatial prediction of pollution: Vancouver's hourly ambient PM10 fieldENVIRONMETRICS, Issue 5-6 2002Jim Zidek Abstract In this article we describe an approach for predicting average hourly concentrations of ambient PM10 in Vancouver. We know our solution also applies to hourly ozone fields and believe it may be quite generally applicable. We use a hierarchical Bayesian approach. At the primary level we model the logarithmic field as a trend model plus Gaussian stochastic residual. That trend model depends on hourly meteorological predictors and is common to all sites. The stochastic component consists of a 24-hour vector response that we model as a multivariate AR(3) temporal process with common spatial parameters. Removing the trend and AR structure leaves ,whitened' time series of vector series. With this approach (as opposed to using 24 separate univariate time series models), there is little loss of spatial correlation in these residuals compared with that in just the detrended residuals (prior to removing the AR component). Moreover our multivariate approach enables predictions for any given hour to ,borrow strength' through its correlation with adjoining hours. On this basis we develop a spatial predictive distribution for these residuals at unmonitored sites. By transforming the predicted residuals back to the original data scales we can impute Vancouver's hourly PM10 field. Copyright © 2002 John Wiley & Sons, Ltd. [source] Factors influencing the spatial distribution of zooplankton and fish in Loch Ness, UKFRESHWATER BIOLOGY, Issue 4 2000D. G. George Summary 1The vertical and horizontal distribution of phytoplankton, zooplankton and fish in Loch Ness, Scotland, were monitored during one day-time and one night-time survey in July 1992. The vertical samples were collected at a site located at the northern end of the loch and the horizontal samples along a longitudinal transect. 2The vertical distribution surveys demonstrated that the phytoplankton, the zooplankton and the fish were concentrated in the top 30 m of water above the seasonal thermocline. Within this layer, Cyclops stayed much closer to the surface than Eudiaptomus but both species moved towards the surface at night. 3The most important factor influencing the horizontal distribution of the phytoplankton was the north- south gradient in productivity. The sub-catchments surrounding the north basin contain a greater proportion of arable land than those to the south and the concentrations of nitrate-nitrogen and phytoplankton chlorophyll increased systematically from south to north. 4Zooplankton distribution patterns were influenced by wind-induced water movements and the dispersion of allochthonous material from the main inflows. The highest concentrations of Cyclops were recorded in the north, where there was more phytoplankton, and the highest concentrations of Eudiaptomus in the south, where there were higher concentrations of non-algal particulates. 5There was no spatial correlation between total zooplankton and total fish abundance but the highest concentrations of small (1,5 cm) fish were recorded in the south where there was a large patch of Eudiaptomus. The number of Eudiaptomus at specific locations within this patch were, however, negatively correlated with the numbers of small fish. These results suggest that the fish were actively foraging within the patch and were depleting their zooplankton prey in the areas where they were most abundant. [source] Microglial dystrophy in the aged and Alzheimer's disease brain is associated with ferritin immunoreactivityGLIA, Issue 10 2008Kryslaine O. Lopes Abstract Degeneration of microglial cells may be important for understanding the pathogenesis of aging-related neurodegeneration and neurodegenerative diseases. In this study, we analyzed the morphological characteristics of microglial cells in the nondemented and Alzheimer's disease (AD) human brain using ferritin immunohistochemistry. The central hypothesis was that expression of the iron storage protein ferritin increases the susceptibility of microglia to degeneration, particularly in the aged brain since senescent microglia might become less efficient in maintaining iron homeostasis and free iron can promote oxidative damage. In a primary set of 24 subjects (age range 34,97 years) examined, microglial cells immunoreactive for ferritin were found to constitute a subpopulation of the larger microglial pool labeled with an antibody for HLA-DR antigens. The majority of these ferritin-positive microglia exhibited aberrant morphological (dystrophic) changes in the aged and particularly in the AD brain. No spatial correlation was found between ferritin-positive dystrophic microglia and senile