Great Smoky Mountains National Park (GRSM) received 12.5 million visitors in 2020. With a high traffic volume, it is imperative roadways remain open and free from obstruction. Annual unanticipated rockfall events in GRSM often obstruct traffic flow. Using the Unstable Slope Management Program for Federal Land Management Agencies (USMP for FLMA) protocols, this study analyzes high priority unstable rock slopes through 1) creation of an unstable slope geodatabase and 2) generation of a final rockfall risk model using Co-Kriging from a preliminary risk model and susceptibility model. A secondary goal of this study is to provide risk estimation for the three most traveled transportation corridors within GRSM, as well as investigate current rockfall hazard warning sign location to ultimately improve visitor safety with regards to rockfall hazards.

This research estimated the spatial-temporal patterns of tornadoes in the continental United States from 1950-2019 using the National Weather Service Storm Prediction Center’s Severe Weather GIS (SVRGIS) database. This study employed Space-Time Cube Analysis and Linear Kernel Density (Kernel Density Linear Process, (KDLP)) rather than the standard Kernel Density Estimation (KDE) approach; to evaluate whether tornado hotspot locations and intensities shift over time. The first phase of the study utilized KDLP to map changes in tornado hotspots and qualitatively assess decadal shifts in hotspot locations and intensities by occurrence and magnitude between decades using ArcGIS Pro and CrimeStat. Next an Emerging Hot Spot Analysis (EHSA) was employed to identify the changes in tornado occurrence and magnitude. ESHA results identified, by both occurrence and magnitude, significant intensifying hot spots in the Southeast region and diminishing hot spots in the Great Plains indicating an east-south-east shift.

The heterogeneity of the continental crust has a first order control on the dynamics of plate tectonic processes and the compositions of the Earth in both time and space. Heterogeneity can be characterized at a variety of scales and in a multitude of tectonic environments, but it is the links between seemingly disparate tectonic settings and crustal levels that are critical in understanding construction of the continents. The focus of this dissertation work is to apply microtextural, microgeochemical, whole rock geochemical and traditional petrographic techniques to study features in both deep and shallow crustal igneous rocks. The goal of these efforts is to better understand the roles that magmatic processes, mafic-felsic magma interaction, and partial melting have on the evolution of continental crust. Two principal field areas were selected, the Gouldsboro pluton in coastal Maine and the Fehr granite in northern Saskatchewan, Canada, because they each represent end-members of the processes involved with the generation, modification, transport, and emplacement of magmas that build continental crust. Evidence for bimodal magmatism preserved in the Silurian age Gouldsboro pluton has led to a refined model for the construction of shallow crustal magma chambers. Research efforts focused on the Neoarchean Fehr granite and Paleoproterozoic Chipman dike swarm have contributed to the current understanding of the links between high temperature metamorphism (migmitization) and the production of new felsic magmas as well as the rheological and chemical influences of mafic-felsic magma interaction in the deep crust. The results of these combined field and laboratory efforts have demonstrated the important role of mafic-felsic magma interaction on the strength and composition of both deep and shallow continental crust and have contributed to the current understanding of the complex links between deep crustal heterogeneity and bimodal magmatism at shallow crustal levels.

<p>Understanding the response of forest carbon uptake and growth to interannual climate variability and forest management practices is important, given the large quantity of carbon stored in forests, and their significant role in the global carbon cycle. Since 2004, biometric and micrometeorological measurements were taken in an age-sequence (10-, 38- and 73-years-old as of 2012) of white pine (<em>Pinus strobes</em> L.) plantation forests in southern Ontario, Canada, providing an 8 year record of carbon sequestration, growth and climate. The 73-year old conifer site was thinned in early 2012, where 25% of trees were removed to improve light and water dynamics of this stand, providing an opportunity to study the impacts of thinning on its carbon cycle. Additionally, in 2012, similar biometric and micrometeorological measurements were initiated in a naturally-regenerated, managed 80-year-old deciduous (Carolinian) forest, located in close proximity to the pine stands. Similar to the conifer sites, the deciduous site is also a managed forest. The objectives of this study were to determine differences in carbon pools and carbon sequestration capacity: (a) across an age-sequence of afforested, managed conifer stands; (b) between similarly-aged managed coniferous and deciduous stands; and (c) in a mature conifer plantation before and after a thinning event. Results show that carbon assimilated in the stem of mature white pine trees follows a linear growth trend, while that of young white pines shows an exponential increase in carbon assimilation over the course of this study. Overall, carbon sequestration increased with stand age across the age-sequence, except when disturbed by an event such as thinning. Thinning substantially reduced the live aboveground carbon pool (by 14%), while increasing woody debris (by 122%) due to logging residue left on-site. Comparison between the mature coniferous and deciduous stands, showed that total aboveground carbon storage within the pine stand (144 t C/ha) was generally higher than in the oak-dominated deciduous stand (83 t C/ha), despite both growing in similar soil and climate. While monthly tree growth exhibited a positive correlation with mean monthly temperature across all sites, tree growth negatively correlated with precipitation at the 10-year old white pine and 80-year old deciduous sites and no apparent correlation existed at the 73- and 38-year old sites. At the three coniferous stands, total annual net primary productivity (NPP) exhibited no correlation with mean growing season temperature or precipitation. This suggested that tree growth in young coniferous stands could be as sensitive as that of mature deciduous stands to precipitation. However, overall NPP seemed to be less sensitive to climatic variables across these stands, irrespective of their age and NPP may be driven more by stand physiology. Finally, eddy covariance and biometric estimations of NPP and NEP were compared, and results showed that although some growth trends do compare between the two techniques, magnitude discrepancies do exist and should be studied further. Results from this study will be informative to forest managers, forest conservationists and those interested in forest carbon sequestration.</p> / Master of Science (MSc)

