Darmstadt, Techn. Universiẗat, Diss., 2007. / Dateien im PDF-Format.

Motiviert durch strukturelle Eigenschaften molekularer Ähnlichkeitsnetzwerke werden die Evolution der größten Komponente eines Netzwerkes in zwei verschiedenen stochastischen Modellen, zufälligen Hypergraphen und zufälligen Schnittgraphen, untersucht. Zuerst wird bewiesen, dass die Anzahl der Knoten in der größten Komponente d-uniformer Hypergraphen einer Normalverteilung folgt. Der Beweis nutzt dabei ausschließlich probabilistische Argumente und keine enumerative Kombinatorik. Diesem grundlegenden Resultat folgen weitere Grenzwertsätze für die gemeinsame Verteilung von Knoten- und Kantenzahl sowie Sätze zur Zusammenhangswahrscheinlichkeit zufälliger Hypergraphen und zur asymptotischen Anzahl zusammenhängender Hypergraphen. Da das Hypergraphenmodell einige Eigenschaften der Realweltdaten nur unzureichend abbildet, wird anschließend die Evolution der größten Komponente in zufälligen Schnittgraphen, die Clustereigenschaften realer Netzwerke widerspiegeln, untersucht. Es wird gezeigt, dass zufällige Schnittgraphen sich von zufälligen (Hyper-)Graphen dadurch unterscheiden, dass (bei einer durchschnittlichen Nachbaranzahl von mehr als eins) weder die größte Komponente linear noch die zweitgrößte Komponente logarithmisch groß in Abhängigkeit von der Knotenzahl ist. Weiterhin wird ein Polynomialzeitalgorithmus zur Überdeckung der Kanten eines Graphen mit möglichst wenigen Cliquen (vollständigen Graphen) beschrieben und seine asymptotische Optimalität im Modell der zufälligen Schnittgraphen bewiesen. Anschließend wird die Entwicklung der chromatischen Zahl untersucht und gezeigt, dass zufällige Schnittgraphen mit hoher Wahrscheinlichkeit mittels verschiedener Greedystrategien optimal gefärbt werden können. Letztendlich zeigen Experimente auf realen Netzen eine Übereinstimmung mit den theoretischen Vorhersagen und legen eine gegenseitige Zertifizierung der Optimalität von Cliquen- und Färbungszahl durch Heuristiken nahe. / Motivated by structural properties of molecular similarity networks we study the behaviour of the component evolution in two different stochastic network models, that is random hypergraphs and random intersection graphs. We prove gaussian distribution for the number of vertices in the giant component of a random d-uniform hypergraph. We provide a proof using only probabilistic arguments, avoiding enumerative methods completely. This fundamental result is followed by further limit theorems concerning joint distributions of vertices and edges as well as the connectivity probability of random hypergraphs and the number of connected hypergraphs. Due to deficiencies of the hypergraph model in reflecting properties of the real--world data, we switch the model and study the evolution of the order of the largest component in the random intersection graph model which reflects some clustering properties of real--world networks. We show that for appropriate choice of the parameters random intersection graphs differ from random (hyper-)graphs in that neither the so-called giant component, appearing when the average number of neighbours of a vertex gets larger than one, has linear order nor is the second largest of logarithmic order in the number of vertices. Furthermore we describe a polynomial time algorithm for covering graphs with cliques, prove its asymptotic optimality in a random intersection graph model and study the evolution of the chromatic number in the model showing that, in a certain range of parameters, these random graphs can be coloured optimally with high probability using different greedy algorithms. Experiments on real network data confirm the positive theoretical predictions and suggest that heuristics for the clique and the chromatic number can work hand in hand proving mutual optimality.

