Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Trimestralización y conciliación de magnitudes económicas : una ampliación del método Chow-Lin

Una de las herramientas estadísticas más importantes para el seguimiento y análisis de la evolución de la actividad económica a corto plazo es la disponibilidad de estimaciones de la evolución trimestral de los componentes del PIB, en lo que afecta tanto a la oferta como a la demanda. La necesidad de disponer de esta información con un retraso temporal reducido hace imprescindible la utilización de métodos de trimestralización que permitan desagregar la información anual a trimestral. El método más aplicado, puesto que permite resolver este problema de manera muy elegante bajo un enfoque estadístico de estimador óptimo, es el método de Chow-Lin. Pero este método no garantiza que las estimaciones trimestrales del PIB en lo que respecta a la oferta y a la demanda coincidan, haciendo necesaria la aplicación posterior de algún método de conciliación. En este trabajo se desarrolla una ampliación multivariante del método de Chow-Lin que permite resolver el problema de la estimación de los valores trimestrales de manera óptima, sujeta a un conjunto de restricciones. Una de las aplicaciones potenciales de este método, que hemos denominado método de Chow-Lin restringido, es precisamente la estimación conjunta de valores trimestrales para cada uno de los componentes del PIB en lo que afecta tanto a la demanda como a la oferta condicionada a que ambas estimaciones trimestrales del PIB sean iguales, evitando así la necesidad de aplicar posteriormente métodos de conciliación

Identifying the socioeconomic determinants of crime in Spanish provinces

In this paper we study, having as theoretical reference the economic model of crime (Becker, 1968; Ehrlich, 1973), which are the socioeconomic and demographic determinants of crime in Spain paying attention on the role of provincial peculiarities. We estimate a crime equation using a panel dataset of Spanish provinces (NUTS3) for the period 1993 to 1999 employing the GMMsystem estimator. Empirical results suggest that lagged crime rate and clear-up rate are correlated to all typologies of crime rate considered. Property crimes are better explained by socioeconomic variables (GDP per capita, GDP growth rate and percentage of population with high school and university degree), while demographic factors reveal important and significant influences, in particular for crimes against the person. These results are obtained using an instrumental variable approach that takes advantage of the dynamic properties of our dataset to control for both measurement errors in crime data and joint endogeneity of the explanatory variables

Evolution of source EEG synchronization in early Alzheimer's disease.

Alzheimer's disease (AD) disrupts functional connectivity in distributed cortical networks. We analyzed changes in the S-estimator, a measure of multivariate intraregional synchronization, in electroencephalogram (EEG) source space in 15 mild AD patients versus 15 age-matched controls to evaluate its potential as a marker of AD progression. All participants underwent 2 clinical evaluations and 2 EEG recording sessions on diagnosis and after a year. The main effect of AD was hyposynchronization in the medial temporal and frontal regions and relative hypersynchronization in posterior cingulate, precuneus, cuneus, and parietotemporal cortices. However, the S-estimator did not change over time in either group. This result motivated an analysis of rapidly progressing AD versus slow-progressing patients. Rapidly progressing AD patients showed a significant reduction in synchronization with time, manifest in left frontotemporal cortex. Thus, the evolution of source EEG synchronization over time is correlated with the rate of disease progression and should be considered as a cost-effective AD biomarker.

From the Apennines to the Alps: colonization genetics of the naturally expanding Italian wolf (Canis lupus) population

