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Tobler's first law of geography is widely recognized as reflecting broad empirical realities in geography. Its key concepts of "near" and "related" are intuitive in a univariate setting. However, when moving to the joint consideration of spatial patterns among multiple variables, the combination of attribute similarity and geographical similarity that underlies the concept of spatial autocorrelation is much harder to deal with. This article uses the notion of distance in multiattribute space to explore and visualize the connection between "near" and "related" in a multivariate context. We approach this from a global, local, and regional perspective. We outline a number of ways to combine different visualization techniques and introduce a new local neighbor match test for multivariate local clusters. We illustrate the methods by means of Guerry's classic data set on moral statistics in 1833 France. [ABSTRACT FROM AUTHOR]

Based on a unique data set of French municipalities and a large number of budgetary variables, we estimate the extent of spatial fiscal interaction among the 33,484 French municipalities in 2008 by accounting for inter-municipal cooperation. Using a spatial autoregressive model with inter-municipal group fixed effects, we show that spatial interactions among French municipalities are inflated by correlated effects that affect similarly municipalities that cooperate together. Removing these confounding effects leads to considerably smaller positive spatial interactions for tax decisions and even negative ones for capital expenditures. In addition, we observe a clear distinction between complementary choices on current budget items and substitutable choices on capital budget items. [ABSTRACT FROM AUTHOR]

Purpose: We sought to determine whether significant variation in the incidence of clinically relevant psychoses existed at an ecological level in an urban French setting, and to examine possible factors associated with this variation. We aimed to advance the literature by testing this hypothesis in a novel population setting and by comparing a variety of spatial models.Methods: We sought to identify all first episode cases of non-affective and affective psychotic disorders presenting in a defined urban catchment area over a 4 years period, over more than half a million person-years at-risk. Because data from geographic close neighbourhoods usually show spatial autocorrelation, we used for our analyses Bayesian modelling. We included small area neighbourhood measures of deprivation, migrants' density and social fragmentation as putative explanatory variables in the models.Results: Incidence of broad psychotic disorders shows spatial patterning with the best fit for models that included both strong autocorrelation between neighbouring areas and weak autocorrelation between areas further apart. Affective psychotic disorders showed similar spatial patterning and were associated with the proportion of migrants/foreigners in the area (inverse correlation). In contrast, non-affective psychoses did not show spatial patterning.Conclusions: At ecological level, the variation in the number of cases and the factors that influence this variation are different for non-affective and affective psychotic disorders. Important differences in results-compared with previous studies in different settings-point to the importance of the context and the necessity of further studies to understand these differences. [ABSTRACT FROM AUTHOR]

This paper studies the spatial dynamics of French agricultural cooperatives using the recently developed exploratory spatial data analysis tool. Analysis at the level of French districts in 1995 and 2005 shows strong evidence for global and local spatial autocorrelations in the geographical distribution of agricultural cooperatives. The presence of spatial disparities between French districts is confirmed by the detection of such specific spatial patterns as district clusters, a group of neighbouring districts with the same high or low level of agricultural cooperative activities. A typology of all the different Regions is developed to examine the specific spatial patterns of the agricultural cooperative activities. The results indicate that major organizational changes in cooperatives do not significantly modify the initial dynamics concerning the location of activities. [ABSTRACT FROM PUBLISHER]

Abstract: Test fluxes of planktic foraminifera in the Bay of Biscay were sampled in spring using drifting sediment traps deployed at 200m depth. At a temporal and spatial resolution of 3h and approximately 1km the foraminifer flux varied with a factor of 5. The consecutive deployments within the same area, at distances of ∼50km differed significantly in flux and relative species abundances. Flux sequences of the total foraminifer assemblage and individual species were significantly autocorrelated. The significance of autocorrelation analyses was affected by sample size of the flux sequences and limited to flux sequences with large fluxes. Autocorrelation in planktic foraminifer fluxes and standing stocks was restricted to distances <2km, and were not attributed to the temporal domain. [Copyright &y& Elsevier]

The hypothesis of financial market efficiency predicts that the stock prices show instantaneously all the applicable information available on the market (Fama, 1970). If the market is efficient, and if the investors are neutral to the risk, then the stock prices are unpredictable. This paper studies the predictability of stock returns listed on the French stock market. The objective of this paper is to examine the nature of the phenomenon characterizing the behavior of the prices. It is about examining the phenomena of underreaction and overreaction on the French stock market during the period 1974-2004. If these two phenomena do not exist, then the stock prices follow a random walk. We adopt the methodology of De Bondt and Thaler (1985) for the construction of winning and losing portfolio and performed different econometric tests to study the phenomena of underreaction and overreaction. We find that the hypotheses of overreaction and underreaction are rarely significant. Therefore, we can say that the variation of stock returns is often unforeseeable which is based on the sets of ex post returns. [ABSTRACT FROM AUTHOR]

