44 resultados para Multivariate normal distribution

em Université de Lausanne, Switzerland


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We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.

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1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

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The exposure to dust and polynuclear aromatic hydrocarbons (PAH) of 15 truck drivers from Geneva, Switzerland, was measured. The drivers were divided between "long-distance" drivers and "local" drivers and between smokers and nonsmokers and were compared with a control group of 6 office workers who were also divided into smokers and nonsmokers. Dust was measured on 1 workday both by a direct-reading instrument and by sampling. The local drivers showed higher exposure to dust (0.3 mg/m3) and PAH than the long-distance drivers (0.1 mg/m3), who showed no difference with the control group. This observation may be due to the fact that the local drivers spend more time in more polluted areas, such as streets with heavy traffic and construction sites, than do the long-distance drivers. Smoking does not influence exposure to dust and PAH of professional truck drivers, as measured in this study, probably because the ventilation rate of the truck cabins is relatively high even during cold days (11-15 r/h). The distribution of dust concentrations was shown in some cases to be quite different from the expected log-normal distribution. The contribution of diesel exhaust to these exposures could not be estimated since no specific tracer was used. However, the relatively low level of dust exposure dose not support the hypothesis that present day levels of diesel exhaust particulates play a significant role in the excess occurrence of lung cancer observed in professional truck drivers.

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OBJECTIVE: Previous studies reported that the severity of cognitive deficits in euthymic patients with bipolar disorder (BD) increases with the duration of illness and postulated that progressive neuronal loss or shrinkage and white matter changes may be at the origin of this phenomenon. To explore this issue, the authors performed a case-control study including detailed neuropsychological and magnetic resonance imaging analyses in 17 euthymic elderly patients with BD and 17 healthy individuals. METHODS: Neuropsychological evaluation concerned working memory, episodic memory, processing speed, and executive functions. Volumetric estimates of the amygdala, hippocampus, entorhinal cortex, and anterior cingulate cortex were obtained using both voxel-based and region of interest morphometric methods. Periventricular and deep white matter were assessed semiquantitatively. Differences in cognitive performances and structural data between BD and comparison groups were analyzed using paired t-test or analysis of variance. Wilcoxon test was used in the absence of normal distribution. RESULTS: Compared with healthy individuals, patients with BD obtained significantly lower performances in processing speed, working memory, and episodic memory but not in executive functions. Morphometric analyses did not show significant volumetric or white matter differences between the two groups. CONCLUSIONS: Our results revealed impairment in verbal memory, working memory, and processing speed in euthymic older adults with BD. These cognitive deficits are comparable both in terms of affected functions and size effects to those previously reported in younger cohorts with BD. Both this observation and the absence of structural brain abnormalities in our cohort do not support a progressively evolving neurotoxic effect in BD.

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Autoantibodies to apolipoprotein/A-1 (anti-ApoA-1 IgG) have pro-atherogenic properties in patients at high cardiovascular risk, but its prevalence in patients with end-stage kidney disease is unknown. The aims of this single-center, cross-sectional study were to assess the prevalence of anti-ApoA-1 antibodies in patients on maintenance hemodialysis (MHD), and to examine its correlation with inflammatory biomarkers related to atherosclerotic plaque vulnerability and dialysis vintage. To this purpose, anti-ApoA-1 IgG levels and the concentrations of interleukin-6 (IL-6), interleukin-8 (IL-8), monocyte chemoattractant protein-1 (MCP-1), metalloproteinase-9 (MMP-9), tumor necrosis factor-α, and C-reactive protein (CRP) were assessed in the sera of 66 MHD patients (mean age: 68 ± 14 years, 36% women, 32% diabetics). Anti-ApoA-1 IgG positivity (defined as a blood value ≥ 97.5(th) percentile of the normal distribution as assessed in healthy blood donors) was 20%. Circulating levels of anti-ApoA-1 IgG correlated positively with dialysis vintage, but not with cardiovascular risk factors or previous cardiovascular events; no significant correlations were found between the anti-ApoA1 IgG levels and circulating levels of IL-6, IL-8, MCP-1, MMP-9, CRP, or low-density lipoprotein-cholesterol. In multivariable linear regression, adjusted for age and sex, only dialysis vintage remained positively and independently associated with anti-ApoA-1 titers (β = 0.05, 95% CI: 0.006; 0.28, P = 0.049). In conclusion, the prevalence of anti-ApoA-1 IgG is raised in the MHD-population, and positively associated with dialysis vintage, a major determinant of cardiovascular outcome. Whether antiApoA-1 antibodies play a role in the pathophysiology of accelerated atherosclerosis in the MHD-population merits further study.

