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Spatial Dependence (spatial + dependence)
Selected AbstractsA Structural Equation Approach to Models with Spatial DependenceGEOGRAPHICAL ANALYSIS, Issue 2 2008Johan H. L. Oud We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it possible to obtain a closer correspondence between theory and empirics, to explicitly account for measurement errors, and to reduce multicollinearity. We extend the standard SEM maximum likelihood estimator to allow for spatial dependence and propose easily accessible SEM software like LISREL 8 and Mx. We present an illustration based on Anselin's Columbus, OH, crime data set. Furthermore, we combine the spatial lag model with the latent multiple-indicators,multiple-causes model and discuss estimation of this latent spatial lag model. We present an illustration based on the Anselin crime data set again. [source] Spatial dependence in agricultural land prices: does it exist?AGRICULTURAL ECONOMICS, Issue 3 2009Philip Kostov Spatial dependence; Hedonic models; Functional form Abstract Trade-offs arise between spatial dependence and choice of functional form in agricultural land price hedonic models. We discuss these trade-offs and how they can create spurious spatial dependence. Using a land sales dataset with apparent spatial dependence, we implement a semiparametric approach avoiding potential problems with the functional form. The results show that in addition to being nonlinear, the impacts are also characterized by significance thresholds that are difficult to capture in a parametric model. More importantly, we fail to detect any spatial dependence demonstrating that inappropriate functional form can indeed be responsible for finding spatial dependence in hedonic models. [source] Spatial variation of metals and acid volatile sulfide in floodplain lake sedimentENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 3 2003Corine van Griethuysena Abstract In risk assessment of aquatic sediments, much attention is paid to the immobilizing effect of acid volatile sulfide (AVS) on trace metals. The difference of AVS and simultaneously extracted metals (SEM) gives an indication of metal availability. In floodplain sediments, where changing redox conditions occur. AVS may play a major role in determining variation in metal availability. The importance of spatial heterogeneity has been recognized in risk assessment of trace-metal-polluted sediments. However, little is known about spatial variation of available metal fractions. We studied spatial variability of sediment, environmental conditions, total contaminant concentrations, and available metals (as SEM-AVS or SEM-AVS/fOC) in a floodplain lake. The top 5 cm of sediment was sampled at 43 locations. Data were analyzed with correlation and principal component analysis as well as with geostatistical methods. Trace metal and SEM concentrations and most sediment characteristics were more or less constant within 10%. In contrast, AVS concentrations were much more variable and showed a strong spatial dependence due to differences in lake depth, total sulfur pools, and redox potential (Eh), which resulted in crucial differences in trace-metal availability within the lake. The spatial pattern of SEM-AVS deviates from total or normalized trace-metal patterns. This particularly has implications for risk assessment of sediments prone to dynamic hydrological conditions, where AVS concentrations are also variable in time. [source] Statistics for spatial functional data: some recent contributionsENVIRONMETRICS, Issue 3-4 2010P. Delicado Abstract Functional data analysis (FDA) is a relatively new branch in statistics. Experiments where a complete function is observed for each individual give rise to functional data. In this work we focus on the case of functional data presenting spatial dependence. The three classic types of spatial data structures (geostatistical data, point patterns, and areal data) can be combined with functional data as it is shown in the examples of each situation provided here. We also review some contributions in the literature on spatial functional data. Copyright © 2009 John Wiley & Sons, Ltd. [source] Testing for trends in the violation frequency of an environmental threshold in riversENVIRONMETRICS, Issue 1 2009Lieven Clement Abstract Nutrient pollution in rivers is a common problem. It can provoke algae blooms which are related to increased fish mortality. To restore the water status, the regulator recently has promulgated more restrictive regulations. In Flanders for instance, the government has introduced several manure decrees (MDs) to restrict nutrient pollution. Environmental regulations are commonly expressed in terms of threshold levels. This provides a binary response to the decision maker. To handle such data, we propose the use of marginalised generalised linear mixed models. They provide valid inference on trends in the exceedance frequency. The spatio-temporal