Locusts are generalist herbivores meaning that they are able to consume a variety of plants. Because of their broad diet, and ability to respond rapidly to a favorable environment with giant swarms of voracious insects, they are dangerous pests. Their potential impacts on humans increase dramatically when individuals switch from their solitarious phase to their gregarious phase where they congregate and begin marching and eventually swarming together. These swarms, often billions strong, can consume the vegetation of enormous swaths of land and can travel hundreds of kilometers in a single day producing a complex threat to food security. To better understand the biology of these important pests we explored the gut microbiome of the South American locust (Schistocerca cancellata). We hypothesized generally that the gut microbiome in this species would be critically important as has been shown in many other species. We extracted and homogenized entire guts from male S. cancellata, and then extracted gut microbiome genomic DNA. Genomic DNA was then confirmed on a gel. The initial extractions were of poor quality for sequencing, but subsequent extractions performed by collaborators during troubleshooting at Southern Illinois University Edwardsville proved more useful and were used for PCR. This resulted in the detections of the following bacterial genera in the gut of S. cancellata: Enterobacter, Enterococcus, Serratia, Pseudomonas, Actinobacter, and Weisella. With this data, we are able to speculate about the physiological roles that they hold within the locust gut generating hypotheses for further testing. Understanding the microbial composition of this species’ gut may help us better understand the locust in general in an effort to more sustainably manage them.

Optimal foraging theory provides a suite of tools that model the best way that an animal will <br/>structure its searching and processing decisions in uncertain environments. It has been <br/>successful characterizing real patterns of animal decision making, thereby providing insights<br/>into why animals behave the way they do. However, it does not speak to how animals make<br/>decisions that tend to be adaptive. Using simulation studies, prior work has shown empirically<br/>that a simple decision-making heuristic tends to produce prey-choice behaviors that, on <br/>average, match the predicted behaviors of optimal foraging theory. That heuristic chooses<br/>to spend time processing an encountered prey item if that prey item's marginal rate of<br/>caloric gain (in calories per unit of processing time) is greater than the forager's<br/>current long-term rate of accumulated caloric gain (in calories per unit of total searching<br/>and processing time). Although this heuristic may seem intuitive, a rigorous mathematical<br/>argument for why it tends to produce the theorized optimal foraging theory behavior has<br/>not been developed. In this thesis, an analytical argument is given for why this<br/>simple decision-making heuristic is expected to realize the optimal performance<br/>predicted by optimal foraging theory. This theoretical guarantee not only provides support<br/>for why such a heuristic might be favored by natural selection, but it also provides<br/>support for why such a heuristic might a reliable tool for decision-making in autonomous<br/>engineered agents moving through theatres of uncertain rewards. Ultimately, this simple<br/>decision-making heuristic may provide a recipe for reinforcement learning in small robots<br/>with little computational capabilities.

This thesis is a supplement textbook designed with ASU’s MAT 370, or more generally, a course in introductory real analysis (IRA). With research in the realms of mathematics textbook creation and IRA pedagogy, this supplement aims to provide students or interested readers an additional presentation of the materials. Topics discussed include the real number system, some topology of the real line, sequences of real numbers, continuity, differentiation, integration, and the Fundamental Theorem of Calculus. Special emphasis was placed on worked examples of proven results and exercises with hints at the end of every chapter. In this respect, this supplement aims to be both versatile and self-contained for the different mathematics skill levels of readers.