Lower Pennsylvanian, coal-bearing, siliciclastic strata of the central Appalachian foreland basin were deposited in continental to marginal marine environments influenced by high-amplitude relative sea level fluctuations. Sediment was derived from both the low-grade metamorphic terrain of the emergent Alleghanian orogen towards the southeast, and the cratonic Archean Superior Province in the north. Immature sediments derived proximally from the Alleghanian orogen, including sublithic sandstone bodies, were deposited as a southeasterly-thickening clastic wedge within a southeast-northwest oriented transverse drainage system. Texturally and mineralogically mature quartzarenites were deposited in strike-parallel elongate belts along the western periphery of the basin. These mature quartzarenites are braided fluvial in origin and were deposited within northeast-southwest oriented axial drainage head-watered in a northerly cratonic source area. The contemporaneity of transverse and axial fluvial systems defines a trunk--tributary drainage system operating in the central Appalachian foreland basin during the early Pennsylvanian. Detailed analysis of core, gamma ray logs, and cross-sections reveals a hierarchy of bounding discontinuities and architectural elements within the study interval. Discontinuities are both erosional and depositional (condensed) surfaces of interpreted 3rd-order (~ 2.5 Ma) and 4th-order (~ 400 k.y.) origin. Architectural elements within 4th-order sequences consist of upward-fining lowstand and transgressive incised valley fill, alluvial, and estuarine deposits, and upward-coarsening highstand deltaic deposits that are separated by condensed sections. 4th-order sequences are stacked into 3rd-order composite sequences. Sequence stratigraphic architecture in the central Appalachian basin can therefore be attributed to 4th-order Milankovitch orbital eccentricity cycles superimposed on 3rd-order orogenically driven subsidence, or more likely, 4th-order Milankovitch orbital eccentricity cycles superimposed on a lower-frequency eccentricity cycle. The widespread nature of both 3rd- and 4th-order marine flooding zones and sequence boundaries enables both genetic and depositional sequence stratigraphy to be applied to terrigenous to marginal marine coal-bearing strata of the central Appalachian basin. Regionally extensive coal beds occur in close association with both 4th-order condensed sections as well as within highstand deltaic deposits. Formation of coal beds in the central Appalachian basin of southwest Virginia is therefore attributed to both an allocyclic glacio-eustatic mechanism, associated with Milankovitch orbital eccentricity cycles, and autocyclic deltaic processes related to channel avulsion and delta lobe switching. / Master of Science

The lower Pennsylvanian, coal-bearing, siliciclastic strata in Dickenson/Wise counties of southwest Virginia were deposited in continental to marginal marine environments influenced by high-amplitude relative sea level fluctuations. Coal-bearing siliciclastics of the eastern facies belt are fluvio-deltaic in origin, with sediment derived from the erosion of low-grade metamorphic and Grenvillian-Avalonian terranes of the Alleghanian orogen to the southeast. Elongate NNE trending quartzarenite belts in the northwestern region of the basin are braided-fluvial deposits and were sourced by the cratonic Archean Superior Province to the north. This orthogonal relationship between the southeastern coal-bearing siliciclastics and the northwestern quartzarenites reflect a trunk-tributary drainage system operating during the lower Pennsylvanian in the central Appalachian basin. Analysis of core, gamma ray and density logs, and six cross-sections within an approximately 20 km² study area reveals a hierarchy of bounding discontinuities and architectural elements. Discontinuities are both erosional (unconformable) and depositional (condensed) and are 3rd-order (~ 2.5 Ma) and 4th-order (~ 400 k.y.) in origin. Architectural elements are bound by 4th-order discontinuities and consist of upward-fining lowstand and transgressive incised valley fill, alluvial, and estuarine deposits, and upward-coarsening highstand deltaic deposits and represent 4th-order sequences. Lowstand and transgressive deposits are separated from the highstand deposits by marine flooding zones (condensed sections). 4th-order sequences are stacked into composite 3rd-order sequences. Sequence development can be attributed to 4th-order Milankovitch orbital eccentricity cycles superimposed on a lower-frequency eccentricity cycle. Extensive coals occur in both transgressive and highstand systems tracts. Coals within the transgressive systems tract are associated with 4th-order flooding surfaces, while coals within the highstand systems tract occur within high-frequency deltaic autocycles. Therefore, coals formation in the central Appalachian basin can be attributed to be of both allocyclic (glacio-eustacy) and autocyclic (deltaic processes) mechanisms. / Master of Science

