951 resultados para hierarchical tree-structure


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Item response theory (IRT) comprises a set of statistical models which are useful in many fields, especially when there is an interest in studying latent variables (or latent traits). Usually such latent traits are assumed to be random variables and a convenient distribution is assigned to them. A very common choice for such a distribution has been the standard normal. Recently, Azevedo et al. [Bayesian inference for a skew-normal IRT model under the centred parameterization, Comput. Stat. Data Anal. 55 (2011), pp. 353-365] proposed a skew-normal distribution under the centred parameterization (SNCP) as had been studied in [R. B. Arellano-Valle and A. Azzalini, The centred parametrization for the multivariate skew-normal distribution, J. Multivariate Anal. 99(7) (2008), pp. 1362-1382], to model the latent trait distribution. This approach allows one to represent any asymmetric behaviour concerning the latent trait distribution. Also, they developed a Metropolis-Hastings within the Gibbs sampling (MHWGS) algorithm based on the density of the SNCP. They showed that the algorithm recovers all parameters properly. Their results indicated that, in the presence of asymmetry, the proposed model and the estimation algorithm perform better than the usual model and estimation methods. Our main goal in this paper is to propose another type of MHWGS algorithm based on a stochastic representation (hierarchical structure) of the SNCP studied in [N. Henze, A probabilistic representation of the skew-normal distribution, Scand. J. Statist. 13 (1986), pp. 271-275]. Our algorithm has only one Metropolis-Hastings step, in opposition to the algorithm developed by Azevedo et al., which has two such steps. This not only makes the implementation easier but also reduces the number of proposal densities to be used, which can be a problem in the implementation of MHWGS algorithms, as can be seen in [R.J. Patz and B.W. Junker, A straightforward approach to Markov Chain Monte Carlo methods for item response models, J. Educ. Behav. Stat. 24(2) (1999), pp. 146-178; R. J. Patz and B. W. Junker, The applications and extensions of MCMC in IRT: Multiple item types, missing data, and rated responses, J. Educ. Behav. Stat. 24(4) (1999), pp. 342-366; A. Gelman, G.O. Roberts, and W.R. Gilks, Efficient Metropolis jumping rules, Bayesian Stat. 5 (1996), pp. 599-607]. Moreover, we consider a modified beta prior (which generalizes the one considered in [3]) and a Jeffreys prior for the asymmetry parameter. Furthermore, we study the sensitivity of such priors as well as the use of different kernel densities for this parameter. Finally, we assess the impact of the number of examinees, number of items and the asymmetry level on the parameter recovery. Results of the simulation study indicated that our approach performed equally as well as that in [3], in terms of parameter recovery, mainly using the Jeffreys prior. Also, they indicated that the asymmetry level has the highest impact on parameter recovery, even though it is relatively small. A real data analysis is considered jointly with the development of model fitting assessment tools. The results are compared with the ones obtained by Azevedo et al. The results indicate that using the hierarchical approach allows us to implement MCMC algorithms more easily, it facilitates diagnosis of the convergence and also it can be very useful to fit more complex skew IRT models.

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The mechanisms responsible for containing activity in systems represented by networks are crucial in various phenomena, for example, in diseases such as epilepsy that affect the neuronal networks and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided into modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory, through which containment of activity is achieved by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, namely, random, Barabasi-Albert and geographical networks. The generality of this finding was confirmed by showing that modularity is no longer needed if the dynamics based on the integrate-and-fire dynamics incorporated the decay factor. Taken together, these results provide a proof of principle that persistent, restrained network activation might occur in the absence of any particular topological structure. This may be the reason why neuronal activity does not spread out to the entire neuronal network, even when no special topological organization exists.

