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The odorous house ant, Tapinoma sessile, is a widespread, common pest in North American residential areas, yet the understanding of how viral pathogens shape its behavior, management, and interactions with other insects remains limited. Over the course of my thesis, I characterized four novel viruses in T. sessile using metatranscriptomic analysis, investigated their infectivity, and explored how colony social organization influences viral infection patterns. Inoculation experiments confirmed active infection in T. sessile colonies, suggesting trophallaxis as a route for horizontal transmission. These viruses were prevalent in urban populations with polygyne, unicolonial traits, indicating a potential association between colony social structure, colony location, and virus presence and diversity. Additionally, common honey bee viruses including Deformed Wing Virus and Kashmir Bee Virus were detected in T. sessile colonies, with higher prevalence near beehives, indicating a route for virus spillover between the species. Furthermore, the impact of viral infection on foraging behavior was assessed, revealing altered activity and diet preferences in infected colonies and highlighting the need for modified control strategies. Finally, I explored virus transmission between T. sessile and associated arthropods and found shared viruses and active replication in arthropods within ant nests, indicating a novel case of virus spillover between ants and myrmecophiles. These findings offer insights into viral pathogen interactions within ant colonies, the influence of social organization on infection dynamics, and the potential for pathogen transmission between ants and associated arthropods and offer a deeper understanding of an important native ant species that may shape future pest management strategies. / Master of Science in Life Sciences / In my thesis research I studied the odorous house ant or sugar ant, a common pest in homes and businesses in North America, to understand how viral pathogens shape its behavior, management, and interactions with other insects. I discovered four new odorous house ant viruses infecting these ants using molecular analysis techniques and found that they can pass from ant to ant when they share food. Interestingly, these viruses were more common in urban ant colonies with multiple queens, suggesting a link between the ants' social structure and the viruses they carry. Additionally, I found viruses typically seen in honey bees in these ant colonies, especially when those colonies were close to beehives, indicating that the odorous house ant can pick up viruses from honey bees. Furthermore, I studied how these viruses affect ant behavior and found that infected ant colonies change their activity and food preferences. Lastly, I investigated if these viruses are able to jump from ants to other insects and found evidence that insects living in their nests shared the same or similar virus infections. These findings provide important insights into how viruses spread among ant colonies and nearby insects, how their social structure affects transmission of viruses, and how viruses can move between different species of insects. Understanding these interactions is crucial for developing better ways to control ant pests and for gaining a deeper understanding of this important native ant species.

Nest survival often is lower at habitat edges than in habitat cores because of greater nest predation and parasitism near edges. I studied nest survival of breeding birds in bottomland hardwood forests of the lower Roanoke River, North Carolina. Nesting success was monitored in two forest width classes: narrow bands of levee forest that were dominated by two edge types, and wide, continuous levee forest stands that have edges but most forest is relatively far from edge. Nest success of Acadian Flycatchers and Prothonotary Warblers was similar in narrow and wide levees; nest success of Northern Cardinals was greater in narrow levees. Results of my study indicate that edge effects are not universal, and that amount of contrast at edges may interact with landscape context to alter ecological processes, such as nest predation. Bird populations are remarkably constant over time relative to other taxa, implying strong regulation. Avian population ecologists, however, have not studied regulatory mechanisms as often as seasonal limiting factors. Conversely, avian behavioral ecologists seldom emphasize the population dynamic consequences of habitat selection and reproductive success. This study describes the intersection of individual behavior and population regulation in the context of a new model of population regulation, site dependence, which is based on characteristics of breeding sites and behavior of individuals. I studied habitat distribution, age structure, reproductive output, and breeding site fidelity of Prothonotary Warblers (Protonotaria citrea) in two different bottomland hardwood forest habitats of the lower Roanoke River in North Carolina. Older males (³ 2 yr old) were equally common in cypress-gum swamps and mixed oak hardwood levee forest. Pairing success and success of first nests indicated that older males occupied the most suitable territories available in each habitat. Bird density was three times greater in swamps, and birds nesting in swamps averaged greater clutch sizes and fledged more young per nest than birds in levees. Greater reproductive output was the result of greater fecundity because nest survival and predation pressure appeared equal in the two habitats. Annual return