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.

Host plant choice by herbivorous insects can be driven by a variety of factors including plant nutrient composition and mechanical properties. In this study, I investigated the role of plant protein and carbohydrate composition, water content, and leaf thickness on plant preference for the Australian Plague Locust (Chortoicetes terminifera). For this, I used four economically important cereal crop species: barley Hordeum vulgare, wheat Triticum aestivum L., rye Secale cereale, and corn Zea mays. Using a full factorial design, I gave the choice to the locusts between two plant species then I measured 1) visual preference by pairing, 2) surface area consumed, and 3) dry mass consumed. For each leaf, I measured protein content, carbohydrate content, foliar wet mass, and Specific Leaf Area (SLA, a measure of plant thickness). I found plant nutrient content was not a good predictor of host plant choice in the short term, however, leaf thickness had a significant relationship with dry amount of leaf consumed and defoliation. Overall locusts preferred plants that were thinner. I discuss these results in light of our current knowledge of the nutritional ecology of this important cereal crop pest.

Engineered pavements cover a large fraction of cities and offer significant potential for urban heat island mitigation. Though rapidly increasing research efforts have been devoted to the study of pavement materials, thermal interactions between buildings and the ambient environment are mostly neglected. In this study, numerical models featuring a realistic representation of building-environment thermal interactions, were applied to quantify the effect of pavements on the urban thermal environment at multiple scales. It was found that performance of pavements inside the canyon was largely determined by the canyon geometry. In a high-density residential area, modifying pavements had insignificant effect on the wall temperature and building energy consumption. At a regional scale, various pavement types were also found to have a limited cooling effect on land surface temperature and 2-m air temperature for metropolitan Phoenix. In the context of global climate change, the effect of pavement was evaluated in terms of the equivalent CO2 emission. Equivalent CO2 emission offset by reflective pavements in urban canyons was only about 13.9e46.6% of that without building canopies, depending on the canyon geometry. This study revealed the importance of building-environment thermal interactions in determining thermal conditions inside the urban canopy.

Critical flicker fusion thresholds (CFFTs) describe when quick amplitude modulations of a light source become undetectable as the frequency of the modulation increases and are thought to underlie a number of visual processing skills, including reading. Here, we compare the impact of two vision-training approaches, one involving contrast sensitivity training and the other directional dot-motion training, compared to an active control group trained on Sudoku. The three training paradigms were compared on their effectiveness for altering CFFT. Directional dot-motion and contrast sensitivity training resulted in significant improvement in CFFT, while the Sudoku group did not yield significant improvement. This finding indicates that dot-motion and contrast sensitivity training similarly transfer to effect changes in CFFT. The results, combined with prior research linking CFFT to high-order cognitive processes such as reading ability, and studies showing positive impact of both dot-motion and contrast sensitivity training in reading, provide a possible mechanistic link of how these different training approaches impact reading abilities.

Although autism spectrum disorder (ASD) is a serious lifelong condition, its underlying neural mechanism remains unclear. Recently, neuroimaging-based classifiers for ASD and typically developed (TD) individuals were developed to identify the abnormality of functional connections (FCs). Due to over-fitting and interferential effects of varying measurement conditions and demographic distributions, no classifiers have been strictly validated for independent cohorts. Here we overcome these difficulties by developing a novel machine-learning algorithm that identifies a small number of FCs that separates ASD versus TD. The classifier achieves high accuracy for a Japanese discovery cohort and demonstrates a remarkable degree of generalization for two independent validation cohorts in the USA and Japan. The developed ASD classifier does not distinguish individuals with major depressive disorder and attention-deficit hyperactivity disorder from their controls but moderately distinguishes patients with schizophrenia from their controls. The results leave open the viable possibility of exploring neuroimaging-based dimensions quantifying the multiple-disorder spectrum.

Nutrient recycling by fish can be an important part of nutrient cycles in both freshwater and marine ecosystems. As a result, understanding the mechanisms that influence excretion elemental ratios of fish is of great importance to a complete understanding of aquatic nutrient cycles. As fish consume a wide range of diets that differ in elemental composition, stoichiometric theory can inform predictions about dietary effects on excretion ratios.
We conducted a meta-analysis to test the effects of diet elemental composition on consumption and nutrient excretion by fish. We examined the relationship between consumption rate and diet N : P across all laboratory studies and calculated effect sizes for each excretion metric to test for significant effects.
Consumption rate of N, but not P, was significantly negatively affected by diet N : P. Effect sizes of diet elemental composition on consumption-specific excretion N, P and N : P in laboratory studies were all significantly different from 0, but effect size for raw excretion N : P was not significantly different from zero in laboratory or field surveys.
Our results highlight the importance of having a mechanistic understanding of the drivers of consumer excretion rates and ratios. We suggest that more research is needed on how consumption and assimilation efficiency vary with N : P and in natural ecosystems in order to further understand mechanistic processes in consumer-driven nutrient recycling.