Distribution network design and optimization

The objective of this thesis is to examine distribution network designs and modeling practices and create a framework to identify best possible distribution network structure for the case company. The main research question therefore is: How to optimize case company’s distribution network in terms of customer needs and costs? Theory chapters introduce the basic building blocks of the distribution network design and needed calculation methods and models. Framework for the distribution network projects was created based on the theory and the case study was carried out by following the defined framework. Distribution network calculations were based on the company’s sales plan for the years 2014 - 2020. Main conclusions and recommendations were that the new Asian business strategy requires high investments in logistics and the first step is to open new satellite DC in China as soon as possible to support sales and second possible step is to open regional DC in Asia within 2 - 4 years.

Acute promyelocytic leukemia: the study of t(15;17) translocation by fluorescent in situ hybridization, reverse transcriptase-polymerase chain reaction and cytogenetic techniques

Acute promyelocytic leukemia (AML M3) is a well-defined subtype of leukemia with specific and peculiar characteristics. Immediate identification of t(15;17) or the PML/RARA gene rearrangement is fundamental for treatment. The objective of the present study was to compare fluorescent in situ hybridization (FISH), reverse transcriptase-polymerase chain reaction (RT-PCR) and karyotyping in 18 samples (12 at diagnosis and 6 after treatment) from 13 AML M3 patients. Bone marrow samples were submitted to karyotype G-banding, FISH and RT-PCR. At diagnosis, cytogenetics was successful in 10 of 12 samples, 8 with t(15;17) and 2 without. FISH was positive in 11/12 cases (one had no cells for analysis) and positivity varied from 25 to 93% (mean: 56%). RT-PCR was done in 6/12 cases and all were positive. Four of 8 patients with t(15;17) presented positive RT-PCR as well as 2 without metaphases. The lack of RT-PCR results in the other samples was due to poor quality RNA. When the three tests were compared at diagnosis, karyotyping presented the translocation in 80% of the tested samples while FISH and RT-PCR showed the PML/RARA rearrangement in 100% of them. Of 6 samples evaluated after treatment, 3 showed a normal karyotype, 1 persistence of an abnormal clone and 2 no metaphases. FISH was negative in 4 samples studied and 2 had no material for analysis. RT-PCR was positive in 4 (2 of which showed negative FISH, indicating residual disease) and negative in 2. When the three tests were compared after treatment, they showed concordance in 2 of 6 samples or, when there were not enough cells for all tests, concordance between karyotype and RT-PCR in one. At remission, RT-PCR was the most sensitive test in detecting residual disease, as expected (positive in 4/6 samples). An incidence of about 40% of 5' breaks and 60% of 3' breaks, i.e., bcr3 and bcr1/bcr2, respectively, was observed.

Spatial modeling techniques for mapping and characterization of acid sulfate soils

