Problems of population genetics are magnified by problems of big data. My dissertation spans the disciplines of computer science and population genetics, leveraging computational approaches to biological problems to address issues in genomics research. In this dissertation I develop more efficient metric search algorithms. I also show that vast majority of the genomes of great apes are impacted by the forces of natural selection. Finally, I introduce a heuristic to identify neutralomes—regions that are evolving with minimal selective pressures—and use these neutralomes for inferences on effective population size in great apes. We begin with a formal and far-reaching problem that impacts a broad array of disciplines including biology and computer science; the 𝑘-nearest neighbors problem in generalized metric spaces. The 𝑘-nearest neighbors (𝑘-NN) problem is deceptively simple. The problem is as follows: given a query q and dataset D of size 𝑛, find the 𝑘-closest points to q. This problem can be easily solved by algorithms that compute 𝑘th order statistics in O(𝑛) time and space. It follows that if D can be ordered, then it is perhaps possible to solve 𝑘-NN queries in sublinear time. While this is not possible for an arbitrary distance function on the points in D, I show that if the points are constrained by the triangle inequality (such as with metric spaces), then the dataset can be properly organized into a dispersion tree (Appendix A). Dispersion trees are a hierarchical data structure that is built around a large dispersed set of points. Dispersion trees have construction times that are sub-quadratic (O(𝑛¹·⁵ log⁡ 𝑛)) and use O(𝑛) space, and they use a provably optimal search strategy that minimizes the number of times the distance function is invoked. While all metric data structures have worst-case O(𝑛) search times, dispersion trees have average-case search times that are substantially faster than a large sampling of comparable data structures in the vast majority of spaces sampled. Exceptions to this include extremely high dimensional space (d>20) which devolve into near-linear scans of the dataset, and unstructured low-dimensional (d<6) Euclidean spaces. Dispersion trees have empirical search times that appear to scale as O(𝑛ᶜ) for 0<c<1. As solutions to the 𝑘-NN problem are in general too slow to be used effectively in the arena of big data in genomics, it is my hope that dispersion trees may help lift this barrier. With source-code that is freely available for academic use, dispersion trees may be useful for nearest neighbor classification problems in machine learning, fast read-mapping against a reference genome, and as a general computational tool for problems such clustering. Next, I turn to problems in population genomics. Genomic patterns of diversity are a complex function of the interplay between demographics, natural selection and mechanistic forces. A central tenet of population genetics is the neutral theory of molecular evolution which states the vast majority of changes at the molecular level are (relatively) selectively neutral; that is, they do not effect fitness. A corollary of the neutral theory is that the frequency of most alleles in populations are dictated by neutral processes and not selective processes. The forces of natural selection impact not just the site of selection, but linked neutral sites as well. I proposed an empirical assessment of the extents of linked selection in the human genome (Appendix B). Recombination decouples sites of selection from the genomic background, thus it serves to mitigate the effects of linked selection. I use two metrics on recombination, both the minimum genetic distance to genes and local rates of recombination, to parse the effects of linked selection into selection from genic and nongenic sources in the human genome. My empirical assessment shows profound linked selective effects from nongenic sources, with these effects being greater than that of genic sources on the autosomes, as well as generally greater effects on the X chromosome than on the autosomes. I quantify these trends using multiple linear regression, and then I model the effects of linked selection to conserved elements across the whole of the genome. Places predicted to be neutral by my model do not, unlike the vast majority of the genome, show these linked selective effects. This demonstrates that linkage to these regulatory elements, and not some other mechanistic force, accounts for our findings. Further, neutrally evolving regions are extremely rare (~1%) in the genome, and despite generally larger linked selective effects on the X chromosome, the size of this “neutralome” is proportionally larger on the X chromosome than on the autosomes. To account for this and to extend my findings to other great apes I improve on my procedure to find neutralomes, and apply this procedure to the genome of humans, Nigerian chimpanzees, bonobos, and western lowland gorillas (Appendix C). In doing so I show that like humans, these other apes are also enormously impacted by linked selection, with their neutralomes being substantially smaller than the neutralomes of humans. I then use my genomic predictions on neutrality to see how the landscape of linked selection changes across the X chromosome and the autosomes in regions close to, and far from, genes. While I had previously demonstrated the linked selective forces near genes are stronger on the X chromosome than on the autosomes in these taxa, I show that regions far from genes show the opposite; regions far from genes show more selection from noncoding targets on the autosomes than on the X chromosome. This finding is replicated across our great ape samples. Further, inferences on the relative effective population size of the X chromosome and the autosomes both near and far from genes can be biased as a result.

