36 resultados para R12 - Size and Spatial Distributions of Regional Economic Activity


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Size and copy number of organelles are influenced by an equilibrium of membrane fusion and fission. We studied this equilibrium on vacuoles-the lysosomes of yeast. Vacuole fusion can readily be reconstituted and quantified in vitro, but it had not been possible to study fission of the organelle in a similar way. Here we present a cell-free system that reconstitutes fragmentation of purified yeast vacuoles (lysosomes) into smaller vesicles. Fragmentation in vitro reproduces physiological aspects. It requires the dynamin-like GTPase Vps1p, V-ATPase pump activity, cytosolic proteins, and ATP and GTP hydrolysis. We used the in vitro system to show that the vacuole-associated TOR complex 1 (TORC1) stimulates vacuole fragmentation but not the opposing reaction of vacuole fusion. Under nutrient restriction, TORC1 is inactivated, and the continuing fusion activity then dominates the fusion/fission equilibrium, decreasing the copy number and increasing the volume of the vacuolar compartment. This result can explain why nutrient restriction not only induces autophagy and a massive buildup of vacuolar/lysosomal hydrolases, but also leads to a concomitant increase in volume of the vacuolar compartment by coalescence of the organelles into a single large compartment.

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The development of statistical models for forensic fingerprint identification purposes has been the subject of increasing research attention in recent years. This can be partly seen as a response to a number of commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. In addition, key forensic identification bodies such as ENFSI [1] and IAI [2] have recently endorsed and acknowledged the potential benefits of using statistical models as an important tool in support of the fingerprint identification process within the ACE-V framework. In this paper, we introduce a new Likelihood Ratio (LR) model based on Support Vector Machines (SVMs) trained with features discovered via morphometric and spatial analyses of corresponding minutiae configurations for both match and close non-match populations often found in AFIS candidate lists. Computed LR values are derived from a probabilistic framework based on SVMs that discover the intrinsic spatial differences of match and close non-match populations. Lastly, experimentation performed on a set of over 120,000 publicly available fingerprint images (mostly sourced from the National Institute of Standards and Technology (NIST) datasets) and a distortion set of approximately 40,000 images, is presented, illustrating that the proposed LR model is reliably guiding towards the right proposition in the identification assessment of match and close non-match populations. Results further indicate that the proposed model is a promising tool for fingerprint practitioners to use for analysing the spatial consistency of corresponding minutiae configurations.

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Aim This study used data from temperate forest communities to assess: (1) five different stepwise selection methods with generalized additive models, (2) the effect of weighting absences to ensure a prevalence of 0.5, (3) the effect of limiting absences beyond the environmental envelope defined by presences, (4) four different methods for incorporating spatial autocorrelation, and (5) the effect of integrating an interaction factor defined by a regression tree on the residuals of an initial environmental model. Location State of Vaud, western Switzerland. Methods Generalized additive models (GAMs) were fitted using the grasp package (generalized regression analysis and spatial predictions, http://www.cscf.ch/grasp). Results Model selection based on cross-validation appeared to be the best compromise between model stability and performance (parsimony) among the five methods tested. Weighting absences returned models that perform better than models fitted with the original sample prevalence. This appeared to be mainly due to the impact of very low prevalence values on evaluation statistics. Removing zeroes beyond the range of presences on main environmental gradients changed the set of selected predictors, and potentially their response curve shape. Moreover, removing zeroes slightly improved model performance and stability when compared with the baseline model on the same data set. Incorporating a spatial trend predictor improved model performance and stability significantly. Even better models were obtained when including local spatial autocorrelation. A novel approach to include interactions proved to be an efficient way to account for interactions between all predictors at once. Main conclusions Models and spatial predictions of 18 forest communities were significantly improved by using either: (1) cross-validation as a model selection method, (2) weighted absences, (3) limited absences, (4) predictors accounting for spatial autocorrelation, or (5) a factor variable accounting for interactions between all predictors. The final choice of model strategy should depend on the nature of the available data and the specific study aims. Statistical evaluation is useful in searching for the best modelling practice. However, one should not neglect to consider the shapes and interpretability of response curves, as well as the resulting spatial predictions in the final assessment.