Wolves in Italy strongly declined in the past and were confined south of the Alps since the turn of the last century, reduced in the 1970s to approximately 100 individuals surviving in two fragmented subpopulations in the central-southern Apennines. The Italian wolves are presently expanding in the Apennines, and started to recolonize the western Alps in Italy, France and Switzerland about 16 years ago. In this study, we used a population genetic approach to elucidate some aspects of the wolf recolonization process. DNA extracted from 3068 tissue and scat samples collected in the Apennines (the source populations) and in the Alps (the colony), were genotyped at 12 microsatellite loci aiming to assess (i) the strength of the bottleneck and founder effects during the onset of colonization; (ii) the rates of gene flow between source and colony; and (iii) the minimum number of colonizers that are needed to explain the genetic variability observed in the colony. We identified a total of 435 distinct wolf genotypes, which showed that wolves in the Alps: (i) have significantly lower genetic diversity (heterozygosity, allelic richness, number of private alleles) than wolves in the Apennines; (ii) are genetically distinct using pairwise F(ST) values, population assignment test and Bayesian clustering; (iii) are not in genetic equilibrium (significant bottleneck test). Spatial autocorrelations are significant among samples separated up to c. 230 km, roughly correspondent to the apparent gap in permanent wolf presence between the Alps and north Apennines. The estimated number of first-generation migrants indicates that migration has been unidirectional and male-biased, from the Apennines to the Alps, and that wolves in southern Italy did not contribute to the Alpine population. These results suggest that: (i) the Alps were colonized by a few long-range migrating wolves originating in the north Apennine subpopulation; (ii) during the colonization process there has been a moderate bottleneck; and (iii) gene flow between sources and colonies was moderate (corresponding to 1.25-2.50 wolves per generation), despite high potential for dispersal. Bottleneck simulations showed that a total of c. 8-16 effective founders are needed to explain the genetic diversity observed in the Alps. Levels of genetic diversity in the expanding Alpine wolf population, and the permanence of genetic structuring, will depend on the future rates of gene flow among distinct wolf subpopulation fragments.

Land-use systems affect Archaeal community structure and functional diversity in western Amazon soils

The study of the ecology of soil microbial communities at relevant spatial scales is primordial in the wide Amazon region due to the current land use changes. In this study, the diversity of the Archaea domain (community structure) and ammonia-oxidizing Archaea (richness and community composition) were investigated using molecular biology-based techniques in different land-use systems in western Amazonia, Brazil. Soil samples were collected in two periods with high precipitation (March 2008 and January 2009) from Inceptisols under primary tropical rainforest, secondary forest (5-20 year old), agricultural systems of indigenous people and cattle pasture. Denaturing gradient gel electrophoresis of polymerase chain reaction-amplified DNA (PCR-DGGE) using the 16S rRNA gene as a biomarker showed that archaeal community structures in crops and pasture soils are different from those in primary forest soil, which is more similar to the community structure in secondary forest soil. Sequence analysis of excised DGGE bands indicated the presence of crenarchaeal and euryarchaeal organisms. Based on clone library analysis of the gene coding the subunit of the enzyme ammonia monooxygenase (amoA) of Archaea (306 sequences), the Shannon-Wiener function and Simpson's index showed a greater ammonia-oxidizing archaeal diversity in primary forest soils (H' = 2.1486; D = 0.1366), followed by a lower diversity in soils under pasture (H' = 1.9629; D = 0.1715), crops (H' = 1.4613; D = 0.3309) and secondary forest (H' = 0.8633; D = 0.5405). All cloned inserts were similar to the Crenarchaeota amoA gene clones (identity > 95 %) previously found in soils and sediments and distributed primarily in three major phylogenetic clusters. The findings indicate that agricultural systems of indigenous people and cattle pasture affect the archaeal community structure and diversity of ammonia-oxidizing Archaea in western Amazon soils.

Functionally and phylogenetically diverse plant communities key to soil biota

Recent studies assessing the role of biological diversity for ecosystem functioning indicate that the diversity of functional traits and the evolutionary history of species in a community, not the number of taxonomic units, ultimately drives the biodiversity-ecosystem-function relationship. Here, we simultaneously assessed the importance of plant functional trait and phylogenetic diversity as predictors of major trophic groups of soil biota (abundance and diversity), six years from the onset of a grassland biodiversity experiment. Plant functional and phylogenetic diversity were generally better predictors of soil biota than the traditionally used species or functional group richness. Functional diversity was a reliable predictor for most biota, with the exception of soil microorganisms, which were better predicted by phylogenetic diversity. These results provide empirical support for the idea that the diversity of plant functional traits and the diversity of evolutionary lineages in a community are important for maintaining higher abundances and diversity of soil communities.