Complex networks have been successfully employed to represent different levels of biological systems, ranging from gene regulation to protein-protein interactions and metabolism. Network-based research has mainly focused on identifying unifying structural properties, including small average path length, large clustering coefficient, heavy-tail degree distribution, and hierarchical organization, viewed as requirements for efficient and robust system architectures. Existing studies estimate the significance of network properties using a generic randomization scheme - a Markov-chain switching algorithm - which generates unrealistic reactions in metabolic networks, as it does not account for the physical principles underlying metabolism. Therefore, it is unclear whether the properties identified with this generic approach are related to the functions of metabolic networks. Within this doctoral thesis, I have developed an algorithm for mass-balanced randomization of metabolic networks, which runs in polynomial time and samples networks almost uniformly at random. The properties of biological systems result from two fundamental origins: ubiquitous physical principles and a complex history of evolutionary pressure. The latter determines the cellular functions and abilities required for an organism’s survival. Consequently, the functionally important properties of biological systems result from evolutionary pressure. By employing randomization under physical constraints, the salient structural properties, i.e., the smallworld property, degree distributions, and biosynthetic capabilities of six metabolic networks from all kingdoms of life are shown to be independent of physical constraints, and thus likely to be related to evolution and functional organization of metabolism. This stands in stark contrast to the results obtained from the commonly applied switching algorithm. In addition, a novel network property is devised to quantify the importance of reactions by simulating the impact of their knockout. The relevance of the identified reactions is verified by the findings of existing experimental studies demonstrating the severity of the respective knockouts. The results suggest that the novel property may be used to determine the reactions important for viability of organisms. Next, the algorithm is employed to analyze the dependence between mass balance and thermodynamic properties of Escherichia coli metabolism. The thermodynamic landscape in the vicinity of the metabolic network reveals two regimes of randomized networks: those with thermodynamically favorable reactions, similar to the original network, and those with less favorable reactions. The results suggest that there is an intrinsic dependency between thermodynamic favorability and evolutionary optimization. The method is further extended to optimizing metabolic pathways by introducing novel chemically feasibly reactions. The results suggest that, in three organisms of biotechnological importance, introduction of the identified reactions may allow for optimizing their growth. The approach is general and allows identifying chemical reactions which modulate the performance with respect to any given objective function, such as the production of valuable compounds or the targeted suppression of pathway activity. These theoretical developments can find applications in metabolic engineering or disease treatment. The developed randomization method proposes a novel approach to measuring the significance of biological network properties, and establishes a connection between large-scale approaches and biological function. The results may provide important insights into the functional principles of metabolic networks, and open up new possibilities for their engineering. / In der Systembiologie und Bioinformatik wurden in den letzten Jahren immer komplexere Netzwerke zur Beschreibung verschiedener biologischer Prozesse, wie Genregulation, Protein-Interaktionen und Stoffwechsel (Metabolismus) rekonstruiert. Ein Hauptziel der Forschung besteht darin, die strukturellen Eigenschaften von Netzwerken für Vorhersagen über deren Funktion nutzbar zu machen, also eine Verbindung zwischen Netzwerkeigenschaften und Funktion herzustellen. Die netzwerkbasierte Forschung zielte bisher vor allem darauf ab, gemeinsame Eigenschaften von Netzwerken unterschiedlichen Ursprungs zu entdecken. Dazu zählen die durchschnittliche Länge von Verbindungen im Netzwerk, die Häufigkeit redundanter Verbindungen, oder die hierarchische Organisation der Netzwerke, welche als Voraussetzungen für effiziente Kommunikationswege und Robustheit angesehen werden. Dabei muss zunächst bestimmt werden, welche Eigenschaften für die Funktion eines