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An efficient screening strategy for the identification of potentially interesting low-abundance antifungal natural products in crude extracts that combines both a sensitive bioautography assay and high performance liquid chromatography (HPLC) microfractionation was developed. This method relies on high performance thin layer chromatography (HPTLC) bioautography with a hypersusceptible engineered strain of Candida albicans (DSY2621) for bioactivity detection, followed by the evaluation of wild type strains in standard microdilution antifungal assays. Active extracts were microfractionated by HPLC in 96-well plates, and the fractions were subsequently submitted to the bioassay. This procedure enabled precise localisation of the antifungal compounds directly in the HPLC chromatograms of the crude extracts. HPLC-PDA-mass spectrometry (MS) data obtained in parallel to the HPLC antifungal profiles provided a first chemical screening about the bioactive constituents. Transposition of the HPLC analytical conditions to medium-pressure liquid chromatography (MPLC) allowed the efficient isolation of the active constituents in mg amounts for structure confirmation and more extensive characterisation of their biological activities. The antifungal properties of the isolated natural products were evaluated by their minimum inhibitory concentration (MIC) in a dilution assay against both wild type and engineered strains of C. albicans. The biological activity of the most promising agents was further evaluated in vitro by electron microscopy and in vivo in a Galleria mellonella model of C. albicans infection. The overall procedure represents a rational and comprehensive means of evaluating antifungal activity from various perspectives for the selection of initial hits that can be explored in more in-depth mode-of-action studies. This strategy is illustrated by the identification and bioactivity evaluation of a series of antifungal compounds from the methanolic extract of a Rubiaceae plant, Morinda tomentosa, which was used as a model in these studies.

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OBJECTIVE: To investigate by electromyography (EMG), the presence of complex repetitive discharges (CRDs) and decelerating bursts (DBs) in the striated external urethral sphincter during the menstrual cycle in female volunteers with no urinary symptoms and complete bladder emptying. SUBJECTS AND METHODS: Healthy female volunteers aged 20-40 years, with regular menstrual cycles and no urinary symptoms were recruited. Volunteers completed a menstruation chart, urinary symptom questionnaires, pregnancy test, urine dipstick, urinary free flow and post-void ultrasound bladder scan. Exclusion criteria included current pregnancy, use of hormonal medication or contraception, body mass index of >35 kg/m(2) , incomplete voiding and a history of pelvic surgery. Eligible participants underwent an external urethral sphincter EMG, using a needle electrode in the early follicular phase and the mid-luteal phase of their menstrual cycles. Serum oestradiol and progesterone were measured at each EMG test. RESULTS: In all, 119 women enquired about the research and following screening, 18 were eligible to enter the study phase. Complete results were obtained in 15 women. In all, 30 EMG tests were undertaken in the 15 asymptomatic women. Sphincter EMG was positive for CRDs and DBs at one or both phases of the menstrual cycle in eight (53%) of the women. Three had CRDs and DBs in both early follicular and mid-luteal phases. Five had normal EMG activity in the early follicular phase and CRDs and DBs in the mid-luteal phase. No woman had abnormal EMG activity in the early follicular phase and normal activity in the luteal phase. There was no relationship between EMG activity and age, parity or serum levels of oestradiol and progesterone. CONCLUSIONS: CRDs and DB activity in the external striated urethral sphincter is present in a high proportion of asymptomatic young women. This abnormal EMG activity has been shown for the first time to change during the menstrual cycle in individual women. CRDs and DBs are more commonly found in the luteal phase of the menstrual cycle. The importance of CRDs and DBs in the aetiology of urinary retention in young women remains uncertain. The distribution and or quantity of abnormal EMG activity in the external urethral sphincter may be important. In a woman with urinary retention the finding of CRDs and DBs by needle EMG does not automatically establish Fowler's syndrome as the explanation for the bladder dysfunction. Urethral pressure profilometry may be helpful in establishing a diagnosis. Opiate use and psychological stress should be considered in young women with urinary retention.