Acid sulfate (a.s.) soils constitute a major environmental issue. Severe ecological damage results from the considerable amounts of acidity and metals leached by these soils in the recipient watercourses. As even small hot spots may affect large areas of coastal waters, mapping represents a fundamental step in the management and mitigation of a.s. soil environmental risks (i.e. to target strategic areas). Traditional mapping in the field is time-consuming and therefore expensive. Additional more cost-effective techniques have, thus, to be developed in order to narrow down and define in detail the areas of interest. The primary aim of this thesis was to assess different spatial modeling techniques for a.s. soil mapping, and the characterization of soil properties relevant for a.s. soil environmental risk management, using all available data: soil and water samples, as well as datalayers (e.g. geological and geophysical). Different spatial modeling techniques were applied at catchment or regional scale. Two artificial neural networks were assessed on the Sirppujoki River catchment (c. 440 km2) located in southwestern Finland, while fuzzy logic was assessed on several areas along the Finnish coast. Quaternary geology, aerogeophysics and slope data (derived from a digital elevation model) were utilized as evidential datalayers. The methods also required the use of point datasets (i.e. soil profiles corresponding to known a.s. or non-a.s. soil occurrences) for training and/or validation within the modeling processes. Applying these methods, various maps were generated: probability maps for a.s. soil occurrence, as well as predictive maps for different soil properties (sulfur content, organic matter content and critical sulfide depth). The two assessed artificial neural networks (ANNs) demonstrated good classification abilities for a.s. soil probability mapping at catchment scale. Slightly better results were achieved using a Radial Basis Function (RBF) -based ANN than a Radial Basis Functional Link Net (RBFLN) method, narrowing down more accurately the most probable areas for a.s. soil occurrence and defining more properly the least probable areas. The RBF-based ANN also demonstrated promising results for the characterization of different soil properties in the most probable a.s. soil areas at catchment scale. Since a.s. soil areas constitute highly productive lands for agricultural purpose, the combination of a probability map with more specific soil property predictive maps offers a valuable toolset to more precisely target strategic areas for subsequent environmental risk management. Notably, the use of laser scanning (i.e. Light Detection And Ranging, LiDAR) data enabled a more precise definition of a.s. soil probability areas, as well as the soil property modeling classes for sulfur content and the critical sulfide depth. Given suitable training/validation points, ANNs can be trained to yield a more precise modeling of the occurrence of a.s. soils and their properties. By contrast, fuzzy logic represents a simple, fast and objective alternative to carry out preliminary surveys, at catchment or regional scale, in areas offering a limited amount of data. This method enables delimiting and prioritizing the most probable areas for a.s soil occurrence, which can be particularly useful in the field. Being easily transferable from area to area, fuzzy logic modeling can be carried out at regional scale. Mapping at this scale would be extremely time-consuming through manual assessment. The use of spatial modeling techniques enables the creation of valid and comparable maps, which represents an important development within the a.s. soil mapping process. The a.s. soil mapping was also assessed using water chemistry data for 24 different catchments along the Finnish coast (in all, covering c. 21,300 km2) which were mapped with different methods (i.e. conventional mapping, fuzzy logic and an artificial neural network). Two a.s. soil related indicators measured in the river water (sulfate content and sulfate/chloride ratio) were compared to the extent of the most probable areas for a.s. soils in the surveyed catchments. High sulfate contents and sulfate/chloride ratios measured in most of the rivers demonstrated the presence of a.s. soils in the corresponding catchments. The calculated extent of the most probable a.s. soil areas is supported by independent data on water chemistry, suggesting that the a.s. soil probability maps created with different methods are reliable and comparable.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Green welding in practice

Efficient production and consumption of energy has become the top priority of national and international policies around the world. Manufacturing industries have to address the requirements of the government in relation to energy saving and ecologically sustainable products. These industries are also concerned with energy and material usage due to their rising costs. Therefore industries have to find solutions that can support environmental preservation yet maintain competitiveness in the market. Welding, a major manufacturing process, consumes a great deal of material and energy. It is a crucial process in improving a product’s life-cycle cost, strength, quality and reliability. Factors which lead to weld related inefficiencies have to be effectively managed, if industries are to meet their quality requirements and fulfil a high-volume production demand. Therefore it is important to consider some practical strategies in welding process for optimization of energy and material consumption. The main objective of this thesis is to explore the methods of minimizing the ecological footprint of the welding process and methods to effectively manage its material and energy usage in the welding process. The author has performed a critical review of the factors including improved weld power source efficiency, efficient weld techniques, newly developed weld materials, intelligent welding systems, weld safety measures and personnel training. The study lends strong support to the fact that the use of eco-friendly welding units and the quality weld joints obtained with minimum possible consumption of energy and materials should be the main directions of improvement in welding systems. The study concludes that, gradually implementing the practical strategies mentioned in this thesis would help the manufacturing industries to achieve on the following - reduced power consumption, enhanced power control and manipulation, increased deposition rate, reduced cycle time, reduced joint preparation time, reduced heat affected zones, reduced repair rates, improved joint properties, reduced post-weld operations, improved automation, improved sensing and control, avoiding hazardous conditions and reduced exposure of welder to potential hazards. These improvement can help in promotion of welding as a green manufacturing process.

Use of the Wasserman equation in optimization of the duration of the power ramp in a cardiopulmonary exercise test: a study of Brazilian men

This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 47±4 years and that in the coronary artery disease group (CG) was 57±8 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V˙O2)peak(predicted)and V˙O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V˙O2peak(real)was 40% lower than V˙O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lin’s coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer.