rates for plot immigrants vs. previous residents did not differ in swamps. In levees, newly arriving birds were less likely to return the following year than previous residents. Immigrants most likely occupied low quality sites and dispersed in an attempt to improve breeding site quality. Habitat-specific demography and density patterns of this study indicate ideal preemptive distribution. Variance in site quality, between and within habitats, and preemptive use of sites are consistent with theory of population regulation via site dependence. Foraging behavior often reflects food availability. For example, in habitats where food availability is high, predators should move more slowly and attack prey more often than in habitats where food availability is low. I studied the foraging behavior of breeding Prothonotary Warblers in two habitat types to assess relative food availability and implications for habitat quality. The two habitats, levee and swamp forest, differ in hydrology, forest structure, and tree species composition. I quantified foraging behavior with focal animal sampling and continuous recording during foraging bouts. I measured two aspects of foraging behavior: 1) prey attacks per minute, using four attack types (glean, sally, hover, strike), and 2) number of movements per minute (foraging speed), using three types of movement (hop, short flight [£ 1 m], long flight [>1 m]). Male warblers made significantly more prey attacks per minute in swamp forest than in levee forest; the same trend was evident in females. Foraging speed, however, was not different between habitats for males or females. Results indicate that foraging effort is similar in swamps and levees, but that warblers encounter more prey in swamps. Greater food availability may be related to greater reproductive success of warblers nesting in cypress-gum swamps than in coastal plain levee forest. / Ph. D.

Sensemaking tasks, such as reading many news articles to determine the truthfulness of a given claim, are difficult. These tasks require a series of iterative steps to first forage for relevant information and then synthesize this information into a final hypothesis. To assist with such tasks, visual analytics systems provide interactive visualizations of data to enable faster, more accurate, or more thorough analyses. For example, semantic interaction techniques leverage natural or intuitive interactions, like highlighting text, to automatically update the visualization parameters using machine learning. However, this process of using machine learning based on user interaction is not yet well defined. We begin our research efforts by developing a computational pipeline that models and captures how a system processes semantic interactions. We then expanded this model to denote specifically how each component of the pipeline supports steps of the Sensemaking Process. Additionally, we recognized a cognitive symmetry in how analysts consider data items (like news articles) and their attributes (such as terms that appear within the articles). To support this symmetry, we also modeled how to visualize and interact with data items and their attributes simultaneously. We built a testbed system and conducted a user study to determine which analytic tasks are best supported by such symmetry. Then, we augmented the testbed system to scale up to large data using semantic interaction foraging, a method for automated foraging based on user interaction. This experience enabled our development of design challenges and a corresponding future research agenda centered on semantic interaction foraging. We began investigating this research agenda by conducting a second user study on when to apply semantic interaction foraging to better match the analyst's Sensemaking Process. / Doctor of Philosophy / Sensemaking tasks such as determining the truthfulness of a claim using news articles are complex, requiring a series of steps in which the relevance of each piece of information within the articles is first determined. Relevant pieces of information are then combined together until a conclusion may be reached regarding the truthfulness of the claim. To help with these tasks, interactive visualizations of data can make it easier or faster to find or combine information together. In this research, we focus on leveraging natural or intuitive interactions, such organizing documents in a 2-D space, which the system uses to perform machine learning to automatically adjust the visualization to better support the given task. We first model how systems perform such machine learning based on interaction as well as model how each component of the system supports the user's sensemaking task. Additionally, we developed a model and accompanying testbed system for simultaneously evaluating both data items (like news articles) and their attributes (such as terms within the articles) through symmetrical visualization and interaction methods. With this testbed system, we devised and conducted a user study to determine which types of tasks are supported or hindered by such symmetry. We then combined these models to build an additional testbed system that implemented a searching technique to automatically add previously unseen, relevant pieces of information to the visualization. Using our experience in implementing this automated searching technique, we defined design challenges to guide future implementations, along with a research agenda to refine the technique. We also devised and conducted another user study to determine when such automated searching should be triggered to best support the user's sensemaking task.