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A major challenge in community ecology is a thorough understanding of the processes that govern the assembly and composition of communities in time and space. The growing threat of climate change to the vascular plant biodiversity of fragile ecosystems such as mountains has made it equally imperative to develop comprehensive methodologies to provide insights into how communities are assembled. In this perspective, the primary objective of this PhD thesis is to contribute to the theoretical and methodological development of community ecology, by proposing new solutions to better detect the ecological and evolutionary processes that govern community assembly. As phylogenetic trees provide by far, the most advanced tools to integrate the spatial, ecological and evolutionary dynamics of plant communities, they represent the cornerstone on which this work was based. In this thesis, I proposed new solutions to: (i) reveal trends in community assembly on phylogenies, depicted by the transition of signals at the nodes of the different species and lineages responsible for community assembly, (ii) contribute to evidence the importance of evolutionarily labile traits in the distribution of mountain plant species. More precisely, I demonstrated that phylogenetic and functional compositional turnover in plant communities was driven by climate and human land use gradients mostly influenced by evolutionarily labile traits, (iii) predict and spatially project the phylogenetic structure of communities using species distribution models, to identify the potential distribution of phylogenetic diversity, as well as areas of high evolutionary potential along elevation. The altitudinal setting of the Diablerets mountains (Switzerland) provided an appropriate model for this study. The elevation gradient served as a compression of large latitudinal variations similar to a collection of islands within a single area, and allowed investigations on a large number of plant communities. Overall, this thesis highlights that stochastic and deterministic environmental filtering processes mainly influence the phylogenetic structure of plant communities in mountainous areas. Negative density-dependent processes implied through patterns of phylogenetic overdispersion were only detected at the local scale, whereas environmental filtering implied through phylogenetic clustering was observed at both the regional and local scale. Finally, the integration of indices of phylogenetic community ecology with species distribution models revealed the prospects of providing novel and insightful explanations on the potential distribution of phylogenetic biodiversity in high mountain areas. These results generally demonstrate the usefulness of phylogenies in inferring assembly processes, and are worth considering in the theoretical and methodological development of tools to better understand phylogenetic community structure.

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Abstract : The existence of a causal relationship between the spatial distribution of living organisms and their environment, in particular climate, has been long recognized and is the central principle of biogeography. In turn, this recognition has led scientists to the idea of using the climatic, topographic, edaphic and biotic characteristics of the environment to predict its potential suitability for a given species or biological community. In this thesis, my objective is to contribute to the development of methodological improvements in the field of species distribution modeling. More precisely, the objectives are to propose solutions to overcome limitations of species distribution models when applied to conservation biology issues, or when .used as an assessment tool of the potential impacts of global change. The first objective of my thesis is to contribute to evidence the potential of species distribution models for conservation-related applications. I present a methodology to generate pseudo-absences in order to overcome the frequent lack of reliable absence data. I also demonstrate, both theoretically (simulation-based) and practically (field-based), how species distribution models can be successfully used to model and sample rare species. Overall, the results of this first part of the thesis demonstrate the strong potential of species distribution models as a tool for practical applications in conservation biology. The second objective this thesis is to contribute to improve .projections of potential climate change impacts on species distributions, and in particular for mountain flora. I develop and a dynamic model, MIGCLIM, that allows the implementation of dispersal limitations into classic species distribution models and present an application of this model to two virtual species. Given that accounting for dispersal limitations requires information on seed dispersal, distances, a general methodology to classify species into broad dispersal types is also developed. Finally, the M~GCLIM model is applied to a large number of species in a study area of the western Swiss Alps. Overall, the results indicate that while dispersal