Previous historical and cultural geographic studies of the cemetery suggest that gravemarkers are surrogates for ethnicity and cultural assimilation. While studies of this type among single ethnic groups are common, examination of the multiethnic cemetery has largely been ignored. This study focuses on the necrogeography (regional burial practices) of the Melungeons, an understudied and underrepresented minority group. Their diverse ancestry purportedly includes a mixture of European, Native American, and African heritage. They have settled primarily in the Central Appalachian region, and more specifically within Hancock County, Tennessee. Their traditional burial practices include the construction of a unique gravehouse. I conducted personal interviews with Melungeons, religious leaders, and cemetery workers to determine the social meanings attached to these unique gravemarkers. I inspected 116 cemeteries located within Hancock County. A Melungeon Burial Index (MBI) was calculated based on the number and type of gravemarkers in individual cemeteries. The MBI acts a cultural inventory to measure varying degrees of Melungeon burial assimilation. Next, I interpreted the spatial patterns of assimilation to describe qualities of material cultural diffusion in the area. My findings show that traditional gravehouses are gradually being abandoned by the residents and over 93% of cemeteries exhibit complete burial assimilation. This suggests that gravehouse construction, a material and cultural practice of a U.S. minority group, has ended. / Master of Science

Abstract Background: Over 100 million people in the United States (U.S.) have diagnosed diabetes or pre-diabetes. People with this condition are at an increased risk of Peripheral Arterial Disease (PAD). There is a high prevalence of people with risk factors of diabetes especially in the rural Central Appalachia region. People with diabetes are at a higher risk of developing atherosclerosis, which is the most common cause of PAD. Although about 20–30% of 12 million people affected with PAD in the U.S. have diabetes, little is known about diabetes in PAD patients in Central Appalachia. Therefore, this study aimed to examine the risk factors of diabetes in patients with PAD within the Central Appalachian region. Methods: The study population consisted of patients with PAD with medical comorbidities of Cardiovascular disease (CVD). All patients were admitted to a large health system in Central Appalachia between 2008 and 2018. 13,455 index cases were extracted from the Electronic Medical Records (EMR) using the ICD-9 and ICD-10 codes. With diabetes as the outcome variable under study, the risk factors included Myocardial Infarction (MI) history, hypertension, smoking status and hypercholesterolemia. Socio-demographic variables considered in the study included gender, age, ethnicity and marital status and the covariates were Body Mass Index (BMI), Low density lipoproteins (LDL), High density lipoproteins (HDL), Total Cholesterol, and Triglycerides (TG). Multivariable logistic regression was performed to examine potential risk factors of diabetes in PAD patients. Results: The results showed that BMI {OR =1.056 (CI: 1.039, 1.073)}, HDL {OR =0.980 (CI: 0.965, 0.995)}, TG {OR=1.003 (CI: 1.001, 1.005)}, MI history {OR= 1.375 (CI: 1.111, 1.703)}, hypertension {OR=2.822 (CI: 1.804, 4.415)} and smoking {OR =0.802(CI: 0.641, 1.003)} were significant for diabetes in known PAD. To control for potential confounders, Stratification was used. Among males and females with PAD, diabetes was associated with last BMI, MI, hypertension and TG. HDL seemed to be negatively associated with hypertension and female diabetics while smoking seemed to be negatively associated in males. Upon stratification with hypertension, diabetes in PAD patients was significant with BMI, TG, MI history and HDL. After stratification with MI, diabetes in PAD female patients was associated with BMI, and previous MI history. On the other hand, patients without MI had an elevated TG level and an increased risk of hypertension. Conclusion: CVD risk factors are strongly associated with PAD comorbidities, which are worsened in the presence of diabetes. We suggest that hospitals and health care systems should strongly control for the risk factors of diabetes and adopt a multi-risk-factor approach for improving health outcomes for PAD patients.