Soil fauna as an indicator of soil quality in forest stands, pasture and secondary forest

The interactions between soil invertebrates and environmental variations are relatively unknown in the assessment of soil quality. The objective of this study was to evaluate soil quality in areas with different soil management systems, based on soil fauna as indicator, in Além Paraíba, Minas Gerais, Brazil. The soil invertebrate community was sampled using pitfall traps, in the dry and rainy seasons, from areas with five vegetation types (acacia, mimosa, eucalyptus, pasture, and secondary forest). The abundance of organisms and the total and average richness, Shannon's diversity index, the Pielou uniformity index, and change index V were determined. The fauna was most abundant in the areas of secondary forest and mimosa plantations in the dry season (111.3 and 31.7 individuals per trap per day, respectively). In the rainy season, the abundance of organisms in the three vegetation types did not differ. The highest values of average and total richness were recorded in the secondary forest in the dry season and in the mimosa stand in the rainy season. Shannon's index ranged from 1.57 in areas with acacia and eucalyptus in the rainy season to 3.19 in the eucalyptus area in the dry season. The uniformity index was highest in forest stands (eucalyptus, acacia and mimosa) in the dry season, but higher in the rainy season in the pasture and secondary forest than in the forest stands. The change index V indicated that the percentage of extremely inhibited groups was lowest in the area with mimosa, both in the dry and rainy season (36 and 23 %, respectively). Of all forest stands, the mimosa area had the most abundant soil fauna.

Influence of mineral fertilization on edaphic fauna in Acacia auriculiformis (A. Cunn) plantations

Fertilization and/or the accumulation of organic matter from plant residues can influence the composition of soil and litter community. The goal of this study was to evaluate the effects of P and K fertilization on total faunal and nematode faunal composition and richness in plant litter and soil for 360 days in an area reforested with Acacia auriculiformis (A. Cunn), located in the municipality of Conceição de Macabu in the State of Rio de Janeiro. For each treatment (fertilized and unfertilized plots), samples of litter and soil (to a depth of 5 cm) were collected and transferred into a Berlese-Tüllgren funnels for the extraction of fauna. Mesofauna and macrofauna were quantified, and the major taxa identified. Nematodes were extracted by centrifugal flotation in sucrose solution and identified according to feeding habits. Density (number of individuals m-2) of total fauna, microphages, social insects and saprophages varied significantly per treatment and sampling time in both litter and soil. The total number of individuals collected was 5,127, and the total number of nematodes 894. Phosphorus and potassium fertilization resulted in an increase in total fauna density and richness in the litter due to an increased abundance of social insects, saprophages and herbivores. In the soil, fertilization increased the saprophage and predator densities. Saprophages were the predominant taxa in the litter, while social insects (Formicidae) prevailed in the soil. Litter nematode populations were favored by mineral fertilization. Bacteriophages were the predominant nematode group in both litter and soil.

Plant species distributions along environmental gradients: do belowground interactions with fungi matter?

The distribution of plants along environmental gradients is constrained by abiotic and biotic factors. Cumulative evidence attests of the impact of biotic factors on plant distributions, but only few studies discuss the role of belowground communities. Soil fungi, in particular, are thought to play an important role in how plant species assemble locally into communities. We first review existing evidence, and then test the effect of the number of soil fungal operational taxonomic units (OTUs) on plant species distributions using a recently collected dataset of plant and metagenomic information on soil fungi in the Western Swiss Alps. Using species distribution models (SDMs), we investigated whether the distribution of individual plant species is correlated to the number of OTUs of two important soil fungal classes known to interact with plants: the Glomeromycetes, that are obligatory symbionts of plants, and the Agaricomycetes, that may be facultative plant symbionts, pathogens, or wood decayers. We show that including the fungal richness information in the models of plant species distributions improves predictive accuracy. Number of fungal OTUs is especially correlated to the distribution of high elevation plant species. We suggest that high elevation soil show greater variation in fungal assemblages that may in turn impact plant turnover among communities. We finally discuss how to move beyond correlative analyses, through the design of field experiments manipulating plant and fungal communities along environmental gradients.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Environment and dispersal paths override life strategies and residence time in determining regional patterns of invasion by alien plants.