<p>У раду је анализирана вaријабилност, генски ефекти, наслеђивање компонената приноса у укрштању пет сорти хексаплоидне пшенице (Triticum aestivum L.). Резултати истраживања<br />iv<br />указују да између родитеља и генерација потомстaва постоје значајне разлике у средњим вредностима испитиваних својстава. Методом диалелног укрштања утврђена је комбинациона способност родитељских линија и добијене су информације о природи генских ефеката за важне агрономске особине. У наслеђивању компонената приноса (висина биљке, маса биљке, дужина класа, број зрна по класу, маса зрна по класу и маса зрна по биљци), применом адитивно-доминантног модела, уочено је присуство неалелне интеракције &ndash; епистазе. Aнализом међузависних односа установљене су значајне или високо значајне вредности коефицијената корелације између већине испитиваних својстава.</p> / <p>U radu je analizirana varijabilnost, genski efekti, nasleđivanje komponenata prinosa u ukrštanju pet sorti heksaploidne pšenice (Triticum aestivum L.). Rezultati istraživanja<br />iv<br />ukazuju da između roditelja i generacija potomstava postoje značajne razlike u srednjim vrednostima ispitivanih svojstava. Metodom dialelnog ukrštanja utvrđena je kombinaciona sposobnost roditeljskih linija i dobijene su informacije o prirodi genskih efekata za važne agronomske osobine. U nasleđivanju komponenata prinosa (visina biljke, masa biljke, dužina klasa, broj zrna po klasu, masa zrna po klasu i masa zrna po biljci), primenom aditivno-dominantnog modela, uočeno je prisustvo nealelne interakcije &ndash; epistaze. Analizom međuzavisnih odnosa ustanovljene su značajne ili visoko značajne vrednosti koeficijenata korelacije između većine ispitivanih svojstava.</p> / <p>A study has been conducted to assess variability, gene effect and inheritance of yield components in five crosses of hexaploid wheat genotypes (Triticum aestivum L.). The results of the study have shown that the mean values of parents and their progenies were significantly different. In diallel<br />vii<br />crossing information about combining ability of parental lines and the nature of genetic effects for some important agronomic traits had been obtained. Non-allelic interactions, epistatic gene effect, were observed in the inheritance of yield components (stem height, biomass, spike length, kernel number per spike, kernel weight per spike and kernel weight per plant) using the additive-dominance model. Significant and highly significant values of correlation coefficients were calculated for the most of studied traits.<br />&nbsp;</p>

<p>Značajan porast prevalence dentalnih erozija u savremenom dru&scaron;tvu, zahteva sve vi&scaron;e pažnje ka&nbsp; istraživanju njihove etiologije i preventivnih mera koje se mogu preduzeti. Cilj ove studije bio je da se ispita erozivni potencijal gaziranih napitaka i njihov uticaj na zubna tkiva, tokom različitih vremenskih intervala.<br />Stepen kiselosti izražen pH vrednostima za svaki ispitivani napitak (gaziranu vodu &bdquo;Knjaz Milo&scaron;&ldquo;, Coca-Cola-u i Schweppes Bitter Lemon), određen je odmah po otvaranju ambalaže sa napitkom, nakon 5 i 60 minuta kao i nakon 12 i 24 sata od potapanja zubnih uzoraka. U ovoj studiji posmatrane su mikroskopske promene proučavanjem skening elektronske mikrofotografije spolja&scaron;nje povr&scaron;ine gleđi, kao i uzdužni presek gleđi i dentina zuba nakon izlaganja gore navedenim napicima 5 i 60 minuta,12 i 24 sata kao i 7 i 30 dana, ali i makroskopske promene boje i strukture gleđi u svim navedenim vremenskim intervalima. Za određivanje stepena nastalih mikroskopskih i makroskopskih promena primenjene su individualno prilagođene skale.<br />Početna pH vrednost svih ispitivanih napitaka je niža od kritične pH vrednosti za demineralizaciju gleđi. Sa porastom vremena od potapanja zubnih uzoraka u napitke, njihova pH vrednost značajno raste. Na SEM mikrofotografijama gleđi i dentina se uočavaju promene u morfologiji, čiji intenzitet zavisi od vrste napitka i vremena koje je uzorak u njemu proveo. Centralni tip demineralizacije prisutan je kod uzoraka potopljenih u kiselu vodu i Coca Cola napitak a periferni kod Schweppes Bitter Lemon. Intenzitet promena zubnih tkiva raste u funkciji vremena, ali statistički značajna razlika ne postoji između svih vremenskih intervala. Zubi koji su bili izloženi delovanju gazirane vode &bdquo;Knjaz Milo&scaron;&ldquo; ne pokazuju izmene u makroskopskom izgledu, za razliku od zuba koji su tretirani Coca-Cola-om i Schweppes Bitter Lemon-om čiji intenzitet izmenjenosti raste u funkciji vremena, s tim da je statitički značajna razlika prisutna između pojedinih vremenskih intervala. S obzirom na erozivni potencijal i promene koje gazirani napitci izazivaju u in vitro условима, potrebno je preduzeti odgovarajuće preventivne mere kako bi se smanjio njihov uticaj na zube u in vivo uslovima.