Netzwerks von besonderer Bedeutung (Signifikanz) sind. Die bisherigen Studien verwenden dafür eine Methode zur Erzeugung von Zufallsnetzwerken, welche bei der Anwendung auf Stoffwechselnetzwerke unrealistische chemische Reaktionen erzeugt, da sie physikalische Prinzipien missachtet. Es ist daher fraglich, ob die Eigenschaften von Stoffwechselnetzwerken, welche mit dieser generischen Methode identifiziert werden, von Bedeutung für dessen biologische Funktion sind, und somit für aussagekräftige Vorhersagen in der Biologie verwendet werden können. In meiner Dissertation habe ich eine Methode zur Erzeugung von Zufallsnetzwerken entwickelt, welche physikalische Grundprinzipien berücksichtigt, und somit eine realistische Bewertung der Signifikanz von Netzwerkeigenschaften ermöglicht. Die Ergebnisse zeigen anhand der Stoffwechselnetzwerke von sechs Organismen, dass viele der meistuntersuchten Netzwerkeigenschaften, wie das Kleine-Welt-Phänomen und die Vorhersage der Biosynthese von Stoffwechselprodukten, von herausragender Bedeutung für deren biologische Funktion sind, und somit für Vorhersagen und Modellierung verwendet werden können. Die Methode ermöglicht die Identifikation von chemischen Reaktionen, welche wahrscheinlich von lebenswichtiger Bedeutung für den Organismus sind. Weiterhin erlaubt die Methode die Vorhersage von bisher unbekannten, aber physikalisch möglichen Reaktionen, welche spezifische Zellfunktionen, wie erhöhtes Wachstum in Mikroorganismen, ermöglichen könnten. Die Methode bietet einen neuartigen Ansatz zur Bestimmung der funktional relevanten Eigenschaften biologischer Netzwerke, und eröffnet neue Möglichkeiten für deren Manipulation.

<p>This dissertation consists of four chapters. The first three chapters examine protected areas (or parks) from multiple perspectives. Parks are the first, and often only, line of defense in efforts to conserve biodiversity. Understanding of their promise and problems is necessary to achieve conservation outcomes. Chapter One determines vegetation patterns in and around parks of differing management categories across the Amazon, Congo, South American Atlantic Coast, and West African forests. Within these forests, protected areas are the principle defense against forest loss and species extinctions. In the Amazon and Congo, parks are generally large and retain high levels of forest cover, as do their surroundings. In contrast, parks in the Atlantic Coast forest and West Africa show sharp boundaries in forest cover at their edges. This effective protection of forest cover is partially offset by their very small size: little area is deep inside park boundaries. Compared to West Africa, areas outside parks in the Atlantic Coast forest are unusually fragmented. </p><p>Chapter Two addresses a human dimension of protected areas. Given certain characteristics, parks areas may either attract or repel human settlement. Disproportionate increases in population growth near park boundaries may threaten their ability to conserve biodiversity. Using decadal population datasets, we analyze population growth across 45 countries and 304 parks. We find no evidence for population growth near parks to be greater than growth of rural areas in the same country. Furthermore, we argue that what growth does occur near parks likely results from a general expansion of nearby population centers. Parks may experience unusual population pressures near their edges; indeed, individual case studies provide examples. There is no evidence, however, of a general pattern of disproportionate population growth near their boundaries.</p><p>Chapter Three provides a review of common approaches to evaluating protection's impact on deforestation, identifies three hurdles to empirical evaluation, and notes that matching techniques from economic impact evaluation address those hurdles. The central hurdle derives from the fact that protected areas are distributed non-randomly across landscapes. Matching controls for landscape characteristics when inferring the impact of protection. Applications of matching have revealed considerably lower impact estimates of forest protection than produced by other methods. These results indicate the importance of variation across locations in how much impact protection could possibly have on rates of deforestation.