Using life strategies to explore the vulnerability of ecosystem services to invasion by alien plants

Invasive plants can have different effects of ecosystem functioning and on the provision of ecosystem services, from strongly deleterious impacts to positive effects. The nature and intensity of such effects will depend on the service and ecosystem being considered, but also on features of life strategies of invaders that influence their invasiveness as well as their influence of key processes of receiving ecosystems. To address the combined effect of these various factors we developed a robust and efficient methodological framework that allows to identify areas of possible conflict between ecosystem services and alien invasive plants, considering interactions between landscape invasibility and species invasiveness. Our framework combines the statistical robustness of multi-model inference, efficient techniques to map ecosystem services, and life strategies as a functional link between invasion, functional changes and potential provision of services by invaded ecosystems. The framework was applied to a test region in Portugal, for which we could successfully predict the current patterns of plant invasion, of ecosystem service provision, and finally of probable conflict (expressing concern for negative impacts, and value for positive impacts on services) between alien species richness (total and per plant life strategy) and the potential provision of selected services. Potential conflicts were identified for all combinations of plant strategy and ecosystem service, with an emphasis for those concerning conflicts with carbon sequestration, water regulation and wood production. Lower levels of conflict were obtained between invasive plant strategies and the habitat for biodiversity supporting service. The added value of the proposed framework in the context of landscape management and planning is discussed in perspective of anticipation of conflicts, mitigation of negative impacts, and potentiation of positive effects of plant invasions on ecosystems and their services.

Quantifying consistency of Event Related Potentials across subjects based on single-trial topographic analysis

Introduction: Non-invasive brain imaging techniques often contrast experimental conditions across a cohort of participants, obfuscating distinctions in individual performance and brain mechanisms that are better characterised by the inter-trial variability. To overcome such limitations, we developed topographic analysis methods for single-trial EEG data [1]. So far this was typically based on time-frequency analysis of single-electrode data or single independent components. The method's efficacy is demonstrated for event-related responses to environmental sounds, hitherto studied at an average event-related potential (ERP) level. Methods: Nine healthy subjects participated to the experiment. Auditory meaningful sounds of common objects were used for a target detection task [2]. On each block, subjects were asked to discriminate target sounds, which were living or man-made auditory objects. Continuous 64-channel EEG was acquired during the task. Two datasets were considered for each subject including single-trial of the two conditions, living and man-made. The analysis comprised two steps. In the first part, a mixture of Gaussians analysis [3] provided representative topographies for each subject. In the second step, conditional probabilities for each Gaussian provided statistical inference on the structure of these topographies across trials, time, and experimental conditions. Similar analysis was conducted at group-level. Results: Results show that the occurrence of each map is structured in time and consistent across trials both at the single-subject and at group level. Conducting separate analyses of ERPs at single-subject and group levels, we could quantify the consistency of identified topographies and their time course of activation within and across participants as well as experimental conditions. A general agreement was found with previous analysis at average ERP level. Conclusions: This novel approach to single-trial analysis promises to have impact on several domains. In clinical research, it gives the possibility to statistically evaluate single-subject data, an essential tool for analysing patients with specific deficits and impairments and their deviation from normative standards. In cognitive neuroscience, it provides a novel tool for understanding behaviour and brain activity interdependencies at both single-subject and at group levels. In basic neurophysiology, it provides a new representation of ERPs and promises to cast light on the mechanisms of its generation and inter-individual variability.

Les traces de pneumatiques en sciences forensiques : de l'analyse chimique à l'évaluation de la force probante

