On the search for spillovers from foreign direct investment (FDI) with spatial dependency

This paper examines various specifications that are used within the literature to test for spillovers from foreign direct investment (FDI). Analysis provides significant evidence of externalities from inward FDI, but it shows that these externalities are more localized than has previously been believed. Further, the results demonstrate that the econometric treatment of issues such as agglomeration, contiguity and spatial dependence significantly changes the conclusions regarding local and national spillovers from FDI, and productivity growth more generally.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Towards more precise sugar beet management based on geostatistical analysis of spatial variability within fields

Within-field variation in sugar beet yield and quality was investigated in three commercial sugar beet fields in the east of England to identify the main associated variables and to examine the possibility of predicting yield early in the season with a view to spatially variable management of sugar beet crops. Irregular grid sampling with some purposively-located nested samples was applied. It revealed the spatial variability in each sugar beet field efficiently. In geostatistical analyses, most variograms were isotropic with moderate to strong spatial dependency indicating a significant spatial variation in sugar beet yield and associated growth and environmental variables in all directions within each field. The Kriged maps showed spatial patterns of yield variability within each field and visual association with the maps of other variables. This was confirmed by redundancy analyses and Pearson correlation coefficients. The main variables associated with yield variability were soil type, organic matter, soil moisture, weed density and canopy temperature. Kriged maps of final yield variability were strongly related to that in crop canopy cover, LAI and intercepted solar radiation early in the growing season, and the yield maps of previous crops. Therefore, yield maps of previous crops together with early assessment of sugar beet growth may make an early prediction of within-field variability in sugar beet yield possible. The Broom’s Barn sugar beet model failed to account for the spatial variability in sugar yield, but the simulation was greatly improved when corrected for early canopy development cover and when the simulated yield was adjusted for weeds and plant population. Further research to optimize inputs to maximise sugar yield should target the irrigation and fertilizing of areas within fields with low canopy cover early in the season.

Spatial variability of infiltration and its relationship to some physical properties

Water infiltration into soil is one of the basic factors for estimating irrigation intensity according to the plants' requirements; this is aimed at avoiding problems of surface run-off and degradation. The purpose of the present investigation was to determine the spatial variation of infiltration and its relationship to some physical properties of soil by means of geostatistical techniques in Typic Plinthaquult soils having average texture and flat relief. A 113 point mesh was designned, having a regular distance of 10 m between points, samples being taken from 0 to 0.20 meters depth. Sand, silt and clay content, bulk density, macroporosity, microporosity and total porosity were determined. Infiltration tests were carried out in the field by means of a 15 cm diameter ring. Descriptive statistics and geostatistics were used for analysing the data. Infiltration, silt and microporosity data did not fit a normal distribution curve. Infiltration had high variability, having an average 36.03 mm h(-1). Total porosity was 56.73%, this being the only property that did not show spatial dependency. The smallest ranges were observed for bulk density, macroporosity and microporosity, having values of less than 40 m. The smallest degrees of spatial dependence were observed for infiltration, silt and clay, evidence also being shown of the influence of silt and clay on infiltration rate. Contour maps were constructed; fitting them to the semivariogram models, together with studying the correlations, led to establishing relationships between the properties.