</p><p>Chapter Four departs from the focus of protected areas and instead addresses a more theoretical aspect of community ecology. Ecological theories suggest that food webs might consist of groups of species forming blocks, compartments or guilds. Chapter Four considers ecological networks (subsets of complete food webs) involving species at adjacent trophic levels. Reciprocal specializations occur when (say) a pollinator (or group of pollinators) specializes on a particular flower species (or group of such species) and vice versa. We characterize the level of reciprocal specialization for various classes of networks. Our analyses include both antagonistic interactions (particularly parasitoids and their hosts), and mutualistic ones (such as insects and the flowers that they pollinate). We also examine whether trophic patterns might be palimpsests. That is, there might be reciprocal specialization within taxonomically related species within a network, but these might be obscured when these relationships are combined. Reciprocal specializations are rare in all these systems even when tested using the most conservative null model.</p> / Dissertation

The Lake Malawi cichlid fishes are a pre-eminent example of adaptive evolutionary radiation. The diversity of species (nearly 1000 extant) is mirrored by an array of variation in dozens of phenotypes (e.g. trophic morphology, tooth shape, color patterns, behavior, development). The unique characteristics of this system have produced unparalleled diversity with very little genetic differentiation between species. This dissertation is composed of four studies addressing different aspects of the variation in the LM cichlids and the mechanisms generating and maintaining this level of diversity at multiple biological levels. Community-level diversity is investigated using null model analysis of species co-occurrence data. We detect signals of non-random community assembly at only the broadest and finest spatial scales. Based on the unique ecological and evolutionary characteristics of this assemblage we suggest that different mechanisms are responsible for these patterns. A core‟ group of species is posited to act as a foundation on which these diverse communities are created as a result of fine-scale species interactions. We identify both positive and negative depth-based correlations between species and suggest these interactions play an important role in species diversity in these fish. The Lake Malawi cichlids exhibit an array of trophic morphologies which may play a role in the fine-scale species interactions described in chapter one. In the second chapter we build a genetic model to predict the evolution of jaw morphology and a complex functional jaw trait. We use a complex biomechanical system, the 4-bar jaw linkage, to simulate trait evolution during interspecific hybridizations. We find rampant transgression (trait values beyond parental distributions) in jaw function in a large proportion of potential crosses. This result is characterized by a lack of novel morphological components but rather is the result of recombinations of existing component traits thus producing functional novelty. In the third chapter we create a laboratory cross of one of the parental combinations suggested from the genetic model. The results of this study serve as a proof of principle to the simulations as we observe a large proportion of transgressive 4-bar function in the F2. As predicted this diversity is produced in the absence of transgressive morphology. We contrast these results between this complex system and data generated from several simple jaw lever traits and report differences in the patterns. Using quantitative trait locus (QTL) mapping approaches we examine the genetic basis for complex and simple jaw traits and discuss correlative patterns within and between systems. Finally we examine the genetic architecture of sex-determination and color morphs in this hybrid cross. We find both ZW and XY sex systems segregating as well as linkage to sex-specific color patterns. Several loci and epistatic interactions are associated with sex-determination and color morphs in this cross. The orange-blotch (OB) color is found associated with ZW as predicted from previous work but a previously undescribed (in these species) male nuptial color (blue) is found associated with both ZW and XY genetic systems as well as other loci segregating for sex-determination. These results are discussed in the context of models of sex chromosome evolution as a result of sexual conflict and the potential importance of sexual selection in the diversification of Lake Malawi cichlids. Overall we observe various mechanisms generating and maintaining diversity at different levels of biological organization. We use community co-occurrence analyses, genetic simulation, and QTL analysis of an F2 hybrid population to examine these mechanisms in this rapidly radiating assemblage. These results bolster our understanding of the origins of diversity and the interplay between variation and aspects of evolution in all biological systems.

