Climate change effects on animal and plant phylogenetic diversity in southern Africa

Much attention has been paid to the effects of climate change on species' range reductions and extinctions. There is however surprisingly little information on how climate change driven threat may impact the tree of life and result in loss of phylogenetic diversity (PD). Some plant families and mammalian orders reveal nonrandom extinction patterns, but many other plant families do not. Do these discrepancies reflect different speciation histories and does climate induced extinction result in the same discrepancies among different groups? Answers to these questions require representative taxon sampling. Here, we combine phylogenetic analyses, species distribution modeling, and climate change projections on two of the largest plant families in the Cape Floristic Region (Proteaceae and Restionaceae), as well as the second most diverse mammalian order in Southern Africa (Chiroptera), and an herbivorous insect genus (Platypleura) in the family Cicadidae to answer this question. We model current and future species distributions to assess species threat levels over the next 70years, and then compare projected with random PD survival. Results for these animal and plant clades reveal congruence. PD losses are not significantly higher under predicted extinction than under random extinction simulations. So far the evidence suggests that focusing resources on climate threatened species alone may not result in disproportionate benefits for the preservation of evolutionary history.

Reforms of the pre-graduate curriculum for medical students: the Bologna process and beyond.

For several years, all five medical faculties of Switzerland have embarked on a reform of their training curricula for two reasons: first, according to a new federal act issued in 2006 by the administration of the confederation, faculties needed to meet international standards in terms of content and pedagogic approaches; second, all Swiss universities and thus all medical faculties had to adapt the structure of their curriculum to the frame and principles which govern the Bologna process. This process is the result of the Bologna Declaration of June 1999 which proposes and requires a series of reforms to make European Higher Education more compatible and comparable, more competitive and more attractive for Europeans students. The present paper reviews some of the results achieved in the field, focusing on several issues such as the shortage of physicians and primary care practitioners, the importance of public health, community medicine and medical humanities, and the implementation of new training approaches including e-learning and simulation. In the future, faculties should work on several specific challenges such as: students' mobility, the improvement of students' autonomy and critical thinking as well as their generic and specific skills and finally a reflection on how to improve the attractiveness of the academic career, for physicians of both sexes.

A flow cytometry based oligotrophic pollutant exposure test to detect bacterial growth inhibition and cell injury.

Toxicity of chemical pollutants in aquatic environments is often addressed by assays that inquire reproductive inhibition of test microorganisms, such as algae or bacteria. Those tests, however, assess growth of populations as a whole via macroscopic methods such as culture turbidity or colony-forming units. Here we use flow cytometry to interrogate the fate of individual cells in low-density populations of the bacterium Pseudomonas fluorescens SV3 exposed or not under oligotrophic conditions to a number of common pollutants, some of which derive from oil contamination. Cells were stained at regular time intervals during the exposure assay with fluorescent dyes that detect membrane injury (i.e., live-dead assay). Reduction of population growth rates was observed upon toxicant insult and depended on the type of toxicant. Modeling and cell staining indicate that population growth rate decrease is a combined effect of an increased number of injured cells that may or may not multiply, and live cells dividing at normal growth rates. The oligotrophic assay concept presented here could be a useful complement for existing biomarker assays in compliance with new regulations on chemical effect studies or, more specifically, for judging recovery after exposure to fluctuating toxicant conditions.

Evolutionary history and its relevance in understanding and conserving southern African biodiversity