This work is focused on the development of a methodology for the use of chemical characteristic of tire traces to help answer the following question: "Is the offending tire at the origin of the trace found on the crime scene?". This methodology goes from the trace sampling on the road to statistical analysis of its chemical characteristics. Knowledge about the composition and manufacture of tread tires as well as a review of instrumental techniques used for the analysis of polymeric materials were studied to select, as an ansi vi cal technique for this research, pyrolysis coupled to a gas Chromatograph with a mass spectrometry detector (Py-GC/MS). An analytical method was developed and optimized to obtain the lowest variability between replicates of the same sample. Within-variability of the tread was evaluated regarding width and circumference with several samples taken from twelve tires of different brands and/or models. The variability within each of the treads (within-variability) and between the treads (between-variability) could be quantified. Different statistical methods have shown that within-variability is lower than between-variability, which helped differentiate these tires. Ten tire traces were produced with tires of different brands and/or models by braking tests. These traces have been adequately sampled using sheets of gelatine. Particles of each trace were analysed using the same methodology as for the tires at their origin. The general chemical profile of a trace or of a tire has been characterized by eighty-six compounds. Based on a statistical comparison of the chemical profiles obtained, it has been shown that a tire trace is not differentiable from the tire at its origin but is generally differentiable from tires that are not at its origin. Thereafter, a sample containing sixty tires was analysed to assess the discrimination potential of the developed methodology. The statistical results showed that most of the tires of different brands and models are differentiable. However, tires of the same brand and model with identical characteristics, such as country of manufacture, size and DOT number, are not differentiable. A model, based on a likelihood ratio approach, was chosen to evaluate the results of the comparisons between the chemical profiles of the traces and tires. The methodology developed was finally blindly tested using three simulated scenarios. Each scenario involved a trace of an unknown tire as well as two tires possibly at its origin. The correct results for the three scenarios were used to validate the developed methodology. The different steps of this work were useful to collect the required information to test and validate the underlying assumption that it is possible to help determine if an offending tire » or is not at the origin of a trace, by means of a statistical comparison of their chemical profile. This aid was formalized by a measure of the probative value of the evidence, which is represented by the chemical profile of the trace of the tire. - Ce travail s'est proposé de développer une méthodologie pour l'exploitation des caractéristiques chimiques des traces de pneumatiques dans le but d'aider à répondre à la question suivante : «Est-ce que le pneumatique incriminé est ou n'est pas à l'origine de la trace relevée sur les lieux ? ». Cette méthodologie s'est intéressée du prélèvement de la trace de pneumatique sur la chaussée à l'exploitation statistique de ses caractéristiques chimiques. L'acquisition de connaissances sur la composition et la fabrication de la bande de roulement des pneumatiques ainsi que la revue de techniques instrumentales utilisées pour l'analyse de matériaux polymériques ont permis de choisir, comme technique analytique pour la présente recherche, la pyrolyse couplée à un chromatographe en phase gazeuse avec un détecteur de spectrométrie de masse (Py-GC/MS). Une méthode analytique a été développée et optimisée afin d'obtenir la plus faible variabilité entre les réplicas d'un même échantillon. L'évaluation de l'intravariabilité de la bande de roulement a été entreprise dans sa largeur et sa circonférence à l'aide de plusieurs prélèvements effectués sur douze pneumatiques de marques et/ou modèles différents. La variabilité au sein de chacune des bandes de roulement (intravariabilité) ainsi qu'entre les bandes de roulement considérées (intervariabilité) a pu être quantifiée. Les différentes méthodes statistiques appliquées ont montré que l'intravariabilité est plus faible que l'intervariabilité, ce qui a permis de différencier ces pneumatiques. Dix traces de pneumatiques ont été produites à l'aide de pneumatiques de marques et/ou modèles différents en effectuant des tests de freinage. Ces traces ont pu être adéquatement prélevées à l'aide de feuilles de gélatine. Des particules de chaque trace ont été analysées selon la même méthodologie que pour les pneumatiques à leur origine. Le profil chimique général d'une trace de pneumatique ou d'un pneumatique a été caractérisé à l'aide de huitante-six composés. Sur la base de la comparaison statistique des profils chimiques obtenus, il a pu être montré qu'une trace de pneumatique n'est pas différenciable du pneumatique à son origine mais est, généralement, différenciable des pneumatiques qui ne sont pas à son origine. Par la suite, un échantillonnage comprenant soixante pneumatiques a été analysé afin d'évaluer le potentiel de discrimination de la méthodologie développée. Les méthodes statistiques appliquées ont mis en évidence que des pneumatiques de marques et modèles différents sont, majoritairement, différenciables entre eux. La méthodologie développée présente ainsi un bon potentiel de discrimination. Toutefois, des pneumatiques de la même marque et du même modèle qui présentent des caractéristiques PTD (i.e. pays de fabrication, taille et numéro DOT) identiques ne sont pas différenciables. Un modèle d'évaluation, basé sur une approche dite du likelihood ratio, a été adopté pour apporter une signification au résultat des comparaisons entre les profils chimiques des traces et des pneumatiques. La méthodologie mise en place a finalement été testée à l'aveugle à l'aide de la simulation de trois scénarios. Chaque scénario impliquait une trace de pneumatique inconnue et deux pneumatiques suspectés d'être à l'origine de cette trace. Les résultats corrects obtenus pour les trois scénarios ont permis de valider la méthodologie développée. Les différentes étapes de ce travail ont permis d'acquérir les informations nécessaires au test et à la validation de l'hypothèse fondamentale selon laquelle il est possible d'aider à déterminer si un pneumatique incriminé est ou n'est pas à l'origine d'une trace, par le biais d'une comparaison statistique de leur profil chimique. Cette aide a été formalisée par une mesure de la force probante de l'indice, qui est représenté par le profil chimique de la trace de pneumatique.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