Populations of the common vole Microtus arvalis in mid-western France show cyclic dynamics with a three-year period. Studies of cyclic vole populations in Fennoscandia have often found inter-specific synchrony between the voles and other small mammals which share the voles' predators. Although predators are central to the favoured mechanism to explain Fennoscandian vole cycles and the spatial variation of small mammal populations, their role in vole cycles elsewhere, including France, is less clear. Establishing whether alternative prey species in France cycle in parallel with voles as they do in Fennoscandia is thus an important step towards understanding the generality of predators' influence on cyclic vole populations. We applied spatial and temporal autocorrelation and cross-correlation methods to French populations of M. arvalis and two sympatric non-cyclic small mammal species, Apodemus sylvaticus and Crocidura russula. Patterns of time-lagged cross-correlation between the abundance of M. arvalis and the other two species suggested synchrony in their dynamics beyond that expected of stochastic environmental variation, and indicated a weak three-year cycle in A. sylvaticus and C. russula that was in phase with that of M. arvalis. We interpret the synchrony between these species as the effect of shared predators and environmental stochasticity. Abundance within species showed weak spatial autocorrelation in June at scales consistent with dispersal being the mechanism responsible, but a more general lack of spatial structure within and between species was consistent with the strong spatial synchrony at regional scales often found in fluctuations of small mammal abundance. [ABSTRACT FROM AUTHOR]

1. Effective restoration of ecosystem structure and function needs to be built on a strong conceptual basis. The evaluation of restoration is critical in this respect, as it requires an accurate understanding of vegetation dynamics. This study was, therefore, designed to analyse how initial restoration treatments and spontaneous ecological processes act together to produce spatial heterogeneity of plant species at various scales, taking into account that species might respond differentially to these processes in accordance with their biological attributes. 2. In a model system consisting of a large land settlement located on the banks of the river Rhône (France), 85 geo-referenced plots were located, and the abundance of all plant species and seven biotic and abiotic environmental factors that have been modified by restoration were recorded. All species were classified into emergent groups (EGs) based on 12 plant traits, and the abundance of each EG was derived for each plot. Spatial variables that explained the spatial autocorrelation of the EGs at four scales were computed. This was performed using a spatial eigenvector mapping technique. The spatial variables were then linked to a range of selected environmental factors. 3. Large-scale patterning of EGs was explained mainly by the spatial heterogeneity of soil quality and vegetation cover. The attribute combination of the EGs that varied most at this scale suggested that the restoration had influenced vegetation development by inducing harsh physical conditions in some part of the studied area and biotic filtering (through competition) in others. 4. A large amount of the spatial variation of EGs was not explained by the environmental factors providing some evidence for pure spatial autocorrelation effects. At the finest scale, this was linked to poor dispersal abilities of some EGs. 5. Synthesis and applications. By combining a trait-based approach with spatially explicit methods, we explained and quantified the role of environmental changes induced by restoration and spontaneous biotic processes in structuring plant communities on different spatial scales within a large land settlement. We discuss how such an approach offers new opportunities for an improved assessment of induced and spontaneous structuring factors for restoring and for monitoring plant communities during ecological restoration. [ABSTRACT FROM AUTHOR]

Accounting for spatial scale is essential for understanding habitat selection, but few studies have used spatial statistics to reveal the characteristic scale at which organisms respond to their environment. We studied habitat selection by GPS-tracked red deer (Cervus elaphus L., 1758) in the Pyrenees Mountains, France, by applying a geostatistical model that compares autocorrelation of a resource between used and available sites to uncover the scale at which animals assess habitat. Using an artificial landscape, we demonstrated that the model can handle discrete habitat classes. Based on conventional hierarchical analysis, deer selected for open habitat, especially meadow, and avoided coniferous forest, more strongly at the coarse level of the home range than GPS locations. Home ranges exhibited generally lower autocorrelation in elevation and meadow habitat than random locations within the population range, indicative of preference for high habitat heterogeneity. Mean maximum discrepancy in autocorrelation, which was more pronounced at the level of the home range than GPS locations, occurred at 830 m for meadow habitat and at 1511 m for elevation, suggesting that red deer responded to their environment at this scale. Our study demonstrates how spatial statistics can serve as an instructive complement to conventional approaches to habitat selection. L’étude de l’échelle spatiale est essentielle pour comprendre la sélection de l’habitat, mais peu d’études ont utilisé des statistiques spatiales pour révéler l’échelle caractéristique à laquelle un organisme répond à son environnement. Nous avons étudié la sélection de l’habitat par des cerfs rouges (Cervus elaphus L., 1758) suivis par GPS dans les montagnes pyrénéennes, en France, en appliquant un modèle géostatistique, qui compare l’autocorrélation d’une ressource entre les sites utilisés et disponibles pour découvrir l’échelle à laquelle les animaux évaluent leur habitat. À partir d’un paysage artificiel, nous démontrons que ce modèle peut être généralisé pour traiter des classes discrètes d’habitat. D’après une analyse hiérarchique conventionnelle, les cerfs sélectionnent un habitat ouvert, plus particulièrement les prairies, et évitent les forêts de conifères, de façon plus marquée au niveau plus grossier du domaine vital que celui des localisations GPS. Les domaines révèlent généralement une plus faible autocorrélation pour l’altitude et l’habitat prairie que les localisations aléatoires dans le domaine populationnel, révélateur d’une préférence pour une forte hétérogénéité d’habitats. L’écart moyen maximum d’autocorrélation, plus prononcé à l’échelle du domaine individuel que des localisations GPS, est de 830 m pour l’habitat prairie et de 1511 m pour l’altitude, ce qui laisse croire que le cerf réagit à son environnement à cette échelle. Notre étude démontre comment les statistiques spatiales peuvent servir de complément instructif aux approches conventionnelles de sélection de l’habitat. [ABSTRACT FROM AUTHOR]