Landslides are mass movements that affect infrastructure across East Tennessee, causing problems for the Tennessee Department of Transportation (TDOT). An assessment of conditions and locations of unstable slopes can aid TDOT in infrastructure management. Landslide susceptibility was evaluated for Anderson and Morgan counties, TN, off State Route 116 in the New River watershed. Susceptibility maps used a landslide inventory and six factors: elevation, slope, geology, distance from stream, rainfall, and curvature, input in forest-based classification and logistic regression models. Additionally, affected trees along these unstable slopes in Anderson and Morgan counties were cored to analyze mass movement impacts on tree rings. This research demonstrates the importance of causative factors used to model landslide susceptible areas and how trees rings can carry the signature of landslides. These two studies can help aid in mitigation practices for TDOT and potentially apply landslide susceptibility research to other parts of East Tennessee.

Fossil localities across the state of Tennessee and the data related to those sites were compiled from Tennessee Division of Geology Bulletin 84, titled “Tennessee’s Prehistoric Vertebrates,” and stored in a Microsoft Access geodatabase housed by the Department of Collections at the East Tennessee State University Museum of Natural History located at the Gray Fossil Site. Included in the database are forms to enter new site localities, view information about those already entered, view and add data to a master faunal list for the state, view sites repository information and store and add documents that are key-word searchable from the main menu. This database was compiled to give researchers a straightforward and easy to use means of analyzing known information about paleontological sites across the state, with the potential to be expanded worldwide. Conservation of data is crucial and can be lost over time unless data preservation efforts are made.