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BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.

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The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

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The distribution of parvalbumin (PV), calretinin (CR), and calbindin (CB) immunoreactive neurons was studied with the help of an image analysis system (Vidas/Zeiss) in the primary visual area 17 and associative area 18 (Brodmann) of Alzheimer and control brains. In neither of these areas was there a significant difference between Alzheimer and control groups in the mean number of PV, CR, or CB immunoreactive neuronal profiles, counted in a cortical column going from pia to white matter. Significant differences in the mean densities (numbers per square millimeter of cortex) of PV, CR, and CB immunoreactive neuronal profiles were not observed either between groups or areas, but only between superficial, middle, and deep layers within areas 17 and 18. The optical density of the immunoreactive neuropil was also similar in Alzheimer and controls, correlating with the numerical density of immunoreactive profiles in superficial, middle, and deep layers. The frequency distribution of neuronal areas indicated significant differences between PV, CR, and CB immunoreactive neuronal profiles in both areas 17 and 18, with more large PV than CR and CB positive profiles. There were also significantly more small and less large PV and CR immunoreactive neuronal profiles in Alzheimer than in controls. Our data show that, although the brain pathology is moderate to severe, there is no prominent decrease of PV, CR and CB positive neurons in the visual cortex of Alzheimer brains, but only selective changes in neuronal perikarya.

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Ovalbumin-like serine protease inhibitors are mainly localized intracellularly and their in vivo functions are largely unknown. To elucidate their physiological role(s), we studied the expression of one of these inhibitors, protease inhibitor 8 (PI-8), in normal human tissues by immunohistochemistry using a PI-8-specific monoclonal antibody. PI-8 was strongly expressed in the nuclei of squamous epithelium of mouth, pharynx, esophagus, and epidermis, and by the epithelial layer of skin appendages, particularly by more differentiated epithelial cells. PI-8 was also expressed by monocytes and by neuroendocrine cells in the pituitary gland, pancreas, and digestive tract. Monocytes showed nuclear and cytoplasmic localization of PI-8, whereas neuroendocrine cells showed only cytoplasmic staining. In vitro nuclear localization of PI-8 was confirmed by confocal analysis using serpin-transfected HeLa cells. Furthermore, mutation of the P(1) residue did not affect the subcellular distribution pattern of PI-8, indicating that its nuclear localization is independent of the interaction with its target protease. We conclude that PI-8 has a unique distribution pattern in human tissues compared to the distribution patterns of other intracellular serpins. Additional studies must be performed to elucidate its physiological role.