Interactions spatiales et auto-organisation des végétations semi-arides

Les recherches récapitulées dans cette thèse de doctorat ont porté sur les causes de l’organisation spatiale des végétations périodiques. Ces structures paysagères aux motifs réguliers, tachetés, tigrés ou labyrinthiques, d’échelle décamétrique à hectométrique, couvrant des étendues considérables sur au moins trois continents, constituent un cas d’école dans l’étude des processus endogènes présidant à l’hétérogénéité du couvert végétal. Ces structures prennent place sur un substrat homogène, mis à part la rétroaction du couvert lui-même, et sont marquées par des écotones abrupts et la persistance d’une proportion considérable de sol nu. Plusieurs modèles ont mis en avant l’existence possible d’un phénomène d’auto-organisation du couvert, qui verrait une structure d’ensemble émerger des interactions locales entre individus. Ces modèles se basent sur le jeu simultané de la consommation de la ressource (compétition) et de l’amélioration de l’un ou l’autre des éléments du bilan de la même ressource par le couvert (facilitation). La condition à l’existence d’une structure d’ensemble spatialement périodique et stable réside dans une différence entre la portée de la compétition (plus grande) et celle de la facilitation. L’apparition de ces structures est modulée par le taux de croissance biologique, qui est le reflet des contraintes extérieures telles que l’aridité, le pâturage ou la coupe de bois. Le modus operandi des interactions spatiales supposées entre individus reste largement à préciser.

Nos recherches ont été menées au sud-ouest de la République du Niger, à l’intérieur et dans les environs du parc Régional du W. Trois axes ont été explorés :(i) Une étude de la dépendance spatiale entre la structure de la végétation (biovolumes cartographiés) et les paramètres du milieu abiotique (relief, sol), sur base d’analyses spectrales et cross-spectrales par transformée de Fourier (1D et 2D). (ii) Une étude diachronique (1956, 1975 et 1996) à large échelle (3000 km²) de l’influence de l’aridité et des pressions d’origine anthropique sur l’auto-organisation des végétations périodiques, basée sur la caractérisation de la structure spatiale des paysages sur photos aériennes via la transformée de Fourier en 2D. (iii) Trois études portant sur les interactions spatiales entre individus :En premier lieu, via l’excavation des systèmes racinaires (air pulsé) ;Ensuite, par un suivi spatio-temporel du bilan hydrique du sol (blocs de gypse) ;Enfin, via le marquage de la ressource par du deutérium.

Nous avons ainsi pu établir que les végétations périodiques constituent bien un mode d’auto-organisation pouvant survenir sur substrat homogène et modulé par les contraintes climatiques et anthropiques. Un ajustement rapide entre l’organisation des végétations périodiques et le climat a pu être montrée en zone protégée. La superficie et l’organisation des végétations périodiques y ont tour à tour progressé et régressé en fonction d’épisodes secs ou humides. Par contre, en dehors de l’aire protégée, la possibilité d’une restauration du couvert semble fortement liée au taux d’exploitation des ressources végétales. Ces résultats ont d’importantes implications quant à la compréhension des interactions entre climat et écosystèmes et à l’évaluation de leurs capacités de charge. La caractérisation de la structure spatiale des végétations arides, notamment par la transformée de Fourier d’images HR, devrait être généralisée comme outil de monitoring de l’état de ces écosystèmes. Nos études portant sur les modes d’interactions spatiales ont permis de confirmer l’existence d’une facilitation à courte portée du couvert végétal sur la ressource. Cependant, cette facilitation ne semble pas s’exercer sur le terme du bilan hydrique traditionnellement avancé, à savoir l’infiltration, mais plutôt sur le taux d’évaporation (deux fois moindre à l’ombre des canopées). Ce mécanisme exclut l’existence de transferts diffusifs souterrains entre sols nu et fourrés. Des transferts inverses semblent d’ailleurs montrés par le marquage isotopique. L’étude du bilan hydrique et la cartographie du micro-relief, ainsi que la profondeur fortement réduite de la zone d’exploitation racinaire, jettent de sérieux doutes quant au rôle communément admis des transferts d’eau par ruissellement/diffusion de surface en tant que processus clé dans la compétition à distance entre les plantes. L’alternative réside dans l’existence d’une compétition racinaire de portée supérieure aux canopées. Cette hypothèse trouve une confirmation tant par les rhizosphères excavées, superficielles et étendues, que dans le marquage isotopique, montrant des contaminations d’arbustes situés à plus de 15 m de la zone d’apport. De même, l’étude du bilan hydrique met en évidence les influences simultanées et contradictoires (facilitation/compétition) des ligneux sur l’évapotranspiration.

