Modified Corneal Collagen Crosslinking (CXL) Reduces Corneal Edema and Diurnal Visual Fluctuations in Fuchs' Dystrophy

Purpose: Crosslinking of corneal collagen with riboflavin and ultraviolet-A irradiation (CXL) induces crosslinks within and between collagen fibers. CXL increases corneal biomechanical and biochemical stability and is currently used clinically to treat keratectasia. CXL also significantly reduces the stromal swelling capacity. We investigated whether a modified CXL treatment protocol would be beneficial in early Fuchs' dystrophy with various degrees of corneal edema and diurnal variations in visual acuity. Methods: CXL was performed as published previously with the following modification: in cases where the stroma was thicker than 450 µm after abrasion and 30 minutes of instillation of isoosmolar riboflavin solution, glycerol 70% solution was applied every 5 seconds for two minutes, and central corneal thickness (CCT) was measured using ultrasound pachymetry. Glycerol 70% solution was administered repeatedly until the target corneal thickness of 370-430 µm was reached. During irradiation, CCT was monitored by ultrasound pachymetry every five minutes and glycerol 70% solution was applied, if necessary. Results: Three eyes in two patients were treated using the modified CXL protocol. Representative case: a 50-year-old woman with Fuchs' dystrophy and a history of 3 years of diurnal visual fluctuations was referred to us in March 2008. Preoperative best spectacle-corrected visual acuity (BSCVA) was 20/50. We performed modified CXL in the left eye. At one month after CXL, Scheimpflug analysis of CCT showed a reduction of more than 100 µm, and the Corneal Thickness Spatial Profile (CTSP) and Percentage of Increase in Thickness (PIT) showed a regularization of the "flattening" typical for Fuchs' dystrophy. Accordingly, diurnal analysis of corneal thickness showed a distinct postoperative reduction in CCT at all time points measured. At one month after CXL, the patient reported a reduction of diurnal visual fluctuations and we measured an increase in BSCVA to 20/32. The patient showed stable topographical and visual acuity at the three months follow-up. Conclusions: We saw a distinct reduction in CCT, an improvement of the corneal thickness spatial profile (CTSP) and an increase in BSCVA at one month after treatment, which remained stable at the three months follow-up. Patients with early Fuchs' dystrophy and disturbing diurnal visual fluctuations represent a novel application for CXL. Although CXL may not prevent the outcome of the dystrophy, it may increase the patients' visual comfort until keratoplasty becomes necessary.

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.

Dispersal strategies, few dominating or many coexisting: the effect of environmental spatial structure and multiple sources of mortality.

Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.

On landslide risk, resilience and vulnerability of mountain communities in Central-Eastern Nepal

