Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling

Analyses of ecological data should account for the uncertainty in the process(es) that generated the data. However, accounting for these uncertainties is a difficult task, since ecology is known for its complexity. Measurement and/or process errors are often the only sources of uncertainty modeled when addressing complex ecological problems, yet analyses should also account for uncertainty in sampling design, in model specification, in parameters governing the specified model, and in initial and boundary conditions. Only then can we be confident in the scientific inferences and forecasts made from an analysis. Probability and statistics provide a framework that accounts for multiple sources of uncertainty. Given the complexities of ecological studies, the hierarchical statistical model is an invaluable tool. This approach is not new in ecology, and there are many examples (both Bayesian and non-Bayesian) in the literature illustrating the benefits of this approach. In this article, we provide a baseline for concepts, notation, and methods, from which discussion on hierarchical statistical modeling in ecology can proceed. We have also planted some seeds for discussion and tried to show where the practical difficulties lie. Our thesis is that hierarchical statistical modeling is a powerful way of approaching ecological analysis in the presence of inevitable but quantifiable uncertainties, even if practical issues sometimes require pragmatic compromises.

Growth and Characterization of Silicon Carbide Thin Films Using a Nontraditional Hollow Cathode Sputtering Technique

Silicon carbide (SiC) is considered a suitable candidate for high-power, high-frequency devices due to its wide bandgap, high breakdown field, and high electron mobility. It also has the unique ability to synthesize graphene on its surface by subliming Si during an annealing stage. The deposition of SiC is most often carried out using chemical vapor deposition (CVD) techniques, but little research has been explored with respect to the sputtering of SiC. Investigations of the thin film depositions of SiC from pulse sputtering a hollow cathode SiC target are presented. Although there are many different polytypes of SiC, techniques are discussed that were used to identify the film polytype on both 4H-SiC substrates and Si substrates. Results are presented about the ability to incorporate Ge into the growing SiC films for the purpose of creating a possible heterojunction device with pure SiC. Efforts to synthesize graphene on these films are introduced and reasons for the inability to create it are discussed. Analysis mainly includes crystallographic and morphological studies about the deposited films and their quality using x-ray diffraction (XRD), reflection high energy electron diffraction (RHEED), transmission electron microscopy (TEM), scanning electron microscopy (SEM), atomic force microscopy (AFM), Auger electron spectroscopy (AES) and Raman spectroscopy. Optical and electrical properties are also discussed via ellipsometric modeling and resistivity measurements. The general interpretation of these analytical experiments indicates that the films are not single crystal. However, the majority of the films, which proved to be the 3C-SiC polytype, were grown in a highly ordered and highly textured manner on both (111) and (110) Si substrates.