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This PhD thesis gathers results of a research dealing with the causes of the spatial organisation of periodic vegetations. These landscape structures, featuring regular spotted, labyrinthine or banded patterns of decametric to hectometric scale, and extending over considerable areas on at least three continents, constitute a perfect study case to approach endogenous processes leading to vegetation heterogeneities. These patterns occur over homogeneous substratum, except for vegetation’s own feedbacks, and are marked by sharp ecotones and the persistence of a considerable amount of bare soil. A number of models suggested a possible case of self-organized patterning, in which the general structure would emerge from local interactions between individuals. Those models rest on the interplay of competitive and facilitative effects, relating to soil water consumption and to soil water budget enhancement by vegetation. A general necessary condition for pattern formation to occur is that negative interactions (competition) have a larger range than positive interactions (facilitation). Moreover, all models agree with the idea that patterning occurs when vegetation growth decreases, for instance as a result of reduced water availability, domestic grazing or wood cutting, therefore viewing patterns as a self-organised response to environmental constraints. However the modus operandi of the spatial interactions between individual plants remains largely to be specified.

We carried out a field research in South-West Niger, within and around the W Regional Park. Three research lines were explored: (i) The study of the spatial dependency between the vegetation pattern (mapped biovolumes) and the factors of the abiotic environment (soil, relief), on the basis of spectral and cross-spectral analyses with Fourier transform (1D and 2D). (ii) A broad scale diachronic study (1956, 1975, 1996) of the influence of aridity and human induced pressures on the vegetation self-patterning, based on the characterisation of patterns on high resolution remote sensing data via 2D Fourier transform. (iii) Three different approaches of the spatial interactions between individuals: via root systems excavation with pulsed air; via the monitoring in space and time of the soil water budget (gypsum blocks method); and via water resource labelling with deuterated water.

We could establish that periodic vegetations are indeed the result of a self-organisation process, occurring in homogeneous substratum conditions and modulated by climate and human constraints. A rapid adjustment between vegetation patterning and climate could be observed in protected zones. The area and patterning of the periodic vegetations successively progressed and regressed, following drier or wetter climate conditions. On the other hand, outside protected areas, the restoration ability of vegetation appeared to depend on the degree of vegetation resource exploitation. These results have important implications regarding the study of vegetation-climate interactions and the evaluation of ecosystems’ carrying capacities. Spatial pattern characterisation in arid vegetations using Fourier transform of HR remote sensing data should be generalised for the monitoring of those ecosystems. Our studies dealing with spatial interaction mechanisms confirmed the existence of a short range facilitation of the cover on water resource. However, this facilitation does not seem to act through the commonly accepted infiltration component, but rather on the evaporative rate (twice less within thickets). This mechanism excludes underground diffusive transfers between bare ground and vegetation. Inverse transfers were even shown by deuterium labelling. Water budget study and micro-elevation mapping, along with consistent soil shallowness, together cast serious doubts on the traditional mechanism of run-off/diffusion of surface water as a key process of the long range competition between plants. An alternative explanation lies in long range root competition. This hypothesis find support as well in the excavated root systems, shallow and wide, as in isotopic labelling, showing contaminations of shrubs located up to 15 m of the irrigated area. Water budget study also evidenced simultaneous contradictory effects (facilitation/competition) of shrubs on evapotranspiration.

Within-Otolith Variability in Chemical Fingerprints: Implications for Sampling Designs and Possible Environmental Interpretation