dependence of the river monitoring network is incorporated by the use of a latent variable. The temporal dependence is assumed to be AR(1) and the spatial dependence is derived from the river topology. The mean model contains a term for the trend and corrects for seasonal variation. The model formulation allows an assessment on the level of individual sampling locations and on a more regional scale. The methodology is applied to a case study on the river Yzer (Flanders). It assesses the impact of the MDs on the violation probability of the nitrate standard. A trend change is detected after the introduction of the second MD. Copyright © 2008 John Wiley & Sons, Ltd. [source] Analysis of particulate matter air pollution using Markov random field models of spatial dependenceENVIRONMETRICS, Issue 5-6 2002Mark S. Kaiser Abstract Researchers are beginning to realize the need to take spatial structure into account when modeling data on air pollutants. We develop several models for particulate matter in an urban region that allow spatial dependence to be represented in different manners over a time period of one year. The models are based on a Markov random field approach, and a conceptualization of observed data as arising from two random processes, a conditionally independent observation process and a spatially dependent latent pollution process. Optimal predictors are developed for both of these processes, and predictions of the observation process are used for model assessment. Copyright © 2002 John Wiley & Sons, Ltd. [source] Assessing sources of variability in measurement of ambient particulate matterENVIRONMETRICS, Issue 6 2001Michael J. Daniels Abstract Particulate matter (PM), a component of ambient air pollution, has been the subject of United States Environmental Protection Agency regulation in part due to many epidemiological studies examining its connection with health. Better understanding the PM measurement process and its dependence on location, time, and other factors is important for both modifying regulations and better understanding its effects on health. In light of this, in this paper, we will explore sources of variability in measuring PM including spatial, temporal and meteorological effects. In addition, we will assess the degree to which there is heterogeneity in the variability of the micro-scale processes, which may suggest important unmeasured processes, and the degree to which there is unexplained heterogeneity in space and time. We use Bayesian hierarchical models and restrict attention to the greater Pittsburgh (USA) area in 1996. The analyses indicated no spatial dependence after accounting for other sources of variability and also indicated heterogeneity in the variability of the micro-scale processes over time and space. Weather and temporal effects were very important and there was substantial heterogeneity in these effects across sites. Copyright © 2001 John Wiley & Sons, Ltd. [source] Comparing and contrasting some environmental and experimental design problems,ENVIRONMETRICS, Issue 4 2001R. J. Martin Abstract Designing an unreplicated field trial essentially involves firstly selecting the plots for the check varieties, and secondly arranging the check varieties among these plots. Selecting the check plots appears to be very similar to choosing sites for a monitoring network, or choosing sites in a region at which to take a sample. The problems appear to be even closer if spatial dependence is postulated, when another aim in choosing the sites is to allow efficient estimation of the dependence. In this paper, the designs of monitoring networks and spatial samples, and some related design problems, are considered to see if they have implications for the design of unreplicated field trials. Copyright © 2001 John Wiley & Sons, Ltd. [source] Geostatistical and multi-elemental analysis of soils to interpret land-use history in the Hebrides, ScotlandGEOARCHAEOLOGY: AN INTERNATIONAL JOURNAL, Issue 4 2007J.A. Entwistle In the absence of documentary evidence about settlement form and agricultural practice in northwest Scotland before the mid-18th century, a geoarchaeological approach to reconstructing medieval land use and settlement form is presented here. This study applies multielemental analysis to soils previously collected from a settlement site in the Hebrides and highlights the importance of a detailed knowledge of the local soil environment and the cultural context. Geostatistical methods were used to analyze the spatial variability and distribution of a range of soil properties typically associated with geoarchaeological investigations. Semivariograms were produced to determine the spatial dependence of soil properties, and ordinary kriging was undertaken to produce prediction maps of the spatial distribution of these soil properties and enable interpolation over nonsampled locations in an attempt to more fully elucidate former land-use activity and settlement patterns. The