Master of Science (MS), Ohio University, 2017, Biological Sciences (Arts and Sciences)

Evolutionary theory predicts a trade-off between sexual selection and natural selection on secondary sexual traits. Understanding the relationship between mating success and predation risk can give insight into the evolutionary dynamics that interact to promote or constrain phenotypic change, yet it has been little studied in the wild. I conducted a two-year cross-sectional field study on the Banded Demoiselle damselfly (Calopteryx splendens) to test for trade-offs between sexual selection and predation risk, and to assess variation in sexual and natural selection. At the study population, the White Wagtail (Motacilla alba) captures C. splendens in flight, then flies to feeding stations where it removes the wings and consumes the body. I used geometric morphometric techniques to quantify damselfly wing morphology, and compared wing shape and secondary sexual traits of wings from feeding stations to a random sample of wings from the population to quantify the strength, mode, and direction of natural selection on males. Simultaneously, I measured wing traits from individuals caught in the act of mating and compared them to a random sample of wings from the population to quantify the strength, mode, and direction of sexual selection on male wings. By comparing natural selection and sexual selection on wing traits simultaneously, I tested for trade-offs between types of selection. My results suggest that predator-mediated selection fluctuates through time, and is especially variable in how it operates on the size of secondary sexual traits displayed by males. Sexual selection operated almost exclusively on secondary sexual traits, and was consistent across years. Predator-mediated selection acted differently on fore- and hindwings, favoring males with long, narrow forewings and short, broad hindwings. A trade-off between natural and sexual selection was revealed on wing patch characteristics, with males possessing larger and darker wing patches experiencing higher preda (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2011, Higher Education Administration

Resident advisors (RAs) are the foundation of nearly every residence hall program in the United States (Blimling, 2010). RAs play a pivotal role in the development of the whole student and supporting the educational mission of higher education and selection of the most qualified applicants is imperative to the success of the residence hall program. Although residence life professionals attempt to improve RA selection in hopes of identifying the most qualified students for these roles, researchers have found few proven systematic techniques to select the most qualified candidates for the RA positions. This study sought to examine if the five-factor model of personality was a good predictor of RA performance at one large, rural, public, four-year university in the Midwest. Secondary purposes were to determine if demographic variables affected RA performance. The major variables for this study included gender, class rank, experience as a RA, grade point average, academic major, type of residents, residential learning community, RA evaluation overall and sub-scores, and IPIP-NEO scores. RAs were surveyed to gather demographic and personality information while RA performance data were gathered from existing performance evaluations from their supervisors at the participant institution. Multiple regressions were conducted using both the International Personality Item Pool -“Neuroticism, Openness to Experience, and Extraversion scale and RA performance data. Only openness to experience significantly predicted overall fall RA performance; however, none of the five factors predicted overall spring RA performance. Despite insignificant results related to overall performance, the five-factor model was related significantly to several of the sub-categories of RA performance (e.g., fall policies and procedures scores). Only grade point average, class rank, RA experience, and the number of residents living on the floor had a large effect size on RA performance after performing (open full item for complete abstract)

Doctor of Philosophy (Ph.D.), Bowling Green State University, 2019, Statistics

Linear regression model is the classical approach to explain the relationship between the response variable (dependent) and predictors (independent). However, when the number of predictors in the data increases, the likelihood of the correlation between predictors also increases, which is problematic. To avoid that, the linear mixed effects model was proposed which consists of a fixed effects term and a random effects term. The fixed effects term represents the traditional linear regression coefficients, and the random effects term represents the values that are drawn randomly from the population. Thus, the linear mixed model allows us to represent the mean as well as the covariance structure of the data in a single model. When the fixed and random effects terms increase in their dimensions, selection as appropriate model, which is the optimum fit, becomes increasingly difficult. Due to this natural complexity inherent in the linear mixed model, in this dissertation we propose a two-stage method for selecting fixed and random effects terms. In the first stage, we select the most significant fixed effects in the model based on the conditional distribution of the response variable given the random effects. This is achieved by minimizing the penalized least square estimator with a SCAD Lasso penalty term. We used the Newton-Raphson optimization algorithm to implement the parameter estimations. In this process, the coefficients of the unimportant predictors shrink towards exactly zero, thus eliminating the noise from the model. Subsequently, in the second stage we choose the most important random effects by maximizing the penalized profile log-likelihood function. This maximization is achieved using the Newton-Raphson optimization algorithm. As in the first stage, the penalty term appended is SCAD Lasso. Unlike the fixed effects, the random effects are drawn randomly from the population; hence, they need to be predicted. This prediction is done by estimating (open full item for complete abstract)