plaques in AD tissues. Analysis of a secondary set of human postmortem brain tissues with a wide range of postmortem intervals (PMI, average 10.94 ± 5.69 h) showed that the occurrence of microglial dystrophy was independent of PMI and consequently not a product of tissue autolysis. Collectively, these results suggest that microglial involvement in iron storage and metabolism contributes to their degeneration, possibly through increased exposure of the cells to oxidative stress. We conclude that ferritin immunohistochemistry may be a useful method for detecting degenerating microglia in the human brain. © 2008 Wiley-Liss, Inc. [source] Detection of trends in annual extreme rainfallHYDROLOGICAL PROCESSES, Issue 18 2003Kaz Adamowski Abstract Information on intensity,duration,frequency of rainfall is commonly required for a variety of hydrologic applications. In this study, trends are estimated for different durations of annual extreme rainfall using the regional average Mann,Kendall S trend test. The method of L-moments was employed to delineate homogeneous regions. The trend test was modified to account for observed autocorrelation, and a bootstrap methodology was used to account for the observed spatial correlation. Numerical analysis was performed on 44 rainfall stations from the province of Ontario, Canada, for a 20 year time frame. This was done using data from homogeneous regions established using the L-moments procedure for the annual maximum observations for the following durations: 5, 10, 15 and 30 min, and 1, 2, 6 and 12 h. Depending on different rainfall durations, four or five homogeneous regions were delineated. Based on a 5% significance level, approximately 23% of the regions tested had a significant trend, predominantly for short-duration storms. Serial dependency was observed in 2·3% of data sets and spatial correlation was found in 18% of the regions. The presence of serial and spatial correlation had a significant impact on trend determination. Copyright © 2003 John Wiley & Sons, Ltd. [source] Characteristics of preferential flow and groundwater discharge to Shingobee Lake, Minnesota, USAHYDROLOGICAL PROCESSES, Issue 10 2002Hans F. Kishel Abstract Small-scale heterogeneities and large changes in hydraulic gradient over short distances can create preferential groundwater flow paths that discharge to lakes. A 170 m2 grid within an area of springs and seeps along the shore of Shingobee Lake, Minnesota, was intensively instrumented to characterize groundwater-lake interaction within underlying organic-rich soil and sandy glacial sediments. Seepage meters in the lake and piezometer nests, installed at depths of 0·5 and 1·0 m below the ground surface and lakebed, were used to estimate groundwater flow. Statistical analysis of hydraulic conductivity estimated from slug tests indicated a range from 21 to 4·8 × 10,3 m day,1 and small spatial correlation. Although hydraulic gradients are overall upward and toward the lake, surface water that flows onto an area about 2 m onshore results in downward flow and localized recharge. Most flow occurred within 3 m of the shore through more permeable pathways. Seepage meter and Darcy law estimates of groundwater discharge agreed well within error limits. In the small area examined, discharge decreases irregularly with distance into the lake, indicating that sediment heterogeneity plays an important role in the distribution of groundwater discharge. Temperature gradients showed some relationship to discharge, but neither temperature profiles nor specific electrical conductance could provide a more convenient method to map groundwater,lake interaction. These results suggest that site-specific data may be needed to evaluate local water budget and to protect the water quality and quantity of discharge-dominated lakes. Copyright © 2002 John Wiley & Sons, Ltd. [source] Empirical orthogonal functions and related techniques in atmospheric science: A reviewINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 9 2007A. Hannachi Abstract Climate and weather constitute a typical example where high dimensional and complex phenomena meet. The atmospheric system is the result of highly complex interactions between many degrees of freedom or modes. In order to gain insight in understanding the dynamical/physical behaviour involved it is useful to attempt to understand their interactions in terms of a much smaller number of prominent modes of variability. This has led to the development by atmospheric researchers of methods that give a space display and a time display of large space-time atmospheric data. Empirical orthogonal functions (EOFs) were first used in meteorology in the late 1940s. The method, which decomposes a