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Although studies have addressed the chemical analysis and the biological activity of oleoresin in species of Copaifera, the cellular mechanisms of oleoresin production, storage, and release have rarely been investigated. This study detailed the distribution, ontogeny, and ultrastructure of secretory cavities and canals distributed in leaf and stem, respectively, of Copaifera trapezifolia, a Brazilian species included in a plant group of great economic interest. Axillary vegetative buds, leaflets, and portions of stem in primary and secondary growth were collected and processed in order to study the anatomy, histolocalization of substances, and ultrastructure. Secretory cavities are observed in the foliar blade and secretory canals in the petiolule and stem. They are made up of a uniseriate epithelium delimiting an isodiametric or elongated lumen. Biseriate epithelium is rarely observed and is a novelty for Leguminosae. Cavities and canals originate from ground meristem cells and the lumen is formed by schizogenesis. The content of the cavities and canals of both stem and leaf is oily and resinous, which suggests that the oleoresin could be extracted from the leaf instead of the stem. Phenolic compounds are also detected in the epithelial cell cytoplasm. Cavities and canals in the beginning of developmental stages have polarized epithelial cells. The cytoplasm is rich in smooth and rough endoplasmic reticula connected to vesicles or plastids. Smooth and rough endoplasmic reticulum and plastids were found to be predominant in the epithelial cells of the secretory cavities and canals of C. trapezifolia. Such features testify the quantities of oleoresin found in the lumen and phenolic compounds in the epithelial cell cytoplasm of these glands. Other studies employing techniques such as correlative light electron microscopy could show the vesicle traffic and the compartmentalization of the produced substances in such glands.

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Questions What are the main features of the seed rain in a fragmented Atlantic forest landscape? Can seed rain species attributes (life form, dispersal mode, successional status) relate to the spatial arrangement (size and number of fragments, edge density and presence of corridor) of forest fragments in the landscape? How does the rain forest landscape structure affect the seed rain? Location Atlantic rainforest, Sao Paulo State, Southeastern Brazil. Methods Seed rain samples were collected monthly throughout 1yr, counted, identified and classified according to species dispersal mode, successional status and life form. Seed rain composition was compared with woody species near the seed traps. Relationships between seed rain composition and landscape spatial arrangement (fragment area, presence of corridor, number of fragments in the surroundings, proximity of fragments, and edge density) were tested using canonical correspondence analysis (CCA). Results We collected 20142 seeds belonging to 115 taxa, most of them early successional and anemochorous trees. In general, the seed rain had a species composition distinct from that of the nearby forest tree community. Small isolated fragments contained more seeds, mainly of anemochorous, epiphytic and early-successional species; large fragments showed higher association with zoochorous and late-successional species compared to small fragments. The CCA significantly distinguished the species dispersal mode according to fragment size and isolation, anemochorous species being associated to small and isolated fragments, and zoochorous species to larger areas and fragment aggregation. Nevertheless, a gradient driven by proximity (PROX) and edge density (ED) segregated lianas (in the positive extremity), early successional and epiphyte species (in the negative end); large fragments were positively associated to PROX and ED. Conclusions The results highlight the importance of the size and spatial arrangement of forest patches to promote habitat connectivity and improve the flux of animal-dispersed seeds. Landscape structure controls seed fluxes and affects plant dispersal capacity, potentially influencing the composition and structure of forest fragments. The seed rain composition may be used to assess the effects of landscape spatial structure on plant assemblages, and provide relevant information for biodiversity conservation.

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Hancornia speciosa Gomes is a fruit tree native from Brazil that belongs to Apocinaceae family, and is popularly known as Mangabeira. Its fruits are widely consumed raw or processed as fruit jam, juices and ice creams, which have made it a target of intense exploitation. The extractive activities and intense human activity on the environment of natural occurrence of H. speciosa has caused genetic erosion in the species and little is known about the ecology or genetic structure of natural populations. The objective of this research was the evaluation of the genetic diversity and genetic structure of H. speciosa var. speciosa. The genetic variability was assessed using 11 allozyme loci with a sample of 164 individuals distributed in six natural populations located in the States of Pernambuco and Alagoas, Northeastern Brazil. The results showed a high level of genetic diversity within the species (e= 0.36) seeing that the most of the genetic variability of H. speciosa var. speciosa is within its natural populations with low difference among populations ( or = 0.081). The inbreeding values within ( = -0.555) and among populations ( =-0.428) were low showing lacking of endogamy and a surplus of heterozygotes. The estimated gene flow ( m ) was high, ranging from 2.20 to 13.18, indicating to be enough to prevent the effects of genetic drift and genetic differentiation among populations. The multivariate analyses indicated that there is a relationship between genetic and geographical distances, which was confirmed by a spatial pattern analysis using Mantel test (r = 0.3598; p = 0.0920) with 1000 random permutations. The high genetic diversity index in these populations indicates potential for in situ genetic conservation.