Largely used as a natural biological tag in studies of dispersal/connectivity of fish, otolith elemental fingerprinting is usually analyzed by laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS). LA-ICP-MS produces an elemental fingerprint at a discrete time-point in the life of a fish and can generate data on within-otolith variability of that fingerprint. The presence of within-otolith variability has been previously acknowledged but not incorporated into experimental designs on the presumed, but untested, grounds of both its negligibility compared to among-otolith variability and of spatial autocorrelation among multiple ablations within an otolith. Here, using a hierarchical sampling design of spatial variation at multiple scales in otolith chemical fingerprints for two Mediterranean coastal fishes, we explore: 1) whether multiple ablations within an otolith can be used as independent replicates for significance tests among otoliths, and 2) the implications of incorporating within-otolith variability when assessing spatial variability in otolith chemistry at a hierarchy of spatial scales (different fish, from different sites, at different locations on the Apulian Adriatic coast). We find that multiple ablations along the same daily rings do not necessarily exhibit spatial dependency within the otolith and can be used to estimate residual variability in a hierarchical sampling design. Inclusion of within-otolith measurements reveals that individuals at the same site can show significant variability in elemental uptake. Within-otolith variability examined across the spatial hierarchy identifies differences between the two fish species investigated, and this finding leads to discussion of the potential for within-otolith variability to be used as a marker for fish exposure to stressful conditions. We also demonstrate that a 'cost'-optimal allocation of sampling effort should typically include some level of within-otolith replication in the experimental design. Our findings provide novel evidence to aid the design of future sampling programs and improve our general understanding of the mechanisms regulating elemental fingerprints.

Spatio-temporal Rich Model Based Video Steganalysis on Cross Sections of Motion Vector Planes

A rich model based motion vector steganalysis benefiting from both temporal and spatial correlations of motion vectors is proposed in this work. The proposed steganalysis method has a substantially superior detection accuracy than the previous methods, even the targeted ones. The improvement in detection accuracy lies in several novel approaches introduced in this work. Firstly, it is shown that there is a strong correlation, not only spatially but also temporally, among neighbouring motion vectors for longer distances. Therefore, temporal motion vector dependency along side the spatial dependency is utilized for rigorous motion vector steganalysis. Secondly, unlike the filters previously used, which were heuristically designed against a specific motion vector steganography, a diverse set of many filters which can capture aberrations introduced by various motion vector steganography methods is used. The variety and also the number of the filter kernels are substantially more than that of used in previous ones. Besides that, filters up to fifth order are employed whereas the previous methods use at most second order filters. As a result of these, the proposed system captures various decorrelations in a wide spatio-temporal range and provides a better cover model. The proposed method is tested against the most prominent motion vector steganalysis and steganography methods. To the best knowledge of the authors, the experiments section has the most comprehensive tests in motion vector steganalysis field including five stego and seven steganalysis methods. Test results show that the proposed method yields around 20% detection accuracy increase in low payloads and 5% in higher payloads.

Regional consumption of antibiotics : a demand system approach

Through this paper. we have attempted to model the demand for different classes of antibiotics used for respiratory infections in outpatient care in Switzerland using a spatial version of the linear approximate Almost Ideal Demand System (AIDS) model. This model takes spatial dependency into account by means of spatial lags of antibiotic budget shares. We control for the health status of patients and the potential harmful effects of antibiotic use in terms of bacterial resistance. Elasticities to socioeconomic determinants of consumption and own- and cross-price elasticities between different groups of antibiotic have also been computed in this paper. Significant cross-price elasticities are found between newer or more expensive generations and older or less expensive generations of antibiotics. (C) 2009 Elsevier B.V. All rights reserved.

Calibrating flood inundation models: identifying and addressing uncertainty in satellite observed flood extents