space-time field into spatial patterns and associated time indices, contributed much in advancing our knowledge of the atmosphere. However, since the atmosphere contains all sorts of features, e.g. stationary and propagating, EOFs are unable to provide a full picture. For example, EOFs tend, in general, to be difficult to interpret because of their geometric properties, such as their global feature, and their orthogonality in space and time. To obtain more localised features, modifications, e.g. rotated EOFs (REOFs), have been introduced. At the same time, because these methods cannot deal with propagating features, since they only use spatial correlation of the field, it was necessary to use both spatial and time information in order to identify such features. Extended and complex EOFs were introduced to serve that purpose. Because of the importance of EOFs and closely related methods in atmospheric science, and because the existing reviews of the subject are slightly out of date, there seems to be a need to update our knowledge by including new developments that could not be presented in previous reviews. This review proposes to achieve precisely this goal. The basic theory of the main types of EOFs is reviewed, and a wide range of applications using various data sets are also provided. Copyright © 2007 Royal Meteorological Society [source] Application of independent component analysis with mixture density model to localize brain alpha activity in fMRI and EEGINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 4 2004Jeong-Won Jeong Abstract Independent component analysis (ICA) is an approach to solve the blind source separation problem. In the original and extended versions of ICA, nonlinearity functions are fixed to have specific density forms such as super-Gaussian or sub-Gaussian, thereby limiting their performance when sources with different classes of densities are mixed in multichannel data. In this article, we have incorporated a mixture density model such that no assumption about source density would be required. We show that this leads to better source separation due to increased flexibility in handling source- densities with flexible parametric nonlinearity. The algorithm was validated through simulation studies and its performance was compared to other versions of ICA. The modified mixture density ICA was then applied to functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data to localize independent sources of alpha activity in the human brain. A good spatial correlation was found in the spatial distribution of alpha sources derived independently from fMRI and EEG, suggesting that spontaneous alpha rhythm can be imaged by fMRI using ICA without concurrent acquisition of EEG. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 170,180, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20021 [source] Spatiotemporal Correlation Between Phase Singularities and Wavebreaks During Ventricular FibrillationJOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, Issue 10 2003YEN-BIN LIU M.D. Introduction: Phase maps and the detection of phase singularities (PSs) have become a well-developed method for characterizing the organization of ventricular fibrillation (VF). How precisely PS colocalizes with wavebreak (WB) during VF, however, is unknown. Methods and Results: We performed optical mapping of 27 episodes of VF in nine Langendorff-perfused rabbit hearts. A WB is a point where the activation wavefront and the repolarization waveback meet. A PS is a site where its phase is ambiguous and its neighboring pixels exhibit a continuous phase progression from ,, to +,. The correlation coefficient between the number of WBs and PSs was 0.78 ± 0.09 for each heart and 0.81 for all VF episodes (P < 0.001), indicating a significant temporal correlation. We then superimposed the WBs and PSs for every 100 frames of each episode. These maps showed a high degree of spatial colocalization. To quantify spatial colocalization, the spatial shifts between the cumulative maps of WBs and PSs in corresponding frames were calculated by automatic alignment to obtain maximum overlap between these two maps. The spatial shifts were 0.04 ± 0.31 mm on the x-axis and 0.06 ± 0.27 mm on the y-axis over a 20 × 20 mm2 mapped field, indicating highly significant spatial correlation. Conclusion: Phase mapping provides a convenient and robust approach to quantitatively describe wave propagation and organization during VF. The close spatiotemporal correlation between PSs and WBs establishes that PSs are a valid alternate representation of WB during VF and further validated the use of phase mapping in the study of VF dynamics. (J Cardiovasc Electrophysiol, Vol. 14, pp. 