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Hierarchical multi-label classification is a complex classification task where the classes involved in the problem are hierarchically structured and each example may simultaneously belong to more than one class in each hierarchical level. In this paper, we extend our previous works, where we investigated a new local-based classification method that incrementally trains a multi-layer perceptron for each level of the classification hierarchy. Predictions made by a neural network in a given level are used as inputs to the neural network responsible for the prediction in the next level. We compare the proposed method with one state-of-the-art decision-tree induction method and two decision-tree induction methods, using several hierarchical multi-label classification datasets. We perform a thorough experimental analysis, showing that our method obtains competitive results to a robust global method regarding both precision and recall evaluation measures.

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The main aim of this Ph.D. dissertation is the study of clustering dependent data by means of copula functions with particular emphasis on microarray data. Copula functions are a popular multivariate modeling tool in each field where the multivariate dependence is of great interest and their use in clustering has not been still investigated. The first part of this work contains the review of the literature of clustering methods, copula functions and microarray experiments. The attention focuses on the K–means (Hartigan, 1975; Hartigan and Wong, 1979), the hierarchical (Everitt, 1974) and the model–based (Fraley and Raftery, 1998, 1999, 2000, 2007) clustering techniques because their performance is compared. Then, the probabilistic interpretation of the Sklar’s theorem (Sklar’s, 1959), the estimation methods for copulas like the Inference for Margins (Joe and Xu, 1996) and the Archimedean and Elliptical copula families are presented. In the end, applications of clustering methods and copulas to the genetic and microarray experiments are highlighted. The second part contains the original contribution proposed. A simulation study is performed in order to evaluate the performance of the K–means and the hierarchical bottom–up clustering methods in identifying clusters according to the dependence structure of the data generating process. Different simulations are performed by varying different conditions (e.g., the kind of margins (distinct, overlapping and nested) and the value of the dependence parameter ) and the results are evaluated by means of different measures of performance. In light of the simulation results and of the limits of the two investigated clustering methods, a new clustering algorithm based on copula functions (‘CoClust’ in brief) is proposed. The basic idea, the iterative procedure of the CoClust and the description of the written R functions with their output are given. The CoClust algorithm is tested on simulated data (by varying the number of clusters, the copula models, the dependence parameter value and the degree of overlap of margins) and is compared with the performance of model–based clustering by using different measures of performance, like the percentage of well–identified number of clusters and the not rejection percentage of H0 on . It is shown that the CoClust algorithm allows to overcome all observed limits of the other investigated clustering techniques and is able to identify clusters according to the dependence structure of the data independently of the degree of overlap of margins and the strength of the dependence. The CoClust uses a criterion based on the maximized log–likelihood function of the copula and can virtually account for any possible dependence relationship between observations. Many peculiar characteristics are shown for the CoClust, e.g. its capability of identifying the true number of clusters and the fact that it does not require a starting classification. Finally, the CoClust algorithm is applied to the real microarray data of Hedenfalk et al. (2001) both to the gene expressions observed in three different cancer samples and to the columns (tumor samples) of the whole data matrix.