Pelagic Sargassum is one type of marine macroalgae that is known to be abundant in the Gulf of Mexico and Sargasso Sea. It is also known to serve as a critical habitat for many marine animals. In the past few years, large amounts of Sargassum have been reported in the Tropical Atlantic and Caribbean Sea (CS), causing significant environmental and economic problems. The goal of this study is to improve the understanding of Sargassum distributions, quantity, transport pathways, and bloom mechanisms in the CS and Tropic Atlantic through combining a variety of techniques including satellite remote sensing, field and laboratory measurements, and numerical modeling. The first question is where and how much Sargassum is in the CS and Tropic Atlantic. Previous field observations revealed strong seasonal and spatial variations of Sargassum, yet these observations are all limited in their spatial and temporal coverage. Satellite observations offer an effective means to measure their distributions with synoptic coverage and high sampling frequency, yet it is technically challenging to extract and quantify the small Sargassum features in coarse-resolution satellite imagery. Chapter 2 focuses on Sargassum detection and quantification algorithm development using Moderate Resolution Imaging Spectroradiometer (MODIS) data (Appendix A). The algorithm is based on MODIS alternative floating algae index (AFAI), which examines the red-edge reflectance of floating vegetation. The algorithm includes three basic steps: 1) classification of Sargassum-containing pixels through correction of large-scale gradient, masking clouds and cloud shadows, and removal of ambiguous pixels; 2) linear unmixing of Sargassum-containing pixels; and, 3) statistical analysis of Sargassum area coverage in pre-defined grids at monthly, seasonal, and annual intervals. The algorithm is applied to MODIS observations between 2000 and 2015 over the Central West Atlantic (CWA) region (0 – 22oN, 38 – 63oW) to derive the spatial and temporal distribution patterns as well as the total areal coverage of Sargassum. Results indicate that the first widespread Sargassum distribution event occurred in 2011, consistent with previous findings from the Medium Resolution Imaging Spectrometer (MERIS). Since 2011, only 2013 showed minimal Sargassum coverage similar to the period of 2000 to 2010; all other years showed significantly more coverage. More alarmingly, the summer months of 2015 showed mean coverage of > 2000 km2, or about 4 times of the summer 2011 coverage and 20 times of the summer 2000 to 2010 coverage. Analysis of several environmental variables provided some hints on the reasons causing the inter-annual changes after 2010, yet further multi-disciplinary research (including in situ measurements) is required to understand such changes and long-term trends in Sargassum coverage. To better understand the potential ecological and environmental impacts of Sargassum, field and laboratory experiments are conducted to link the Sargassum areal coverage observations to biomass per area (density) and measure the nutrient contents and pigment concentrations (Chapter 3, Appendix B). An AFAI-biomass density model is established to derive Sargassum biomass density from the spectral reflectance, with a relative uncertainty of ~ 12%. Monthly mean integrated Sargassum biomass in the CS and CWA reached > 4.4 million tons in July 2015. The average % C, % N, and % P per dry-weight, measured from samples collected in Gulf of Mexico and Florida Straits in summer 2017, are 27.16, 1.06, and 0.10, respectively. The mean chlorophyll-a concentration is ~ 0.05% of the dry-weight. With these parameters, the amounts of nutrients and pigments can be estimated directly from remotely-sensed Sargassum biomass. During bloom seasons, Sargassum carbon can account for ~ 18% of the total particulate organic carbon in the upper water column. This chapter provides the first quantitative assessment of the overall Sargassum biomass, nutrients, and pigment abundance from remote-sensing observations, thus helping to quantify their ecological roles and facilitate management decisions. To investigate the Sargassum transport patterns and potential bloom sources, a Lagrangian particle tracking model is established to track the Sargassum transport driven by surface currents and winds (Chapter 4, Appendix C). The mean Sargassum distributions derived from MODIS observations are used to initiate and evaluate a Lagrangian particle tracking model that tracks Sargassum advection under surface currents and winds. Among the thirty-nine experiments, adding surface currents alone improves model performance (i.e., by reducing difference between modeled and observed Sargassum distributions) in 82% of the cases after tracking Sargassum for one month. Adding 1% wind forcing to the advection model also shows improved performance in 67% of the cases. Adding a time- and location-dependent Sargassum growth/mortality rate (i.e., change rate), derived from time-series of the MODIS-based Sargassum abundance and the corresponding environmental data via a Random Forest regression, leads to further improvement in model performance (i.e., by increasing the matchup percentage between modeled and observed Sargassum distributions) in 64% of the cases, although the modeled change rates only explain ~ 27% of the variance of the validation dataset, possibly due to uncertainties in such-derived change rates. The Sargassum transport model, with the mean currents, winds, and change rates acting as the forcing, is applied to track the mean Sargassum distributions forward and backward. The results demonstrate the model’s capacity of simulating the Sargassum distribution patterns, with emphasis on the role of biological terms in determining the large-scale distributions. These tracking experiments also suggest that Sargassum blooms in the CS are strongly connected to the Central Atlantic regions, and blooms in the Tropical Atlantic show relatively weak connections to the Atlantic regions further north. Although it is straightforward to apply the transport model to predict Sargassum blooms, such long-term prediction could suffer from large error accumulations and unable to achieve satisfactory performance. Therefore historical Sargassum distributions derived from MODIS are used to provide an alternative way to realize the bloom prediction. Chapter 5 proposes such a prediction based on a hindcast of 2000–2016 observations from MODIS, which shows Sargassum abundance in the CS and the CWA, as well as connectivity between the two regions with time lags (Appendix D). This information is used to derive bloom and nonbloom probability matrices for each 1° square in the CS for the months of May–August, predicted from bloom conditions in a hotspot region in the CWA in February. A suite of standard statistical measures is used to gauge the prediction accuracy, among which the user’s accuracy and kappa statistics show high fidelity of the probability maps in predicting both blooms and nonblooms in the eastern CS with several months of lead time, with an overall accuracy often exceeding 80%. The bloom probability maps from this hindcast analysis will provide early warnings to better study Sargassum blooms and prepare for beaching events near the study region. This approach may also be extendable to many other regions around the world that face similar challenges and opportunities of macroalgal blooms and beaching events. Using this forecasting scheme, the summer blooms in the CS in 2017 were successfully predicted. Since February 2018, we have also generated monthly-updated 1-page Sargassum outlook bulletins to help these regions to better prepare for potential beaching events. Currently, the mean Sargassum distribution statistics used in this study are derived from MODIS, which has been operating well beyond the designed mission life, arousing concerns as to whether the Sargassum observation statistics can be continued in the future. As a follow-on sensor, the Visible Infrared Imaging Radiometer Suite (VIIRS) has the appropriate spectral bands to detect and quantify floating macroalgae. Based on previous works on MODIS, Chapter 6 presents an improved procedure to extract floating algae pixels from VIIRS AFAI imagery, with image filtering used to suppress noise and adjusted thresholds used to mask sun glint, clouds, and cloud shadows. The overall extraction accuracy is about 85%. Simultaneous daily observations from MODIS and VIIRS over the CWA show consistent spatial patterns, but VIIRS estimations of the algae coverage (in km2) are consistently lower than MODIS (around – 19% mean relative difference or MRD), possibly due to lower sensitivity of the VIIRS near-infrared (NIR) bands than the corresponding MODIS bands. Similarly, at monthly scale VIIRS also shows lower coverage than MODIS, and their difference (around – 29% MRD) is larger than the difference between MODIS-Aqua and MODIS-Terra estimates (around – 14% MRD). Despite these differences, the spatial and temporal patterns between VIIRS and MODIS observed algae distributions match very well at all spatial and temporal scales. These results suggest that VIIRS can provide continuous and consistent observations of floating algae distributions and abundance from MODIS as long as their differences are accounted for, thus assuring continuity in the future. In summary, this study has worked on four connected topics regarding Sargassum distributions, biomass and nutrients, transport pathways, and bloom predictions through combined efforts in satellite remote sensing, field and laboratory measurements, physical modelling, and statistical analyses. To my best knowledge, this is the first comprehensive and multi-disciplinary study to investigate pelagic Sargassum at synoptic scale in the Intra-Americas Sea (IAS) and Atlantic Ocean. Although several questions remain to be answered (e.g., “What cause the inter-annual variations of Sargassum blooms?” and “Where are the bloom origins?”), the outcomes of this study (remote sensing algorithms, Sargassum distribution and abundance maps, established bio-physical model, and a bloom forecast model) are expected to make significant contributions in both scientific research (including new critical baseline data) and management decision support.