1103-1109, October 2003) [source] Spatial distribution of populations of solitarious adult desert locust (Schistocerca gregaria Forsk.) on the coastal plain of SudanAGRICULTURAL AND FOREST ENTOMOLOGY, Issue 3 2004Gebremedhin Woldewahid Abstract 1,Densities of solitarious adult desert locusts were measured on regular grids of up to 126 sample sites in the southern part of the coastal plain of Sudan during the winters of 1999/2000 and 2000/2001. Geostatistical procedures were used to characterize spatial dependence of locust density, to evaluate the possibility of estimating locust densities at unvisited sites, based on information obtained at surveyed sites, and to create density maps. 2,Sample variograms indicate that population densities were spatially correlated over ranges from 5 to 24 km. The range of spatial correlation decreased as dry conditions towards the end of the rainy season concentrated the locusts in contracting areas of sufficient humidity and availability of green vegetation. The rather small ranges of spatial correlation indicate that sampling needs to be conducted at a refined scale (< 24 km between sample points) to avoid missing hot spots of desert locust. 3,Locust densities were highly correlated with cover abundance of the wild plant Heliotropium arbainense and cultivated millet, Pennisetum typhoidum. The association of locusts with these host plants can be used to target sampling and enhance detection chance. 4,The relationship between sampling intensity and kriging variance was explored. Implications for monitoring of desert locust are discussed. [source] Spatial variability of O layer thickness and humus forms under different pine beech,forest transformation stages in NE GermanyJOURNAL OF PLANT NUTRITION AND SOIL SCIENCE, Issue 1 2006Oliver Bens Abstract Spatial variability of humus layer (O layer) thicknesses can have important impacts upon soil water dynamics, nutrient storage and availability, as well as plant growth. The purpose of the present study was to elucidate the impact of forest-transformation practices on the spatial variability of O layer thicknesses. The study focused on the Kahlenberg forest area (NE Germany) with stands of Scots pine (Pinus sylvestris) and European beech (Fagus sylvatica) of different age structures that form a transformation chronosequence from pure Scots pine stands towards pure European beech stands. Topsoil profiles including both, the O layer and the uppermost humic mineral soil horizon were excavated at intervals of 0.4 m along 15,20 m long transects, and spatial variability of O layer thicknesses was quantified by variogram analysis. The correlation lengths of total O layer thickness increased in the sequence consisting of pure pine stand (3.1 m) , older mixed stand (3.7 m) , pure beech stand (4.5 m), with the exception of the younger mixed stand, for which no correlation lengths of total O layer thickness could be determined. The degree of spatial correlation, i.e., the percentage of the total variance which can be described by variograms, was highest for the two monospecies stands, whereas this percentage was distinctly lower for the two mixed stands. A similar minimum for the two mixed stands was observed for the correlation lengths of the Oh horizon. These results suggest that the spatial structures of forest-transformation stands may be interpreted in terms of a disturbance (in the form of the underplanting of beech trees). After this disturbance, the forest ecosystem requires at least 100 y to again reach relative equilibrium. These findings are in line with the results of other soil-related investigations at these sites. Räumliche Variabilität der Humuslagenmächtigkeit und Humusformen in verschiedenen Stadien des Waldumbaus von Kiefer zu Buche in NO-Deutschland Die räumliche Variabilität der Humusauflagenmächtigkeit kann einen bedeutenden Einfluss auf die Bodenwasserdynamik, Nährstoffspeicherung und -verfügbarkeit sowie das Pflanzenwachstum haben. Ziel dieser Studie war es, die Auswirkungen von Waldumbaumaßnahmen auf die räumliche Verteilung der Auflagehumusmächtigkeiten zu untersuchen. Im Forstrevier Kahlenberg, mit Beständen von Kiefer (Pinus sylvestris) und Buche (Fagus sylvatica) unterschiedlichen Alters, welche eine Transformations-Chronosequenz von einem Kiefern-Reinbestand hin zu einem reinen Buchenbestand darstellen, wurden Humusprofile entlang von 15,20 m langen Transekten in Abständen von 0,4 m aufgenommen. Die räumliche Variabilität der Mächtigkeiten der Auflagehumushorizonte wurde durch Variogramm-Analysen quantifiziert. Die Korrelationslängen der Mächtigkeiten des gesamten Auflagehumus stiegen in der Reihenfolge reiner Kiefernbestand (3,1 m) , älterer Mischbestand (3,7 