Doctor of Philosophy, Miami University, 2011, Ecology, Evolution and Environmental Biology

Adaptive foraging is a recent theoretical synthesis linking foraging decisions to the structure and functioning of ecological communities. However, empirical research is required to characterize the consequences of different environmental challenges on organisms foraging behavior. The goal of this dissertation was to explore ecological factors that are responsible for variation in the foraging behavior of a common generalist predator, the wolf spider Pardosa milvina. I conducted four studies to investigate aspects of the adaptive foraging framework, space use and prey selection. I first explored the how habitat structure affects density and foraging ability. Spiders preferred areas containing more structural features, but contrary to predictions, they preferred patches low in prey. Foraging rate was reduced by some habitat features, and habitat structure lowered interference levels between spiders. I examined the role of prey abundance and predator abundance on interference determined by changes in patch leaving frequency and in their functional response. While prey abundance had strong effects on the tendency to leave patches, indicating the importance of prey to predator patch use, increasing the abundance of predators led to increased dispersal rates and interference. I used a two-pronged approach to understanding prey selection in this spider. In one set of experiments I measured changes in consumption of a target prey group in the field using a molecular probe. Although there was variation in the proportion of spiders testing positive for prey, the consumption of prey did not follow strict frequency dependence expected for generalist species. In a second set of experiments I tested for one prey characteristic, nutrient quality, to help explain predation rate and prey choice. The functional response of spiders to different prey nutrient compositions was comparable, but when spiders were fed on a prior nutrient enhanced diet, spiders killed a significantly greate (open full item for complete abstract)

Master of Education (MEd), Bowling Green State University, 2011, Reading

It is a well-supported fact that students who have an internalized motivation to read will engage in literacy-related practices throughout life. Because of this, teachers must strive to help students develop intrinsic desires to become avid readers. However, this is not always a simple task, especially when concerned with intermediate-level students who face the impending “fourth-grade slump.” The encouragement of avid reading requires implementation of fundamental aspects of motivation: choice, access, and self-selection of literature. This study focused primarily on the self-selection strategies utilized by third and sixth grade students attending a nearby intermediate school. Little is known about how self-selection methods alter as students age. To avoid the decline in motivation that most students encounter around fourth grade, educators must be aware of how students choose texts to provide them with appealing literature, successful selection strategies, and guidance to promote autonomy. To determine how third and sixth grade students choose recreational literature, participants responded to a 12-question survey. A variety of questions were used to collect information related to students' reading habits, preferences, and self-selection processes. The data obtained from the survey were analyzed to determine the degree to which age is a factor in the self-selection processes exercised by students in intermediate grades. The findings of this study indicate that no methodology of choosing literature is specific to a certain grade level. Despite this, it was acknowledged that both third and sixth graders were likely to implement a variation of the same three steps first when choosing texts: reading the title, identifying the author, and surveying the cover design. Although there were similarities found between the surveyed age groups, it was concluded that age is a factor in relation to the number of steps students take when choosing a book, the degree of imp (open full item for complete abstract)

MS, Kent State University, 2024, College of Arts and Sciences / Department of Geography

In 2018, the largest wildfire to ever occur in the Santa Monica Mountains National Recreation Area burned 88% of National Park Service (NPS) land. Located near Los Angeles, this park is the largest urban national park in the U.S. and home to mountain lions (Puma concolor) that are severely threatened. High levels of urbanization force them to live in overlapping and too small of home ranges, leading to intraspecific conflicts and inbreeding. The frequent wildfires add another threat, killing pumas directly or damaging their habitat. Current research conflicts as to how pumas select habitat post-fire, and most do not incorporate remote sensing metrics or consider how movements change with time since fire. In this study, I used global positioning system (GPS) collar data supplied by the NPS to analyze post-fire puma habitat selection. I conducted integrated step selection functions (iSSFs) at individual and population levels, for every 6-month seasonal period following the 2018 fire through 2023. I analyzed nine static variables to account for abiotic landscape variability and three variables derived from multi-temporal remote sensing to capture the dynamic, biotic environment, mainly focused on burn severity and vegetation condition and structure metrics. Habitat selection and variable importance were compared within each time period, as well as throughout the study period. I focused results on the population level analyses only. Results indicated that pumas consistently selected for increased vegetation vigor and selected for higher landscape heterogeneity and structure for the majority of time periods. Vegetation vigor also appeared as one of the most important variables to movement, along with terrain ruggedness and slope. Seasonal trends emerged for some variables post-fire. This study suggests that pumas are considerate of vegetation condition and fire impacts when selecting habitat, highlighting key habitat characteristics that pumas prefer post-fire. The influ (open full item for complete abstract)

