Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Instrumental leadership: Measurement and extension of transformational-transactional leadership theory.

Leaders must scan the internal and external environment, chart strategic and task objectives, and provide performance feedback. These instrumental leadership (IL) functions go beyond the motivational and quid-pro quo leader behaviors that comprise the full-range-transformational, transactional, and laissez faire-leadership model. In four studies we examined the construct validity of IL. We found evidence for a four-factor IL model that was highly prototypical of good leadership. IL predicted top-level leader emergence controlling for the full-range factors, initiating structure, and consideration. It also explained unique variance in outcomes beyond the full-range factors; the effects of transformational leadership were vastly overstated when IL was omitted from the model. We discuss the importance of a "fuller full-range" leadership theory for theory and practice. We also showcase our methodological contributions regarding corrections for common method variance (i.e., endogeneity) bias using two-stage least squares (2SLS) regression and Monte Carlo split-sample designs.

Parts, places, and perspectives : a theory of spatial relations based an mereotopology and convexity

This thesis suggests to carry on the philosophical work begun in Casati's and Varzi's seminal book Parts and Places, by extending their general reflections on the basic formal structure of spatial representation beyond mereotopology and absolute location to the question of perspectives and perspective-dependent spatial relations. We show how, on the basis of a conceptual analysis of such notions as perspective and direction, a mereotopological theory with convexity can express perspectival spatial relations in a strictly qualitative framework. We start by introducing a particular mereotopological theory, AKGEMT, and argue that it constitutes an adequate core for a theory of spatial relations. Two features of AKGEMT are of particular importance: AKGEMT is an extensional mereotopology, implying that sameness of proper parts is a sufficient and necessary condition for identity, and it allows for (lower- dimensional) boundary elements in its domain of quantification. We then discuss an extension of AKGEMT, AKGEMTS, which results from the addition of a binary segment operator whose interpretation is that of a straight line segment between mereotopological points. Based on existing axiom systems in standard point-set topology, we propose an axiomatic characterisation of the segment operator and show that it is strong enough to sustain complex properties of a convexity predicate and a convex hull operator. We compare our segment-based characterisation of the convex hull to Cohn et al.'s axioms for the convex hull operator, arguing that our notion of convexity is significantly stronger. The discussion of AKGEMTS defines the background theory of spatial representation on which the developments in the second part of this thesis are built. The second part deals with perspectival spatial relations in two-dimensional space, i.e., such relations as those expressed by 'in front of, 'behind', 'to the left/right of, etc., and develops a qualitative formalism for perspectival relations within the framework of AKGEMTS. Two main claims are defended in part 2: That perspectival relations in two-dimensional space are four- place relations of the kind R(x, y, z, w), to be read as x is i?-related to y as z looks at w; and that these four-place structures can be satisfactorily expressed within the qualitative theory AKGEMTS. To defend these two claims, we start by arguing for a unified account of perspectival relations, thus rejecting the traditional distinction between 'relative' and 'intrinsic' perspectival relations. We present a formal theory of perspectival relations in the framework of AKGEMTS, deploying the idea that perspectival relations in two-dimensional space are four-place relations, having a locational and a perspectival part and show how this four-place structure leads to a unified framework of perspectival relations. Finally, we present a philosophical motivation to the idea that perspectival relations are four-place, cashing out the thesis that perspectives are vectorial properties and argue that vectorial properties are relations between spatial entities. Using Fine's notion of "qua objects" for an analysis of points of view, we show at last how our four-place approach to perspectival relations compares to more traditional understandings.

Theory of mind and cognitive processes in aging and Alzheimer type dementia: a systematic review.

OBJECTIVES: Theory of mind (ToM) performance in aging and dementia of the Alzheimer type (DAT) has been a growing interest of researchers and recently, theoretical trends in ToM development have led to a focus on determining the cognitive skills involved in ToM performance. The aim of the present review is to answer three main questions: How is ToM assessed in aging and DAT? How does ToM performance evolve in aging and DAT? Do cognitive processes influence ToM performance in aging and DAT? METHOD: A systematic review was conducted to provide a targeted overview of recent studies relating ToM performance with cognitive processes in aging and DAT. RESULTS: RESULTS suggest a decrease in ToM performance, more pronounced in complex ToM tasks. Moreover, the review points up the strong involvement of executive functions, especially inhibition, and reasoning skills in ToM task achievement. CONCLUSION: Current data suggest that the structure of ToM tasks itself could lead to poor performance, especially in populations with reduced cognitive abilities.