importance of identifying the spatial covariance of elements and the need for several lines of physical and chemical evidence is highlighted. For many townships in the Hebrides, whose precise location and layout prior to extensive land reorganization in the late 18th,early 19th century is not recoverable through plans, multi-elemental analysis of soils can offer a valuable prospective and diagnostic tool. © 2007 Wiley Periodicals, Inc. [source] A Structural Equation Approach to Models with Spatial DependenceGEOGRAPHICAL ANALYSIS, Issue 2 2008Johan H. L. Oud We introduce the class of structural equation models (SEMs) and corresponding estimation procedures into a spatial dependence framework. SEM allows both latent and observed variables within one and the same (causal) model. Compared with models with observed variables only, this feature makes it possible to obtain a closer correspondence between theory and empirics, to explicitly account for measurement errors, and to reduce multicollinearity. We extend the standard SEM maximum likelihood estimator to allow for spatial dependence and propose easily accessible SEM software like LISREL 8 and Mx. We present an illustration based on Anselin's Columbus, OH, crime data set. Furthermore, we combine the spatial lag model with the latent multiple-indicators,multiple-causes model and discuss estimation of this latent spatial lag model. We present an illustration based on the Anselin crime data set again. [source] Spatial Effects in Website Adoption by Firms in European RegionsGROWTH AND CHANGE, Issue 1 2009MARGARITA BILLON ABSTRACT The purpose of this paper is to provide empirical evidence on the neighboring effects of Internet adoption as measured by the percentage of firms with their own website in the European regions. This is the first study that explicitly analyzes the role played by spatial effects to explain website adoption for the European case. A set of instruments and techniques commonly used in the spatial econometrics framework is employed to test the hypothesis that proximity matters when explaining Internet adoption by firms. Results show that firms in physically adjacent regions register a similar degree of Internet adoption, confirming the presence in this context of positive spatial dependence. Nevertheless, the spatial effects detected are mainly constrained by national borders. Gross domestic product (GDP) per capita, population density, sectoral composition, and education are positively related to geographic distribution of Internet adoption in the enlarged European Union. In addition, regional disparities in Internet adoption were found to be less important than territorial inequalities in GDP per capita. [source] Evidence for the accelerations of sea level on multi-decade and century timescalesINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 6 2009P. L. Woodworth Abstract A modification in the rate of change of sea level (i.e. an ,acceleration' or ,nonlinear trend') is an important climate-related signal, which requires confirmation and explanation. In this study, the evidence for accelerations in regional and global average sea level on timescales of several decades and longer is reviewed by inter-comparison of the recent findings of different researchers and by inspection of original tide gauge records. Most sea-level data originate from Europe and North America, and both the sets display evidence for a positive acceleration, or ,inflexion', around 1920,1930 and a negative one around 1960. These inflexions are the main contributors to reported accelerations since the late 19th century, and to decelerations during the mid- to late 20th century. However, these characteristic features are not always found in records from other parts of the world. Although some aspects of the sea-level time series are consistent with changes in rates of globally averaged temperature changes, volcanic eruptions and natural climate variability, modelling undertaken so far has been unable to describe these features adequately. This emphasizes the need for a major enhancement of the sea-level data set, especially for those parts of the world without long tide gauge records, in order to obtain greater insight into the spatial dependence of accelerations. A number of complementary methods must be employed, of which salt marsh techniques offer the possibility of obtaining time series similar to those that would have been obtained from coastal tide gauges. Copyright © 2008 Royal Meteorological Society [source] Influence of the carrier diffusion process on the transient response of vertical-cavity surface-emitting lasersINTERNATIONAL JOURNAL OF NUMERICAL MODELLING: ELECTRONIC NETWORKS, DEVICES AND FIELDS, Issue 1 2003M. S. Torre Abstract We investigate the transverse mode dynamics of weakly index-guided vertical-cavity surface-emitting lasers (VCSEL). The turn-on time of transverse modes are calculated by implementing a model for the VCSEL dynamics including