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The pathogenesis of Duchenne muscular dystrophy (DMD), characterised by lack of the cytoskeletal protein dystrophin, is not completely understood. An early event in the degenerative process of DMD muscle could be a rise in cytosolic calcium concentration. In order to investigate whether this leads to alterations of contractile behaviour, we studied the excitability and contractile properties of cultured myotubes from control (C57BL/10) and mdx mice, an animal model for DMD. The myotubes were stimulated electrically and their motion was recorded photometrically. No significant differences were found between control and mdx myotubes with respect to the following parameters: chronaxy and rheobase (0.33 +/- 0.03 ms and 23 +/- 4 V vs. 0.39 +/- 0.07 ms and 22 +/- 2 V for C57 and mdx myotubes, respectively), tetanisation frequency (a similar distribution pattern was found between 5 and 30 Hz), fatigue during tetanus (found in 35% of both types of myotubes) and post-tetanic contracture. In contrast, contraction and relaxation times were longer (P < 0.005) in mdx (36 +/- 2 and 142 +/- 13 ms, respectively) than in control myotubes (26 +/- 1 and 85 +/- 9 ms, respectively). Together with our earlier findings, these results suggest a decreased capacity for calcium removal in mdx cells leading, in particular, to alterations of muscle relaxation.

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INTRODUCTION: Solid tumors are known to have an abnormal vasculature that limits the distribution of chemotherapy. We have recently shown that tumor vessel modulation by low-dose photodynamic therapy (L-PDT) could improve the uptake of macromolecular chemotherapeutic agents such as liposomal doxorubicin (Liporubicin) administered subsequently. However, how this occurs is unknown. Convection, the main mechanism for drug transport between the intravascular and extravascular spaces, is mostly related to interstitial fluid pressure (IFP) and tumor blood flow (TBF). Here, we determined the changes of tumor and surrounding lung IFP and TBF before, during, and after vascular L-PDT. We also evaluated the effect of these changes on the distribution of Liporubicin administered intravenously (IV) in a lung sarcoma metastasis model. MATERIALS AND METHODS: A syngeneic methylcholanthrene-induced sarcoma cell line was implanted subpleurally in the lung of Fischer rats. Tumor/surrounding lung IFP and TBF changes induced by L-PDT were determined using the wick-in-needle technique and laser Doppler flowmetry, respectively. The spatial distribution of Liporubicin in tumor and lung tissues following IV drug administration was then assessed in L-PDT-pretreated animals and controls (no L-PDT) by epifluorescence microscopy. RESULTS: L-PDT significantly decreased tumor but not lung IFP compared to controls (no L-PDT) without affecting TBF. These conditions were associated with a significant improvement in Liporubicin distribution in tumor tissues compared to controls (P < .05). DISCUSSION: L-PDT specifically enhanced convection in blood vessels of tumor but not of normal lung tissue, which was associated with a significant improvement of Liporubicin distribution in tumors compared to controls.