Extended family structure in the ant Formica paralugubris: the role of the breeding system

In populations of various ant species, many queens reproduce in the same nest (polygyny), and colony boundaries appear to be absent with individuals able to move fi eely between nests (unicoloniality). Such societies depart strongly from a simple family structure and pose a potential challenge to kin selection theory, because high queen number coupled with unrestricted gene flow among nests should result in levels of relatedness among nestmates close to zero. This study investigated the breeding system and genetic structure of a highly polygynous and largely unicolonial population of the wood ant Formica paralugubris. A microsatellite analysis revealed that nestmate workers, reproductive queens and reproductive males (the queens' mates) are all equally related to each other, with relatedness estimates centring around 0.14. This suggests that most of the queens and males reproducing in the study population had mated within or close to their natal nest, and that the queens did not disperse far after mating. We developed a theoretical model to investigate how the breeding system affects the relatedness structure of polygynous colonies. By combining the model and our empirical data, it was estimated that about 99.8% of the reproducing queens and males originated from within the nest, or from a nearby nest. This high rate of local mating and the rarity of long-distance dispersal maintain significant relatedness among nestmates, and contrast with the common view that unicoloniality is coupled with unrestricted gene flow among nests.

Impact of social structure variation on population genetics, social conflicts and life histories in ants