Background: Over 100 million people in the United States (U.S.) have diagnosed diabetes or pre-diabetes. People with this condition are at an increased risk of Peripheral Arterial Disease (PAD). There is a high prevalence of people with risk factors of diabetes especially in the rural Central Appalachia region. People with diabetes are at a higher risk of developing atherosclerosis, which is the most common cause of PAD. Although about 20–30% of 12 million people affected with PAD in the U.S. have diabetes, little is known about diabetes in PAD patients in Central Appalachia. Therefore, this study aimed to examine the risk factors of diabetes in patients with PAD within the Central Appalachian region. Methods: The study population consisted of patients with PAD with medical comorbidities of Cardiovascular disease (CVD). All patients were admitted to a large health system in Central Appalachia between 2008 and 2018. 13,455 index cases were extracted from the Electronic Medical Records (EMR) using the ICD-9 and ICD-10 codes. With diabetes as the outcome variable under study, the risk factors included Myocardial Infarction (MI) history, hypertension, smoking status and hypercholesterolemia. Socio-demographic variables considered in the study included gender, age, ethnicity and marital status and the covariates were Body Mass Index (BMI), Low density lipoproteins (LDL), High density lipoproteins (HDL), Total Cholesterol, and Triglycerides (TG). Multivariable logistic regression was performed to examine potential risk factors of diabetes in PAD patients. Results: The results showed that BMI {OR =1.056 (CI: 1.039, 1.073)}, HDL {OR =0.980 (CI: 0.965, 0.995)}, TG {OR=1.003 (CI: 1.001, 1.005)}, MI history {OR= 1.375 (CI: 1.111, 1.703)}, hypertension {OR=2.822 (CI: 1.804, 4.415)} and smoking {OR =0.802(CI: 0.641, 1.003)} were significant for diabetes in known PAD. To control for potential confounders, Stratification was used. Among males and females with PAD, diabetes was associated with last BMI, MI, hypertension and TG. HDL seemed to be negatively associated with hypertension and female diabetics while smoking seemed to be negatively associated in males. Upon stratification with hypertension, diabetes in PAD patients was significant with BMI, TG, MI history and HDL. After stratification with MI, diabetes in PAD female patients was associated with BMI, and previous MI history. On the other hand, patients without MI had an elevated TG level and an increased risk of hypertension. Conclusion: CVD risk factors are strongly associated with PAD comorbidities, which are worsened in the presence of diabetes. We suggest that hospitals and health care systems should strongly control for the risk factors of diabetes and adopt a multi-risk-factor approach for improving health outcomes for PAD patients.

Late Ordovician (Cincinnatian) strata of the central Appalachians provide an opportunity to study the effects of both tectonics and eustasy within a foreland-basin setting. The Juniata Formation consists of red sandstones, siltstones, and shales that were deposited as part of an extensive siliciclastic basin-fill that resulted from the Taconic Orogeny. This study attempts to resolve some of the questions regarding tectonic and eustatic influences on sedimentation by (1) reconstructing the paleogeographic environment of the Juniata Formation and (2) examining the stratigraphic architecture of the Juniata Formation. A combination of both outcrop and subsurface data was analyzed. Seven facies were identified in this study, including: (1) "proto-vertisols", (2) red shale/mudstone, (3) siltstone/silty mudstone with interbedded sandstones, (4) quartz arenite and sublithic arenite, (5) argillaceous sandstone, (6) hummocky-bedded sandstones and siltstones, and (7) lithic sandstones and conglomerates. These facies are grouped into four facies associations (A–D), which are interpreted to be deposited from the inner shelf to the upper shoreface. Isopach and paleocurrent data suggest the shoreline was oriented NE–SW and detrital sediment was dispersed west and southwest across the basin. Tectonics controlled the 2nd-Order basin-fill pattern, and these patterns vary along the strike of the basin. Eustatic changes are expressed in two 3rd-Order sequences that were identified in the formation, and possibly in the 4th-Order (?) cycles of Facies Association A. The Ordovician–Silurian boundary is expressed as an unconformity throughout the study area, and along-strike variations in the structural setting of the basin were important in its development. / Master of Science