Abstract : Understanding how biodiversity is distributed is central to any conservation effort and has traditionally been based on niche modeling and the causal relationship between spatial distribution of organisms and their environment. More recently, the study of species' evolutionary history and relatedness has permeated the fields of ecology and conservation and, coupled with spatial predictions, provides useful insights to the origin of current biodiversity patterns, community structuring and potential vulnerability to extinction. This thesis explores several key ecological questions by combining the fields of niche modeling and phylogenetics and using important components of southern African biodiversity. The aims of this thesis are to provide comparisons of biodiversity measures, to assess how climate change will affect evolutionary history loss, to ask whether there is a clear link between evolutionary history and morphology and to investigate the potential role of relatedness in macro-climatic niche structuring. The first part of my thesis provides a fine scale comparison and spatial overlap quantification of species richness and phylogenetic diversity predictions for one of the most diverse plant families in the Cape Floristic Region (CFR), the Proteaceae. In several of the measures used, patterns do not match sufficiently to argue that species relatedness information is implicit in species richness patterns. The second part of my thesis predicts how climate change may affect threat and potential extinction of southern African animal and plant taxa. I compare present and future niche models to assess whether predicted species extinction will result in higher or lower V phylogenetic diversity survival than what would be experienced under random extinction processes. l find that predicted extinction will result in lower phylogenetic diversity survival but that this non-random pattern will be detected only after a substantial proportion of the taxa in each group has been lost. The third part of my thesis explores the relationship between phylogenetic and morphological distance in southern African bats to assess whether long evolutionary histories correspond to equally high levels of morphological variation, as predicted by a neutral model of character evolution. I find no such evidence; on the contrary weak negative trends are detected for this group, as well as in simulations of both neutral and convergent character evolution. Finally, I ask whether spatial and climatic niche occupancy in southern African bats is influenced by evolutionary history or not. I relate divergence time between species pairs to climatic niche and range overlap and find no evidence for clear phylogenetic structuring. I argue that this may be due to particularly high levels of micro-niche partitioning. Résumé : Comprendre la distribution de la biodiversité représente un enjeu majeur pour la conservation de la nature. Les analyses se basent le plus souvent sur la modélisation de la niche écologique à travers l'étude des relations causales entre la distribution spatiale des organismes et leur environnement. Depuis peu, l'étude de l'histoire évolutive des organismes est également utilisée dans les domaines de l'écologie et de la conservation. En combinaison avec la modélisation de la distribution spatiale des organismes, cette nouvelle approche fournit des informations pertinentes pour mieux comprendre l'origine des patterns de biodiversité actuels, de la structuration des communautés et des risques potentiels d'extinction. Cette thèse explore plusieurs grandes questions écologiques, en combinant les domaines de la modélisation de la niche et de la phylogénétique. Elle s'applique aux composants importants de la biodiversité de l'Afrique australe. Les objectifs de cette thèse ont été l) de comparer différentes mesures de la biodiversité, 2) d'évaluer l'impact des changements climatiques à venir sur la perte de diversité phylogénétique, 3) d'analyser le lien potentiel entre diversité phylogénétique et diversité morphologique et 4) d'étudier le rôle potentiel de la phylogénie sur la structuration des niches macro-climatiques des espèces. La première partie de cette thèse fournit une comparaison spatiale, et une quantification du chevauchement, entre des prévisions de richesse spécifique et des prédictions de la diversité phylogénétique pour l'une des familles de plantes les plus riches en espèces de la région floristique du Cap (CFR), les Proteaceae. Il résulte des analyses que plusieurs mesures de diversité phylogénétique montraient des distributions spatiales différentes de la richesse spécifique, habituellement utilisée pour édicter des mesures de conservation. La deuxième partie évalue les effets potentiels des changements climatiques attendus sur les taux d'extinction d'animaux et de plantes de l'Afrique australe. Pour cela, des modèles de distribution d'espèces actuels et futurs ont permis de déterminer si l'extinction des espèces se traduira par une plus grande ou une plus petite perte de diversité phylogénétique en comparaison à un processus d'extinction aléatoire. Les résultats ont effectivement montré que l'extinction des espèces liées aux changements climatiques pourrait entraîner une perte plus grande de diversité phylogénétique. Cependant, cette perte ne serait plus grande que celle liée à un processus d'extinction aléatoire qu'à partir d'une forte perte de taxons dans chaque groupe. La troisième partie de cette thèse explore la relation entre distances phylogénétiques et morphologiques d'espèces de chauves-souris de l'Afrique australe. ll s'agit plus précisément de déterminer si une longue histoire évolutive correspond également à des variations morphologiques plus grandes dans ce groupe. Cette relation est en fait prédite par un modèle neutre d'évolution de caractères. Aucune évidence de cette relation n'a émergé des analyses. Au contraire, des tendances négatives ont été détectées, ce qui représenterait la conséquence d'une évolution convergente entre clades et des niveaux élevés de cloisonnement pour chaque clade. Enfin, la dernière partie présente une étude sur la répartition de la niche climatique des chauves-souris de l'Afrique australe. Dans cette étude je rapporte temps de divergence évolutive (ou deux espèces ont divergé depuis un ancêtre commun) au niveau de chevauchement de leurs niches climatiques. Les résultats n'ont pas pu mettre en évidence de lien entre ces deux paramètres. Les résultats soutiennent plutôt l'idée que cela pourrait être I dû à des niveaux particulièrement élevés de répartition de la niche à échelle fine.

Nucleation and growth of metamorphic minerals in contact aureoles

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.

Differential Recognition of Old World and New World Arenavirus Envelope Glycoproteins by Subtilisin Kexin Isozyme 1 (SKI-1)/Site 1 Protease (S1P).