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Machine learning comprises a series of techniques for automatic extraction of meaningful information from large collections of noisy data. In many real world applications, data is naturally represented in structured form. Since traditional methods in machine learning deal with vectorial information, they require an a priori form of preprocessing. Among all the learning techniques for dealing with structured data, kernel methods are recognized to have a strong theoretical background and to be effective approaches. They do not require an explicit vectorial representation of the data in terms of features, but rely on a measure of similarity between any pair of objects of a domain, the kernel function. Designing fast and good kernel functions is a challenging problem. In the case of tree structured data two issues become relevant: kernel for trees should not be sparse and should be fast to compute. The sparsity problem arises when, given a dataset and a kernel function, most structures of the dataset are completely dissimilar to one another. In those cases the classifier has too few information for making correct predictions on unseen data. In fact, it tends to produce a discriminating function behaving as the nearest neighbour rule. Sparsity is likely to arise for some standard tree kernel functions, such as the subtree and subset tree kernel, when they are applied to datasets with node labels belonging to a large domain. A second drawback of using tree kernels is the time complexity required both in learning and classification phases. Such a complexity can sometimes prevents the kernel application in scenarios involving large amount of data. This thesis proposes three contributions for resolving the above issues of kernel for trees. A first contribution aims at creating kernel functions which adapt to the statistical properties of the dataset, thus reducing its sparsity with respect to traditional tree kernel functions. Specifically, we propose to encode the input trees by an algorithm able to project the data onto a lower dimensional space with the property that similar structures are mapped similarly. By building kernel functions on the lower dimensional representation, we are able to perform inexact matchings between different inputs in the original space. A second contribution is the proposal of a novel kernel function based on the convolution kernel framework. Convolution kernel measures the similarity of two objects in terms of the similarities of their subparts. Most convolution kernels are based on counting the number of shared substructures, partially discarding information about their position in the original structure. The kernel function we propose is, instead, especially focused on this aspect. A third contribution is devoted at reducing the computational burden related to the calculation of a kernel function between a tree and a forest of trees, which is a typical operation in the classification phase and, for some algorithms, also in the learning phase. We propose a general methodology applicable to convolution kernels. Moreover, we show an instantiation of our technique when kernels such as the subtree and subset tree kernels are employed. In those cases, Direct Acyclic Graphs can be used to compactly represent shared substructures in different trees, thus reducing the computational burden and storage requirements.

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This PhD Thesis is the result of my research activity in the last three years. My main research interest was centered on the evolution of mitochondrial genome (mtDNA), and on its usefulness as a phylogeographic and phylogenetic marker at different taxonomic levels in different taxa of Metazoa. From a methodological standpoint, my main effort was dedicated to the sequencing of complete mitochondrial genomes, and the approach to whole-genome sequencing was based on the application of Long-PCR and shotgun sequences. Moreover, this research project is a part of a bigger sequencing project of mtDNAs in many different Metazoans’ taxa, and I mostly dedicated myself to sequence and analyze mtDNAs in selected taxa of bivalves and hexapods (Insecta). Sequences of bivalve mtDNAs are particularly limited, and my study contributed to extend the sampling. Moreover, I used the bivalve Musculista senhousia as model taxon to investigate the molecular mechanisms and the evolutionary significance of their aberrant mode of mitochondrial inheritance (Doubly Uniparental Inheritance, see below). In Insects, I focused my attention on the Genus Bacillus (Insecta Phasmida). A detailed phylogenetic analysis was performed in order to assess phylogenetic relationships within the genus, and to investigate the placement of Phasmida in the phylogenetic tree of Insecta. The main goal of this part of my study was to add to the taxonomic coverage of sequenced mtDNAs in basal insects, which were only partially analyzed.