We describe a novel dissimilarity framework to analyze spatial patterns of species diversity and illustrate it with alien plant invasions in Northern Portugal. We used this framework to test the hypothesis that patterns of alien invasive plant species richness and composition are differently affected by differences in climate, land use and landscape connectivity (i.e. Geographic distance as a proxy and vectorial objects that facilitate dispersal such as roads and rivers) between pairs of localities at the regional scale. We further evaluated possible effects of plant life strategies (Grime's C-S-R) and residence time. Each locality consisted of a 1 km(2) landscape mosaic in which all alien invasive species were recorded by visiting all habitat types. Multi-model inference revealed that dissimilarity in species richness is more influenced by environmental distance (particularly climate), whereas geographic distance (proxies for dispersal limitations) is more important to explain dissimilarity in species composition, with a prevailing role for ecotones and roads. However, only minor differences were found in the responses of the three C-S-R strategies. Some effect of residence time was found, but only for dissimilarity in species richness. Our results also indicated that environmental conditions (e.g. climate conditions) limit the number of alien species invading a given site, but that the presence of dispersal corridors determines the paths of invasion and therefore the pool of species reaching each site. As geographic distances (e.g. ecotones and roads) tend to explain invasion at our regional scale highlights the need to consider the management of alien invasions in the context of integrated landscape planning. Alien species management should include (but not be limited to) the mitigation of dispersal pathways along linear infrastructures. Our results therefore highlight potentially useful applications of the novel multimodel framework to the anticipation and management of plant invasions. (C) 2013 Elsevier GmbH. All rights reserved.

Temporal and spatial dynamics of benthic invertebrate communities in an alpine glacier-fed alluvial system