A novel device for reducing hemolysis provoked by cardiotomy suction during open heart cardiopulmonary bypass surgery: a randomized prospective study.

Since the inception of cardiopulmonary bypass (CPB), little progress has been made concerning the design of cardiotomy suction (CS). Because this is a major source of hemolysis, we decided to test a novel device (Smartsuction [SS]) specifically aimed at minimizing hemolysis during CPB in a clinical setting. Block randomization was carried out on a treated group (SS, n=28) and a control group (CTRL, n=26). Biochemical parameters were taken pre-, peri-, and post CPB and were compared between the two groups using the Student's t-test with statistical significance when P<0.05. No significant differences in patient demographics were observed between the two groups. Lactate dehydrogenase (LDH) and plasma free hemoglobin (PFH) pre-CPB were comparable for the CTRL and SS groups, respectively. LDH peri-CPB was 275+/-100 U/L versus 207+/-83 U/L for the CTRL and SS groups, respectively (P<0.05). PFH was 486+/-204 mg/L versus 351+/-176 mg/L for the CTRL and SS groups, respectively (P<0.05). LDH post CPB was 354+/-116 U/L versus 275+/-89 U/L for the CTRL and SS groups, respectively (P<0.05). PFH was 549+/-271 mg/L versus 460+/-254 mg/L for the CTRL and SS groups, respectively (P<0.05). Preoperative hematocrit (Hct) of 43+/-5% (CTRL) versus 37+/-5% (SS), and hemoglobin (Hb) of 141+/-16 g/L (CTRL) versus 122+/-17 g/L (SS) were significantly lower in the SS group. However, when normalized (N), the SS was capable of conserving Hct, Hb, and erythrocyte count perioperatively. Erythrocytes (N) were 59+/-5% (CTRL) versus 67+/-9% (SS); Hct (N) was 59+/-6% (CTRL) versus 68+/-9% (SS), and Hb (N) was 61+/-6% (CTRL) versus 70+/-10% (SS) (all P<0.05). This novel SS device evokes significantly lowered blood PFH and LDH values peri- and post CPB compared with the CTRL blood using a CS system. The SS may be a valuable alternative compared to traditional CS techniques.

Indications et techniques actuelles de reconstruction mammaire après mastectomie [Indications and techniques of reconstruction after mastectomy].

Reconstructive surgery takes an important place in breast cancer treatment. Immediate breast reconstruction is performed during the same operation as mastectomy. It is contraindicated following radiotherapy. Reconstruction performed after mastectomy is called differed breast reconstruction. It is completed 6 months after chemotherapy and 1 year after radiotherapy. Prosthetic breast reconstruction is indicated when tissues are of good qualities and breast are small. Autologous reconstruction is performed in case of radiotherapy or large breast. After breast reconstruction, imperfections can be corrected with autologous fat injection.