Summary The evolution of social structures and breeding systems in animals is a complex process that combines ecological, genetical and social factors. This thesis sheds light on important changes in population genetics, life-history and social behavior that are associated with variation in social structure in ants. The socially polymorphic ant Formica selysi was chosen as the model organism because single- and multiple-queen colonies occur in close proximity within a single large population. The shift from single- to multiple-queen colonies is generally associated with profound changes in dispersal behavior and mode of colony founding. In chapter 1, we examine the genetic consequences of variation in social structure at both the colony and population levels. A detailed microsatellite analysis reveals that both colony types have similar mating systems, with few or no queen turnover. Furthermore, the complete lack of genetic differentiation observed between single- and multiple-queen colonies provides no support to the hypothesis that change in queen number leads to restricted gene flow between social forms. Besides changes in the genetic composition of the colony, the variation in the number of queens per colony is associated with changes in a network of behavioral and life-history traits that have been described as forming a "polygyny syndrome". In chapter 2, we demonstrate that multiple-queen colonies profoundly differ from single-queen ones in terms of size, nest density and lifespan of colonies, in weight of queens produced, as well as in allocation to reproductive individuals relative to workers. These multifaceted changes in life-history traits can provide various fitness benefits to members of multiple-queen colonies. Increasing the number of queens in a colony usually results in a decreased level of aggression towards non-nestmates. The phenotype matching hypothesis predicts that, compared to single-queen colonies, multiple-queen colonies have more diverse genetically-derived cues used for recognition, resulting in a lower ability to discriminate non-nestmates. In sharp contrast to this hypothesis, we show in chapter 3 that single- and multiple-queen colonies exhibit on average similar levels of aggression. Moreover, stronger aggression is recorded between colonies of different social structure than between colonies of the same social structure. Several hypotheses propose that the evolution of multiple-queen colonies is at least partly due to benefits resulting from an increase in colony genetic diversity. The task-efficiency hypothesis holds that genetic variation improves task performance due to a more complete or more sensitive expression of the genetically-based division of labor. In .chapter 4, we evaluate if higher colony genetic diversity increases worker size polymorphism and thus may improve division of labor. We show that despite the fact that worker size has a heritable component, higher levels of genetic diversity do not result in more polymorphic workers. The smaller size and lower polymorphism levels of workers of multiple-queen colonies compared to single-queen ones further indicate that an increase in colony genetic diversity does not increase worker size polymorphism but might improve colony homeostasis. In chapter 5, we provide clear evidence for an ongoing conflict between queens and workers on sex allocation, as predicted by kin selection theory. Our data show that queens of F. selysi strongly influence colony sex allocation by biasing the sex ratio of their eggs. However, there is also evidence that workers eliminated some male brood, resulting in a population sex-investment ratio that is between the queens' and workers' equilibria. Résumé L'évolution des structures sociales et systèmes d'accouplement chez les animaux est un processus complexe combinant à la fois des facteurs écologiques, génétiques et sociaux. Cette thèse met en lumière des changements importants dans la génétique des populations, les traits d'histoire de vie et les comportements sociaux qui sont associés à des variations de structure sociale chez les fourmis. Durant ce travail, nous avons étudié une population de Formica selysi composée à la fois de colonies à une reine et de colonies à plusieurs reines. La transition de colonie à une reine à colonie à plusieurs reines est généralement associée à des changements profonds dans le comportement de dispersion ainsi que le mode de fondation des sociétés. Dans le chapitre 1, nous examinons les conséquences génétiques de la variation de structure sociale tant au niveau de la colonie qu'au niveau de la population. Une analyse détaillée à l'aide de marqueurs microsatellites nous révèle que les deux types de colonies ont des systèmes d'accouplements similaires avec peu ou pas de renouvellement de reines. L'absence totale de différenciation génétique entre les colonies à une et à plusieurs reines n'apporte aucun support à l'hypothèse selon laquelle un changement dans le nombre de reines conduit à un flux de gènes restreint entre les deux formes sociales. A côté de changements dans la composition génétique de la colonie, la variation du nombre de reines dans une colonie est associée à une multitude de changements comportementaux et de traits d'histoire de vie qui ont été décrits comme formant un "syndrome polygyne". Dans le chapitre 2, nous démontrons que les colonies à plusieurs reines diffèrent profondément des colonies à une reine en terme de taille, densité de nids, longévité des colonies, poids des nouvelles reines produites ainsi que dans l'allocation entre les individus reproducteurs et les ouvrières. Ces changements multiples dans les traits d'histoire de vie peuvent apporter des bénéfices variés en terme de fitness aux colonies à plusieurs reines. L'augmentation du nombre de reines dans une colonie est généralement associée à une baisse du degré d'agressivité envers les fourmis étrangères au nid. L'hypothèse "phénotype matching" prédit que les colonies à plusieurs reines ont une plus grande diversité dans les facteurs d'origine génétique utilisés pour la reconnaissance, résultant en une capacité diminuée à discriminer une fourmi étrangère au nid. Contrairement à cette hypothèse, nous montrons dans le chapitre 3 que les colonies à une et à plusieurs reines ont des niveaux d'agressivité similaires. De plus, une agressivité accrue est observée entre colonies de structures sociales différentes comparée à des colonies de même structure sociale. Plusieurs hypothèses ont proposé que l'évolution de colonies ä plusieurs reines soit en partie due aux bénéfices résultant d'une augmentation de la diversité génétique dans la colonie. L'hypothèse "task efficiency" prédit que la diversité génétique améliore l'efficacité à effectuer certaines tâches grâce à une expression plus complète et plus souple d'une division du travail génétiquement déterminée. Nous évaluons dans le chapitre 4 si un accroissement de la diversité génétique augmente le polymorphisme de taille des ouvrières, d'où peut ainsi découler une meilleure division du travail. Nous montrons qu'en dépit du fait que la taille des ouvrières soit un caractère héritable, une forte diversité génétique ne se traduit pas par un plus fort polymorphisme chez les ouvrières. Les ouvrières de colonies à plusieurs reines sont plus petites et moins polymorphes que celles des colonies à une seule reine. Dans le chapitre 5, nous démontrons l'existence d'un conflit ouvert entre reines et ouvrières à propos de l'allocation dans les sexes, comme le prédit la théorie de la sélection de parentèle. Nos données révèlent que les reines de F. selysi influencent fortement l'allocation dans les sexes en biaisant la sexe ratio des oeufs. Cependant, certains indices indiquent que les ouvrières éliminent une partie du couvain mâle, ce qui a pour effet d'avoir un investissement dans les sexes au niveau de la population intermédiaire entre les intérêts des reines et des ouvrières.