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This PhD Thesis is part of a long-term wide research project, carried out by the "Osservatorio Astronomico di Bologna (INAF-OABO)", that has as primary goal the comprehension and reconstruction of formation mechanism of galaxies and their evolution history. There is now substantial evidence, both from theoretical and observational point of view, in favor of the hypothesis that the halo of our Galaxy has been at least partially, built up by the progressive accretion of small fragments, similar in nature to the present day dwarf galaxies of the Local Group. In this context, the photometric and spectroscopic study of systems which populate the halo of our Galaxy (i.e. dwarf spheroidal galaxy, tidal streams, massive globular cluster, etc) permits to discover, not only the origin and behaviour of these systems, but also the structure of our Galactic halo, combined with its formation history. In fact, the study of the population of these objects and also of their chemical compositions, age, metallicities and velocity dispersion, permit us not only an improvement in the understanding of the mechanisms that govern the Galactic formation, but also a valid indirect test for cosmological model itself. Specifically, in this Thesis we provided a complete characterization of the tidal Stream of the Sagittarius dwarf spheroidal galaxy, that is the most striking example of the process of tidal disruption and accretion of a dwarf satellite in to our Galaxy. Using Red Clump stars, extracted from the catalogue of the Sloan Digital Sky Survey (SDSS) we obtained an estimate of the distance, the depth along the line of sight and of the number density for each detected portion of the Stream (and more in general for each detected structure along our line of sight). Moreover comparing the relative number (i.e. the ratio) of Blue Horizontal Branch stars and Red Clump stars (the two features are tracers of different age/different metallicity populations) in the main body of the galaxy and in the Stream, in order to verify the presence of an age-metallicity gradient along the Stream. We also report the detection of a population of Red Clump stars probably associated with the recently discovered Bootes III stellar system. Finally, we also present the results of a survey of radial velocities over a wide region, extending from r ~ 10' out to r ~ 80' within the massive star cluster Omega Centauri. The survey was performed with FLAMES@VLT, to study the velocity dispersion profile in the outer regions of this stellar system. All the results presented in this Thesis, have already been published in refeered journals.

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Pollination and seed dispersal are important ecological processes for the regeneration of plant populations and both vectors for gene exchange between plant populations. For my thesis, I studied the pollination ecology of the South African tree Commiphora harveyi (Burseraceae) and compared it with C. guillauminii from Madagascar. Both species have low visitation rates and a low number of pollinating insect species, resulting in a low fruit set. While their pollination ecology is very similar, they differ in their seed dispersal with a low seed dispersal rate in the Malagasy and a high seed dispersal rate in the South African species. This should be reflected in a stronger genetic differentiation among populations in the Malagasy than in the South African species. My results, based on AFLP markers, contradict these expectations, the overall differentiation was lower in the Malagasy (FST = 0.05) than in the South African species (FST = 0.16). However, at a smaller spatial scale (below 3 km), the Malagasy species was genetically more strongly differentiated than the South African species, which was reflected by the high inter-population variance within the sample site (C. guillauminii: 72.2 - 85.5 %; C. harveyi: 8.4 - 14.5 %). This strong differentiation could arise from limited gene flow, which was confirmed by spatial autocorrelation analyses. The shape of the autocorrelogram suggested that gene exchange between individuals occurred only up to 3 km in the Malagasy species, whereas up to 30 km in the South African species. These results on the genetic structure correspond to the expectations based on seed dispersal data. Thus, seed dispersal seems to be a key factor for the genetic structure in plant populations on a local scale.

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The city is a collection of built structures and infrastructure embedded in socio-cultural processes: any investigation into a city’s transformations involves considerations on the degree to which its composite elements respond to socio-economical changes. The main purpose of this research is to investigate how transformations in the functional requirements of New York’s society have spurred, since the 1970s, changes in both the city’s urban structure and physical form. The present work examines the rise of Amenity Zones in New York, and investigates the transformations that have occurred in New York’s built environment since the 1970s. By applying qualitative measures and analyzing the relationship between urban amenities and the creative class, the present work has investigated changes in the urban structure and detected a hierarchical series of amenity zones classes, namely, Super Amenity Zones (SAZs), Nodal Amenity Zones (NAZs) and Peripheral Amenity Zones (PAZs). This series allows for a more comprehensive reading of the urban structure in a complex city like New York, bringing advancements to the amenity zone’s methodology. In order to examine the manner in which the other component of the city, the physical form, has changed or adapted to the new socio-economic condition, the present research has applied Conzenian analysis to a select study area, Atlantic Avenue. The results of this analysis reveal that, contrary to the urban structure, which changes rapidly, the physical form of New York is hard to modify completely, due to the resilience of the town plan and its elements, and to preservation laws; the city rather adapts to socio-economical changes through process of adaptive reuses or conversion. Concluding, this research has examined the dialectic between the ever-changing needs of society and the complexity of the built environment and urban structure, showing the different degrees to which the urban landscape modifies, reacts and sometimes adapts to the population’s functional requirements.