Summary The present thesis work focused on the ecology of benthic invertebrates in the proglacial floodplain of the Rhone in the Swiss Alps. The main glacial Rhone River and a smaller glacial tributary, the Mutt River, joined and entered a braiding multi-thread area. A first part concentrated on the disruption of the longitudinal patterns of environmental conditions and benthic invertebrate fauna in the Rhone by its tributary the Mutt. The Mutt had less harsh environmental conditions, higher taxonomic richness and more abundant zoobenthos compared to the Rhone upstream of the confluence. Although the habitat conditions in the main stream were little modified by the tributary, the fauna was richer and more diverse below the confluence. Colonisation from the Mutt induced the occurrence of faunal elements uncommon of glacial streams in the upper Rhone, where water temperature remains below 4°C. Although the glacial Rhone dominated the system with regard to hydrology and certain environmental conditions, the Mutt tributary has to be seen as the faunal driver of the system. The second part of the study concerned the spatio-temporal differentiation of the habitats and the benthic communities along and across the flood plain. No longitudinal differentiation was found. The spatial transversal differentiation of three habitat types with different environmental characteristics was successfully reflected in the spatial variability of benthic assemblages. This typology separated marginal sites of the flood plain, left bank sites under the influence of the Mutt, and the right bank sites under the influence of the Rh6ne. Faunistic spatial differences were emphasized by the quantitative structure of the fauna, richness, abundances and Simpson index of diversity. Seasonal environmental variability was positively related with Simpson index of diversity and the total richness per site. Low flow conditions were the most favourable season for the fauna and November was characterized by low spatial environmental heterogeneity, high spatial heterogeneity of faunal assemblage, maximum taxonomic richness, a particular taxonomic composition, highest abundances, as well as the highest primary food resources. The third part studied the egg development of three species of Ephemeroptera in the laboratory at 1.5 to 7°C and the ecological implications in the field. Species revealed very contrasting development strategies. Baetis alpinus has a synchronous and efficient egg development, which is faster in warmer habitats, enabling it to exploit short periods of favourable conditions in the floodplain. Ecdyonurus picteti has a very long development time slightly decreasing in warmer conditions. The high degree of individual variation suggests a genetic determination of the degree-days demand. Combined with the glacial local conditions, this strategy leads to an extreme delay of hatching and allows it to develop in very unpredictable habitats. Rhithrogena nivata is the second cold adapted species in Ephemeroptera. The incubation duration is long and success largely depends on the timing of hatching and the discharge conditions. This species is able to exploit extremely unstable and cold habitats where other species are limited by low water temperatures. The fourth part dealt with larval development in different habitats of the floodplain. Addition of data on egg development allowed the description of the life histories of the species from oviposition until emergence. Rhithrogena nivata and loyolaea generally have a two-year development, with the first winter passed as eggs and the second one as larvae. Development of Ecdyonurus picteti is difficult to document but appears to be efficient in a harsh and unpredictable environment. Baetis alpinus was studied separately in four habitats of the floodplain system with contrasting thermal regimes. Differences in success and duration of larval development and in growth rates are emphasised. Subvention mechanisms between habitats by migration of young or grown larvae were demonstrated. Development success and persistence of the populations in the system were thus increased. Emergence was synchronised to the detriment of the optimisation of the adult's size and fecundity. These very different development strategies induce a spatial and temporal distribution in the use of food resources and ecological niches. The last part of this work aimed at the synthesis of the characteristics and the ecological features of three distinct compartments of the system that are the upper Rhone, the Mutt and the floodplain. Their particular role as well as their inter-dependence concerning the structure and the dynamics of the benthic communities was emphasised. Résumé Ce travail de thèse est consacré à l'écologie des invertébrés benthiques dans la zone alluviale proglaciaire du Rhône dans les Alpes suisses. Le Rhône, torrent glaciaire principal, reçoit les eaux de la Mutt, affluent glaciaire secondaire, puis pénètre dans une zone de tressage formée de plusieurs bras. La première partie de l'étude se concentre sur la disruption par la Mutt des processus longitudinaux, tant environnementaux que faunistiques, existants dans le Rhône. Les conditions environnementales régnant dans la Mutt sont moins rudes, la richesse taxonomique plus élevée et le zoobenthos plus abondant que dans le Rhône en amont de la confluence. Bien que les conditions environnementales dans le torrent principal soient peu modifiées par l'affluent, la faune s'avère être plus riche et plus diversifiée en aval de la confluence. La colonisation depuis la Mutt permet l'occurrence de taxons inhabituels dans le Rhône en amont de la confluence, où la température de l'eau se maintient en dessous de 4°C. Bien que le Rhône, torrent glaciaire principal, domine le système du point de vu de l'hydrologie et de certains paramètres environnementaux, l'affluent Mutt doit être considéré comme l'élément structurant la faune dans le système. La deuxième partie concerne la différentiation spatiale et temporelle des habitats et des communautés benthiques à travers la plaine alluviale. Aucune différentiation longitudinale n'a été mise en évidence. La différentiation transversale de trois types d'habitats sur la base des caractéristiques environnementales a été confirmée par la variabilité spatiale de la faune. Cette typologie sépare les sites marginaux de la plaine alluviale, ceux sous l'influence de la Mutt (en rive gauche) et ceux sous l'influence du Rhône amont (en rive droite). Les différences spatiales de la faune sont mises en évidence par la structure quantitative de la faune, la richesse, les abondances et l'indice de diversité de Simpson. La variabilité saisonnière du milieu est positivement liée avec l'indice de diversité de Simpson et la richesse totale par site. L'étiage correspond à la période la plus favorable pour la faune et novembre réunit des conditions de faible hétérogénéité spatiale du milieu, de forte hétérogénéité spatiale de la faune, une richesse taxonomique maximale, une composition faunistique particulière, les abondances ainsi que les ressources primaires les plus élevées. La troisième partie est consacrée à l'étude du développement des oeufs de trois espèces d'Ephémères au laboratoire à des températures de 1.5 à 7°C, ainsi qu'aux implications écologiques sur le terrain. Ces espèces présentent des stratégies de développement très contrastées. Baetis alpinus a un développement synchrone et efficace, plus rapide en milieu plus chaud et lui permettant d'exploiter les courtes périodes de conditions favorables. Ecdyonurus picteti présente une durée de développement très longue, diminuant légèrement dans des conditions plus chaudes. L'importante variation interindividuelle suggère un déterminisme génétique de la durée de développement. Cette stratégie, associée aux conditions locales, conduit à un décalage extrême des éclosions et permet à l'espèce de se développer dans des habitats imprévisibles. Rhithrogena nivata est la seconde espèce d'Ephémères présentant une adaptation au froid. L'incubation des oeufs est longue et son succès dépend de la période des éclosions et des conditions hydrologiques. Cette espèce est capable d'exploiter des habitats extrêmement instables et froids, où la température est facteur limitant pour d'autres espèces. La quatrième partie traite du développement larvaire dans différents habitats de la plaine alluviale. Le développement complet est décrit pour les espèces étudiées de la ponte jusqu'à l'émergence. Rhithrogena nivata et loyolaea atteignent généralement le stade adulte en deux ans, le premier hiver étant passé sous forme d'oeuf et le second sous forme de larve. Le développement de Ecdyonurus picteti est difficile à documenter, mais s'avère cependant efficace dans un environnement rude et imprévisible. Baetis alpinus a été étudié séparément dans quatre habitats de la plaine ayant des régimes thermiques contrastés. La réussite et la durée du développement embryonnaire ainsi que les taux de croissance y sont variables. Des mécanismes de subvention entre habitats sont possibles par la migration de larves juvéniles ou plus développées, augmentant ainsi la réussite du développement et le maintien des populations dans le système. L'émergence devient synchrone, au détriment de l'optimisation de la taille et de la fécondité des adultes. Ces stratégies très différentes induisent une distribution spatiale et temporelle dans l'usage des ressources et des niches écologiques. La dernière partie synthétise les caractéristiques écologiques des trois compartiments du système que sont le Rhône amont, la Mutt et la zone alluviale. Leurs rôles particuliers et leurs interdépendances du point de vue de la structure et de la dynamique des communautés benthiques sont mis en avant.