</p> / <p>Značajan porast prevalence dentalnih erozija u savremenom dru&scaron;tvu, zahteva sve vi&scaron;e pažnje ka&nbsp; istraživanju njihove etiologije i preventivnih mera koje se mogu preduzeti. Cilj ove studije bio je da se ispita erozivni potencijal gaziranih napitaka i njihov uticaj na zubna tkiva, tokom različitih vremenskih intervala.<br />Stepen kiselosti izražen pH vrednostima za svaki ispitivani napitak (gaziranu vodu &bdquo;Knjaz Milo&scaron;&ldquo;, Coca-Cola-u i Schweppes Bitter Lemon), određen je odmah po otvaranju ambalaže sa napitkom, nakon 5 i 60 minuta kao i nakon 12 i 24 sata od potapanja zubnih uzoraka. U ovoj studiji posmatrane su mikroskopske promene proučavanjem skening elektronske mikrofotografije spolja&scaron;nje povr&scaron;ine gleđi, kao i uzdužni presek gleđi i dentina zuba nakon izlaganja gore navedenim napicima 5 i 60 minuta,12 i 24 sata kao i 7 i 30 dana, ali i makroskopske promene boje i strukture gleđi u svim navedenim vremenskim intervalima. Za određivanje stepena nastalih mikroskopskih i makroskopskih promena primenjene su individualno prilagođene skale.<br />Početna pH vrednost svih ispitivanih napitaka je niža od kritične pH vrednosti za demineralizaciju gleđi. Sa porastom vremena od potapanja zubnih uzoraka u napitke, njihova pH vrednost značajno raste. Na SEM mikrofotografijama gleđi i dentina se uočavaju promene u morfologiji, čiji intenzitet zavisi od vrste napitka i vremena koje je uzorak u njemu proveo. Centralni tip demineralizacije prisutan je kod uzoraka potopljenih u kiselu vodu i Coca Cola napitak a periferni kod Schweppes Bitter Lemon. Intenzitet promena zubnih tkiva raste u funkciji vremena, ali statistički značajna razlika ne postoji između svih vremenskih intervala. Zubi koji su bili izloženi delovanju gazirane vode &bdquo;Knjaz Milo&scaron;&ldquo; ne pokazuju izmene u makroskopskom izgledu, za razliku od zuba koji su tretirani Coca-Cola-om i Schweppes Bitter Lemon-om čiji intenzitet izmenjenosti raste u funkciji vremena, s tim da je statitički značajna razlika prisutna između pojedinih vremenskih intervala. S obzirom na erozivni potencijal i promene koje gazirani napitci izazivaju u in vitro uslovima, potrebno je preduzeti odgovarajuće preventivne mere kako bi se smanjio njihov uticaj na zube u in vivo uslovima.</p> / <p>Due to the fact that prevalence of dental erosion significantly increased in modern society, it is important to investigate its etiological factors and all available preventive measures. The aim of this study was to investigate erosive potential of carbonated beverages and their influence on dental hard tissues, during different intervals.<br />The acidity or pH level was measured for each beverage (carbonated water &bdquo;Knjaz Milos&ldquo;, Coca-cola and Schweppes Bitter Lemon), on opening of the bottle, after 5 minutes and 60 minutes, and after 12 hours and 24 hours immersion of tooth samples in adequate beverage. In this study, microscopic changes of dental tissues were examined using a scanning electron microphotography of outer surface of enamel and longitudinal section of enamel and dentin, after exposure to beverages during 5 and 60 minutes, 12 and 24 hours, and 7 and 30 days, as well as macroscopic changes of tooth color and structure at same intervals. Individually adopted scales were used for grading of the severity of microscopic and macroscopic changes.<br />Initiated pH value of each tested beverage was lower than critical pH for enamel demineralisation. SEM images of enamel and dentin showed different morphology changes, which intensivity depended on type of beverages and time that sample were stored. Central type of demineralisation was visible on samples treated with carbonated water and Coca-Cola, while peripheral type of demineralisation was detected on samples treated with Schweppes Bitter Lemon. The intensity of alterations of dental tissues increased during time, but there was not statistically significant difference between all intervals. There wasn&rsquo;t detected macroscopic changes on teeth stored in carbonated water, while teeth treated with Coca-Cola and Schweppes Bitter Lemon showed changes which intensity increased during time, but statistically significant difference between all intervals wasn&rsquo;t detected. Due to erosive potential and changes influenced by carbonated beverages in vitro, preventive measures are necessary for reducing their effect on teeth in vivo.</p>