Spirulina platensis: process optimization to obtain biomass

Spirulina platensis is a photoautotrophic mesophilic cyanobacterium. Its main sources of nutrients are nitrate, urea, and ammonium salts. Spirulina cultivation requires temperature, light intensity, and nutrient content control. This microalgae has been studied and used commercially due to its therapeutic and antioxidant potential. In addition, several studies have reported its ability to use CO2, its immune activity, and use as an adjuvant nutritive factor in the treatment of obesity. The objective of this study is the production of biomass of S. platensis using different rates of stirring, nitrogen source, amount of micronutrients, and luminosity. A 2(4) experimental design with the following factors: stirring (120 and 140 RPM), amount of nitrogen (1.5 and 2.5 g/L), amount of micronutrients (0,25 and 0,75 mL/L) (11 and 15 W), and luminosity was used. Fermentation was performed in a 500 mL conical flask with 250 mL of culture medium and 10% inoculum in an incubator with controlled stirring and luminosity. Fermentation was monitored using a spectrophotometer (560 nm), and each fermentation lasted 15 days. Of the parameters studied, luminosity is the one with the highest significance, followed by the amount of nitrogen and the interaction between stirring and micronutrients. Maximum production of biomass for 15 days was 2.70 g/L under the following conditions: luminosity15W; stirring, 120 RPM; source of nitrogen, 1.5 g/L; and micronutrients, 0.75 mL/L.

Production optimization and characterization of immunomodulatory peptides obtained from fermented goat placenta

The goat placental immunomodulatory peptides were produced by fermentation with Aspergillus Niger. The objective of the present study was to investigate the effects of fermentation parameters (carbon source content, pH, and time) on spleen lymphocyte proliferation for the highest immune activity of the fermentation broth using response surface methodology (RSM). According to the data analysis by the Design-Expert® software, the stimulation index value (23.51%), which is the maximum immune activity, was obtained under the following conditions: content of carbon source 1.97 g·L-1, initial pH 5.0, and 74.43 h of fermentation time. Under the optimized fermentation conditions, at a certain concentration range, the fermentation broth produced a significant effect on the proliferation of mouse spleen lymphocytes. Ultrafiltration technique was performed to separate the fermentation broth with different MW (molecular weight). It was found that peptides in the range of <10 KDa were the main bioactivity fractions for the immunomodulatory and antioxidant activities.

Optimization of the HS-SPME-GC/MS technique for determining volatile compounds in red wines made from Isabel grapes (Vitis labrusca)

Abstract Brazilian wine production is characterized by Vitis labrusca grape varieties, especially the economically important Isabel cultivar, with over 80% of its production destined for table wine production. The objective of this study was to optimize and validate the conditions for extracting volatile compounds from wine with the solid-phase microextraction technique, using the response surface method. Based on the response surface analysis, it can be concluded that the central point values maximize the process of extracting volatile compounds from wine, i.e., an equilibrium time of 15 minutes, an extraction time of 35 minutes, and an extraction temperature of 30 °C. Esters were the most numerous compounds found under these extraction conditions, indicating that wines made from Isabel cultivar grapes are characterized by compounds that confer a fruity aroma; this finding corroborates the scientific literature.

Utilization of multi-branding in business to business markets

Case company utilizes multi-branding strategy (or house of brands strategy) in its product portfolio. In practice the company has multiple brands – one main brand and four acquired brands – which all utilize one single product platform. The objective of this research is to analyze case company’s multi-branding strategy and its benefits and challenges. Moreover, the purpose is to clarify that how could a company in B2B markets utilize multi-branding strategy more efficiently and profitably. The theoretical part of this thesis consists of aspects of branding strategies; different brand name architectures, benefits and challenges of different strategies and different ways of utilize branding strategies in mergers and acquisitions. The empirical part, on the other hand, includes the description of the case company’s branding strategy and the employees’ perspective on the benefits and challenges of multi-branding strategy, and how to utilize it more efficiently and profitably. This study shows, that the major benefits of utilizing multi-branding are lower production costs, ability to reach wider market coverage, possibility to utilize common sales tools, synergies in R&D and shared resources. On the other hand, the major challenges are lack of product differentiation, internal competition, branding issues in production and deliveries, pricing issues and conflicts, and compromises in product compatibility and suitability. Based on the results, several ways to utilize multi-branding strategy more efficiently and profitably were found; by putting more effort on brand image and product differentiation, by having more co-operation among the brands and by focusing on more precise customer and market segmentation.