m) , reiner Buchenbestand (4,5 m) an. Aus dieser Reihe fällt der jüngere Mischbestand heraus; für ihn konnten keine Korrelationslängen ermittelt werden. Der Grad der räumlichen Korrelation, d. h. der Anteil der gesamten Varianz, der durch Variogramme beschrieben wird, ist für die beiden Reinbestände am höchsten, während er für die beiden Mischbestände deutlich geringer ist. Ein ähnliches Minimum für die beiden Mischbestände ergibt sich, wenn nur die Korrelationslängen der Oh-Mächtigkeiten betrachtet werden. Diese Ergebnisse deuten darauf hin, dass die räumlichen Strukturen von Waldumbaubeständen im Sinne einer Störung gedeutet werden können (wobei die Umbaumaßnahme und der Unterbau mit Buchen die Störung darstellt). Diese Störung dauert offenbar mindestens 100 a an. Dieser Befund stimmt mit den Ergebnissen aus Studien zu weiteren relevanten Bodeneigenschaften an Forststandorten im nordostdeutschen Tiefland überein. [source] RAINGAGE NETWORK DESIGN USING NEXRAD PRECIPITATION ESTIMATES,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 5 2002A. Allen Bradley ABSTRACT: A general framework is proposed for using precipitation estimates from NEXRAD weather radars in raingage network design. NEXRAD precipitation products are used to represent space time rainfall fields, which can be sampled by hypothetical raingage networks. A stochastic model is used to simulate gage observations based on the areal average precipitation for radar grid cells. The stochastic model accounts for subgrid variability of precipitation within the cell and gage measurement errors. The approach is ideally suited to raingage network design in regions with strong climatic variations in rainfall where conventional methods are sometimes lacking. A case study example involving the estimation of areal average precipitation for catchments in the Catskill Mountains illustrates the approach. The case study shows how the simulation approach can be used to quantify the effects of gage density, basin size, spatial variation of precipitation, and gage measurement error, on network estimates of areal average precipitation. Although the quality of NEXRAD precipitation products imposes limitations on their use in network design, weather radars can provide valuable information for empirical assessment of rain-gage network estimation errors. Still, the biggest challenge in quantifying estimation errors is understanding subgrid spatial variability. The results from the case study show that the spatial correlation of precipitation at subgrid scales (4 km and less) is difficult to quantify, especially for short sampling durations. Network estimation errors for hourly precipitation are extremely sensitive to the uncertainty in subgrid spatial variability, although for storm total accumulation, they are much less sensitive. [source] Combining evidence on air pollution and daily mortality from the 20 largest US cities: a hierarchical modelling strategyJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 3 2000Francesca Dominici Reports over the last decade of association between levels of particles in outdoor air and daily mortality counts have raised concern that air pollution shortens life, even at concentrations within current regulatory limits. Criticisms of these reports have focused on the statistical techniques that are used to estimate the pollution,mortality relationship and the inconsistency in findings between cities. We have developed analytical methods that address these concerns and combine evidence from multiple locations to gain a unified analysis of the data. The paper presents log-linear regression analyses of daily time series data from the largest 20 US cities and introduces hierarchical regression models for combining estimates of the pollution,mortality relationship across cities. We illustrate this method by focusing on mortality effects of PM10 (particulate matter less than 10 ,m in aerodynamic diameter) and by performing univariate and bivariate analyses with PM10 and ozone (O3) level. In the first stage of the hierarchical model, we estimate the relative mortality rate associated with PM10 for each of the 20 cities by using semiparametric log-linear models. The second stage of the model describes between-city variation in the true relative rates as a function of selected city-specific covariates. We also fit two variations of a spatial model with the goal of exploring the spatial correlation of the pollutant-specific coefficients among cities. Finally, to explore the results of considering the two pollutants jointly, we fit and compare univariate and bivariate models. All posterior distributions from the second stage are estimated by using Markov chain Monte Carlo techniques. In