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Anthropogene Fragmentierung und Störung von Wäldern beeinflussen ökologische Prozesse. Darüber hinaus werden genetische Drift und Inzucht verstärkt und die Fitness von Populationen beeinträchtigt. Um die Einflüsse von Fragmentierung und Störung auf die Biodiversität und Prozesse in tropischen Wäldern zu ermitteln, habe ich im „Kakamega Forest“, West-Kenia, die Baumart Prunus africana genauer untersucht. Dabei lag der Fokus auf (i) der Frugivorengemeinschaft und Samenausbreitung, (ii) der Kleinsäugergemeinschaft im Kontext der Samenprädation und (iii) der genetische Populationsstruktur von Keimlingen und adulten Bäumen. Der Vergleich von Keimlingen mit adulten Bäumen ermöglicht es, Veränderungen im Genfluss zwischen Generationen festzustellen. Die Ergebnisse zeigten, dass im untersuchten Waldgebiet insgesamt 49 frugivore Arten (Affen und Vögel) vorkommen. Dabei lag die Gesamtartenzahl im zusammenhängenden Wald höher als in den isoliert liegenden Fragmenten. An den Früchten von P. africana konnten insgesamt 36 Arten fressend beobachtet werden. Hier jedoch wurden in Fragmenten eine leicht erhöhte Frugivorenzahl sowie marginal signifikant erhöhte Samenausbreitungsraten nachgewiesen. Der Vergleich von stark gestörten mit weniger gestörten Flächen zeigte eine höhere Gesamtartenzahl sowie eine signifikant höhere Frugivorenzahl in P. africana in stark gestörten Flächen. Entsprechend war die Samenausbreitungsrate in stark gestörten Flächen marginal signifikant erhöht. Diese Ergebnisse deuten darauf hin, dass die quantitative Samenausbreitung in fragmentierten und gestörten Flächen etwas erhöht ist und somit eine gewisse Artenredundanz besteht, die den Verlust einzelner Arten ausgleichen könnte. Prunus africana Samen, die auf dem Boden lagen, wurden hauptsächlich von einer Nagerart (Praomys cf. jacksonii) erbeutet. Dabei war in gestörten Waldbereichen eine tendenziell höhere Prädatoraktivität zu beobachten als in weniger gestörten. Zudem waren einzelne Samen im Gegensatz zu Samengruppen in gestörten Flächen signifikant höherem Prädationsdruck ausgesetzt. Diese Ergebnisse zeigen, dass Fragmentierung sowie anthropogene Störungen auf unterschiedliche Prozesse im Lebenszyklus eines tropischen Baumes gegensätzliche Effekte haben können. Eine Extrapolation von einem auf einen anderen Prozess kann somit nicht erfolgen. Die genetische Differenzierung der adulten Baumpopulationen war gering (FST = 0.026). Der Großteil ihrer Variation (~ 97 %) lag innerhalb der Populationen, was intensiven Genfluss in der Vergangenheit widerspiegelt. Die genetische Differenzierung der Keimlinge war etwas erhöht (FST = 0.086) und ~ 91 % ihrer Variation lag innerhalb der Populationen. Im Gegensatz zu den adulten Bäumen konnte ich für Keimlinge ein „Isolation-by-distance“-Muster feststellen. Somit sind erste Hinweise auf begrenzten Genfluss im Keimlingsstadium infolge von Fragmentierung gegeben. Obwohl die Momentaufnahmen im Freiland keine Abnahme in der Frugivorenzahl und Samenausbreitung von P. africana als Folge von Fragmentierung beobachten ließen, weisen die Ergebnisse der genetischen Studie auf einen bereits reduzierten Genaustausch zwischen den Populationen hin. Somit lässt sich feststellen, dass die Faktoren Fragmentierung und Störung genetische Diversität, ökologische Prozesse und Artendiversität in Wäldern jeweils auf unterschiedliche Weise beeinflussen. Um Konsequenzen derartiger Einflüsse folgerichtig abschätzen zu können, sind Studien auf unterschiedlichen Diversitätsebenen unabdingbar.