Linear least squares estimation of the first order moving average parameter

We propose an iterative procedure to minimize the sum of squares function which avoids the nonlinear nature of estimating the first order moving average parameter and provides a closed form of the estimator. The asymptotic properties of the method are discussed and the consistency of the linear least squares estimator is proved for the invertible case. We perform various Monte Carlo experiments in order to compare the sample properties of the linear least squares estimator with its nonlinear counterpart for the conditional and unconditional cases. Some examples are also discussed

Leadership at the upper echelons : three essays

"IT'S THE ECONOMY STUPID", BUT CHARISMA MATTERS TOO: A DUAL PROCESS MODEL OF PRESIDENTIAL ELECTION OUTCOMES. ABSTRACT Because charisma is assumed to be an important determinant of effective leadership, the extent to which a presidential nominee is more charismatic than his opponent should be an important determinant of voter choices. We computed a composite measure of the rhetorical richness of acceptances speeches given by U.S. presidential candidates at their national party convention. We added this marker of charisma to Ray C. Fair's presidential vote-share equation (1978; 2009). We theorized that voters decide using psychological attribution (i.e., due to macroeconomics and incumbency) as well as inferential processes (i.e., due to leader charismatic behavior) when voting. Controlling for the macro-level variables and incumbency in the Fair model, our results indicated that difference between nominees' charisma is a significant determinant of electoral success, particularly in close elections. This extended model significantly improves the precision of the Fair model and correctly predicts 23 out of the last 24 U.S. presidential elections. Paper 2: IT CEO LEADERSHIP, CORPORATE SOCIAL AND FINANCIAL PERFORMANCE. ABSTRACT We investigated whether CEO leadership predicted corporate financial performance (CFP) and corporate social performance (CSP). Using longitudinal data on 258 CEOs from 117 firms across 19 countries and 10 industry sectors, we found that determinants of CEO leadership (i.e., implicit motives) significantly predicted both CFP and CSP. As expected, the most consistent positive predictor was Responsibility Disposition when interacting with n (need for) Power. n Achievement and n Affiliation were generally negatively related or unrelated to outcomes. CSP was positively related to accounting measures of CFP. Our findings suggest that executive leader characteristics have important consequences for corporate level outcomes. Paper 3. PUNISHING THE POWERFUL: ATTRIBUTIONS OF BLAME AND LEADERSHIP ABSTRACT We propose that individuals are more lenient in attributing blame to leaders than to nonleaders. We advance a motivational explanation building on the perspective of punishment and on system justification theory. We conducted two scenario experiments which supported our proposition. In study 1, wrongdoer leader status was negatively related to blame and the perceived seriousness of the wrongdoing. In study 2, controlling for the Big-Five personality factor and individual differences in moral evaluation (i.e., moral foundations), wrongdoer leader status was negatively related with desired severity of punishment, and fair punishments were perceived as more just for non-leaders than for leaders.