Distributed energy resources in an electricity retailer’s short-term profit optimization

Liberalization of electricity markets has resulted in a competed Nordic electricity market, in which electricity retailers play a key role as electricity suppliers, market intermediaries, and service providers. Although these roles may remain unchanged in the near future, the retailers’ operation may change fundamentally as a result of the emerging smart grid environment. Especially the increasing amount of distributed energy resources (DER), and improving opportunities for their control, are reshaping the operating environment of the retailers. This requires that the retailers’ operation models are developed to match the operating environment, in which the active use of DER plays a major role. Electricity retailers have a clientele, and they operate actively in the electricity markets, which makes them a natural market party to offer new services for end-users aiming at an efficient and market-based use of DER. From the retailer’s point of view, the active use of DER can provide means to adapt the operation to meet the challenges posed by the smart grid environment, and to pursue the ultimate objective of the retailer, which is to maximize the profit of operation. This doctoral dissertation introduces a methodology for the comprehensive use of DER in an electricity retailer’s short-term profit optimization that covers operation in a variety of marketplaces including day-ahead, intra-day, and reserve markets. The analysis results provide data of the key profit-making opportunities and the risks associated with different types of DER use. Therefore, the methodology may serve as an efficient tool for an experienced operator in the planning of the optimal market-based DER use. The key contributions of this doctoral dissertation lie in the analysis and development of the model that allows the retailer to benefit from profit-making opportunities brought by the use of DER in different marketplaces, but also to manage the major risks involved in the active use of DER. In addition, the dissertation introduces an analysis of the economic potential of DER control actions in different marketplaces including the day-ahead Elspot market, balancing power market, and the hourly market of Frequency Containment Reserve for Disturbances (FCR-D).

Bio-inspired optimization & sampling technique for side-chain packing in MCCE

The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

Anatomo-functional magnetic resonance imaging of the spinal cord and its application to the characterization of spinal lesions in cats

Les lésions de la moelle épinière ont un impact significatif sur la qualité de la vie car elles peuvent induire des déficits moteurs (paralysie) et sensoriels. Ces déficits évoluent dans le temps à mesure que le système nerveux central se réorganise, en impliquant des mécanismes physiologiques et neurochimiques encore mal connus. L'ampleur de ces déficits ainsi que le processus de réhabilitation dépendent fortement des voies anatomiques qui ont été altérées dans la moelle épinière. Il est donc crucial de pouvoir attester l'intégrité de la matière blanche après une lésion spinale et évaluer quantitativement l'état fonctionnel des neurones spinaux. Un grand intérêt de l'imagerie par résonance magnétique (IRM) est qu'elle permet d'imager de façon non invasive les propriétés fonctionnelles et anatomiques du système nerveux central. Le premier objectif de ce projet de thèse a été de développer l'IRM de diffusion afin d'évaluer l'intégrité des axones de la matière blanche après une lésion médullaire. Le deuxième objectif a été d'évaluer dans quelle mesure l'IRM fonctionnelle permet de mesurer l'activité des neurones de la moelle épinière. Bien que largement appliquées au cerveau, l'IRM de diffusion et l'IRM fonctionnelle de la moelle épinière sont plus problématiques. Les difficultés associées à l'IRM de la moelle épinière relèvent de sa fine géométrie (environ 1 cm de diamètre chez l'humain), de la présence de mouvements d'origine physiologique (cardiaques et respiratoires) et de la présence d'artefacts de susceptibilité magnétique induits par les inhomogénéités de champ, notamment au niveau des disques intervertébraux et des poumons. L'objectif principal de cette thèse a donc été de développer des méthodes permettant de contourner ces difficultés. Ce développement a notamment reposé sur l'optimisation des paramètres d'acquisition d'images anatomiques, d'images pondérées en diffusion et de données fonctionnelles chez le chat et chez l'humain sur un IRM à 3 Tesla. En outre, diverses stratégies ont été étudiées afin de corriger les distorsions d'images induites par les artefacts de susceptibilité magnétique, et une étude a été menée sur la sensibilité et la spécificité de l'IRM fonctionnelle de la moelle épinière. Les résultats de ces études démontrent la faisabilité d'acquérir des images pondérées en diffusion de haute qualité, et d'évaluer l'intégrité de voies spinales spécifiques après lésion complète et partielle. De plus, l'activité des neurones spinaux a pu être détectée par IRM fonctionnelle chez des chats anesthésiés. Bien qu'encourageants, ces résultats mettent en lumière la nécessité de développer davantage ces nouvelles techniques. L'existence d'un outil de neuroimagerie fiable et robuste, capable de confirmer les paramètres cliniques, permettrait d'améliorer le diagnostic et le pronostic chez les patients atteints de lésions médullaires. Un des enjeux majeurs serait de suivre et de valider l'effet de diverses stratégies thérapeutiques. De telles outils représentent un espoir immense pour nombre de personnes souffrant de traumatismes et de maladies neurodégénératives telles que les lésions de la moelle épinière, les tumeurs spinales, la sclérose en plaques et la sclérose latérale amyotrophique.