Zufallsgraphen sind Graphen, die durch einen zufälligen Prozess erzeugt werden. Ein im Zusammenhang mit Zufallsgraphen häufig auftretendes Phänomen ist, dass sich die typischen Eigenschaften eines Graphen durch Hinzufügen einer relativ kleinen Anzahl von zufälligen Kanten radikal verändern. Wir betrachten den Zufallsgraphen G(n,p), der n Knoten enthält und in dem zwei Knoten unabhängig und mit Wahrscheinlichkeit p durch eine Kante verbunden sind. Erdös und Rényi zeigten, dass ein Graph für p = c/n und c < 1 mit hoher Wahrscheinlichkeit aus Komponenten mit O(log n) Knoten besteht. Für p = c/n und c > 1 enthält G(n,p) mit hoher Wahrscheinlichkeit genau eine Komponente mit Theta(n) Knoten, welche viel größer als alle anderen Komponenten ist. Dieser Punkt in der Entwicklung des Graphen, an dem sich die Komponentenstruktur durch eine kleine Erhöhung der Anzahl von Kanten stark verändert, wird Phasenübergang genannt. Wenn p = (1+epsilon)/n, wobei epsilon eine Funktion von n ist, die gegen 0 geht, sind wir in der kritischen Phase, welche eine der interessantesten Phasen der Entwicklung des Zufallsgraphen ist. In dieser Arbeit betrachten wir drei verschiedene Modelle von Zufallsgraphen. In Kapitel 4 studieren wir den Minimalgrad-Graphenprozess. In diesem Prozess werden sukzessive Kanten vw hinzugefügt, wobei v ein zuällig ausgewählter Knoten von minimalem Grad ist. Wir beweisen, dass es in diesem Graphenprozess einen Phasenübergang, und wie im G(n,p) einen Doppelsprung, gibt. Die zwei anderen Modelle sind Zufallsgraphen mit einer vorgeschriebenen Gradfolge und zufällige gerichtete Graphen. Für diese Modelle wurde bereits in den Arbeiten von Molloy und Reed (1995), Karp (1990) und Luczak (1990) gezeigt, dass es einen Phasenübergang bezüglich der Komponentenstruktur gibt. In dieser Arbeit untersuchen wir in Kapitel 5 und 6 die kritische Phase dieser Prozesse genauer, und zeigen, dass sich diese Modelle ähnlich zum G(n,p) verhalten. / Random graphs are graphs which are created by a random process. A common phenomenon in random graphs is that the typical properties of a graph change radically by the addition of a relatively small number of random edges. This phenomenon was first investigated in the seminal papers of Erdös and Rényi. We consider the graph G(n,p) which contains n vertices, and where any two vertices are connected by an edge independently with probability p. Erdös and Rényi showed that if p = c/n$ and c < 1, then with high probability G(n,p) consists of components with O(log n) vertices. If p = c/n$ and c>1, then with high probability G(n,p) contains exactly one component, called the giant component, with Theta(n) vertices, which is much larger than all other components. The point at which the giant component is formed is called the phase transition. If we let $p = (1+epsilon)/n$, where epsilon is a function of n tending to 0, we are in the critical phase of the random graph, which is one of the most interesting phases in the evolution of the random graph. In this case the structure depends on how fast epsilon tends to 0. In this dissertation we consider three different random graph models. In Chapter 4 we consider the so-called minimum degree graph process. In this process edges vw are added successively, where v is a randomly chosen vertex with minimum degree. We prove that a phase transition occurs in this graph process as well, and also that it undergoes a double jump, similar to G(n,p). The two other models we will consider, are random graphs with a given degree sequence and random directed graphs. In these models the point of the phase transition has already been found, by Molloy and Reed (1995), Karp (1990) and Luczak (1990). In Chapter 5 and 6 we investigate the critical phase of these processes, and show that their behaviour resembles G(n,p).