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In many plant species, the genetic template of early life-stages is formed by animal-mediated pollination and seed dispersal and has profound impact on further recruitment and population dynamics. Understanding the impact of pollination and seed dispersal on genetic patterns is a central issue in plant population biology. In my thesis, I investigated (i) contemporary dispersal and gene flow distances as well as (ii) genetic diversity and spatial genetic structure (SGS) across subsequent recruitment stages in a population of the animal-pollinated and dispersed tree Prunus africana in Kakamega Forest, West Kenya. Using microsatellite markers and parentage analyses, I inferred distances of pollen dispersal (father-to-mother), seed dispersal/maternal gene flow (mother-to-offspring) as well as paternal gene flow (father-to-offspring) for four early life stages of the species (seeds and fruits, current year seedlings, seedlings ≤ 3yr, seedlings > 3yr). Distances of pollen and seed dispersal as well as paternal gene flow were significantly shorter than expected from the spatial arrangement of trees and sampling plots. They were not affected by the density of conspecific trees in the surrounding. At the propagule stage, mean pollen dispersal distances were considerably (23-fold) longer than seed dispersal distances, and paternal gene flow distances exceeded maternal gene flow by a factor of 25. Seed dispersal distances were remarkably restricted, potentially leading to a strong initial SGS. The initial genetic template created by pollination and seed dispersal was extensively altered during later recruitment stages. Potential Janzen-Connell effects led to markedly increasing distances between offspring and both parental trees in older life stages. This showed that distance and density-dependent mortality factors are not exclusively related to the mother tree, but also to the father. Across subsequent recruitment stages, the pollen to seed dispersal ratio and the paternal to maternal gene flow ratio dropped to 2.1 and 3.4, respectively, in seedlings > 3yr. The relative changes in effective pollen dispersal, seed dispersal, and paternal gene flow distances across recruitment stages elucidate the mechanisms affecting the contribution of the two processes pollen and seed dispersal to overall gene flow. Using the same six microsatellite loci, I analyzed genetic diversity and SGS across five life stages, from seed rain to adults. Levels of genetic diversity within the studied P. africana population were comparable to other Prunus species and did not vary across life stages. In congruence with the short seed dispersal distances, I found significant SGS in all life stages. SGS decreased from seed and early seedling stages to older juvenile stages, and it was higher in adults than in late juveniles of the next generation. A comparison of the data with direct assessments of contemporary gene flow patterns indicate that distance- or density-dependent mortality, potentially due to Janzen-Connell effects, led to the initial decrease in SGS. Intergeneration variation in SGS could have been driven by variation in demographic processes, the effect of overlapping generations, and local selection processes. Overall, my study showed that complex sequential processes during recruitment contribute to the spatial genetic structure of tree populations. It highlights the importance of a multistage perspective for a comprehensive understanding of the impact of animal-mediated pollen and seed dispersal on spatial population dynamics and genetic patterns of trees.

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In this work self-assembling model systems in aqueous solution were studied. The systems contained charged polymers, polyelectrolytes, that were combined with oppositely charged counterions to build up supramolecular structures. With imaging, scattering and spectroscopic techniques it was investigated how the structure of building units influences the structure of their assemblies. Polyelectrolytes with different chemical structure, molecular weight and morphology were investigated. In addition to linear polyelectrolytes, semi-flexible cylindrical bottle-brush polymers that possess a defined cross-section and a relatively high persistence along the backbone were studied. The polyelectrolytes were combined with structural organic counterions having charge numbers one to four. Especially the self-assembly of polyelectrolytes with different tetravalent water-soluble porphyrins was studied. Porphyrins have a rigid aromatic structure that has a structural effect on their self-assembly behavior and through which porphyrins are capable of self-aggregation via π-π interaction. The main focus of the thesis is the self-assembly of cylindrical bottle-brush polyelectrolytes with tetravalent porphyrins. It was shown that the addition of porphyrins to oppositely charged brush molecules induces a hierarchical formation of stable nanoscale brush-porphyrin networks. The networks can be disconnected by addition of salt and single porphyrin-decoratedrncylindrical brush polymers are obtained. These two new morphologies, brush-porphyrin networks and porphyrin-decorated brush polymers, may have potential as functional materials with interesting mechanical and optical properties.