univariate analyses using concurrent day pollution values to predict mortality, we find that an increase of 10 ,g m -3 in PM10 on average in the USA is associated with a 0.48% increase in mortality (95% interval: 0.05, 0.92). With adjustment for the O3 level the PM10 -coefficient is slightly higher. The results are largely insensitive to the specific choice of vague but proper prior distribution. The models and estimation methods are general and can be used for any number of locations and pollutant measurements and have potential applications to other environmental agents. [source] The Air is Always Cleaner on the Other Side: Race, Space, and Ambient Air Toxics Exposures in CaliforniaJOURNAL OF URBAN AFFAIRS, Issue 2 2005Manuel Pastor Jr. This article uses U.S. EPA's National Air Toxics Assessment (NATA) for 1996 to examine environmental inequality in California, a state that has been a recent innovator in environmental justice policy. We first estimate potential lifetime cancer risks from mobile and stationary sources. We then consider the distribution of these risks using both simple comparisons and a multivariate model in which we control for income, land use, and other explanatory factors, as well as spatial correlation. We find large racial disparities in California's "riskscape" as well as inequalities by other factors and suggest several implications for environmental and land use policy. [source] Environmental colour intensifies the Moran effect when population dynamics are spatially heterogeneousOIKOS, Issue 10 2007David A. Vasseur Evidence for synchronous fluctuations of spatially separated populations is ubiquitous in the literature, including accounts within and across taxa. Among the few mechanisms explaining this phenomenon is the Moran effect, whereby independent populations are synchronized by spatially correlated environmental disturbances. The body of research on the Moran effect predominantly assumes that environmental disturbances within a local site are serially uncorrelated; that is, successive observations in time at a particular local site are independent. Yet, many environmental variables are known to possess strong temporal autocorrelation , a character which has often been described as ,colour'. The omission of environmental colour from research on the Moran effect may be due in part to the lack of methods capable of generating sets of time series with a desired colour and spatial correlation. Here I present a novel and simple method designated as ,phase partnering' to generate such sets of time series and I investigate the combined impact of spatial correlation and environmental colour on population synchrony in two common models of population dynamics. For linear population dynamics, and for a subset of nonlinear population dynamics, coloured environments intensify the Moran effect when population dynamics are spatially heterogeneous; in coloured environments the spatial correlation between populations more closely mimics the spatial correlation between their respective environments. Given that most environmental variables are coloured, these results imply that the Moran effect may be a far more significant driver of regional-scale population and interspecific synchrony than is currently believed. [source] Evidence for hyperparasitism of coffee rust (Hemileia vastatrix) by the entomogenous fungus, Lecanicillium lecanii, through a complex ecological webPLANT PATHOLOGY, Issue 4 2009J. Vandermeer The entomogenous fungus, Lecanicillium lecanii is hyperparasitic on Hemileia vastatrix, the cause of coffee leaf rust in the laboratory, and has frequently been observed attacking it in the field. The existence of a complex ecological web involving the spatially clustered mutualism of an ant (Azteca instabilis) with a scale insect (Coccus viridis), where the scale insect was infected by L. lecanii, prompted a search for a spatial correlation between the attack of L. lecanii on the scale insect and the incidence of rust in a commercial coffee crop. A weak but statistically significant effect of hyperparasitic control of coffee rust was observed on two distinct scales: in a 45-ha plot and on a scale of approximately 10 m. It was concluded that this effect was linked to an indirect effect of the ant,coccid mutualism, where L. lecanii was a parasite of the coccid. [source] Spatial scale of GIS-derived categorical variables affects their ability to separate sites by community compositionAPPLIED VEGETATION SCIENCE, Issue 3 2008Emily A. Holt Abstract. Questions: How well do GIS-derived categorical variables (e.g., vegetation, soils, geology, elevation, geography, and physiography) separate plots based on community composition? How does the ability