The application of chemometrics on Infrared and Raman spectra as a tool for the forensic analysis of paints

The aim of this work is to evaluate the capabilities and limitations of chemometric methods and other mathematical treatments applied on spectroscopic data and more specifically on paint samples. The uniqueness of the spectroscopic data comes from the fact that they are multivariate - a few thousands variables - and highly correlated. Statistical methods are used to study and discriminate samples. A collection of 34 red paint samples was measured by Infrared and Raman spectroscopy. Data pretreatment and variable selection demonstrated that the use of Standard Normal Variate (SNV), together with removal of the noisy variables by a selection of the wavelengths from 650 to 1830 cm−1 and 2730-3600 cm−1, provided the optimal results for infrared analysis. Principal component analysis (PCA) and hierarchical clusters analysis (HCA) were then used as exploratory techniques to provide evidence of structure in the data, cluster, or detect outliers. With the FTIR spectra, the Principal Components (PCs) correspond to binder types and the presence/absence of calcium carbonate. 83% of the total variance is explained by the four first PCs. As for the Raman spectra, we observe six different clusters corresponding to the different pigment compositions when plotting the first two PCs, which account for 37% and 20% respectively of the total variance. In conclusion, the use of chemometrics for the forensic analysis of paints provides a valuable tool for objective decision-making, a reduction of the possible classification errors, and a better efficiency, having robust results with time saving data treatments.

Urinary oxalate and urate to creatinine ratios in a healthy pediatric population.

The purpose of the study was to determine reference percentiles for the urinary (U) oxalate (Ox) and urate (Ura) to creatinine (Cr) concentration ratios in the second morning urine of healthy infants, children, and adolescents. The urinary oxalate and urate to creatinine ratios were determined in the spontaneously voided second morning urine sample. To test reproducibility, two urine samples were analyzed on 2 consecutive weeks in 63% of the subjects. Three hundred eighty-four healthy children (181 girls, 203 boys), aged 1 month to 17 years, from nurseries, kindergartens, and schools of Lausanne, Switzerland, were studied. The 5th and 95th percentiles were determined from the total number of urine samples (627) after confirmation that there was no order effect between repeated measurements and there were no significant sex differences. A nonlinear regression analysis in terms of age was used to smooth the calculated percentiles. In this manner, curves were obtained from which the reference values can be read at any given age. The 95th percentiles decreased with age: for UOx/Cr from 0.175 mg/mg (0.22 mol/mol) at 1 to 6 months to 0.048 mg/mg (0.06 mol/mol) from 7 years and beyond; and UUra/Cr from 2.378 mg/mg (1.6 mol/mol) at 1 to 6 months to 0.594 mg/mg (0.4 mol/mol) in adolescence. We provide 5th and 95th percentile curves for the UOx/Cr and UUra/Cr ratios determined from the second morning urine samples in a large cohort of healthy infants, children, and adolescents. Values were determined by standard analytical chemical techniques and were analyzed by powerful statistical methods. The calculated 95th percentile for the UOx/Cr values fell rather rapidly and reached normal adult values by the age of 7 years, whereas for UUra/Cr, the 95th percentile decreased slowly and stabilized in adolescence.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

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.

Techniques for analytical testing of unconventional samples.

Forensic scientists have long detected the presence of drugs and their metabolites in biological materials using body fluids such as urine, blood and/or other biological liquids or tissues. For doping analysis, only urine has so far been collected. In recent years, remarkable advances in sensitive analytical techniques have encouraged the analysis of drugs in unconventional biological samples such as hair, saliva and sweat. These samples are easily collected, although drug levels are often lower than the corresponding levels in urine or blood. This chapter reviews recent studies in the detection of doping agents in hair, saliva and sweat. Sampling, analytical procedures and interpretation of the results are discussed in comparison with those obtained from urine and blood samples.

Species distribution models for conservation-oriented studies in Switzerland : filling data and tools gaps

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.