Executive SummaryIn Nepal, landslides are one of the major natural hazards after epidemics, killing over 100 persons per year. However, this figure is an underreported reflection of the actual impact that landslides have on livelihoods and food security in rural Nepal. With predictions of more intense rainfall patterns, landslide occurrence in the Himalayas is likely to increase and continue to be one of the major impediments to development. Due to the remoteness of many localities and lack of resources, responsibilities for disaster preparedness and response in mountain areas usually lie with the communities themselves. Everyday life is full of risk in mountains of Nepal. This is why mountain populations, as well as other populations living in harsh conditions have developed a number of coping strategies for dealing with adverse situations. Perhaps due to the dispersed and remote nature of landslides in Nepal, there have been few studies on vulnerability, coping- and mitigation strategies of landslide affected populations. There are also few recommendations available to guide authorities and populations how to reduce losses due to landslides in Nepal, and even less so, how to operationalize resilience and vulnerability.Many policy makers, international donors, NGOs and national authorities are currently asking what investments are needed to increase the so-called 'resilience' of mountain populations to deal with climate risks. However, mountain populations are already quite resilient to seasonal fluctuations, temperature variations, rainfall patterns and market prices. In spite of their resilience, they continue to live in places at risk due to high vulnerability caused by structural inequalities: access to land, resources, markets, education. This interdisciplinary thesis examines the concept of resilience by questioning its usefulness and validity as the current goal of international development and disaster risk reduction policies, its conceptual limitations and its possible scope of action. The goal of this study is two-fold: to better define and distinguish factors and relationships between resilience, vulnerability, capacities and risk; and to test and improve a participatory methodology for evaluating landslide risk that can serve as a guidance tool for improving community-based disaster risk reduction. The objective is to develop a simple methodology that can be used by NGOs, local authorities and communities to reduce losses from landslides.Through its six case studies in Central-Eastern Nepal, this study explores the relation between resilience, vulnerability and landslide risk based on interdisciplinary methods, including geological assessments of landslides, semi-structured interviews, focus groups and participatory risk mapping. For comparison, the study sites were chosen in Tehrathum, Sunsari and Dolakha Districts of Central/Eastern Nepal, to reflect a variety of landslide types, from chronic to acute, and a variety of communities, from very marginalized to very high status. The study uses the Sustainable Livelihoods Approach as its conceptual basis, which is based on the notion that access and rights to resources (natural, human/institutional, economic, environmental, physical) are the basis for coping with adversity, such as landslides. The study is also intended as a contribution to the growing literature and practices on Community Based Disaster Risk Reduction specifically adapted to landslide- prone areas.In addition to the six case studies, results include an indicator based methodology for assessing and measuring vulnerability and resilience, a composite risk assessment methodology, a typology of coping strategies and risk perceptions and a thorough analysis of the relation between risk, vulnerability and resilience. The methodology forassessing vulnerability, resilience and risk is relatively cost-effective and replicable in a low-data environment. Perhaps the major finding is that resilience is a process that defines a community's (or system's) capacity to rebound following adversity but it does not necessarily reduce vulnerability or risk, which requires addressing more structural issues related to poverty. Therefore, conclusions include a critical view of resilience as a main goal of international development and disaster risk reduction policies. It is a useful concept in the context of recovery after a disaster but it needs to be addressed in parallel with vulnerability and risk.This research was funded by an interdisciplinary grant (#26083591) from the Swiss National Science Foundation for the period 2009-2011 and a seed grant from the Faculty of Geosciences and Environment at the University of Lausanne in 2008.Résumé en françaisAu Népal, les glissements de terrain sont un des aléas les plus dévastateurs après les épidémies, causant 100 morts par an. Pourtant, ce chiffre est une sous-estimation de l'impact réel de l'effet des glissements sur les moyens de subsistance et la sécurité alimentaire au Népal. Avec des prévisions de pluies plus intenses, l'occurrence des glissements dans les Himalayas augmente et présente un obstacle au développement. Du fait de l'éloignement et du manque de ressources dans les montagnes au Népal, la responsabilité de la préparation et la réponse aux catastrophes se trouve chez les communautés elles-mêmes. Le risque fait partie de la vie quotidienne dans les montagnes du Népal. C'est pourquoi les populations montagnardes, comme d'autres populations vivant dans des milieux contraignants, ont développé des stratégies pour faire face aux situations défavorables. Peu d'études existent sur la vulnérabilité, ceci étant probablement dû à l'éloignement et pourtant, les stratégies d'adaptation et de mitigation des populations touchées par des glissements au Népal existent.Beaucoup de décideurs politiques, bailleurs de fonds, ONG et autorités nationales se demandent quels investissements sont nécessaires afin d'augmenter la 'resilience' des populations de montagne pour faire face aux changements climatiques. Pourtant, ces populations sont déjà résilientes aux fluctuations des saisons, des variations de température, des pluies et des prix des marchés. En dépit de leur résilience, ils continuent de vivre dans des endroits à fort risque à cause des vulnérabilités créées par les inégalités structurelles : l'accès à la terre, aux ressources, aux marchés et à l'éducation. Cette thèse interdisciplinaire examine le concept de la résilience en mettant en cause son utilité et sa validité en tant que but actuel des politiques internationales de développement et de réduction des risques, ainsi que ses limitations conceptuelles et ses possibles champs d'action. Le but de cette étude est double : mieux définir et distinguer les facteurs et relations entre la résilience, la vulnérabilité, les capacités et le risque ; Et tester et améliorer une méthode participative pour évaluer le risque des glissements qui peut servir en tant qu'outil indicatif pour améliorer la réduction des risques des communautés. Le but est de développer une méthodologie simple qui peut être utilisée par des ONG, autorités locales et communautés pour réduire les pertes dues aux glissements.A travers les études de cas au centre-est du Népal, cette étude explore le rapport entre la résilience, la vulnérabilité et les glissements basée sur des méthodes interdisciplinaires ; Y sont inclus des évaluations géologiques des glissements, des entretiens semi-dirigés, des discussions de groupes et des cartes de risques participatives. Pour la comparaison, les zones d'études ont été sélectionnées dans les districts de Tehrathum, Sunsari et Dolakha dans le centre-est du Népal, afin de refléter différents types de glissements, de chroniques à urgents, ainsi que différentes communautés, variant de très marginalisées à très haut statut. Pour son cadre conceptuel, cette étude s'appuie sur l'approche de moyens de subsistance durable, qui est basée sur les notions d'accès et de droit aux ressources (naturelles, humaines/institutionnelles, économiques, environnementales, physiques) et qui sont le minimum pour faire face à des situations difficiles, comme des glissements. Cette étude se veut aussi une contribution à la littérature et aux pratiques en croissantes sur la réduction des risques communautaires, spécifiquement adaptées aux zones affectées par des glissements.En plus des six études de cas, les résultats incluent une méthodologie basée sur des indicateurs pour évaluer et mesurer la vulnérabilité et la résilience, une méthodologie sur le risque composé, une typologie de stratégies d'adaptation et perceptions des risques ainsi qu'une analyse fondamentale de la relation entre risque, vulnérabilité et résilience. Les méthodologies pour l'évaluation de la vulnérabilité, de la résilience et du risque sont relativement peu coûteuses et reproductibles dans des endroits avec peu de données disponibles. Le résultat probablement le plus pertinent est que la résilience est un processus qui définit la capacité d'une communauté (ou d'un système) à rebondir suite à une situation défavorable, mais qui ne réduit pas forcement la vulnérabilité ou le risque, et qui requiert une approche plus fondamentale s'adressant aux questions de pauvreté. Les conclusions incluent une vue critique de la résilience comme but principal des politiques internationales de développement et de réduction des risques. C'est un concept utile dans le contexte de la récupération après une catastrophe mais il doit être pris en compte au même titre que la vulnérabilité et le risque.Cette recherche a été financée par un fonds interdisciplinaire (#26083591) du Fonds National Suisse pour la période 2009-2011 et un fonds de préparation de recherches par la Faculté des Géosciences et Environnement à l'Université de Lausanne en 2008.