to distinguish plots by community composition vary with spatial scale, specifically number of patch types, patch size and spatial correlation? Both these questions bear on the effective use of stratifying variables in landscape ecology. Location: Arctic tundra; Bering Land Bridge National Preserve, northwestern Alaska, USA. Methods: We evaluated the strength of numerous alternative stratifying variables using the multi-response permutation procedure (MRPP). We also created groups based on lichen community composition, using cluster analyses, and evaluated the relationship between these groups and groupings within categorical variables using Mantel tests. Each test represents different measures of community separation, which were then evaluated with respect to each variable's spatial characteristics. Results: We found each categorical variable derived from GIS separated lichen communities to some degree. Separation success ranged from strong (Alaska Subsections) to weak (Watersheds and Reindeer Ownership). Lichen community groups derived from cluster analysis demonstrated statistically significant relationships with 13 of the 17 categorical variables. Partialling out effects of spatial distance had little effect on these relationships. Conclusions: Greater number of patch types and larger average patch sizes contribute to optimal success in separating lichen communities; geographic distance did not appear to significantly alter separation success. Group distinctiveness or strength increased with more patch types or groups. Alternatively, congruence between lichen community types derived from cluster analysis and the 17 categorical variables was inversely related to patch size and spatial correlation. [source] Integrated technologies for archaeological investigation; the Celone Valley projectARCHAEOLOGICAL PROSPECTION, Issue 3 2007Marcello Ciminale Abstract A non-intrusive investigation integrating complementary technologies was carried out at four vast archaeological settlements located in the northern part of Apulia (Southern Italy). An aerial photographic survey combined with a high-resolution magnetic investigation was used to detect many buried archaeological features. After processing, both crop marks and magnetic anomalies appeared very sharp and well-defined, outlining the shape and plan of the buried structures with notable accuracy. Furthermore, differential global positioning system measurements were carried out in order to geocode the magnetic grids, to orthorectify the oblique coloured photographs and to make these data sets suitable for input into a GIS; a very good spatial correlation and a more rigorous and comprehensive interpretation of the various data elements were attained. Finally, as a result of this combined and accurate multilayer analysis, an archaeological interpretation was proposed, enabling useful information to be obtained on the transformations that have occurred over time at these study sites. Copyright © 2007 John Wiley & Sons, Ltd. [source] Improved Detection of Differentially Expressed Genes Through Incorporation of Gene LocationsBIOMETRICS, Issue 3 2009Guanghua Xiao Summary In determining differential expression in cDNA microarray experiments, the expression level of an individual gene is usually assumed to be independent of the expression levels of other genes, but many recent studies have shown that a gene's expression level tends to be similar to that of its neighbors on a chromosome, and differentially expressed (DE) genes are likely to form clusters of similar transcriptional activity along the chromosome. When modeled as a one-dimensional spatial series, the expression level of genes on the same chromosome frequently exhibit significant spatial correlation, reflecting spatial patterns in transcription. By modeling these spatial correlations, we can obtain improved estimates of transcript levels. Here, we demonstrate the existence of spatial correlations in transcriptional activity in the,Escherichia coli,(E. coli) chromosome across more than 50 experimental conditions. Based on this finding, we propose a hierarchical Bayesian model that borrows information from neighboring genes to improve the estimation of the expression level of a given gene and hence the detection of DE genes. Furthermore, we extend the model to account for the circular structure of,E. coli,chromosome and the intergenetic distance between gene neighbors. The simulation studies and analysis of real data examples in,E. coli,and yeast,Saccharomyces cerevisiae,show that the proposed method outperforms the commonly used significant analysis of microarray (SAM),t -statistic in detecting DE genes. [source] | ||||||||||||||||||||||||||||||||||||||||