limitations can have an important impact on the outcome of future projections of species distributions under climate change scenarios, estimating species threat levels (e.g. species extinction rates) for a mountainous areas of limited size (i.e. regional scale) can also be successfully achieved when considering dispersal as unlimited (i.e. ignoring dispersal limitations, which is easier from a practical point of view). Finally, I present the largest fine scale assessment of potential climate change impacts on mountain vegetation that has been carried-out to date. This assessment involves vegetation from 12 study areas distributed across all major western and central European mountain ranges. The results highlight that some mountain ranges (the Pyrenees and the Austrian Alps) are expected to be more affected by climate change than others (Norway and the Scottish Highlands). The results I obtain in this study also indicate that the threat levels projected by fine scale models are less severe than those derived from coarse scale models. This result suggests that some species could persist in small refugias that are not detected by coarse scale models. Résumé : L'existence d'une relation causale entre la répartition des espèces animales et végétales et leur environnement, en particulier le climat, a été mis en évidence depuis longtemps et est un des principes centraux en biogéographie. Ce lien a naturellement conduit à l'idée d'utiliser les caractéristiques climatiques, topographiques, édaphiques et biotiques de l'environnement afin d'en prédire la qualité pour une espèce ou une communauté. Dans ce travail de thèse, mon objectif est de contribuer au développement d'améliorations méthodologiques dans le domaine de la modélisation de la distribution d'espèces dans le paysage. Plus précisément, les objectifs sont de proposer des solutions afin de surmonter certaines limitations des modèles de distribution d'espèces dans des applications pratiques de biologie de la conservation ou dans leur utilisation pour évaluer l'impact potentiel des changements climatiques sur l'environnement. Le premier objectif majeur de mon travail est de contribuer à démontrer le potentiel des modèles de distribution d'espèces pour des applications pratiques en biologie de la conservation. Je propose une méthode pour générer des pseudo-absences qui permet de surmonter le problème récurent du manque de données d'absences fiables. Je démontre aussi, de manière théorique (par simulation) et pratique (par échantillonnage de terrain), comment les modèles de distribution d'espèces peuvent être utilisés pour modéliser et améliorer l'échantillonnage des espèces rares. Ces résultats démontrent le potentiel des modèles de distribution d'espèces comme outils pour des applications de biologie de la conservation. Le deuxième objectif majeur de ce travail est de contribuer à améliorer les projections d'impacts potentiels des changements climatiques sur la flore, en particulier dans les zones de montagnes. Je développe un modèle dynamique de distribution appelé MigClim qui permet de tenir compte des limitations de dispersion dans les projections futures de distribution potentielle d'espèces, et teste son application sur deux espèces virtuelles. Vu que le fait de prendre en compte les limitations dues à la dispersion demande des données supplémentaires importantes (p.ex. la distance de dispersion des graines), ce travail propose aussi une méthode de classification simplifiée des espèces végétales dans de grands "types de disperseurs", ce qui permet ainsi de d'obtenir de bonnes approximations de distances de dispersions pour un grand nombre d'espèces. Finalement, j'applique aussi le modèle MIGCLIM à un grand nombre d'espèces de plantes dans une zone d'études des pré-Alpes vaudoises. Les résultats montrent que les limitations de dispersion peuvent avoir un impact considérable sur la distribution potentielle d'espèces prédites sous des scénarios de changements climatiques. Cependant, quand les modèles sont utilisés pour évaluer les taux d'extinction d'espèces dans des zones de montages de taille limitée (évaluation régionale), il est aussi possible d'obtenir de bonnes approximations en considérant la dispersion des espèces comme illimitée, ce qui est nettement plus simple d'un point dé vue pratique. Pour terminer je présente la plus grande évaluation à fine échelle d'impact potentiel des changements climatiques sur la flore des montagnes conduite à ce jour. Cette évaluation englobe 12 zones d'études réparties sur toutes les chaines de montages principales d'Europe occidentale et centrale. Les résultats montrent que certaines chaines de montagnes (les Pyrénées et les Alpes Autrichiennes) sont projetées comme plus sensibles aux changements climatiques que d'autres (les Alpes Scandinaves et les Highlands d'Ecosse). Les résultats obtenus montrent aussi que les modèles à échelle fine projettent des impacts de changement climatiques (p. ex. taux d'extinction d'espèces) moins sévères que les modèles à échelle large. Cela laisse supposer que les modèles a échelle fine sont capables de modéliser des micro-niches climatiques non-détectées par les modèles à échelle large.