Cold-air damming (CAD) is a prevalent Mid-Atlantic United States weather phenomenon that occurs when cold, dense air is dammed alongside the eastern slopes of the Appalachian Mountains. Lower-than-normal maximum temperatures, increased and prolonged cloud cover, and precipitation that produces hazardous impacts are common features of this weather event, which are well known for presenting difficulties to both human forecasters and weather prediction models. This study explores CAD events between 2007 and 2016 archived in a Blacksburg National Weather Service ‘bust’ database – instances when forecasters erred by at least 8°F (4.4°C) on either maximum or minimum daily air temperature. The database includes the temperature error within Model Output Statistics (MOS) guidance in association with these forecast ‘busts.’ During the 10-year study period, MOS guidance produced warm-biased maximum temperatures and cold-biased minimum temperatures for most of the problematic CAD events, suggesting MOS guidance tended to underestimate the strength of CAD in these cases, seeming to struggle with weaker CAD events. During CAD erosion, MOS tended to prematurely erode CAD scenarios at night and predicted them to persist for too long during the day. Hourly surface meteorological and synoptic atmosphere composites during these ‘busted’ CAD events failed to reveal obvious differences from what is expected for central Appalachian CAD. However, a comparison to well-forecast classic cold-season CAD events suggest that busted cases of this same type of CAD may be drier than is typical. As the atmospheric patterns associated with busted CAD events are typical of the phenomenon, but a bit weaker or more marginal, forecast errors appear to stem from subtle model errors rather than forecaster error. It is possible that the models may inadequately characterize low-level moisture, but further research is needed to isolate the source of model forecast error. Nonetheless, the results of this research serve as guidance for operational forecasters as they consider model guidance during weak CAD events. / Master of Science / Cold-air damming (CAD) is a common weather pattern that affects the Blue Ridge Mountain region of the eastern United States, in which cold air at the atmosphere’s surface is directed from the Northeast and is dammed against the eastern Appalachian Mountains. This weather event causes lower-than-normal temperatures over the region and is often characterized by prolonged cloudy skies and precipitation. CAD is very difficult for forecasters to accurately predict, as they rely on weather forecast models that often simulate these situations poorly. CAD also strains emergency managers who rely on accurate forecasts to support public safety during CAD. This study explores CAD events between 2007 and 2016 archived in a Blacksburg National Weather Service ‘bust’ database – instances when forecasters erred by at least 8°F (4.4°C) on either maximum or minimum daily air temperature. The database includes the temperature error within Model Output Statistics (MOS) guidance in association with these forecast ‘busts.’ During the 10-year study period, MOS guidance forecasted maximum temperatures too high and minimum temperatures too low for most of the problematic CAD events, suggesting MOS guidance tended to underestimate the strength of CAD in these cases, seeming to struggle with weaker CAD events. During instances where CAD dissolved from the Appalachians, MOS tended to prematurely erode CAD scenarios at night and predicted them to persist for too long during the day. Hourly surface meteorological and synoptic atmosphere composites during these ‘busted’ CAD events failed to reveal obvious differences from what is expected for central Appalachian CAD. However, a comparison to well-forecast classic cold-season CAD events suggest that busted cases of this same type of CAD may be drier than is typical. As the atmospheric patterns associated with busted CAD events are typical of the phenomenon, but a bit weaker or more marginal, forecast errors appear to stem from subtle model errors rather than forecaster error. It is possible that the models may inadequately characterize low-level moisture, but further research is needed to isolate the source of model forecast error. Nonetheless, the results of this research serve as guidance for operational forecasters as they consider model guidance during weak CAD events.