Compreender os fatores que afetam a distribuição das espécies tem sido um dos principais objetivos dos ecólogos. Atualmente, sabe-se que os processos ecológicos e evolutivos moldam a dinâmica de especiação e extinção de espécies, e determinam a distribuição e abundância das mesmas. Ao longo dos últimos anos, tem havido um aumento no número de estudos que utilizam informação filogenética para explicar as dinâmicas populacionais e as distribuições de espécies, e que buscam identificar os mecanismos responsáveis pela montagem das comunidades. Interações das espécies, sejam elas intraespecífica, interespecífica ou com o ambiente, ocorrem baseadas nas diferenças e semelhanças fenotípicas. Essas variações fenotípicas tem origem na evolução das espécies, e com isso espera-se que as espécies proximamente relacionadas tendam a ser ecologicamente mais semelhantes entre si do que as espécies distantemente relacionadas. Esta concepção tem dado origem a um conceito importante, com implicações para estudos tanto ecológicos quanto evolutivos: o conceito de conservação filogenética de nicho, isto é, quando as espécies relacionadas mantêm seus nichos ancestrais ao longo do tempo evolutivo. Esse padrão tem importância para diversas áreas de ecologia, permitindo a ligação das espécies aos processos ecológicos e auxiliando na maior compreensão da ecologia evolutiva das diferentes linhagens. Devido à sua importância, é fundamental o desenvolvimento de métodos estatísticos adequados para quantificar esses padrões e inferir os processos que o subjazem. Atualmente, os métodos utilizados para inferir conservação filogenética de nicho são, em sua maioria, incompatíveis com determinados conceitos ecológicos e não abrangem todos os tipos de dados e esse fato explica uma visão incompleta dos processos presentes nas comunidades e conflitante com o objetivo de muitos estudos ecológicos e conservacionistas que buscam vincular as espécies aos processos ecológicos e evolutivos. Desta forma, o principal objetivo desta tese é propor novos métodos para quantificar o sinal filogenético que integrem diferentes aspectos do conceito de nicho ecológico. Apresentamos aqui os novos métodos em detalhes e avaliamos suas propriedades estatísticas (erro tipo I e poder estatístico) por meio de dados simulados. No capítulo 1, nós propomos um método para medir sinal filogenético utilizando o teste de Mantel, incorporando modelos evolutivos para testar hipóteses específicas da evolução dos atributos. No capítulo 2, descrevemos um conjunto de funções e um novo pacote estatístico para explorar os padrões filogenéticos no nível de metacomunidade. Este pacote permite explorar a distribuição de linhagens filogenéticas através de gradientes ecológicos, a análise de sinal filogenético no nível da metacomunidade e explorar a associação entre clados e gradientes ecológicos. No capítulo 3, investigamos a relação entre sinal filogenético dos atributos com os padrões de coocorrência das espécies nos níveis da comunidade. Esta abordagem permite testar se espécies filogeneticamente relacionadas que coocorrem expressam as suas dimensões de nicho com maior semelhança do que seria esperado por modelos neutros de evolução. Por fim, testamos as propriedades estatísticas destes métodos em relação dois modelos nulos, que incorporam diferentes aspectos da estrutura da comunidade e evolução dos atributos das espécies. Os três capítulos representam diferentes trabalhos que se interconectam no sentido de elucidar o conceito de sinal filogenético e conservação filogenética de nicho. / Understanding the factors that can affect species distributions has been a main goal of ecologists. Currently, it is known that evolutionary and ecological processes shape the speciation dynamics, species extinction and determine the distribution and abundance of species. Over the last years, there has been an increase in the number of studies using phylogenetic information to explain the dynamics of population, species distribution and identifying the mechanisms of community assembly. Species interactions – intraspecific, interspecific or with the environment – occur based on their phenotypic differences and similarities. As phenotypic variation has a basis in evolutionary history, it is expected that closely related species tend to be more ecologically similar to each other than distantly related ones. This notion has given rise to an important concept, with implications for both evolutionary and ecological studies: the concept of phylogenetic niche conservatism, that is, when related species maintain their ancestral niches over evolutionary time. This pattern is important for several areas of ecology, and allows to link species to ecological processes and to understand the evolutionary ecology of different lineages. Despite its importance, it is crucial the development of appropriate statistical method to measure this pattern and to infer the processes behind it. The methods currently available to infer phylogenetic niche conservatism are sometimes incompatible with some ecological concepts and do not cover all kind of data, this fact leads to an incomplete view of the process acting in the currents communities and conflict with the goal of many ecological and conservation studies that need to link species to ecological and evolutionary processes. The main goal of this dissertation is to propose novel methods to measure phylogenetic signal incorporating different aspects of ecological niche. We introduce novel methods in detail and evaluate its statistical properties (type I error and statistical power) by means of simulated data with known structure. In chapter 1 we propose a method to measure phylogenetic signal using the Mantel test, incorporating evolutionary model to test specific hypothesis of trait evolution. In chapter 2, we describe a set of function and a new statistical package for exploring the phylogenetic patterns at the metacommunity level. This package allows the exploration of distribution of phylogenetic lineages across ecological gradients, the analysis of phylogenetic signal at metacommunity level and to explore the association between clades and ecological gradients. In the chapter 3, we access the relationship between phylogenetic signal in traits and species co-occurrence patterns in the community levels. This approach allows one to test whether phylogenetic close related species cooccurring in metacommunities express their niche dimensions more similarly than would be expected by neutral expectation. We tested the statistical properties of these methods in relation to two null models, which incorporate these different aspects of the community structure and evolution of species traits. The three chapters represent different works that are interconnected in order to elucidate the concept of phylogenetic signal and phylogenetic niche conservatism.