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Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S-SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient.Location Two study areas in the Alps of Switzerland.Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S-SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways - summing binary predictions, summing random draws of binomial trials and summing predicted probabilities - to obtain a final species count.Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S-SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump-shaped pattern of SR observed along the elevational gradient. The S-SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S-SDM approaches the summed binomial trials based on predicted probabilities and summed predicted probabilities - do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S-SDM approaches fail to appropriately reproduce the observed hump-shaped patterns of SR along the elevational gradient.Main conclusions Macroecological approach and S-SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S-SDM by MEM predictions.

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Language is typically a function of the left hemisphere but the right hemisphere is also essential in some healthy individuals and patients. This inter-subject variability necessitates the localization of language function, at the individual level, prior to neurosurgical intervention. Such assessments are typically made by comparing left and right hemisphere language function to determine "language lateralization" using clinical tests or fMRI. Here, we show that language function needs to be assessed at the region and hemisphere specific level, because laterality measures can be misleading. Using fMRI data from 82 healthy participants, we investigated the degree to which activation for a semantic word matching task was lateralized in 50 different brain regions and across the entire cortex. This revealed two novel findings. First, the degree to which language is lateralized across brain regions and between subjects was primarily driven by differences in right hemisphere activation rather than differences in left hemisphere activation. Second, we found that healthy subjects who have relatively high left lateralization in the angular gyrus also have relatively low left lateralization in the ventral precentral gyrus. These findings illustrate spatial heterogeneity in language lateralization that is lost when global laterality measures are considered. It is likely that the complex spatial variability we observed in healthy controls is more exaggerated in patients with brain damage. We therefore highlight the importance of investigating within hemisphere regional variations in fMRI activation, prior to neuro-surgical intervention, to determine how each hemisphere and each region contributes to language processing. Hum Brain Mapp, 2010. © 2010 Wiley-Liss, Inc.

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Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km(2) to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

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THESIS ABSTRACT Nucleation and growth of metamorphic minerals are the consequence of changing P-T-X-conditions. The thesis presented here focuses on processes governing nucleation and growth of minerals in contact metamorphic environments using a combination of geochemical analytics (chemical-, isotope-, and trace element composition), statistical treatments of spatial data, and numerical models. It is shown, that a combination of textural modeling and stable isotope analysis allows a distinction between several possible reaction paths for olivine growth in a siliceous dolomite contact aureole. It is suggested that olivine forms directly from dolomite and quartz. The formation of olivine from this metastable reaction implies metamorphic crystallization far from equilibrium. As a major consequence, the spatial distribution of metamorphic mineral assemblages in a contact aureole cannot be interpreted as a proxy for the temporal evolution of a single rock specimen, because each rock undergoes a different reaction path, depending on temperature, heating rate, and fluid-infiltration rate. A detailed calcite-dolomite thermometry study was initiated on multiple scales ranging from aureole scale to the size of individual crystals. Quantitative forward models were developed to evaluate the effect of growth zoning, volume diffusion and the formation of submicroscopic exsolution lamellae (<1 µm) on the measured Mg-distribution in individual calcite crystals and compare the modeling results to field data. This study concludes that Mg-distributions in calcite grains of the Ubehebe Peak contact aureole are the consequence of rapid crystal