White-tailed deer (Odocoileus virginianus) are a highly charismatic game species with considerable ecological and economic impacts across most of their range. In the Central Appalachian Mountains, deer are a keystone species in forested ecosystems. Regionally, populations vary in herd growth or decline. These fluctuations are important in that they often drive many aspects of population management and regulation, which are dependent on herd demographics. Some key population vital rates allowing better understanding of these changes in white-tailed deer herds are survival, cause-specific mortality, home-range variation, both broad and fine-scale resource selection, and ultimately population growth trends in response to changes in both population vital rates and hunter harvest regulations. In this study, I address each of these concepts within a deer population in Bath County, Virginia, that has presumably been in overall decline since the early 1990's. From June-September, 2019-2020, I monitored survival and cause specific mortality of 57 neonate white-tailed deer until 12 weeks of age. Fawn and adult female survival was 0.310 (95% CI = 0.210-0.475) and 0.871 (95%CI=0.790-0.961) respectively. During the study, I observed a total of 37 fawn mortalities and identified the cause of death using field evidence and through analyzing genetics from residual predator salvia recovered on deer carcasses. Mortalities included 28 predation events and 9 deaths from other causes (e.g., abandonment, malnutrition, or disease). Black bears accounted for 48.6% of all mortality and 64.2% of known predations within our study. My top model identified elevation as a significant predictor of fawn survival, with mortality risk increasing 20% for every 100m increase in elevation. My model using observed vital rates predicted an increasing population of λ = 1.10 (interquartile range, IQR 1.06-1.14). The population was predicted to increase by 2% with a 10% increase in doe harvest (λ = 1.02, IQR = 0.97-1.06) but declined by 7% at 20% harvest (λ = 0.93, IQR = 0.89-0.96). I found that fawning home ranges of females that successfully reared fawns to the end of the season had significantly larger home ranges than those that were unsuccessful at higher elevations. Fawning home ranges for females with fawns increased approximately 71ha in size for every 100m increase in mean home range elevation, whereas seasonal home ranges of females without fawns decreased approximately 1.5 ha for every 100m increase in mean home range elevation. Deer selected fawn-rearing areas nearer to forested edges, open habitats, and at higher elevations, while they avoided areas near disturbed and mature forests. Within the fawn rearing area, females selected locations closer to disturbed forest, open habitats, and forested edge, while avoiding mature forest habitats, and higher elevations. Females selected birth sites with higher levels of visual obstruction. Using a step-selection method for real-time resource selection across biological seasons, we found that female deer selected for open areas during the fawning, breeding, early gestational, and late gestational seasons. During the fall breeding season, females avoided forested edge, but selected for areas at higher elevations. During early gestational seasons females selected disturbed habitats and areas at higher elevations while again avoiding forested edge. Overall, my work highlights variations in population dynamics of white-tailed deer in areas of the Central Appalachian Mountains that are primarily characterized by poor habitat quality and provides novel insights into fine-scale spatial ecology of female deer across biological seasons within the region. Ultimately, while the deer population in our study was not predicted to be in decline, this work supports predation risk as being a significant factor associated with habitat quality. / Doctor of Philosophy / White-tailed deer (Odocoileus virginianus) are a game species with extensive ecological and economic impacts across most of their range. In the central Appalachian Mountains, many populations across the region vary in terms of herd size growth, stability, or decline. These fluctuations are important in that they often drive many aspects of population management and regulation, which are dependent on the status of herd demographics. Some key population vital rates that aid us in better understanding these changes in white-tailed deer herds are survival and cause-specific mortality, home-range variation in association with habitat quality and the ability to successfully reproduce, population trends under hypothetical management scenarios, and resource selection of various habitats that are available across the landscape. In this study, I address each of these concepts within a deer population in Bath County, Virginia, which has presumably been in decline since the early 1990's. As expected, fawn survival was lower than previously reported from other study areas of the Central Appalachians Mountains. Predation was the leading cause of fawn mortality, with black bears being responsible for most predation events. Fawn mortality risk was significantly associated with elevation - where fawns at higher elevations were those at greater risk. Surprisingly, the deer population in Bath County was projected to be increasing under current conditions and was also projected to be stable-to-increasing even under some hypothetical scenarios which would negatively impact population growth (i.e., 10% increase in female harvest or 17% reduction in fawn survival). Fawning home ranges of collared females which successfully reared known fawns to the end of the biological season were significantly influenced by elevation; such that females with fawns had home ranges that increased in size with increasing elevation, whereas females without fawns had home ranges which decreased slightly in size with increasing elevation. At birth sites, females selected locations characterized by higher levels of visual obstruction compared to randomly sampled areas. Of the habitat types analyzed, both selection or avoidance of specific habitats varied across both biological season and spatial scale. Ultimately, while I found that some deer populations associated with poor quality habitats in the Central Appalachians may not be in decline, deer were likely influenced greatly by habitat quality – especially pertaining to predation risk – throughout Bath County.