diffusion and transport/capture phenomena. It takes into account the spatial dependence of the two carrier density profiles associated with the confined carriers in the quantum wells, and with the unconfined carriers in the barrier region. Devices of different aperture diameter under different excitation conditions are also studied. The model displays the correct turn-on time dependence on the injection current density when compared with the experimental data available. We show that the turn-on time of the modes increases when capture time increases and escape time decreases and also when diffusion increases. Copyright © 2002 John Wiley & Sons, Ltd. [source] War and Peace in Space and Time: The Role of DemocratizationINTERNATIONAL STUDIES QUARTERLY, Issue 1 2000Kristian S. Gleditsch Democratization reduces the risk of war, but uneven transitions toward democracy can increase the probability of war. Using country-level data on democratization and international war from the period 1875,1996, we develop a general additive statistical model reassessing this claim in light of temporal and spatial dependence. We also develop a new geopolitical database of contiguities and demonstrate new statistical techniques for probing the extent of spatial clustering and its impact on the relationship between democratization and war. Our findings reaffirm that democratization generally does reduce the risk of war, but that large swings back and forth between democracy and autocracy can increase war proneness. We show that the historical context of peace diminishes the risk of war, while a regional context plagued by conflict greatly magnifies it. [source] Spatial Effects within the Agricultural Land Market in Northern IrelandJOURNAL OF AGRICULTURAL ECONOMICS, Issue 1 2003Myles Patton The importance of dealing properly with spatial effects, such as spatial autocorrelation, in cross-sectional econometric estimation has become more widely recognised in recent years. Spatial autocorrelation is similar in many ways to serial correlation, but while the latter is ordered on a one-dimensional time axis, the former is ordered in two dimensions. The multi-directional nature of spatial dependence means that specialised techniques are needed for diagnostic testing and estimation purposes. This paper uses these specialised diagnostics to test for spatial effects within a hedonic pricing study of the agricultural land market. The tests indicate that spatial autocorrelation (in the form of spatial lag dependence) and spatially distinct sub-markets (or spatial heterogeneity) are present. Ignoring these effects in the estimation process is likely to lead to biased parameter estimates. Consequently, we re-specify the hedonic model to allow for these spatial effects. The presence of spatial lag dependence suggests that there is circularity of price setting within the agricultural land market. This means that agricultural land prices are not solely determined by the inherent characteristics of the land, but tend to reflect also the average local price per acre. [source] Socio-economic distance and spatial patterns in unemploymentJOURNAL OF APPLIED ECONOMETRICS, Issue 4 2002Timothy G. Conley This paper examines the spatial patterns of unemployment in Chicago between 1980 and 1990. We study unemployment clustering with respect to different social and economic distance metrics that reflect the structure of agents' social networks. Specifically, we use physical distance, travel time, and differences in ethnic and occupational distribution between locations. Our goal is to determine whether our estimates of spatial dependence are consistent with models in which agents' employment status is affected by information exchanged locally within their social networks. We present non-parametric estimates of correlation across Census tracts as a function of each distance metric as well as pairs of metrics, both for unemployment rate itself and after conditioning on a set of tract characteristics. Our results indicate that there is a strong positive and statistically significant degree of spatial dependence in the distribution of raw unemployment rates, for all our metrics. However, once we condition on a set of covariates, most of the spatial autocorrelation is eliminated, with the exception of physical and occupational distance. Racial and ethnic composition variables are the single most important factor in explaining the observed correlation patterns. Copyright © 2002 John Wiley & Sons, Ltd. [source] Impact of shade on the spatial distribution of Sahlbergella singularis in traditional cocoa agroforestsAGRICULTURAL AND FOREST ENTOMOLOGY, Issue 1 2010Régis Babin 1Shade management is commonly considered to be an effective pest management strategy for cocoa mirids, yet shade management recommendations are not based on extensive knowledge of the mirid ecology in traditional cocoa agroforests. 