Compreender os fatores que afetam a distribuição das espécies tem sido um dos principais objetivos dos ecólogos. Atualmente, sabe-se que os processos ecológicos e evolutivos moldam a dinâmica de especiação e extinção de espécies, e determinam a distribuição e abundância das mesmas. Ao longo dos últimos anos, tem havido um aumento no número de estudos que utilizam informação filogenética para explicar as dinâmicas populacionais e as distribuições de espécies, e que buscam identificar os mecanismos responsáveis pela montagem das comunidades. Interações das espécies, sejam elas intraespecífica, interespecífica ou com o ambiente, ocorrem baseadas nas diferenças e semelhanças fenotípicas. Essas variações fenotípicas tem origem na evolução das espécies, e com isso espera-se que as espécies proximamente relacionadas tendam a ser ecologicamente mais semelhantes entre si do que as espécies distantemente relacionadas. Esta concepção tem dado origem a um conceito importante, com implicações para estudos tanto ecológicos quanto evolutivos: o conceito de conservação filogenética de nicho, isto é, quando as espécies relacionadas mantêm seus nichos ancestrais ao longo do tempo evolutivo. Esse padrão tem importância para diversas áreas de ecologia, permitindo a ligação das espécies aos processos ecológicos e auxiliando na maior compreensão da ecologia evolutiva das diferentes linhagens. Devido à sua importância, é fundamental o desenvolvimento de métodos estatísticos adequados para quantificar esses padrões e inferir os processos que o subjazem. Atualmente, os métodos utilizados para inferir conservação filogenética de nicho são, em sua maioria, incompatíveis com determinados conceitos ecológicos e não abrangem todos os tipos de dados e esse fato explica uma visão incompleta dos processos presentes nas comunidades e conflitante com o objetivo de muitos estudos ecológicos e conservacionistas que buscam vincular as espécies aos processos ecológicos e evolutivos. Desta forma, o principal objetivo desta tese é propor novos métodos para quantificar o sinal filogenético que integrem diferentes aspectos do conceito de nicho ecológico. Apresentamos aqui os novos métodos em detalhes e avaliamos suas propriedades estatísticas (erro tipo I e poder estatístico) por meio de dados simulados. No capítulo 1, nós propomos um método para medir sinal filogenético utilizando o teste de Mantel, incorporando modelos evolutivos para testar hipóteses específicas da evolução dos atributos. No capítulo 2, descrevemos um conjunto de funções e um novo pacote estatístico para explorar os padrões filogenéticos no nível de metacomunidade. Este pacote permite explorar a distribuição de linhagens filogenéticas através de gradientes ecológicos, a análise de sinal filogenético no nível da metacomunidade e explorar a associação entre clados e gradientes ecológicos. No capítulo 3, investigamos a relação entre sinal filogenético dos atributos com os padrões de coocorrência das espécies nos níveis da comunidade. Esta abordagem permite testar se espécies filogeneticamente relacionadas que coocorrem expressam as suas dimensões de nicho com maior semelhança do que seria esperado por modelos neutros de evolução. Por fim, testamos as propriedades estatísticas destes métodos em relação dois modelos nulos, que incorporam diferentes aspectos da estrutura da comunidade e evolução dos atributos das espécies. Os três capítulos representam diferentes trabalhos que se interconectam no sentido de elucidar o conceito de sinal filogenético e conservação filogenética de nicho. / Understanding the factors that can affect species distributions has been a main goal of ecologists. Currently, it is known that evolutionary and ecological processes shape the speciation dynamics, species extinction and determine the distribution and abundance of species. Over the last years, there has been an increase in the number of studies using phylogenetic information to explain the dynamics of population, species distribution and identifying the mechanisms of community assembly. Species interactions – intraspecific, interspecific or with the environment – occur based on their phenotypic differences and similarities. As phenotypic variation has a basis in evolutionary history, it is expected that closely related species tend to be more ecologically similar to each other than distantly related ones. This notion has given rise to an important concept, with implications for both evolutionary and ecological studies: the concept of phylogenetic niche conservatism, that is, when related species maintain their ancestral niches over evolutionary time. This pattern is important for several areas of ecology, and allows to link species to ecological processes and to understand the evolutionary ecology of different lineages. Despite its importance, it is crucial the development of appropriate statistical method to measure this pattern