growth in combination with diffusion and exsolution. The crystallization history of a rock is recorded in the chemical composition, the size and the distribution of its minerals. Near the Cima Uzza summit, located in the southern Adamello massif (Italy), contact metamorphic brucite bearing dolomite marbles are exposed as xenoliths surrounded by mafic intrusive rocks. Brucite is formed retrograde pseudomorphing spherical periclase crystals. Crystal size distributions (CSD's) of brucite pseudomorphs are presented for two profiles and combined with geochemistry data and petrological information. Textural analyses are combined with geochemistry data in a qualitative model that describes the formation periclase. As a major outcome, this expands the potential use of CSD's to systems of mineral formation driven by fluid-infiltration. RESUME DE LA THESE La nucléation et la croissance des minéraux métamorphiques sont la conséquence de changements des conditions de pression, température et composition chimique du système (PT-X). Cette thèse s'intéresse aux processus gouvernant la nucléation et la croissance des minéraux au cours d'un épisode de métamorphisme de contact, en utilisant la géochimie analytique (composition chimique, isotopique et en éléments traces), le traitement statistique des données spatiales et la modélisation numérique. Il est montré que la combinaison d'un modèle textural avec des analyses en isotopes stables permet de distinguer plusieurs chemins de réactions possibles conduisant à la croissance de l'olivine dans une auréole de contact riche en Silice et dolomite. Il est suggéré que l'olivine se forme directement à partir de la dolomie et du quartz. Cette réaction métastable de formation de l'olivine implique une cristallisation métamorphique loin de l'équilibre. La principale conséquence est que la distribution spatiale des assemblages de minéraux métamorphiques dans une auréole de contact ne peut pas être considérée comme un témoin de l'évolution temporelle d'un type de roche donné, puisque chaque type de roche suit différents chemins de réactions, en fonction de la température, la vitesse de réchauffement et le taux d'infiltration du fluide. Une étude thermométrique calcite-dolomite détaillée a été réalisée à diverses échelles, depuis l'échelle de l'auréole de contact jusqu'à l'échelle du cristal. Des modèles numériques quantitatifs ont été développés pour évaluer l'effet des zonations de croissance, de la diffusion volumique et de la formation de lamelles d'exsolution submicroscopiques (<1µm) sur la distribution du magnésium mesuré dans des cristaux de calcite individuels. Les résultats de ce modèle ont été comparés ä des échantillons naturels. Cette étude montre que la distribution du Mg dans les grains de calcite de l'auréole de contact de l'Ubehebe Peak (USA) résulte d'une croissance cristalline rapide, associée aux processus de diffusion et d'exsolution. L'histoire de cristallisation d'une roche est enregistrée dans la composition chimique, la taille et la distribution de ses minéraux. Près du sommet Cima Uzza situé au sud du massif d'Adamello (Italie), des marbres dolomitiques à brucite du métamorphisme de contact forment des xénolithes dans une intrusion mafique. La brucite constitue des pseudomorphes rétrogrades du périclase. Les distributions de taille des cristaux (CSD) des pseudomorphes de brucite sont présentées pour deux profiles et sont combinées aux données géochimiques et pétrologiques. Les analyses textorales sont combinées aux données géochimiques dans un modèle qualitatif qui décrit la formation du périclase. Ceci élargit l'utilisation potentielle de la C5D aux systèmes de formation de minéraux controlés par les infiltrations fluides. THESIS ABSTRACT (GENERAL PUBLIC) Rock textures are essentially the result of a complex interaction of nucleation, growth and deformation as a function of changing physical conditions such as pressure and temperature. Igneous and metamorphic textures are especially attractive to study the different mechanisms of texture formation since most of the parameters like pressure-temperature-paths are quite well known for a variety of geological settings. The fact that textures are supposed to record the crystallization history of a rock traditionally allowed them to be used for geothermobarometry or dating. During the last decades the focus of metamorphic petrology changed from a static point of view, i.e. the representation of a texture as one single point in the petrogenetic grid towards a more dynamic view, where multiple metamorphic processes govern the texture formation, including non-equilibrium processes. This thesis tries to advance our understanding on the processes governing nucleation and growth of minerals in contact metamorphic environments and their dynamic interplay by using