Impact of small variations in temperature and humidity on the reproductive activity and survival of Aedes aegypti (Diptera, Culicidae)

In short space of time increase in temperature and rainfall can affect vector populations and, consequently, the diseases for them transmitted. The present study analyzed the effect of small temperature and humidity variations on the fecundity, fertility and survival of Aedes aegypti. These parameters were analyzed using individual females at temperatures ranging from 23 to 27 °C (mean 25 °C); 28 to 32 °C (mean 30 °C) and 33 to 37 °C (mean 35 ºC) associated to 60±8% and 80±6% relative humidity. Females responded to an increase in temperature by reducing egg production, oviposition time and changing oviposition patterns. At 25 ºC and 80% relative humidity, females survived two-fold more and produced 40% more eggs when compared to those kept at 35 ºC and 80% relative humidity. However, in 45% of females kept at 35 ºC and 60% relative humidity oviposition was inhibited and only 15% females laid more than 100 eggs, suggesting that the intensity of the temperature effect was influenced by humidity. Gradual reductions in egg fertility at 60% relative humidity were observed with the increase in temperature, although such effect was not found in the 80% relative humidity at 25 º C and 30 º C. These results suggest that the reduction in population densities recorded in tropical areas during seasons when temperatures reach over 35 ºC is likely to be strongly influenced by temperature and humidity, with a negative effect on several aspects of mosquito biology.

Spatial analysis of corresponding fingerprint features from match and close non-match populations

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.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Resting-state temporal synchronization networks emerge from connectivity topology and heterogeneity.