and to infer the processes behind it. The methods currently available to infer phylogenetic niche conservatism are sometimes incompatible with some ecological concepts and do not cover all kind of data, this fact leads to an incomplete view of the process acting in the currents communities and conflict with the goal of many ecological and conservation studies that need to link species to ecological and evolutionary processes. The main goal of this dissertation is to propose novel methods to measure phylogenetic signal incorporating different aspects of ecological niche. We introduce novel methods in detail and evaluate its statistical properties (type I error and statistical power) by means of simulated data with known structure. In chapter 1 we propose a method to measure phylogenetic signal using the Mantel test, incorporating evolutionary model to test specific hypothesis of trait evolution. In chapter 2, we describe a set of function and a new statistical package for exploring the phylogenetic patterns at the metacommunity level. This package allows the exploration of distribution of phylogenetic lineages across ecological gradients, the analysis of phylogenetic signal at metacommunity level and to explore the association between clades and ecological gradients. In the chapter 3, we access the relationship between phylogenetic signal in traits and species co-occurrence patterns in the community levels. This approach allows one to test whether phylogenetic close related species cooccurring in metacommunities express their niche dimensions more similarly than would be expected by neutral expectation. We tested the statistical properties of these methods in relation to two null models, which incorporate these different aspects of the community structure and evolution of species traits. The three chapters represent different works that are interconnected in order to elucidate the concept of phylogenetic signal and phylogenetic niche conservatism.

Compreender os fatores que afetam a distribuição das espécies tem sido um dos principais objetivos dos ecólogos. Atualmente, sabe-se que os processos ecológicos e evolutivos moldam a dinâmica de especiação e extinção de espécies, e determinam a distribuição e abundância das mesmas. Ao longo dos últimos anos, tem havido um aumento no número de estudos que utilizam informação filogenética para explicar as dinâmicas populacionais e as distribuições de espécies, e que buscam identificar os mecanismos responsáveis pela montagem das comunidades. Interações das espécies, sejam elas intraespecífica, interespecífica ou com o ambiente, ocorrem baseadas nas diferenças e semelhanças fenotípicas. Essas variações fenotípicas tem origem na evolução das espécies, e com isso espera-se que as espécies proximamente relacionadas tendam a ser ecologicamente mais semelhantes entre si do que as espécies distantemente relacionadas. Esta concepção tem dado origem a um conceito importante, com implicações para estudos tanto ecológicos quanto evolutivos: o conceito de conservação filogenética de nicho, isto é, quando as espécies relacionadas mantêm seus nichos ancestrais ao longo do tempo evolutivo. Esse padrão tem importância para diversas áreas de ecologia, permitindo a ligação das espécies aos processos ecológicos e auxiliando na maior compreensão da ecologia evolutiva das diferentes linhagens. Devido à sua importância, é fundamental o desenvolvimento de métodos estatísticos adequados para quantificar esses padrões e inferir os processos que o subjazem. Atualmente, os métodos utilizados para inferir conservação filogenética de nicho são, em sua maioria, incompatíveis com determinados conceitos ecológicos e não abrangem todos os tipos de dados e esse fato explica uma visão incompleta dos processos presentes nas comunidades e conflitante com o objetivo de muitos estudos ecológicos e conservacionistas que buscam vincular as espécies aos processos ecológicos e evolutivos. Desta forma, o principal objetivo desta tese é propor novos métodos para quantificar o sinal filogenético que integrem diferentes aspectos do conceito de nicho ecológico. Apresentamos aqui os novos métodos em detalhes e avaliamos suas propriedades estatísticas (erro tipo I e poder estatístico) por meio de dados simulados. No capítulo 1, nós propomos um método para medir sinal filogenético utilizando o teste de Mantel, incorporando modelos evolutivos para testar hipóteses específicas da evolução dos atributos. No capítulo 2, descrevemos um conjunto de funções e um novo pacote estatístico para explorar os padrões filogenéticos no nível de metacomunidade. Este pacote permite explorar a distribuição de linhagens filogenéticas através de gradientes ecológicos, a análise de sinal filogenético no nível da metacomunidade e explorar a associação entre clados e gradientes ecológicos. No capítulo 3, investigamos a relação entre sinal filogenético dos