The genetical theory of social behaviour.

We survey the population genetic basis of social evolution, using a logically consistent set of arguments to cover a wide range of biological scenarios. We start by reconsidering Hamilton's (Hamilton 1964 J. Theoret. Biol. 7, 1-16 (doi:10.1016/0022-5193(64)90038-4)) results for selection on a social trait under the assumptions of additive gene action, weak selection and constant environment and demography. This yields a prediction for the direction of allele frequency change in terms of phenotypic costs and benefits and genealogical concepts of relatedness, which holds for any frequency of the trait in the population, and provides the foundation for further developments and extensions. We then allow for any type of gene interaction within and between individuals, strong selection and fluctuating environments and demography, which may depend on the evolving trait itself. We reach three conclusions pertaining to selection on social behaviours under broad conditions. (i) Selection can be understood by focusing on a one-generation change in mean allele frequency, a computation which underpins the utility of reproductive value weights; (ii) in large populations under the assumptions of additive gene action and weak selection, this change is of constant sign for any allele frequency and is predicted by a phenotypic selection gradient; (iii) under the assumptions of trait substitution sequences, such phenotypic selection gradients suffice to characterize long-term multi-dimensional stochastic evolution, with almost no knowledge about the genetic details underlying the coevolving traits. Having such simple results about the effect of selection regardless of population structure and type of social interactions can help to delineate the common features of distinct biological processes. Finally, we clarify some persistent divergences within social evolution theory, with respect to exactness, synergies, maximization, dynamic sufficiency and the role of genetic arguments.

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling

The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Estimation of the correlation structure of crustal velocity heterogeneity from seismic reflection data

Numerous sources of evidence point to the fact that heterogeneity within the Earth's deep crystalline crust is complex and hence may be best described through stochastic rather than deterministic approaches. As seismic reflection imaging arguably offers the best means of sampling deep crustal rocks in situ, much interest has been expressed in using such data to characterize the stochastic nature of crustal heterogeneity. Previous work on this problem has shown that the spatial statistics of seismic reflection data are indeed related to those of the underlying heterogeneous seismic velocity distribution. As of yet, however, the nature of this relationship has remained elusive due to the fact that most of the work was either strictly empirical or based on incorrect methodological approaches. Here, we introduce a conceptual model, based on the assumption of weak scattering, that allows us to quantitatively link the second-order statistics of a 2-D seismic velocity distribution with those of the corresponding processed and depth-migrated seismic reflection image. We then perform a sensitivity study in order to investigate what information regarding the stochastic model parameters describing crustal velocity heterogeneity might potentially be recovered from the statistics of a seismic reflection image using this model. Finally, we present a Monte Carlo inversion strategy to estimate these parameters and we show examples of its application at two different source frequencies and using two different sets of prior information. Our results indicate that the inverse problem is inherently non-unique and that many different combinations of the vertical and lateral correlation lengths describing the velocity heterogeneity can yield seismic images with the same 2-D autocorrelation structure. The ratio of all of these possible combinations of vertical and lateral correlation lengths, however, remains roughly constant which indicates that, without additional prior information, the aspect ratio is the only parameter describing the stochastic seismic velocity structure that can be reliably recovered.

The genetic structure of metapopulations and conservation biology.

A range of models describing metapopulations is surveyed and their implications for conservation biology are described. An overview of the use of both population genetic elements and demographic theory in metapopulation models is given. It would appear that most of the current models suffer from either the use of over-simplified demography or the avoidance of selectively important genetic factors. The scale for which predictions are made by the various models is often obscure. A conceptual framework for describing metapopulations by utilising the concept of fitness of local populations is provided and some examples are given. The expectation that any general theory, such as that of metapopulations, can make useful predictions for particular problems of conservation is examined and compared with the prevailing 'state of the art' recommendations.