BS, Kent State University, 2023, College of Arts and Sciences / Department of Biological Sciences

In North America, the genus Lobelia includes several very similar species that also usually have very high degrees of overlap; most species are sympatric, often with five or more species (Spaulding and Barger, 2016). These geographically-overlapping species also often have overlapping reproductive seasons, which means that they do not experience geographic or temporal isolation. However, despite this lack of isolation and their similarity, the species have remained distinct. This suggests that there is another isolating mechanism that prevents hybridization, possibly morphological shifts in populations that are at a higher risk for hybridization due to sympatry. To test this, I measured 50+ floral traits for 223 flowers from 20 species of North American Lobelias. I used this data to compare the floral morphologies between sympatric and allopatric populations. I calculated the amount of sympatry and the type of morphological change in several different ways, but in every one, I found that there was a large difference between flowers from sympatric and allopatric populations. I also tested the species-specific effect of sympatry, or whether living with specific species would affect a flower in different ways. I found strong evidence that the effect of sympatry is very different if that sympatry is with L. cardinalis or L. inflata, likely due to the fact that neither species can hybridize; L. inflata is exclusively self-pollinating and L. cardinalis is the only bird-pollinated species. There is little existing research into the effects of different types of sympatry on Lobelia floral morphology, so I hope future research will continue to investigate these interactions.

Doctor of Philosophy, The Ohio State University, 2022, Horticulture and Crop Science

Contemporary processing and fresh-market tomato varieties grown in humid environments must possess a combination of yield, fruit quality, and disease resistance traits to produce marketable fruit amidst the challenging growing conditions present in the field. The focus of this dissertation was to use assays for DNA variation, molecular markers, to enable strategies to efficiently combine resistances to multiple diseases and predict performance for traits across populations and environments. The first objective was to select for coupling-phase recombination events on chromosome 11 of tomato that combine resistances to four tomato pathogens. Resistances to bacterial spot (QTL-11 and Xv3/Rx4) caused by Xanthomonas spp., gray leaf spot (Sm) caused by Stemphylium spp., fusarium wilt (I2) caused by race 2 of Fusarium oxysporum f. sp. lycopersici, and tomato yellow leaf curl virus (Ty-2) caused by begomoviruses are located on chromosome 11. We used molecular markers linked to these resistance loci to select for rare recombination events and created a linked cassette that can be inherited together in future crosses. Notably, we created a novel coupling of Xv3/Rx4 and Ty-2, with recombination between the two genes estimated as 0.056 cM. Progeny from the recombinant plants had resistance levels comparable to resistant controls when tested in inoculated seedling trials, demonstrating that effective combinations of resistance genes can be established using publicly available germplasm. The second objective was to investigate genomic selection (GS) models to predict yield and quality traits within the context of a processing tomato breeding program. Genomic selection is a widely used tool in plant breeding, but applications of GS in vegetable crops have been limited compared to grain crops, primarily due to resource and population size limitations. We developed models for two inbred line populations to predict inbred and hybrid performance. Both individual inbred populations and (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2022, Horticulture and Crop Science