Improvements in the resolution of satellite imagery have enabled extraction of water surface elevations at the margins of the flood. Comparison between modelled and observed water surface elevations provides a new means for calibrating and validating flood inundation models, however the uncertainty in this observed data has yet to be addressed. Here a flood inundation model is calibrated using a probabilistic treatment of the observed data. A LiDAR guided snake algorithm is used to determine an outline of a flood event in 2006 on the River Dee, North Wales, UK, using a 12.5m ERS-1 image. Points at approximately 100m intervals along this outline are selected, and the water surface elevation recorded as the LiDAR DEM elevation at each point. With a planar water surface from the gauged upstream to downstream water elevations as an approximation, the water surface elevations at points along this flooded extent are compared to their ‘expected’ value. The pattern of errors between the two show a roughly normal distribution, however when plotted against coordinates there is obvious spatial autocorrelation. The source of this spatial dependency is investigated by comparing errors to the slope gradient and aspect of the LiDAR DEM. A LISFLOOD-FP model of the flood event is set-up to investigate the effect of observed data uncertainty on the calibration of flood inundation models. Multiple simulations are run using different combinations of friction parameters, from which the optimum parameter set will be selected. For each simulation a T-test is used to quantify the fit between modelled and observed water surface elevations. The points chosen for use in this T-test are selected based on their error. The criteria for selection enables evaluation of the sensitivity of the choice of optimum parameter set to uncertainty in the observed data. This work explores the observed data in detail and highlights possible causes of error. The identification of significant error (RMSE = 0.8m) between approximate expected and actual observed elevations from the remotely sensed data emphasises the limitations of using this data in a deterministic manner within the calibration process. These limitations are addressed by developing a new probabilistic approach to using the observed data.

The impact of uncertainty in satellite data on the assessment of flood inundation models

The performance of flood inundation models is often assessed using satellite observed data; however these data have inherent uncertainty. In this study we assess the impact of this uncertainty when calibrating a flood inundation model (LISFLOOD-FP) for a flood event in December 2006 on the River Dee, North Wales, UK. The flood extent is delineated from an ERS-2 SAR image of the event using an active contour model (snake), and water levels at the flood margin calculated through intersection of the shoreline vector with LiDAR topographic data. Gauged water levels are used to create a reference water surface slope for comparison with the satellite-derived water levels. Residuals between the satellite observed data points and those from the reference line are spatially clustered into groups of similar values. We show that model calibration achieved using pattern matching of observed and predicted flood extent is negatively influenced by this spatial dependency in the data. By contrast, model calibration using water elevations produces realistic calibrated optimum friction parameters even when spatial dependency is present. To test the impact of removing spatial dependency a new method of evaluating flood inundation model performance is developed by using multiple random subsamples of the water surface elevation data points. By testing for spatial dependency using Moran’s I, multiple subsamples of water elevations that have no significant spatial dependency are selected. The model is then calibrated against these data and the results averaged. This gives a near identical result to calibration using spatially dependent data, but has the advantage of being a statistically robust assessment of model performance in which we can have more confidence. Moreover, by using the variations found in the subsamples of the observed data it is possible to assess the effects of observational uncertainty on the assessment of flooding risk.

How do neighbouring populations affect local population change over time?

This study covers a period when society changed from a pre-industrial agricultural society to a post-industrial service-producing society. Parallel with this social transformation, major population changes took place. In this study, we analyse how local population changes are affected by neighbouring populations. To do so we use the last 200 years of local population change that redistributed population in Sweden. We use literature to identify several different processes and spatial dependencies in the redistribution between a parish and its surrounding parishes. The analysis is based on a unique unchanged historical parish division, and we use an index of local spatial correlation to describe different kinds of spatial dependencies that have influenced the redistribution of the population. To control inherent time dependencies, we introduce a non-separable spatial temporal correlation model into the analysis of population redistribution. Hereby, several different spatial dependencies can be observed simultaneously over time. The main conclusions are that while local population changes have been highly dependent on the neighbouring populations in the 19th century, this spatial dependence have become insignificant already when two parishes is separated by 5 kilometres in the late 20th century. Another conclusion is that the time dependency in the population change is higher when the population redistribution is weak, as it currently is and as it was during the 19th century until the start of industrial revolution.

