1,721,225 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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Methods for Comparative Model Selection and Parameter Estimation in Diverse Modeling Applications
Get PDFPredictive accuracy of a model is of key importance in research and to a lay audience. Diverse modeling methods and parameter estimation methods exist, such that a wide range of techniques are available from which to select when approaching a modeling task. Given this, two questions naturally arise in relation to a modeling task: model selection and model parameter estimation. This dissertation is intended to advance the theory and practice of model selection and parameter estimation for the topics discussed here. * In Chapter 2, I develop A3, a novel method for assessing predictive accuracy and enabling direct comparisons between competing models in an accessible framework. This method uses resampling techniques to "wrap" predictive modeling methods and estimate a standard set of error metrics for both the model as a whole and additionally for each explanatory variable utilized by the model. Two case studies in the chapter illustrate the applied utility of the method and how improved models may not only result in increased predictive accuracy, but also potentially alter inferences and conclusions about the effects of parameters in the model. An R package implementing the method is made available on CRAN.* In Chapter 3, I develop ICE, a novel method of home range estimation. ICE uses a competitive method for estimating home ranges. Effectively, an estimator of estimators, ICE pits existing home range estimators against each other, each of which may be best suited for a given type of data. By selecting between different approaches, ICE can theoretically improve on the performance of any individual estimator across heterogeneous data sets.* In Chapter 4, I develop Contingent Kernel Density Estimation, an extension to Kernel Density Estimation designed to account for the case when observations are measured with a specific form of error. Chapter 4 develops the method and derives contingent kernels for commonly-used kernels and sampling regimes. An application of the method is presented to data collected from the social networking site, Twitter, to estimate the national distribution of a sample of Twitter users.* The study in Chapter 5 analyzes a large data set collected from Twitter. This study is based on data from over four million Twitter users and estimates parameters of this population with a primary focus on color preference choices made by these users. Novel results are found in this "big data" analysis approach that may not have been able to be identified with earlier, traditional approaches of sampling and surveying the behavior of individuals
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Extensible Tools for Movement Ecology with Applications for the Study and Conservation of Namibian Ungulates
Get PDFMovement ecology is a young sub-discipline in ecology in which researchers apply high resolution location and activity data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses con-tribute to various other subfields within ecology—inter alia behavioral, disease, landscape, resource, and wildlife—and may also facilitate novel exploration in fields ranging from conservation planning to public health. Using a decade of GPS relocation data from zebra (Equus quagga), black rhino (Diceros bicornis), and African elephant (Loxodonta africana) captured and collared in Etosha National Park from 2008–2018, this dissertation reviews developing methods within movement ecology, extends and applies these methods to a threatened and understudied species, and presents a new software package distilling a growing movement ecology tool set for researchers and managers unfamiliar with the domain specific analyses and/or the command line interface of modern statistical analysis (e.g. R). Despite the growing availability of animal movement data and the potential for broad application in geographic analysis beyond animal ecology, the analytical methods of movement ecology have yet to be fully incorporated in a broader understanding of geographic analysis. Chapter 2, a review written for the Geographical Information Sciences (GIS) community, provides an overview of the most common movement metrics and methods of analysis em-ployed by animal ecologists and emphasizes the potential for movement analyses to promote transdisciplinary research: comparing advances in the young field of movement ecology to parallel developments within the broader field of geographic information sciences. Two limitations remain common within the growing field of movement analysis. First, within movement ecology, many, even most, analyses require clean, complete, and regular time series of relocations, limiting the available research on species that are hard to track and/or often return gappy, irregular data; including some of the world’s most endangered animals, e.g. black rhinos. In chapter 3, extending and applying recursion analyses to irregular spatio-temporal data from this understudied and critically endangered species, I investigated daily, biweekly and annual recursion behaviors of rhinos, to aid conservation applications and increase our fundamental knowledge about these important ecosystem engineers. Results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Initial results indicate that recursion at the daily and biweekly scales maybe driven by hydration and productivity cycles respectively. Recursion across larger timescales is also evident