Analyse multi-échelle des champs magnétiques dans des nuages moléculaires à structures filmentaires

Associée à d'autres techniques observationnelles, la polarimétrie dans le visible ou dans le proche infrarouge permet d'étudier la morphologie des champs magnétiques à la périphérie de nombreuses régions de formation stellaire. A l'intérieur des nuages molécualires la morphologie des champs est connue par polarimétrie submillimétrique, mais rarement pour les mêmes régions. Habituellement, il manque une échelle spatiale intermédiaire pour pouvoir comparer correctement la morphologie du champ magnétique galactique avec celle située à l'intérieur des nuages moléculaires. -- Cette thèse propose les moyens nécessaires pour réaliser ce type d'analyse multi-échelle afin de mieux comprendre le rôle que peuvent jouer les champs magnétiques dans les processus de formation stellaire. La première analyse traite de la région GF 9. Vient ensuite une étude de la morphologie du champ magnétique dans les filaments OMC-2 et OMC-3 suivie d'une analyse multi-échelle dans le complexe de nuages moléculaires Orion A dont OMC-2 et OMC-3 font partie. -- La synthèse des résultats couvrant GF 9 et Orion A est la suivante. Les approches statistiques employées montrent qu'aux grandes échelles spatiales la morphologie des champs magnétiques est poloïdale dans la région GF 9, et probablement hélicoïdale dans la région Orion A. A l'échelle spatiale des enveloppes des nuages moléculaires, les champs magnétiques apparaissent alignés avec les champs situés à leur périphérie. A l'échelle spatiale des coeurs, le champ magnétique poloïdal environnant la région GF 9 est apparemment entraîné par le coeur en rotation, et la diffusion ambipolaire n'y semble pas effective actuellement. Dans Orion A, la morphologie des champs est difficilement détectable dans les sites actifs de formation d'OMC-2, ou bien très fortement contrainte par les effets de la gravité dans OMC-1. Des effets probables de la turbulence ne seont détectés dans aucune des régions observées. -- Les analyses multi-échelles suggèrent donc qu'indépendamment du stade évolutif et de la gamme de masse des régions de formation stellaires, le champ magnétique galactique subit des modifications de sa morphologie aux échelles spatiales comparables à celles des coeurs protostellaires, de la même façon que les propriétés structurelles des nuages moléculaires suivent des lois d'autosimilarité jusqu'à des échelles comparables à celles des coeurs.