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SUMMARYSpecies distribution models (SDMs) represent nowadays an essential tool in the research fields of ecology and conservation biology. By combining observations of species occurrence or abundance with information on the environmental characteristic of the observation sites, they can provide information on the ecology of species, predict their distributions across the landscape or extrapolate them to other spatial or time frames. The advent of SDMs, supported by geographic information systems (GIS), new developments in statistical models and constantly increasing computational capacities, has revolutionized the way ecologists can comprehend species distributions in their environment. SDMs have brought the tool that allows describing species realized niches across a multivariate environmental space and predict their spatial distribution. Predictions, in the form of probabilistic maps showing the potential distribution of the species, are an irreplaceable mean to inform every single unit of a territory about its biodiversity potential. SDMs and the corresponding spatial predictions can be used to plan conservation actions for particular species, to design field surveys, to assess the risks related to the spread of invasive species, to select reserve locations and design reserve networks, and ultimately, to forecast distributional changes according to scenarios of climate and/or land use change.By assessing the effect of several factors on model performance and on the accuracy of spatial predictions, this thesis aims at improving techniques and data available for distribution modelling and at providing the best possible information to conservation managers to support their decisions and action plans for the conservation of biodiversity in Switzerland and beyond. Several monitoring programs have been put in place from the national to the global scale, and different sources of data now exist and start to be available to researchers who want to model species distribution. However, because of the lack of means, data are often not gathered at an appropriate resolution, are sampled only over limited areas, are not spatially explicit or do not provide a sound biological information. A typical example of this is data on 'habitat' (sensu biota). Even though this is essential information for an effective conservation planning, it often has to be approximated from land use, the closest available information. Moreover, data are often not sampled according to an established sampling design, which can lead to biased samples and consequently to spurious modelling results. Understanding the sources of variability linked to the different phases of the modelling process and their importance is crucial in order to evaluate the final distribution maps that are to be used for conservation purposes.The research presented in this thesis was essentially conducted within the framework of the Landspot Project, a project supported by the Swiss National Science Foundation. The main goal of the project was to assess the possible contribution of pre-modelled 'habitat' units to model the distribution of animal species, in particular butterfly species, across Switzerland. While pursuing this goal, different aspects of data quality, sampling design and modelling process were addressed and improved, and implications for conservation discussed. The main 'habitat' units considered in this thesis are grassland and forest communities of natural and anthropogenic origin as defined in the typology of habitats for Switzerland. These communities are mainly defined at the phytosociological level of the alliance. For the time being, no comprehensive map of such communities is available at the national scale and at fine resolution. As a first step, it was therefore necessary to create distribution models and maps for these communities across Switzerland and thus to gather and collect the necessary data. In order to reach this first objective, several new developments were necessary such as the definition of expert models, the classification of the Swiss territory in environmental domains, the design of an environmentally stratified sampling of the target vegetation units across Switzerland, the development of a database integrating a decision-support system assisting in the classification of the relevés, and the downscaling of the land use/cover data from 100 m to 25 m resolution.The main contributions of this thesis to the discipline of species distribution modelling (SDM) are assembled in four main scientific papers. In the first, published in Journal of Riogeography different issues related to the modelling process itself are investigated. First is assessed the effect of five different stepwise selection methods on model performance, stability and parsimony, using data of the forest inventory of State of Vaud. In the same paper are also assessed: the effect of weighting absences to ensure a prevalence of 0.5 prior to model calibration; the effect of limiting absences beyond the environmental envelope defined by presences; four different methods for incorporating spatial autocorrelation; and finally, the effect of integrating predictor interactions. Results allowed to specifically enhance the GRASP tool (Generalized Regression Analysis and Spatial Predictions) that now incorporates new selection methods and the possibility of dealing with interactions among predictors as well as spatial autocorrelation. The contribution of different sources of remotely sensed