and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna. A second, and equally challenging, limitation to the growing movement ecology tool kit is accessibility. The growth in analysis techniques, and the concomitant growth of open-source software for analysis, pose a stumbling block to general acceptance in interdisciplinary and management settings, where researchers may be unfamiliar with the expansive set of tools or the command line interface of modern analysis packages. In chapter 4, to reduce this friction and enhance the accessibility of exploratory data analysis tools for animal movement data, I built stmove, an R package designed to make report building and exploratory data analysis simple for users who may not be familiar with the extent of available analytical tools. Furthermore, stmove sets forth a framework of best practice analyses, which offers a common starting point for the interpretation of terrestrial movement data, promoting comparability of results across movement ecology studies. The datasets, analyses, and tools presented in this dissertation seek to enhance communication, application, and accessibility of a growing movement ecology toolkit while providing a special glimpse into a diverse ecological community and the individual and population movement behavior through within Etosha National Park over the last decade. We demonstrate new tools built for exploratory data analysis in movement ecology using this data and explore how insights from movement ecology can help inform successful conservation efforts in the region and beyond
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Using Infectious Disease Modeling to Explain the Distribution of Disease Burden: from Health Economics to Molecular Epidemiology
Get PDFInfectious disease modeling has an untapped potential to provide insight into how disease burden is distributed in human populations. Here, we apply the techniques of infectious disease modeling to applications ranging from health economics to molecular epidemiology.The persistence of extreme poverty is increasingly attributed to dynamic interactions between biophysical processes and economics, though there remains a dearth of integrated theoretical frameworks that can inform policy. In Chapter 1, we present a stochastic model of disease-driven poverty traps. Whereas deterministic models can result in poverty traps that can only be broken by substantial external changes to the initial conditions, in the stochastic model there is always some probability that a population will leave or enter a poverty trap. We show that a `safety net', defined as an externally enforced minimum level of health or economic conditions, can guarantee ultimate escape from a poverty trap, even if the safety net is setwithin the basin of attraction of the poverty trap, and even if the safety net is only in the form of a public health measure. Whereas the deterministic model implies that small improvements in initial conditions near the poverty-trap equilibrium are futile, the stochastic model suggests that the impact of changes in the location of the safety net on the rate of development may be strongest near the poverty-trap equilibrium.In Chapter 2, we show that the same feedbacks between health and income explored in the first chapter, when applied to an individual level (rather than population level), can lead to persistent poverty and high levels of disease among certain individuals in a population, even when the population overall has high income and low disease. This suggests that disease-induced poverty might be a compelling mechanistic explanation for the persistence of health and wealth disparities. Using an individual-based network model with community structure, we show that the structure of the disease transmission network is crucial for the formation of clusters of high poverty and high disease, further highlighting the importance of population structure in studying issues of human health, a topic of increasing importance in both infectious disease modeling as well as social epidemiology.In Chapter 3, we show how network structure could potentially be measured, using standard molecular epidemiology techniques. Using DNA sequence data from pathogens to infer transmission networks has traditionally been done in the context of epidemics and outbreaks. Sequence data could analogously be applied to cases of ubiquitous commensal bacteria; however, instead of inferring chains of transmission to track the spread of a pathogen, sequence data for bacteria circulating in an endemic equilibrium could be used to infer information about host contact networks. We show - using simulated data - that multilocus DNA sequence data, based on multilocus sequence typing schemes (MLST), from isolates of commensal bacteria can be used to infer both local and global properties of the contact networks of the populations being sampled. Specifically, for MLST data simulated from small-world networks, the small world parameter controlling the degree of structure in the contact network can robustly be estimated. Moreover, we show that pairwise distances in the network - degrees of separation - correlate with genetic distances between isolates, so that how far apart two individuals in the network are can be inferred from MLST analysis of their commensal bacteria. This result has important consequences, and we show an example from epidemiology - how this result could be used to test for infectious origins of diseases of unknown etiology
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Economic conditions predict prevalence of West Nile virus.