2The main objectives of the present study were an assessment of the impact of shade on the spatial distribution of mirid populations and thus the evaluation of shade management strategies. 3Mirid densities were measured and shade was characterized for three plots located in three different agroecological zones in the Centre region of Cameroon. Mirid densities generally followed a negative binomial law. Geostatistical procedures were used to characterize spatial distribution of mirid density. Light conditions were assessed using hemispherical photography. 4Populations of Sahlbergella singularis were highly aggregated in the plots. Semivariance analysis and kriging visualized the spatial dependence of mirid densities. Clearly distinguishable mirid pockets of 20,30 adjacent infested cocoa trees were identified in two of the three plots. 5The high diversity of shade tree species and the large variability in density and size of shade trees resulted in a considerable heterogeneity of plot light conditions. Percentage transmitted light varied in the range 9.4,80.1% in the most heterogeneous plot. 6For two of the three plots, mirid pockets were aggregated in those areas where light transmission was highest. In the third plot, relatively high mirid densities and the presence of an alternative host resulted in a more homogeneous distribution. The importance of these findings for improved mirid control is discussed. [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 dependence in agricultural land prices: does it exist?AGRICULTURAL ECONOMICS, Issue 3 2009Philip Kostov Spatial dependence; Hedonic models; Functional form Abstract Trade-offs arise between spatial dependence and choice of functional form in agricultural land price hedonic models. We discuss these trade-offs and how they can create spurious spatial dependence. Using a land sales dataset with apparent spatial dependence, we implement a semiparametric approach avoiding potential problems with the functional form. The results show that in addition to being nonlinear, the impacts are also characterized by significance thresholds that are difficult to capture in a parametric model. More importantly, we fail to detect any spatial dependence demonstrating that inappropriate functional form can indeed be responsible for finding spatial dependence in hedonic models. [source] Spatial variability of sequentially extracted P fractions in a silty loamJOURNAL OF PLANT NUTRITION AND SOIL SCIENCE, Issue 3 2005Elena Heilmann Abstract Knowledge of the spatial distribution of soil P forms in agricultural fields is important for evaluating the risk of P transfer to waterways. The objective of this study was to characterize the spatial variation of total P (Pt) and sequentially extracted P forms in the Ap horizon of arable soils at the field scale. Soil samples were taken on a regular grid of 50 m × 50 m with 40 sampling points. Chemical analyses included basic soil properties, Pt, sequentially extracted P forms, and acid phosphomonoesterase activity. The spatial variability was analyzed by geostatistics and descriptive statistics. The concentrations of Pt ranged from 521 to 1020 mg,kg,1 with lower values observed for Gleysols and Stagnic Phaeozems and higher values for Luvisols and Cambisols. For the sequentially extracted P fractions, the largest coefficients of variation (c.v.) were found for NaHCO3 -Po (41%), NaHCO3 -Pi (36%), NaOH-Po (34%), and resin-P (33%). Despite this great spatial variability, no spatial dependence could be proved by geostatistics because the calculated range of P forms (<10 m) was below the smallest sampling distance (50 m). A clear trend of increasing concentrations and proportions of organic NaHCO3 - and NaOH-P fractions and phosphomonoesterase activity towards lower slope positions and the discharging brook indicated that Gleysols were a particular source of P losses to waterways in this catchment. It was concluded that these soils require a specific management with reduced P inputs and, perhaps, chemical treatment to fix leachable P. Räumliche Variabilität sequenziell extrahierter P-Fraktionen in einem Schlufflehm Kenntnisse über die räumliche Verteilung der P-Formen in landwirtschaftlichen Flächen sind notwendig für die Abschätzung des Risikos von P-Austrägen. Gegenstand dieser Untersuchung war die räumliche Verteilung von Gesamt-P (Pt) und P-Formen im Ap-Horizont von landwirtschaftlich genutzten Böden im Feldmaßstab. Dazu wurden Proben auf einem Raster von 50 m × 50 m an 40 Punkten entnommen. Die chemischen Analysen umfassten Grundeigenschaften sowie Pt, sequenziell extrahierte P-Formen und die Aktivität der sauren Phosphomonoesterase. Die räumliche Variabilität wurde mit räumlicher und deskriptiver Statistik untersucht. Die Pt -Gehalte lagen im Bereich von 521 bis 1020 mg,kg,1, wobei Gleye und Pseudogleye die niedrigsten Werte hatten. Bei den sequenziell extrahierten P-Fraktionen wurden die größten Variationskoeffizienten für NaHCO3 -Po (41%), NaHCO3 -Pi (36 %), NaOH-Po (34 %) und Harz-P (33 %) festgestellt. Trotz