Constraints on the permeability structure of alluvial aquifers from the poro-elastic inversion of multi-frequency P-wave velocity logs

We have explored the possibility of obtaining first-order permeability estimates for saturated alluvial sediments based on the poro-elastic interpretation of the P-wave velocity dispersion inferred from sonic logs. Modern sonic logging tools designed for environmental and engineering applications allow one for P-wave velocity measurements at multiple emitter frequencies over a bandwidth covering 5 to 10 octaves. Methodological considerations indicate that, for saturated unconsolidated sediments in the silt to sand range and typical emitter frequencies ranging from approximately 1 to 30 kHz, the observable velocity dispersion should be sufficiently pronounced to allow one for reliable first-order estimations of the permeability structure. The corresponding predictions have been tested on and verified for a borehole penetrating a typical surficial alluvial aquifer. In addition to multifrequency sonic logs, a comprehensive suite of nuclear and electrical logs, an S-wave log, a litholog, and a limited number laboratory measurements of the permeability from retrieved core material were also available. This complementary information was found to be essential for parameterizing the poro-elastic inversion procedure and for assessing the uncertainty and internal consistency of corresponding permeability estimates. Our results indicate that the thus obtained permeability estimates are largely consistent with those expected based on the corresponding granulometric characteristics, as well as with the available evidence form laboratory measurements. These findings are also consistent with evidence from ocean acoustics, which indicate that, over a frequency range of several orders-of-magnitude, the classical theory of poro-elasticity is generally capable of explaining the observed P-wave velocity dispersion in medium- to fine-grained seabed sediments

The four- vs. alternative six-factor structure of the French WISC-IV: Comparison using confirmatory factor analyses

Exploratory and confirmatory factor analyses reported in the French technical manual of the WISC-IV provides evidence supporting a structure with four indices: Verbal Comprehension (VCI), Perceptual Reasoning (PRI), Working Memory (WMI), and Processing Speed (PSI). Although the WISC-IV is more attuned to contemporary theory, it is still not in total accordance with the dominant theory: the Cattell-Horn-Carroll (CHC) theory of cognitive ability. This study was designed to determine whether the French WISC-IV is better described with the four-factor solution or whether an alternative model based on the CHC theory is more appropriate. The intercorrelations matrix reported in the French technical manual was submitted to confirmatory factor analysis. A comparison of competing models suggests that a model based on the CHC theory fits the data better than the current WISC-IV structure. It appears that the French WISC-IV in fact measures six factors: crystallized intelligence (Gc), fluid intelligence (Gf), short-term memory (Gsm), processing speed (Gs), quantitative knowledge (Gq), and visual processing (Gv). We recommend that clinicians interpret the subtests of the French WISC-IV in relation to this CHC model in addition to the four indices.

The evolution of unicoloniality in ant societies : recognition, dispersal and population genetic structure