Spatial patterns of coherent activity across different brain areas have been identified during the resting-state fluctuations of the brain. However, recent studies indicate that resting-state activity is not stationary, but shows complex temporal dynamics. We were interested in the spatiotemporal dynamics of the phase interactions among resting-state fMRI BOLD signals from human subjects. We found that the global phase synchrony of the BOLD signals evolves on a characteristic ultra-slow (<0.01Hz) time scale, and that its temporal variations reflect the transient formation and dissolution of multiple communities of synchronized brain regions. Synchronized communities reoccurred intermittently in time and across scanning sessions. We found that the synchronization communities relate to previously defined functional networks known to be engaged in sensory-motor or cognitive function, called resting-state networks (RSNs), including the default mode network, the somato-motor network, the visual network, the auditory network, the cognitive control networks, the self-referential network, and combinations of these and other RSNs. We studied the mechanism originating the observed spatiotemporal synchronization dynamics by using a network model of phase oscillators connected through the brain's anatomical connectivity estimated using diffusion imaging human data. The model consistently approximates the temporal and spatial synchronization patterns of the empirical data, and reveals that multiple clusters that transiently synchronize and desynchronize emerge from the complex topology of anatomical connections, provided that oscillators are heterogeneous.

Visuo-spatial processing in a dynamic and a static working memory paradigm in schizophrenia.

Recent findings suggest that the visuo-spatial sketchpad (VSSP) may be divided into two sub-components processing dynamic or static visual information. This model may be useful to elucidate the confusion of data concerning the functioning of the VSSP in schizophrenia. The present study examined patients with schizophrenia and matched controls in a new working memory paradigm involving dynamic (the Ball Flight Task - BFT) or static (the Static Pattern Task - SPT) visual stimuli. In the BFT, the responses of the patients were apparently based on the retention of the last set of segments of the perceived trajectory, whereas control subjects relied on a more global strategy. We assume that the patients' performances are the result of a reduced capacity in chunking visual information since they relied mainly on the retention of the last set of segments. This assumption is confirmed by the poor performance of the patients in the static task (SPT), which requires a combination of stimulus components into object representations. We assume that the static/dynamic distinction may help us to understand the VSSP deficits in schizophrenia. This distinction also raises questions about the hypothesis that visuo-spatial working memory can simply be dissociated into visual and spatial sub-components.

Spatial and linear correlations between soil and corn

The Technologies setting at Agricultural production system have the main characteristics the vertical productivity, reduced costs, soil physical, chemical and biological improvement to promote production sustainable growth. Thus, the study aimed to determine the variability and the linear and special correlations between the plant and soil attributes in order to select and indicate good representation of soil physical quality for forage productivity. In the growing season of 2006, on the Fazenda Bonança in Pereira Barreto (SP), the productivity of autumn corn forage (FDM) in an irrigated no-tillage system and the soil physical properties were analyzed. The purpose was to study the variability and the linear and spatial correlations between the plant and soil properties, to select an indicator of soil physical quality related to corn forage yield. A geostatistical grid was installed to collect soil and plant data, with 125 sampling points in an area of 2,500 m². The results show that the studied properties did not vary randomly and that data variability was low to very high, with well-defined spatial patterns, ranging from 7.8 to 38.0 m. On the other hand, the linear correlation between the plant and the soil properties was low and highly significant. The pairs forage dry matter versus microporosity and stem diameter versus bulk density were best correlated in the 0-0.10 m layer, while the other pairs - forage dry matter versus macro - and total porosity - were inversely correlated in the same layer. However, from the spatial point of view, there was a high inverse correlation between forage dry matter with microporosity, so that microporosity in the 0-0.10 m layer can be considered a good indicator of soil physical quality, with a view to corn forage yield.