dieser großen räumlichen Variabilität konnte mit Geostatistik keine räumliche Abhängigkeit nachgewiesen werden, möglicherweise weil die geschätzte Reichweite der P-Formen mit <10 m unterhalb der kleinsten Beprobungsdistanz von 50 m lag. Deutliche gerichtete Trends steigender Gehalte und Anteile organischer NaHCO3 - und NaOH-P-Fraktionen und Phosphomonoesterase-Aktivitäten hin zu niedrigeren Geländepositionen und zur Nachbarschaft zu dem entwässernden Bach deuteten darauf hin, dass insbesondere Gleye eine Quelle der P-Einträge in Oberflächengewässer des Einzugsgebietes sein können. Es ergibt sich daher die Schlussfolgerung, dass diese Böden einer teilschlagspezifischen Bewirtschaftung mit reduzierten P-Zufuhren und eventuell P-fixierenden Behandlungen bedürfen. [source] A General Misspecification Test for Spatial Regression Models: Dependence, Heterogeneity, and NonlinearityJOURNAL OF REGIONAL SCIENCE, Issue 2 2001Thomas De Graaff There is an increasing awareness of the potentials of nonlinear modeling in regional science. This can be explained partly by the recognition of the limitations of conventional equilibrium models in complex situations, and also by the easy availability and accessibility of sophisticated computational techniques. Among the class of nonlinear models, dynamic variants based on, for example, chaos theory stand out as an interesting approach. However, the operational significance of such approaches is still rather limited and a rigorous statistical-econometric treatment of nonlinear dynamic modeling experiments is lacking. Against this background this paper is concerned with a methodological and empirical analysis of a general misspecification test for spatial regression models that is expected to have power against nonlinearity, spatial dependence, and heteroskedasticity. The paper seeks to break new research ground by linking the classical diagnostic tools developed in spatial econometrics to a misspecification test derived directly from chaos theory,the BDS test, developed by Brock, Dechert, and Scheinkman (1987). A spatial variant of the BDS test is introduced and applied in the context of two examples of spatial process models, one of which is concerned with the spatial distribution of regional investments in The Netherlands, the other with spatial crime patterns in Columbus, Ohio. [source] Spatial risk assessment for extreme river flowsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 5 2009Caroline Keef Summary., The UK has in recent years experienced a series of fluvial flooding events which have simultaneously affected communities over different parts of the country. For the co-ordination of flood mitigation activities and for the insurance and reinsurance industries, knowledge of the spatial characteristics of fluvial flooding is important. Past research into the spatiotemporal risk of fluvial flooding has largely been restricted to empirical estimates of risk measures. A weakness with such an approach is that there is no basis for extrapolation of these estimates to rarer events, which is required as empirical evidence suggests that larger events tend to be more localized in space. We adopt a model-based approach using the methods of Heffernan and Tawn. However, the large proportion of missing data over a network of sites makes direct application of this method highly inefficient. We therefore propose an extension of the Heffernan and Tawn method which accounts for missing values. Furthermore, as the risk measures are spatiotemporal an extension of the Heffernan and Tawn method is also required to handle temporal dependence. We illustrate the benefits of the procedure with a simulation study and by assessing spatial dependence over four fluvial sites in Scotland. [source] Simulation and extremal analysis of hurricane eventsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2000E. Casson In regions affected by tropical storms the damage caused by hurricane winds can be catastrophic. Consequently, accurate estimates of hurricane activity in such regions are vital. Unfortunately, the severity of events means that wind speed data are scarce and unreliable, even by standards which are usual for extreme value analysis. In contrast, records of atmospheric pressures are more complete. This suggests a two-stage approach: the development of a model describing spatiotemporal patterns of wind field behaviour for hurricane events; then the simulation of such events, using meteorological climate models, to obtain a realization of associated wind speeds whose extremal characteristics are summarized. This is not a new idea, but we apply careful statistical modelling for each aspect of the model development and simulation, taking the Gulf and Atlantic coastlines of the USA as our study area. Moreover, we address for the first time the issue of spatial dependence in extremes of hurricane events, which we find to have substantial implications for regional risk assessments. [source] Spatial