Breeders use genomic selection (GS) for rapid cycling of parents for crop improvement. GS increases efficiency of breeding by shortening the duration of breeding cycles. The effect of rapid cycling on the wheat genome is unknown. The first objective of this dissertation was to assess the effect of five rapid cycles on the wheat genome. The OSU wheat breeding program began GS with a training population (YTP) phenotyped for yield, quality, and fusarium head blight (FHB) resistance traits. This YTP was genotyped with 3972 single nucleotide polymorphism (SNP) markers. The phenotypes and genotypes were used to build a GS model to obtain genomic estimated breeding values (GEBV). The GEBVs of F2 plants were then used to advance plants through five cycles of GS (YC1, YC2, YC3, YC4, YC5). We assessed the impact of GS on allele frequencies, the forces driving these changes, genetic distance (GD), population differentiation (FST), and linkage disequilibrium (LD). Relative to the YTP, we found that 27% of SNP had a significant change in allele frequency, 18% SNPs were under selection, 13% changed due to genetic drift, 9.3% were undiscernible for drift or selection, and 18.5% were fixed by YC5. Genetic distance narrowed within cycle while the GD between cycles increased at a 0.02 units per cycle. The cycles differentiated from the YTP at a rate of 0.046 FST units per cycle. The YC5 was highly differentiated from the YTP with an FST value of 0.224. We found the correlation between LD matrices decreasing at -0.057 units per cycle. Overall, we found reduction in genetic diversity, increased genetic differentiation of cycles from the YTP, and changes in LD patterns over cycles. The change in the genome is not desired when implementing GS because the changes will lower the prediction accuracy as the number of cycles increases. The second objective of this dissertation was to estimate the accuracy of GS at predicting the phenotypes of lines derived from cycles of GS. Prediction accur (open full item for complete abstract)

PhD, University of Cincinnati, 2021, Arts and Sciences: Mathematical Sciences

The focus of this dissertation is on uncertainty quantification for model selection. In recent years, model selection methods for high-dimensional data have achieved many exciting results in terms of efficient algorithms and theoretical developments. Even if the number of predictors is much larger than the sample size, the powerful penalization methods for variable selection in regression can provide a sparse representation of the data. However, quantifying the model selection uncertainty is still a pressing task. In this dissertation, we propose model selection deviation to quantify the model selection uncertainty for linear regressions and propose confidence graphs to analyze the graphical model selection uncertainty for graphical models. In the first part of this dissertation, we introduce several graphical tools, such as G-plot and H-plot, to visualize the distribution of the selected model. We propose the concept of model selection deviation (MSD) to quantify the uncertainty. Similar to the standard error of an estimator, model selection deviation measures the stability of the selected model given by a model selection procedure. For such a measure, we discuss a bootstrap estimation procedure and demonstrate its desirable performance through simulation studies and real data analysis. In the second part, we introduce the concept of confidence graphs (CG) for graphical model selection. CG first identifies two nested graphical models - called small and large confidence graphs (SCG and LCG) - trapping the true graphical model in between at a given level of confidence, just like the endpoints of traditional confidence interval capturing the population parameter. Therefore, SCG and LCG provide us with more insights about the simplest and most complex forms of dependence structure the true model can possibly have, and their difference also offers us a measure of model selection uncertainty. In addition, rather than relying on a single selected model, CG con (open full item for complete abstract)

Master of Arts (MA), Bowling Green State University, 2021, Psychology/Industrial-Organizational

Creativity is essential for organizational progress and functioning, yet an important part of the creative process, idea selection, has received comparatively little research. Existing research on this process has shown that creative idea selection is particularly difficult, and people may select at no better than chance levels. The idea that there exists a bias against creativity has been proposed to explain the difficulty in effectively selecting creative ideas. This bias against creativity is thought to exist because creative ideas are by definition novel, and novelty carries with it a level of ambiguity that is aversive to many people. This study built upon previous research, using the bias against creativity as an explanatory framework to investigate how dispositional ambiguity tolerance and deliberative or intuitive processing instructions relate to the creativity of selected ideas. It was hypothesized that ambiguity tolerance and instructions to engage in intuitive processing would improve creative idea selection, reduce uncertainty experienced during the task, and increase confidence in ideas, perhaps by reducing the bias against creativity. 221 participants were randomly assigned into an intuitive, deliberative, or control condition and completed an idea selection task. Hypotheses were largely unsupported by the data.