a combination of geochemical analyses (chemical-, isotope-, and trace element composition), statistical treatments of spatial data and numerical models. In a first part the thesis describes the formation of metamorphic olivine porphyroblast in the Ubehebe Peak contact aureole (USA). It is shown that not the commonly assumed succession of equilibrium reactions along a T-t-path formed the textures present in the rocks today, but rather the presence of a meta-stable reaction is responsible for forming the olivine porphyroblast. Consequently, the spatial distribution of metamorphic minerals within a contact aureole can no longer be regarded as a proxy for the temporal evolution of a single rock sample. Metamorphic peak temperatures for samples of the Ubehebe Peak contact aureole were determined using calcite-dolomite. This geothermometer is based on the temperature-dependent exchange of Mg between calcite and dolomite. The purpose of the second part of this thesis was to explain the interfering systematic scatter of measured Mg-content on different scales and thus to clarify the interpretation of metamorphic temperatures recorded in carbonates. Numerical quantitative forward models are used to evaluate the effect of several processes on the distribution of magnesium in individual calcite crystals and the modeling results were then compared to measured field. Information about the crystallization history is not only recorded in the chemical composition of grains, like isotope composition or mineral zoning. Crystal size distributions (CSD's) provide essential information about the complex interaction of nucleation and growth of minerals. CSD's of brucite pseudomorphs formed retrograde after periclase of the southern Adamello massif (Italy) are presented. A combination of the textural 3D-information with geochemistry data is then used to evaluate reaction kinetics and to constrain the actual reaction mechanism for the formation of periclase. The reaction is shown to be the consequence of the infiltration of a limited amount of a fluid phase at high temperatures. The composition of this fluid phase is in large disequilibrium with the rest of the rock resulting in very fast reaction rates. RESUME DE LA THESE POUR LE GRAND PUBLIC: La texture d'une roche résulte de l'interaction complexe entre les processus de nucléation, croissance et déformation, en fonction des variations de conditions physiques telles que la pression et la température. Les textures ignées et métamorphiques présentent un intérêt particulier pour l'étude des différents mécanismes à l'origine de ces textures, puisque la plupart des paramètres comme les chemin pression-température sont relativement bien contraints dans la plupart des environnements géologiques. Le fait que les textures soient supposées enregistrer l'histoire de cristallisation des roches permet leur utilisation pour la datation et la géothermobarométrie. Durant les dernières décennies, la recherche en pétrologie métamorphique a évolué depuis une visualisation statique, c'est-à-dire qu'une texture donnée correspondait à un point unique de la grille pétrogénétique, jusqu'à une visualisation plus dynamique, où les multiples processus métamorphiques qui gouvernent 1a formation d'une texture incluent des processus hors équilibre. Cette thèse a pour but d'améliorer les connaissances actuelles sur les processus gouvernant la nucléation et la croissance des minéraux lors d'épisodes de métamorphisme de contact et l'interaction dynamique existant entre nucléation et croissance. Pour cela, les analyses géochimiques (compositions chimiques en éléments majeurs et traces et composition isotopique), le traitement statistique des données spatiales et la modélisation numérique ont été combinés. Dans la première partie, cette thèse décrit la formation de porphyroblastes d'olivine métamorphique dans l'auréole de contact de l'Ubehebe Peak (USA). Il est montré que la succession généralement admise des réactions d'équilibre le long d'un chemin T-t ne peut pas expliquer les textures présentes dans les roches aujourd'hui. Cette thèse montre qu'il s'agirait plutôt d'une réaction métastable qui soit responsable de la formation des porphyroblastes d'olivine. En conséquence, la distribution spatiale des minéraux métamorphiques dans l'auréole de contact ne peut plus être interprétée comme le témoin de l'évolution temporelle d'un échantillon unique de roche. Les pics de température des échantillons de l'auréole de contact de l'Ubehebe Peak ont été déterminés grâce au géothermomètre calcite-dolomite. Celui-ci est basé sur l'échange du magnésium entre la calcite et la dolomite, qui est fonction de la température. Le but de la deuxième partie de cette thèse est d'expliquer la dispersion systématique de la composition en magnésium à différentes échelles, et