Get PDFUnderstanding the conditions underlying the proliferation of infectious diseases is crucial for mitigating future outbreaks. Since its arrival in North America in 1999, West Nile virus (WNV) has led to population-wide declines of bird species, morbidity and mortality of humans, and expenditures of millions of dollars on treatment and control. To understand the environmental conditions that best explain and predict WNV prevalence, we employed recently developed spatial modeling techniques in a recognized WNV hotspot, Orange County, California. Our models explained 85-95% of the variation of WNV prevalence in mosquito vectors, and WNV presence in secondary human hosts. Prevalence in both vectors and humans was best explained by economic variables, specifically per capita income, and by anthropogenic characteristics of the environment, particularly human population and neglected swimming pool density. While previous studies have shown associations between anthropogenic change and pathogen presence, results show that poorer economic conditions may act as a direct surrogate for environmental characteristics related to WNV prevalence. Low-income areas may be associated with higher prevalence for a number of reasons, including variations in property upkeep, microhabitat conditions conducive to viral amplification in both vectors and hosts, host community composition, and human behavioral responses related to differences in education or political participation. Results emphasize the importance and utility of including economic variables in mapping spatial risk assessments of disease
Pathogen-mediated evolution of immunogenetic variation in plains zebra (Equus quagga) of southern Africa
Get PDFIn this thesis, I examined the evolution of two equine Major Histocompatibility Complex (MHC) genes, DRA and DQA, over the history of the genus Equus and across free-ranging plains zebra (E. quagga) populations of southern Africa: Etosha National Park (ENP), Namibia and Kruger National Park (KNP), South Africa. Furthermore, I evaluated the relationships between the DRA locus and parasite intensity in E. quagga of ENP, to elucidate the mechanisms by which parasites have shaped diversity at the MHC. In equids, the full extent of diversity and selection on the MHC in wild populations is unknown. Therefore, in this study, I molecularly characterized MHC diversity and selection across equid species to shed light on its mode of evolution in Equus and to identify specific sites under positive selection. Both the DRA and DQA exhibited a high degree of polymorphism and more intriguingly, greater allelic diversity was observed at the DRA than has previously been shown in any other vertebrate taxon. Global selection analyses of both loci indicated that the majority of codon sites are under purifying selection which may be explained by functional constraints on the protein. However, maximum likelihood based codon models of selection, allowing for heterogeneity in selection across codons, suggested that selective pressures varied across sites. Furthermore, at the DQA locus, all sites predicted to be under positive selection were antigen binding sites, implying that a few selected amino acid residues may play a significant role in equid immune function. Observations of trans-species polymorphisms and elevated genetic diversity were concordant with the hypothesis that balancing selection is acting on these genes. Over the past half century, the role of neutral versus selective processes in shaping genetic diversity has been at the center of an ongoing dialogue among evolutionary biologists. To determine the relative influence of demography versus selection on the DRA and DQA loci, I contrasted diversity patterns of neutral and MHC data across the E. quagga populations of ENP and KNP. Neutrality tests, along with observations of elevated diversity and low differentiation across populations relative to nuclear intron data, provided further evidence for balancing selection at these loci among E. quagga populations. However, at the DRA locus, differentiation was comparable to results at microsatellite loci. Furthermore, zebra in ENP exhibited reduced levels of diversity relative to KNP due to a highly skewed allele frequency distribution that could not be explained by demography. These findings were indicative of spatially heterogeneous selection and suggested directional selection and local adaptation at the DRA locus. There still remains a great deal of discussion over the mechanisms by which pathogens preserve immune gene diversity. The leading hypotheses that have been predominantly considered are: (i) heterozygote advantage (i.e. overdominant selection), (ii) rare allele advantage (i.e. frequency-dependent selection), and (iii) spatiotemporally fluctuating selection. An increasing number of studies have investigated MHC-parasite relationships to reconcile this debate, with conflicting results. To elucidate the mechanism driving the population-level patterns of diversity at the DRA locus, I examined relationships between this locus and both gastrointestinal (GI) and ectoparasite intensity in plains zebra of ENP. I discovered antagonistic pleiotropic effects of particular DRA alleles, with rare alleles predicting increased GI parasitism and common alleles associated with higher tick burdens. These results supported a frequency-dependent process and because maladaptive 'susceptibility alleles' were found at reduced frequencies, suggested that GI parasites exert strong selective pressure at this locus. Furthermore, heterozygote advantage also played a role in decreasing GI parasite burden, but only when a common allele was paired with a more divergent allele, implying that frequency-dependent and overdominant selection are acting in synchrony. These results indicated that an immunogenetic tradeoff may modulate resistance/susceptibility to parasites in this system, such that with MHC-based resistance to GI parasitism, a fitness cost is incurred to the host in the form of increased ectoparasite susceptibility. It is also suggested that these selective mechanisms are not mutually exclusive. (Abstract shortened by UMI.