Plant functional and phylogenetic turnover correlate with climate and land use in the Western Swiss Alps

Understanding the relative importance of historical and environmental processes in the structure and composition of communities is one of the longest quests in ecological research. Increasingly, researchers are relying on the functional and phylogenetic β-diversity of natural communities to provide concise explanations on the mechanistic basis of community assembly and the drivers of trait variation among species. The present study investigated how plant functional and phylogenetic β-diversity change along key environmental and spatial gradients in the Western Swiss Alps. Methods Using the quadratic diversity measure based on six functional traits: specific leaf area (SLA), leaf dry matter content (LDMC), plant height (H), leaf carbon content (C), leaf nitrogen content (N), and leaf carbon to nitrogen content (C/N) alongside a species-resolved phylogenetic tree, we relate variations in climate, spatial geographic, land use and soil gradients to plant functional and phylogenetic turnover in mountain communities of the Western Swiss Alps. Important findings Our study highlights two main points. First, climate and land use factors play an important role in mountain plant community turnover. Second, the overlap between plant functional and phylogenetic turnover along these gradients correlates with the low phylogenetic signal in traits, suggesting that in mountain landscapes, trait lability is likely an important factor in driving plant community assembly. Overall, we demonstrate the importance of climate and land use factors in plant functional and phylogenetic community turnover, and provide valuable complementary insights into understanding patterns of β-diversity along several ecological gradients.

The importance of host spatial distribution for parasite specialization and speciation: a comparative study of bird fleas (Siphonaptera : Ceratophyllidae)

1. The environment of parasites is determined largely by their hosts. Variation in host quality, abundance and spatial distribution affects the balance between selection within hosts and gene flow between hosts, and this should determine the evolution of a parasite's host-range and its propensity to locally adapt and speciate. 2. We investigated the relationship between host spatial distribution and (1) parasite host range, (2) parasite mobility and (3) parasite geographical range, in a comparative study of a major group of avian ectoparasites, the birds fleas belonging to the Ceratophyllidae (Siphonaptera). 3. Flea species parasitizing colonial birds had narrower host ranges than those infesting territorial nesters or birds with an intermediate level of nest aggregation. 4. The potential mobility and geographical ranges of fleas decreased with increasing level of aggregation of their hosts and increased with the fleas' host ranges. 5. Birds with aggregated nest distribution harboured more flea species mainly due to a larger number of specialists than solitarily nesting hosts. 6. These results emphasize the importance of host spatial distribution for the evolution of specialization, and for local adaptation and speciation in Ceratophyllid bird fleas.

Multiple Kernel Learning of Environmental Data. Case study: Analysis and Mapping of Wind Fields

The paper presents the Multiple Kernel Learning (MKL) approach as a modelling and data exploratory tool and applies it to the problem of wind speed mapping. Support Vector Regression (SVR) is used to predict spatial variations of the mean wind speed from terrain features (slopes, terrain curvature, directional derivatives) generated at different spatial scales. Multiple Kernel Learning is applied to learn kernels for individual features and thematic feature subsets, both in the context of feature selection and optimal parameters determination. An empirical study on real-life data confirms the usefulness of MKL as a tool that enhances the interpretability of data-driven models.

Spatial pattern and process at the plant neighbourhood scale: insights from communities dominated by the clonal grass Elymus repens (L.) Gould.

Question: How do clonal traits of a locally dominant grass (Elymus repens (L.) Gould.) respond to soil heterogeneity and shape spatial patterns of its tillers? How do tiller spatial patterns constrain seedling recruitment within the community?Locations: Artificial banks of the River Rhone, France.Material and Methods: We examined 45 vegetation patches dominated by Elymus repens. During a first phase we tested relationships between soil variables and three clonal traits (spacer length, number of clumping tillers and branching rate), and between the same clonal traits and spatial patterns (i.e. density and degree of spatial aggregation) of tillers at a very fine scale. During a second phase, we performed a sowing experiment to investigate effects of density and spatial patterns of E. repens on recruitment of eight species selected from the regional species pool.Results: Clonal traits had clear effects - especially spacer length - on densification and aggregation of E. repens tillers and, at the same time, a clear response of these same clonal traits as soil granulometry changed. The density and degree of aggregation of E. repens tillers was positively correlated to total seedling cover and diversity at the finest spatial scales.Conclusions: Spatial patterning of a dominant perennial grass responds to soil heterogeneity through modifications of its clonal morphology as a trade-off between phalanx and guerrilla forms. In turn, spatial patterns have strong effects on abundance and diversity of seedlings. Spatial patterns of tillers most probably led to formation of endogenous gaps in which the recruitment of new plant individuals was enhanced. Interestingly, we also observed more idiosyncratic effects of tiller spatial patterns on seedling cover and diversity when focusing on different growth forms of the sown species.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.