Doctor of Philosophy, Case Western Reserve University, 2021, Biology

Habitat characteristics can affect how organisms use environments. Individuals are expected to have evolved the ability assess habitat quality to maximize their fitness. I investigated the effects of habitat characteristics on aquatic and terrestrial environment use in multiple amphibian life-stages. In Chapter 1, I investigated how female breeding habitat selection is influenced by competitors and how this affects offspring performance. Female eastern gray treefrogs (Hyla versicolor) used pools without larval competitors more than pools with green frog (Rana clamitans) or bullfrog (Rana catesbeiana) tadpoles. Treefrog tadpoles developed faster and grew larger without heterospecifics, indicating larval performance matched female preference. Males may use habitat quality cues differently. In Chapter 2, I evaluated male use of these same habitats and the male quality as potential mates for females using recordings of male advertisement calls. Males used pools with heterospecifics the same as pools without, and the advertisements of males at all habitat types were similar. Thus, while females avoided pools with heterospecifics, males did not. In Chapter 3, I tested if male treefrogs using fringe habitats differ from residents at an adjacent core pond by comparing the calls of males in both habitats. I also evaluated how fringe males changed their calls at the core pond. Fringe males produced more yet shorter calls than males in the core habitat, but called at a similar effort. When fringe males were moved to the core habitat, they adjusted their calls to match the core males. Finally, in Chapter 4, I investigated how the terrestrial environment affects juvenile development. In collaboration with David Burke at the Holden Arboretum, I tested how forest acidification affects the American toad (Anaxyrus americanus) and its interaction with the invertebrate community. Toads tended to grow larger in elevated soil pH, although survival and diet were not affecte (open full item for complete abstract)

Doctor of Philosophy (PhD), Ohio University, 2020, Biological Sciences (Arts and Sciences)

Alternative reproductive tactics (ARTs) occur when members of the same sex within a species are dimorphic for reproductive phenotypes. ARTs typically evolve in response to strong sexual selection and involve alternate ways to gain reproductive success through suites of correlated behavioral, morphological, and life history traits. Due to their shared genome, ARTs likely share the genetic architecture for homologous traits, yet may have different phenotypic optima for these traits. If this is the case, the evolution of dimorphism or further dimorphism towards an ART's specific optimum may be constrained by their genetic architecture, resulting in intralocus tactical conflict (IATC). Studies on the evolutionary effects of intralocus conflict have mainly focused on shared traits between the sexes, while investigations into intralocus conflict on ARTs is relatively new. My dissertation investigates whether IATC is acting on shared reproductive traits between the male ARTs of the swordtail fish Xiphophorus multilineatus. Xiphophorus multilineatus males exhibit two ARTs, a courter that uses only courtship to attract females, and a sneaker that is behaviorally plastic and uses both courtship and forced copulatory sneak-chases. In chapter 1, I characterized the dimorphism between courter and sneaker males for body shape, which has implications for swimming performance and thus successful execution of each ARTs' mating behavior. In addition, I investigated the relationship between body shape and mating behavior in the sneaker males to determine if sneak-chase and courtship is phenotypically integrated with body shape. I found that courter and sneaker males are dimorphic for body shape, even when males overlap in size, and that more fusiform sneaker males are more likely to use sneak-chase behavior. In chapter 2, I used measures of reproductive success from a wild population to estimate selection gradients on three tactically dimorphic traits involved in sexual selection: (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2019, Biology

Many animals use elaborate adult traits to attract mates and intimidate rivals. However, the development of these sexually selected traits, and the reproductive interactions that confer their benefits, occur against a complex backdrop of environmental factors. When such features of the habitat modify the costs and benefits of displaying and developing these traits, environmental variation across space and time can shape their diversification. Likewise, sexual selection on these characters may have consequences for how organisms interact with and adapt to different ecological contexts. Here, I explore these themes by investigating the interplay between sexually selected coloration, the external environment, and physiology in dragonflies. I begin by examining the adaptive function of wing pigmentation in a dragonfly (Pachydiplax longipennis), finding that this trait is intrasexually selected. Using this dragonfly system, I then document how interactions between the environment and an organism's physiological state can drive the divergence in its sexually selected wing coloration. I first show that thermal physiology causes the performance benefits of wing coloration to depend on ambient temperature, and, as a result, males in the warmest parts of North America nearly lack this trait all together. I next illustrate how improving an individual's physiological condition to develop better sexually selected coloration can harm its juvenile survival in the presence of predators. I then consider how sexual selection could feed back to influence ecological adaptation by examining links between wing coloration and immune defense. I find that, in addition to several important ecological costs of deploying immune defenses during the larval stage (e.g. predation vulnerability, delayed emergence), producing a strong immune response directly inhibits wing color development. Moreover, when comparing across species, I show that those species with more wing coloration tend to have wea (open full item for complete abstract)