Product development process begins at a very abstract level of understanding the requirements. The data needs to be passed on the next phase of development. This happens after every stage for further development and finally a product is made. This thesis deals with the data exchange process of software development process in specific. The problem lies in handling of data in terms of redundancy and versions of the data to be handled. Also, once data passed on to next stage, the ability to exchange it in reveres order is not existent in evident forms. The results found during this thesis discusses the solutions for the problem by getting all the data at same level, in terms of its format. Having the concept ready, provides an opportunity to use this data based on our requirements. In this research, the problem of data consistency, data verification is dealt with. This data is used during the development and data merging from various sources. The concept that is formulated can be expanded to a wide variety of applications with respect to development process. If the process involves exchange of data - scalability and generalization are the main foundation concepts that are contained within the concept.

Intellectual Capital is considered an intangible asset that occurs in many organizations, especially service organizations, mainly because South African banks offer a service to their customers. This results in Intellectual Capital being an important factor in obtaining competitive advantage and success. If organizations do not consider Intellectual Capital as an important factor, it could lead to brands devoted to competitors, the loss of talented employees and unsatisfied customers. This in turn could affect the image of the organization. Financial organizations have the responsibility to identify and to monitor the various components of Intellectual Capital. Intellectual Capital consists of three main components, namely, Human Capital, Structural Capital and Relationship Capital. One of the biggest challenges of Intellectual Capital is that no one hundred percent accurate measurement method exists to measure Intellectual Capital items. An inaccurate value of Intellectual Capital leads to inaccurate disclosure of financial statements which, in turn, could result in various stakeholders (such as shareholders and public) losing faith and confidence in the organization. The purpose of the study is to describe the various components of Intellectual Capital, the linked costs and to examine the measurement of Intellectual Capital, in order to provide accurate disclosure. An empirical study was conducted to assess the impact and importance of Intellectual Capital in a South African bank. Recommendations were made on the manner problems regarding Intellectual Capital are managed and dealt with by the management of the bank. / Thesis (MCom (Management Accountancy))--North-West University, Potchefstroom Campus, 2013.

Intellectual Capital is considered an intangible asset that occurs in many organizations, especially service organizations, mainly because South African banks offer a service to their customers. This results in Intellectual Capital being an important factor in obtaining competitive advantage and success. If organizations do not consider Intellectual Capital as an important factor, it could lead to brands devoted to competitors, the loss of talented employees and unsatisfied customers. This in turn could affect the image of the organization. Financial organizations have the responsibility to identify and to monitor the various components of Intellectual Capital. Intellectual Capital consists of three main components, namely, Human Capital, Structural Capital and Relationship Capital. One of the biggest challenges of Intellectual Capital is that no one hundred percent accurate measurement method exists to measure Intellectual Capital items. An inaccurate value of Intellectual Capital leads to inaccurate disclosure of financial statements which, in turn, could result in various stakeholders (such as shareholders and public) losing faith and confidence in the organization. The purpose of the study is to describe the various components of Intellectual Capital, the linked costs and to examine the measurement of Intellectual Capital, in order to provide accurate disclosure. An empirical study was conducted to assess the impact and importance of Intellectual Capital in a South African bank. Recommendations were made on the manner problems regarding Intellectual Capital are managed and dealt with by the management of the bank. / Thesis (MCom (Management Accountancy))--North-West University, Potchefstroom Campus, 2013.

Werden Softwaresysteme auf Basis eines komponentenorientierten Architekturparadigmas entwickelt, stellt sich die Frage, welches Vorgehensmodell zur Projektabwicklung herangezogen werden kann. In der Literatur werden unterschiedliche Vorgehensmodelle zur komponentenorientierten Softwareentwicklung vorgeschlagen. Aus diesen werden in der vorliegenden Untersuchung vier Modelle ausgewählt: Catalysis, Perspective, Rational Unified Process 2002 und V-Modell ’97. Die ausgewählten Vorgehensmodelle werden auf Basis eines allgemeinen Rahmens beschrieben und verglichen. Dabei werden die Aspekte Terminologie, Klassifizierung, Komponentenbegriff, Abdeckung des Lebenszyklus einer Komponente, Abdeckung der Tätigkeitsbereiche, Prozessarchitektur, Prozesssteuerung, Rollenabdeckung und Adaption untersucht. Komponentenorientierte Vorgehensmodelle sind sowohl Weiterentwicklungen bekannter konventioneller Vorgehensmodelle als auch ausschließlich auf die komponentenorientierte Entwicklung ausgerichtet. Obwohl die ausgewählten Vorgehensmodelle speziell auf eine komponentenorientierte Entwicklung ausgerichtet sind, zeigt sich, dass wesentliche Lebenszyklen einer Komponente nur rudimentär behandelt werden. Eine Ausnahme bildet hier Catalysis.