Aim Worldwide, functional homogenization is now considered to be one of the most prominent forms of biotic impoverishment induced by current global changes. Yet this process has hardly been quantified on a large scale through simple indices, and the connection between landscape disturbance and functional homogenization has hardly been established. Here we test whether changes in land use and landscape fragmentation are associated with functional homogenization of bird communities at a national scale. Location France. Methods We estimated functional homogenization of a community as the average specialization of the species present in that community. We studied the spatial variation of this community specialization index (CSI) using 1028 replicates from the French Breeding Bird Survey along spatial gradients of landscape fragmentation and recent landscape disturbance, measured independently, and accounting for spatial autocorrelation. Results The CSI was very sensitive to both measures of environmental degradation: on average, 23% of the difference in the CSI values between two sample sites was attributed to the difference in fragmentation and the disturbance between sites. This negative correlation between CSI and sources of landscape degradation was consistent over various habitats and biogeographical zones. Main conclusions We demonstrate that the functional homogenization of bird communities is strongly positively correlated to landscape disturbance and fragmentation. We suggest that the CSI is particularly effective for measuring functional homogenization on both local and global scales for any sort of organism and with abundance or presence–absence data. [ABSTRACT FROM AUTHOR]

The autocorrelation in stock returns is one of the most important anomalies in financial markets worldwide. In this paper, we have investigated differences in return autocorrelation on a day-to-day basis in the Spanish and French stock markets. Our research provides strong evidence of the importance of non-trading periods, not only weekends and holidays but also overnight closings, to explain return autocorrelation anomalies. While close-to-close stock returns are highly autocorrelated, specially on Mondays, when we compute daily returns on an open-to-close basis they do not exhibit a significant level of autocorrelation. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the role played by habitat diversity in the landscape on species richness and on the stability of farmland bird communities was investigated. Species richness was estimated on 374 samples monitored in farmland by the French breeding bird survey during the 2001–2005 period. A capture–recapture approach was used to estimate species richness accounting for the variation in detection probability among species of the 100 most common species detected in farmland. Landscape structure and composition were measured both in farmland and in adjacent habitats. The independent effect of each variable on community richness and stability was further assessed using hierarchical variance partitioning and taking spatial autocorrelation into account. A strong matrix effect was detected: non-cropped land deeply influenced richness and stability of bird assemblages. [Copyright &y& Elsevier]

Objective: This empirical study was designed to explore the role of ecological features of species in the spatial patterning of a grassland community. Location: Banks of the river Rhône in France. Material and Methods: First, we explored the spatial pattern of 29 species recorded in the community using spatial autocorrelation analysis of species cover values. Second, we then explored the relationship between the patterns found and a set of life attributes that characterized the ecological features of species for resource foraging or dispersion. Finally, we explored the spatial relationship of groups of species that shared the same ecological features using cross-correlation analysis. Results: We found a significant relationship between the spatial pattern and life attributes of the species highlighting three groups of species: (1) species characterized as competitors, reproducing by runner clonal organs and forming large, dense patches; (2) species characterized as competitive-ruderals, dispersing exclusively by seed production and forming small periodic patches; and (3) species classified as CSR, characterized by rosette morphology and short rhizomes as clonal organs without any significant spatial autocorrelation. Spatial segregation was found between group 1 and group 2 up to 14 m; no significant cross-correlation between groups 1 and 3 between 0 and 3.5 m, and association between groups 2 and 3 up to 14 m. Conclusions: These results helped to understand how species attributes (relative to stature or dispersion abilities); external factors (such as disturbance) and biotic processes (competition) interplay in structuring the plant community under study in space. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the spatial and space-time distributions of cases of childhood acute leukaemia (CL) during 1990-2000 over the whole French territory. A global spatial heterogeneity and a spatial autocorrelation were first considered using the methods proposed by Potthoff and Whittinghill, Moran and Rogerson methods. The presence of space-time interaction between the places of residence and the dates of diagnosis was investigated with the Knox's test. Finally, the Kulldorff's statistic permitted to scan the whole territory in search for localised clusters. Two time periods were considered (1990-1994, 1995-2000). Overall, a statistically significant spatial heterogeneity of a very small magnitude was observed in the incidence of CL over 1990-1994, but neither over 1995-2000 nor over the whole time period. Moreover, a significant overdispersion of 5.5% was evidenced for 0-4 year children living in isolated areas with more than 50 inhabitants per km(2). Cases older than 10 years living in the same area at diagnosis also tended to cluster within 6 months. [ABSTRACT FROM AUTHOR]