PHD, Kent State University, 2019, College of Business and Entrepreneurship, Ambassador Crawford / Department of Management and Information Systems

Internships, or temporary work arrangements, are used extensively by U.S. companies. Internships may be used as a means of recruitment, and to provide companies an opportunity to develop qualified entry-level candidates at relatively low cost. As interns require little additional training when hired into full-time positions, internships may help companies substantially reduce training costs without affecting performance on the full-time positions. Academic support on how to select qualified interns will help practitioners do a better job for companies. Yet, surprisingly, little research on internships has been published, especially with regard to selection for internship positions. This dissertation has several objectives. The initial objective is to develop a conceptual framework for internship selection that would incorporate and examine two perspectives on internship selection. The first perspective examines the relationship between selection for internship and entry-level full-time positions. The two positions are similar in that each requires less specific job-related knowledge or experience than higher level positions do; therefore, internship selection might be designed in a manner similar to a selection process for full-time, entry-level positions. However, they are different in that, internship positions are not full-time positions. Therefore, differences between internship positions and full-time positions must also be incorporated into the proposed framework for internship selection. The second perspective examines the relationship between internship selection and work sample test. Internships might also be regarded as a selection method similar to an elaborated work sample test where companies could observe samples of job-related behaviors of job applicants in the process of internship. The next objective is to perform an empirical analysis of the proposed conceptual framework using survey data collected from 139 organizations in the United States con (open full item for complete abstract)

PhD, University of Cincinnati, 2018, Arts and Sciences: Mathematical Sciences

In epidemiology and clinical research, the relative risk (RR) is commonly used as a measure of the risk of developing a disease. The log-binomial regression is a preferred statistical model to estimate RR as it provides a convenient form of RR. However, the constrained parameter space of the log-binomial model often causes numerical difficulties in applying this model for data analysis. In this dissertation, we conduct model selections for the log-binomial regression where three objectives are addressed. Firstly, we develop Bayesian variable selection methods for log-binomial model, where the Bayes factor is used as the selection criterion and five Monte Carlo methods are utilized to compute the Bayes factor while dealing with the constrained parameter space. These Monte Carlo methods are then assessed for computational accuracy and efficiency. Secondly, we study the sensitivity of Bayes factor to the prior distributions of the regression parameters by evaluating the performances of five popular priors in the log-binomial variable selection, i.e. independent Gaussian prior, independent t prior, independent Cauchy prior, the g-prior (g=n) and the Zellner-Siow Cauchy prior. Finally, we perform Bayesian model selection between the log-binomial and the logistic regressions where the Bayes factor, the fractional Bayes factor, LPML, DIC and BIC are used as the model selection methods. In addition, four prior densities of the regression parameters are considered: the flat prior, Cauchy prior, Jeffreys prior and an elicited proper prior. The theoretical properties of these priors are also investigated. These methods and priors are compared via simulations on their capabilities of distinguishing between the log-binomial and logit models.

Doctor of Philosophy, The Ohio State University, 2017, Economics

Various spatial econometrics models have been proposed to characterize spatially correlated data. As economic theories provide little guidance on constructing a true model, we are often faced with the problem to choose among spatial econometrics models. My dissertation develops a Vuong-type test and an adaptive Lasso procedure that complement existing spatial model selection methods in several aspects. Chapter 1 develops a likelihood-ratio test for model selection between two spatial econometrics models. It generalizes Vuong (1989) to models with spatial near-epoch dependent (NED) data. We measure the distance from a model to a data generating process by Kullback-Leibler Information Criterion and test the null hypothesis that two models are equally close to the data generating process. We make no assumption on the model specification of the truth and allow for the cases where both, either or neither of the two competing models is mis-specified.As a prerequisite of the test, we first show that the quasi-maximum likelihood estimators (QMLE) of spatial econometrics models are consistent estimators of their pseudo-true values and are asymptotically normal under regularity conditions. In particular, we study spatial autoregressive models with spatial autoregressive errors (SARAR) and matrix exponential spatial specification (MESS) models. With asymptotic properties of QMLEs and limit theorems for NED random fields, we then derive the limiting null distribution of the test statistic. A spatial heteroskedastic and autoregressive consistent estimator of asymptotic variance of the test statistic under the null, which is necessary to implement the test, is constructed. Monte Carlo experiments are designed to investigate finite sample performance of QMLEs for SARAR and MESS models, as well as the size and power of the proposed test. Chapter 2 proposes a penalized maximum likelihood approach with adaptive Lasso penalty to estimate SARAR models. It allows for simultaneou (open full item for complete abstract)