Community coalitions are an important part of the public health milieu and thus subject to many of the same external pressures as public health organizations--including changes in required strategic orientation. Many funding agencies have shifted their funding agenda from program development to policy change. Thus, the Florida Prevention Research Center created the Community-Based Prevention Marketing for Policy Development framework to teach community coalitions how to apply social marketing to policy change. The dissertation research reported here was designed to explicate the framework's theory-of-change. The research question was: "What are the linkages and connections between CBPM inputs, activities, immediate outcomes, intermediate outcomes, and ultimate impacts?" The author implemented a case study design, with the case being a normative community coalition. The study adhered to a well-developed series of steps for system dynamics modeling. Results from model simulations show how gains in performance depend on a community coalition's initial culture and initial efficiency, and that only the most efficient coalitions may see benefits in coalition performance from implementing Community-Based Prevention Marketing for Policy Development. Theoretical implications for social marketers--e.g., real-world example of how to work `upstream'--and system dynamics modelers--e.g., application of generic structures--are discussed. Practical implications for the framework's developers--namely, the importance of managing the early expectations of framework adopters--are discussed as well.

<p>Denna studie är en undersökning av hur elever i år 6 uppfattade det geografiska rummet, vilka omvärldsbilder elever i skolan innehade, hur de påverkades av olika intryck från omgivningen samt om elevernas omvärldsbilder förändrades under en termin. Att inneha en omvärldsbild innebär att ha en föreställning om hur den rumsliga världen ser ut och förhåller sig. Undersökningen var av empirisk art och bestod av en namngeografisk undersökning av geografiska objket i Sverige, elevernas ritade bilder av världen, intervjufrågor samt en kartförståelseuppgift. Studien genomfördes vid två olika tillfällen för att se på eventuella förändringar i elevernas omvärldsbilder. Studien visade på att elevernas omvärldsbilder påverkades, utvecklades och innehöll all den information individen mötte och hade med sig sedan tidigare om den rumsliga världen. Undersökningen visade även på att omvärldsbilder kan förändras och utvecklas unnder en termin.</p>

<p>A study has been conducted to assess the possibilities to introduce dead cattle organs as the raw material for biogas generation at the rural household level in Bangladesh. At the same time, the present energy situation in Bangladesh is highlighted. The actors in the energy sector have been identified. The energy policy of Bangladesh is not transparent and there seems to be no energy strategy for the country. Possibilities of other renewable sources of energy are also discussed. Biomass fuels comprise the main source of energy for the rural people and the major share of energy use is consumed after cooking and household lightning. Enormous amount of labor is spent in gathering and collecting of fuel wood and agricultural residues that reduces productivity among women and young children. Besides, biogas is generated from agricultural residues and animal excreta in Bangladesh. Tremendous pressure on rural forests for fuel wood is increasing and environmental degradation is occurring. Agricultural lands are losing vital nutrients as people are using crop residues and animal excreta for energy. Under present condition, the possibilities of adopting biogas technology and dead cattle organs as the raw materials to generate biogas is analyzed in terms of availability of the raw material. Sustainable development using biogas is also considered. And lastly, some recommendation is suggested, based on the current energy situation of Bangladesh.</p>