The arenaviruses are an important family of emerging viruses that includes several causative agents of severe hemorrhagic fevers in humans that represent serious public health problems. A crucial step of the arenavirus life cycle is maturation of the envelope glycoprotein precursor (GPC) by the cellular subtilisin kexin isozyme 1 (SKI-1)/site 1 protease (S1P). Comparison of the currently known sequences of arenavirus GPCs revealed the presence of a highly conserved aromatic residue at position P7 relative to the SKI-1/S1P cleavage side in Old World and clade C New World arenaviruses but not in New World viruses of clades A and B or cellular substrates of SKI-1/S1P. Using a combination of molecular modeling and structure-function analysis, we found that residueY285 of SKI-1/S1P, distal from the catalytic triad, is implicated in the molecular recognition of the aromatic "signature residue" at P7 in the GPC of Old World Lassa virus. Using a quantitative biochemical approach, we show that Y285 of SKI-1/S1P is crucial for the efficient processing of peptides derived from Old World and clade C New World arenavirus GPCs but not of those from clade A and B New World arenavirus GPCs. The data suggest that during coevolution with their mammalian hosts, GPCs of Old World and clade C New World viruses expanded the molecular contacts with SKI-1/S1P beyond the classical four-amino-acid recognition sequences and currently occupy an extended binding pocket.

Lack of Enantioselectivity in the SULT1A3-catalyzed Sulfoconjugation of Normetanephrine Enantiomers: An In Vitro and Computational Study.

(1R)-Normetanephrine is the natural stereoisomeric substrate for sulfotransferase 1A3 (SULT1A3)-catalyzed sulfonation. Nothing appears known on the enantioselectivity of the reaction despite its potential significance in the metabolism of adrenergic amines and in clinical biochemistry. We confronted the kinetic parameters of the sulfoconjugation of synthetic (1R)-normetanephrine and (1S)-normetanephrine by recombinant human SULT1A3 to a docking model of each normetanephrine enantiomer with SULT1A3 and the 3'-phosphoadenosine-5'-phosphosulfate cofactor on the basis of molecular modeling and molecular dynamics simulations of the stability of the complexes. The K(M) , V(max) , and k(cat) values for the sulfonation of (1R)-normetanephrine, (1S)-normetanephrine, and racemic normetanephrine were similar. In silico models were consistent with these findings as they showed that the binding modes of the two enantiomers were almost identical. In conclusion, SULT1A3 is not substrate-enantioselective toward normetanephrine, an unexpected finding explainable by a mutual adaptability between the ligands and SULT1A3 through an "induced-fit model" in the catalytic pocket. Chirality, 00:000-000, 2012.© 2012 Wiley Periodicals, Inc.

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula.

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.

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.

Business model design: an evaluation of paper-based and computer-aided canvases

In recent years, Business Model Canvas design has evolved from being a paper-based activity to one that involves the use of dedicated computer-aided business model design tools. We propose a set of guidelines to help design more coherent business models. When combined with functionalities offered by CAD tools, they show great potential to improve business model design as an ongoing activity. However, in order to create complex solutions, it is necessary to compare basic business model design tasks, using a CAD system over its paper-based counterpart. To this end, we carried out an experiment to measure user perceptions of both solutions. Performance was evaluated by applying our guidelines to both solutions and then carrying out a comparison of business model designs. Although CAD did not outperform paper-based design, the results are very encouraging for the future of computer-aided business model design.

Emerging environmental and weather challenges in outdoor sports

Given the climatic changes around the world and the growing outdoor sports participation, existing guidelines and recommendations for exercising in naturally challenging environments such as heat, cold or altitude, exhibit potential shortcomings. Continuous efforts from sport sciences and exercise physiology communities aim at minimizing the risks of environmental-related illnesses during outdoor sports practices. Despite this, the use of simple weather indices does not permit an accurate estimation of the likelihood of facing thermal illnesses. This provides a critical foundation to modify available human comfort modeling and to integrate bio-meteorological data in order to improve the current guidelines. Although it requires further refinement, there is no doubt that standardizing the recently developed Universal Thermal Climate Index approach and its application in the field of sport sciences and exercise physiology may help to improve the appropriateness of the current guidelines for outdoor, recreational and competitive sports participation. This review first summarizes the main environmental-related risk factors that are susceptible to increase with recent climate changes when exercising outside and offers recommendations to combat them appropriately. Secondly, we briefly address the recent development of thermal stress models to assess the thermal comfort and physiological responses when practicing outdoor activities in challenging environments.