Master of Arts (MA), Bowling Green State University, 2016, Psychology

This study sought to examine three potential reasons for public-sector resistance to the use of unproctored internet testing (UIT) for administering preliminary employment tests. Utilizing a policy capturing design, this study examined the relative importance of perceived diffusion, test security/cheating prevention, and test type on current public-sector practitioners' likelihood of using UIT administered tests. Additionally, test-type was examined as a moderator of the relative importance of perceived diffusion and test security/cheating prevention on practitioners' likelihood of using a UIT test. All three situational characteristics were found to be significant predictors of likelihood of using tests administered by UIT. Test type was found to be the most heavily weighted factor in public-sector practitioners' decisions regarding UIT, followed by test security/cheating prevention. Test type was not supported as a moderator. Implications for researchers and practitioners involved in employment testing are discussed.

Bachelor of Science (BS), Ohio University, 2015, Biological Sciences

Sexual selection is comprised of intersexual mate choice and intrasexual competition. In order for female choice to be adaptive, the benefits of being choosey need to outweigh the costs. Females could benefit from preferences for male traits that relay information about male quality and/or that increase offspring fitness. Female preferences are affected by genotype, environment, or a combination of the two. In the study species, Xiphophorus multilineatus, males belong to one of four genetic size classes, and one of two genetic reproductive tactics. Between these alternative reproductive tactics, growth rate may be under disruptive selection. Since growth rate relates to fitness, it is possible that females assess a potential mate's growth rate by evaluating variation in male vertical body bars. I identified two aspects of the vertical body bars that are correlated with male juvenile growth rate. In addition, I demonstrated that females from a population of exclusively sneaker males show a preference for the barring pattern that represents a slower growth rate, which supports the proposed tactical disruptive selection on growth rate. Females from the sneaker line were also choosier in their preferences, which could potentially indicate that the fitness advantage to growing slower as a sneaker male may be greater than the fitness advantage to growing faster as a courter male.

Master of Science, The Ohio State University, 2015, Horticulture and Crop Science

Phytophthora root and stem rot of soybean (Glycine max) is caused by the oomycete pathogen Phytophthora sojae. This disease can be controlled by genetic resistance, but can cause devastating yield losses in fields planted with susceptible soybean cultivars and results in losses of around $300 million annually in the US. Partial resistance is considered to be more durable against P. sojae than race-specific resistance conferred by Rps genes and is theoretically effective against all races of this pathogen. Evaluation of a historical set of public cultivars representing 80 years of soybean breeding indicated that there have been genetic gains for partial resistance; however, these gains may have begun to plateau in the 1970s to early 1980s. Cultivars developed in Ohio generally have high levels of partial resistance to P. sojae; however, there is little known about the genetic regions associated with the partial resistance. Further improvement of increasing partial resistance could be achieved through the introgression of known quantitative trait loci (QTL) from plant introductions from the Republic of Korea (South Korea), which contain high levels of partial resistance. From an analysis of 1,398 plant introductions with a wide range of phenotypic expression of resistance, sixteen single nucleotide polymorphisms (SNPs) were associated with partial resistance to P. sojae. These SNPs were located in three genomic regions, or QTL, on chromosomes 3, 13, and 19. The QTL on chromosome 19 represented a novel locus, whereas the QTL on chromosomes 3 and 13 were coincident with previously identified QTL for partial resistance and/or Rps genes. In contrast, a genome-wide association study carried out in Ohio breeding lines was unable to detect any significant marker-trait associations, limiting the ability to use marker assisted selection to improve partial resistance in this population. However, genomic selection (GS) was shown to be a promising means of selection, with (open full item for complete abstract)