information to species distribution models was also assessed. The second paper (to be submitted) explores the combined effects of sample size and data post-stratification on the accuracy of models using data on grassland distribution across Switzerland collected within the framework of the Landspot project and supplemented with other important vegetation databases. For the stratification of the data, different spatial frameworks were compared. In particular, environmental stratification by Swiss Environmental Domains was compared to geographical stratification either by biogeographic regions or political states (cantons). The third paper (to be submitted) assesses the contribution of pre- modelled vegetation communities to the modelling of fauna. It is a two-steps approach that combines the disciplines of community ecology and spatial ecology and integrates their corresponding concepts of habitat. First are modelled vegetation communities per se and then these 'habitat' units are used in order to model animal species habitat. A case study is presented with grassland communities and butterfly species. Different ways of integrating vegetation information in the models of butterfly distribution were also evaluated. Finally, a glimpse to climate change is given in the fourth paper, recently published in Ecological Modelling. This paper proposes a conceptual framework for analysing range shifts, namely a catalogue of the possible patterns of change in the distribution of a species along elevational or other environmental gradients and an improved quantitative methodology to identify and objectively describe these patterns. The methodology was developed using data from the Swiss national common breeding bird survey and the article presents results concerning the observed shifts in the elevational distribution of breeding birds in Switzerland.The overall objective of this thesis is to improve species distribution models as potential inputs for different conservation tools (e.g. red lists, ecological networks, risk assessment of the spread of invasive species, vulnerability assessment in the context of climate change). While no conservation issues or tools are directly tested in this thesis, the importance of the proposed improvements made in species distribution modelling is discussed in the context of the selection of reserve networks.RESUMELes modèles de distribution d'espèces (SDMs) représentent aujourd'hui un outil essentiel dans les domaines de recherche de l'écologie et de la biologie de la conservation. En combinant les observations de la présence des espèces ou de leur abondance avec des informations sur les caractéristiques environnementales des sites d'observation, ces modèles peuvent fournir des informations sur l'écologie des espèces, prédire leur distribution à travers le paysage ou l'extrapoler dans l'espace et le temps. Le déploiement des SDMs, soutenu par les systèmes d'information géographique (SIG), les nouveaux développements dans les modèles statistiques, ainsi que la constante augmentation des capacités de calcul, a révolutionné la façon dont les écologistes peuvent comprendre la distribution des espèces dans leur environnement. Les SDMs ont apporté l'outil qui permet de décrire la niche réalisée des espèces dans un espace environnemental multivarié et prédire leur distribution spatiale. Les prédictions, sous forme de carte probabilistes montrant la distribution potentielle de l'espèce, sont un moyen irremplaçable d'informer chaque unité du territoire de sa biodiversité potentielle. Les SDMs et les prédictions spatiales correspondantes peuvent être utilisés pour planifier des mesures de conservation pour des espèces particulières, pour concevoir des plans d'échantillonnage, pour évaluer les risques liés à la propagation d'espèces envahissantes, pour choisir l'emplacement de réserves et les mettre en réseau, et finalement, pour prévoir les changements de répartition en fonction de scénarios de changement climatique et/ou d'utilisation du sol. En évaluant l'effet de plusieurs facteurs sur la performance des modèles et sur la précision des prédictions spatiales, cette thèse vise à améliorer les techniques et les données disponibles pour la modélisation de la distribution des espèces et à fournir la meilleure information possible aux gestionnaires pour appuyer leurs décisions et leurs plans d'action pour la conservation de la biodiversité en Suisse et au-delà. Plusieurs programmes de surveillance ont été mis en place de l'échelle nationale à l'échelle globale, et différentes sources de données sont désormais disponibles pour les chercheurs qui veulent modéliser la distribution des espèces. Toutefois, en raison du manque de moyens, les données sont souvent collectées à une résolution inappropriée, sont échantillonnées sur des zones limitées, ne sont pas spatialement explicites ou ne fournissent pas une information écologique suffisante. Un exemple typique est fourni par les données sur 'l'habitat' (sensu biota). Même s'il s'agit d'une information essentielle pour des mesures de conservation efficaces, elle est souvent approximée par l'utilisation du sol, l'information qui s'en approche le plus. En outre, les données ne sont souvent pas échantillonnées selon un plan d'échantillonnage établi, ce qui biaise les échantillons et par conséquent les résultats de la modélisation. Comprendre les sources de variabilité liées aux différentes phases du processus de modélisation s'avère crucial afin d'évaluer l'utilisation des cartes de distribution prédites à des fins de conservation.La