ainsi d'améliorer l'interprétation des températures du métamorphisme enregistrées dans les carbonates. Des modèles numériques quantitatifs ont permis d'évaluer le rôle de différents processus sur la distribution du magnésium dans des cristaux de calcite individuels. Les résultats des modèles ont été comparés aux échantillons naturels. La composition chimique des grains, comme la composition isotopique ou la zonation minérale, n'est pas le seul témoin de l'histoire de la cristallisation. La distribution de la taille des cristaux (CSD) fournit des informations essentielles sur les interactions entre nucléation et croissance des minéraux. La CSD des pseudomorphes de brucite retrograde formés après le périclase dans le sud du massif Adamello (Italie) est présentée dans la troisième partie. La combinaison entre les données textorales en trois dimensions et les données géochimiques a permis d'évaluer les cinétiques de réaction et de contraindre les mécanismes conduisant à la formation du périclase. Cette réaction est présentée comme étant la conséquence de l'infiltration d'une quantité limitée d'une phase fluide à haute température. La composition de cette phase fluide est en grand déséquilibre avec le reste de la roche, ce qui permet des cinétiques de réactions très rapides.

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Understanding factors that shape ranges of species is central in evolutionary biology. Species distribution models have become important tools to test biogeographical, ecological and evolutionary hypotheses. Moreover, from an ecological and evolutionary perspective, these models help to elucidate the spatial strategies of species at a regional scale. We modelled species distributions of two phylogenetically, geographically and ecologically close Tupinambis species (Teiidae) that occupy the southernmost area of the genus distribution in South America. We hypothesized that similarities between these species might have induced spatial strategies at the species level, such as niche differentiation and divergence of distribution patterns at a regional scale. Using logistic regression and MaxEnt we obtained species distribution models that revealed interspecific differences in habitat requirements, such as environmental temperature, precipitation and altitude. Moreover, the models obtained suggest that although the ecological niches of Tupinambis merianae and T. rufescens are different, these species might co-occur in a large contact zone. We propose that niche plasticity could be the mechanism enabling their co-occurrence. Therefore, the approach used here allowed us to understand the spatial strategies of two Tupinambis lizards at a regional scale.

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We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.

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The loss of biodiversity has become a matter of urgent concern and a better understanding of local drivers is crucial for conservation. Although environmental heterogeneity is recognized as an important determinant of biodiversity, this has rarely been tested using field data at management scale. We propose and provide evidence for the simple hypothesis that local species diversity is related to spatial environmental heterogeneity. Species partition the environment into habitats. Biodiversity is therefore expected to be influenced by two aspects of spatial heterogeneity: 1) the variability of environmental conditions, which will affect the number of types of habitat, and 2) the spatial configuration of habitats, which will affect the rates of ecological processes, such as dispersal or competition. Earlier, simulation experiments predicted that both aspects of heterogeneity will influence plant species richness at a particular site. For the first time, these predictions were tested for plant communities using field data, which we collected in a wooded pasture in the Swiss Jura mountains using a four-level hierarchical sampling design. Richness generally increased with increasing environmental variability and "roughness" (i.e. decreasing spatial aggregation). Effects occurred at all scales, but the nature of the effect changed with scale, suggesting a change in the underlying mechanisms, which will need to be taken into account if scaling up to larger landscapes. Although we found significant effects of environmental heterogeneity, other factors such as history could also be important determinants. If a relationship between environmental heterogeneity and species richness can be shown to be general, recently available high-resolution environmental data can be used to complement the assessment of patterns of local richness and improve the prediction of the effects of land use change based on mean site conditions or land use history.