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The ecology of anthrax and coinfection trade-offs from an immunological perspective: seasonal aspects of host susceptibility
Get PDFSeasonal fluctuations in infectious disease incidence are common, and have been observed for many infectious agents. Immune condition can also change seasonally due to such pathogen fluctuations, a well as to changes in other stress-inducing and immunomodulatory factors such as reproduction and lactation. In addition, most vertebrate hosts are concurrently infected with multiple pathogens, and such coinfections can interact with each other, with the immune system, and with other physiological factors to affect both the individual hosts and population dynamics. While many studies regarding the effects of coinfections and immune trade-offs have been conducted in laboratory settings, similar studies in wildlife are as yet very rare. Fewer studies have been conducted regarding disease and immune seasonality, as these are difficult to model in laboratory settings and require difficult, longitudinal studies in natural systems. In addition, most research regarding disease seasonality in natural systems that has been done has focused on the impacts of abiotic factors on pathogen and vector survival and abundance, or on population-wide dynamics, rather than on physiological mechanisms of host susceptibility. To fully understand the ecology of infectious diseases and the reasons for disease outbreaks, it is necessary to extend laboratory studies into natural hosts in natural systems, as well as to extend wildlife studies to incorporate the complex interactions between environmental, physiological, and coinfection factors. My dissertation research thus focused on the ecological immunology of infectious disease in a natural system, from physiological, seasonal, and coinfection perspectives. I examined the ability of plains zebra (Equus quagga), springbok (Antidocas marsupialis), and African elephant (Loxodonta africana) to respond immunologically to regular anthrax outbreaks in an endemic anthrax system (Etosha National Park, ENP, Namibia). I also examined how zebra and springbok macroparasite coinfections varied with and affected changes in immune parameters, stress, reproductive hormone levels, and seasonal timing of anthrax outbreaks. Despite the fact that anthrax is an ancient disease known to affect wildlife, livestock, and humans on nearly every continent, its natural ecology is not well understood. In particular, little is known about the adaptive immune responses of wild herbivore hosts against Bacillus anthracis, the causative agent of anthrax. Thus, I worked to determine the extent to which natural anthrax hosts can fight off sublethal anthrax doses via adaptive immunity. I used enzyme-linked immunosorbent assays, and developed new assay mensuration rules to determine serum antibody titers against the anthrax protective antigen (PA) toxin, an important, potentially protective aspect of adaptive immunity against anthrax. I found that more than 60% of all zebra, up to 15% of springbok, and up to 50% of elephants had measurable anti-PA antibody titers, indicating that these hosts experience and survive sublethal anthrax infections, likely encounter more anthrax in the wet season compared to in the dry, and can partially booster their immunity to B. anthracis over time. Most pathogen-pathogen interactions occur indirectly through the host immune system, and are particularly strong in mixed micro-macroparasite infections because of the strong immunomodulatory effects of helminth parasites. As pathogen transmission changes with season, host immunity may be more strongly influenced by coinfection immunomodulatory effects than by external factors such as changing dietary and demographic patterns. I thus examined the seasonality of immune functionality, pathogen infectivity, and interactions between concurrent infections and immunity in wild zebra in ENP, a system with strongly seasonal patterns of gastrointestinal (GI) helminth infection intensity and concurrent anthrax outbreaks. I found evidence that wet seasons in ENP are characterized by Th2-type immune skewing driven by GI helminth infections, and that these trade-offs make hosts less capable of mounting effective Th1-type immune responses against anthrax infections at this time. I also found evidence that coinfections and immune tradeoffs affect long-term host survival, and that GI parasites likely exert more selection pressure on zebra hosts than do ectoparasites and anthrax, but may actually be a stabilizing force in this host-pathogen system. Stress and reproductive hormones can modulate each other and the immune system, and can affect disease incidence. Pathogens can also cause host stress, as well as exploit host niches exposed by stress and reproductive hormone-induced immunomodulation. Therefore, I examined seasonal correlations between host stress, reproduction, and GI parasite coinfections in zebra and springbok in ENP. All three macroparasites examined (strongyle helminths, Strongyloides helminths, and Eimeria coccidia) had strongly seasonal signals, with hosts experiencing the highest parasite infection intensities during times of highest rainfall and highest anthrax outbreaks. Strongyles appeared to be perhaps most potent immunomodulating pathogen in this system, influencing zebra immune responses to anthrax and susceptibility to tick infestations, as well as springbok susceptibility to Strongyloides infections. However, helminths were mostly negatively associated with stress hormone concentrations and Eimeria had almost no interaction with stress, indicating that most hosts have developed tolerance toward even high macroparasite loads. Stress hormone concentrations were nearly uniformly higher in drier times than in wetter ones, and were positively affected by estrogen concentrations in females, likely indicating that seasonal nutritional and water stressors, as well as pregnancy stress during the dry season trumped the effects of pathogen infection intensities in causing host stress. In addition, adult animals had higher stress levels than did yearlings, despite yearlings being the largest aggregator of parasites, corroborating the idea that reproductive status is more influential in determining host stress than are pathogens in this system and that mechanisms of tolerance to GI parasites are substantial. In conclusion, my results indicate that GI parasites play a large role in determining host immune status and susceptibility to micro- and macroparasite coinfections. While ENP herbivores survive anthrax infections with regularity, host immunomodulation by GI parasites likely determines whether a host will mount a successful immune response against this potentially deadly pathogen. GI parasites modulate these coinfection interactions despite causing hosts little direct stress; thus, these coinfection interactions likely take place mostly through direct immunomodulatory effects rather than indirectly through host pathology, nutritional depletion, and other potentially stress-inducing sequelae. ENP zebra and springbok appear to be tolerant of their macroparasite loads, trading off parasite immunomodulatory and pathological effects in favor of balancing resource allocation toward reproductive efforts
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