Die Besiedlung von Gewässern durch Fische, ist neben abiotischen Lebensraumbedingungen auch von der Erreichbarkeit d.h. von der art-spezifischen Ausbreitungsfähigkeit sowie von Wanderhindernissen abhängig. Der erste Teil dieser Arbeit bietet die erste umfangreiche quantitative Analyse von Ausbreitungsmustern und -distanzen von Flussfischen. Aus der Fachliteratur wurden 160 empirische Datensätze aus 71 wissenschaftlichen Studien zur Ausbreitung von 62 Fischarten in Flüssen extrahiert und an leptokurse Wahrscheinlichkeits-Dichte-Funktionen (Dispersal kernel) angepasst. Es konnte bei Fischpopulationen zwischen einer stationären (ca. 2/3) und einer mobilen Komponente (ca. 1/3) unterschieden werden deren Ausbreitungsdistanzen von vier Faktoren abhängig sind: Fischlänge, Form der Schwanzflosse, Fließgewässergröße, betrachtete Zeitspanne. Der zweite Teil dieser Arbeit widmet sich dem neu entwickelten Fischausbreitungsmodell FIDIMO einem GIS-Softwareprogramm zur Modellierung und Simulation der räumlichen und zeitlichen Ausbreitungsmuster von Fischen in Flüssen unter Berücksichtigung von Wanderhindernissen. FIDIMO verknüpft konzeptionelle Überlegungen zu Ausbreitungsmodellen in verzweigten Fließgewässernetzwerken mit empirisch bestimmten leptokursen Fischausbreitungskurven unter ausschließlicher Verwendung von Free and Open Source Software. Im dritten Teil der Arbeit wurde FIDIMO zur Modellierung der Ausbreitung von 17 Fischarten angewendet um die Einflüsse von (i) Habitatqualität, (ii) Ausbreitungsfähigkeit und (iii) Fließgewässer-Fragmentierung auf die Besiedlungsmuster durch Fische zu bestimmen. Die Ergebnisse zeigen, dass die artspezifische Habitatqualität und Ausbreitungsfähigkeit die Besiedlung maßgeblich bestimmen. Dagegen wurde kein signifikanter Einfluss von Barrieren auf das Vorkommen einer Art gefunden. Über längere Zeiträume sinkt der Einfluss von Fischausbreitung auf das lokale Vorkommen einer Fischart während die Habitatqualität relativ wichtiger wird. / The colonisation of rivers by fishes is directly linked to abiotic habitat conditions but often impaired by dispersal abilities of fishes and movement constraints such as barriers. The first part of this thesis provides the first comprehensive quantitative analysis of freshwater fish movement while considering fish populations consisting of differently mobile specimens. 160 empirical datasets from 71 studies on the movement of 62 riverine fish species were analysed based on refitted leptokurtic probability-density functions (dispersal kernels). A share of one third and two thirds emerged as a general pattern of the mobile and stationary component of a fish population, respectively. Moreover, four variables were identified primarily determining dispersal distances: fish length, aspect ratio of the caudal fin, river size and time. In the second part of the thesis, the novel fish dispersal model FIDIMO is introduced. FIDIMO provides a GIS-tool for predicting and simulating spatio-temporal patterns of fish dispersal in dendritic river networks considering movement barriers. The fish dispersal model FIDIMO links conceptual considerations on dispersal modelling with empirically observed leptokurtic fish movement patterns and the strengths of geographically explicit modelling in Free and Open Source GIS. In the third part of the thesis, FIDIMO was applied for modelling dispersal of 17 fish species to disentangle the effects of (i) habitat suitability, (ii) dispersal constraints and (iii) network fragmentation on the distribution of river fishes. The results show significant positive effects of both, local-scale habitat quality and species-specific dispersal ability on the distribution of river fishes, whereas no significant effect of barriers influencing the presence of a species could be found. Over longer time periods the importance of dispersal decreased in favour of habitat suitability becoming relatively more relevant in determining species'' presence.