patterns and associations in a Quercus-Betula forest in northern ChinaJOURNAL OF VEGETATION SCIENCE, Issue 3 2004J.H. Hou Abstract: Question: Are species-specific regeneration strategies and competition the dominant processes facilitating species coexistence in a Quercus liaotungensis dominated temperate deciduous forest? Location: Dongling Mountains, North China, 1300 m a.s.l. Methods: Ripley's K -function was used to characterize the spatial patterns and spatial associations of two dominant tree species, Quercus liaotungensis and Betula dahurica, and a common subcanopy species, Acer mono, at different growth stages (adult, sapling, seedling). Results: Seedlings, saplings and adults of all three species exhibited clumped distributions at most spatial scales. Quercus seedlings and saplings were positively associated with conspecific adult trees and spatially independent of dead trees suggesting that seed dispersal and vegetative regeneration influenced the spatial patterning of Quercus trees. Betula seedlings and saplings were positively associated with both live and dead trees of conspecific adults at small scales (<5 m) but negatively associated with live and dead trees of other species indicating sprouting as an important mechanism of reproduction. Saplings of Acer had a strong spatial dependence on the distribution of conspecific adult trees indicating its limited seed dispersal range. Negative associations between adult trees of Betula and Quercus demonstrated interspecific competition at local scales (<5 m). Conclusions: Different regeneration strategies among the three species play an important role in regulating their spatial distribution patterns, while competition between individuals of Betula and Quercus at the adult stage also contributes to spatial patterning of these communities. The recruitment limitations of Betula and Quercus may affect the persistence of these species and the long-term dynamics of the forest. [source] A grid-based method for sampling and analysing spatially ambiguous plantsJOURNAL OF VEGETATION SCIENCE, Issue 4 2001Jeffrey S. Fehmi Hickman (1993). Abstract. Spatial data can provide much information about the interrelations of plants and the relationship between individuals and the environment. Spatially ambiguous plants, i.e. plants without readily identifiable loci, and plants that are profusely abundant, present non-trivial impediments to the collection and analysis of vegetation data derived from standard spatial sampling techniques. Sampling with grids of presence/absence quadrats can ameliorate much of this difficulty. Our analysis of 10 fully-mapped grassland plots demonstrates the applicability of the grid-based approach which revealed spatial dependence at a much lower sampling effort than mapping each plant. Ripley's K -function, a test commonly used for point patterns, was effective for pattern analysis on the grids and the gridded quadrat technique was an effective tool for quantifying spatial patterns. The addition of spatial pattern measures should allow for better comparisons of vegetation structure between sites, instead of sole reliance on species composition data. [source] Spatial variability of total soil carbon and nitrogen stocks for some reclaimed minesoils of southeastern Ohio,LAND DEGRADATION AND DEVELOPMENT, Issue 3 2008G. Nyamadzawo Abstract Reclamation of drastically disturbed minesoils and subsequent planting of trees and/or grasses can result in a rapid build-up of carbon (C) in the soil. However, the amount of C sequestered in reclaimed minesoils may vary with the amount of time since reclamation. In this study, we assessed total carbon (TC) and total nitrogen (TN) concentrations for reclaimed minesoils located in northeastern Ohio and characterized by distinct reclamation age chronosequences. Reclaimed minesoils studied were R78G, reclaimed in 1978 and immediately seeded to grass; R82GT, reclaimed in 1982 and immediately seeded to grass and trees were planted 5 years later; and R87G, reclaimed in 1987 and immediately seeded to grass. An unmined site, UMG, was also included as a reference. Our objectives were to evaluate the variability with respect to mean and the spatial variability of pH, bulk density (,b), TC and TN concentrations, and stocks in each reclaimed minesoil. Thirty soil samples were collected at each of the 0,15, 15,30, and 30,50,cm depth. The coefficient of variation (CV) for ,b was least, <15 per cent at each site and depth. For TN concentration and stock, CV was moderate, 15,35 per cent, in each field except the UMG where it was high, >35 per cent at 0,15, and 15,30,cm depths. For TC concentration and stocks, CV was high, >35 per cent, across all minesoils and generally increased with depth. The C/N ratio followed the same tend as TC and TN stocks and ranged from 40 per cent to 123 per cent across minesoils. Geostatistical analysis also showed an increase in sample variance with increasing amount of time since reclamation