Structure et dynamique des communautés multi-espèces : le rôle de l’espace

Cette thèse porte sur le rôle de l’espace dans l’organisation et dans la dynamique des communautés écologiques multi-espèces. Deux carences peuvent être identifiées dans les études théoriques actuelles portant sur la dimension spatiale des communautés écologiques : l’insuffisance de modèles multi-espèces représentant la dimension spatiale explicitement, et le manque d’attention portée aux interactions positives, tel le mutualisme, en dépit de la reconnaissance de leur ubiquité dans les systèmes écologiques. Cette thèse explore cette problématique propre à l’écologie des communautés, en utilisant une approche théorique s’inspirant de la théorie des systèmes complexes et de la mécanique statistique. Selon cette approche, les communautés d’espèces sont considérées comme des systèmes complexes dont les propriétés globales émergent des interactions locales entre les organismes qui les composent, et des interactions locales entre ces organismes et leur environnement. Le premier objectif de cette thèse est de développer un modèle de métacommunauté multi-espèces, explicitement spatial, orienté à l’échelle des individus et basé sur un réseau d’interactions interspécifiques générales comprenant à la fois des interactions d’exploitation, de compétition et de mutualisme. Dans ce modèle, les communautés locales sont formées par un processus d’assemblage des espèces à partir d’un réservoir régional. La croissance des populations est restreinte par une capacité limite et leur dynamique évolue suivant des mécanismes simples de reproduction et de dispersion des individus. Ces mécanismes sont dépendants des conditions biotiques et abiotiques des communautés locales et leur effet varie en fonction des espèces, du temps et de l’espace. Dans un deuxième temps, cette thèse a pour objectif de déterminer l’impact d’une connectivité spatiale croissante sur la dynamique spatiotemporelle et sur les propriétés structurelles et fonctionnelles de cette métacommunauté. Plus précisément, nous évaluons différentes propriétés des communautés en fonction du niveau de dispersion des espèces : i) la similarité dans la composition des communautés locales et ses patrons de corrélations spatiales; ii) la biodiversité locale et régionale, et la distribution locale de l’abondance des espèces; iii) la biomasse, la productivité et la stabilité dynamique aux échelles locale et régionale; et iv) la structure locale des interactions entre les espèces. Ces propriétés sont examinées selon deux schémas spatiaux. D’abord nous employons un environnement homogène et ensuite nous employons un environnement hétérogène où la capacité limite des communautés locales évoluent suivant un gradient. De façon générale, nos résultats révèlent que les communautés écologiques spatialement distribuées sont extrêmement sensibles aux modes et aux niveaux de dispersion des organismes. Leur dynamique spatiotemporelle et leurs propriétés structurelles et fonctionnelles peuvent subir des changements profonds sous forme de transitions significatives suivant une faible variation du niveau de dispersion. Ces changements apparaissent aussi par l’émergence de patrons spatiotemporels dans la distribution spatiale des populations qui sont typiques des transitions de phases observées généralement dans les systèmes physiques. La dynamique de la métacommunauté présente deux régimes. Dans le premier régime, correspondant aux niveaux faibles de dispersion des espèces, la dynamique d’assemblage favorise l’émergence de communautés stables, peu diverses et formées d’espèces abondantes et fortement mutualistes. La métacommunauté possède une forte diversité régionale puisque les communautés locales sont faiblement connectées et que leur composition demeure ainsi distincte. Par ailleurs dans le second régime, correspondant aux niveaux élevés de dispersion, la diversité régionale diminue au profit d’une augmentation de la diversité locale. Les communautés locales sont plus productives mais leur stabilité dynamique est réduite suite à la migration importante d’individus. Ce régime est aussi caractérisé par des assemblages incluant une plus grande diversité d’interactions interspécifiques. Ces résultats suggèrent qu’une augmentation du niveau de dispersion des organismes permet de coupler les communautés locales entre elles ce qui accroît la coexistence locale et favorise la formation de communautés écologiques plus riches et plus complexes. Finalement, notre étude suggère que le mutualisme est fondamentale à l’organisation et au maintient des communautés écologiques. Les espèces mutualistes dominent dans les habitats caractérisés par une capacité limite restreinte et servent d’ingénieurs écologiques en facilitant l’établissement de compétiteurs, prédateurs et opportunistes qui bénéficient de leur présence.