Introduction Societies of ants, bees, wasps and termites dominate many terrestrial ecosystems (Wilson 1971). Their evolutionary and ecological success is based upon the regulation of internal conflicts (e.g. Ratnieks et al. 2006), control of diseases (e.g. Schmid-Hempel 1998) and individual skills and collective intelligence in resource acquisition, nest building and defence (e.g. Camazine 2001). Individuals in social species can pass on their genes not only directly trough their own offspring, but also indirectly by favouring the reproduction of relatives. The inclusive fitness theory of Hamilton (1963; 1964) provides a powerful explanation for the evolution of reproductive altruism and cooperation in groups with related individuals. The same theory also led to the realization that insect societies are subject to internal conflicts over reproduction. Relatedness of less-than-one is not sufficient to eliminate all incentive for individual selfishness. This would indeed require a relatedness of one, as found among cells of an organism (Hardin 1968; Keller 1999). The challenge for evolutionary biology is to understand how groups can prevent or reduce the selfish exploitation of resources by group members, and how societies with low relatedness are maintained. In social insects the evolutionary shift from single- to multiple queens colonies modified the relatedness structure, the dispersal, and the mode of colony founding (e.g. (Crozier & Pamilo 1996). In ants, the most common, and presumably ancestral mode of reproduction is the emission of winged males and females, which found a new colony independently after mating and dispersal flights (Hölldobler & Wilson 1990). The alternative reproductive tactic for ant queens in multiple-queen colonies (polygyne) is to seek to be re-accepted in their natal colonies, where they may remain as additional reproductives or subsequently disperse on foot with part of the colony (budding) (Bourke & Franks 1995; Crozier & Pamilo 1996; Hölldobler & Wilson 1990). Such ant colonies can contain up to several hundred reproductive queens with an even more numerous workforce (Cherix 1980; Cherix 1983). As a consequence in polygynous ants the relatedness among nestmates is very low, and workers raise brood of queens to which they are only distantly related (Crozier & Pamilo 1996; Queller & Strassmann 1998). Therefore workers could increase their inclusive fitness by preferentially caring for their closest relatives and discriminate against less related or foreign individuals (Keller 1997; Queller & Strassmann 2002; Tarpy et al. 2004). However, the bulk of the evidence suggests that social insects do not behave nepotistically, probably because of the costs entailed by decreased colony efficiency or discrimination errors (Keller 1997). Recently, the consensus that nepotistic behaviour does not occur in insect colonies was challenged by a study in the ant Formica fusca (Hannonen & Sundström 2003b) showing that the reproductive share of queens more closely related to workers increases during brood development. However, this pattern can be explained either by nepotism with workers preferentially rearing the brood of more closely related queens or intrinsic differences in the viability of eggs laid by queens. In the first chapter, we designed an experiment to disentangle nepotism and differences in brood viability. We tested if workers prefer to rear their kin when given the choice between highly related and unrelated brood in the ant F. exsecta. We also looked for differences in egg viability among queens and simulated if such differences in egg viability may mistakenly lead to the conclusion that workers behave nepotistically. The acceptance of queens in polygnous ants raises the question whether the varying degree of relatedness affects their share in reproduction. In such colonies workers should favour nestmate queens over foreign queens. Numerous studies have investigated reproductive skew and partitioning of reproduction among queens (Bourke et al. 1997; Fournier et al. 2004; Fournier & Keller 2001; Hammond et al. 2006; Hannonen & Sundström 2003a; Heinze et al. 2001; Kümmerli & Keller 2007; Langer et al. 2004; Pamilo & Seppä 1994; Ross 1988; Ross 1993; Rüppell et al. 2002), yet almost no information is available on whether differences among queens in their relatedness to other colony members affects their share in reproduction. Such data are necessary to compare the relative reproductive success of dispersing and non-dispersing individuals. Moreover, information on whether there is a difference in reproductive success between resident and dispersing queens is also important for our understanding of the genetic structure of ant colonies and the dynamics of within group conflicts. In chapter two, we created single-queen colonies and then introduced a foreign queens originating from another colony kept under similar conditions in order to estimate the rate of queen acceptance into foreign established colonies, and to quantify the reproductive share of resident and introduced queens. An increasing number of studies have investigated the discrimination ability between ant workers (e.g. Holzer et al. 2006; Pedersen et al. 2006), but few have addressed the recognition and discrimination behaviour of workers towards reproductive individuals entering colonies (Bennett 1988; Brown et al. 2003; Evans 1996; Fortelius et al. 1993; Kikuchi et al. 2007; Rosengren & Pamilo 1986; Stuart et al. 1993; Sundström 1997; Vásquez & Silverman in press). These studies are important, because accepting new queens will generally have a large impact on colony kin structure and inclusive fitness of workers (Heinze & Keller 2000). In chapter three, we examined whether resident workers reject young foreign queens that enter into their nest. We introduced mated queens into their natal nest, a foreign-female producing nest, or a foreign male-producing nest and measured their survival. In addition, we also introduced young virgin and mated queens into their natal nest to examine whether the mating status of the queens influences their survival and acceptance by workers. On top of polgyny, some ant species have evolved an extraordinary social organization called 'unicoloniality' (Hölldobler & Wilson 1977; Pedersen et al. 2006). In unicolonial ants, intercolony borders are absent and workers and queens mix among the physically separated nests, such that nests form one large supercolony. Super-colonies can become very large, so that direct cooperative interactions are impossible between individuals of distant nests. Unicoloniality is an evolutionary paradox and a potential problem for kin selection theory because the mixing of queens and workers between nests leads to extremely low relatedness among nestmates (Bourke & Franks 1995; Crozier & Pamilo 1996; Keller 1995). A better understanding of the evolution and maintenance of unicoloniality requests detailed information on the discrimination behavior, dispersal, population structure, and the scale of competition. Cryptic genetic population structure may provide important information on the relevant scale to be considered when measuring relatedness and the role of kin selection. Theoretical studies have shown that relatedness should be measured at the level of the `economic neighborhood', which is the scale at which intraspecific competition generally takes place (Griffin & West 2002; Kelly 1994; Queller 1994; Taylor 1992). In chapter four, we conducted alarge-scale study to determine whether the unicolonial ant Formica paralugubris forms populations that are organised in discrete supercolonies or whether there is a continuous gradation in the level of aggression that may correlate with genetic isolation by distance and/or spatial distance between nests. In chapter five, we investigated the fine-scale population structure in three populations of F. paralugubris. We have developed mitochondria) markers, which together with the nuclear markers allowed us to detect cryptic genetic clusters of nests, to obtain more precise information on the genetic differentiation within populations, and to separate male and female gene flow. These new data provide important information on the scale to be considered when measuring relatedness in native unicolonial populations.