for most soil properties under investigation. Sample variance for TC concentration and stocks also increased with depth in reclaimed minesoils. However, no definite relationship emerged between amount of time since reclamation and the spatial dependence of TC and TN concentrations and stocks. Overall this study showed that reclamation of drastically disturbed minesoils increased the soil C concentration and stocks and reclamation by initially seeding to grasses followed by planting trees was the best management option for speedy accretion of soil C and soil quality enhancement. Copyright © 2007 John Wiley & Sons, Ltd. [source] Polarization properties of the in vitro old human crystalline lensOPHTHALMIC AND PHYSIOLOGICAL OPTICS, Issue 2 2003Juan M. Bueno Abstract We have studied the spatially resolved polarization properties of the in vitro intact old human crystalline lens (from 56 to 88 years old) by using Mueller-matrix imaging polarimetry. Analysis was performed within an average of 54 h of death. Results show that the overall retardation is small (7° on average) and decreases from the centre of the lens to the periphery. Lenticular birefringence is linear but has a spatial dependence, reducing outwards along the radius. The distribution of azimuthal angle of the birefringent structure of the crystalline lens changes depending on each individual lens. Diattenuation and polarizance were found to be small, however, depolarization was about 35% for the set of lenses studied here. [source] Spatial and sectoral composition effects of agglomeration economies in the Netherlands,PAPERS IN REGIONAL SCIENCE, Issue 1 2007Frank G. Van Oort Agglomeration economies; spatial econometric models; dynamic externalities; urban growth; spatial regimes Abstract., In this article we test for dynamic inter- and intra-industry externalities on the urban level in the Netherlands. We argue that previous contributions might be sensitive to untested spatial and sectoral composition effects of urban data. We conclude that research results are better controlled when analysed on lower spatial scales, that results improve in robustness when spatial dependence in the form of spatially lagged versions of explained (growth) variables is introduced in the econometric models, and that results are more informative when hierarchical urban regimes are tested for. Introducing spatially lagged versions of explanatory agglomeration variables is informative but leads to less robust outcomes. In general our research results are more conclusive on inter-industry externalities circumstances when outcomes of city-industry as well as sectoral research designs are compared with the same dataset. [source] Empirical growth models with spatial effects*PAPERS IN REGIONAL SCIENCE, Issue 2 2006Bernard Fingleton Spatial spillovers; regional productivity; spatial econometrics; EU regions Abstract., Recent contributions to the regional science literature have considered spatial effects in empirical growth specifications. In the case of spatial dependence, following theoretical arguments from new economic geography, and endogenous growth models, this phenomenon has been associated with the existence of externalities that cross regional borders. However, despite the general consensus that interactions or externalities are likely to be the major source of spatial dependence, they have been modelled in a rather ad hoc manner in most existing empirical studies. In contrast, we advocate basing the analysis on structural growth models which include externalities across economies, applying the appropriate spatial econometrics tools to test for their presence and estimate the magnitude of these externalities in the real world. [source] Bayesian Spatial Survival Models for Political Event ProcessesAMERICAN JOURNAL OF POLITICAL SCIENCE, Issue 1 2009David Darmofal Research in political science is increasingly, but independently, modeling heterogeneity and spatial dependence. This article draws together these two research agendas via spatial random effects survival models. In contrast to standard survival models, which assume spatial independence, spatial survival models allow for spatial autocorrelation at neighboring locations. I examine spatial dependence in both semiparametric Cox and parametric Weibull models and in both individual and shared frailty models. I employ a Bayesian approach in which spatial autocorrelation in unmeasured risk factors across neighboring units is incorporated via a conditionally autoregressive (CAR) prior. I apply the Bayesian spatial survival modeling approach to the timing of U.S. House members' position announcements on NAFTA. I find that spatial shared frailty models outperform standard nonfrailty models and nonspatial frailty models in both the semiparametric and parametric analyses. The modeling of spatial dependence also produces changes in the effects of substantive covariates in the analysis. [source] | |||||||||||||||||||||||||