recherche présentée dans cette thèse a été essentiellement menée dans le cadre du projet Landspot, un projet soutenu par le Fond National Suisse pour la Recherche. L'objectif principal de ce projet était d'évaluer la contribution d'unités 'd'habitat' pré-modélisées pour modéliser la répartition des espèces animales, notamment de papillons, à travers la Suisse. Tout en poursuivant cet objectif, différents aspects touchant à la qualité des données, au plan d'échantillonnage et au processus de modélisation sont abordés et améliorés, et leurs implications pour la conservation des espèces discutées. Les principaux 'habitats' considérés dans cette thèse sont des communautés de prairie et de forêt d'origine naturelle et anthropique telles que définies dans la typologie des habitats de Suisse. Ces communautés sont principalement définies au niveau phytosociologique de l'alliance. Pour l'instant aucune carte de la distribution de ces communautés n'est disponible à l'échelle nationale et à résolution fine. Dans un premier temps, il a donc été nécessaire de créer des modèles de distribution de ces communautés à travers la Suisse et par conséquent de recueillir les données nécessaires. Afin d'atteindre ce premier objectif, plusieurs nouveaux développements ont été nécessaires, tels que la définition de modèles experts, la classification du territoire suisse en domaines environnementaux, la conception d'un échantillonnage environnementalement stratifié des unités de végétation cibles dans toute la Suisse, la création d'une base de données intégrant un système d'aide à la décision pour la classification des relevés, et le « downscaling » des données de couverture du sol de 100 m à 25 m de résolution. Les principales contributions de cette thèse à la discipline de la modélisation de la distribution d'espèces (SDM) sont rassemblées dans quatre articles scientifiques. Dans le premier article, publié dans le Journal of Biogeography, différentes questions liées au processus de modélisation sont étudiées en utilisant les données de l'inventaire forestier de l'Etat de Vaud. Tout d'abord sont évalués les effets de cinq méthodes de sélection pas-à-pas sur la performance, la stabilité et la parcimonie des modèles. Dans le même article sont également évalués: l'effet de la pondération des absences afin d'assurer une prévalence de 0.5 lors de la calibration du modèle; l'effet de limiter les absences au-delà de l'enveloppe définie par les présences; quatre méthodes différentes pour l'intégration de l'autocorrélation spatiale; et enfin, l'effet de l'intégration d'interactions entre facteurs. Les résultats présentés dans cet article ont permis d'améliorer l'outil GRASP qui intègre désonnais de nouvelles méthodes de sélection et la possibilité de traiter les interactions entre variables explicatives, ainsi que l'autocorrélation spatiale. La contribution de différentes sources de données issues de la télédétection a également été évaluée. Le deuxième article (en voie de soumission) explore les effets combinés de la taille de l'échantillon et de la post-stratification sur le la précision des modèles. Les données utilisées ici sont celles concernant la répartition des prairies de Suisse recueillies dans le cadre du projet Landspot et complétées par d'autres sources. Pour la stratification des données, différents cadres spatiaux ont été comparés. En particulier, la stratification environnementale par les domaines environnementaux de Suisse a été comparée à la stratification géographique par les régions biogéographiques ou par les cantons. Le troisième article (en voie de soumission) évalue la contribution de communautés végétales pré-modélisées à la modélisation de la faune. C'est une approche en deux étapes qui combine les disciplines de l'écologie des communautés et de l'écologie spatiale en intégrant leurs concepts de 'habitat' respectifs. Les communautés végétales sont modélisées d'abord, puis ces unités de 'habitat' sont utilisées pour modéliser les espèces animales. Une étude de cas est présentée avec des communautés prairiales et des espèces de papillons. Différentes façons d'intégrer l'information sur la végétation dans les modèles de répartition des papillons sont évaluées. Enfin, un clin d'oeil aux changements climatiques dans le dernier article, publié dans Ecological Modelling. Cet article propose un cadre conceptuel pour l'analyse des changements dans la distribution des espèces qui comprend notamment un catalogue des différentes formes possibles de changement le long d'un gradient d'élévation ou autre gradient environnemental, et une méthode quantitative améliorée pour identifier et décrire ces déplacements. Cette méthodologie a été développée en utilisant des données issues du monitoring des oiseaux nicheurs répandus et l'article présente les résultats concernant les déplacements observés dans la distribution altitudinale des oiseaux nicheurs en Suisse.L'objectif général de cette thèse est d'améliorer les modèles de distribution des espèces en tant que source d'information possible pour les différents outils de conservation (par exemple, listes rouges, réseaux écologiques, évaluation des risques de propagation d'espèces envahissantes, évaluation de la vulnérabilité des espèces dans le contexte de changement climatique). Bien que ces questions de conservation ne soient pas directement testées dans cette thèse, l'importance des améliorations proposées pour la modélisation de la distribution des espèces est discutée à la fin de ce travail dans le contexte de la sélection de réseaux de réserves.