atributos com os padrões de coocorrência das espécies nos níveis da comunidade. Esta abordagem permite testar se espécies filogeneticamente relacionadas que coocorrem expressam as suas dimensões de nicho com maior semelhança do que seria esperado por modelos neutros de evolução. Por fim, testamos as propriedades estatísticas destes métodos em relação dois modelos nulos, que incorporam diferentes aspectos da estrutura da comunidade e evolução dos atributos das espécies. Os três capítulos representam diferentes trabalhos que se interconectam no sentido de elucidar o conceito de sinal filogenético e conservação filogenética de nicho. / Understanding the factors that can affect species distributions has been a main goal of ecologists. Currently, it is known that evolutionary and ecological processes shape the speciation dynamics, species extinction and determine the distribution and abundance of species. Over the last years, there has been an increase in the number of studies using phylogenetic information to explain the dynamics of population, species distribution and identifying the mechanisms of community assembly. Species interactions – intraspecific, interspecific or with the environment – occur based on their phenotypic differences and similarities. As phenotypic variation has a basis in evolutionary history, it is expected that closely related species tend to be more ecologically similar to each other than distantly related ones. This notion has given rise to an important concept, with implications for both evolutionary and ecological studies: the concept of phylogenetic niche conservatism, that is, when related species maintain their ancestral niches over evolutionary time. This pattern is important for several areas of ecology, and allows to link species to ecological processes and to understand the evolutionary ecology of different lineages. Despite its importance, it is crucial the development of appropriate statistical method to measure this pattern and to infer the processes behind it. The methods currently available to infer phylogenetic niche conservatism are sometimes incompatible with some ecological concepts and do not cover all kind of data, this fact leads to an incomplete view of the process acting in the currents communities and conflict with the goal of many ecological and conservation studies that need to link species to ecological and evolutionary processes. The main goal of this dissertation is to propose novel methods to measure phylogenetic signal incorporating different aspects of ecological niche. We introduce novel methods in detail and evaluate its statistical properties (type I error and statistical power) by means of simulated data with known structure. In chapter 1 we propose a method to measure phylogenetic signal using the Mantel test, incorporating evolutionary model to test specific hypothesis of trait evolution. In chapter 2, we describe a set of function and a new statistical package for exploring the phylogenetic patterns at the metacommunity level. This package allows the exploration of distribution of phylogenetic lineages across ecological gradients, the analysis of phylogenetic signal at metacommunity level and to explore the association between clades and ecological gradients. In the chapter 3, we access the relationship between phylogenetic signal in traits and species co-occurrence patterns in the community levels. This approach allows one to test whether phylogenetic close related species cooccurring in metacommunities express their niche dimensions more similarly than would be expected by neutral expectation. We tested the statistical properties of these methods in relation to two null models, which incorporate these different aspects of the community structure and evolution of species traits. The three chapters represent different works that are interconnected in order to elucidate the concept of phylogenetic signal and phylogenetic niche conservatism.

I used a theoretical model to determine the conditions under which Cactoblastis cactorum populations would be expected to experience positive population growth. Results from simulations suggest that host species richness, host quality, and the C. cactorum death rate interact to determine the probability of C. cactorum positive population growth. I also studied the influence of host diversity empirically. Cactoblastis cactorum prevalence was significantly higher when O. stricta was present in the community. Also, higher species richness within host assemblages led to a higher prevalence of infestation than in single-species host assemblages. Finally, I explored cooccurrence patterns of native cactuseeding insects in an effort to document the impact of C. cactorum to native insect assemblages. The presence of C. cactorum in a community did not appear to affect the structure of native cactuseeding insect assemblages.

No description available.