The social disembedding of business theory and practice. A (neo-)institutional analysis of the homo economicus and corporate social responsibility, and the inherent responsibility of business scholars

Aim Structure of the Thesis In the first article, I focus on the context in which the Homo Economicus was constructed - i.e., the conception of economic actors as fully rational, informed, egocentric, and profit-maximizing. I argue that the Homo Economicus theory was developed in a specific societal context with specific (partly tacit) values and norms. These norms have implicitly influenced the behavior of economic actors and have framed the interpretation of the Homo Economicus. Different factors however have weakened this implicit influence of the broader societal values and norms on economic actors. The result is an unbridled interpretation and application of the values and norms of the Homo Economicus in the business environment, and perhaps also in the broader society. In the second article, I show that the morality of many economic actors relies on isomorphism, i.e., the attempt to fit into the group by adopting the moral norms surrounding them. In consequence, if the norms prevailing in a specific group or context (such as a specific region or a specific industry) change, it can be expected that actors with an 'isomorphism morality' will also adapt their ethical thinking and their behavior -for the 'better' or for the 'worse'. The article further describes the process through which corporations could emancipate from the ethical norms prevailing in the broader society, and therefore develop an institution with specific norms and values. These norms mainly rely on mainstream business theories praising the economic actor's self-interest and neglecting moral reasoning. Moreover, because of isomorphism morality, many economic actors have changed their perception of ethics, and have abandoned the values prevailing in the broader society in order to adopt those of the economic theory. Finally, isomorphism morality also implies that these economic actors will change their morality again if the institutional context changes. The third article highlights the role and responsibility of business scholars in promoting a systematic reflection and self-critique of the business system and develops alternative models to fill the moral void of the business institution and its inherent legitimacy crisis. Indeed, the current business institution relies on assumptions such as scientific neutrality and specialization, which seem at least partly challenged by two factors. First, self-fulfilling prophecy provides scholars with an important (even if sometimes undesired) normative influence over practical life. Second, the increasing complexity of today's (socio-political) world and interactions between the different elements constituting our society question the strong specialization of science. For instance, economic theories are not unrelated to psychology or sociology, and economic actors influence socio-political structures and processes, e.g., through lobbying (Dobbs, 2006; Rondinelli, 2002), or through marketing which changes not only the way we consume, but more generally tries to instill a specific lifestyle (Cova, 2004; M. K. Hogg & Michell, 1996; McCracken, 1988; Muniz & O'Guinn, 2001). In consequence, business scholars are key actors in shaping both tomorrow's economic world and its broader context. A greater awareness of this influence might be a first step toward an increased feeling of civic responsibility and accountability for the models and theories developed or taught in business schools.