Beetle Diversity within Ecosystems; Insight of the Order Coleoptera in the Eastern Kentucky Region

Having a multitude of definitions, biodiversity can most commonly be seen as the variety and diversity of life within an ecosystem. Its relevance is crucial for species survival and resource availability; a lack of biodiversity sets an ecosystem up for failure, reducing its productivity, species richness, and increasing organismal vulnerability. Measuring biodiversity is crucial for the understanding of an ecosystem’s health, giving scientists knowledge of its stability, productivity, and persistence. This collected information can be implemented in various ways outside the scientific field as well, such as with policy decisions and legal regulations. Biodiversity is most commonly analyzed through quantitative assessment of mammal and bird species, but the relatively low numbers of species and few individuals in defined areas tend to cause flawed statistical results. Beetles, however, can be found in large numbers in just about all ecosystems. Having an immense diversity of species, they play significant roles in environments, filling ecological roles as herbivores, decomposers, predators, coprophages, fungivores, etc. As beetles are tremendously diverse and very abundant, quantitative assessments of their diversity are more statistically rigorous. We are sampling beetles from 3 sites located near Morehead, KY. Beetles were collected using pan traps and leaf litter sifting. Collected beetles were then pinned or pointed and sorted by family groups. The primary focus of the study was to determine the various beetle species and their quantitative presence within the multiple sampling sites.https://scholarworks.moreheadstate.edu/celebration_posters_2022/1013/thumbnail.jp

Experiment to Characterize Aircraft Volatile Aerosol and Trace-Species Emissions (EXCAVATE)

The Experiment to Characterize Aircraft Volatile and Trace Species Emissions (EXCAVATE) was conducted at Langley Research Center (LaRC) in January 2002 and focused upon assaying the production of aerosols and aerosol precursors by a modern commercial aircraft, the Langley B757, during ground-based operation. Remaining uncertainty in the postcombustion fate of jet fuel sulfur contaminants, the need for data to test new theories of particle formation and growth within engine exhaust plumes, and the need for observations to develop air quality models for predicting pollution levels in airport terminal areas were the primary factors motivating the experiment. NASA's Atmospheric Effects of Aviation Project (AEAP) and the Ultra Effect Engine Technology (UEET) Program sponsored the experiment which had the specific objectives of determining ion densities; the fraction of fuel S converted from S(IV) to S(VI); the concentration and speciation of volatile aerosols and black carbon; and gas-phase concentrations of long-chain hydrocarbon and PAH species, all as functions of engine power, fuel composition, and plume age

A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants.

This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/ng.3448Advanced age-related macular degeneration (AMD) is the leading cause of blindness in the elderly, with limited therapeutic options. Here we report on a study of >12 million variants, including 163,714 directly genotyped, mostly rare, protein-altering variants. Analyzing 16,144 patients and 17,832 controls, we identify 52 independently associated common and rare variants (P < 5 × 10(-8)) distributed across 34 loci. Although wet and dry AMD subtypes exhibit predominantly shared genetics, we identify the first genetic association signal specific to wet AMD, near MMP9 (difference P value = 4.1 × 10(-10)). Very rare coding variants (frequency <0.1%) in CFH, CFI and TIMP3 suggest causal roles for these genes, as does a splice variant in SLC16A8. Our results support the hypothesis that rare coding variants can pinpoint causal genes within known genetic loci and illustrate that applying the approach systematically to detect new loci requires extremely large sample sizes.We thank all participants of all the studies included for enabling this research by their participation in these studies. Computer resources for this project have been provided by the high-performance computing centers of the University of Michigan and the University of Regensburg. Group-specific acknowledgments can be found in the Supplementary Note. The Center for Inherited Diseases Research (CIDR) Program contract number is HHSN268201200008I. This and the main consortium work were predominantly funded by 1X01HG006934-01 to G.R.A. and R01 EY022310 to J.L.H