Análise da distribuição espacial da hanseníase no Estado de São Paulo, 1991-2002

A hanseníase no Brasil ainda é um problema a ser equacionado e, no Estado de São Paulo, há varias regiões com altas taxas de detecção. O presente estudo objetivou analisar a distribuição e quantificar a dependência espacial das taxas médias de detecção da hanseníase no Estado de São Paulo, no período de 1991-2002, empregando técnicas geoestatísticas. Verificou-se tendência levemente decrescente das taxas médias de detecção para o Estado de São Paulo. Altos índices do indicador podem ser visualizados nas regiões oeste e noroeste de São Paulo. A dependência espacial encontrada foi de aproximadamente 30 km. Com os resultados encontrados, conclui-se que a análise de superfície das taxas médias de detecção pode auxiliar na escolha de áreas prioritárias visando aos exames de coletividade e ao incremento dos exames nos contatos dos casos detectados.

Variabilidade espacial de atributos químicos em latossolo e argissolos

O trabalho teve como objetivo caracterizar a variabilidade espacial de atributos químicos de Latossolos e Argissolos, sob cultivo de cana-de-açúcar em áreas com variações na forma do relevo. No presente estudo utilizou-se duas áreas, sendo uma em Latossolo em pedoforma convexa (158ha) e a outra em Argissolo na pedoforma linear (172ha). Foi coletada amostra de solo em malha na profundidade de 0,00-0,50m, realizando-se análise química de cada ponto amostrado. Os maiores coeficientes de variação e alcances foram observados na pedoforma convexa (Latossolo). Portanto, o Latossolo inserido na pedoforma convexa apresentou maior variabilidade espacial para os atributos químicos em relação ao Argissolo na pedoforma linear. O latossolo inserido pedoforma convexa necessita de maior número de pontos de coleta por apresentar maior variabilidade espacial. Recomenda-se que o intervalo de amostragem seja igual ao alcance da dependência espacial, para associar menor esforço de amostragem com maior representatividade.

Análise geoestatística de casos de hanseníase no Estado de São Paulo, 1991-2002

OBJETIVO: Analisar o padrão espacial da ocorrência dos casos de hanseníase para identificar áreas com probabilidade de riscos de transmissão da doença. MÉTODOS: Estudo ecológico, tendo como unidade de análise os municípios do Estado de São Paulo georreferenciados em seus centróides. A fonte de dados utilizada foi o banco informatizado dos casos de hanseníase notificados do Centro de Vigilância Epidemiológica do Estado de São Paulo, no período de 1991 a 2002. Utilizou-se de técnicas de geoestatística para a detecção das áreas de probabilidade de risco para hanseníase e quantificação da dependência espacial dos casos. RESULTADOS: Detectou-se o alcance de dependência espacial de 0,55 graus de coordenadas georreferenciadas, correspondendo aproximadamente a 60 km. As principais áreas de probabilidade de risco encontradas foram as regiões nordeste, norte e noroeste do Estado. CONCLUSÕES: A verificação de áreas com probabilidades de riscos de casos de hanseníase, utilizando-se a análise da dependência espacial, pode ser ferramenta útil para avaliar a situação de saúde e planejar alocação de recursos.

Correlação da produtividade do feijão com a resistência à penetração do solo sob plantio direto

The soil mechanical resistance to penetration (PR) has great influence on vegetative development as the root growth and the crop productivity change in inverse proportion. Thus, the objective of this research was to study correlation between the bean grain productivity and the PR in an Oxisol cultivated for four years in no-tillage system at FEIS/UNESP. The attributes PR and yield were determined in a regular grid with 119 sample points. The PR was determined in the layers of 0-0.05, 0.05-0.10, 0.10-0.15, 0.15-0.20 and 0.25-0.30 m. The results were submitted to procedures of descriptive statistics, linear correlation and geostatistic analysis. The linear correlation between the yield and PR was practically null, as in all soil layers investigated it showed determination coefficients (R2) smaller than 0.03 and not significant. The geostatistic analysis showed moderate structure of spatial dependency for PR in the layers of 0.05-0.10 and 0.10-0.15 m, and strong for yield; however, the conjugate spatial analysis of such attributes showed no correlation, therefore, the spatial variability of PR did not influence the yield.